Suchergebnisse - Meta-learning. Particle Swarm Optimization. Genetic Programming. Algorithm generation.*

Optimizing Multi-Modal Electromagnetic Design Problems Using Quantum Particle Swarm Optimization With Differential Evolution

Autoren: Shah Fahad Shoaib Ahmed Khan Shiyou Yang et al.

Quelle: IEEE Access, Vol 11, Pp 101760-101775 (2023)

Schlagwörter: Artificial intelligence, Premature convergence, Swarm intelligence, Metaheuristic, Evolutionary computation, 7. Clean energy, DE, Swarm behaviour, Artificial Intelligence, energy storage device (SMES), Evolutionary algorithm, FOS: Mathematics, Swarm Intelligence Optimization Algorithms, Optimization problem, hybridization, Geography, Multi-Objective Optimization, Multi-swarm optimization, Particle swarm optimization, Meta-optimization, Optimization Applications, Mathematical optimization, Differential Evolution, Computer science, Ant Colony Optimization, TK1-9971, Algorithm, Computational Theory and Mathematics, Particle Swarm Optimization, Application of Genetic Programming in Machine Learning, Computer Science, Physical Sciences, Boltzmann selection strategy, Crossover, Electrical engineering. Electronics. Nuclear engineering, Smart particle, Differential evolution, Benchmark (surveying), QPSO, Multiobjective Optimization in Evolutionary Algorithms, Mathematics, Geodesy

Zugangs-URL: https://doaj.org/article/00ed682f369d46719fabbd735c109536

Algorithm tuners for PSO methods and genetic programming techniques for learning tuning rules.

Autoren: Kanemasa, Minoru Aiyoshi, Eitaro

Quelle: IEEJ Transactions on Electrical & Electronic Engineering; Jul2014, Vol. 9 Issue 4, p407-414, 8p

Schlagwörter: PARTICLE swarm optimization, GENETIC programming, MATHEMATICAL optimization, GENETIC algorithms

An Enhanced Firefly Algorithm Using Pattern Search for Solving Optimization Problems

Autoren: Fazli Wahid Maryam Zia Rao Naveed Bin Rais et al.

Quelle: IEEE Access, Vol 8, Pp 148264-148288 (2020)

Schlagwörter: optimization problems, minimization and maximization functions, Economics, fast convergence, Firefly algorithm, pattern search, rich exploration and exploitation, Premature convergence, Metaheuristic, 02 engineering and technology, Artificial Intelligence, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Firefly Algorithm, Swarm Intelligence Optimization Algorithms, Ant colony optimization algorithms, Economic growth, Global Optimization, Meta-optimization, Particle swarm optimization, Optimization Applications, Mathematical optimization, Computer science, TK1-9971, Algorithm, Computational Theory and Mathematics, Genetic algorithm, Particle Swarm Optimization, Application of Genetic Programming in Machine Learning, Computer Science, Physical Sciences, Nature-Inspired Algorithms, Convergence (economics), Maximization, Electrical engineering. Electronics. Nuclear engineering, Differential evolution, Multiobjective Optimization in Evolutionary Algorithms, Mathematics

Dateibeschreibung: application/pdf

Zugangs-URL: https://ieeexplore.ieee.org/ielx7/6287639/8948470/09163099.pdf
https://doaj.org/article/c4884aac1c2946c6a6a6a15d7b7743e7
https://dblp.uni-trier.de/db/journals/access/access8.html#WahidZRABAAKK20
https://ieeexplore.ieee.org/document/9163099

Uma hiper-heurística híbrida para a otimização de algorítmos

Autoren: MIRANDA, Pericles Barbosa Cunha de

Thesis Advisors: PRUDÊNCIO, Ricardo Bastos Cavalcante

Quelle: Repositório Institucional da UFPEUniversidade Federal de PernambucoUFPE.

Schlagwörter: Meta-aprendizado. Otimização por enxame de partículas. Programação Genética. Geração de algoritmos., Meta-learning. Particle Swarm Optimization. Genetic Programming. Algorithm generation.

Verfügbarkeit: https://repositorio.ufpe.br/handle/123456789/18703

Combinatorial Test Suites Generation Strategy Utilizing the Whale Optimization Algorithm

Autoren: Ali Hassan Salwani Abdullah Kamal Z. Zamli et al.

Quelle: IEEE Access, Vol 8, Pp 192288-192303 (2020)

Schlagwörter: FOS: Computer and information sciences, Population, Software Defect Prediction, Code coverage, 02 engineering and technology, Search-based software engineering, Sociology, Machine learning, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Heuristics, Software design, Demography, Dynamic Test Generation, Automated Software Testing Techniques, Geography, Particle swarm optimization, Mathematical optimization, Test suite, Cuckoo search, software testing, Software development, Computer science, meta-heuristic, TK1-9971, Programming language, FOS: Sociology, Algorithm, Operating system, Search-based software engineering (SBSE), T-way testing, Solver, Computer Science, Physical Sciences, Search-Based Testing, Electrical engineering. Electronics. Nuclear engineering, Software Reliability Assessment and Prediction, Test case, Benchmark (surveying), Regression analysis, combinatorial testing, Software, Mathematics, Geodesy, Empirical Studies in Software Engineering, Information Systems

Zugangs-URL: https://ieeexplore.ieee.org/ielx7/6287639/6514899/09234407.pdf
https://doaj.org/article/8c88ca18811a4fa89883a2d86d896100

Dynamical Sphere Regrouping Particle Swarm Optimization Programming: An Automatic Programming Algorithm Avoiding Premature Convergence.

Autoren: Montes Rivera, Martín Guerrero-Mendez, Carlos Lopez-Betancur, Daniela et al.

Quelle: Mathematics (2227-7390). Oct2024, Vol. 12 Issue 19, p3021. 53p.

Schlagwörter: *MACHINE learning, *GENETIC programming, *MATHEMATICAL mappings, *MATHEMATICAL models, *ALGORITHMS

Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection.

Autoren: Nwogbaga, Nweso Emmanuel Latip, Rohaya Affendey, Lilly Suriani et al.

Quelle: Journal of Cloud Computing (2192-113X); 6/4/2022, Vol. 11 Issue 1, p1-17, 17p

Schlagwörter: PARTICLE swarm optimization, GENETIC algorithms, JAVA programming language, ALGORITHMS, PROCESS capability

Hybrid Particle Swarm Optimization — Genetic algorithm and Particle Swarm Optimization — Evolutionary programming for long-term generation maintenance scheduling

Autoren: C. Christober Asir Rajan G. Giftson Samuel

Quelle: 2013 International Conference on Renewable Energy and Sustainable Energy (ICRESE). :227-232

Schlagwörter: 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 7. Clean energy

Zugangs-URL: https://neredataltics.org/asi/index.php/ijarer/article/view/6791
http://ieeexplore.ieee.org/iel7/6917610/6927783/06927820.pdf
http://ieeexplore.ieee.org/abstract/document/6927820

Modified grasshopper optimization algorithm-based genetic algorithm for global optimization problems: the system of nonlinear equations case study

Autoren: Hazem Omar M.A. El‐Shorbagy

Schlagwörter: Economics, Quantum mechanics, Artificial Intelligence, Nonlinear programming, FOS: Mathematics, Swarm Intelligence Optimization Algorithms, Optimization problem, Economic growth, Numerical Analysis, Computer network, Global Optimization, Numerical Optimization Techniques, Optimization Software, Multi-Objective Optimization, 4. Education, Meta-optimization, Physics, Mathematical optimization, Rate of convergence, Computer science, Process (computing), Algorithm, Optimization algorithm, Operating system, Genetic algorithm, Particle Swarm Optimization, Channel (broadcasting), Application of Genetic Programming in Machine Learning, Computer Science, Physical Sciences, Nature-Inspired Algorithms, Convergence (economics), Nonlinear system, Global optimization, Mathematics

Routing algorithm with QoS constraints for real time multicast communications using particle swarm optimization and genetic meta-optimizer.

Autoren: CAMARGO, Y. E. I. S. O. N. J. U. L. I. A. N. Ramirez, Leonardo Juan Martinez, Ana Karina

Quelle: Engineering Computations; 2016, Vol. 33 Issue 2, p344-365, 22p

Schlagwörter: QUALITY of service, WIRELESS sensor nodes, ROUTING (Computer network management), ROUTING algorithms, JAVA programming language

Application of Meta-Heuristic Techniques for Optimal Load Shedding in Islanded Distribution Network with High Penetration of Solar PV Generation

Autoren: Mohammad Dreidy Hazlie Mokhlis Saad Mekhilef et al.

Weitere Verfasser: Mohammad Dreidy Hazlie Mokhlis Saad Mekhilef et al.

Quelle: Energies, Vol 10, Iss 2, p 150 (2017)
Energies
Volume 10
Issue 2

Schlagwörter: Distribution Generation (DG), Renewable Energy Resources (RESs), Technology, 02 engineering and technology, 7. Clean energy, TK Electrical engineering. Electronics Nuclear engineering, 3. Good health, 13. Climate action, Binary Particle Swarm Optimization (BPSO), 0202 electrical engineering, electronic engineering, information engineering, Under Frequency Load Shedding (UFLS), Binary Evolutionary Programming (BEP), Binary Genetic Algorithm (BGA)

Dateibeschreibung: application/pdf

Zugangs-URL: https://www.mdpi.com/1996-1073/10/2/150/pdf
https://doaj.org/article/08db27028478468294524b68544a7d55
https://www.mdpi.com/1996-1073/10/2/150/pdf
https://EconPapers.repec.org/RePEc:gam:jeners:v:10:y:2017:i:2:p:150-:d:88625
http://eprints.um.edu.my/19193/
https://ideas.repec.org/a/gam/jeners/v10y2017i2p150-d88625.html
https://core.ac.uk/display/90717153
https://www.mdpi.com/1996-1073/10/2/150

Generation of Particle Swarm Optimization algorithms: An experimental study using Grammar-Guided Genetic Programming.

Autoren: Miranda, Péricles B.C. Prudêncio, Ricardo B.C.

Quelle: Applied Soft Computing. Nov2017, Vol. 60, p281-296. 16p.

Schlagwörter: Particle swarm optimization, Genetic programming, Algorithms, Heuristic algorithms, Soft computing

CDMO: Chaotic Dwarf Mongoose Optimization Algorithm for feature selection

Autoren: Mohamed Abdelrazek Mohamed Abd Elaziz A. H. El-Baz

Quelle: Sci Rep
Scientific Reports, Vol 14, Iss 1, Pp 1-18 (2024)

Schlagwörter: Optimization, 0209 industrial biotechnology, Artificial intelligence, Science, Biomedical Engineering, Metaheuristic, 02 engineering and technology, FOS: Medical engineering, Pattern recognition (psychology), Article, Swarm behaviour, Engineering, Artificial Intelligence, 0202 electrical engineering, electronic engineering, information engineering, Artificial Immune Systems in Science and Engineering, FOS: Mathematics, 14. Life underwater, Swarm Intelligence Optimization Algorithms, Feature Selection, Ant colony optimization algorithms, Multi-swarm optimization, Particle swarm optimization, Meta-optimization, Mathematical optimization, Computer science, Ant Colony Optimization, Algorithm, Particle Swarm Optimization, Application of Genetic Programming in Machine Learning, Computer Science, Physical Sciences, Nature-Inspired Algorithms, Feature selection, Medicine, Mathematics

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/38184680
https://doaj.org/article/cfa71326180e4ca29a72d450fcf895f3

Multidimensional knapsack problem optimization using a binary particle swarm model with genetic operations.

Autoren: Mingo López, Luis Fernando Gómez Blas, Nuria Arteta Albert, Alberto

Quelle: Soft Computing - A Fusion of Foundations, Methodologies & Applications; Apr2018, Vol. 22 Issue 8, p2567-2582, 16p

Schlagwörter: KNAPSACK problems, INTEGER programming, PARTICLE swarm optimization, ALGORITHMS, GENETIC algorithms

Enhanced Tunicate Swarm Algorithm for Solving Large-Scale Nonlinear Optimization Problems

Autoren: Rizk M. Rizk‐Allah O. Saleh Enas A. Hagag et al.

Quelle: International Journal of Computational Intelligence Systems. 14

Schlagwörter: Artificial intelligence, Robustness (evolution), Swarm intelligence, 0211 other engineering and technologies, Heuristic, 02 engineering and technology, Tunicate, Biochemistry, Gene, 7. Clean energy, Swarm behaviour, Database, Semantic Genetic Programming, Artificial Intelligence, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Swarm Intelligence Optimization Algorithms, Biology, Ecology, Geography, Particle swarm optimization, Optimization Applications, Mathematical optimization, Scalability, Computer science, Ant Colony Optimization, Algorithm, Chemistry, Computational Theory and Mathematics, Particle Swarm Optimization, Application of Genetic Programming in Machine Learning, FOS: Biological sciences, Computer Science, Physical Sciences, Nature-Inspired Algorithms, Benchmark (surveying), Multiobjective Optimization in Evolutionary Algorithms, Mathematics, Geodesy

Zugangs-URL: https://link.springer.com/content/pdf/10.1007/s44196-021-00039-4.pdf
https://link.springer.com/article/10.1007/s44196-021-00039-4
https://dblp.uni-trier.de/db/journals/ijcisys/ijcisys14.html#Rizk-AllahSHM21
https://link.springer.com/content/pdf/10.1007/s44196-021-00039-4.pdf

Enhanced Route Optimization for Wireless Networks Using Meta-Heuristic Engineering

Autoren: Srivatsan Krishnan P. Sundara Vadivel D. Yuvaraj et al.

Quelle: Computer Systems Science and Engineering. 43:17-26

Schlagwörter: Artificial intelligence, Computer Networks and Communications, Mobile Sensor Deployment, Acknowledgement, 02 engineering and technology, 7. Clean energy, Real-time computing, Artificial Intelligence, 0202 electrical engineering, electronic engineering, information engineering, Swarm Intelligence Optimization Algorithms, Data mining, Computer network, Wireless Sensor Networks: Survey and Applications, Network packet, Particle swarm optimization, Intrusion detection system, Optimization Applications, Routing Techniques, Computer science, Algorithm, Particle Swarm Optimization, Application of Genetic Programming in Machine Learning, Computer Science, Physical Sciences, Kalman filter, Wireless Sensor Networks, Wireless sensor network

Estimation for Model Parameters and Maximum Power Points of Photovoltaic Modules Using Stochastic Fractal Search Algorithms

Autoren: Duy C. Huynh Matthew W. Dunnigan Corina Barbălată

Quelle: IEEE Access, Vol 10, Pp 104408-104428 (2022)

Schlagwörter: Photovoltaic Arrays, PV System, Parameter Estimation, 02 engineering and technology, meta-heuristic algorithms, 7. Clean energy, Artificial Intelligence, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Machine Learning Methods for Solar Radiation Forecasting, Maximum power principle, Biology, Photovoltaic system, Maximum Power Point Tracking, photovoltaic modules, Energy, Ecology, Renewable Energy, Sustainability and the Environment, Minification, Particle swarm optimization, Mathematical optimization, Statistics, Photovoltaic Maximum Power Point Tracking Techniques, Computer science, TK1-9971, Algorithm, Application of Genetic Programming in Machine Learning, FOS: Biological sciences, maximum power point, Computer Science, Physical Sciences, Photovoltaic Power, Mean squared error, model parameter, Electrical engineering. Electronics. Nuclear engineering, Estimation, Mathematics

Zugangs-URL: https://doaj.org/article/f785eb72cd854970a7a49c9130ed9249

Supply chain scheduling optimization based on genetic particle swarm optimization algorithm.

Autoren: Xiong, Feng Gong, Peisong Jin, P. et al.

Quelle: Cluster Computing; Nov2019 Supplement 6, Vol. 22, p14767-14775, 9p

Schlagwörter: PARTICLE swarm optimization, MATHEMATICAL optimization, MATHEMATICAL programming, SUPPLY chains, SEARCH algorithms, GENETIC algorithms

Dynamic economic dispatch: a comparative study for differential evolution, particle swarm optimization, evolutionary programming, genetic algorithm, and simulated annealing

Autoren: Jagat Kishore Pattanaik Mousumi Basu Deba Prasad Dash

Quelle: Journal of Electrical Systems and Information Technology, Vol 6, Iss 1, Pp 1-18 (2019)

Schlagwörter: Dynamic economic dispatch, Differential evolution, Particle swarm optimization, Evolutionary programming, Genetic algorithm, Simulated annealing, Electrical engineering. Electronics. Nuclear engineering, TK1-9971, Information technology, T58.5-58.64

Dateibeschreibung: electronic resource

Relation: http://link.springer.com/article/10.1186/s43067-019-0001-4; https://doaj.org/toc/2314-7172

Zugangs-URL: https://doaj.org/article/34d54be82e78414584039c2990acbf3c

FIREWORKS ALGORITHM FOR UNCONSTRAINED FUNCTION OPTIMIZATION PROBLEMS

Autoren: Evans Baidoo

Quelle: Applied Computer Science, Vol 13, Iss 1, Pp 61-74 (2017)

Schlagwörter: Natural computing, Swarm intelligence, Fireworks algorithm, Function optimization, Information technology, 02 engineering and technology, Artificial Intelligence, a kind of parallel diffuse optimization algorithm is based on the explosive phenomenon of fireworks. The algorithm presented promising results when compared to other population or iterative based meta-heuristic algorithm after it was experimented on five standard benchmark problems. The software application was implemented in Java with interactive interface which allow for easy modification and extended experimentation. Additionally, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Firefly Algorithm, Swarm Intelligence Optimization Algorithms, Optimization problem, this paper validates the effect of runtime on the algorithm performance, Global Optimization, Geography, Multi-Objective Optimization, Optimization Applications, Mathematical optimization, Mathematical programming, QA75.5-76.95, T58.5-58.64, Computer science, Programming language, Algorithm, Computational Theory and Mathematics, Particle Swarm Optimization, Electronic computers. Computer science, Application of Genetic Programming in Machine Learning, Computer Science, Physical Sciences, Benchmark (surveying), Multiobjective Optimization in Evolutionary Algorithms, Java, Software, Mathematics, Geodesy

Zugangs-URL: https://doaj.org/article/7e11e6f616cb4859957fdc1045cadaf6