Journal articles on the topic 'Best view selection'
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Moreira, P. M. "Best multiple-view selection for the visualization of urban rescue simulations." International Journal of Simulation Modelling 5, no. 4 (December 15, 2006): 167–73. http://dx.doi.org/10.2507/ijsimm05(4)4.081.
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Boukorca, Ahcene, Ladjel Bellatreche, Sid-Ahmed Benali Senouci, and Zoé Faget. "Coupling Materialized View Selection to Multi Query Optimization." International Journal of Data Warehousing and Mining 11, no. 2 (April 2015): 62–84. http://dx.doi.org/10.4018/ijdwm.2015040104.
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Materialized views are queries whose results are stored and maintained in order to facilitate access to data in their underlying base tables of extremely large databases. Selecting the best materialized views for a given query workload is a hard problem. Studies on view selection have considered sharing common sub expressions and other multi-query optimization techniques. Multi-Query Optimization is a well-studied domain in traditional and advanced databases. It aims at optimizing a workload of queries by finding and reusing common sub-expression between queries. Finding the best shared expression is known as a NP-hard problem. The shared expressions usually identified by graph structure have been used to be candidate for materialized views. This shows the strong interdependency between the problems of materialized view selection (PVS) and multi query optimization (PMQO), since the PVS uses the graph structure of the PMQO. Exploring the existing works on PVS considering the interaction between PVS and PMQO figures two main categories of studies: (i) those considering the PMQO as a black box where the output is the graph and (ii) those preparing the graph to guide the materialized view selection process. In this category, the graph generation is based on individual query plans, an approach that does not scale, especially with the explosion of Big Data applications requiring large number of complex queries with high interaction. To ensure a scalable solution, this work proposes a new technique to generate a global processing plan without using individual plans by borrowing techniques used in the electronic design automation (EDA) domain. This paper first presents a rich state of art regarding the PVS and a classification of the most important existing work. Secondly, an analogy between the MQO problem and the EDA domain, in which large circuits are manipulated, is established. Thirdly, it proposes to model the problem with hypergraphs which are massively used to design and test integrated circuits. Fourthly, it proposes a deterministic algorithm to select materialized views using the global processing plan. Finally, experiments are conducted to show the scalability of our approach.
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Alarfaj, Fawaz, Naif Almusallam, Abdulatif Alabdulatif, Mohammed Ahmed Alomair, Abdulaziz Khalid Alsharidi, and Tarek Moulahi. "UFODMV: Unsupervised Feature Selection for Online Dynamic Multi-Views." Applied Sciences 13, no. 7 (March 28, 2023): 4310. http://dx.doi.org/10.3390/app13074310.
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In most machine learning (ML) applications, data that arrive from heterogeneous views (i.e., multiple heterogeneous sources of data) are more likely to provide complementary information than does a single view. Hence, these are known as multi-view data. In real-world applications, such as web clustering, data arrive from diverse groups (i.e., sets of features) and therefore have heterogeneous properties. Each feature group is referred to as a particular view. Although multi-view learning provides complementary information for machine learning algorithms, it results in high dimensionality. However, to reduce the dimensionality, feature selection is an efficient method that can be used to select only the representative features of the views so to reduce the dimensionality. In this paper, an unsupervised feature selection for online dynamic multi-views (UFODMV) is developed, which is a novel and efficient mechanism for the dynamic selection of features from multi-views in an unsupervised stream. UFODMV consists of a clustering-based feature selection mechanism enabling the dynamic selection of representative features and a merging process whereby both features and views are received incrementally in a streamed fashion over time. The experimental evaluation demonstrates that the UFODMV model has the best classification accuracy with values of 20% and 50% compared with well-known single-view and multi-view unsupervised feature selection methods, namely OMVFS, USSSF, and SPEC.
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Fan, Zhen, Xiu Li, and Yipeng Li. "Multi-Agent Deep Reinforcement Learning for Online 3D Human Poses Estimation." Remote Sensing 13, no. 19 (October 6, 2021): 3995. http://dx.doi.org/10.3390/rs13193995.
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Most multi-view based human pose estimation techniques assume the cameras are fixed. While in dynamic scenes, the cameras should be able to move and seek the best views to avoid occlusions and extract 3D information of the target collaboratively. In this paper, we address the problem of online view selection for a fixed number of cameras to estimate multi-person 3D poses actively. The proposed method exploits a distributed multi-agent based deep reinforcement learning framework, where each camera is modeled as an agent, to optimize the action of all the cameras. An inter-agent communication protocol was developed to transfer the cameras’ relative positions between agents for better collaboration. Experiments on the Panoptic dataset show that our method outperforms other view selection methods by a large margin given an identical number of cameras. To the best of our knowledge, our method is the first to address online active multi-view 3D pose estimation with multi-agent reinforcement learning.
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K, Jayakrishna, Vimal K.E.K, and Sekar Vinodh. "ANP based sustainable concept selection." Journal of Modelling in Management 10, no. 1 (March 16, 2015): 118–36. http://dx.doi.org/10.1108/jm2-12-2012-0042.
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Purpose – The purpose of this paper is to report a study in which analytical network process (ANP) was used for selecting the best concept from sustainability view point. Design/methodology/approach – The concept selection in the sustainability viewpoint is a typical multi-criteria decision-making (MCDM) problem involving complex interrelationship among the decision criteria. The formulated MCDM problem of sustainable concept selection was solved using ANP. The sensitivity analysis was also being conducted to validate the results. Findings – The interrelationship among the decision criteria was analyzed using ANP, and the best alternative was selected based on the computation of Product Sustainability Weighted Index (PSWI). The selected best alternative was subjected to implementation in the case organization. Research limitations/implications – The study deals with the formulation of sustainable concept selection as a typical MCDM problem and providing solutions using ANP. The best alternative “weight reduction” was subjected to implementation. The developed MCDM problem also could be solved using hybrid MCDM methods. Practical implications – The study focuses on selecting the best sustainability concept for an Indian automotive component manufacturing organization. Hence, the inferences being derived from the study are practically feasible and contribute toward the improvement of product sustainability. Originality/value – The formulation of a hierarchical model for sustainable concept selection as MCDM problem and generating solution using ANP is the contribution of the authors.
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Rajeevan, A. K., P. V. Shouri, and Usha Nair. "A Reliability Based Model for Wind Turbine Selection." International Journal of Renewable Energy Development 2, no. 2 (June 17, 2013): 69–74. http://dx.doi.org/10.14710/ijred.2.2.69-74.
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A wind turbine generator output at a specific site depends on many factors, particularly cut- in, rated and cut-out wind speed parameters. Hence power output varies from turbine to turbine. The objective of this paper is to develop a mathematical relationship between reliability and wind power generation. The analytical computation of monthly wind power is obtained from weibull statistical model using cubic mean cube root of wind speed. Reliability calculation is based on failure probability analysis. There are many different types of wind turbinescommercially available in the market. From reliability point of view, to get optimum reliability in power generation, it is desirable to select a wind turbine generator which is best suited for a site. The mathematical relationship developed in this paper can be used for site-matching turbine selection in reliability point of view.
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Mouna, Mustapha, Ladjel Bellatreche, and Narhimene Boustia. "ProRes: Proactive re-selection of materialized views." Computer Science and Information Systems, no. 00 (2022): 3. http://dx.doi.org/10.2298/csis210606003m.
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Materialized View Selection is one of the most studied problems in the database field, covering SQL and NoSQL technologies as well as different deployment infrastructures (centralized, parallel, cloud). This problem has become more complex with the arrival of data warehouses, being coupled with the physical de sign phase that aims at optimizing query performance. Selecting the best set of materialized views to optimize query performance is a challenging task. Given their importance and the complexity of their selection, several research efforts both from academia and industry have been conducted. Results are promising - some solutions are being implemented by commercial and open-source DBMSs -, but they do not factor in the following properties of nowadays analytical queries: (i) large scale queries, (ii) their dynamicity, and (iii) their high interaction. Studies to date fail to consider that complete set of properties. Considering the three properties simultaneously is crucial regarding today?s analytical requirements, which involve dynamic and interactive queries. In this paper, we first present a concise state of the art of the materialized view selection problem (VSP) by analyzing its ecosystem. Secondly, we propose a proactive re-selection approach that considers the three properties concurrently. It features twomain phases: offline and online. In the offline phase, we manage a set of the first queries based on a given threshold _ by selecting materialized views through a hypergraph structure. The second phase manages the addition of new queries by scheduling them, updates the structure of the hypergraph, and selects new views by eliminating the least beneficial ones. Finally, extensive experiments are conducted using the Star Schema Benchmark data set to evaluate the effectiveness and efficiency of our approach.
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Hong, Hotak, Gimun Um, and Jongho Nang. "A Best View Selection Method in Videos of Interested Player Captured by Multiple Cameras." Journal of KIISE 44, no. 12 (December 31, 2017): 1319–32. http://dx.doi.org/10.5626/jok.2017.44.12.1319.
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Gosain, Anjana, and Kavita Sachdeva. "Handling Constraints Using Penalty Functions in Materialized View Selection." International Journal of Natural Computing Research 8, no. 2 (April 2019): 1–17. http://dx.doi.org/10.4018/ijncr.2019040101.
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Materialized view selection (MVS) plays a vital role for efficiently making decisions in a data warehouse. This problem is NP-hard and constrained optimization problem. The authors have handled both the space and maintenance cost constraint using penalty functions. Three penalty function methods i.e. static, dynamic and adaptive penalty functions have been used for handling constraints and Backtracking Search Optimization algorithm (BSA) has been used for optimizing the total query processing cost. Experiments were conducted comparing the static, dynamic and adaptive penalty functions on varying the space constraint. The adaptive penalty function method yields the best results in terms of minimum query processing cost and achieves the optimality, scalability and feasibility of the problem on varying the lattice dimensions and on increasing the number of user queries. The authors proposed work has been compared with other evolutionary algorithms i.e. PSO and genetic algorithm and yields better results in terms of minimum total query processing cost of the materialized views.
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Imangaliyev, Sultan, Jörg Schlötterer, Folker Meyer, and Christin Seifert. "Diagnosis of Inflammatory Bowel Disease and Colorectal Cancer through Multi-View Stacked Generalization Applied on Gut Microbiome Data." Diagnostics 12, no. 10 (October 17, 2022): 2514. http://dx.doi.org/10.3390/diagnostics12102514.
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Most of the microbiome studies suggest that using ensemble models such as Random Forest results in best predictive power. In this study, we empirically evaluate a more powerful ensemble learning algorithm, multi-view stacked generalization, on pediatric inflammatory bowel disease and adult colorectal cancer patients’ cohorts. We aim to check whether stacking would lead to better results compared to using a single best machine learning algorithm. Stacking achieves the best test set Average Precision (AP) on inflammatory bowel disease dataset reaching AP = 0.69, outperforming both the best base classifier (AP = 0.61) and the baseline meta learner built on top of base classifiers (AP = 0.63). On colorectal cancer dataset, the stacked classifier also outperforms (AP = 0.81) both the best base classifier (AP = 0.79) and the baseline meta learner (AP = 0.75). Stacking achieves best predictive performance on test set outperforming the best classifiers on both patient cohorts. Application of the stacking solves the issue of choosing the most appropriate machine learning algorithm by automating the model selection procedure. Clinical application of such a model is not limited to diagnosis task only, but it also can be extended to biomarker selection thanks to feature selection procedure.
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Osten, Evariste F. "Binomial Attribute Sampling as an Aid in Defining a Representative Field of View in Microscopy." Proceedings, annual meeting, Electron Microscopy Society of America 48, no. 1 (August 12, 1990): 466–67. http://dx.doi.org/10.1017/s0424820100181087.
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Statistical analyses are routinely applied to microscope data from micrographs (measurements, shape factors) and, using electron microscopes, from x-ray microanalytical systems (net counts, peak ratios). However selection of a field of view which is recorded on a micrograph and implied to be a representative image of the bulk of the sample (at that magnification) is done intuitively. Experienced microscopists do consider a number of factors in selecting and preparing a sample and then choose from many instrument operating parameters before they view the sample. At this point assuming that the best microscopy practice has been exercised there is still the problem of a great number of fields of view to select from. High magnifications exacerbate this selection problem: in an Ultra High Resolution Field Emission Scanning Electron Microscope sharp images of routine samples are easily obtained at magnifications of X100,000 - at this magnification, even with a small sample size (4mm × 7mm), there are 28 million mutually exclusive fields of view.
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Turoń, Katarzyna. "Carsharing Vehicle Fleet Selection from the Frequent User’s Point of View." Energies 15, no. 17 (August 25, 2022): 6166. http://dx.doi.org/10.3390/en15176166.
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Short-term car rental services, i.e., carsharing, is a solution that has been developing better and better in urban transport systems in recent years. Along with intensive expansion, service providers have to face an increasing number of challenges to compete with each other. One of them is meeting the expectations of customers about the fleet of vehicles offered in the system. While this aspect is noticed in the literature review mainly in terms of fleet optimization and management, there is a research gap regarding the appropriate selection of vehicle models. In response, the article was dedicated to identifying the vehicles that were best suited to carsharing systems from the point of view of frequent customers. The selection of appropriate vehicles was treated as a multi-criteria decision issue, therefore the study used one of the multi-criteria decision support methods—ELECTRE III. The work focuses on researching the opinions of users (experts) who often use carsharing services in Poland. The study included a list of the most popular vehicles in Europe in 2021, including classic, electric, and hybrid cars, and a list of 11 evaluation criteria. The research results indicate for frequent users the advantage of conventional drive vehicles over electric and hydrogen vehicles. Moreover, they indicate that the best vehicles are relatively large cars (European car segments C and D) with the greatest possible length, boot capacity, engine power, number of safety systems, and quality. On the other hand, the least important issues are the number of seats in the vehicle and the number of doors. Interestingly, the vehicles selected by frequent users questioned the concept of small city cars, which occupied a small public space on which carsharing was supposed to focus. The results obtained support the operators of carsharing services in making fleet decisions.
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Wu, Qian, and Ya Nan Gao. "Selection Model of Concessionaire in PPP Projects." Applied Mechanics and Materials 174-177 (May 2012): 2906–10. http://dx.doi.org/10.4028/www.scientific.net/amm.174-177.2906.
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The failure or success of the PPP project depends on choosing a reasonable concessionaire.And it is particularly important.From the view of the government,the article launch a more accurate,comprehensive quantitive evaluation analysis on the basis of the characteristics of the PPP projects: construct a model to choose concessionaire of the project.Using fuzzy AHP method, we can build a model and solve it. Thus, we could get the best concessionaire and benefit all the parties.
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Vaupel, B. G. L. "The Best Remaining Seat: Evaluating Auditorium Plans for Desirability." Building Acoustics 5, no. 1 (March 1998): 1–16. http://dx.doi.org/10.1177/1351010x9800500101.
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It is important that an auditorium be designed to have as many good seats as possible. Not all seats in an auditorium are judged to be equally good. This is manifested in that the audience does not choose its seats randomly. The audience understands intuitively that, generally speaking, the closer a seat is to the performers, and the more straight on the better it is. Acoustics should be the most important consideration in selecting a seat, prior to a concert. However, the visual, comfort and economic factors are also important, along with others, not easy to isolate or define. Imagine an auditorium with open seating and the audience entering one at a time. People will in turn make a selection of what in their opinion is the best remaining seat. The order in which the seats are chosen is an indicator of the rank order of the desirability of the individual seats. As the audience makes its seat selection, a geometric pattern of the occupied seats unfolds, and reveals the boundary of the preferred seats. The perimeters describe the equal desirability curves and outlines the auditorium plan with as many good seats as possible. The audience choice of seat is recorded by time lapse photography. The data is analysed in a combined computer drawing and mathematics program. A mathematical model has been developed that evaluates the desirability of the seating in an auditorium from the audience point of view.
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AlShehri, Mohammed Abdul Rahman, and Shailendra Mishra. "Feature Based Comparison and Selection of SDN Controller." International Journal of Innovation and Technology Management 16, no. 05 (August 2019): 1950029. http://dx.doi.org/10.1142/s0219877019500299.
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Software defined network (SDN) controller selection in SDN is a key challenge to the network administrator. In SDN, control plane is an isolated process and operate on control layer. The controller provides a universal view of the entire network and support applications and services. The three focused parameters for controller selection are productivity, campus network and open source. In SDN, it is vital to have a good device for the efficient processing of all requests made by the switch and for good behavior of the network. For selecting best controller for the specified parameters, decision logic has to be developed that allow us to do comparison of the available controllers. Therefore, in this research we have suggested a methodology that uses analytic-hierarchy-process (AHP) to find a best controller. The approach has been studied and verified for a big organization network setup of Al-Majmaah University, Saudi Arabia. The approach is found to be more effective and increase the network performance significantly.
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Anstis, Stuart, Grace Hong, and Alan Ho. "Salience-Based Edge Selection in Flicker and Binocular Color Vision." i-Perception 11, no. 3 (May 2020): 204166952092904. http://dx.doi.org/10.1177/2041669520929047.
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A test cross that flickers between light yellow and dark blue at 5 to 8Hz looks apparently yellow on a dark gray surround and apparently blue on a light gray surround ( flicker augmented contrast). The achromatic surround cannot be inducing the perceived colors. Instead, the visual system selects the more salient apparent color with the higher Michelson contrast. The same is true for dichoptic vision. When one eye views a steady, light yellow cross and the other eye views a congruent steady dark blue cross, the binocular combination of colors looks apparently yellow on a dark gray surround and apparently blue on a light gray surround. Thus, when competing stimuli are distributed over time (flicker) or space (dichoptic vision), the visual system overweights the stimulus with the higher contrast. To see objects clearly, we accept the best view of any object and downplay inferior alternatives.
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Singha, Chiranjit, Kishore Chandra Swain, and Sanjay Kumar Swain. "Best Crop Rotation Selection with GIS-AHP Technique Using Soil Nutrient Variability." Agriculture 10, no. 6 (June 9, 2020): 213. http://dx.doi.org/10.3390/agriculture10060213.
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Crop selections and rotations are very important in optimising land and labour productivities, enhancing higher cropping intensities, producing better crop yield. A land suitability analysis system based on the analytical hierarchy process (AHP) technique coupled with the Geographic Information System (GIS) software environment can be a unique tool for better crop selection. The AHP-GIS technique was used in land suitability analysis in crop rotation decisions, for rice-jute (Kharif season) and potato-lentil (Rabi season) crops in the Hooghly District, West Bengal, India. The study area covering 291 ha was classified based on eight major soil nutrient levels with 70 randomly selected plots for soil sampling and analysis. The soil nutrient variability was examined with descriptive statistics followed by best semivariogram-based model selection for kriging interpolation in the ‘R’ software environment. The pairwise comparison matrix based ranking of parameters and giving weights was carried out considering the importance of each parameter for specific crops. The total area, being under the major rice-potato belt, could be classified from the suitability view point to the ‘highly suitable’(S1) class occupying 29.2%, and ‘not suitable’ (N) class; 4.5% for rice, about 6.5% of land is ‘highly suitable’ (S1), ‘and nearly 2.1% area is ‘not suitable’ (N) for jute; and 21.3% is ‘highly suitable’ (S1) for potato and 12.4% for lentil crops. The yield maps showed nearly 75% and 90% of the area for rice and potato crops, respectively, gave sound crop yield. Furthermore, the GIS platform was used for crop rotation analysis to spread multiple seasons ensuring better crop management in long run. Overall, 25% of the rice crop area for jute in Kharif and 8% of potato crop area for lentil in the Rabi season were recommended as replacements.
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Flores-Rodriguez, Karen-Lizbeth, Felipe Trujillo-Romero, and Jose-Joel Gonzalez-Barbosa. "Active object search using a pyramid approach to determine the next-best-view." IAES International Journal of Robotics and Automation (IJRA) 11, no. 1 (March 1, 2022): 70. http://dx.doi.org/10.11591/ijra.v11i1.pp70-88.
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<p>The development of service robotics continues to arouse interest in the scientific community due to the complexity of the activities performed like interaction in human environments, identifying and manipulating objects, and even learning by themselves. This paper proposed to improve the perception of the environment by searching for objects in service robotics tasks. We present the development and implementation of an active object search method based on three main phases: Firstly, image pyramid segmentation to examine in detail the im- age features. Second step, object detection at each level of the pyramid through a local feature descriptor and a mutual information calculation. Finally, the next camera position selection through analyzing the object detections accumulation in the pyramid. To evaluate the implementation of the proposed method, we use a NAO robot in a familiar place for humans, such as an office or a home. Ordinary objects are part of our database with the premise that a robot must know them before looking for an object. The results in the experiments showed an acceptable performance in simulation and with a real platform.</p>
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Westphal, Max, and Werner Brannath. "Evaluation of multiple prediction models: A novel view on model selection and performance assessment." Statistical Methods in Medical Research 29, no. 6 (September 12, 2019): 1728–45. http://dx.doi.org/10.1177/0962280219854487.
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Model selection and performance assessment for prediction models are important tasks in machine learning, e.g. for the development of medical diagnosis or prognosis rules based on complex data. A common approach is to select the best model via cross-validation and to evaluate this final model on an independent dataset. In this work, we propose to instead evaluate several models simultaneously. These may result from varied hyperparameters or completely different learning algorithms. Our main goal is to increase the probability to correctly identify a model that performs sufficiently well. In this case, adjusting for multiplicity is necessary in the evaluation stage to avoid an inflation of the family wise error rate. We apply the so-called maxT-approach which is based on the joint distribution of test statistics and suitable to (approximately) control the family-wise error rate for a wide variety of performance measures. We conclude that evaluating only a single final model is suboptimal. Instead, several promising models should be evaluated simultaneously, e.g. all models within one standard error of the best validation model. This strategy has proven to increase the probability to correctly identify a good model as well as the final model performance in extensive simulation studies.
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Martin, Micaela Y., Mateu Sbert, and Miguel Chover. "Viewpoint Selection for 3D-Games with f-Divergences." Entropy 26, no. 6 (May 29, 2024): 464. http://dx.doi.org/10.3390/e26060464.
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In this paper, we present a novel approach for the optimal camera selection in video games. The new approach explores the use of information theoretic metrics f-divergences, to measure the correlation between the objects as viewed in camera frustum and the ideal or target view. The f-divergences considered are the Kullback–Leibler divergence or relative entropy, the total variation and the χ2 divergence. Shannon entropy is also used for comparison purposes. The visibility is measured using the differential form factors from the camera to objects and is computed by casting rays with importance sampling Monte Carlo. Our method allows a very fast dynamic selection of the best viewpoints, which can take into account changes in the scene, in the ideal or target view, and in the objectives of the game. Our prototype is implemented in Unity engine, and our results show an efficient selection of the camera and an improved visual quality. The most discriminating results are obtained with the use of Kullback–Leibler divergence.
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Geffner, Hector. "The Model-Based Approach to Autonomous Behavior: A Personal View." Proceedings of the AAAI Conference on Artificial Intelligence 24, no. 1 (July 5, 2010): 1709–12. http://dx.doi.org/10.1609/aaai.v24i1.7765.
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The selection of the action to do next is one of the central problems faced by autonomous agents. In AI, three approaches have been used to address this problem: the programming-based approach, where the agent controller is given by the programmer, the learning-based approach, where the controller is induced from experience via a learning algorithm, and the model-based approach, where the controller is derived from a model of the problem. Planning in AI is best conceived as the model-based approach to action selection. The models represent the initial situation, actions, sensors, and goals. The main challenge in planning is computational, as all the models, whether accommodating feedback and uncertainty or not, are intractable in the worst case. In this article, I review some of the models considered in current planning research, the progress achieved in solving these models, and some of the open problems.
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ÖZDEMİR, Yavuz, and Kemal Gökhan NALBANT. "A REAL PERSONNEL SELECTION PROBLEM USING THE GENERALIZED CHOQUET INTEGRAL METHODOLOGY." Business & Management Studies: An International Journal 6, no. 2 (September 2, 2018): 694–716. http://dx.doi.org/10.15295/bmij.v6i2.270.
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The main objective in the selection of personnel is to select the most appropriate candidate for a job. Personnel selection for human resources management is a very important issue.The aim of this paper is to determine the best-performing personnel for promotion using an application of a Multi Criteria Decision Making(MCDM) method, generalized Choquet integral, to a real personnel selection problem of a case study in Turkey and 17 alternatives are ranked according to personnel selection criteria (22 subcriteria are classified under 5 main criteria). The main contribution of this paper is to determine the interdependency among main criteria and subcriteria, the nonlinear relationship among them and the environmental uncertainties while selecting personnel alternatives using the generalized Choquet integral method with the experts’ view. To the authors’ knowledge, this will be the first study which uses the generalized Choquet Integral methodology for human resources.
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Malinowska, Agnieszka, Ryszard Hejmanowski, and Janusz Rusek. "Estimation of the Parameters Affecting the Water Pipelines on the Mining Terrains with A Use of An Adaptive Fuzzy System." Archives of Mining Sciences 61, no. 1 (April 1, 2016): 183–97. http://dx.doi.org/10.1515/amsc-2016-0014.
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Abstract The research presented in this paper is basically focused on two objectives. Firstly, the selection of parameters affecting the water supply network damage. The causes of failures were selected from a population of tens of breakdown cases and then classified in view of their importance. Secondly, attention was paid to the selection of the most suitable linguistic model which could be commonly used for selecting factors which generate failures. Finally a Mamdani-based model could be worked out as a system possessing best generalization qualities. This model can create bases for an adaptative decision system which can show the type of water supply-sewage network, depending on continuous surface strains due to the mining activity.
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Amador, I. C. B., B. M. Viegas, E. N. Macêdo, K. G. P. Nunes, L. A. Féris, and D. C. Estumano. "ESTIMATION OF PARAMETERS AND SELECTION OF MODELS APPLIED IN ADSORPTION." Revista de Engenharia Térmica 20, no. 2 (July 28, 2021): 03. http://dx.doi.org/10.5380/reterm.v20i2.81780.
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The modeling of complex phenomena such as adsorption often requires the determination of parameters that cannot be directly measured and, therefore, must be estimated. An important point is related to the analysis of the inverse problem as a method of estimating parameters and selecting models. In view of this, this work aims to apply the Monte Carlo method via Markov Chains (MCMC) as a technique for solving the inverse problem of estimating fixed-bed adsorption parameters using analytical models proposed in the literature. In addition, this work aims to select the best model through the statistical metrics Akaike, corrected Akaike and Bayesian Information Criterion. The use of the Bayesian approach allowed the analysis of the convergence of the chains, as well as selected the best model to represent the experimental data obtained from the literature.
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Khan, Seemab, Muhammad Attique Khan, Majed Alhaisoni, Usman Tariq, Hwan-Seung Yong, Ammar Armghan, and Fayadh Alenezi. "Human Action Recognition: A Paradigm of Best Deep Learning Features Selection and Serial Based Extended Fusion." Sensors 21, no. 23 (November 28, 2021): 7941. http://dx.doi.org/10.3390/s21237941.
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Human action recognition (HAR) has gained significant attention recently as it can be adopted for a smart surveillance system in Multimedia. However, HAR is a challenging task because of the variety of human actions in daily life. Various solutions based on computer vision (CV) have been proposed in the literature which did not prove to be successful due to large video sequences which need to be processed in surveillance systems. The problem exacerbates in the presence of multi-view cameras. Recently, the development of deep learning (DL)-based systems has shown significant success for HAR even for multi-view camera systems. In this research work, a DL-based design is proposed for HAR. The proposed design consists of multiple steps including feature mapping, feature fusion and feature selection. For the initial feature mapping step, two pre-trained models are considered, such as DenseNet201 and InceptionV3. Later, the extracted deep features are fused using the Serial based Extended (SbE) approach. Later on, the best features are selected using Kurtosis-controlled Weighted KNN. The selected features are classified using several supervised learning algorithms. To show the efficacy of the proposed design, we used several datasets, such as KTH, IXMAS, WVU, and Hollywood. Experimental results showed that the proposed design achieved accuracies of 99.3%, 97.4%, 99.8%, and 99.9%, respectively, on these datasets. Furthermore, the feature selection step performed better in terms of computational time compared with the state-of-the-art.
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Sahoo, Deepanjali, Arun Kumar Tripathy, Jitendra Kumar Pati, and Prashant Kumar Parida. "A selection of level of supplier in supply chain management using binary coded genetic algorithm with a case study towards Pareto optimality." Journal of Decision Analytics and Intelligent Computing 3, no. 1 (December 15, 2023): 90–104. http://dx.doi.org/10.31181/jdaic10015072023s.
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In this work, authors discuss the way of selecting level of supplier by using the concept of binary coded genetic algorithm. For the best solution due to involvement of multi objective functions, the process of Tournament selection is widely discussed. In addition to this, authors involve fuzzy parameters due to the aspiration levels of Decision maker in analysis part for more clarity towards optimality. As a case study towards pareto optimality, the theory of non-dominance of solutions is properly discussed with the help of Pareto frontier. At last the values of objective functions based on quality, cost and service levels following an example are being analyzed with a significant view towards optimality. Based on the optimal solutions, the level of supplier selection is properly discussed.
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Moran, Peter, Michele Simoni, and Gianluca Vagnani. "Becoming the best: by beating or ignoring the best? Toward an expanded view of the role of managerial selection in complex and turbulent environments." Journal of Management & Governance 15, no. 3 (January 30, 2010): 447–81. http://dx.doi.org/10.1007/s10997-010-9129-2.
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Wahlberg, Mats. "Natural Selection, Scarcity and Evil:." Scientia et Fides 12, no. 1 (April 9, 2024): 107–18. http://dx.doi.org/10.12775/setf.2024.006.
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It is often claimed that our knowledge of the evolutionary process adds an extra dimension to the classical problem of natural evil and makes this problem worse. Especially the principle of natural selection is often portrayed as morally inappropriate or “unfitting” for a perfectly good God to use as a means for creating biological complexity. In this article, I argue that this common view is misconceived, and that natural selection is a wholly innocuous principle. The real source of evolutionary evils is the fact that resources in nature are scarce – a fact that was known long before Darwin. The problem of natural and evolutionary evil, therefore, is best construed as a question about why God permits scarcity in nature. I argue that recent research about the interrelation between competition and cooperation in the evolutionary process provides resources for answering this perennial question in a more satisfactory way than could be done before the advent of evolutionary theory.
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Dahm, Stephan Frederic, Emiko J. Muraki, and Penny M. Pexman. "Hand and Foot Selection in Mental Body Rotations Involves Motor-Cognitive Interactions." Brain Sciences 12, no. 11 (November 4, 2022): 1500. http://dx.doi.org/10.3390/brainsci12111500.
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Action imagery involves the mental representation of an action without overt execution, and can contribute to perspective taking, such as that required for left-right judgments in mental body rotation tasks. It has been shown that perspective (back view, front view), rotational angle (head-up, head-down), and abstractness (abstract, realistic) of the stimulus material influences speed and correctness of the judgement. The present studies investigated whether left-right judgements are more difficult on legs than on arms and whether the type of limb interacts with the other factors. Furthermore, a combined score for speed and accuracy was explored to eliminate possible tradeoffs and to obtain the best possible measure of subjects’ individual ability. Study 1 revealed that the front view is more difficult than the back view because it involves a vertical rotation in perspective taking. Head-down rotations are more difficult than head-up rotations because they involve a horizontal rotation in perspective taking. Furthermore, leg stimuli are more difficult than hand stimuli, particularly in head-down rotations. In Study 2, these findings were replicated in abstract stimuli as well as in realistic stimuli. In addition, perspective taking for realistic stimuli in the back view is easier than realistic stimuli in the front view or abstract stimuli (in both perspectives). We conclude that realistic stimulus material facilitates task comprehension and amplifies the effects of perspective. By replicating previous findings, the linear speed-accuracy score was shown to be a valid measure to capture performance in mental body rotations.
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Wang, Ren Zheng, Xing Wei Wang, and Min Huang. "An ABC Supported Heterogeneous Access Networks Selection Mechanism." Applied Mechanics and Materials 602-605 (August 2014): 3080–83. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.3080.
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The popularity of mobile communications and coexistence of heterogeneous access networks make it possible that the person can achieve the communication business with little restrict, which requires the support of ABC (always best connected) and the guarantee of users’ QoS requirement. For the property that the network status and users’ QoS requirements are difficult to get, this paper proposes an ABC supported heterogeneous access networks selection mechanism based on the particle swarm optimization based on adaptive diffusion and hybrid mutation in view of users’ preference, users’ cost and network providers’ income. The simulation result shows that this mechanism can not only satisfy the users’ requirements, but also maximizes the utility of both sides.
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Albattah, Waleed, Rehan Ullah Khan, Mohammed F. Alsharekh, and Samer F. Khasawneh. "Feature Selection Techniques for Big Data Analytics." Electronics 11, no. 19 (October 3, 2022): 3177. http://dx.doi.org/10.3390/electronics11193177.
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Big data applications have tremendously increased due to technological developments. However, processing such a large amount of data is challenging for machine learning algorithms and computing resources. This study aims to analyze a large amount of data with classical machine learning. The influence of different random sampling techniques on the model performance is investigated by combining the feature selection techniques and machine learning classifiers. The experiments used two feature selection techniques: random subset and random projection. Two machine learning classifiers were also used: Naïve Bayes and Bayesian Network. This study aims to maximize the model performance by reducing the data dimensionality. In the experiments, 400 runs were performed by reducing the data dimensionality of a video dataset that was more than 40 GB. The results show that the overall performance fluctuates between 70% accuracy to 74% for using sampled and non-sample (all the data), a slight difference in performance compared to the non-sampled dataset. With the overall view of the results, the best performance among all combinations of experiments is recorded for combination 3, where the random subset technique and the Bayesian network classifier were used. Except for the round where 10% of the dataset was used, combination 1 has the best performance among all combinations.
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Rotimi, Adeyoriju, and Fajebe Folorunso. "Human Resources Recruitment and Selection Practices in Nigerian Organisations." INTERDISCIPLINARY JOURNAL OF EDUCATION (IJE) 1, no. 2 (December 26, 2018): 230–38. http://dx.doi.org/10.53449/ije.v1i2.54.
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This study examined human resources recruitment and selection practices in Nigerian organizations. To achieve this, literature were reviewed on recruitment and selection practices, current trends on recruitment and selection in Nigeria workplace, challenges and consequences of poor recruitment and selection practices, along with strategies for managing recruitment and selection in the Nigerian workplace. This study utilized Resource Based View and Equity Theory in order to build a solid argument for the discourse. Hence, this study concluded that recruiting right calibre of employee in the right position is sine qua non to organizational success. It is recommended that organizations in Nigeria should constantly ensure proper validity of recruitment and selection criteria in-line with global best practices so as to have a round peg in a round hole.
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Hu, Shirui, Zhiyuan Li, Shaohua Wang, Mingyao Ai, and Qingwu Hu. "A Texture Selection Approach for Cultural Artifact 3D Reconstruction Considering Both Geometry and Radiation Quality." Remote Sensing 12, no. 16 (August 5, 2020): 2521. http://dx.doi.org/10.3390/rs12162521.
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3D reconstruction of culture artifacts has great potential in digital heritage documentation and protection. Choosing the proper images for texture mapping from multi-view images is a major challenge for high precision and high quality 3D reconstruction of culture artifacts. In this study, a texture selection approach, considering both the geometry and radiation quality for 3D reconstruction of cultural artifacts while using multi-view dense matching is proposed. First, a Markov random field (MRF) method is presented to select images from the best angle of view among texture image sets. Then, an image radiation quality evaluation model is proposed in the virtue of a multiscale Tenengrad definition and brightness detection to eliminate fuzzy and overexposed textures. Finally, the selected textures are mapped to the 3D model under the mapping parameters of the multi-view dense matching and a semi-automatic texture mapping is executed on the 3DMax MudBox platform. Experimental results with two typical cultural artifacts data sets (bronze wares and porcelain) show that the proposed method can reduce abnormal exposure or fuzzy images to yield high quality 3D model of cultural artifacts.
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Uliasz-Misiak, Barbara, Joanna Lewandowska-Śmierzchalska, and Rafał Matuła. "Selection of Underground Hydrogen Storage Risk Assessment Techniques." Energies 14, no. 23 (December 1, 2021): 8049. http://dx.doi.org/10.3390/en14238049.
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The article proposes the use of the analytic hierarchy process (AHP) method to select a risk assessment technique associated with underground hydrogen storage. The initial choosing and ranking of risk assessment techniques can be considered as a multi-criteria decision problem. The usage of a decision model based on six criteria is proposed. A ranking of methods for estimating the risks associated with underground hydrogen storage is presented. The obtained results show that the application of the AHP-based approach may be a useful tool for selecting the UHS risk assessment technique. The proposed method makes it possible to make an objective decision of the most satisfactory approach, from the point of view of all the adopted decision criteria, regarding the selection of the best risk assessment technique.
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Furtado, Paulo Antônio Xavier, and Antônio Vanderley Herrero Sola. "Fuzzy Complex Proportional Assessment Applied in Location Selection for Installation of Photovoltaic Plants." Energies 13, no. 23 (November 27, 2020): 6260. http://dx.doi.org/10.3390/en13236260.
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This article proposes the application of a multi-criteria decision-making method based on fuzzy complex proportional assessment (COPRAS-F), applying business sustainability criteria, to rank alternative sites for the installation of photovoltaic plants, as selected from a geographic suitability index map of vast and heterogeneous regions in Southern Brazil, obtained from a geographic information system. As a key feature, the methodology serves the interests of stakeholders during decision-making meetings in a personalized manner, eliminating the need for consensus to overcome conflicts and antagonistic positions, allowing them to maintain a strictly professional view and to communicate in business language. The results indicate that the best location from a geographical viewpoint may not be the best location from a business viewpoint.
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Yoga Religia and Amali Amali. "Perbandingan Optimasi Feature Selection pada Naïve Bayes untuk Klasifikasi Kepuasan Airline Passenger." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 5, no. 3 (June 19, 2021): 527–33. http://dx.doi.org/10.29207/resti.v5i3.3086.
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The quality of an airline's services cannot be measured from the company's point of view, but must be seen from the point of view of customer satisfaction. Data mining techniques make it possible to predict airline customer satisfaction with a classification model. The Naïve Bayes algorithm has demonstrated outstanding classification accuracy, but currently independent assumptions are rarely discussed. Some literature suggests the use of attribute weighting to reduce independent assumptions, which can be done using particle swarm optimization (PSO) and genetic algorithm (GA) through feature selection. This study conducted a comparison of PSO and GA optimization on Naïve Bayes for the classification of Airline Passenger Satisfaction data taken from www.kaggle.com. After testing, the best performance is obtained from the model formed, namely the classification of Airline Passenger Satisfaction data using the Naïve Bayes algorithm with PSO optimization, where the accuracy value is 86.13%, the precision value is 87.90%, the recall value is 87.29%, and the value is AUC of 0.923.
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Mok, Esmond, and Paul A. Cross. "A Fast Satellite Selection Algorithm for Combined GPS and GLONASS Receivers." Journal of Navigation 47, no. 3 (September 1994): 383–89. http://dx.doi.org/10.1017/s0373463300012327.
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This paper derives a fast satellite selection algorithm; that is, an algorithm to select the best subset of satellites to use for positioning in circumstances whereby a satellite navigation receiver is not capable of using all satellites in view. The algorithm adopts the weighting factor concept to determine the contribution of each satellite to the overall positioning accuracy. Selection by this algorithm is shown to be especially efficient when the number of available satellites is large, so it is likely to be particularly useful for receivers capable of making combined measurements to GPS and GLONASS satellites.
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Ganslandt, T., and W. O. Hackl. "Findings from the Clinical Information Systems Perspective." Yearbook of Medical Informatics 24, no. 01 (August 2015): 90–94. http://dx.doi.org/10.15265/iy-2015-037.
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Summary Objective: To summarize recent research and to propose a selection of best papers published in 2014 in the field of Clinical Information Systems (CIS).Method: A query with search terms from the Medical Subject Headings (MeSH) catalog as well as additional free text search terms was designed to identify relevant publications in the field of clinical information systems from PubMed and Web of Science®. The retrieved articles were then categorized in a multi-pass review carried out separately by the section editors. The final selection of 15 candidate papers was then peer-reviewed by Yearbook editors and external reviewers. Based on the review results the four best papers were then selected at the best papers selection meeting with the IMIA Yearbook editorial board. Results: The query was carried out in mid-January 2015, yielding a combined result set of 1525 articles which were published in 722 different journals. Among these articles two main thematic sections were identified: i) Interoperability from a syntactical and semantic point of view as well as from a long-term preservation and organizational/legal point of view and ii) secondary use of existing health data in all its shades. Here, patient safety was a major scope of application. Conclusions: CIS have become mature over the last years. The focus has now moved beyond data acquisition for just supporting the local care workflows. Actual research efforts in the CIS domain comprise the breakdown of information silos, the reduction of barriers between different systems of different care providers and secondary use of accumulated health data for multiple purposes.
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Cai, Guo Yin, Jie Huan, Yang Liu, and Ming Yi Du. "DEM Generation and Accuracy Assessment Using ZY-3 Stereo Image Pairs." Applied Mechanics and Materials 738-739 (March 2015): 613–17. http://dx.doi.org/10.4028/www.scientific.net/amm.738-739.613.
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Digital Elevation Model (DEM) is an important data source for topographic analysis, 3D visualization and satellite image ortho-rectification. This paper focused on the DEM extraction and accuracy assessment from ZY-3 satellite with 3 stereo images. DEM was extracted using three different stereo pair image groups composed of forward and nadir view images, nadir and backward view images as well as forward and backward view images. The accuracy of the DEM was indicated by root-mean-square error (RMSE) values. The results showed that the stereo pair of nadir and forward view images achieved the best accuracy, while the pair of forward and backward view images obtained the worst. This might be useful for the selection of the stereo pair images for extracting DEM using ZY-3 satellite images.
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Zhou, Li. "On the C-E Translation Strategies of Chinese Folk Culture from the Perspective of Eco-translatology." Frontiers in Humanities and Social Sciences 2, no. 6 (June 20, 2022): 75–77. http://dx.doi.org/10.54691/fhss.v2i6.896.
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Folk culture, as an important part of Chinese culture, is characterized by collective, regional, repetitive and typological features. From the point view of Eco-translatology, this paper explores how the translator makes the adaptive selection and transformation from the linguistic, cultural and communicative dimensions in order to achieve the best translation effects under the guidance of the principle of “multi-dimensional adaptation and adaptive selection” by analyzing some typical C-E translations of folk culture, which is expected to offer references to the translation of the Chinese folk culture.
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Caissie, Daniel, and Nassir El-Jabi. "A stochastic study of floods in Canada: truncation level by region." Canadian Journal of Civil Engineering 18, no. 2 (April 1, 1991): 328–30. http://dx.doi.org/10.1139/l91-038.
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The main problem in applying a partial duration series model in flood frequency analysis lies in the selection of the truncation level. From a practical point of view, it is important to have a simple and effective way of selecting this level. A truncation level study was conducted on hydrometric stations across Canada and regional equations were developed for estimating the truncation level using regression analysis. The homogeneous region was selected based on previous countrywide hydrological studies. From the hydrologic and physiographic parameters used in the regression analysis, the mean annual flood best explained the truncation level for all of the regions. Key words: flood, partial duration series, truncation level.
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Emmanuel Ampong Afoakwah and Hannah Kemevor. "The Impact of Supplier Selection and Monitoring on the Effectiveness of Public Procurement in Ghana: Cost Reduction Point of View." international journal of engineering technology and management sciences 7, no. 3 (2023): 103–10. http://dx.doi.org/10.46647/ijetms.2023.v07i03.014.
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The aim of this study is to examine the role of supplier selection and monitoring on the effectiveness of public procurement in terms of cost reduction in Ghana. Procurement effectiveness as an element of public performance management can contribute to achieving Value for Money by reducing administrative overhead costs and directing resources to support more complex procurement processes. Procurement adds value by reducing costs, without the compromise of quality, product failures, assuring the operational efficiency to enable better quality without any additional cost with an aim to achieve the best objectives, output at a reduced cost in the supply chain. This study provides procurement practitioners with insights into selecting the proper suppliers and embracing supplier monitoring to achieve procurement efficiency in terms of cost reduction. This study examines the effects of supplier selection and supplier monitoring on procurement cost reduction as a measure of public procurement efficiency in the Ghanaian context. Consequently, it provides empirical evidence of supplier management practices in the public procurement context. A structured questionnaire was used to collect cross-sectional survey data from 170 public procuring entities in Ghana. Structural equation modelling (SEM) was used to analyse the collected data.
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Vidal, J. M., S. A. Edwards, O. MacPherson, P. R. English, and A. G. Taylor. "Effect of environmental temperature on dietary selection in lactating sows." Proceedings of the British Society of Animal Production (1972) 1991 (March 1991): 122. http://dx.doi.org/10.1017/s0308229600020729.
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The choice-feeding method has been suggested as an effective way of estimating nutritional requirements and it may be helpful from a practical point of view for meeting the nutrient requirements of animals with great variability in nutrient intake and requirements, for example sows in lactation. Friend (1971) reported high variability in protein intake in lactating sows on choice feeding. Growing rats (Leshner et al.,1971) respond to temperature changes by modifying the proportion of protein selected in order to maintain their protein intake. The main objective of this experiment was to investigate the ability of sows offered diets of different nutrient content to select the combination that best fits their requirement, particularly in relation to problems of reduced food intake routinely encountered in high summer temperatures.
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Shin, Young Eui, Yeon Sung Kim, Hyoung-Il Kim, Jong Min Kim, Kyong Ho Chang, and Dave F. Farson. "Selection of Proper Fatigue Model for Flip Chip Package Reliability." Materials Science Forum 502 (December 2005): 393–98. http://dx.doi.org/10.4028/www.scientific.net/msf.502.393.
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There have been diverse fatigue models and approaches to properly estimate solder joint reliability. However, it is one of the most difficult problems to determine which solder constitutive models and fatigue models can be applied best. In this paper, both viscoplastic and elastic-plastic-creep solder constitutive models could be utilized to calculate accumulated inelastic response under 208 K to 423 K(-65 °C to 150 °C) thermal cycling condition. And two different fatigue models, Darveaux and creep-fatigue model were applied to find solder joints fatigue life for flip chip assembly. Moreover, each fatigue life was compared to experimental result for the validation of finite element analysis. The actual number of cycles to failure was obtained from cross sectional view of the package with SEM.
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Nguefack-Tsague, Georges, and Ingo Bulla. "A Focused Bayesian Information Criterion." Advances in Statistics 2014 (October 14, 2014): 1–8. http://dx.doi.org/10.1155/2014/504325.
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Myriads of model selection criteria (Bayesian and frequentist) have been proposed in the literature aiming at selecting a single model regardless of its intended use. An honorable exception in the frequentist perspective is the “focused information criterion” (FIC) aiming at selecting a model based on the parameter of interest (focus). This paper takes the same view in the Bayesian context; that is, a model may be good for one estimand but bad for another. The proposed method exploits the Bayesian model averaging (BMA) machinery to obtain a new criterion, the focused Bayesian model averaging (FoBMA), for which the best model is the one whose estimate is closest to the BMA estimate. In particular, for two models, this criterion reduces to the classical Bayesian model selection scheme of choosing the model with the highest posterior probability. The new method is applied in linear regression, logistic regression, and survival analysis. This criterion is specially important in epidemiological studies in which the objective is often to determine a risk factor (focus) for a disease, adjusting for potential confounding factors.
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Mantos, Tracy, Honey Lou Layon, Nikkithea Beduya, Iris Gulbe, Hannibal Layon, Ledesma Romagos Layon, and Lanndon Ocampo. "Supplier Selection in Family Small and Medium Enterprises." International Journal of Service Science, Management, Engineering, and Technology 14, no. 1 (January 23, 2023): 1–29. http://dx.doi.org/10.4018/ijssmet.317085.
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Current literature on family businesses and small and medium enterprises (SMEs) offers some disintegrated insights in view of managing supply chains, particularly the supplier selection agenda. The presence of distinct characteristics inherent to both enterprises calls for a new line of inquiry regarding supplier selection for family SMEs. This work advances the literature by (1) identifying a set of supplier selection attributes best encapsulating the interests of family SMEs, and (2) evaluating these attributes to guide relevant decision-making. With a case study in the food industry and previous lists of supplier selection attributes, ten attributes were considered relevant to family SMEs. Applying the hybrid entropy-MARCOS method yields the priority attributes in decreasing order: on-time delivery, total service quality, product quality, productivity, attitude, response to customer requests, problem-solving capacity, payment terms, price, and flexibility. An analysis with other comparable methods suggests high consistency of these findings. Theoretical insights were discussed.
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Shafiei, Saeid, Raeoof Vaelizadeh, Frederic Bertrand, and Manouchehr Ansari. "Evaluating and Ranking of Travel Mode in Metropolitan a Transportation Approach." Civil Engineering Journal 4, no. 6 (July 4, 2018): 1303. http://dx.doi.org/10.28991/cej-0309174.
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Nowadays metropolitans' planners faced with a significant growth of private cars and consequently, creation a lot of environmental costs. To tackle the problem, the planners should find the best suitable way with due to the stakeholders’ views and other affected criteria to encourage the passengers for using the public transportation instead of their own cars. This paper has been performed to identifying and verifying main criteria affecting travel mode selection; getting different point of views; identifying the most effective travel mode from stakeholders' point of view and finally evaluating and ranking of travel modes in in Tehran metropolis. This study is a quantitative research based on survey and two structured questionnaires for passengers, experts and managers. In order to have an accurate data analysis, AHP as an MCDM models has been used to evaluate and ranking of travel modes. By identifying main criteria (variables) affecting travel mode selection, also collecting and analyzing stakeholders’ different points of views, the weight of each related criterion has been identified and determined and consequently the priority of effective travel mode in Tehran metropolis has been achieved. Finally, the managerial report has been prepared.
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ESPINILLA, MACARENA, IVÁN PALOMARES, LUIS MARTÍNEZ, and DA RUAN. "A COMPARATIVE STUDY OF HETEROGENEOUS DECISION ANALYSIS APPROACHES APPLIED TO SUSTAINABLE ENERGY EVALUATION." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 20, supp01 (June 2012): 159–74. http://dx.doi.org/10.1142/s0218488512400120.
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The evaluation of sustainable energy policies supports the selection of the best policy to put it in practice. In this evaluation, stakeholders may express their preferences in different domains, considering their diverse background and the imprecision and uncertainty of the related information, as well as the nature of assessed criteria. Therefore, these evaluation problems require the selection of an adequate approach to manage such a heterogeneous framework. In this paper, we review three approaches with different strategies to deal with heterogeneous information and apply them to the evaluation of sustainable energy policies, with the view of analyzing their influence in a complex evaluation process, mainly in terms of interpretability and understandability.
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Yubin Wu. "Reference Image Aided Color Matching Design Based on Interactive Genetic Algorithm." Journal of Electrical Systems 20, no. 2 (April 4, 2024): 400–410. http://dx.doi.org/10.52783/jes.1193.
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This paper proposes an interactive genetic algorithm to assist designers in color selection and match different color combinations extracted. Then, based on the CorelDraw development environment, this paper establishes a graphic-based man-machine dialogue model. Through simulation experiments, genetic algorithms such as random selection, hybridization, variation, color region adjustment, etc. Finally, the best color combination is obtained and combined with the image. Within the scope of color extraction value, designers can use interactive genetic algorithm rules to view color planning from a holistic perspective. Under the influence of human-computer interaction, each scheme is optimized step by step, so that the color ideas matching the designer can be found quickly.
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Ibrahim M. Hezam. "An Intelligent Decision Support Model for Optimal Selection of Machine Tool under Uncertainty: Recent Trends." Neutrosophic Systems with Applications 3 (March 17, 2023): 35–44. http://dx.doi.org/10.61356/j.nswa.2023.12.
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Many scholars have been interested in the subject of machine tool selection as a result of the growing number of different machines and the continuous advancement of technology associated with these machines. The selection of an unsuitable machine tool may lead to a variety of issues, including limitations on production capacities and productivity indicators when taking into account both time and money from an industrial and practical perspective. The present strategy of selecting machine tools, known as multi-criteria decision-making (MCDM), relies on the subjective viewpoint the vast majority of the time. When selecting an appropriate machining tool, however, it is necessary to take both the subjective and objective points of view into consideration. This is due to the fact that the objective assessment accurately reflects the performance of the machine tools. As a result, the purpose of this work is to provide a strategy for selecting machine tools that are based on an innovative hybrid MCDM framework. The study was conducted under a neutrosophic environment and using triangular neutrosophic numbers (TNNs). In the beginning, the CRiteria Importance through Intercriteria Correlation (CRITIC) method is used to assess and prioritize the criteria set for the study. Then, the Additive Ratio Assessment (ARAS) method is applied to evaluate and rank four machine tools that were selected and used as alternatives in the study. The results indicate that the criteria of maximum spindle speed and linkage accuracy are the most important in determining the best machine tool. Also, the results indicate that the best alternative among the four tools used is FIDLA GTF-28. As a result, the requirements and priorities for research in the future are highlighted.