Search Results - (( java implementation using algorithm ) OR ( problem solving selection algorithm ))

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  1. 1

    Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar by Tengku Jaafar, Tengku Salman Fathi

    Published 2006
    “…By taking the bus services in Universiti Teknologi MARA as sample, the research has used the genetic algorithm approach to solve the problem which is similar to the Travel Salesman Problem. …”
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    Thesis
  2. 2

    Improving Class Timetabling using Genetic Algorithm by Qutishat, Ahmed Mohammed Ali

    Published 2006
    “…We have targeted the research on class timetabling problem. Hence, Genetic Algorithm (GA) is used as one of the most popular optimization solutions. …”
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    Thesis
  3. 3

    Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions by Ahmed, Mashuk, Nasser, Abdullah B., Kamal Z., Zamli, Heripracoyo, Sulistyo

    Published 2022
    “…To help engineers select the best metaheuristic algorithms for their problems, there is a need to evaluate the performance of different metaheuristic algorithms against each other using common case studies. …”
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    Conference or Workshop Item
  4. 4

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…Finally, the algorithm found, which would solve the image segmentation problem.…”
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    Thesis
  5. 5

    Batch mode heuristic approaches for efficient task scheduling in grid computing system by Maipan-Uku, Jamilu Yahaya

    Published 2016
    “…Many algorithms have been implemented to solve the grid scheduling problem. …”
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    Thesis
  6. 6

    Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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    Article
  7. 7

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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    Final Year Project
  8. 8

    Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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    Article
  9. 9

    Provider independent cryptographic tools by Ibrahim, Subariah, Salleh, Mazleena, Abdul Aziz, Shah Rizan

    Published 2003
    “…The library is implemented by using Java cryptographic service provider framework that conforms to Java Cryptographic Architecture (JCA) and Java Cryptographic Extension (JCE). …”
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    Monograph
  10. 10

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    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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    Thesis
  11. 11

    Bats echolocation-inspired algorithms for global optimisation problems by Nafrizuan, Mat Yahya

    Published 2016
    “…An adaptive bats sonar algorithm is proposed for solving single objective optimisation problems. …”
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    Thesis
  12. 12

    Approximate maximum clique algorithm (AMCA): A clever technique for solving the maximum clique problem through near optimal algorithm for minimum vertex cover problem by Fayaz, Muhammad, Arshad,, Shakeel, Shah,, Abdul Salam, Shah, Asadullah

    Published 2018
    “…Background and Objective: The process of solving the Maximum Clique (MC) problem through approximation algorithms is harder, however, the Maximum Vertex Cover (MVC) problem can easily be solved using approximation algorithms. …”
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    Article
  13. 13

    A fuzzy genetic algorithm based on binary encoding for solving multidimensional knapsack problems by Varnamkhasti, Mohammad Jalali, Lee, Lai Soon

    Published 2012
    “…Computational experiments are conducted on the proposed techniques and the results are compared with other genetic operators, heuristics, and local search algorithms commonly used for solving multidimensional 0/1 knapsack problems published in the literature.…”
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    Article
  14. 14

    Genetic Algorithm Performance with Different Selection Strategies in Solving TSP by Noraini, Mohd Razali, Geraghty, John

    Published 2011
    “…There are several ways for selection. This paper presents the comparison of GA performance in solving travelling salesman problem (TSP) using different parent selection strategy. …”
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    Conference or Workshop Item
  15. 15

    Some metaheuristic algorithms for solving multiple cross-functional team selection problems by Ngo, S.T., Jaafar, J., Izzatdin, A.A., Tong, G.T., Bui, A.N.

    Published 2022
    “…We introduced a method that combines a compromise programming (CP) approach and metaheuristic algorithms, including the genetic algorithm (GA) and ant colony optimization (ACO), to solve the proposed optimization problem. …”
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    Article
  16. 16

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
    “…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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    Thesis
  17. 17

    Evolutionary algorithm with roulette-tournament selection for solving aquaculture diet formulation by Abd Rahman, Rosshairy, Ramli, Razamin, Jamari, Zainoddin, Ku-Mahamud, Ku Ruhana

    Published 2016
    “…In this paper, a new selection operator is introduced for a real valued encoding problem, which specifically exists in a shrimp diet formulation problem.This newly developed selection operator is a hybrid between two well-known established selection operators: roulette wheel and binary tournament selection.A comparison of the performance of the proposed operator and the other existing operator was made for evaluation purposes.The result shows that the proposed roulette-tournament selection is better in terms of its ability to provide many good feasible solutions when a population size of 30 is used.Thus, the proposed roulette-tournament is suitable and comparable to established selection for solving a real valued shrimp diet formulation problem.The selection operator can also be generalized to any problems related to EA.…”
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    Article
  18. 18

    Enhanced selection method for genetic algorithm to solve traveling salesman problem by Jubeir, Mohammed, Almazrooie, Mishal, Abdullah, Rosni

    Published 2017
    “…Genetic algorithms (GAs) have been applied by many researchers to get an optimized solution for hard problems such as Traveling Salesman Problem (TSP). …”
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  19. 19

    Investigation of evolutionary multi-objective algorithms in solving view selection problem / Seyed Hamid Talebian by Talebian, Seyed Hamid

    Published 2013
    “…In this research, we showed how evolutionary multi-objective algorithms can be used to solve the view selection problem and its advantage over classical optimization problems were described. …”
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    Thesis
  20. 20

    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…We hyave used the CPU profiler of Oracle JavaTM VisualVM to monitor the execution of LRE-TL as well as USG algorithms. …”
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    Conference or Workshop Item