Search Results - (( developing demand function algorithm ) OR ( java selection based algorithm ))*
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Java based expert system for selection of natural fibre composite materials
Published 2013“…Computer oriented materials selection and knowledge-based expert systems are the prevailing approach in materials selection. …”
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Article -
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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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Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…But, the computer oriented materials selection and knowledge-based expert systems are the robust approach in materials selection to handle huge amount of materials of choice. …”
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Thesis -
4
Application of genetic algorithm and JFugue in an evolutionary music generator
Published 2025“…This project explores the application of Genetic Algorithms (GA) with JFugue, which is a Java-based music programming library to develop an Evolutionary Music Generator. …”
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Final Year Project / Dissertation / Thesis -
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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…EACO selects the resources based on the pheromone value on each resource which is recorded in a matrix form. …”
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Monograph -
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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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8
Hybrid optimization approach to estimate random demand
Published 2012“…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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Conference or Workshop Item -
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Long term energy demand forecasting based on hybrid, optimization: Comparative study
Published 2012“…The objective of this research is to develop a long term energy demand forecasting model that used hybrid optimization.To accomplish this goal, a hybrid algorithm that combined a genetic algorithm and a local search algorithm method has been developed to overcome premature convergence.Model performances of hybrid algorithm were compared with former single algorithm model in estimating parameter values of an objective function to measure the goodness-of-fit between the observed data and simulated results.Averages error between two models was adopt to select the proper model for future projection of energy demand.…”
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Article -
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A Toolkit for Simulation of Desktop Grid Environment
Published 2014“…The selected methodology for the application development is based on prototyping methodology. …”
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Final Year Project -
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Inter-cell and intra-cell facility layout models under different demand environments in cellular manufacturing systems
Published 2012“…Moreover, the computation time (CPU Time) of the developed SA algorithm is significantly less than the benchmarked algorithm. …”
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Thesis -
12
A genetic algorithm based approach for economic dispatch in power system / Mohd Rozely Kalil
Published 1998“…The Genetic Algorithm developed in the project was tested on two objective functions for optimizing the economic dispatch problem, which are the total generation cost and the incremental cost function. …”
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Thesis -
13
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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Thesis -
14
Irrigation management based on reservoir operation with an improved weed algorithm
Published 2023Article -
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Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms
Published 2016“…The latest effort to solve this selection problem is the development of the metrics selection model that uses genetic algorithm (GA). …”
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Thesis -
16
Optimal demand response of solar energy generation using Genetic Algorithm / Muhammad Asyraaf Adlan
Published 2025“…The aim of this study is to optimize the demand response of solar energy generation using Genetic Algorithm (GA) to minimize the daily yield loss caused by load shedding. …”
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Thesis -
17
Resource management in grid computing using ant colony optimization
Published 2011“…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion 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.Experimental results show that EACO produced better grid resource management solution.…”
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Monograph -
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Irrigation Management Based on Reservoir Operation with an Improved Weed Algorithm
Published 2018“…The Aswan High Dam, one of the most important dams in Egypt, was selected for this study to supply irrigation demands. The improved weed algorithm (IWA) had developed local search ability so that the exploration ability for the IWA increased and it could escape from local optima. …”
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Economic power dispatch solution with non-smooth cost functions using differential evolution: article / Muhammad Firdaus Abd Rahim
Published 2011“…The results obtained show that DE can solve Economic Dispatch with non-smooth cost function successfully. The program for this algorithm has been developed in Matlab 7.6 platform.…”
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