Výsledky vyhledávání - Application of Genetic Programming in Machine Learning

Adaptive load consumption modelling on the user side: contributions to load forecasting modelling based on supervised mixture of experts and genetic programming

Autoři: Giacometto Torres, Francisco Javier

Přispěvatelé: University/Department: Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica

Thesis Advisors: Romeral Martínez, José Luis

Zdroj: TDX (Tesis Doctorals en Xarxa)

Témata: Energy management, Machine learning, Knowledge discovery algorithms, Short time load forecasting, Ensemble learning, Àrees temàtiques de la UPC::Enginyeria electrònica

Time: 621.3

Popis souboru: application/pdf

Přístupová URL adresa: http://hdl.handle.net/10803/457631
https://dx.doi.org/10.5821/dissertation-2117-111507

Automatic Design of Metaheuristics for Practical Engineering Applications

Autoři: Daniel F. Zambrano-Gutierrez Jorge M. Cruz–Duarte Juan Gabriel Avina–Cervantes a další

Zdroj: IEEE Access, Vol 11, Pp 7262-7276 (2023)

Témata: Artificial intelligence, Metaheuristic, Heuristic, Metaheuristics, 02 engineering and technology, Parallel metaheuristic, control theory, Engineering, Context (archaeology), Artificial Intelligence, Machine learning, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Heuristics, Swarm Intelligence Optimization Algorithms, Optimization problem, Constraint Handling, Biology, fractional model design, Analysis and Design of Fractional Order Control Systems, hyper-heuristics, Global Optimization, Particle swarm optimization, Meta-optimization, Optimization Applications, Mathematical optimization, Cuckoo search, Paleontology, PID controllers, Computer science, TK1-9971, Algorithm, Control and Systems Engineering, Application of Genetic Programming in Machine Learning, Computer Science, Physical Sciences, Nature-Inspired Algorithms, Electrical engineering. Electronics. Nuclear engineering, artificial neural networks, Mathematics

Přístupová URL adresa: https://doaj.org/article/a6de439d2e23406886c939ff4e7837d6

Adaptive Endpoints Selection with Application in Rare Disease

Autoři: Huan Xu Yi Liu Robert A. Beckman

Zdroj: Statistics in Biopharmaceutical Research. 16:55-63

Témata: Artificial intelligence, Evolutionary biology, Computer science, 01 natural sciences, 3. Good health, Computational biology, 03 medical and health sciences, Selection (genetic algorithm), 0302 clinical medicine, Artificial Intelligence, Application of Genetic Programming in Machine Learning, Computer Science, Physical Sciences, Medicine, Disease, 0101 mathematics, Rare disease, Internal medicine, Biology

Application of genetic programming in electrokinetic treatment of soil and COPR: Focus on Cr(VI) fractionation.

Autoři: Yu, Qiu Zheng, Yi Jiang, Zhao a další

Zdroj: Journal of Environmental Chemical Engineering. Apr2025, Vol. 13 Issue 2, pN.PAG-N.PAG. 1p.

Témata: Genetic programming, Artificial intelligence, Waste management, Solid waste, Soil pollution, Deep learning, Hexavalent chromium

Computable model discovery and high-level-programming approximations to algorithmic complexity

Autoři: V. Lemus Eduardo Acuña-Yeomans V. Zamora a další

Zdroj: Theoretical Computer Science. 927:31-41

Témata: FOS: Computer and information sciences, Computer Science - Logic in Computer Science, Artificial intelligence, Generative grammar, Computer Science - Information Theory, 0102 computer and information sciences, 02 engineering and technology, 01 natural sciences, Turing machine, Computational Complexity and Algorithmic Information Theory, Causal Discovery, Theoretical computer science, Artificial Intelligence, Theory and Applications of Cellular Automata, 0202 electrical engineering, electronic engineering, information engineering, Universal Turing machine, Computability, Information Theory (cs.IT), Complex Systems, Computer science, Logic in Computer Science (cs.LO), Programming language, Computational Theory and Mathematics, Application of Genetic Programming in Machine Learning, Computer Science, Physical Sciences, Computation, Computational Depth

Přístupová URL adresa: http://arxiv.org/abs/2112.12197

Multi-objective genetic programming strategies for topic-based search with a focus on diversity and global recall

Autoři: Cecilia Baggio Carlos M. Lorenzetti Rocío L. Cecchini a další

Zdroj: PeerJ Comput Sci
PeerJ Computer Science, Vol 9, p e1710 (2023)
CONICET Digital (CONICET)
Consejo Nacional de Investigaciones Científicas y Técnicas

Témata: Artificial intelligence, LEARNING COMPLEX QUERIES, Topic-based search, Genetic Programming, Weighting, Genetic programming, Selection (genetic algorithm), Similarity (geometry), Diversity preservation, Multi-Objective Optimization, Physics, GLOBAL RECALL, INFORMATION RETRIEVAL, Global recall, FOS: Philosophy, ethics and religion, Multi-objective genetic programming, Computational Theory and Mathematics, Application of Genetic Programming in Machine Learning, Physical Sciences, Medicine, DIVERSITY PRESERVATION, Radiology, Quantum mechanics, Semantic Genetic Programming, Artificial Intelligence, Automatic query formulation, Machine learning, Image (mathematics), Entropy (arrow of time), Information retrieval, Swarm Intelligence Optimization Algorithms, Data mining, TOPIC-BASED SEARCH, Precision and recall, Global Optimization, MULTI-OBJECTIVE GENETIC PROGRAMMING, Linguistics, QA75.5-76.95, Computer science, INFORMATION-THEORETIC FITNESS FUNCTIONS, Philosophy, AUTOMATIC QUERY FORMULATION, Electronic computers. Computer science, Computer Science, Nature-Inspired Algorithms, FOS: Languages and literature, Recall, DIVERSITY MAXIMIZATION, Multiobjective Optimization in Evolutionary Algorithms

Popis souboru: application/pdf

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/38077536
https://doaj.org/article/4e58ef5525c3417f88c2978ff2f09b9a
http://hdl.handle.net/11336/225085

Application of genetic programming for proton-proton interactions

Autoři: El-Sayed A. El-Dahshan

Zdroj: Open Physics, Vol 9, Iss 3, Pp 874-883 (2011)

Témata: multiplicity distribution, machine learning, Physics, QC1-999, 0103 physical sciences, modeling, genetic programming, 01 natural sciences, proton-proton interaction

Přístupová URL adresa: https://doaj.org/article/c55c85c0138444768cb955a44ed45028
https://ui.adsabs.harvard.edu/abs/2011CEJPh...9..874E/abstract
https://www.degruyter.com/view/j/phys.2011.9.issue-3/s11534-010-0088-7/s11534-010-0088-7.xml
http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.-psjd-doi-10_2478_s11534-010-0088-7
https://link.springer.com/article/10.2478/s11534-010-0088-7
https://link.springer.com/content/pdf/10.2478%2Fs11534-010-0088-7.pdf

Investigating boosting techniques’ efficacy in feature selection: A comparative analysis

Autoři: Ubaid Ahmed Anzar Mahmood Majid Ali Tunio a další

Zdroj: Energy Reports. 11:3521-3532

Témata: Artificial intelligence, Electricity Price and Load Forecasting Methods, 4. Education, Load Forecasting, Boosting (machine learning), 15. Life on land, Pattern recognition (psychology), Computer science, 7. Clean energy, Engineering, Selection (genetic algorithm), Artificial Intelligence, 13. Climate action, Application of Genetic Programming in Machine Learning, Computer Science, Physical Sciences, Feature selection, Machine learning, FOS: Electrical engineering, electronic engineering, information engineering, Machine Learning Methods for Solar Radiation Forecasting, Electrical and Electronic Engineering, Feature Selection, Short-Term Forecasting, Probabilistic Forecasting, Forecasting

Medical Data Classification Using Genetic Programming: A Systematic Literature Review.

Autoři: Maurya, Pratibha Kushwaha, Arati Prakash, Om

Zdroj: Expert Systems. Mar2025, Vol. 42 Issue 3, p1-21. 21p.

Témata: *ALGORITHMS, *EXPERTISE, MEDICAL coding, MACHINE learning, CLASSIFICATION

Deep Learning in Mining Biological Data

Autoři: Mufti Mahmud M. Shamim Kaiser TM McGinnity a další

Zdroj: Cognit Comput

Témata: Data Analysis, Artificial neural network, FOS: Computer and information sciences, Artificial intelligence, Bioinformatics, 02 engineering and technology, Article, Data science, FOS: Economics and business, Big data, Artificial Intelligence, Biochemistry, Genetics and Molecular Biology, Microarray Data Analysis and Gene Expression Profiling, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, Business, Molecular Biology, Data mining, Biology, Marketing, Prediction of Protein Subcellular Localization, Data type, Life Sciences, Deep learning, Computer science, Programming language, Biological data, Benchmarking, Application of Genetic Programming in Machine Learning, Computer Science, Physical Sciences

Popis souboru: application/pdf

Přístupová URL adresa: https://link.springer.com/content/pdf/10.1007/s12559-020-09773-x.pdf
https://pubmed.ncbi.nlm.nih.gov/33425045
https://irep.ntu.ac.uk/id/eprint/41954/1/1382810_Mahmud.pdf
https://pubmed.ncbi.nlm.nih.gov/33425045/
https://ulster-staging.pure.elsevier.com/en/publications/deep-learning-in-mining-biological-data
https://link.springer.com/content/pdf/10.1007/s12559-020-09773-x.pdf
https://www.scilit.net/article/23100583bf52ad3d713cf904d26bd282?action=show-references
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7783296
https://dblp.uni-trier.de/db/journals/corr/corr2003.html#abs-2003-00108

IHHO: an improved Harris Hawks optimization algorithm for solving engineering problems

Autoři: Dalia T. Akl Mahmoud M. Saafan Amira Y. Haikal a další

Zdroj: Neural Computing and Applications. 36:12185-12298

Témata: 0209 industrial biotechnology, Bayesian Optimization, Multi-Objective Optimization, 4. Education, Optimization Applications, Mathematical optimization, 02 engineering and technology, Metaheuristics, 15. Life on land, Computer science, 7. Clean energy, Algorithm, Optimization algorithm, Computational Theory and Mathematics, Artificial Intelligence, Application of Genetic Programming in Machine Learning, Computer Science, Physical Sciences, 0202 electrical engineering, electronic engineering, information engineering, FOS: Mathematics, 14. Life underwater, Swarm Intelligence Optimization Algorithms, Multiobjective Optimization in Evolutionary Algorithms, Constraint Handling, Mathematics

Assessing opportunities of SYCL for biological sequence alignment on GPU-based systems

Autoři: Manuel Costanzo Enzo Rucci Carlos García a další

Přispěvatelé: Manuel Costanzo Enzo Rucci Carlos García a další

Zdroj: Docta Complutense
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Témata: Parallel computing, Programmer, 0301 basic medicine, FOS: Computer and information sciences, Bioinformatics, 0206 medical engineering, GPU, CUDA, 02 engineering and technology, 03 medical and health sciences, Sequence alignment, Artificial Intelligence, Biochemistry, Genetics and Molecular Biology, 1203.17 Informática, RNA Sequencing Data Analysis, Molecular Biology, SYCL, 0303 health sciences, Computer Science - Programming Languages, Prediction of Protein Subcellular Localization, oneAPI, Protein, Life Sciences, DNA, Computer science, Programming language, 3. Good health, Computer Science - Distributed, Parallel, and Cluster Computing, Ciencias, Application of Genetic Programming in Machine Learning, Implementation, SYCLomatic, Computer Science, Physical Sciences, sequence alignment, Distributed, Parallel, and Cluster Computing (cs.DC), Software portability, Programming Languages (cs.PL)

Popis souboru: application/pdf

Přístupová URL adresa: http://arxiv.org/abs/2211.10769
https://hdl.handle.net/20.500.14352/113792

Demographic inference in complex populations: the North African case

Autoři: Serradell Noguera, Jose Miguel

Přispěvatelé: University/Department: Universitat Pompeu Fabra. Departament de Medicina i Ciències de la Vida

Thesis Advisors: Comas, David, Lao Grueso, Oscar

Zdroj: TDX (Tesis Doctorals en Xarxa)

Témata: Human population genetics, North Africa, Demographic history, Deep-learning, Genetic programming, Genomas completos, Inteligencia Artificial, Inferencia demografica, Norte de Africa, Génetica de poblaciones

Popis souboru: application/pdf

Přístupová URL adresa: http://hdl.handle.net/10803/690463

Optimizing neural network algorithms for submerged membrane bioreactor: A comparative study of OVAT and RSM hyperparameter optimization techniques

Autoři: Syahira Ibrahim Norhaliza Abdul Wahab

Zdroj: Water Science and Technology, Vol 89, Iss 7, Pp 1701-1724 (2024)

Témata: Artificial neural network, Artificial intelligence, Hyperparameter Optimization, neural network, Bioreactor, 02 engineering and technology, doe implementation, Environmental technology. Sanitary engineering, 01 natural sciences, Learning with Noisy Labels in Machine Learning, Bioreactors, Engineering, Response surface methodology, Artificial Intelligence, Machine learning, FOS: Mathematics, Computer Simulation, Swarm Intelligence Optimization Algorithms, Biology, TD1-1066, 0105 earth and related environmental sciences, Hyperparameter, Multi-Objective Optimization, computational time, submerged membrane bioreactor data, Optimization Applications, Botany, optimization techniques, Computer science, Ant Colony Optimization, 6. Clean water, Biochemical engineering, Particle Swarm Optimization, Application of Genetic Programming in Machine Learning, Computer Science, Physical Sciences, Neural Networks, Computer, 0210 nano-technology, Algorithms, Mathematics

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/38619898
https://doaj.org/article/c8bb7ab8ab2345c4b2debbad56d53d08

Demo Application for the AutoGOAL Framework

Autoři: Suilán Estévez-Velarde Alejandro Piad-Morffis Yoan Gutiérrez a další

Přispěvatelé: Suilán Estévez-Velarde Alejandro Piad-Morffis Yoan Gutiérrez a další

Zdroj: RUA. Repositorio Institucional de la Universidad de Alicante
Universidad de Alicante (UA)

Témata: Software engineering, 02 engineering and technology, Computer science, Learning with Noisy Labels in Machine Learning, Artificial Intelligence, Application of Genetic Programming in Machine Learning, Meta-Learning, Machine learning, Lenguajes y Sistemas Informáticos, Computer Science, Physical Sciences, 0202 electrical engineering, electronic engineering, information engineering, AutoGOAL framework, Active Learning in Machine Learning Research, Natural Language Processing

Přístupová URL adresa: https://www.aclweb.org/anthology/2020.coling-demos.4.pdf
http://hdl.handle.net/10045/110741
https://dblp.uni-trier.de/db/conf/coling/coling2020d.html#Estevez-Velarde20a
http://rua.ua.es/dspace/bitstream/10045/110741/1/2020.coling-demos.4.pdf
https://www.aclweb.org/anthology/2020.coling-demos.4/
https://aclanthology.org/2020.coling-demos.4/
http://rua.ua.es/dspace/handle/10045/110741
https://hdl.handle.net/10045/110741

A Novel Binary Seagull Optimizer and its Application to Feature Selection Problem

Autoři: Vijay Kumar Dinesh Kumar Manjit Kaur a další

Zdroj: IEEE Access, Vol 9, Pp 103481-103496 (2021)

Témata: Artificial intelligence, Computer Networks and Communications, Metaheuristic, 02 engineering and technology, exploration, feature selection, Artificial Intelligence, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Distributed Coordination in Online Robotics Research, Swarm Intelligence Optimization Algorithms, Optimization problem, Seagull algorithm, Global Optimization, Arithmetic, Geography, Multi-swarm optimization, Optimization Applications, Mathematical optimization, Online Algorithms, nature-inspired algorithms, Computer science, Search algorithm, TK1-9971, Algorithm, Particle Swarm Optimization, Application of Genetic Programming in Machine Learning, Continuous optimization, Computer Science, Physical Sciences, Nature-Inspired Algorithms, discrete optimization, Electrical engineering. Electronics. Nuclear engineering, Binary search algorithm, Benchmark (surveying), Binary number, Mathematics, Geodesy

Přístupová URL adresa: https://ieeexplore.ieee.org/ielx7/6287639/6514899/09491083.pdf
https://doaj.org/article/760e68bd496741579707583356c5c093
https://dblp.uni-trier.de/db/journals/access/access9.html#KumarKKSIA21
https://ieeexplore.ieee.org/document/9491083/
https://doi.org/10.1109/ACCESS.2021.3098642
https://doaj.org/article/760e68bd496741579707583356c5c093

Population Dynamics in Genetic Programming for Dynamic Symbolic Regression.

Autoři: Fleck, Philipp Werth, Bernhard Affenzeller, Michael

Zdroj: Applied Sciences (2076-3417); Jan2024, Vol. 14 Issue 2, p596, 24p

Témata: GENETIC programming, POPULATION dynamics, MACHINE learning, EVOLUTIONARY algorithms, DYNAMIC programming, GENETIC algorithms, WILDLIFE reintroduction

Geografický termín: ALPS

An efficient adaptive-mutated Coati optimization algorithm for feature selection and global optimization

Autoři: Fatma A. Hashim Essam H. Houssein Reham R. Mostafa a další

Zdroj: Alexandria Engineering Journal, Vol 85, Iss, Pp 29-48 (2023)

Témata: Feature selection, Coati optimization algorithm, Optimization problems, Optimization, Artificial intelligence, Beräkningsmatematik, Biomedical Engineering, Metaheuristic, Operator (biology), FOS: Medical engineering, Biochemistry, Gene, 7. Clean energy, Engineering, Artificial Intelligence, Evolutionary algorithm, Machine learning, Artificial Immune Systems in Science and Engineering, FOS: Mathematics, 14. Life underwater, Swarm Intelligence Optimization Algorithms, Feature Selection, Optimization problem, Global Optimization, Multi-Objective Optimization, Particle swarm optimization, Optimization Applications, Mathematical optimization, Test suite, 15. Life on land, Engineering (General). Civil engineering (General), Computer science, Algorithm, Computational Mathematics, Chemistry, Application of Genetic Programming in Machine Learning, Computer Science, Physical Sciences, Repressor, TA1-2040, Test case, Transcription factor, Regression analysis, Mathematics

Popis souboru: application/pdf

Přístupová URL adresa: https://doaj.org/article/d906edae9d5447ee902c25afa6508348
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-200389

A novel reinforcement learning-based reptile search algorithm for solving optimization problems

Autoři: Mohamed Ghetas Mohamed Issa

Zdroj: Neural Computing and Applications. 36:533-568

Témata: Artificial intelligence, Population, 02 engineering and technology, Local optimum, Sociology, Artificial Intelligence, Reinforcement learning, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, FOS: Mathematics, 14. Life underwater, Swarm Intelligence Optimization Algorithms, Constraint Handling, Demography, Geography, 4. Education, Optimization Applications, Mathematical optimization, 15. Life on land, Computer science, Ant Colony Optimization, FOS: Sociology, Algorithm, Particle Swarm Optimization, Application of Genetic Programming in Machine Learning, Computer Science, Physical Sciences, Nature-Inspired Algorithms, Benchmark (surveying), Mathematics, Geodesy

Heap-Based Optimizer Algorithm with Chaotic Search for Nonlinear Programming Problem Global Solution

Autoři: Rizk M. Rizk‐Allah Islam M. Eldesoky Ekram A. Aboali a další

Zdroj: International Journal of Computational Intelligence Systems, Vol 16, Iss 1, Pp 1-21 (2023)

Témata: Optimization, Artificial intelligence, Chaotic, Robustness (evolution), Biomedical Engineering, 02 engineering and technology, FOS: Medical engineering, Heap-based optimizer algorithm, Biochemistry, Quantum mechanics, Gene, Engineering, Artificial Intelligence, Nonlinear programming, 0202 electrical engineering, electronic engineering, information engineering, Artificial Immune Systems in Science and Engineering, FOS: Mathematics, Swarm Intelligence Optimization Algorithms, Optimization problem, Constraint Handling, Global Optimization, Geography, Physics, Optimization Applications, Mathematical optimization, QA75.5-76.95, Computer science, Algorithm, Chemistry, Electronic computers. Computer science, Application of Genetic Programming in Machine Learning, Chaotic search, Computer Science, Physical Sciences, Nature-Inspired Algorithms, Heap (data structure), Nonlinear system, Global optimization, Benchmark (surveying), Mathematics, Geodesy

Přístupová URL adresa: https://doaj.org/article/e741eb39fd9a4b2f8c8b25711d4bf967