Search Results - (( developing a models algorithm ) OR ( java optimization techniques algorithm ))
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…Recently, various techniques based on different algorithms have been developed. …”
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An enhancement of multi-factor weighted approach technique in prioritizing test cases by comparing similarity distance
Published 2025“…Software testing is one of the most critical phases in the software development life cycle model (SDLC), where the quality of a software product is evaluated. …”
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Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT
Published 2006“…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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Evolutionary cost-cognizant regression test case prioritization for object-oriented programs
Published 2019“…The recent trend of software development uses OO paradigm. Therefore, this study proposed a cost-cognizant TCP approach for object-oriented software that uses path-based integration testing to identify the possible execution path extracted from the Java System Dependence Graph (JSDG) model of the source code using forward slicing technique. …”
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Hybrid genetic algorithm for improving fault localization
Published 2018“…Genetic algorithm (GA) is well known in finding an optimal solution to a problem while local search is capable of removing duplication. …”
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Examination timetabling using genetic algorithm case study: KUiTTHO
Published 2005“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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Scalable approach for mining association rules from structured XML data
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Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO
Published 2005“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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Improving Class Timetabling using Genetic Algorithm
Published 2006“…We have targeted the research on class timetabling problem. Hence, Genetic Algorithm (GA) is used as one of the most popular optimization solutions. …”
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Model structure selection for a discrete-time non-linear system using genetic algorithm
Published 2004“…First the effect of different combinations of GA operators on the performance of the model developed is studied. A proposed algorithm called modified GA, or MGA, is presented and a comparison between a simple GA and a modified GA is carried out. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…First the effect of different combinations of GA operators on the performance of the model developed is studied. A proposed algorithm called modified GA, or MGA, is presented and a comparison between a simple GA and a modified GA is carried out. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…First the effect of different combinations of GA operators on the performance of the model developed is studied. A proposed algorithm called modified GA, or MGA, is presented and a comparison between a simple GA and a modified GA is carried out. …”
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Hybrid DE-PEM algorithm for identification of UAV helicopter
Published 2014“…Purpose – The purpose of this paper is to develop a hybrid algorithm using differential evolution (DE) and prediction error modeling (PEM) for identification of small-scale autonomous helicopter state-space model. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…First the effect of different combinations of GA operators on the performance of the model developed is studied. A proposed algorithm called modified GA, or MGA, is presented and a comparison between a simple GA and a modified GA is carried out. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
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