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Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line
Published 2010“…A heuristic algorithm was introduced to generate the initial population for intelligence based genetic algorithm. …”
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Hybrid bat algorithm for minimum dominating set problem
Published 2017“…In this paper, the stochastic search represented by hybrid swarm intelligence algorithm to find the smallest set of nodes that dominate the graph. …”
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A coevolutionary multiobjective evolutionary algorithm for game artificial intelligence
Published 2013“…Recently, the growth of Artificial Intelligence (AI) has provided a set of effective techniques for designing computer-based controllers to perform various tasks autonomously in game area, specifically to produce intelligent optimal game controllers for playing video and computer games. …”
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Time series data intelligent clustering algorithm for landslide displacement prediction
Published 2018“…To address this problem, an intelligent clustering algorithm for time series data in landslide displacement prediction based on nonlinear dynamic time bending is proposed in this paper. …”
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Active intelligent control of vibration of flexible plate structures
Published 2011“…In this work active intelligent control comprises a set of control techniques based on particle swarm optimisation (PSO), real coded genetic algorithm (RCGA) and artificial immune system (AIS). …”
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A coevolutionary multiobjective evolutionary algorithm for game artificial intelligence
Published 2013“…Recently, the growth of Artificial Intelligence (AI) has provided a set of effective techniques for designing computer-based controllers to perform various tasks autonomously in game area, specifically to produce intelligent optimal game controllers for playing video and computer games. …”
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Solving the minimum dominating set problem of partitioned graphs using a hybrid bat algorithm
Published 2020“…This paper investigates the swarm intelligence behaviour represented by a population-based approach called the bat algorithm (BA) to find the smallest set of nodes that dominate the graph. …”
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Discovering decision algorithm of distance protective relay based on rough set theory and rule quality measure
Published 2011“…The discovered decision algorithm and association rule from the Rough-Set based data mining had been compared with and successfully validated by those discovered using the benchmarking Decision-Tree based data mining strategy. …”
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Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems
Published 2024“…The IWD is a recent metaheuristic population-based algorithm belonging to the swarm intelligent category which simulates the dynamic of the river systems. …”
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E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm
Published 2022“…The model design is Decision Tree (DT) algorithm-based, with an approach to data balancing since the data set used is highly unbalanced and one more approach for feature selection. …”
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Automatic Initialization Of Contour For Level Set Algorithms Guided By Integration Of Multiple Views To Segment Abdominal CT Scans
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Vision Based Multi Sensor Feedback System For Robot System With Intelligent
Published 2009“…The feedback system also feeds the Artificial Intelligent program necessary information to make the right decision, which is based on rules of a popular game, Tic-Tac-Toe. …”
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Intelligent sizing and output prediction techniques for grid-connected photovoltaic system / Shahril Irwan Sulaiman
Published 2012“…Initially, two intuitive-based sizing algorithms for GCPV system design, termed as Conventional Sizing Algorithm (CSA), were developed based on two design goals. …”
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Nature-inspired parameter controllers for ACO-based reactive search
Published 2015“…This study proposes machine learning strategies to control the parameter adaptation in ant colony optimization algorithm, the prominent swarm intelligence metaheuristic.The sensitivity to parameters’ selection is one of the main limitations within the swarm intelligence algorithms when solving combinatorial problems.These parameters are often tuned manually by algorithm experts to a set that seems to work well for the problem under study, a standard set from the literature or using off-line parameter tuning procedures. …”
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