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Application of Evolutionary Algorithm for Assisted History Matching
Published 2014“…In this project, we will define and discuss the application of evolutionary algorithm in assisted history matching. …”
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Final Year Project -
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Evolutionary cost cognizant regression test prioritization for object-oriented programs based on fault dependency
Published 2018“…Furthermore, they did not consider incorporating evolution process such as applying genetic algorithms to their technique. In this work, we proposed an evolutionary cost-cognizant regression testing approach that prioritizes test case according to the rate of severity detection of test cases connected with dependent faults using genetic algorithms. …”
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Optimisation model for scheduling MapReduce jobs in big data processing / Ibrahim Abaker Targio Hashem
Published 2017“…The multi-objective approaches which are, Sorting Genetic Algorithm II (NSGA-II) and Strength Pareto Evolutionary Algorithm II (SPEA2) are applied to find the Pareto front of the Makespan and total cost. …”
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Thesis -
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Hybrid evolutionary-dolphin echolocation programming for sizing optimization of stand-alone photovoltaic systems / Zulkifli Othman
Published 2021“…Subsequently, the CI-based sizing algorithm, known as Evolutionary-Dolphin Echolocation Programming Sizing Algorithm (EDEPSA) is formulated to determine the optimal models of each system component such that either Performance Ratio (PR) or Levelized Cost of Electricity (LCOE) of the system is optimized. …”
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Thesis -
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Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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Undergraduates Project Papers -
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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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An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming
Published 2018“…Basically,one important issue in the power system network is to provide the optimal Economic Load Dispatch (ELD) solution in order to guarantee the sustainable consumer load demand.However,today ELD solution is essential to include together with the environmental aspect and known as Environmental Economic Load Dispatch (EELD).For that reason, many researchers continue in the development of new simulation tool specifically to overcome the EELD problems.Therefore,this study prepared an improved hybrid metaheuristic technique named as New Meta Heuristic Evolutionary Programming (NMEP) to provide the best possible solution in solving the identified single objective and multi objective functions for EELD solution.This new technique a merging cloning strategy that involved in an Artificial Immune System (AIS) algorithm into algorithm of Meta Heuristic Evolutionary Programming (Meta-EP).The development of NMEP technique is to minimize total cost,reduce the total emission during generator operation through the common formula in EELD and lowest total system loss.Besides that,all mentioned objective functions were also optimized together simultaneously that formulated using the weighted sum method before had been executed on the multi objective NMEP or called MONMEP.Both individual and multi objective NMEP techniques performance were verified among other two common heuristic methods known as AIS and Meta-EP techniques.In addition,the best possible solution defined using the aggregate function method.Through this method,the selection of the best MOEELD solution became effortless as compared with MO individually that required compare two or more objective function in one time manually.Among those three optimization techniques the lowest total aggregate values mostly resulted via the NMEP technique.Based upon that,the proposed technique is proving as the outstanding method compared with Meta-EP and AIS techniques in solving the EELD problem for both standard IEEE 26 bus and 57 bus systems.…”
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Thesis -
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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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Thesis -
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Some metaheuristic algorithms for solving multiple cross-functional team selection problems
Published 2022“…The developed method also demonstrated the effectiveness of the multi-criteria decision-making process when compared with the multi-objective evolutionary algorithm (MOEA). …”
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Unit commitment in power system using multi-agent evolutionary programming incorporating priority listing optimisation technique / Muhammad Nazree Che Othman
Published 2013“…This research presents an approach to solve the UC problem using a newly developed Multi-agent Evolutionary Programming incorporating Priority Listing optimisation technique (MAEP-PL). …”
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Thesis -
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A random search based effective algorithm for pairwise test data generation
Published 2011“…This paper proposes an effective random search based pairwise test data generation algorithm named R2Way to optimize the number of test cases. …”
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Conference or Workshop Item -
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Operating a reservoir system based on the shark machine learning algorithm
Published 2018“…The performance of the SMLA was compared with the performance of the most widespread evolutionary algorithms, namely, the genetic algorithm (GA). …”
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Article -
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Scalable approach for mining association rules from structured XML data
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Conference or Workshop Item -
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EasyA: Easy and effective way to generate pairwise test data
Published 2013“…This paper proposes a matrix based calculation for pairwise test data generation algorithm named EasyA to optimize the number of test cases. …”
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Conference or Workshop Item -
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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Thesis -
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Forecast of Muslimah fashion trends in Caca's company / Muhammad Saifullah Mohd Taip
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Student Project -
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Thesis -
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