Search Results - (( selection implementation new algorithm ) OR ( java application optimization algorithm ))
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Final Year Project -
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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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Ant colony optimization algorithm for load balancing in grid computing
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Monograph -
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Implementation of a new Preference Based Final Year Project title selection system for undergraduate engineering students in UNITEN
Published 2023“…The Network Flow Optimization algorithm, which was able to produce a selection with the lowest cost, was selected and used to allocate titles for students from Semester 1 of the 2009/2010 academic year. …”
Article -
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
Published 2023“…Within the GA, nearest neighbor algorithm is used in determining the most similar recorded case that can be used in solving the new case. …”
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Improved combined mutation clonal selection algorithm
Published 2023“…In this paper, the performance of a clonal selection optimization algorithm implementing a combined mutation strategy using Gaussian and Cauchy mutations was further improved with the addition of two new operators, namely the Cell Repair Operator (CPO) and Dynamic Mutation Size Operator (DMSO). …”
Conference paper -
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Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT
Published 2006“…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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Thesis -
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Examination timetabling using genetic algorithm case study: KUiTTHO
Published 2005“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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Selection, generation and extraction of MCCTree using XMCCTree
Published 2012“…Thus, this paper presents a new algorithm that implements the same notions with different approach. …”
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Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO
Published 2005“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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Thesis -
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…This algorithm has been tested and implemented successfully via a dual beam optical scanning system.…”
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Thesis -
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Harmony search algorithm for curriculum-based course timetabling problem
Published 2013“…In this paper, harmony search algorithm is applied to curriculum-based course timetabling.The implementation, specifically the process of improvisation consists of memory consideration, random consideration and pitch adjustment.In memory consideration, the value of the course number for new solution was selected from all other course number located in the same column of the Harmony Memory.This research used the highest occurrence of the course number to be scheduled in a new harmony.The remaining courses that have not been scheduled by memory consideration will go through random consideration, i.e. will select any feasible location available to be scheduled in the new harmony solution. …”
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Article -
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Harmony search algorithm for curriculum-based course timetabling problem
Published 2013“…In this paper, harmony search algorithm is applied to curriculum-based course timetabling.The implementation, specifically the process of improvisation consists of memory consideration, random consideration and pitch adjustment.In memory consideration, the value of the course number for new solution was selected from all other course number located in the same column of the Harmony Memory.This research used the highest occurrence of the course number to be scheduled in a new harmony.The remaining courses that have not been scheduled by memory consideration will go through random consideration, i.e. will select any feasible location available to be scheduled in the new harmony solution.Each course scheduled out of memory consideration is examined as to whether it should be pitch adjusted with probability of eight procedures. …”
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Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…In its operation, the metaheuristic algorithm optimizes the feature selection process,which will later be processed using the classification algorithm.Three (3) meta-heuristics were implemented, namely Genetic Algorithm, Particle Swarm Optimization, and Cuckoo Search Algorithm; the experiment was conducted, and the results were collected and analyzed. …”
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