Results 1 to 10 of about 714,519 (262)
Genetic Drift in Genetic Algorithm Selection Schemes [PDF]
IEEE Transactions on Evolutionary Computation, 1999 A method for calculating genetic drift in terms of changing population fitness variance is presented. The method allows for an easy comparison of different selection schemes and exact analytical results are derived for traditional generational selection,
Prügel-Bennett, A., Rogers, A.
core +4 more sources
Comparison Study for Clonal Selection Algorithm and Genetic Algorithm [PDF]
International Journal of Computer Science & Information Technology
(IJCSIT) Vol 4, No 4, August 2012 pp 107-118, 2012 Two metaheuristic algorithms namely Artificial Immune Systems (AIS) and Genetic Algorithms are classified as computational systems inspired by theoretical immunology and genetics mechanisms. In this work we examine the comparative performances of two algorithms.
Sadik Ulker, Ezgi Deniz Ulker
arxiv +5 more sources
Anisotropic selection in cellular genetic algorithms [PDF]
Dans Proceedings of the 8th annual conference on Genetic and
evolutionary computation - Genetic And Evolutionary Computation Conference,
Seatle : \'Etats-Unis d'Am\'erique (2006), 2008 In this paper we introduce a new selection scheme in cellular genetic algorithms (cGAs). Anisotropic Selection (AS) promotes diversity and allows accurate control of the selective pressure. First we compare this new scheme with the classical rectangular grid shapes solution according to the selective pressure: we can obtain the same takeover time with ...
Simoncini, David +3 more
arxiv +6 more sources
Distributed Genetic Algorithm for Feature Selection [PDF]
arXivWe empirically show that process-based Parallelism speeds up the Genetic Algorithm (GA) for Feature Selection (FS) 2x to 25x, while additionally increasing the Machine Learning (ML) model performance on metrics such as F1-score, Accuracy, and Receiver Operating Characteristic Area Under the Curve (ROC-AUC).
Gordon, Cameron +3 more
arxiv +2 more sources
Mathematics, 2021 Since the discovery that machine learning can be used to effectively detect Android malware, many studies on machine learning-based malware detection techniques have been conducted.
Jaehyeong Lee +3 more
doaj +1 more source
Complexity, 2021 This article proposes an Analytic Hierarchy Process Dempster-Shafer (AHP-DS) and similarity-based network selection algorithm for the scenario of dynamic changes in user requirements and network environment; combines machine learning with network ...
Weiwei Xiao
doaj +1 more source
Hierarchical Mission Planning for Cleaning Photovoltaic Panels Based on Improved Genetic Algorithm
Shanghai Jiaotong Daxue xuebao, 2021 Aimed at the mission planning for cleaning photovoltaic panels in large-area photovoltaic plants with mobile cleaning robots, a district planning strategy is hereby proposed.
LI Cuiming, WANG Ning, ZHANG Chen
doaj +1 more source
Gab-SSDS: An AI-Based Similar Days Selection Method for Load Forecast
Frontiers in Energy Research, 2022 The important, while mostly underestimated, step in the process of short-term load forecasting–STLF is the selection of similar days. Similar days are identified based on numerous factors, such as weather, time, electricity prices, geographical ...
Zoran Janković +4 more
doaj +1 more source
Intelligent Feature Selection Methods: A Survey [PDF]
Engineering and Technology Journal, 2021 Consider feature selection is the main in intelligent algorithms and machine learning to select the subset of data to help acquire the optimal solution.
Noor Jameel, Hasanen S. Abdullah
doaj +1 more source
Hybrid genetic algorithm for dual selection [PDF]
Pattern Analysis and Applications, 2007 Ce travail présente un algorithme génétique hybride pour résoudre le problème suivant : sélectionner dans une base d'exemples le sous ensemble qui présente la meilleure performance en classification avec le plus petit nombre d'attributs pour le plus grand nombre d'exemples.
Ros, F. +3 more
openaire +4 more sources