Search Results - (( parameter adoption model algorithm ) OR ( java implementation learning algorithm ))

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  1. 1

    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
  2. 2

    Segment Particle Swarm Optimization Adoption for Large-Scale Kinetic Parameter Identification of Metabolic Network Model by Azrag, M. A. K., Tuty Asmawaty, Abdul Kadir, Jaber, Aqeel S.

    Published 2018
    “…The seven sensitive kinetic parameters were used in both the algorithms to minimize the model response errors. …”
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    Article
  3. 3
  4. 4

    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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    Conference or Workshop Item
  5. 5

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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    Thesis
  6. 6

    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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    Thesis
  7. 7

    Enhancing harmony search parameters based on step and linear function for bus driver scheduling and rostering problems by Mansor, Nur Farraliza

    Published 2018
    “…Optimization is a major challenge in numerous practical world problems.According to the “No Free Lunch (NFL)” theorem,there is no existing single optimizer algorithm that is able to resolve all issues in an effective and efficient manner.It is varied and need to be solved according to the specific capabilities inherent to certain algorithms making it hard to foresee the algorithm that is best suited for each problem.As a result,the heuristic technique is adopted for this research as it has been identified as a potentially suitable algorithm.Alternative heuristic algorithms are also suggested to obtain optimal solutions with reasonable computational effort.However,the heuristic approach failed to produce a solution that nears optimum when the complexity of a problem increases;therefore a type of nature-inspired algorithm known as meta-euristics which utilises an intelligent searching mechanism over a population is considered and consequently used.The meta-heuristic approach is widely used to substitute heuristic terms and is broadly applied to address problems with regards to driver scheduling.However,this meta-heuristic technique is still unable to address the fairness issue in the scheduling and rostering problems.Hence,this research proposes a strategy to adopt an amendment of the harmony search algorithm in order to address the fairness issue which in turn will escalate the level of fairness in driver scheduling and rostering.The harmony search algorithm is classified as a meta-heuristics algorithm that is capable of solving hard and combinatorial or discrete optimisation problems.In this respect,the three main operators in harmony search,namely the Harmony Memory Consideration Rate (HMCR),Pitch Adjustment Rate (PAR) and Bandwidth (BW) play a vital role in balancing local exploitation and global exploration.These parameters influence the overall performance of the HS algorithm,and therefore it is crucial to fine-tune them. …”
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  8. 8

    On determination of input parameters of the mass transfer process by fuzzy approach. by Maan, Normah, Talib, Jamalludin, Arshad, Khairil Annuar, Ahmad, Tahir

    Published 2005
    “…The algorithm is also capable of determining the optimal values of the input parameters. …”
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    Article
  9. 9

    A comparative study for parameter selection in online auctions by Gan, Kim Soon

    Published 2009
    “…Self adaptation genetic algorithm is the last model that will be used to evolve the bidding strategy. …”
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    Thesis
  10. 10

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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    Thesis
  11. 11

    Genetic algorithm optimisation for fuzzy control of wheelchair lifting and balancing by Ahmad, Salmiah, Tokhi, M. Osman, Toha, Siti Fauziah

    Published 2009
    “…Genetic Algorithm is used to control the two-wheeled wheelchair and results show that the optimised parameters give better system performance.…”
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    Proceeding Paper
  12. 12

    Automatic control of flotation process using computer vision by Saravani, Ali Jahed

    Published 2015
    “…Finally, a control strategy implementing the developed froth model and prediction system was introduced for direct optimization of metallurgical parameters. …”
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  13. 13

    Large-scale kinetic parameters estimation of metabolic model of escherichia coli by Azrag, M. A. K., Tuty Asmawaty, Abdul Kadir, Kabir, M. Nomani, Jaber, Aqeel S.

    Published 2019
    “…In this work, the PSO algorithm has been adopted to estimate the kinetic parameters by minimizing the errors of the large-scale of metabolic model response of E. coli with reference to real experimental data. …”
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    Article
  14. 14

    Long term energy demand forecasting based on hybrid, optimization: Comparative study by Musa, Wahab, Ku-Mahamud, Ku Ruhana, Yasin, Azman

    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
  15. 15

    Application of memetic algorithm in modelling discrete-time multivariable dynamics systems by Ahmad, Robiah, Jamaluddin, Hishamuddin, Hussain, Mohd. Azlan

    Published 2008
    “…There are more possible structures to choose from and more parameters are required to obtain a good fit. In this work, a new model structure selection in system identification problems based on a modified GA with an element of local search known as memetic algorithm (MA) is adopted. …”
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    Article
  16. 16

    Novel direct and self-regulating approaches to determine optimum growing multi-experts network structure by Loo, C.K., Rajeswari, M., Rao, M.V.C.

    Published 2004
    “…However, GMN is not ergonomic due to too many network control parameters. Therefore, a self-regulating GMN (SGMN) algorithm is proposed. …”
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    Article
  17. 17

    Investigation of Meta-heuristics Algorithms in ANN Streamflow Forecasting by Wei Y., Hashim H., Chong K.L., Huang Y.F., Ahmed A.N., El-Shafie A.

    Published 2024
    “…This study investigated the efficacy of a hybrid model that adopted a meta-heuristic algorithm (MHA) as an optimizer to extend the training ANN method, from a gradient-based to a stochastic population-based approach for streamflow forecasting. …”
    Article
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    Mathematical modelling of mass transfer in a multi-stage rotating disc contactor column by Maan, Normah

    Published 2005
    “…A series of algorithms in solving the inverse problem were then developed corresponding to the forward models. …”
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    Thesis
  19. 19

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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  20. 20

    Predictive modelling of machining parameters of S45C mild steel by Abbas, Adnan Jameel

    Published 2016
    “…The artificial neural network type Network Fitting Tool (NFTOOL) is used as a modeling technique for manipulating the ideal algorithm parameters. …”
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