Journal articles: 'Algorithmes à phases'

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Domenech, P. "La décision, cette inconnue…" European Psychiatry 30, S2 (November 2015): S51. http://dx.doi.org/10.1016/j.eurpsy.2015.09.145.

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Qu’avons nous appris de l’architecture fonctionnelle des processus de prise de décision dans le cerveau humain grâce aux neurosciences computationnelles ? Dans un premier temps, nous verrons comment les modèles de diffusion ont permis de proposer des algorithmes de décision capable d’expliquer les relations complexes entre proportion de choix et temps de décision observés lors de décision simple, et de faire des prédictions testables sur l’activité cérébrale des régions impliquées dans ces processus cognitifs. En prenant l’exemple de choix économiques simples, nous illustrerons l’intérêt de ce cadre mathématique pour comprendre comment différentes régions cérébrales peuvent interagir pour produire des décisions reflétant nos préférences subjectives. Finalement, nous discuterons autour d’un modèle mathématique capable de détecter les changements d’environnements pour interrompre les tâches en cours et déclencher des phases actives d’exploration afin d’illustrer la façon dont les modèles computationnels permettent de détecter des transitions brutales dans les stratégies comportementales et de prédire avec précision l’activité cérébrale dans le cortex préfrontal humain. Nous conclurons sur l’importance du cadre théorique de l’inférence Bayesienne et, en particulier, des notions de confiance et d’incertitude pour caractériser les algorithmes utilisés par le cerveau humain pour choisir.

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Szekely, D. "La dépression bipolaire : une indication préférentielle de la stimulation cérébrale transcrânienne répétée ?" European Psychiatry 29, S3 (November 2014): 666. http://dx.doi.org/10.1016/j.eurpsy.2014.09.057.

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La prise en charge des patients bipolaires par les stabilisateurs de l’humeur de différentes classes thérapeutiques fait consensus (HAS, 2009). Si les recommandations nationales et internationales fournissent des algorithmes efficients dans le traitement des épisodes aigus maniaques, hypomaniaques et mixtes, la prise en charge des phases dépressives est plus complexe et le clinicien est bien souvent démunis s’il applique « au pied de la lettre » les recommandations. Dans la pratique quotidienne, le recours aux antidépresseurs bien que déconseillé, reste donc largement utilisée par les praticiens, faute de solution alternative efficace à ce jour. Dans cette situation, les recommandations incitent à utiliser les antidépresseurs en association aux stabilisateurs de l’humeur, en cures courtes d’environ 8 à 12 semaines après une réponse thérapeutique satisfaisante, qui ne survient que chez moins de 25 % des patients déprimés bipolaire (HAS, 2009). Le risque de virage de l’humeur induit par les antidépresseurs rapporté dans la littérature est de 3 à 10 % même lorsqu’une association thymorégulatrice est proposée [1].Parmi les alternatives thérapeutiques, la rTMS représente une piste prometteuse : le taux de virage de l’humeur induit est faible (0,84 % d’état maniaque dans le groupe actif vs 0,73 % dans le groupe placebo dans une revue de la littérature publiée par Xia et al. [2], et dans la pratique quotidienne, les déprimés bipolaires semblent répondent plus rapidement que les patients déprimés unipolaires à la rTMS.Nous proposons de faire une revue de la littérature concernant l’efficacité et la tolérance de la rTMS dans cette indication.

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Chin, Marshall H., Nasim Afsar-Manesh, Arlene S. Bierman, Christine Chang, Caleb J. Colón-Rodríguez, Prashila Dullabh, Deborah Guadalupe Duran, et al. "Guiding Principles to Address the Impact of Algorithm Bias on Racial and Ethnic Disparities in Health and Health Care." JAMA Network Open 6, no. 12 (December 15, 2023): e2345050. http://dx.doi.org/10.1001/jamanetworkopen.2023.45050.

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ImportanceHealth care algorithms are used for diagnosis, treatment, prognosis, risk stratification, and allocation of resources. Bias in the development and use of algorithms can lead to worse outcomes for racial and ethnic minoritized groups and other historically marginalized populations such as individuals with lower income.ObjectiveTo provide a conceptual framework and guiding principles for mitigating and preventing bias in health care algorithms to promote health and health care equity.Evidence ReviewThe Agency for Healthcare Research and Quality and the National Institute for Minority Health and Health Disparities convened a diverse panel of experts to review evidence, hear from stakeholders, and receive community feedback.FindingsThe panel developed a conceptual framework to apply guiding principles across an algorithm’s life cycle, centering health and health care equity for patients and communities as the goal, within the wider context of structural racism and discrimination. Multiple stakeholders can mitigate and prevent bias at each phase of the algorithm life cycle, including problem formulation (phase 1); data selection, assessment, and management (phase 2); algorithm development, training, and validation (phase 3); deployment and integration of algorithms in intended settings (phase 4); and algorithm monitoring, maintenance, updating, or deimplementation (phase 5). Five principles should guide these efforts: (1) promote health and health care equity during all phases of the health care algorithm life cycle; (2) ensure health care algorithms and their use are transparent and explainable; (3) authentically engage patients and communities during all phases of the health care algorithm life cycle and earn trustworthiness; (4) explicitly identify health care algorithmic fairness issues and trade-offs; and (5) establish accountability for equity and fairness in outcomes from health care algorithms.Conclusions and RelevanceMultiple stakeholders must partner to create systems, processes, regulations, incentives, standards, and policies to mitigate and prevent algorithmic bias. Reforms should implement guiding principles that support promotion of health and health care equity in all phases of the algorithm life cycle as well as transparency and explainability, authentic community engagement and ethical partnerships, explicit identification of fairness issues and trade-offs, and accountability for equity and fairness.

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Hu, Qijin. "Performance Comparison and Analysis of UCB, ETC, and Thompson Sampling Algorithms in the Multi-Armed Bandit Problem." Highlights in Science, Engineering and Technology 94 (April 26, 2024): 273–78. http://dx.doi.org/10.54097/a73zqy52.

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In this study, the nuanced interplay between problem complexity, prior knowledge, and the exploration-exploitation balance is examined, given their critical impact on algorithmic performance in diverse settings. To gain a deeper understanding of these dynamics, three algorithms – Upper Confidence Bound (UCB), Explore-Then-Commit (ETC), and Thompson Sampling – are selected for a comprehensive investigation. Each of these algorithms presents unique approaches to handling the challenges posed by varying problem contexts. The UCB algorithm, known for its robustness in balancing exploration and exploitation, is scrutinized for its performance in environments with differing levels of complexity and uncertainty. This algorithm's reliance on confidence bounds makes it particularly relevant in scenarios where accurate estimates of uncertainty can significantly enhance decision-making processes. ETC, on the other hand, is characterized by its phased approach, initially exploring options before committing to a seemingly optimal choice. This study examines how the ETC algorithm's performance is influenced by the availability of prior knowledge and the intricacy of the problem at hand. Its phased nature makes it a subject of interest in environments where initial exploration can yield substantial insights for subsequent exploitation.

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Amouzou, Gildas Yaovi, and Azzeddine Soulaïmani. "Numerical Algorithms for Elastoplacity: Finite Elements Code Development and Implementation of the Mohr–Coulomb Law." Applied Sciences 11, no. 10 (May 19, 2021): 4637. http://dx.doi.org/10.3390/app11104637.

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Two numerical algorithms for solving elastoplastic problems with the finite element method are presented. The first deals with the implementation of the return mapping algorithm and is based on a fixed-point algorithm. This method rewrites the system of elastoplasticity non-linear equations in a form adapted to the fixed-point method. The second algorithm relates to the computation of the elastoplastic consistent tangent matrix using a simple finite difference scheme. A first validation is performed on a nonlinear bar problem. The results obtained show that both numerical algorithms are very efficient and yield the exact solution. The proposed algorithms are applied to a two-dimensional rockfill dam loaded in plane strain. The elastoplastic tangent matrix is calculated by using the finite difference scheme for Mohr–Coulomb’s constitutive law. The results obtained with the developed algorithms are very close to those obtained via the commercial software PLAXIS. It should be noted that the algorithm’s code, developed under the Matlab environment, offers the possibility of modeling the construction phases (i.e., building layer by layer) by activating the different layers according to the imposed loading. This algorithmic and implementation framework allows to easily integrate other laws of nonlinear behaviors, including the Hardening Soil Model.

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Meshram, Bandu B., Vikas Mendhe, and Manish Kumar Singh. "Medical Forensics Principles and Cyber Crime Forensic Investigation Model." Journal of Web Applications and Cyber Security 2, no. 1 (January 29, 2024): 1–17. http://dx.doi.org/10.48001/jowacs.2024.211-17.

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The paper deals with medical principles of forensic and their proposed utilization in computer forensic. This paper explores how the medical/traditional forensic science law principles like individuality, exchange, progressive change, comparison analysis, facts do not lie are useful in cybercrime forensic investigation with forensic principles applicability cybercrime scenarios with case law. Lastly the research explores the Digital forensics methodology useful for the prosecution of digital criminals. The researchers have done extensive literature survey of the existing crime investigation forensic investigation frameworks proposed from 1995 to 2022 to identify the detailed activities in each process. Based on this collective information, their limitations and practical experience into the domain, the researchers proposed a robust digital forensic process model to obtain the digital evidence. The authors proposed the digital forensic investigation model with the algorithmic steps used in proposed phases of investigation model. Phase 1 starts the investigation process-readiness phase with procedure 1: digital forensic case management, procedure 2: investigation preparation (fir). Phase 2 seizer and isolation explore for communication shielding. Phase 3: data acquisition/duplication & deleted data recovery explore volatile data collection, non-volatile data, and evidence collection from network with widely used tools with respect to computing OS Infrastructure. The procedures explored in phase 2 are Procedure 3: DataAcquisition (), Procedure 4: Procedure EvidenceCollection () and Procedure 5 HashAlgorithms(). Phase 3 preservation and data security includes packaging, transportation and storage, Access Control and physical Safety. The procedure proposed in Phase3 are Procedure 6: Procedure DataTransfer(). Phase4 Identification, Examination create Procedure7 detailedIdentificationofData(). Phase 4 Digital forensic object Analysis(DFOA) explore analysis of data diagnosis and observe about What, Why, Who When, Where(5W, And How(1H) ? and identify the best deep learning algorithms for examination and analysis for building the investigation tool are identified. The researcher identifies three data bases namely evidence, attacker, and chain of custody for building the report using Procedure 9 Examinationandanalysis() and association of phases with access control, deep learning algorithms and chain of custody. The researcher proposed the design of the secure data structure design of chain of custody and identify the tools used in every phase of the crime investigation.

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McCoy, Airlie J., Ralf W. Grosse-Kunstleve, Paul D. Adams, Martyn D. Winn, Laurent C. Storoni, and Randy J. Read. "Phasercrystallographic software." Journal of Applied Crystallography 40, no. 4 (July 13, 2007): 658–74. http://dx.doi.org/10.1107/s0021889807021206.

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Phaseris a program for phasing macromolecular crystal structures by both molecular replacement and experimental phasing methods. The novel phasing algorithms implemented inPhaserhave been developed using maximum likelihood and multivariate statistics. For molecular replacement, the new algorithms have proved to be significantly better than traditional methods in discriminating correct solutions from noise, and for single-wavelength anomalous dispersion experimental phasing, the new algorithms, which account for correlations betweenF+andF−, give better phases (lower mean phase error with respect to the phases given by the refined structure) than those that use meanFand anomalous differences ΔF. One of the design concepts ofPhaserwas that it be capable of a high degree of automation. To this end,Phaser(written in C++) can be called directly from Python, although it can also be called using traditionalCCP4keyword-style input.Phaseris a platform for future development of improved phasing methods and their release, including source code, to the crystallographic community.

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Jeong, Byeong-Min, Yun-Seo Oh, Dae-Sung Jang, Nam-Eung Hwang, Joon-Won Kim, and Han-Lim Choi. "Makespan-Minimizing Heterogeneous Task Allocation under Temporal Constraints." Aerospace 10, no. 12 (December 14, 2023): 1032. http://dx.doi.org/10.3390/aerospace10121032.

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Task allocation is an essential element for determining the capability of multi-UAV systems to perform various tasks. This paper presents a procedure called a “rebalancing algorithm” for generating task-performing routes in heterogeneous multi-UAV systems. The algorithm adopts a greedy-based heuristic approach to find solutions efficiently in dynamically changing environments. A novel variable named “loitering” is introduced to satisfy temporal constraints, resulting in improved performance compared to heuristic algorithms: a sequential greedy algorithm, a genetic algorithm, and simulated annealing. The rebalancing algorithm is divided into two phases to minimize the makespan, i.e., the initial allocation and reallocation phases. Simulation results demonstrate the proposed algorithm’s effectiveness in highly constrained conditions and its suitability for heterogeneous systems. Additionally, the results show a reduction in calculation time and improved performance compared to the heuristic algorithms.

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Güvenoglu, Büsra, and Belgin Ergenç Bostanoglu. "A qualitative survey on frequent subgraph mining." Open Computer Science 8, no. 1 (December 1, 2018): 194–209. http://dx.doi.org/10.1515/comp-2018-0018.

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AbstractData mining is a popular research area that has been studied by many researchers and focuses on finding unforeseen and important information in large databases. One of the popular data structures used to represent large heterogeneous data in the field of data mining is graphs. So, graph mining is one of the most popular subdivisions of data mining. Subgraphs that are more frequently encountered than the user-defined threshold in a database are called frequent subgraphs. Frequent subgraphs in a database can give important information about this database. Using this information, data can be classified, clustered and indexed. The purpose of this survey is to examine frequent subgraph mining algorithms (i) in terms of frequent subgraph discovery process phases such as candidate generation and frequency calculation, (ii) categorize the algorithms according to their general attributes such as input type, dynamicity of graphs, result type, algorithmic approach they are based on, algorithmic design and graph representation as well as (iii) to discuss the performance of algorithms in comparison to each other and the challenges faced by the algorithms recently.

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Ouchitachen, Hicham, Anouar Darif, Mohamed Er-rouidi, and Mustapha Johri. "A new optimal strategy for energy minimization in wireless sensor networks." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 2 (June 1, 2024): 2265. http://dx.doi.org/10.11591/ijai.v13.i2.pp2265-2274.

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In recent years, evolutionary and metaheuristic algorithms have emerged as crucial tools for optimization in the field of artificial intelligence. These algorithms have the potential to revolutionize various aspects of our lives by leveraging the multidisciplinary nature of wireless sensor networks (WSNs). This study aims to introduce genetic and simulated annealing algorithms as effective solutions for enhancing WSN performance. Our contribution entails two main phases. Firstly, we establish mathematical models and formulate objectives as a nonlinear constrained optimization problem. Secondly, we develop two algorithmic solutions to address the formulated optimization problem. The obtained results from multiple simulations demonstrate the positive impact of the proposed strategies on improving network performance in terms of energy consumption.

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Wang Aiye, 王爱业, 潘安 Pan An, 马彩文 Ma Caiwen, and 姚保利 Yao Baoli. "相位恢复算法：原理、发展与应用（特邀）." Infrared and Laser Engineering 51, no. 11 (2022): 20220402. http://dx.doi.org/10.3788/irla20220402.

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Nahas, Suhas, Anshu Gaur, and Somnath Bhowmick. "First principles prediction of amorphous phases using evolutionary algorithms." Journal of Chemical Physics 145, no. 1 (July 7, 2016): 014106. http://dx.doi.org/10.1063/1.4955105.

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JARADAT, Yousef, Mohammad MASOUD, Ahmad MANSRAH, Ismael JANNOUD, and Mohammad ALIA. "Phases Unlocked: The Crucial Role of Qubit Phases in Quantum Computing." Eurasia Proceedings of Science Technology Engineering and Mathematics 32 (December 30, 2024): 406–16. https://doi.org/10.55549/epstem.1604685.

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Quantum computing applies quantum physics ideas to problems that traditional computers cannot address. The qubit, or quantum equivalent of the classical bit, is fundamental to this paradigm shift. Unlike its classical equivalent, a qubit can exist in a superposition of states, representing both 0 and 1. This superposition is defined not only by magnitudes, but also by important phase variables. These phases have a significant impact on qubit behavior and quantum computation outputs. This work conducts a thorough investigation of qubit phases, exploring their tremendous impact on the efficacy and capabilities of quantum algorithms. We investigate how constructive and destructive interference caused by phase interactions provides the foundation of quantum algorithms. Furthermore, we look into the intricate role of phases in establishing and managing entanglement, a unique quantum phenomenon that allows tremendous interactions between qubits. Our investigation includes the effects of numerous quantum operations on qubit phases. We present a thorough mathematical framework for describing how typical quantum gates, such as Hadamard, Pauli, and phase-shift gates, change the phase and thus the overall state of a qubit. We show these concepts through actual implementations of the Qiskit library. Finally, we discuss the intrinsic difficulty of managing and monitoring qubit phases, particularly the negative impacts of decoherence, which disrupts the delicate phase relationships. We describe tactics for mitigating these obstacles and investigate techniques for extracting phase information indirectly, such as quantum state tomography and interferometry. This comprehensive study seeks to provide a better understanding of the critical role phases play in quantum computing, paving the way for advances in algorithm design, quantum control, and the development of fault-tolerant quantum computers.

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CHEN Roujing, 陈柔婧, 韩森 HAN Sen, 康岩辉 KANG Yanhui, 徐春凤 XU Chunfeng, and 李雪园 LI Xueyuan. "一种小幅度步距相移干涉算法的相移误差分析." ACTA PHOTONICA SINICA 51, no. 11 (2022): 1112003. http://dx.doi.org/10.3788/gzxb20225111.1112003.

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Shi Lili, 师力力, 刘卫国 Liu Weiguo, 田爱玲 Tian Ailing, and 刘丙才 Liu Bingcai. "时间相位解包裹算法的抗噪性能对比研究." Laser & Optoelectronics Progress 58, no. 12 (2021): 1212006. http://dx.doi.org/10.3788/lop202158.1212006.

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Spasojevic, Zoran, Scot Dedeo, and Reed Jensen. "Dwell Scheduling Algorithms for Phased Array Antenna." IEEE Transactions on Aerospace and Electronic Systems 49, no. 1 (January 2013): 42–54. http://dx.doi.org/10.1109/taes.2013.6404090.

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Wilkin, D. J., I. Harrison, and M. S. Woolfson. "Target tracking algorithms for phased array radar." IEE Proceedings F Radar and Signal Processing 138, no. 3 (1991): 255. http://dx.doi.org/10.1049/ip-f-2.1991.0033.

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Xiaopeng Wang, Xiaopeng Wang, Shu-Chuan Chu Xiaopeng Wang, Václav Snášel Shu-Chuan Chu, Hisham A. Shehadeh Václav Snášel, and Jeng-Shyang Pan Hisham A. Shehadeh. "Five Phases Algorithm: A Novel Meta-heuristic Algorithm and Its Application on Economic Load Dispatch Problem." 網際網路技術學刊 24, no. 4 (July 2023): 837–48. http://dx.doi.org/10.53106/160792642023072404002.

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<p>A new meta-heuristic algorithm named the five phases algorithm (FPA) is presented in this paper. The proposed method is inspired by the five phases theory in traditional Chinese thought. FPA updates agents based on the generating and overcoming strategy as well as learning strategy from the agent with the same label. FPA has a simple structure but excellent performance. It also does not have any predefined control parameters, only two general parameters including population size and terminal condition are required. This provides flexibility to users to solve different optimization problems. For global optimization, 10 test functions from the CEC2019 test suite are used to evaluate the performance of FPA. The experimental results confirm that FPA is better than the 6 state-of-the-art algorithms including particle swarm optimization (PSO), grey wolf optimizer (GWO), multi-verse optimizer (MVO), differential evolution (DE), backtracking search algorithm (BSA), and slime mould algorithm (SMA). Furthermore, FPA is applied to solve the Economic Load Dispatch (ELD) from the real power system problem. The experiments give that the minimum cost of power system operation obtained by the proposed FPA is more competitive than the 14 counterparts. The source codes of this algorithm can be found in https://ww2.mathworks.cn/matlabcentral/fileexchange/118215-five-phases-algorithm-fpa.</p> <p> </p>

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Wei, L. F., and Franco Nori. "Quantum phase estimation algorithms with delays: effects of dynamical phases." Journal of Physics A: Mathematical and General 37, no. 16 (April 5, 2004): 4607–17. http://dx.doi.org/10.1088/0305-4470/37/16/010.

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Site, L. Delle. "Two Algorithms for Defining Atoms and Molecules in Condensed Phases." Molecular Simulation 26, no. 3 (March 2001): 217–35. http://dx.doi.org/10.1080/08927020108028294.

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Qiu Sen, 邱森, 张凯 Zhang Kai, 王研 Wang Yan, 张兵兵 Zhang Bingbing, and 陶冶 Tao Ye. "同轴相衬成像中基于约束的三维相位恢复算法." Laser & Optoelectronics Progress 61, no. 16 (2024): 1611019. http://dx.doi.org/10.3788/lop240639.

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XIU Longwang, 修龙汪, 李文青 LI Wenqing, 杨鹏 YANG Peng, 王博伟 WANG Bowei, and 张航 ZHANG Hang. "基于双曲初始相位的GS改进算法." ACTA PHOTONICA SINICA 51, no. 4 (2022): 0405001. http://dx.doi.org/10.3788/gzxb20225104.0405001.

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Xu Wenjing, 徐文婧, 李岩 Li Yan, 刘宇旸 Liu Yuyang, 李永富 Li Yongfu, 郭宏翔 Guo Hongxiang, 邱吉芳 Qiu Jifang, 洪小斌 Hong Xiaobin, 蔚. Li Wei, 左勇 Zuo Yong, and 伍剑 Wu Jian. "相干光通信载波相位恢复算法研究." Acta Optica Sinica 41, no. 12 (2021): 1206002. http://dx.doi.org/10.3788/aos202141.1206002.

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Koçak, Can, and Sema Alaçam. "Marco de diseño asistido por algoritmos para BIM: luz natural en las primeras fases del diseño." ESTOA 12, no. 24 (July 18, 2023): 67–79. http://dx.doi.org/10.18537/est.v012.n024.a06.

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This study proposes an algorithm-aided design (AAD) framework for using daylight in the early phases of architectural design. Within the scope of the proposed AAD, a performance-based design approach has been adopted that can suggest design solutions by optimising with the Genetic Algorithm (GA) that evaluates the results obtained from daylight calculation. The AAD framework was developed using the visual programming application (Dynamo), which interoperates with BIM Software Autodesk Revit. A case study is simulated to show how the algorithm is used to generate, evaluate and evolve a massing study, demonstrating the potential use and implementation of the framework. The investigations focus on the development of the use of daylight in architecture using the advantages of computational design tools.

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Wang, GuoChun, Wenyong Gui, Guoxi Liang, Xuehua Zhao, Mingjing Wang, Majdi Mafarja, Hamza Turabieh, Junyi Xin, Huiling Chen, and Xinsheng Ma. "Spiral Motion Enhanced Elite Whale Optimizer for Global Tasks." Complexity 2021 (August 30, 2021): 1–33. http://dx.doi.org/10.1155/2021/8130378.

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The whale optimization algorithm (WOA) is a high-performance metaheuristic algorithm that can effectively solve many practical problems and broad application prospects. However, the original algorithm has a significant improvement in space in solving speed and precision. It is easy to fall into local optimization when facing complex or high-dimensional problems. To solve these shortcomings, an elite strategy and spiral motion from moth flame optimization are utilized to enhance the original algorithm’s efficiency, called MEWOA. Using these two methods to build a more superior population, MEWOA further balances the exploration and exploitation phases and makes it easier for the algorithm to get rid of the local optimum. To show the proposed method’s performance, MEWOA is contrasted to other superior algorithms on a series of comprehensive benchmark functions and applied to practical engineering problems. The experimental data reveal that the MEWOA is better than the contrast algorithms in convergence speed and solution quality. Hence, it can be concluded that MEWOA has great potential in global optimization.

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Sathyamangalam Imran, Mohammed Irshadh Ismaaeel, Satyesh Shanker Awasthi, Michael Khayyat, Stefano Arrigoni, and Francesco Braghin. "Virtual Validation and Uncertainty Quantification of an Adaptive Model Predictive Controller-Based Motion Planner for Autonomous Driving Systems." Future Transportation 4, no. 4 (December 2, 2024): 1537–58. https://doi.org/10.3390/futuretransp4040074.

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In the context of increasing research on algorithms for different modules of the autonomous driving stack, the development and evaluation of these algorithms for deployment onboard vehicles is the next critical step. In the development and verification phases, simulations play a pivotal role in achieving this aim. The uncertainty quantification of Autonomous Vehicle (AV) systems could be used to enhance safety assurance and define the error-handling capabilities of autonomous driving systems (ADSs). In this paper, a virtual validation methodology for the control module of an autonomous driving stack is proposed. The methodology is applied to a rule-defined Model Predictive Controller (MPC)-based motion planner, where uncertainty quantification (UQ) is performed across various scenarios, based on the intended functionality within the algorithm’s operational design domain (ODD). The framework is designed to assess the performance of the algorithm under localization uncertainties, while performing obstacle vehicle-overtaking, vehicle-following, and safe-stopping maneuvers.

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Leontidis, Epameinondas, Bruce M. Forrest, Albert H. Widmann, and Ulrich W. Suter. "Monte Carlo algorithms for the atomistic simulation of condensed polymer phases." Journal of the Chemical Society, Faraday Transactions 91, no. 16 (1995): 2355. http://dx.doi.org/10.1039/ft9959102355.

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Pisarenko, V. F., A. F. Kushnir, and I. V. Savin. "Statistical adaptive algorithms for estimation of onset moments of seismic phases." Physics of the Earth and Planetary Interiors 47 (August 1987): 4–10. http://dx.doi.org/10.1016/0031-9201(87)90062-8.

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Wang Xiaoshi, 王晓诗, 桂进斌 Gui Jinbin, 李俊昌 Li Junchang, and 宋庆和 Song Qinghe. "基于迭代的纯相位全息图生成算法比较研究." Laser & Optoelectronics Progress 60, no. 6 (2023): 0609001. http://dx.doi.org/10.3788/lop213197.

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Zhou, Qingan, Rong Dai, Guoxiao Zhou, Shenghui Ma, and Shunshe Luo. "An Enhanced Tree-Seed Algorithm for Function Optimization and Production Optimization." Biomimetics 9, no. 6 (May 31, 2024): 334. http://dx.doi.org/10.3390/biomimetics9060334.

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As the fields of engineering, energy, and geology become increasingly complex, decision makers face escalating challenges that require skilled solutions to meet practical production needs. Evolutionary algorithms, inspired by biological evolution, have emerged as powerful methods for tackling intricate optimization problems without relying on gradient data. Among these, the tree-seed algorithm (TSA) distinguishes itself due to its unique mechanism and efficient searching capabilities. However, an imbalance between its exploitation and exploration phases can lead it to be stuck in local optima, impeding the discovery of globally optimal solutions. This study introduces an improved TSA that incorporates water-cycling and quantum rotation-gate mechanisms. These enhancements assist the algorithm in escaping local peaks and achieving a more harmonious balance between its exploitation and exploration phases. Comparative experimental evaluations, using the CEC 2017 benchmarks and a well-known metaheuristic algorithm, demonstrate the upgraded algorithm’s faster convergence rate and enhanced ability to locate global optima. Additionally, its application in optimizing reservoir production models underscores its superior performance compared to competing methods, further validating its real-world optimization capabilities.

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Hama Rashid, Deeam Najmadeen, Tarik A. Rashid, and Seyedali Mirjalili. "ANA: Ant Nesting Algorithm for Optimizing Real-World Problems." Mathematics 9, no. 23 (December 2, 2021): 3111. http://dx.doi.org/10.3390/math9233111.

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In this paper, a novel swarm intelligent algorithm is proposed called ant nesting algorithm (ANA). The algorithm is inspired by Leptothorax ants and mimics the behavior of ants searching for positions to deposit grains while building a new nest. Although the algorithm is inspired by the swarming behavior of ants, it does not have any algorithmic similarity with the ant colony optimization (ACO) algorithm. It is worth mentioning that ANA is considered a continuous algorithm that updates the search agent position by adding the rate of change (e.g., step or velocity). ANA computes the rate of change differently as it uses previous, current solutions, fitness values during the optimization process to generate weights by utilizing the Pythagorean theorem. These weights drive the search agents during the exploration and exploitation phases. The ANA algorithm is benchmarked on 26 well-known test functions, and the results are verified by a comparative study with genetic algorithm (GA), particle swarm optimization (PSO), dragonfly algorithm (DA), five modified versions of PSO, whale optimization algorithm (WOA), salp swarm algorithm (SSA), and fitness dependent optimizer (FDO). ANA outperformances these prominent metaheuristic algorithms on several test cases and provides quite competitive results. Finally, the algorithm is employed for optimizing two well-known real-world engineering problems: antenna array design and frequency-modulated synthesis. The results on the engineering case studies demonstrate the proposed algorithm’s capability in optimizing real-world problems.

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Saxena, Akash, Shalini Shekhawat, and Rajesh Kumar. "Application and Development of Enhanced Chaotic Grasshopper Optimization Algorithms." Modelling and Simulation in Engineering 2018 (2018): 1–14. http://dx.doi.org/10.1155/2018/4945157.

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In recent years, metaheuristic algorithms have revolutionized the world with their better problem solving capacity. Any metaheuristic algorithm has two phases: exploration and exploitation. The ability of the algorithm to solve a difficult optimization problem depends upon the efficacy of these two phases. These two phases are tied with a bridging mechanism, which plays an important role. This paper presents an application of chaotic maps to improve the bridging mechanism of Grasshopper Optimisation Algorithm (GOA) by embedding 10 different maps. This experiment evolves 10 different chaotic variants of GOA, and they are named as Enhanced Chaotic Grasshopper Optimization Algorithms (ECGOAs). The performance of these variants is tested over ten shifted and biased unimodal and multimodal benchmark functions. Further, the applications of these variants have been evaluated on three-bar truss design problem and frequency-modulated sound synthesis parameter estimation problem. Results reveal that the chaotic mechanism enhances the performance of GOA. Further, the results of the Wilcoxon rank sum test also establish the efficacy of the proposed variants.

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Arbogast, Todd, Clint N. Dawson, and Mary F. Wheeler. "A parallel algorithm for two phase multicomponent contaminant transport." Applications of Mathematics 40, no. 3 (1995): 163–74. http://dx.doi.org/10.21136/am.1995.134289.

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Yu, Xin, Shanshan Lai, Yuankun Liu, Wenjing Chen, Junpeng Xue, and Qican Zhang. "Generic nonlinear error compensation algorithm for phase measuring profilometry." Chinese Optics Letters 19, no. 10 (2021): 101201. http://dx.doi.org/10.3788/col202119.101201.

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Song Xianchen, 宋宪晨, 唐东林 Tang Donglin, and 丁超 Ding chao. "基于正交信号融合计算的相位解调算法." Acta Optica Sinica 43, no. 22 (2023): 2206005. http://dx.doi.org/10.3788/aos231270.

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Sahu, Kritika, and Anand V Bakshi. "An Intelligent Protection Algorithm for Unsymmetrical Phase Shifting Transformers." International Journal of Science and Research (IJSR) 11, no. 5 (May 5, 2022): 2072–83. http://dx.doi.org/10.21275/sr22524104809.

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Simpson, Ellen, Andrew Hamann, and Bryan Semaan. "How to Tame "Your" Algorithm." Proceedings of the ACM on Human-Computer Interaction 6, GROUP (January 14, 2022): 1–27. http://dx.doi.org/10.1145/3492841.

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As our social worlds increasingly shift online, many of the technologies people encounter are mediated by algorithms. Algorithms have become deeply embedded into people's online lives, often working to tailor and personalize their routine encounters with the world. How does one domesticate, or make one's own, an algorithmic system? One of the goals as people adopt new technologies is to weave them into their everyday routines, establishing a pattern of use in order to make that technology their own. In this paper we focus on people's experiences domesticating the short-form video sharing application, TikTok. Through an interview study with 16 LGBTQ+ TikTok users, we explore how people's routine experiences with TikTok's For You Page algorithm influence and inform their domestication process. We first highlight people's motivations for adopting TikTok and the challenges they encounter in this initial acquisition phase of domestication. After adopting the platform, we discuss the challenges people experience across the final three phases of domestication: objectification, incorporation, and conversion. We find that though they enjoy TikTok, our participants feel that they are never fully able to domesticate TikTok. As they are never able to fully control their digital selves, and thus integrate it into their routine lives, TikTok is in constant misalignment with their personal moral economy. We discuss the implications of domesticating algorithmic systems, examining the questions of whose values shape the moral economy created by and through people's uses of algorithmic systems, and the impact of nostalgia on the domestication process.

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Li, Xiaofeng, and Junyi Du. "Unexpected superhard phases of niobium triborides: first-principles calculations." RSC Advances 6, no. 54 (2016): 49214–20. http://dx.doi.org/10.1039/c6ra05162f.

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Using an unbiased structure search method based on particle-swarm optimization algorithms in combination with density functional theory calculations, we investigate the phase stability and electronic properties of NbB₃ under high pressures.

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Li, Litao. "Exploring Multi-Armed Bandit algorithms: Performance analysis in dynamic environments." Applied and Computational Engineering 34, no. 1 (January 22, 2024): 252–59. http://dx.doi.org/10.54254/2755-2721/34/20230338.

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The Multi-armed Bandit algorithm, a proficient solver of the exploration-and-exploitation trade-off predicament, furnishes businesses with a robust tool for resource allocation that predominantly aligns with customer preferences. However, varying Multi-armed Bandit algorithm types exhibit dissimilar performance characteristics based on contextual variations. Hence, a series of experiments is imperative, involving alterations to input values across distinct algorithms. Within this study, three specific algorithms were applied, Explore-then-commit (ETC), Upper Confident Bound (UCB) and its asymptotically optimal variant, and Thompson Sampling (TS), to the extensively utilized MovieLens dataset. This application aimed to gauge their effectiveness comprehensively. The algorithms were translated into executable code, and their performance was visually depicted through multiple figures. Through cumulative regret tracking within defined conditions, algorithmic performance was scrutinized, laying the groundwork for subsequent parameter-based comparisons. A dedicated experimentation framework was devised to evaluate the robustness of each algorithm, involving deliberate parameter adjustments and tailored experiments to elucidate distinct performance nuances. The ensuing graphical depictions distinctly illustrated Thompson Sampling's persistent minimal regrets across most scenarios. UCB algorithms displayed steadfast stability. ETC manifested excellent performance with a low number of runs but escalate significantly along the number of runs growing. It also warranting constraints on exploratory phases to mitigate regrets. This investigation underscores the efficacy of Multi-armed Bandit algorithms while elucidating their nuanced behaviors within diverse contextual contingencies.

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Ameen, Azad A., Tarik A. Rashid, and Shavan Askar. "CDDO–HS: Child Drawing Development Optimization–Harmony Search Algorithm." Applied Sciences 13, no. 9 (May 8, 2023): 5795. http://dx.doi.org/10.3390/app13095795.

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Child drawing development optimization (CDDO) is a recent example of a metaheuristic algorithm. The motive for inventing this method is children’s learning behavior and cognitive development, with the golden ratio being employed to optimize the aesthetic value of their artwork. Unfortunately, CDDO suffers from low performance in the exploration phase, and the local best solution stagnates. Harmony search (HS) is a highly competitive algorithm relative to other prevalent metaheuristic algorithms, as its exploration phase performance on unimodal benchmark functions is outstanding. Thus, to avoid these issues, we present CDDO–HS, a hybridization of both standards of CDDO and HS. The hybridized model proposed consists of two phases. Initially, the pattern size (PS) is relocated to the algorithm’s core and the initial pattern size is set to 80% of the total population size. Second, the standard harmony search (HS) is added to the pattern size (PS) for the exploration phase to enhance and update the solution after each iteration. Experiments are evaluated using two distinct standard benchmark functions, known as classical test functions, including 23 common functions and 10 CEC-C06 2019 functions. Additionally, the suggested CDDO–HS is compared to CDDO, the HS, and six others widely used algorithms. Using the Wilcoxon rank-sum test, the results indicate that CDDO–HS beats alternative algorithms.

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Skopec, Robert, Dubnik Dubnik, and Slovakia Slovakia. "Quantum Resourrection: Quantum Algorithm With Complex Conjugation Reverses Phases of The Wave Function Components." Neuroscience and Neurological Surgery 4, no. 2 (July 2, 2019): 01–06. http://dx.doi.org/10.31579/2578-8868/062.

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Light is a powerful tool to manipulate matter, but existing approaches often necessitate focused, high-intensity light that limits the manipulated object’s shape, material and size. The breakthrough development could lead to spacecraft without fuel. What if a spacecraft could travel through our solar system powered and accelerated using only light? That’s the goal of new research coming out of Caltech. More federal spending on directed energy weapon research & development has some stakeholders looking for operational systems to deploy in the next two or three years. The weapons which use focused energy in the forms of lasers, microwaves and other methods against targets ranging from drone swarms to ballistic missiles have long drawn the interest of the Department of Defense and its military services but have previously been relegated largely to the arena of the theoretical. They have artificially created a state that evolves in a direction opposite that of the thermodynamic arrow of time. Scientists have reversed the direction of time with a quantum computer.

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MERRILL, DUANE, and ANDREW GRIMSHAW. "HIGH PERFORMANCE AND SCALABLE RADIX SORTING: A CASE STUDY OF IMPLEMENTING DYNAMIC PARALLELISM FOR GPU COMPUTING." Parallel Processing Letters 21, no. 02 (June 2011): 245–72. http://dx.doi.org/10.1142/s0129626411000187.

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The need to rank and order data is pervasive, and many algorithms are fundamentally dependent upon sorting and partitioning operations. Prior to this work, GPU stream processors have been perceived as challenging targets for problems with dynamic and global data-dependences such as sorting. This paper presents: (1) a family of very efficient parallel algorithms for radix sorting; and (2) our allocation-oriented algorithmic design strategies that match the strengths of GPU processor architecture to this genre of dynamic parallelism. We demonstrate multiple factors of speedup (up to 3.8x) compared to state-of-the-art GPU sorting. We also reverse the performance differentials observed between GPU and multi/many-core CPU architectures by recent comparisons in the literature, including those with 32-core CPU-based accelerators. Our average sorting rates exceed 1B 32-bit keys/sec on a single GPU microprocessor. Our sorting passes are constructed from a very efficient parallel prefix scan "runtime" that incorporates three design features: (1) kernel fusion for locally generating and consuming prefix scan data; (2) multi-scan for performing multiple related, concurrent prefix scans (one for each partitioning bin); and (3) flexible algorithm serialization for avoiding unnecessary synchronization and communication within algorithmic phases, allowing us to construct a single implementation that scales well across all generations and configurations of programmable NVIDIA GPUs.

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Li Liyan, 李丽艳, 范松涛 Fan Songtao, and 周燕 Zhou Yan. "消光强扰动的相位载波解调算法." Infrared and Laser Engineering 50, no. 9 (2021): 20210485. http://dx.doi.org/10.3788/irla20210485.

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Lei Ming, 雷铭, 冯志辉 Feng Zhihui, 南亚明 Nan Yaming, and 冯田 Feng Tian. "基于自适应滤波的相敏检测算法研究." Laser & Optoelectronics Progress 59, no. 1 (2022): 0112003. http://dx.doi.org/10.3788/lop202259.0112003.

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Liang Xue, Liang Xue, Shouyu Wang Shouyu Wang, Keding Yan Keding Yan, Nan Sun Nan Sun, Zhenhua Li Zhenhua Li, and Fei Liu Fei Liu. "Fast pixel shifting phase unwrapping algorithm in quantitative interferometric microscopy." Chinese Optics Letters 12, no. 7 (2014): 071801–71806. http://dx.doi.org/10.3788/col201412.071801.

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Li Huagui, 李华贵, 李少波 Li Shaobo, 刘旭超 Liu Xuchao, and 马树泉 Ma Shuquan. "相干光通信消相位模糊载波同步算法." Acta Optica Sinica 44, no. 5 (2024): 0506006. http://dx.doi.org/10.3788/aos231649.

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JIANG Yichao, 蒋翌超, 顾劭傑 GU Shaojie, 张刚 ZHANG Gang, 许林广 XU Linguang, 葛强 GE Qiang, 吴许强 WU Xuqiang, and 俞本立 YU Benli. "面向激光测振应用的改进相位生成载波解调算法." ACTA PHOTONICA SINICA 53, no. 1 (2024): 0114005. http://dx.doi.org/10.3788/gzxb20245301.0114005.

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WANG, YUPING. "A UNIFORM ENHANCEMENT APPROACH FOR OPTIMIZATION ALGORITHMS: SMOOTHING FUNCTION METHOD." International Journal of Pattern Recognition and Artificial Intelligence 24, no. 07 (November 2010): 1111–31. http://dx.doi.org/10.1142/s0218001410008287.

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In this paper, we propose a uniform enhancement approach called smoothing function method, which can cooperate any optimization algorithm and improve its performance. The method has two phases. In the first phase, a smoothing function is constructed by using a properly truncated Fourier series. It can preserve the overall shape of the original objective function but eliminate many of its local optimal points, thus it can well approach the objective function. Then, the optimal solution of the smoothing function is searched by an optimization algorithm (e.g. traditional algorithm or evolutionary algorithm) so that the search becomes much easier. In the second phase, we switch to optimize the original function for some iterations by using the best solution(s) obtained in phase 1 as an initial point (population). Thereafter, the smoothing function is updated in order to approximate the original function more accurately. These two phases are repeated until the best solutions obtained in several successively second phases cannot be improved obviously. In this manner, any optimization algorithm will become much easier in searching optimal solution. Finally, we use the proposed approach to enhance two typical optimization algorithms: Powell direct algorithm and a simple genetic algorithm. The simulation results on ten challenging benchmarks indicate the proposed approach can effectively improve the performance of these two algorithms.

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Zhao, Hangdong, Shaleen Deep, Paraschos Koutris, Sudeepa Roy, and Val Tannen. "Evaluating Datalog over Semirings: A Grounding-based Approach." Proceedings of the ACM on Management of Data 2, no. 2 (May 10, 2024): 1–26. http://dx.doi.org/10.1145/3651591.

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Datalog is a powerful yet elegant language that allows expressing recursive computation. Although Datalog evaluation has been extensively studied in the literature, so far, only loose upper bounds are known on how fast a Datalog program can be evaluated. In this work, we ask the following question: given a Datalog program over a naturally-ordered semiring σ, what is the tightest possible runtime? To this end, our main contribution is a general two-phase framework for analyzing the data complexity of Datalog over σ: first ground the program into an equivalent system of polynomial equations (i.e. grounding) and then find the least fixpoint of the grounding over σ. We present algorithms that use structure-aware query evaluation techniques to obtain the smallest possible groundings. Next, efficient algorithms for fixpoint evaluation are introduced over two classes of semirings: (1) finite-rank semirings and (2) absorptive semirings of total order. Combining both phases, we obtain state-of-the-art and new algorithmic results. Finally, we complement our results with a matching fine-grained lower bound.

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Hakemi, Shahin, Mahboobeh Houshmand, Seyyed Abed Hosseini, and Xujuan Zhou. "A Modified Quantum-Inspired Genetic Algorithm Using Lengthening Chromosome Size and an Adaptive Look-Up Table to Avoid Local Optima." Axioms 12, no. 10 (October 17, 2023): 978. http://dx.doi.org/10.3390/axioms12100978.

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The quantum-inspired genetic algorithm (QGA), which combines quantum mechanics concepts and GA to enhance search capability, has been popular and provides an efficient search mechanism. This paper proposes a modified QGA, called dynamic QGA (DQGA). The proposed algorithm utilizes a lengthening chromosome strategy for a balanced and smooth transition between exploration and exploitation phases to avoid local optima and premature convergence. Apart from that, a novel adaptive look-up table for rotation gates is presented to boost the algorithm’s optimization abilities. To evaluate the effectiveness of these ideas, DQGA is tested by various mathematical benchmark functions as well as real-world constrained engineering problems against several well-known and state-of-the-art algorithms. The obtained results indicate the merits of the proposed algorithm and its superiority for solving multimodal benchmark functions and real-world constrained engineering problems.

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Journal articles on the topic 'Algorithmes à phases'

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