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

A novel context-free grammar for the generation of PSO algorithms.

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

Quelle: Natural Computing; Sep2020, Vol. 19 Issue 3, p495-513, 19p

Schlagwörter: GRAMMAR, OPERATOR equations, GENETIC programming, ALGORITHMS, MATHEMATICAL optimization

A comprehensive comparative analysis of particle swarm optimization and genetic algorithms in well acidizing optimization.

Autoren: Ebadi, Seyed Mahan Khamehchi, Ehsan Mahdavi Kalatehno, Javad

Quelle: Journal of Petroleum Exploration & Production Technology; Jan2026, Vol. 16 Issue 1, p1-19, 19p

Gene selection based on adaptive neighborhood-preserving multi-objective particle swarm optimization.

Autoren: Mehta, Sumet Han, Fei Sohail, Muhammad et al.

Quelle: PeerJ Computer Science; May2025, p1-35, 35p

Schlagwörter: PARTICLE swarm optimization, FEATURE selection, MATHEMATICAL programming, MULTIPLE criteria decision making, TRANSCRIPTOMES, BIOINFORMATICS, DIMENSIONAL reduction algorithms

Adaptive Hybrid PSO–APF Algorithm for Advanced Path Planning in Next-Generation Autonomous Robots.

Autoren: Benmachiche, Abdelmadjid Derdour, Makhlouf Kahil, Moustafa Sadek et al.

Quelle: Sensors (14248220); Sep2025, Vol. 25 Issue 18, p5742, 32p

Schlagwörter: ROBOTIC path planning, PARTICLE swarm optimization, AUTONOMOUS robots, OBSTACLE avoidance (Robotics), MACHINE learning

Particle Swarm Optimization: Advances, Applications, and Experimental Insights.

Autoren: Abualigah, Laith

Quelle: Computers, Materials & Continua; 2025, Vol. 82 Issue 2, p1539-1592, 54p

Schlagwörter: OPTIMIZATION algorithms, PARTICLE swarm optimization, MACHINE learning, ENGINEERING design, DATA mining

An SVM-Based Anomaly Detection Method for Power System Security Analysis Using Particle Swarm Optimization and t-SNE for High-Dimensional Data Classification.

Autoren: Tao, Ye Yan, Jiongcheng Niu, Enquan et al.

Quelle: Processes; Feb2025, Vol. 13 Issue 2, p549, 24p

Schlagwörter: ELECTRIC power systems, OPTIMIZATION algorithms, PARTICLE swarm optimization, SUPPORT vector machines, SEARCH algorithms

LLM-Enhanced metaheuristics with single-shot and few-shot learning for multi-robot exploration tasks.

Autoren: El Romeh, Ali Snasel, Vaclav Mirjalili, Seyedali

Quelle: Cluster Computing; Dec2025, Vol. 28 Issue 16, p1-35, 35p

Schlagwörter: LANGUAGE models, PARTICLE swarm optimization, MACHINE learning, ROBOTICS, MATHEMATICAL optimization

A hybrid DECSO algorithm for efficient multi objective task scheduling in cloud computing environments.

Autoren: Gunduz, Ali Senan, Sibel Gurkas-Aydin, Zeynep

Quelle: Cluster Computing; Nov2025, Vol. 28 Issue 13, p1-22, 22p

Schlagwörter: CLOUD computing, SCHEDULING, COMPUTER simulation, MULTI-objective optimization, RESOURCE allocation, OPTIMIZATION algorithms, PRODUCTION scheduling, MATHEMATICAL optimization

Multi-Objective Optimization Method for Power Transformer Design Based on Surrogate Modeling and Hybrid Heuristic Algorithm.

Autoren: Shi, Baidi Xiao, Wei Zhang, Liangxian et al.

Quelle: Electronics (2079-9292); Mar2025, Vol. 14 Issue 6, p1198, 28p

Schlagwörter: ENSEMBLE learning, EXTREME learning machines, MULTI-objective optimization, OPTIMIZATION algorithms, HEURISTIC algorithms, PARTICLE swarm optimization

Comparative analysis of direct search methods for material design optimization.

Autoren: Coropețchi, I.C. Constantinescu, D.M. Vasile, A. et al.

Quelle: Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design & Applications (Sage Publications, Ltd.); Apr2025, Vol. 239 Issue 4, p642-660, 19p

Meta learning-based few-shot intrusion detection for 5G-enabled industrial internet.

Autoren: Yan, Yu Yang, Yu Shen, Fang et al.

Quelle: Complex & Intelligent Systems; Jun2024, Vol. 10 Issue 3, p4589-4608, 20p

Schlagwörter: INTRUSION detection systems (Computer security), PARTICLE swarm optimization, MACHINE learning, INDUSTRIAL controls manufacturing, TRAFFIC monitoring, INTERNET, TRANSFORMER models

Synergistic Swarm Optimization Algorithm.

Autoren: Alzoubi, Sharaf Abualigah, Laith Sharaf, Mohamed et al.

Quelle: Computer Modeling in Engineering & Sciences (CMES); 2024, Vol. 139 Issue 3, p2557-2604, 48p

Schlagwörter: OPTIMIZATION algorithms, PARTICLE swarm optimization, ENGINEERING design, SEARCHING behavior, INFORMATION sharing

Encoding local label correlations in multi-instance multi-label learning with an improved multi-objective particle swarm optimization.

Autoren: Bao, Xiang Han, Fei Ling, Qinghua

Quelle: Complex & Intelligent Systems; Jun2025, Vol. 11 Issue 6, p1-25, 25p

Opposite scoring: focusing the tuning process of evolutionary calibrator.

Autoren: Rojas-Morales, Nicolás Riff, María-Cristina

Quelle: Neural Computing & Applications; May2023, Vol. 35 Issue 13, p9269-9283, 15p

Schlagwörter: ANT algorithms, PARTICLE swarm optimization, METAHEURISTIC algorithms, KNAPSACK problems, GENETIC algorithms, EVOLUTIONARY algorithms, LANDSCAPE assessment

Intelligence Techniques in Sustainable Energy: Analysis of a Decade of Advances.

Autoren: Velásquez, Juan D. Cadavid, Lorena Franco, Carlos J.

Quelle: Energies (19961073); Oct2023, Vol. 16 Issue 19, p6974, 45p

Schlagwörter: DEEP learning, CLEAN energy, DIFFERENTIAL evolution, SMART power grids, PARTICLE swarm optimization, WIND power, ARTIFICIAL intelligence, SOLAR energy

A Systematic Literature Review on the Use of Federated Learning and Bioinspired Computing.

Autoren: Marin Machado de Souza, Rafael Holm, Andrew Biczyk, Márcio et al.

Quelle: Electronics (2079-9292); Aug2024, Vol. 13 Issue 16, p3157, 25p

Schlagwörter: FEDERATED learning, MACHINE learning, PARTICLE swarm optimization, EVOLUTIONARY algorithms, SMART cities

A Hybrid Particle Swarm Optimization Algorithm with Dynamic Adjustment of Inertia Weight Based on a New Feature Selection Method to Optimize SVM Parameters.

Autoren: Wang, Jing Wang, Xingyi Li, Xiongfei et al.

Quelle: Entropy; Mar2023, Vol. 25 Issue 3, p531, 23p

Schlagwörter: FEATURE selection, PARTICLE swarm optimization, SEARCH algorithms, SUPPORT vector machines

Dual-objective economic planning of simultaneous allocation of disconnectors and maneuvering points considering the direction of error reduction in the presence of fault detector with the multi-objective PSO.

Autoren: Liu, Yan Lun, Qingqing Zhang, Jingjing

Quelle: Electrical Engineering; Apr2025, Vol. 107 Issue 4, p4021-4036, 16p

Schlagwörter: PARTICLE swarm optimization, POWER resources, CENTRAL economic planning, ELECTRICAL energy, ELECTRICAL supplies

Cyber attack detection in IOT-WSN devices with threat intelligence using hidden and connected layer based architectures.

Autoren: Nandhini, S. Rajeswari, A. Shanker, N. R.

Quelle: Journal of Cloud Computing (2192-113X); 12/20/2024, Vol. 13 Issue 1, p1-21, 21p

Schlagwörter: LONG short-term memory, PARTICLE swarm optimization, ARTIFICIAL intelligence, CYBERTERRORISM, IMAGE processing

A Comprehensive Survey on Rare Event Prediction.

Autoren: Shyalika, Chathurangi Wickramarachchi, Ruwan Sheth, Amit P.

Quelle: ACM Computing Surveys; Mar2025, Vol. 57 Issue 3, p1-39, 39p

Schlagwörter: ARTIFICIAL neural networks, MACHINE learning, PARTICLE swarm optimization, ARTIFICIAL intelligence, LONG short-term memory, SUPERVISED learning, DEEP learning, STATISTICAL learning