Search Results - (( program selection based algorithm ) OR ( java application matching algorithm ))
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…EACO selects the resources based on the pheromone value on each resource which is recorded in a matrix form. …”
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Multi-floor indoor location estimation system based on wireless local area network
Published 2007“…The most probable match is selected and returned as estimated location based on Bayesian filtering algorithm. …”
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Case Slicing Technique for Feature Selection
Published 2004“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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Software regression test case prioritization for object-oriented programs using genetic algorithm with reduced-fitness severity
Published 2015“…And even though several of the code based addresses procedural programs. Some researchers addressed the issue of test case prioritization using Genetic Algorithm, but the authors do not select modification-revealing before prioritization and used the same fault severity. …”
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A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm
Published 2014“…The approach is based on optimization of selected test case from test suite T. …”
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Model structure selection for a discrete-time non-linear system using genetic algorithm
Published 2004“…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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Message based random variable length key encryption algorithm.
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Securing cloud data system (SCDS) for key exposure using AES algorithm
Published 2021“…The AES algorithm has its own structure to encrypt and decrypt sensitive data that make the attackers difficult to get the real data when encrypting by AES algorithm. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun
Published 2000“…Whereas the process of examining through the web pages, retrieving and searching the relevant data in a liTML page, and selecting the best satisfying data are based on the features and operations of the Genetic Algorithms.…”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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