Search Results - (( post implementation using algorithm ) OR ( problem implementation developing algorithm ))
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Parallel Implementation Of Field Visualizations With High Order Tetrahedral Finite Elements
Published 2013“…The developed algorithm was assessed on various problem geometries with considerable high number of unknowns where it is found that the approach is quite scalable.…”
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Thesis -
2
A Survey of metaheuristic approaches for curriculum based course timetabling problem
Published 2017“…The review of available approaches in solving CBCTT problem in this paper produces information that can be used for future development and experimentation such as number of instances that should be used, neighborhood structure(s) that can be applied and number of experiment repetitions.As stated by Wolpert & Macready (1997) that there is no unique ‘best’ algorithm which performs better than any other algorithm on every test problem (data instance), hence, this paper provides guidelines for future investigation on solving CBCTT problem using other metaheuristic techniques or approaches.…”
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Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network
Published 2014“…Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. …”
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Article -
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Optimisation of energy efficient Assembly Sequence Planning using Moth-Flame Optimisation alghorithm
Published 2019“…On the other hand, the recent ASP research tends to explore the potential of a relatively new algorithm to optimise ASP. Therefore, the aim of this research is to establish a methodology and implement the relatively new algorithm to optimise the Energy Efficient Assembly Sequence Planning (EE-ASP) problem. …”
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6
The largest studentized residual test for bad data identification in state estimation of a power system
Published 2015“…The chi-square and normalized residual tests are the common post estimation procedures usually used for detection and identification of gross errors in the estimation algorithm. …”
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Low-level hybridization scripting language with dynamic parameterization in PSO-GA / Suraya Masrom
Published 2015“…However, in many cases, implementing the suitable hybrid algorithms for a given optimization problem is a considerably difficult, which in most cases, is time consuming. …”
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8
Quantum Processing Framework And Hybrid Algorithms For Routing Problems
Published 2010“…The focus of this study is developing a framework of QAPU and hybrid architecture for classical-quantum algorithms. …”
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Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja
Published 2004“…As for WXES3l82, the thesis cover the development of programming code, the code implementation and testing and the evaluation including discussion about the problem/constraints meed in the coding program development. …”
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10
Crosssover-first different evolution: a comprehensive post- Hoc analysis
Published 2017“…Explore a new evolutionary optimization approach using Crossover-First Differential Evolution. Implementation details explained clearly with a comprehensive post-hoc statistical analysis to support the algorithm. …”
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Book -
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Enhancement of Ant System Algorithm for Course Timetabling Problem
Published 2009“…In order to develop a new algorithm for the course scheduling problem, this research follows the experimental research methodology that consist of problem analysis, designing algorithm, implementing algorithm as a computer program in order to examine the results, analyzing the results, and if necessary improving the algorithm by doing all those activities over and over again. …”
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12
Chaotic Immune Symbiotic Organisms Search algorithm for solving optimisation problem
Published 2023“…Good performance of these heuristics-based algorithm has been implied through various implementation in solving optimisation problems. …”
Article -
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Low-level hybridization scripting language with dynamic parameterization in PSO-GA / Suraya Masrom
Published 2015“…However, in many cases, implementing the suitable hybrid algorithms for a given optimization problem is a considerably difficult, which in most cases, is time consuming. …”
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Book Section -
14
Computational Thinking : Experiences of Rural Pupils in Sarawak Primary School
Published 2021“…The Computational Thinking results of quantitative data were collected using pre-test and post-test that consisted of five subjective computational thinking items. …”
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Thesis -
15
Development of dynamic programming algorithm for maintenance scheduling problem
Published 2020“…Then, the data of the maintenance team from one of the utilities provider company in Malaysia was collected to be implemented in the development of a dynamic programming algorithm. …”
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16
Metric's thresholds for encoding evolutionary computing representation in software engineering problem
Published 2015“…This paper presents metrics thresholds encoding algorithm as an alternative to replace human experts in developing problem representation. …”
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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Faculty timetabling using genetic algorithm
Published 2011“…Faculty Timetabling using Genetic Algorithm (FTGA) is an application that generate optimum timetable for faculty.The target user of this application is faculty staff who responsible in generate timetable.The problem statement of the project is many clashing exist in the timetable.Faculty staff needs to solve the clashing manually.This will waste time and it is a problem for staff to solve the clashing.By implement GA,clashing will be reduced.The objective of the project is to develop aprototype in scheduling application for generates an optimum timetable for a faculty.Genetic algorithm will be implemented.The scope of FTGA is Faculty of Computer Systems & Software Engineering (FCSSE).The methodology use in this project is prototype model.The testing result show 95 out of 100 test cases achieved the maximum fitness value which means there is no clashing in the timetable.The maximum generation is set to 15 generation.Population for each generation is 3 populations.Percentage of FTGA solve the problem is 95%.…”
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Undergraduates Project Papers -
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