Search Results - (( development program selection algorithm ) OR ( java three detection algorithm ))
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A multi-filter feature selection in detecting distributed denial-of-service attack
Published 2019“…In addition, the proposed M2FS method is developed through WEKA API with Java Programming language using the IDE of Eclipse Java. …”
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Evolutionary cost-cognizant regression test case prioritization for object-oriented programs
Published 2019“…Afterward evolutionary algorithm (EA) was employed to prioritize test cases based on the rate severity of fault detection per unit test cost. …”
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Real-Time Video Processing Using Native Programming on Android Platform
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Detection and extraction features for signatures images via different techniques
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The results reveal that the proposed hybrid algorithm is capable of achieving classification accuracy values of (95.82 % and 97.68 %), detection rates values of (95.8 % and 99.3 %) and false alarm rates values of (0.083 % and 0.045 %) on both KDD CUP 99 and NSL KDD. …”
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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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Automated path testing using the negative selection algorithm
Published 2017“…The proposed algorithm has been applied to the most commonly used benchmarking program which is triangle classifier. …”
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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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Some metaheuristic algorithms for solving multiple cross-functional team selection problems
Published 2022“…We compared the developed algorithms with the MIQP-CPLEX solver on 500 programming contestants with 37 skills and several randomized distribution datasets. …”
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Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun
Published 2000“…In order to develop an intelligent agent, various programming techniques are used in achieving the property of self learning, information retrieval and searching algorithm. …”
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Development of dynamic programming algorithm for maintenance scheduling problem
Published 2020“…Using the dynamic programming algorithm developed, the model was also able to recalculate alternative schedules by replacing unavailable teams with other teams to avoid delays. …”
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Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus
Published 2003“…A systematic method for selecting the ANN's input variables was developed using Matlab Programming language.…”
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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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A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm
Published 2024“…Validation was conducted through three experiments involving four Java programs. The results demonstrated high effectiveness, with scores ranging from 93.91% to 99.51% on the scaled weighted average percentage of faults detected (APFD) metric. …”
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Global optimal analysis of variant genetic operations in solar tracking
Published 2023“…Genetic Algorithms (GAs), Evolution Strategies (ES), Evolutionary Programming (EP) and Genetic Programming (GP) are some of the best known types of Evolutionary Algorithm (EA)where it is a class of global search algorithms inspired by natural evolution. …”
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Parallel computation of maass cusp forms using mathematica
Published 2013“…Our parallel programme comprises of two important parts namely the pullback algorithm and also the Maass cusp form algorithm. The latter is developed using an adapted algorithm of Hejhal and Then which is based on implicit automorphy and finite Fourier series. …”
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