Search Results - "Population based incremental learning algorithms"

Application of various population based incremental learning algorithms to different optimization problems

Authors: Yörük, Elif Baykasoğlu, Adil

Access URL: https://avesis.deu.edu.tr/publication/details/fb44128d-0737-41e4-8a5a-2869478980d8/oai

Control of dead-time systems using derivative free local search guided population based incremental learning algorithms

Authors: Kanthaswamy Ganapathy Jovitha Jerome

Source: Optimization and Engineering. 15:331-354

Subject Terms: 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 16. Peace & justice

Access URL: https://link.springer.com/article/10.1007/s11081-012-9194-2/fulltext.html
https://link.springer.com/article/10.1007%2Fs11081-012-9194-2

Experimental study on population-based incremental learning algorithms for dynamic optimization problems

Authors: Yang, Shengxiang Yao, X.

Source: Soft Computing. 9:815-834

Subject Terms: Population-based incremental learning, Dual population-based incremental learning, Genetic algorithm, Exclusive-or operator, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, Central probability vector, Dynamic optimization problem

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Access URL: http://bura.brunel.ac.uk/bitstream/2438/5987/3/Fulltext.pdf
https://dblp.uni-trier.de/db/journals/soco/soco9.html#YangY05
https://dora.dmu.ac.uk/handle/2086/13442?show=full
https://bura.brunel.ac.uk/handle/2438/5987
https://doi.org/10.1007/s00500-004-0422-3
https://dl.acm.org/doi/10.1007/s00500-004-0422-3
https://link.springer.com/article/10.1007/s00500-004-0422-3/fulltext.html
http://bura.brunel.ac.uk/handle/2438/5987

Experimental study on population-based incremental learning algorithms for dynamic optimization problems

Authors: Shengxiang Yang Xin Yao The Pennsylvania State University CiteSeerX Archives

Contributors: Shengxiang Yang Xin Yao The Pennsylvania State University CiteSeerX Archives

Source: http://bura.brunel.ac.uk/bitstream/2438/5987/3/Fulltext.pdf.

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Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.368.6600; http://bura.brunel.ac.uk/bitstream/2438/5987/3/Fulltext.pdf

Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.368.6600
http://bura.brunel.ac.uk/bitstream/2438/5987/3/Fulltext.pdf

Design of Sensor Networks for Chemical Plants Based on Meta-Heuristics

Authors: Carnero, Mercedes del Carmen Hernandez, Jose Luis Sanchez, Mabel Cristina

Source: Algorithms, Vol 2, Iss 1, Pp 259-281 (2009)
Algorithms
Volume 2
Issue 1
Pages 259-281
CONICET Digital (CONICET)
Consejo Nacional de Investigaciones Científicas y Técnicas

Subject Terms: Industrial engineering. Management engineering, Stochastic optimization, 0211 other engineering and technologies, QA75.5-76.95, 02 engineering and technology, T55.4-60.8, Tabu search, SENSOR LOCATION, Population based incremental learning algorithms, Electronic computers. Computer science, Scatter search, SCATTER SEARCH, Sensor location, 0204 chemical engineering, TABU SEARCH, STOCHASTIC OPTIMIZATION

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Access URL: https://www.mdpi.com/1999-4893/2/1/259/pdf
https://doaj.org/article/cb6d522d11244d0b9499d7d6fe7669f8
https://www.mdpi.com/1999-4893/2/1/259/pdf
https://ri.conicet.gov.ar/handle/11336/42342
https://www.mdpi.com/1999-4893/2/1/259
https://notablesdelaciencia.conicet.gov.ar/handle/11336/42342
https://ri.conicet.gov.ar/bitstream/11336/42342/2/CONICET_Digital_Nro.2c3bf7dd-3f9e-4a6b-984c-33a304a6764e_A.pdf
https://dblp.uni-trier.de/db/journals/algorithms/algorithms2.html#CarneroHS09
http://hdl.handle.net/11336/42342

Control of dead-time systems using derivative free local search guided population based incremental learning algorithms.

Authors: Ganapathy, Kanthaswamy Jerome, Jovitha

Source: Optimization & Engineering; Jun2014, Vol. 15 Issue 2, p331-354, 24p

Experimental study on population-based incremental learning algorithms for dynamic optimization problems.

Authors: Shengxiang Yang Xin Yao

Source: Soft Computing - A Fusion of Foundations, Methodologies & Applications; Nov2005, Vol. 9 Issue 11, p815-834, 20p

Diabetes Development Prediction Using a Hybrid Model Combining Dendritic Artificial Neuron Model and Logistic Regression.

Authors: Ağraz, Melih Eğrioğlu, Erol Baş, Eren et al.

Source: Endocrinology Research & Practice; Apr2025, Vol. 29 Issue 2, p84-93, 10p

Subject Terms: DIAGNOSIS of diabetes, CHRONIC disease diagnosis, COST control, RANDOM forest algorithms, STATISTICAL models, DATABASES, MEDICAL information storage & retrieval systems, PREDICTION models, EARLY medical intervention, CLUSTER analysis (Statistics), RECEIVER operating characteristic curves, INSURANCE, BODY mass index, ADIPOSE tissues, ARTIFICIAL intelligence, LOGISTIC regression analysis, HEALTH insurance, GLUCOSE tolerance tests, GESTATIONAL diabetes, DIAGNOSTIC errors, INSULIN, AGE distribution, GENEALOGY, PARTICLE swarm optimization, BLOOD sugar, ARTIFICIAL neural networks, MACHINE learning, EARLY diagnosis, DECISION trees, FACTOR analysis, GENETIC techniques, PREDICTIVE validity, SENSITIVITY & specificity (Statistics), MEDICAL care costs, DENDRITIC cells, ALGORITHMS, PREVENTIVE health services, FORECASTING, EVALUATION

A survey on dynamic populations in bio-inspired algorithms.

Authors: Farinati, Davide Vanneschi, Leonardo

Source: Genetic Programming & Evolvable Machines; 7/24/2024, Vol. 25 Issue 2, p1-32, 32p

HYBRID OPTIMIZATION FOR HIGH ASPECT RATIO WINGS WITH CONVOLUTIONAL NEURAL NETWORKS AND SQUIRREL OPTIMIZATION ALGORITHM.

Authors: PENGFEI LI

Source: Scalable Computing: Practice & Experience; Jan2024, Vol. 25 Issue 1, p85-93, 9p

Subject Terms: OPTIMIZATION algorithms, CONVOLUTIONAL neural networks, BINARY codes, GENETIC algorithms

A review of task scheduling in cloud computing based on nature-inspired optimization algorithm.

Authors: Prity, Farida Siddiqi Gazi, Md. Hasan Uddin, K. M. Aslam

Source: Cluster Computing; Oct2023, Vol. 26 Issue 5, p3037-3067, 31p

Subject Terms: OPTIMIZATION algorithms, CLOUD computing, SCHEDULING, MATHEMATICAL optimization, PROBLEM solving

Chaotic Time-Series Prediction using Intelligent Methods.

Authors: Nezhadshahbodaghi, M. Bahmani, K. Mosavi, M. R. et al.

Source: Iranian Journal of Electrical & Electronic Engineering; Jun2023, Vol. 19 Issue 2, p1-12, 12p

Subject Terms: METAHEURISTIC algorithms, NEURAL circuitry, FUZZY systems, MACHINE learning, ALGORITHMS, EVOLUTIONARY algorithms, PARTICLE swarm optimization, ACCURACY, HEURISTIC

A Comparative Study between Haploid Genetic Algorithms and Diploid Genetic Algorithms.

Authors: PETROVAN, ADRIAN MATEI, OLIVIU POP, PETRICĂ C.

Source: Carpathian Journal of Mathematics; 2023, Vol. 39 Issue 2, p433-458, 26p

Subject Terms: RECESSIVE genes, DOMINANCE (Genetics), COMPARATIVE studies, CHROMOSOMES

Winsorized dendritic neuron model artificial neural network and a robust training algorithm with Tukey's biweight loss function based on particle swarm optimization.

Authors: Egrioglu, Erol Bas, Eren Karahasan, Ozlem

Source: Granular Computing; May2023, Vol. 8 Issue 3, p491-501, 11p

A hybrid multi-population framework for dynamic environments combining online and offline learning.

Authors: Uludağ, Gönül Kiraz, Berna Etaner-Uyar, A. Şima et al.

Source: Soft Computing - A Fusion of Foundations, Methodologies & Applications. Dec2013, Vol. 17 Issue 12, p2327-2348. 22p.

Subject Terms: *DISTANCE education, *MACHINE learning, *ALGORITHMS, *RANKING (Statistics), *HEURISTIC algorithms, *PROBLEM solving

Hybrid Optimization Based PID Controller Design for Unstable System.

Authors: Rajeshwaran, Saranya Kumar, C. Agees Ganapathy, Kanthaswamy

Source: Intelligent Automation & Soft Computing; 2023, Vol. 35 Issue 2, p1611-1625, 15p

Subject Terms: PID controllers, ANT algorithms, TIME delay systems, PARTICLE swarm optimization, METAHEURISTIC algorithms

A two stages prediction strategy for evolutionary dynamic multi-objective optimization.

Authors: Sun, Hao Ma, Xuemin Hu, Ziyu et al.

Source: Applied Intelligence; Jan2023, Vol. 53 Issue 1, p1115-1131, 17p

Subject Terms: SUPPORT vector machines, KALMAN filtering, FORECASTING, NONLINEAR equations

Evolutionary mating algorithm.

Authors: Sulaiman, Mohd Herwan Mustaffa, Zuriani Saari, Mohd Mawardi et al.

Source: Neural Computing & Applications; Jan2023, Vol. 35 Issue 1, p487-516, 30p

Subject Terms: EVOLUTIONARY algorithms, FLEXIBLE AC transmission systems, ELECTRICAL load, CONSTRAINED optimization

Triploid genetic algorithm for convolutional neural network–based diagnosis of mild cognitive impairment.

Authors: Bhasin, Harsh Agrawal, R. K.

Source: Alzheimer's & Dementia: The Journal of the Alzheimer's Association; Nov2022, Vol. 18 Issue 11, p2283-2291, 9p

Learning-based monarch butterfly optimization algorithm for solving numerical optimization problems.

Authors: Ghetas, Mohamed

Source: Neural Computing & Applications; Mar2022, Vol. 34 Issue 5, p3939-3957, 19p

Subject Terms: METAHEURISTIC algorithms, MATHEMATICAL optimization, PARTICLE swarm optimization, LEARNING strategies, PROBLEM solving, STANDARD deviations