Search Results - (( development program selection algorithm ) OR ( based based optimization algorithm ))
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Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan
Published 2018“…This study presents the development of Dolphin Echolocation Algorithm (DEA)-based sizing algorithm for sizing optimization of large-scale GCPV systems. …”
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2
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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3
Firefly algorithm for optimal sizing of Standalone Photovoltaic System / Nurizzati Abdul Aziz
Published 2016“…This study presents the development of Firefly Algorithm-based Sizing Algorithm, known as FASA for sizing optimization of SAPV systems. …”
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4
Firefly algorithm for optimal sizing of stand-alone photovoltaic system / Nur Izzati Abdul Aziz
Published 2016“…This study presents the development of firefly algorithm-based sizing algorithm, known as FASA for sizing optimization of SAPV systems. …”
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Successor selection for Ant Colony Optimization technique algorithm / Muhammad Iskandar Isman
Published 2017“…ACO algorithm is the best solution because it included the optimization technique to optimized the result based on the data criteria needs. …”
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6
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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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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8
Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization. …”
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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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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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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…In general, genetic based clustering algorithms showed the ability to reach near global optimal solution. …”
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13
Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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Prediction of UPSR Result using clonal selection algorithm (PUR) / Muhammed Khaleeq Shafii
Published 2012“…This would give a brief overview on which techniques or algorithms give better optimization and faster results in generating Prediction of UPSR result. …”
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Optimization of milling parameters using ant colony optimization
Published 2008“…This study is to develop optimization procedures based on the Ant Colony Optimization (ACO). …”
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Undergraduates Project Papers -
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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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Traditional marble game using ant colony optimization / Muhammad Izzat Imran Che Isa
Published 2017“…In future, traditional marble game can be applied with other search algorithm to optimize the solution…”
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18
Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty
Published 2024“…Further more, an improved non-dominated sorting genetic algorithm with an elite strategy II (IMNSGA-II) has been developed to solve the two bi-objective models, surpassing existing literature’s algorithms such as Pareto Envelope-based Selection Algorithm II (PESA-II) and NSGA-II. …”
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19
An Efficient Genetic Algorithm for Large Scale Vehicle Routing Problem Subject to Precedence Constraints
Published 2015“…Therefore, metaheuristic method based genetic algorithm has been developed to obtain feasible and optimal solution with less computation time. …”
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Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil
Published 2024“…The proposed approach utilizes genetic algorithms to dynamically produce optimized timetables based on individual student needs, with real-time data scraping from 'iCRESS' ensuring the system stays up to date with the latest course information for accurate timetable generation. …”
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