Search Results - meta-learning. particle swart optimization. genetics programming. algorithm generation.~

Automated test design using swarm and evolutionary intelligence algorithms.

Authors: Aktaş, Muhammet Yetgin, Zeki Kılıç, Fatih et al.

Source: Expert Systems; May2022, Vol. 39 Issue 4, p1-21, 21p

Subject Terms: BEES algorithm, SWARM intelligence, EVOLUTIONARY algorithms, TEST design, PARTICLE swarm optimization, SEARCH algorithms, GENETIC algorithms

Innovative Integration of Q-learning in BSO Algorithm for Adaptive Community Detection in Social Networks.

Authors: Beldi, Zohra Bessedik, Malika

Source: ACM Transactions on the Web; May2025, Vol. 19 Issue 2, p1-34, 34p

Subject Terms: OPTIMIZATION algorithms, SOCIAL network analysis, SOCIAL networks, REINFORCEMENT learning, SOCIAL systems

Application of Reinforcement Learning Methods Combining Graph Neural Networks and Self-Attention Mechanisms in Supply Chain Route Optimization.

Authors: Wang, Yang Liang, Xiaoxiang

Source: Sensors (14248220); Feb2025, Vol. 25 Issue 3, p955, 30p

Subject Terms: GRAPH neural networks, SUPPLY chain management, REINFORCEMENT learning, REPRESENTATIONS of graphs, SUPPLY chains

Exploring Multiple-Objective Optimization for Efficient and Effective Test Paper Design with Dynamic Programming Guided Genetic Algorithm.

Authors: Wang, Han Zhuge, Qingfeng Sha, Edwin Hsing-Mean et al.

Source: Mathematical Biosciences & Engineering; 2024, Vol. 21 Issue 3, p1-27, 27p

REliable PIcking by Consensus (REPIC): a consensus methodology for harnessing multiple cryo-EM particle pickers.

Authors: Cameron, Christopher J. F. Seager, Sebastian J. H. Sigworth, Fred J. et al.

Source: Communications Biology; 10/31/2024, Vol. 7 Issue 1, p1-12, 12p

Subject Terms: LINEAR programming, INTEGER programming, SIGNAL-to-noise ratio, ION channels, ALGORITHMS

BuildAMol: a versatile Python toolkit for fragment-based molecular design.

Authors: Kleinschmidt, Noah Lemmin, Thomas

Source: Journal of Cheminformatics; 8/25/2024, Vol. 16 Issue 1, p1-13, 13p

Subject Terms: SOFTWARE development tools, LEARNING curve, DRUG discovery, MOLECULAR structure, MOLECULAR models

Automatic mapping of multiplexed social receptive fields by deep learning and GPU-accelerated 3D videography.

Authors: Ebbesen, Christian L. Froemke, Robert C.

Source: Nature Communications; 2/1/2022, Vol. 13 Issue 1, p1-21, 21p

Subject Terms: VIDEO recording, AUTOMATIC tracking, DEEP learning, NEURAL circuitry, ROBUST optimization, SOCIAL interaction

Enhancement of voltage profile and generation of cost function by hybrid power flow controller using genetic algorithm.

Authors: Murugan, A. Ramakrishnan, V.

Source: Applied Nanoscience; Mar2023, Vol. 13 Issue 3, p2515-2525, 11p

Subject Terms: HYBRID power, COST functions, ELECTRICAL load, GENETIC algorithms, REACTIVE power, FLEXIBLE AC transmission systems

Catecholaminergic modulation of meta-learning

Authors: Dirk E. M. Geurts Jennifer Cook Hanneke E. M. den Ouden et al.

Contributors: Dirk E. M. Geurts Jennifer Cook Hanneke E. M. den Ouden et al.

Source: eLife
eLife, Vol 8 (2019)
Elife, 8

Subject Terms: Adult, Male, 0301 basic medicine, Adolescent, QH301-705.5, Science, Dopamine, volatility, Radboud University Medical Center, 610 Medicine & health, Genetics and Molecular Biology, methylphenidate, 170 Ethics, Radboudumc 13: Stress-related disorders DCMN: Donders Center for Medical Neuroscience, Placebos, Norepinephrine, Young Adult, 03 medical and health sciences, meta-learning, Dopamine Uptake Inhibitors, 1300 General Biochemistry, Genetics and Molecular Biology, 2400 General Immunology and Microbiology, Humans, Learning, 10237 Institute of Biomedical Engineering, learning rate, Biology (General), 2. Zero hunger, 0303 health sciences, Neuro- en revalidatiepsychologie, General Immunology and Microbiology, General Neuroscience, Neuropsychology and rehabilitation psychology, 2800 General Neuroscience, General Medicine, 16. Peace & justice, General Biochemistry, noradrenaline, Methylphenidate, Medicine, Female, dopamine, 170 000 Motivational & Cognitive Control, Neuroscience

File Description: 2019_elife-51439-v2.pdf - application/pdf

Access URL: https://pubmed.ncbi.nlm.nih.gov/31850844
https://doaj.org/article/3595c7cbfb774e99ad570fdbf7453334
https://pubmed.ncbi.nlm.nih.gov/31850844/
https://osf.io/z59us/#!
https://repository.ubn.ru.nl/handle/2066/215394
https://www.zora.uzh.ch/id/eprint/183319/
https://www.zora.uzh.ch/id/eprint/183319/1/2019_elife-51439-v2.pdf
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6974360
https://repository.ubn.ru.nl//bitstream/handle/2066/215394/215394.pdf
https://hdl.handle.net/2066/215394

Studying Dynamic Pricing in Electrical Power Markets with Distributed Generation: Agent-Based Modeling and Reinforcement-Learning Approach.

Authors: Ali, Gasser G. El-adaway, Islam H. Sims, Charles et al.

Source: Journal of Energy Engineering; Oct2022, Vol. 148 Issue 5, p1-21, 21p

Subject Terms: DISTRIBUTED power generation, TIME-based pricing, CONSUMER behavior, ELECTRICITY markets, INDEPENDENT power producers, PUBLIC utilities, POWER plants

Reducing the Vulnerability of Electric Power Infrastructure against Natural Disasters by Promoting Distributed Generation.

Authors: Ali, Gasser G. El-adaway, Islam H. Sims, Charles et al.

Source: Natural Hazards Review; May2023, Vol. 24 Issue 2, p1-17, 17p

Subject Terms: ELECTRIC power, NATURAL disasters, DISTRIBUTED power generation, ELECTRIC networks, ELECTRIC power distribution grids, PHOTOVOLTAIC power generation, ELECTRIC power production

Improving Forest Detection Using Machine Learning and Remote Sensing: A Case Study in Southeastern Serbia.

Authors: Potić, Ivan Srdić, Zoran Vakanjac, Boris et al.

Source: Applied Sciences (2076-3417); Jul2023, Vol. 13 Issue 14, p8289, 24p

Subject Terms: MACHINE learning, REMOTE sensing, MULTISPECTRAL imaging, DISTANCE education, VEGETATION monitoring, PYTHON programming language

Geographic Terms: SERBIA

A Machine Learning Method with Filter-Based Feature Selection for Improved Prediction of Chronic Kidney Disease.

Authors: Ebiaredoh-Mienye, Sarah A. Swart, Theo G. Esenogho, Ebenezer et al.

Source: Bioengineering (Basel); Aug2022, Vol. 9 Issue 8, pN.PAG-N.PAG, 15p

Subject Terms: FEATURE selection, CHRONIC kidney failure, COMPUTER-aided diagnosis, SCREEN time, MACHINE learning

Thefittest: evolutionary machine learning in Python.

Authors: Sherstnev, Pavel

Source: ITM Web of Conferences; 1/10/2024, Vol. 59, p1-11, 11p

Classical symmetries and the Quantum Approximate Optimization Algorithm.

Authors: Shaydulin, Ruslan Hadfield, Stuart Hogg, Tad et al.

Source: Quantum Information Processing; Nov2021, Vol. 20 Issue 11, p1-28, 28p

Subject Terms: MATHEMATICAL optimization, SYMMETRY, SYMMETRY groups, ALGORITHMS, MACHINE learning, APPROXIMATION algorithms, PROBABILITY theory

A Comprehensive Review of Deep Learning: Architectures, Recent Advances, and Applications.

Authors: Mienye, Ibomoiye Domor Swart, Theo G.

Source: Information; Dec2024, Vol. 15 Issue 12, p755, 45p

Subject Terms: REINFORCEMENT learning, GRAPH neural networks, DEEP reinforcement learning, TRANSFORMER models, MOLECULAR biology, DEEP learning

Event generation and statistical sampling for physics with deep generative models and a density information buffer.

Authors: Otten, Sydney Caron, Sascha de Swart, Wieske et al.

Source: Nature Communications; 5/20/2021, Vol. 12 Issue 1, p1-16, 16p

Subject Terms: MONTE Carlo method, STATISTICAL physics, STATISTICAL sampling, QUANTUM field theory, INFORMATION modeling, PARTICLE physics, PROBABILISTIC generative models, PHASE space

A Machine Learning Method with Hybrid Feature Selection for Improved Credit Card Fraud Detection.

Authors: Mienye, Ibomoiye Domor Sun, Yanxia

Source: Applied Sciences (2076-3417); Jun2023, Vol. 13 Issue 12, p7254, 17p

Subject Terms: CREDIT card fraud, MACHINE learning, FRAUD investigation, BLENDED learning, ELECTRONIC funds transfers, FEATURE selection

Load Frequency Control Based on the Bees Algorithm for the Great Britain Power System.

Authors: Shouran, Mokhtar Anayi, Fatih Packianather, Michael et al.

Source: Designs; Sep2021, Vol. 5 Issue 3, p1-28, 28p

Subject Terms: BEES algorithm, MATHEMATICAL optimization, POWER system simulation, FUZZY logic, PARTICLE swarm optimization

Machine and Deep Learning in Agricultural Engineering: A Comprehensive Survey and Meta-Analysis of Techniques, Applications, and Challenges.

Authors: Frimpong, Samuel Akwasi Han, Mu Zheng, Wenyi et al.

Source: Computers (2073-431X); Oct2025, Vol. 14 Issue 10, p438, 33p

Subject Terms: MACHINE learning, DEEP learning, ENVIRONMENTAL monitoring, PRECISION farming, FOOD production, PRODUCT quality, AUTOMATION, AGRICULTURAL engineering