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Improved clustering using robust and classical principal component
Published 2017“…Hence the k-means by robust PCA is developed to rectify the problem of outliers in the dataset. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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Hybrid multiobjective genetic algorithm for integrated dynamic scheduling and routing of jobs and automated guided vehicles in flexible manufacturing systems
Published 2014“…The objectives of this research are to develop an algorithm for integrated scheduling and conflict-free routing of jobs and AGVs in FMS environment using a hybrid genetic algorithm, ensure the algorithm validity and improvement on the performance of the developed algorithm. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
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Approximate maximum clique algorithm (AMCA): A clever technique for solving the maximum clique problem through near optimal algorithm for minimum vertex cover problem
Published 2018“…Results: The development of an efficient approximation algorithm for the Maximum Clique (MC) problem is very difficult due to its complex nature. …”
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Effect of adopting different dispatching rules on the mean flow time in a two machine batch-shop problem
Published 2005“…This means that it is highly unlikely to find a polynomial algorithm to solve the problem. …”
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Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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Data clustering using the bees algorithm
Published 2007“…The authors’ team have developed a new population based search algorithm called the Bees Algorithm that is capable of locating near optimal solutions efficiently. …”
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Development of bacteria foraging optimization algorithm for cell formation in cellular manufacturing system considering cell load variations
Published 2013“…This paper investigates the first applications of this emerging novel optimization algorithm to the cell formation (CF) problem. In addition, for this purpose matrix-based bacteria foraging optimization algorithm traced constraints handling (MBATCH) is developed. …”
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Marketplace product recommendation using collaborative filter / Muhammad Alif Fauzan Ismail
Published 2021“…The algorithm used to develop a product recommendation engine is collaborative filtering algorithm and this algorithm is written in python. …”
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loformation Retrieval - using Porter Stemming Algorithm
Published 2006“…There are many stemming method that have been developed. However, the main focus of this project is on Porter Stemming Algorithm which has been developed by M.F Porter in 1980. …”
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Final Year Project -
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Web based clustering tool using K-MEAN++ algorithm / Muhammad Nur Syazwanie Aznan
Published 2019“…Which is why this project objective is to develop a web based clustering tool using K-MEAN++ algorithm. …”
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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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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
Published 2011“…The algorithm developed in this thesis contains three sub-algorithms. …”
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Elitism Based Migrating Birds Optimization Algorithm for Optimization Testing
Published 2017“…This proposed strategy is the first to utilize population based metaheuristic algorithm i.e. MBO with elitism for solving CIT problem. …”
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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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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Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering
Published 2022“…According to the literature, crowding distance as one of the most efficient algorithms was developed based on density measures to treat the problem of selection mechanism for archive update. …”
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