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Imran, Hafiz Ali, Damiano Gianelle, Michele Scotton, Duccio Rocchini, Michele Dalponte, Stefano Macolino, Karolina Sakowska, Cristina Pornaro et Loris Vescovo. « Potential and Limitations of Grasslands α-Diversity Prediction Using Fine-Scale Hyperspectral Imagery ». Remote Sensing 13, no 14 (6 juillet 2021) : 2649. http://dx.doi.org/10.3390/rs13142649.
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Plant biodiversity is an important feature of grassland ecosystems, as it is related to the provision of many ecosystem services crucial for the human economy and well-being. Given the importance of grasslands, research has been carried out in recent years on the potential to monitor them with novel remote sensing techniques. In this study, the optical diversity (also called spectral diversity) approach was adopted to check the potential of using high-resolution hyperspectral images to estimate α-diversity in grassland ecosystems. In 2018 and 2019, grassland species composition was surveyed and canopy hyperspectral data were acquired at two grassland sites: Monte Bondone (IT-MBo; species-rich semi-natural grasslands) and an experimental farm of the University of Padova, Legnaro, Padua, Italy (IT-PD; artificially established grassland plots with a species-poor mixture). The relationship between biodiversity (species richness, Shannon’s, species evenness, and Simpson’s indices) and optical diversity metrics (coefficient of variation-CV and standard deviation-SD) was not consistent across the investigated grassland plant communities. Species richness could be estimated by optical diversity metrics with an R = 0.87 at the IT-PD species-poor site. In the more complex and species-rich grasslands at IT-MBo, the estimation of biodiversity indices was more difficult and the optical diversity metrics failed to estimate biodiversity as accurately as in IT-PD probably due to the higher number of species and the strong canopy spatial heterogeneity. Therefore, the results of the study confirmed the ability of spectral proxies to detect grassland α-diversity in man-made grassland ecosystems but highlighted the limitations of the spectral diversity approach to estimate biodiversity when natural grasslands are observed. Nevertheless, at IT-MBo, the optical diversity metric SD calculated from post-processed hyperspectral images and transformed spectra showed, in the red part of the spectrum, a significant correlation (up to R = 0.56, p = 0.004) with biodiversity indices. Spatial resampling highlighted that for the IT-PD sward the optimal optical pixel size was 1 cm, while for the IT-MBo natural grassland it was 1 mm. The random pixel extraction did not improve the performance of the optical diversity metrics at both study sites. Further research is needed to fully understand the links between α-diversity and spectral and biochemical heterogeneity in complex heterogeneous ecosystems, and to assess whether the optical diversity approach can be adopted at the spatial scale to detect β-diversity. Such insights will provide more robust information on the mechanisms linking grassland diversity and optical heterogeneity.
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Riemer, N., et M. West. « Quantifying aerosol mixing state with entropy and diversity measures ». Atmospheric Chemistry and Physics Discussions 13, no 6 (12 juin 2013) : 15615–62. http://dx.doi.org/10.5194/acpd-13-15615-2013.
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Abstract. This paper presents the first quantitative metric for aerosol population mixing state, defined as the distribution of per-particle chemical species composition. This new metric, the mixing state index χ, is an affine ratio of the average per-particle species diversity Dα and the bulk population species diversity Dγ, both of which are based on information-theoretic entropy measures. The mixing state index χ enables the first rigorous definition of the spectrum of mixing states from so-called external mixture to internal mixture, which is significant for aerosol climate impacts, including aerosol optical properties and cloud condensation nuclei activity. We illustrate the usefulness of this new mixing state framework with model results from the stochastic particle-resolved model PartMC-MOSAIC. These results demonstrate how the mixing state metrics evolve with time for several archetypal cases, each of which isolates a specific process such as coagulation, emission, or condensation. Further, we present an analysis of the mixing state evolution for a complex urban plume case, for which these processes occur simultaneously. We additionally derive theoretical properties of the mixing state index and present a family of generalized mixing state indexes that vary in the importance assigned to low-mass-fraction species.
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Riemer, N., et M. West. « Quantifying aerosol mixing state with entropy and diversity measures ». Atmospheric Chemistry and Physics 13, no 22 (25 novembre 2013) : 11423–39. http://dx.doi.org/10.5194/acp-13-11423-2013.
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Abstract. This paper presents the first quantitative metric for aerosol population mixing state, defined as the distribution of per-particle chemical species composition. This new metric, the mixing state index χ, is an affine ratio of the average per-particle species diversity Dα and the bulk population species diversity Dγ, both of which are based on information-theoretic entropy measures. The mixing state index χ enables the first rigorous definition of the spectrum of mixing states from so-called external mixture to internal mixture, which is significant for aerosol climate impacts, including aerosol optical properties and cloud condensation nuclei activity. We illustrate the usefulness of this new mixing state framework with model results from the stochastic particle-resolved model PartMC-MOSAIC. These results demonstrate how the mixing state metrics evolve with time for several archetypal cases, each of which isolates a specific process such as coagulation, emission, or condensation. Further, we present an analysis of the mixing state evolution for a complex urban plume case, for which these processes occur simultaneously. We additionally derive theoretical properties of the mixing state index and present a family of generalized mixing state indexes that vary in the importance assigned to low-mass-fraction species.
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Varotsos, George K., Hector E. Nistazakis, Konstantinos Aidinis, Fadi Jaber, Mohd Nasor et Kanhira Kadavath Mujeeb Rahman. « Error Performance Estimation of Modulated Retroreflective Transdermal Optical Wireless Links with Diversity under Generalized Pointing Errors ». Telecom 2, no 2 (1 avril 2021) : 167–80. http://dx.doi.org/10.3390/telecom2020011.
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Recent developments in both optical wireless communication (OWC) systems and implanted medical devices (IMDs) have introduced transdermal optical wireless (TOW) technology as a viable candidate for extremely high-speed in-body to out-of-body wireless data transmissions, which are growing in demand for many vital biomedical applications, including telemetry with medical implants, health monitoring, neural recording and prostheses. Nevertheless, this emerging communication modality is primarily hindered by skin-induced attenuation of the propagating signal bit carrier along with its stochastic misalignment-induced fading. Thus, by considering a typical modulated retroreflective (MRR) TOW system with spatial diversity and optimal combining (OC) for signal reception in this work, we focus, for the first time in the MRR TOW literature, on the stochastic nature of generalized pointing errors with non-zero boresight (NZB). Specifically, under these circumstances, novel analytical mathematical expressions were derived for the total average bit error rate (BER) of various system configurations. Their results revealed significant outage performance enhancements when spatial diversity was utilized. Moreover, taking into consideration the total transdermal pathloss along with the effects of stochastic NZB pointing errors, the critical average signal-to-noise ratio (SNR) metric was evaluated for typical power spectral-density values.
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Polley, H., Chenghai Yang, Brian Wilsey et Philip Fay. « Spectral Heterogeneity Predicts Local-Scale Gamma and Beta Diversity of Mesic Grasslands ». Remote Sensing 11, no 4 (23 février 2019) : 458. http://dx.doi.org/10.3390/rs11040458.
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Plant species diversity is an important metric of ecosystem functioning, but field assessments of diversity are constrained in number and spatial extent by labor and other expenses. We tested the utility of using spatial heterogeneity in the remotely-sensed reflectance spectrum of grassland canopies to model both spatial turnover in species composition and abundances (β diversity) and species diversity at aggregate spatial scales (γ diversity). Shannon indices of γ and β diversity were calculated from field measurements of the number and relative abundances of plant species at each of two spatial grains (0.45 m2 and 35.2 m2) in mesic grasslands in central Texas, USA. Spectral signatures of reflected radiation at each grain were measured from ground-level or an unmanned aerial vehicle (UAV). Partial least squares regression (PLSR) models explained 59–85% of variance in γ diversity and 68–79% of variance in β diversity using spatial heterogeneity in canopy optical properties. Variation in both γ and β diversity were associated most strongly with heterogeneity in reflectance in blue (350–370 nm), red (660–770 nm), and near infrared (810–1050 nm) wavebands. Modeled diversity was more sensitive by a factor of three to a given level of spectral heterogeneity when derived from data collected at the small than larger spatial grain. As estimated from calibrated PLSR models, β diversity was greater, but γ diversity was smaller for restored grassland on a lowland clay than upland silty clay soil. Both γ and β diversity of grassland can be modeled by using spatial heterogeneity in vegetation optical properties provided that the grain of reflectance measurements is conserved.
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He, Xin, et Frank Y. Li. « Metric-Based Cooperative Routing in Multihop Ad Hoc Networks ». Journal of Computer Networks and Communications 2012 (2012) : 1–12. http://dx.doi.org/10.1155/2012/893867.
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Cooperative communication fully leverages the broadcast nature of wireless channels and exploits time/spatial diversity in a distributed manner, thereby achieving significant improvements in system capacity and transmission reliability. Cooperative diversity has been well studied from the physical layer perspective. Thereafter, cooperative MAC design has also drawn much attention recently. However, very little work has addressed cooperation at the routing layer. In this paper, we propose a simple yet efficient scheme for cooperative routing by using cooperative metrics including packet delivery ratio, throughput, and energy consumption efficiency. To make a routing decision based on our scheme, a node needs to first determine whether cooperation on each link is necessary or not, and if necessary, select the optimal cooperative scheme as well as the optimal relay. To do so, we calculate and compare cooperative routing metric values for each potential relay for each different cooperative MAC scheme (C-ARQ and CoopMAC in this study), and further choose the best value and compare it with the noncooperative link metric. Using the final optimal metric value instead of the traditional metric value at the routing layer, new optimal paths are set up in multihop ad hoc networks, by taking into account the cooperative benefits from the MAC layer. The network performance of the cooperative routing solution is demonstrated using a simple network topology.
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Huizing, Geert-Jan, Gabriel Peyré et Laura Cantini. « Optimal transport improves cell–cell similarity inference in single-cell omics data ». Bioinformatics 38, no 8 (14 février 2022) : 2169–77. http://dx.doi.org/10.1093/bioinformatics/btac084.
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Abstract Motivation High-throughput single-cell molecular profiling is revolutionizing biology and medicine by unveiling the diversity of cell types and states contributing to development and disease. The identification and characterization of cellular heterogeneity are typically achieved through unsupervised clustering, which crucially relies on a similarity metric. Results We here propose the use of Optimal Transport (OT) as a cell–cell similarity metric for single-cell omics data. OT defines distances to compare high-dimensional data represented as probability distributions. To speed up computations and cope with the high dimensionality of single-cell data, we consider the entropic regularization of the classical OT distance. We then extensively benchmark OT against state-of-the-art metrics over 13 independent datasets, including simulated, scRNA-seq, scATAC-seq and single-cell DNA methylation data. First, we test the ability of the metrics to detect the similarity between cells belonging to the same groups (e.g. cell types, cell lines of origin). Then, we apply unsupervised clustering and test the quality of the resulting clusters. OT is found to improve cell–cell similarity inference and cell clustering in all simulated and real scRNA-seq data, as well as in scATAC-seq and single-cell DNA methylation data. Availability and implementation All our analyses are reproducible through the OT-scOmics Jupyter notebook available at https://github.com/ComputationalSystemsBiology/OT-scOmics. Supplementary information Supplementary data are available at Bioinformatics online.
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Zhang, Lan. « Hybrid QPSO-NNIA2 Algorithm for Multi-Objective Optimization Problem ». International Journal of Pattern Recognition and Artificial Intelligence 33, no 08 (25 juin 2019) : 1959025. http://dx.doi.org/10.1142/s0218001419590250.
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To improve the convergence and distribution of a multi-objective optimization algorithm, a hybrid multi-objective optimization algorithm, based on the quantum particle swarm optimization (QPSO) algorithm and adaptive ranks clone and neighbor list-based immune algorithm (NNIA2), is proposed. The contribution of this work is threefold. First, the vicinity distance was used instead of the crowding distance to update the archived optimal solutions in the QPSO algorithm. The archived optimal solutions are updated and maintained by using the dynamic vicinity distance based m-nearest neighbor list in the QPSO algorithm. Secondly, an adaptive dynamic threshold of unfitness function for constraint handling is introduced in the process. It is related to the evolution algebra and the feasible solution. Thirdly, a new metric called the distribution metric is proposed to depict the diversity and distribution of the Pareto optimal. In order to verify the validity and feasibility of the QPSO-NNIA2 algorithm, we compare it with the QPSO, NNIA2, NSGA-II, MOEA/D, and SPEA2 algorithms in solving unconstrained and constrained multi-objective problems. The simulation results show that the QPSO-NNIA2 algorithm achieves superior convergence and superior performance by three metrics compared to other algorithms.
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Nunes, Laura A., Samuel T. Turvey et James Rosindell. « The price of conserving avian phylogenetic diversity : a global prioritization approach ». Philosophical Transactions of the Royal Society B : Biological Sciences 370, no 1662 (19 février 2015) : 20140004. http://dx.doi.org/10.1098/rstb.2014.0004.
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The combination of rapid biodiversity loss and limited funds available for conservation represents a major global concern. While there are many approaches for conservation prioritization, few are framed as financial optimization problems. We use recently published avian data to conduct a global analysis of the financial resources required to conserve different quantities of phylogenetic diversity (PD). We introduce a new prioritization metric (ADEPD) that After Downlisting a species gives the Expected Phylogenetic Diversity at some future time. Unlike other metrics, ADEPD considers the benefits to future PD associated with downlisting a species (e.g. moving from Endangered to Vulnerable in the International Union for Conservation of Nature Red List). Combining ADEPD scores with data on the financial cost of downlisting different species provides a cost–benefit prioritization approach for conservation. We find that under worst-case spending $3915 can save 1 year of PD, while under optimal spending $1 can preserve over 16.7 years of PD. We find that current conservation spending patterns are only expected to preserve one quarter of the PD that optimal spending could achieve with the same total budget. Maximizing PD is only one approach within the wider goal of biodiversity conservation, but our analysis highlights more generally the danger involved in uninformed spending of limited resources.
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Yu, Hai-Tao. « Optimize What You Evaluate With : Search Result Diversification Based on Metric Optimization ». Proceedings of the AAAI Conference on Artificial Intelligence 36, no 9 (28 juin 2022) : 10399–407. http://dx.doi.org/10.1609/aaai.v36i9.21282.
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Most of the existing methods for search result diversification (SRD) appeal to the greedy strategy for generating diversified results, which is formulated as a sequential process of selecting documents one-by-one, and the locally optimal choice is made at each round. Unfortunately, this strategy suffers from the following shortcomings: (1) Such a one-by-one selection process is rather time-consuming for both training and inference. (2) It works well on the premise that the preceding choices are optimal or close to the optimal solution. (3) The mismatch between the objective function used in training and the final evaluation measure used in testing has not been taken into account. We propose a novel framework through direct metric optimization for SRD (referred to as MO4SRD) based on the score-and-sort strategy. Specifically, we represent the diversity score of each document that determines its rank position based on a probability distribution. These distributions over scores naturally give rise to expectations over rank positions. Armed with this advantage, we can get the differentiable variants of the widely used diversity metrics. Thanks to this, we are able to directly optimize the evaluation measure used in testing. Moreover, we have devised a novel probabilistic neural scoring function. It jointly scores candidate documents by taking into account both cross-document interaction and permutation equivariance, which makes it possible to generate a diversified ranking via a simple sorting. The experimental results on benchmark collections show that the proposed method achieves significantly improved performance over the state-of-the-art results.
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Liu, Yi, Jun Guo, Huaiwei Sun, Wei Zhang, Yueran Wang et Jianzhong Zhou. « Multiobjective Optimal Algorithm for Automatic Calibration of Daily Streamflow Forecasting Model ». Mathematical Problems in Engineering 2016 (2016) : 1–13. http://dx.doi.org/10.1155/2016/8215308.
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Single-objection function cannot describe the characteristics of the complicated hydrologic system. Consequently, it stands to reason that multiobjective functions are needed for calibration of hydrologic model. The multiobjective algorithms based on the theory of nondominate are employed to solve this multiobjective optimal problem. In this paper, a novel multiobjective optimization method based on differential evolution with adaptive Cauchy mutation and Chaos searching (MODE-CMCS) is proposed to optimize the daily streamflow forecasting model. Besides, to enhance the diversity performance of Pareto solutions, a more precise crowd distance assigner is presented in this paper. Furthermore, the traditional generalized spread metric (SP) is sensitive with the size of Pareto set. A novel diversity performance metric, which is independent of Pareto set size, is put forward in this research. The efficacy of the new algorithm MODE-CMCS is compared with the nondominated sorting genetic algorithm II (NSGA-II) on a daily streamflow forecasting model based on support vector machine (SVM). The results verify that the performance of MODE-CMCS is superior to the NSGA-II for automatic calibration of hydrologic model.
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Qi, Jing Jia, Chuan Jun Guo et Yang Nan. « Study on Application of Super-Resolution Image Reconstruction Method Used in Video Image Processing ». Advanced Materials Research 476-478 (février 2012) : 1142–45. http://dx.doi.org/10.4028/www.scientific.net/amr.476-478.1142.
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Super resolution image reconstruction is a computational process of using multiple low-resolution observations to reconstruct a higher resolution image, which differs from improvement of optical devices. With magnification diversity among those low-resolution imagers, significant performance improvement, compared to traditional methods, is demonstrated. Results include fidelity metrics and simulated reconstructions. Performance improvement of super-resolution imaging systems with magnification diversity is studied in this paper.
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Butler, Harris K., Mark A. Friend, Kenneth W. Bauer et Trevor J. Bihl. « The effectiveness of using diversity to select multiple classifier systems with varying classification thresholds ». Journal of Algorithms & ; Computational Technology 12, no 3 (14 mai 2018) : 187–99. http://dx.doi.org/10.1177/1748301818761132.
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In classification applications, the goal of fusion techniques is to exploit complementary approaches and merge the information provided by these methods to provide a solution superior than any single method. Associated with choosing a methodology to fuse pattern recognition algorithms is the choice of algorithm or algorithms to fuse. Historically, classifier ensemble accuracy has been used to select which pattern recognition algorithms are included in a multiple classifier system. More recently, research has focused on creating and evaluating diversity metrics to more effectively select ensemble members. Using a wide range of classification data sets, methodologies, and fusion techniques, current diversity research is extended by expanding classifier domains before employing fusion methodologies. The expansion is made possible with a unique classification score algorithm developed for this purpose. Correlation and linear regression techniques reveal that the relationship between diversity metrics and accuracy is tenuous and optimal ensemble selection should be based on ensemble accuracy. The strengths and weaknesses of popular diversity metrics are examined in the context of the information they provide with respect to changing classification thresholds and accuracies.
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Jensen, Evelyn L., Arne Ø. Mooers, Adalgisa Caccone et Michael A. Russello. « I-HEDGE : determining the optimum complementary sets of taxa for conservation using evolutionary isolation ». PeerJ 4 (23 août 2016) : e2350. http://dx.doi.org/10.7717/peerj.2350.
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In the midst of the current biodiversity crisis, conservation efforts might profitably be directed towards ensuring that extinctions do not result in inordinate losses of evolutionary history. Numerous methods have been developed to evaluate the importance of species based on their contribution to total phylogenetic diversity on trees and networks, but existing methods fail to take complementarity into account, and thus cannot identify the best order or subset of taxa to protect. Here, we develop a novel iterative calculation of the heightened evolutionary distinctiveness and globally endangered metric (I-HEDGE) that produces the optimal ranked list for conservation prioritization, taking into account complementarity and based on both phylogenetic diversity and extinction probability. We applied this metric to a phylogenetic network based on mitochondrial control region data from extant and recently extinct giant Galápagos tortoises, a highly endangered group of closely related species. We found that the restoration of two extinct species (a project currently underway) will contribute the greatest gain in phylogenetic diversity, and present an ordered list of rankings that is the optimum complementarity set for conservation prioritization.
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Palacios Játiva, Pablo, Iván Sánchez, Ismael Soto, Cesar A. Azurdia-Meza, David Zabala-Blanco, Muhammad Ijaz, Ali Dehghan Firoozabadi et David Plets. « A Novel and Adaptive Angle Diversity-Based Receiver for 6G Underground Mining VLC Systems ». Entropy 24, no 11 (22 octobre 2022) : 1507. http://dx.doi.org/10.3390/e24111507.
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Visible light communication (VLC) is considered an enabling technology for future 6G wireless systems. Among the many applications in which VLC systems are used, one of them is harsh environments such as Underground Mining (UM) tunnels. However, these environments are subject to degrading environmental and intrinsic challenges for optical links. Therefore, current research should focus on solutions to mitigate these problems and improve the performance of Underground Mining Visible Light Communication (UM-VLC) systems. In this context, this article presents a novel solution that involves an improvement to the Angle Diversity Receivers (ADRs) based on the adaptive orientation of the Photo-Diodes (PDs) in terms of the Received Signal Strength Ratio (RSSR) scheme. Specifically, this methodology is implemented in a hemidodecahedral ADR and evaluated in a simulated UM-VLC scenario. The performance of the proposed design is evaluated using metrics such as received power, user data rate, and bit error rate (BER). Furthermore, our approach is compared with state-of-the-art ADRs implemented with fixed PDs and with the Time of Arrival (ToA) reception method. An improvement of at least 60% in terms of the analyzed metrics compared to state-of-the-art solutions is obtained. Therefore, the numerical results demonstrate that the hemidodecahedral ADR, with adaptive orientation PDs, enhances the received optical signal. Furthermore, the proposed scheme improves the performance of the UM-VLC system due to its optimum adaptive angular positioning, which is completed according to the strongest optical received signal power. By improving the performance of the UM-VLC system, this novel method contributes to further consideration of VLC systems as potential and enabling technologies for future 6G deployments.
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Xing, Lining, Rui Wu, Jiaxing Chen et Jun Li. « Handling Irregular Many-Objective Optimization Problems via Performing Local Searches on External Archives ». Mathematics 11, no 1 (20 décembre 2022) : 10. http://dx.doi.org/10.3390/math11010010.
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Adaptive weight-vector adjustment has been explored to compensate for the weakness of the evolutionary many-objective algorithms based on decomposition in solving problems with irregular Pareto-optimal fronts. One essential issue is that the distribution of previously visited solutions likely mismatches the irregular Pareto-optimal front, and the weight vectors are misled towards inappropriate regions. The fact above motivated us to design a novel many-objective evolutionary algorithm by performing local searches on an external archive, namely, LSEA. Specifically, the LSEA contains a new selection mechanism without weight vectors to alleviate the adverse effects of inappropriate weight vectors, progressively improving both the convergence and diversity of the archive. The solutions in the archive also feed back the weight-vector adjustment. Moreover, the LSEA selects a solution with good diversity but relatively poor convergence from the archive and then perturbs the decision variables of the selected solution one by one to search for solutions with better diversity and convergence. At last, the LSEA is compared with five baseline algorithms in the context of 36 widely-used benchmarks with irregular Pareto-optimal fronts. The comparison results demonstrate the competitive performance of the LSEA, as it outperforms the five baselines on 22 benchmarks with respect to metric hypervolume.
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Varotsos, GeorgeK, Hector E. Nistazakis, Argyris N. Stassinakis, Christos K. Volos, Vasileios Christofilakis et George S. Tombras. « Mixed Topology of DF Relayed Terrestrial Optical Wireless Links with Generalized Pointing Errors over Turbulence Channels ». Technologies 6, no 4 (17 décembre 2018) : 121. http://dx.doi.org/10.3390/technologies6040121.
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This study investigated the outage performance of a terrestrial FSO communication system that uses mixed series and parallel decode-and-forward (DF) relay-assisted (i.e., cooperative diversity) configurations, taking into account the influence of both atmospheric turbulence and pointing error effects. Turbulence-induced optical signal fading is modeled by gamma-gamma or the negative exponential distribution for weak to strong and saturated turbulence conditions, respectively. Additionally, weak to strong non-zero boresight misalignment-induced optical signal fading is modeled by the generalized Beckmann distribution. Under these conditions, an outage analysis of the examined FSO system is performed, in terms of both outage probability and mean outage duration metrics. Thus, fairly accurate closed-form mathematical expressions for both performance metrics are derived, while their corresponding analytical results demonstrate concrete performance and availability improvements for the total FSO system, especially when the number of the connected in parallel DF relays increases. Moreover, the obtained results are verified through the corresponding simulation results.
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Androutsos, Nikolaos A., Hector E. Nistazakis, Efstratios V. Chatzikontis, Argyris N. Stassinakis et George S. Tombras. « Spatial Jitter Influence on the Average BLER Performance of SIMO FSO Links over Atmospheric Turbulence Channels ». Electronics 10, no 16 (22 août 2021) : 2033. http://dx.doi.org/10.3390/electronics10162033.
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In the recent years, Free Space Optics (FSO) technology has attracted significant research and commercial interest mostly because of its many advantages in comparison with other radio systems used for point-to-point connections. However, the reliable operation of these systems significantly depends on the conditions of the atmosphere in the area in which the optical beam propagates. The most important of these conditions are atmospheric turbulence and the misalignment between the optical beam and the receiver, which is also known as the pointing errors effect. In this work, in order to obviate the performance mitigation caused by these phenomena, we examined the most widely accepted and one of the most effective techniques, i.e., the implementation of receivers’ diversity. Various metrics have been investigated to evaluate the performance of such systems, but most of them do not take into account that the ultra-fast modern optical communication systems use blocks of bits for the transmission and codes for the detection and/or correction of erroneous bits. Thus, by taking these aspects into account, in this work, we investigated the combined impact of spatial jitter and atmospheric turbulence on the total average block error rate of an optical wireless system with receivers’ diversity. Novel closed-form analytical formulas were derived.
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Morelli, Federico, Fabio Pruscini, Riccardo Santolini, Paolo Perna, Yanina Benedetti et Davide Sisti. « Landscape heterogeneity metrics as indicators of bird diversity : Determining the optimal spatial scales in different landscapes ». Ecological Indicators 34 (novembre 2013) : 372–79. http://dx.doi.org/10.1016/j.ecolind.2013.05.021.
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Liu, Wei, Fengming Luo, Yuanhong Liu et Wei Ding. « Optimal Siting and Sizing of Distributed Generation Based on Improved Nondominated Sorting Genetic Algorithm II ». Processes 7, no 12 (13 décembre 2019) : 955. http://dx.doi.org/10.3390/pr7120955.
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With the development of distributed generation technology, the problem of distributed generation (DG) planning become one of the important subjects. This paper proposes an Improved non-dominated sorting genetic algorithm-II (INSGA-II) for solving the optimal siting and sizing of DG units. Firstly, the multi-objective optimization model is established by considering the energy-saving benefit, line loss, and voltage deviation values. In addition, relay protection constraints are introduced on the basis of node voltage, branch current, and capacity constraints. Secondly, the violation constrained index and improved mutation operator are proposed to increase the population diversity of non-dominated sorting genetic algorithm-II (NSGA-II), and the uniformity of the solution set of the potential crowding distance improvement algorithm is introduced. In order to verify the performance of the proposed INSGA-II algorithm, NSGA-II and multiple objective particle swarm optimization algorithms are used to perform various examples in IEEE 33-, 69-, and 118-bus systems. The convergence metric and spacing metric are used as the performance evaluation criteria. Finally, static and dynamic distribution network planning with the integrated DG are performed separately. The results of the various experiments show the proposed algorithm is effective for the siting and sizing of DG units in a distribution network. Most importantly, it also can achieve desirable economic efficiency and safer voltage level.
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Bosco, G., P. Poggiolini, M. Visintin, Li Liangchuan et Chen Ming. « New Branch Metrics for MLSE Receivers Based on Polarization Diversity for PMD Mitigation ». Journal of Lightwave Technology 27, no 21 (novembre 2009) : 4793–803. http://dx.doi.org/10.1109/jlt.2009.2026720.
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Shi, Yun, et Mark von Itzstein. « How Size Matters : Diversity for Fragment Library Design ». Molecules 24, no 15 (5 août 2019) : 2838. http://dx.doi.org/10.3390/molecules24152838.
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Fragment-based drug discovery (FBDD) has become a major strategy to derive novel lead candidates for various therapeutic targets, as it promises efficient exploration of chemical space by employing fragment-sized (MW < 300) compounds. One of the first challenges in implementing a FBDD approach is the design of a fragment library, and more specifically, the choice of its size and individual members. A diverse set of fragments is required to maximize the chances of discovering novel hit compounds. However, the exact diversity of a certain collection of fragments remains underdefined, which hinders direct comparisons among different selections of fragments. Based on structural fingerprints, we herein introduced quantitative metrics for the structural diversity of fragment libraries. Structures of commercially available fragments were retrieved from the ZINC database, from which libraries with sizes ranging from 100 to 100,000 compounds were selected. The selected libraries were evaluated and compared quantitatively, resulting in interesting size-diversity relationships. Our results demonstrated that while library size does matter for its diversity, there exists an optimal size for structural diversity. It is also suggested that such quantitative measures can guide the design of diverse fragment libraries under different circumstances.
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Khan, Muhammad Waleed, Yasir Muhammad, Muhammad Asif Zahoor Raja, Farman Ullah, Naveed Ishtiaq Chaudhary et Yigang He. « A New Fractional Particle Swarm Optimization with Entropy Diversity Based Velocity for Reactive Power Planning ». Entropy 22, no 10 (1 octobre 2020) : 1112. http://dx.doi.org/10.3390/e22101112.
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Optimal Reactive Power Dispatch (ORPD) is the vital concern of network operators in the planning and management of electrical systems to reduce the real and reactive losses of the transmission and distribution system in order to augment the overall efficiency of the electrical network. The principle objective of the ORPD problem is to explore the best setting of decision variables such as rating of the shunt capacitors, output voltage of the generators and tap setting of the transformers in order to diminish the line loss, and improve the voltage profile index (VPI) and operating cost minimization of standard electrical systems while keeping the variables within the allowable limits. This research study demonstrates a compelling transformative approach for resolving ORPD problems faced by the operators through exploiting the strength of the meta-heuristic optimization model based on a new fractional swarming strategy, namely fractional order (FO)–particle swarm optimization (PSO), with consideration of the entropy metric in the velocity update mechanism. To perceive ORPD for standard 30 and 57-bus networks, the complex nonlinear objective functions, including minimization of the system, VPI improvement and operating cost minimization, are constructed with emphasis on efficacy enhancement of the overall electrical system. Assessment of the results show that the proposed FO-PSO with entropy metric performs better than the other state of the art algorithms by means of improvement in VPI, operating cost and line loss minimization. The statistical outcomes in terms of quantile–quantile illustrations, probability plots, cumulative distribution function, box plots, histograms and minimum fitness evaluation in a set of autonomous trials validate the capability of the proposed optimization scheme and exhibit sufficiency and also vigor in resolving ORPD problems.
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Chauhan, Sonali, Rajan Miglani, Lavish Kansal, Gurjot Singh Gaba et Mehedi Masud. « Performance Analysis and Enhancement of Free Space Optical Links for Developing State-of-the-Art Smart City Framework ». Photonics 7, no 4 (16 décembre 2020) : 132. http://dx.doi.org/10.3390/photonics7040132.
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In this paper, we have investigated and reported the performance of free-space optical (FSO) links operating in adverse atmospheric conditions. Since FSO links share operational similarity with fiber communication; hence, we believe that a cost-effective FSO framework can play a significant role in the transparent integration of high-speed network access backbones with the end-users. Different modulation formats, complemented with spatial diversity techniques, are discussed in this paper to strategize performance optimization of FSO links. Using bit error rate (BER) and signal-to-noise ratio (SNR) as performance metrics, it was found that binary phase-shift keying (BPSK) qualifies as the best technique modulation technique delivering SNR gain of 10 dB over on–off keying (OOK) operating link under similar channel conditions. Further performance optimization was achieved using space diversity reception wherein SNR witnessed a gain of 3 dB gain over the single-channel FSO link. In terms of application, the proposed model can help in developing a citizen-centric smart city ecosystem that can support seamless communication between heterogeneous smart devices.
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Bender Ignacio, Rachel A., Sayan Dasgupta, Terry Stevens-Ayers, Tomasz Kula, Joshua A. Hill, Stephanie J. Lee, Marco Mielcarek, Ann Duerr, Stephen J. Elledge et Michael Boeckh. « Comprehensive viromewide antibody responses by systematic epitope scanning after hematopoietic cell transplantation ». Blood 134, no 6 (8 août 2019) : 503–14. http://dx.doi.org/10.1182/blood.2019897405.
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Abstract Further insight into humoral viral immunity after hematopoietic cell transplantation (HCT) could have potential impact on donor selection or monitoring of patients. Currently, estimation of humoral immune recovery is inferred from lymphocyte counts or immunoglobulin levels and does not address vulnerability to specific viral infections. We interrogated the viral antibody repertoire before and after HCT using a novel serosurvey (VirScan) that detects immunoglobulin G responses to 206 viruses. We performed VirScan on cryopreserved serum from pre-HCT and 30, 100, and 365 days after myeloablative HCT from 37 donor-recipient pairs. We applied ecologic metrics (α- and β-diversity) and evaluated predictors of metrics and changes over time. Donor age and donor/recipient cytomegalovirus (CMV) serostatus and receipt systemic glucocorticoids were most strongly associated with VirScan metrics at day 100. Other clinical characteristics, including pre-HCT treatment and conditioning, did not affect antiviral repertoire metrics. The recipient repertoire was most similar (pairwise β-diversity) to that of donor at day 100, but more similar to pre-HCT self by day 365. Gain or loss of epitopes to common viruses over the year post-HCT differed by donor and recipient pre-HCT serostatus, with highest gains in naive donors to seropositive recipients for several human herpesviruses and adenoviruses. We used VirScan to highlight contributions of donor and recipient to antiviral humoral immunity and evaluate longitudinal changes. This work builds a foundation to test whether such systematic profiling could serve as a biomarker of immune reconstitution, predict clinical events after HCT, or help refine selection of optimal donors.
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Kero, Katja, Niina Hieta, Teemu Kallonen, Anne Ahtikoski, Hanna K. Laine, Jaana Rautava et Eveliina Munukka. « Optimal sampling and analysis methods for clinical diagnostics of vaginal microbiome ». European Journal of Clinical Microbiology & ; Infectious Diseases 42, no 2 (10 janvier 2023) : 201–8. http://dx.doi.org/10.1007/s10096-022-04545-x.
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AbstractNext-generation sequencing-based microbiological analysis is a complex way to profile vaginal microbiome samples since each step affects the results gained. Methodologies for sample collection lack golden standards. We compared Puritan DNA/RNA swab (PS) and Copan FLOQ swab (CS) and provided consistent and reliable microbiome profiles analyzed by 16S rRNA gene sequencing. We collected two consecutive vaginal samples utilizing PS with room temperature storing and CS with instant freezing from 26 women. Variable region 4 of bacterial 16S rRNA gene was amplified with single PCR by custom-designed dual-indexed primers and sequenced with Illumina MiSeq system. Read quality control, operational taxonomic unit tables, and alpha and beta diversities analysis were performed, and community richness, diversity, and evenness were evaluated and compared between the two samplings and tests. Nineteen sample pairs produced detectable, intact DNA during the extraction protocol and/or further microbial profiles. Alpha bacterial diversity indices were independent on the collection protocol. No significant statistical differences were found in the measured beta diversity metrics between the collection methods. Of the women, 43% had Lactobacillus-dominated vaginal microbiome profile despite of collection method. Previously reported important vaginal microbiome phyla Actinobacteria, Bacteroidetes, Firmicutes, Fusobacteria, and Proteobacteria were present in the sample set although their relative abundances varied among individuals. PS and CS enable constant vaginal microbiota sampling. The PS method with no need for instant freezing is suitable for on-site collections at clinics. Furthermore, it seems to be possible to take two samples instead of one with constant microbiological results.
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Karakolis, Evangelos, Panagiotis Kokkinakos et Dimitrios Askounis. « Provider Fairness for Diversity and Coverage in Multi-Stakeholder Recommender Systems ». Applied Sciences 12, no 10 (14 mai 2022) : 4984. http://dx.doi.org/10.3390/app12104984.
Texte intégralRésumé :
Nowadays, recommender systems (RS) are no longer evaluated only for the accuracy of their recommendations. Instead, there is a requirement for other metrics (e.g., coverage, diversity, serendipity) to be taken into account as well. In this context, the multi-stakeholder RS paradigm (MSRS) has gained significant popularity, as it takes into consideration all beneficiaries involved, from item providers to simple users. In this paper, the goal is to provide fair recommendations across item providers in terms of diversity and coverage for users to whom each provider’s items are recommended. This is achieved by following the methodology provided by the literature for solving the recommendation problem as an optimization problem under constraints for coverage and diversity. As the constraints for diversity are quadratic and cannot be solved in sufficient time (NP-Hard problem), we propose a heuristic approach that provides solutions very close to the optimal one, as the proposed approach in the literature for solving diversity constraints was too generic. As a next step, we evaluate the results and identify several weaknesses in the problem formulation as provided in the literature. To this end, we introduce new formulations for diversity and provide a new heuristic approach for the solution of the new optimization problem.
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Supraja, V., P. Nageswara Rao et M. N. Giriprasad. « Quality Assessment of Ambulatory Electrocardiogram Signals by Noise Detection using Optimal Binary Classification ». International Journal on Recent and Innovation Trends in Computing and Communication 10, no 10 (31 octobre 2022) : 91–108. http://dx.doi.org/10.17762/ijritcc.v10i10.5739.
Texte intégralRésumé :
In order to improve the diagnostic capability in Ambulatory Electrocardiogram signal and to reduce the noise signal impacts, there is a need for more robust models in place. In terms of improvising to the existing solutions, this article explores a novel binary classifier that learns from the features optimized by fusion of diversity assessment measures, which performs Quality Assessment of Ambulatory Electrocardiogram Signals (QAAES) by Noise Detection. The performance of the proposed model QAAES has been scaled by comparing it with contemporary models. Concerning performance analysis, the 10-fold cross-validation has been carried on a benchmark dataset. The results obtained from experiments carried on proposed and other contemporary models for cross-validation metrics have been compared to signify the sensitivity, specificity, and noise detection accuracy.
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Bisberg, Alexander J., et Rogelio E. Cardona-Rivera. « SCOPE : Selective Cross-Validation over Parameters for Elo ». Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 15, no 1 (8 octobre 2019) : 116–22. http://dx.doi.org/10.1609/aiide.v15i1.5233.
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It is crucial to develop reusable methods for explaining and evaluating esports given their popularity and diversity. Quantifying skill in an esport has the potential to improve win prediction, matchmaking, and storytelling for these games. Arpad Elo’s skill modeling system for chess has been adapted to many games and sports. In each instance, the modeler is challenged with tuning parameters to optimize for some metric, usually accuracy. Often these approaches are one-off and lack consistency. We propose SCOPE, a framework that uses grid search cross-validation to select optimal parameters for Elo based on accuracy, calibration, or log loss. We demonstrate this method on a season of Call of Duty World League, a first-person shooter esport, and we demonstrate comparable performance to other more complex, state-of-the-art methods.
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Li, Hui, Mengyao Zhang et Chenbo Zeng. « Circular Jaccard distance based multi-solution optimization for traveling salesman problems ». Mathematical Biosciences and Engineering 19, no 5 (2022) : 4458–80. http://dx.doi.org/10.3934/mbe.2022206.
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<abstract><p>Traveling salesman problem is a widely studied NP-hard problem in the field of combinatorial optimization. Many and various heuristics and approximation algorithms have been developed to address the problem. However, few studies were conducted on the multi-solution optimization for traveling salesman problem so far. In this article, we propose a circular Jaccard distance based multi-solution optimization (CJD-MSO) algorithm based on ant colony optimization to find multiple solutions for the traveling salesman problem. The CJD-MSO algorithm incorporates "distancing" niching technique with circular Jaccard distance metric which are both proposed in this paper for the first time. Experimental results verify that the proposed algorithm achieves good performance on both quality and diversity of the optimal solutions.</p></abstract>
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Greffier, Florian, Valérie Muzet, Vincent Boucher, Fabrice Fournela, Laure Lebouc et Sébastien Liandrat. « Influence of Pavement Heterogeneity and Observation Angle on Lighting Design : Study with New Metrics ». Sustainability 13, no 21 (25 octobre 2021) : 11789. http://dx.doi.org/10.3390/su132111789.
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Optimization of lighting installations should be a priority in order to reduce energy consumption and obtrusive light while providing optimal visibility conditions for road users. For the design of lighting installations, it is assumed that the road has homogeneous photometric characteristics and only one viewing angle is used. There are often significant differences between the design of lighting installations and their actual performance. In order to examine whether these differences are due to the photometry of the road, this study proposes metrics to assess the influence of road heterogeneity and observation angle. These metrics have been used on many measurements conducted on site and in the laboratory for different pavements. A calculation engine has been developed to realize road lighting design with several r-tables in the same calculation or for different observation angles. Thus, this study shows that a root mean squared deviation (RMSD) calculation, including average luminance and uniformities associated with different r-tables, is directly correlated to a normalized root mean squared deviation (NRMSD) calculation between these r-tables. With these proposed metrics it is possible to optimize lighting installation while taking into account different types of urban surfaces and the diversity of users.
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Nicholls, Rory, et Antonio Torija Martinez. « An investigation into the impact of unmanned aerial vehicles on soundscape perception in urban and rural environments ». INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, no 6 (1 août 2021) : 577–88. http://dx.doi.org/10.3397/in-2021-1570.
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It is predicted that urban air mobility, including the use of small to medium sized unmanned aerial vehicle (UAV) delivery systems, will be introduced into cities across the globe within the next 15 years. It is known, however, that noise is one of the main limiting factors for the wider adoption of these vehicles. Neither the metrics nor the methods used for conventional aircraft seem to be optimal for this novel source of noise. This research will aid in developing suitable psychoacoustic methodologies and metrics, specifically designed to quantify community noise impact of these vehicles. This paper describes a psychoacoustic experiment used to gather participant responses to UAV sound recordings, both isolated and with typical background noise in a diversity of soundscapes. Results from this psychoacoustic experiment will be used to correlate perceptions of UAV noise with objective sound quality metrics, and build new regression relationships that could describe the impact of a given UAV on the perception of soundscape environments. Future extension to the research may include evaluating the differences in psychoacoustic responses when introducing more accurate reproduction methods, such as virtual reality systems, and how these could be incorporated into a standardised human response measurement procedure.
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Hang, Yu. « Profit Information System of Exhibition Enterprises Based on Multiobjective Optimization Algorithm ». Mobile Information Systems 2022 (11 août 2022) : 1–9. http://dx.doi.org/10.1155/2022/7898076.
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To solve the problem of publishing company revenue data, a multiobjective optimization algorithm is proposed. Therefore, based on the research on the multipurpose optimization algorithm, this paper proposed a multipurpose optimization hybrid approval algorithm. The proposed algorithm generates a candidate set through the hybrid recommendation algorithm and then uses the multiobjective optimization algorithm to generate recommendation list with optimal accuracy and diversity. MATLABR2017a was used to calculate the c-metric and hypervolume of the measurement data. Besides, Excel was used to calculate the Pareto solution developed in this paper many times. The test environment is running on 64 bit Win10, running 6 GB memory, and the CPU frequency is 2.30 GHz. Experimental decisions were made by comparing the Pareto optimal solutions developed by the input algorithm and the control algorithm in 3 consecutive groups of experimental users. Experimental analysis shows that Pareto believes that the solution developed by the hybrid approval algorithm is multipurpose optimization, superior to the solution developed by the board, and that the algorithm can be used to create realistic and diverse results.
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Taugourdeau, Simon, Mathilde Dionisi, Mylène Lascoste, Matthieu Lesnoff, Jean Marie Capron, Fréderic Borne, Philippe Borianne et Lionel Julien. « A First Attempt to Combine NIRS and Plenoptic Cameras for the Assessment of Grasslands Functional Diversity and Species Composition ». Agriculture 12, no 5 (17 mai 2022) : 704. http://dx.doi.org/10.3390/agriculture12050704.
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Grassland represents more than half of the agricultural land. Numerous metrics (biomass, functional trait, species composition) can be used to describe grassland vegetation and its multiple functions. The measures of these metrics are generally destructive and laborious. Indirect measurements using optical tools are a possible alternative. Some tools have high spatial resolutions (digital camera), and others have high spectral resolutions (Near Infrared Spectrometry NIRS). A plenoptic camera is a multifocal camera that produces clear images at different depths in an image. The objective of this study was to test the interest of combining plenoptic images and NIRS data to characterize different descriptors of two Mediterranean legumes mixtures. On these mixtures, we measured biomass, species biomass, and functional trait diversity. NIRS and plenoptic images were acquired just before the field measurements. The plenoptic images were analyzed using Trainable Weka Segmentation ImageJ to evaluate the percentage of each species in the image. We calculated the average and standard deviation of the different colors (red, green, blue reflectance) in the image. We assessed the percentage of explanation of outputs of the images and NIRS analyses using variance partition and partial least squares. The biomass Trifolium michelianum and Vicia sativa were predicted with more than 50% variability explained. For the other descriptors, the variability explained was lower but nevertheless significant. The percentage variance explained was nevertheless quite low, and further work is required to produce a useable tool, but this work already demonstrates the interest in combining image analysis and NIRS.
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Zeltni, Kamel, Souham Meshoul et Heyam H. Al-Baity. « On the Convergence and Diversity of Pareto Fronts Using Swarm Intelligence Metaheuristics for Constrained Search Space ». International Journal of Swarm Intelligence Research 9, no 1 (janvier 2018) : 20–38. http://dx.doi.org/10.4018/ijsir.2018010102.
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This article reviews existing constraint-handling techniques then presents a new design for Swarm Intelligence Metaheuristics (SIM) to deal with constrained multi-objective optimization problems (CMOPs). This new design aims to investigate potential effects of leader concepts that characterize the dynamic of SIM in the hope to help the population to reach Pareto optimal solutions in a constrained search space. The new leader-based constraint handling mechanism is incorporated in Constrained Multi-Objective Cuckoo Search (C-MOCS) and Constrained Multi-Objective Particle Swarm Optimization (C-MOPSO) as specific instances of a more general class of SIMs. The experimental results are carried out using a set of six well-known test functions and two performance metrics. The convergence and diversity of C-MOCS and C-MOPSO are analysed and compared to the well-known Multi-Objective Evolutionary Algorithm (MOEA) NSGA-II and discussed based on the obtained results.
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Wang, Yong, Kuichao Li et Gai-Ge Wang. « Combining Key-Points-Based Transfer Learning and Hybrid Prediction Strategies for Dynamic Multi-Objective Optimization ». Mathematics 10, no 12 (17 juin 2022) : 2117. http://dx.doi.org/10.3390/math10122117.
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Dynamic multi-objective optimization problems (DMOPs) have been of interest to many researchers. These are problems in which the environment changes during the evolutionary process, such as the Pareto-optimal set (POS) or the Pareto-optimal front (POF). This kind of problem imposes more challenges and difficulties for evolutionary algorithms, mainly because it demands population to track the changing POF efficiently and accurately. In this paper, we propose a new approach combining key-points-based transfer learning and hybrid prediction strategies (KPTHP). In particular, the transfer process combines predictive strategy with obtaining anticipated key points depending on the previous moments to acquire the optimal individuals at the new instance during the evolution. Additionally, center-point-based prediction is used to complement transfer learning to comprehensively generate initial populations. KPTHP and six state-of-the-art algorithms are tested on various test functions for MIGD, DMIGD, MMS, and HVD metrics. KPTHP obtains superior results on most of the tested functions, which shows that our algorithm performs excellently in both convergence and diversity, with more competitiveness in addressing dynamic problems.
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Bouchard, Cindy, Étienne Lord, Nathalie Tessier et François-Joseph Lapointe. « Applying novel connectivity networks to wood turtle populations to provide comprehensive conservation management strategies for species at risk ». PLOS ONE 17, no 8 (12 août 2022) : e0271797. http://dx.doi.org/10.1371/journal.pone.0271797.
Texte intégralRésumé :
Genetic diversity within and among populations is frequently used in prioritization processes to rank populations based on their vulnerability or distinctiveness, however, connectivity and gene flow are rarely considered within these frameworks. Using a wood turtle (Glyptemys insculpta) population graph, we introduce BRIDES as a new tool to evaluate populations for conservation purpose without focusing solely on individual nodes. BRIDES characterizes different types of shortest paths among the nodes of a subgraph and compares the shortest paths among the same nodes in a complete network. The main objectives of this study were to (1) introduce a BRIDES selection process to assist conservation biologists in the prioritization of populations, and (2) use different centrality indices and node removal statistics to compare BRIDES results and assess gene flow among wood turtle populations. We constructed six population subgraphs and used a stepwise selection algorithm to choose the optimal number of additional nodes, representing different populations, required to maximize network connectivity under different weighting schemes. Our results demonstrate the robustness of the BRIDES selection process for a given scenario, while inconsistencies were observed among node-based metrics. Results showed repeated selection of certain wood turtle populations, which could have not been predicted following only genetic diversity and distinctiveness estimation, node-based metrics and node removal analysis. Contrary to centrality measures focusing on static networks, BRIDES allowed for the analysis of evolving networks. To our knowledge, this study is the first to apply graph theory for turtle conservation genetics. We show that population graphs can reveal complex gene flow dynamics and population resiliency to local extinction. As such, BRIDES offers an interesting complement to node-based metrics and node removal to better understand the global processes at play when addressing population prioritization frameworks.
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Rankovic, Vladimir, Mikica Drenovak, Boban Stojanovic, Zoran Kalinic et Zora Arsovski. « The mean-value at risk static portfolio optimization using genetic algorithm ». Computer Science and Information Systems 11, no 1 (2014) : 89–109. http://dx.doi.org/10.2298/csis121024017r.
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In this paper we solve the problem of static portfolio allocation based on historical Value at Risk (VaR) by using genetic algorithm (GA). VaR is a predominantly used measure of risk of extreme quantiles in modern finance. For estimation of historical static portfolio VaR, calculation of time series of portfolio returns is required. To avoid daily recalculations of proportion of capital invested in portfolio assets, we introduce a novel set of weight parameters based on proportion of shares. Optimal portfolio allocation in the VaR context is computationally very complex since VaR is not a coherent risk metric while number of local optima increases exponentially with the number of securities. We presented two different single-objective and a multiobjective technique for generating mean-VaR efficient frontiers. Results document good risk/reward characteristics of solution portfolios while there is a trade-off between the ability to control diversity of solutions and computation time.
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Campbell, Neil, Francis Neat, Finlay Burns et Phil Kunzlik. « Species richness, taxonomic diversity, and taxonomic distinctness of the deep-water demersal fish community on the Northeast Atlantic continental slope (ICES Subdivision VIa) ». ICES Journal of Marine Science 68, no 2 (21 juin 2010) : 365–76. http://dx.doi.org/10.1093/icesjms/fsq070.
Texte intégralRésumé :
Abstract Campbell, N., Neat, F., Burns, F., and Kunzlik, P. 2011. Species richness, taxonomic diversity, and taxonomic distinctness of the deep-water demersal fish community on the Northeast Atlantic continental slope (ICES Subdivision VIa). – ICES Journal of Marine Science, 68: 365–376. The fish community on the Atlantic deep continental shelf and upper slope to the northwest of Scotland has been the subject of biological studies for more than a century, and subject to bottom-trawl fishing for around 25 years. In this work, we examine trends in biodiversity of the deep-water demersal fish community revealed by a decade of trawl surveys by Marine Scotland—Science. The composition and structure of the fish assemblage was described using species richness as well as the descriptors of community interrelatedness: taxonomic diversity (Δ) and taxonomic distinctness (Δ*). Results revealed no temporal trends in community composition. The most significant factor in determining richness and taxonomic diversity of the demersal fish fauna was depth, and to a lesser extent latitude. Diversity and distinctness decreased with increasing depth and showed a complex relationship with latitude, while richness peaked at depths around 1400 m. This study shows taxonomic measures of diversity and distinctness to be sensitive indicators of ecological conditions in the deep-water fish community, with respect to depth and latitude, and the fact that no temporal trends were detected suggests that the structure of the fish community at exploitable depths on the Scottish slope has remained stable over the period 1998–2008. These findings imply that care should be taken when planning spatial measures designed to safeguard deep-water fish biodiversity because the optimal area recommended for protection is strongly dependent on the choice of metric used.
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Li, Wei. « Matrix Adaptation Evolution Strategy with Multi-Objective Optimization for Multimodal Optimization ». Algorithms 12, no 3 (5 mars 2019) : 56. http://dx.doi.org/10.3390/a12030056.
Texte intégralRésumé :
The standard covariance matrix adaptation evolution strategy (CMA-ES) is highly effective at locating a single global optimum. However, it shows unsatisfactory performance for solving multimodal optimization problems (MMOPs). In this paper, an improved algorithm based on the MA-ES, which is called the matrix adaptation evolution strategy with multi-objective optimization algorithm, is proposed to solve multimodal optimization problems (MA-ESN-MO). Taking advantage of the multi-objective optimization in maintaining population diversity, MA-ESN-MO transforms an MMOP into a bi-objective optimization problem. The archive is employed to save better solutions for improving the convergence of the algorithm. Moreover, the peaks found by the algorithm can be maintained until the end of the run. Multiple subpopulations are used to explore and exploit in parallel to find multiple optimal solutions for the given problem. Experimental results on CEC2013 test problems show that the covariance matrix adaptation with Niching and the multi-objective optimization algorithm (CMA-NMO), CMA Niching with the Mahalanobis Metric and the multi-objective optimization algorithm (CMA-NMM-MO), and matrix adaptation evolution strategy Niching with the multi-objective optimization algorithm (MA-ESN-MO) have overall better performance compared with the covariance matrix adaptation evolution strategy (CMA-ES), matrix adaptation evolution strategy (MA-ES), CMA Niching (CMA-N), CMA-ES Niching with Mahalanobis Metric (CMA-NMM), and MA-ES-Niching (MA-ESN).
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Bhaladhare, Pawan R., et Devesh C. Jinwala. « A Clustering Approach for the l-Diversity Model in Privacy Preserving Data Mining Using Fractional Calculus-Bacterial Foraging Optimization Algorithm ». Advances in Computer Engineering 2014 (16 septembre 2014) : 1–12. http://dx.doi.org/10.1155/2014/396529.
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In privacy preserving data mining, the l-diversity and k-anonymity models are the most widely used for preserving the sensitive private information of an individual. Out of these two, l-diversity model gives better privacy and lesser information loss as compared to the k-anonymity model. In addition, we observe that numerous clustering algorithms have been proposed in data mining, namely, k-means, PSO, ACO, and BFO. Amongst them, the BFO algorithm is more stable and faster as compared to all others except k-means. However, BFO algorithm suffers from poor convergence behavior as compared to other optimization algorithms. We also observed that the current literature lacks any approaches that apply BFO with l-diversity model to realize privacy preservation in data mining. Motivated by this observation, we propose here an approach that uses fractional calculus (FC) in the chemotaxis step of the BFO algorithm. The FC is used to boost the computational performance of the algorithm. We also evaluate our proposed FC-BFO and BFO algorithms empirically, focusing on information loss and execution time as vital metrics. The experimental evaluation shows that our proposed FC-BFO algorithm derives an optimal cluster as compared to the original BFO algorithm and existing clustering algorithms.
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Ebel, Brian A., Joseph W. Wagenbrenner, Alicia M. Kinoshita et Kevin D. Bladon. « Hydrologic recovery after wildfire : A framework of approaches, metrics, criteria, trajectories, and timescales ». Journal of Hydrology and Hydromechanics 70, no 4 (16 novembre 2022) : 388–400. http://dx.doi.org/10.2478/johh-2022-0033.
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Abstract Deviations in hydrologic processes due to wildfire can alter streamflows across the hydrograph, spanning peak flows to low flows. Fire-enhanced changes in hydrologic processes, including infiltration, interception, and evapotranspiration, and the resulting streamflow responses can affect water supplies, through effects on the quantity, quality, and timing of water availability. Post-fire shifts in hydrologic processes can also alter the timing and magnitude of floods and debris flows. The duration of hydrologic deviations from a pre-fire condition or function, sometimes termed hydrologic recovery, is a critical concern for land, water, and emergency managers. We reviewed and summarized terminology and approaches for defining and assessing hydrologic recovery after wildfire, focusing on statistical and functional definitions. We critically examined advantages and drawbacks of current recovery assessment methods, outline challenges to determining recovery, and call attention to selected opportunities for advancement of post-fire hydrologic recovery assessment. Selected challenges included hydroclimatic variability, post-fire land management, and spatial and temporal variability. The most promising opportunities for advancing assessment of hydrologic recovery include: (1) combining statistical and functional recovery approaches, (2) using a greater diversity of post-fire observations complemented with hydrologic modeling, and (3) defining optimal assemblages of recovery metrics and criteria for common hydrologic concerns and regions.
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Nuh, Jamal Abdullahi, Tieng Wei Koh, Salmi Baharom, Mohd Hafeez Osman et Si Na Kew. « Performance Evaluation Metrics for Multi-Objective Evolutionary Algorithms in Search-Based Software Engineering : Systematic Literature Review ». Applied Sciences 11, no 7 (31 mars 2021) : 3117. http://dx.doi.org/10.3390/app11073117.
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Many recent studies have shown that various multi-objective evolutionary algorithms have been widely applied in the field of search-based software engineering (SBSE) for optimal solutions. Most of them either focused on solving newly re-formulated problems or on proposing new approaches, while a number of studies performed reviews and comparative studies on the performance of proposed algorithms. To evaluate such performance, it is necessary to consider a number of performance metrics that play important roles during the evaluation and comparison of investigated algorithms based on their best-simulated results. While there are hundreds of performance metrics in the literature that can quantify in performing such tasks, there is a lack of systematic review conducted to provide evidence of using these performance metrics, particularly in the software engineering problem domain. In this paper, we aimed to review and quantify the type of performance metrics, number of objectives, and applied areas in software engineering that reported in primary studies—this will eventually lead to inspiring the SBSE community to further explore such approaches in depth. To perform this task, a formal systematic review protocol was applied for planning, searching, and extracting the desired elements from the studies. After considering all the relevant inclusion and exclusion criteria for the searching process, 105 relevant articles were identified from the targeted online databases as scientific evidence to answer the eight research questions. The preliminary results show that remarkable studies were reported without considering performance metrics for the purpose of algorithm evaluation. Based on the 27 performance metrics that were identified, hypervolume, inverted generational distance, generational distance, and hypercube-based diversity metrics appear to be widely adopted in most of the studies in software requirements engineering, software design, software project management, software testing, and software verification. Additionally, there are increasing interest in the community in re-formulating many objective problems with more than three objectives, yet, currently are dominated in re-formulating two to three objectives.
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Morita, Hiroki, et Satoshi Akao. « The effect of soil sample size, for practical DNA extraction, on soil microbial diversity in different taxonomic ranks ». PLOS ONE 16, no 11 (18 novembre 2021) : e0260121. http://dx.doi.org/10.1371/journal.pone.0260121.
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To determine the optimal soil sample size for microbial community structure analysis, DNA extraction, microbial composition analysis, and diversity assessments were performed using soil sample sizes of 0.2, 1, and 5 g. This study focused on the relationship between soil amount and DNA extraction container volume and the alteration in microbial composition at different taxonomic ranks (order, class, and phylum). Horizontal (0.2 and 1 g) and vertical (5 g) shaking were applied during DNA extraction for practical use in a small laboratory. In the case of the 5 g soil sample, DNA extraction efficiency and the value of α-diversity index fluctuated severely, possibly because of vertical shaking. Regarding the 0.2 and 1 g soil samples, the number of taxa, Shannon–Wiener index, and Bray–Curtis dissimilarity were stable and had approximately the same values at each taxonomic rank. However, non-metric multidimensional scaling showed that the microbial compositions of these two sample sizes were different. The higher relative abundance of taxa in the case of the 0.2 g soil sample might indicate that cell wall compositions differentiated the microbial community structures in these two sample sizes due to high shear stress tolerance. The soil sample size and tube volume affected the estimated microbial community structure. A soil sample size of 0.2 g would be preferable to the other sample sizes because of the possible higher shearing force for DNA extraction and lower experimental costs due to smaller amounts of consumables. When the taxonomic rank was changed from order to phylum, some minor taxa identified at the order rank were integrated into major taxa at the phylum rank. The integration affected the value of the β-diversity index; therefore, the microbial community structure analysis, reproducibility of structures, diversity assessment, and detection of minor taxa would be influenced by the taxonomic rank applied.
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Sessions, W. R., J. S. Reid, A. Benedetti, P. R. Colarco, A. da Silva, S. Lu, T. Sekiyama et al. « Development towards a global operational aerosol consensus : basic climatological characteristics of the International Cooperative for Aerosol Prediction Multi-Model Ensemble (ICAP-MME) ». Atmospheric Chemistry and Physics Discussions 14, no 10 (6 juin 2014) : 14933–98. http://dx.doi.org/10.5194/acpd-14-14933-2014.
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Abstract. Over the past several years, there has been a rapid development in the number and quality of global aerosol models intended for operational forecasting use. Indeed, most centers with global numerical weather prediction (NWP) capabilities have some program for aerosol prediction. These aerosol models typically have differences in their underlying meteorology as well as aerosol sources, sinks, microphysics and transformations. However, like similar diversity in aerosol climate models, the aerosol forecast models have fairly similar overall bulk error statistics for aerosol optical thickness (AOT)-one of the few aerosol metrics that is globally available. Experience in climate and weather prediction has shown that in situations such as this where there are several independent models, a multi-model ensemble or consensus will be top performing in many key error metrics. Further, multi-model ensembles provide a highly valuable tool for forecasters attempting to predict severe aerosol events. Here we present the first steps in developing a global multi-model aerosol forecasting ensemble intended for eventual operational and basic research use. Drawing from members of the International Cooperative for Aerosol Prediction (ICAP) latest generation of quasi-operational aerosol models, five day AOT forecasts are analyzed for December 2011 through November 2012 from four institutions: ECMWF, JMA, NASA GSFC, and NRL/FNMOC. For dust, we also include the NOAA NGAC product in our analysis. The Barcelona Supercomputing Centre (NMMC) and UK Met office dust product have also recent become available with ICAP, but have insufficient data to be included in this analysis period. A simple consensus ensemble of member and mean AOT fields for modal species (e.g., fine and coarse mode, and a separate dust ensemble) is used to create the ICAP Multi-Model Ensemble (ICAP-MME). The ICAP-MME is run daily at 0Z for 6 hourly forecasts out to 120 h. Basing metrics on comparisons to 21 regionally representative Aerosol Robotic Network (AERONET) sites, all models generally captured the basic aerosol features of the globe. However, there is an overall AOT low bias among models, particularly for high AOT events. Biomass burning regions have the most diversity in seasonal average AOT. The southern oceans, though low in AOT, nevertheless also have high diversity. In regard to root mean square error, as expected the ICAP-MME placed first over all models worldwide, and was typically first or second in ranking against all models at individual sites. These results are encouraging; as more global operational aerosol models come on line, we expect their inclusion in a robust operational multi-model ensemble will provide valuable aerosol forecasting guidance.
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Phal, Yamuna, Kevin Yeh et Rohit Bhargava. « Design Considerations for Discrete Frequency Infrared Microscopy Systems ». Applied Spectroscopy 75, no 9 (20 avril 2021) : 1067–92. http://dx.doi.org/10.1177/00037028211013372.
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Discrete frequency infrared chemical imaging is transforming the practice of microspectroscopy by enabling a diversity of instrumentation and new measurement capabilities. While a variety of hardware implementations have been realized, design considerations that are unique to infrared (IR) microscopes have not yet been compiled in literature. Here, we describe the evolution of IR microscopes, provide rationales for design choices, and catalog some major considerations for each of the optical components in an imaging system. We analyze design choices that use these components to optimize performance, under their particular constraints, while providing illustrative examples. We then summarize a framework to assess the factors that determine an instrument’s performance mathematically. Finally, we provide a validation approach by enumerating performance metrics that can be used to evaluate the capabilities of imaging systems or suitability for specific intended applications. Together, the presented concepts and examples should aid in understanding available instrument configurations, while guiding innovations in design of the next generation of IR chemical imaging spectrometers.
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Zeng, Yujiao, et Yanguang Sun. « Application of Hybrid MOPSO Algorithm to Optimal Reactive Power Dispatch Problem Considering Voltage Stability ». Journal of Electrical and Computer Engineering 2014 (2014) : 1–12. http://dx.doi.org/10.1155/2014/124136.
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This study presents a novel hybrid multiobjective particle swarm optimization (HMOPSO) algorithm to solve the optimal reactive power dispatch (ORPD) problem. This problem is formulated as a challenging nonlinear constrained multiobjective optimization problem considering three objectives, that is, power losses minimization, voltage profile improvement, and voltage stability enhancement simultaneously. In order to attain better convergence and diversity, this work presents the use of combing the classical MOPSO with Gaussian probability distribution, chaotic sequences, dynamic crowding distance, and self-adaptive mutation operator. Moreover, multiple effective strategies, such as mixed-variable handling approach, constraint handling technique, and stopping criteria, are employed. The effectiveness of the proposed algorithm for solving the ORPD problem is validated on the standard IEEE 30-bus and IEEE 118-bus systems under nominal and contingency states. The obtained results are compared with classical MOPSO, nondominated sorting genetic algorithm (NSGA-II), multiobjective evolutionary algorithm based on decomposition (MOEA/D), and other methods recently reported in the literature from the point of view of Pareto fronts, extreme, solutions and multiobjective performance metrics. The numerical results demonstrate the superiority of the proposed HMOPSO in solving the ORPD problem while strictly satisfying all the constraints.
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Zhang, Haijuan, Gai-Ge Wang, Junyu Dong et Amir H. Gandomi. « Improved NSGA-III with Second-Order Difference Random Strategy for Dynamic Multi-Objective Optimization ». Processes 9, no 6 (21 mai 2021) : 911. http://dx.doi.org/10.3390/pr9060911.
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Most real-world problems that have two or three objectives are dynamic, and the environment of the problems may change as time goes on. For the purpose of solving dynamic multi-objective problems better, two proposed strategies (second-order difference strategy and random strategy) were incorporated with NSGA-III, namely SDNSGA-III. When the environment changes in SDNSGA-III, the second-order difference strategy and random strategy are first used to improve the individuals in the next generation population, then NSGA-III is employed to optimize the individuals to obtain optimal solutions. Our experiments were conducted with two primary objectives. The first was to test the values of the metrics mean inverted generational distance (MIGD), mean generational distance (MGD), and mean hyper volume (MHV) on the test functions (Fun1 to Fun6) via the proposed algorithm and the four state-of-the-art algorithms. The second aim was to compare the metrics’ value of NSGA-III with single strategy and SDNSGA-III, proving the efficiency of the two strategies in SDNSGA-III. The comparative data obtained from the experiments demonstrate that SDNSGA-III has good convergence and diversity compared with four other evolutionary algorithms. What is more, the efficiency of second-order difference strategy and random strategy was also analyzed in this paper.
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Basaligheh, Parvaneh. « Optimal Coverage in Wireless Sensor Network using Augmented Nature-Inspired Algorithm ». International Journal on Future Revolution in Computer Science & ; Communication Engineering 8, no 2 (30 juin 2022) : 71–78. http://dx.doi.org/10.17762/ijfrcsce.v8i2.2082.
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One of the difficult problems that must be carefully considered before any network configuration is getting the best possible network coverage. The amount of redundant information that is sensed is decreased due to optimal network coverage, which also reduces the restricted energy consumption of battery-powered sensors. WSN sensors can sense, receive, and send data concurrently. Along with the energy limitation, accurate sensors and non-redundant data are a crucial challenge for WSNs. To maximize the ideal coverage and reduce the waste of the constrained sensor battery lifespan, all these actions must be accomplished. Augmented Nature-inspired algorithm is showing promise as a solution to the crucial problems in “Wireless Sensor Networks” (WSNs), particularly those related to the reduced sensor lifetime. For “Wireless Sensor Networks” (WSNs) to provide the best coverage, we focus on algorithms that are inspired by Augmented Nature in this research. In wireless sensor networks, the cluster head is chosen using the Diversity-Driven Multi-Parent Evolutionary Algorithm. For Data encryption Improved Identity Based Encryption (IIBE) is used. For centralized optimization and reducing coverage gaps in WSNs Time variant Particle Swarm Optimization (PSO) is used. The suggested model's metrics are examined and compared to various traditional algorithms. This model solves the reduced sensor lifetime and redundant information in Wireless Sensor Networks (WSNs) as well as will give real and effective optimum coverage to the Wireless Sensor Networks (WSNs).
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Fu, Jisi, Ping-An Zhong, Bin Xu, Feilin Zhu, Juan Chen et Jieyu Li. « Comparison of Transboundary Water Resources Allocation Models Based on Game Theory and Multi-Objective Optimization ». Water 13, no 10 (20 mai 2021) : 1421. http://dx.doi.org/10.3390/w13101421.
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Transboundary water resources allocation is an effective measure to resolve water-related conflicts. Aiming at the problem of water conflicts, we constructed water resources allocation models based on game theory and multi-objective optimization, and revealed the differences between the two models. We compare the Pareto front solved by the AR-MOEA method and the NSGA-II method, and analyzed the difference between the Nash–Harsanyi Leader–Follower game model and the multi-objective optimization model. The Huaihe River basin was selected as a case study. The results show that: (1) The AR-MOEA method is better than the NSGA-II method in terms of the diversity metric (Δ); (2) the solution of the asymmetric Nash–Harsanyi Leader–Follower game model is a non-dominated solution, and the asymmetric game model can obtain the same water resources allocation scheme of the multi-objective optimal allocation model under a specific preference structure; (3) after the multi-objective optimization model obtains the Pareto front, it still needs to construct the preference information of the Pareto front for a second time to make the optimal solution of a multi-objective decision, while the game model can directly obtain the water resources allocation scheme at one time by participating in the negotiation. The results expand the solution method of water resources allocation models and provide support for rational water resources allocation.