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  1. 1
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

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

    Published 2008
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  2. 2
    Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method

    Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method by Marlan Z.M., Jamaludin K.R., Harudin N.

    Published 2024
    “…Thus, this study proposed an Opposition-based Learning Binary Bat Algorithm as the feature selection technique in the T-method. …”
    Conference Paper
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  3. 3
    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments

    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments by Chiang, A., Baba, M.S.

    Published 2006
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  4. 4
    An Educational Tool Aimed at Learning Metaheuristics

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

    Published 2020
    “…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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  5. 5
    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment

    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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  6. 6
    A partition based feature selection approach for mixed data clustering / Ashish Dutt

    A partition based feature selection approach for mixed data clustering / Ashish Dutt by Ashish , Dutt

    Published 2020
    “…One such pre-processing algorithm in EDM is clustering. It is a widely used method in data mining to discover unique patterns in underlying data. …”
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  7. 7
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

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

    Published 2022
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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  8. 8
    Development of genetic algorithm for optimization of yield models in oil palm production

    Development of genetic algorithm for optimization of yield models in oil palm production by Hilal, Yousif Y., Wan Ismail, Wan Ishak, Yahya, Azmi, Ash’aari, Zulfa Hanan

    Published 2018
    “…This research concludes that the GA method is a user-friendly variable selection tool with excellent results because it can choose variables correctly.…”
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  9. 9
    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm

    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

    Published 2025
    “…In conclusion, the proposed method successfully yields better prediction accuracy as compared to conventional approaches. …”
    Conference paper
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  10. 10
    Predicting crop yield and field energy output for oil palm using genetic algorithm and neural network models

    Predicting crop yield and field energy output for oil palm using genetic algorithm and neural network models by Hilal, Yousif Yakoub

    Published 2019
    “…This research presents the development of a GA and SW as a variables selection method in ANN and NARX models for predicting oil palm yield and output energy. …”
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  11. 11
    Hybrid binary grey Wolf with Harris hawks optimizer for feature selection

    Hybrid binary grey Wolf with Harris hawks optimizer for feature selection by Al-Wajih, R., Abdulkadir, S.J., Aziz, N., Al-Tashi, Q., Talpur, N.

    Published 2021
    “…The proposed hybrid method outperforms the BGWO algorithm in terms of accuracy, selected feature size, and computational time. …”
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  12. 12
    Hybrid Binary Grey Wolf with Harris Hawks Optimizer for Feature Selection

    Hybrid Binary Grey Wolf with Harris Hawks Optimizer for Feature Selection by Al-Wajih, R., Abdulkadir, S.J., Aziz, N., Al-Tashi, Q., Talpur, N.

    Published 2021
    “…The proposed hybrid method outperforms the BGWO algorithm in terms of accuracy, selected feature size, and computational time. …”
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  13. 13
    Hybrid binary grey Wolf with Harris hawks optimizer for feature selection

    Hybrid binary grey Wolf with Harris hawks optimizer for feature selection by Al-Wajih, R., Abdulkadir, S.J., Aziz, N., Al-Tashi, Q., Talpur, N.

    Published 2021
    “…The proposed hybrid method outperforms the BGWO algorithm in terms of accuracy, selected feature size, and computational time. …”
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  14. 14
    Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics

    Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics by Mohammad Jarrah, Mu'ath Ibrahim

    Published 2018
    “…Chemical Vapor Deposition (CVD) is the most efficient method for CNTs production.However,using CVD method encounters crucial issues such as customization,time and cost.Therefore,Response Surface Methodology (RSM) is proposed for modeling and the ABC-βHC is proposed for optimization purpose to address such issues.The selected CNTs characteristics are CNTs yield and quality represented by the ratio of the relative intensity of the D and G-bands (ID/IG).Six case studies are generated from collected dataset including four cases of CNTs yield and one case of ID/IG as single objective optimization problems,while the sixth case represents multi-objective problem.The input parameters of each case are a subset from the set of input parameters including reaction temperature,duration,carbon dioxide flow rate,methane partial pressure,catalyst loading,polymer weight and catalyst weight.The models for the first three case studies were mentioned in the original work.RSM is proposed to develop polynomial models for the output responses in the other three cases and to identi significant process parameters and interactions that could affect the CNTs output responses.The developed models are validated using t-test,correlation and pattern matching.The predictive results have a good agreement with the actual experimental data.The models are used as objective functions in optimization techniques.For multi-objective optimization,this study proposes Desirability Function Approach (DFA) to be integrated with other proposed algorithms to form hybrid techniques namely RSM-DFA,ABC-DFA and ABC-βHC-DFA.The proposed algorithms and other selected well-known algorithms are evaluated and compared on their CNTs yield and quality.The optimization results reveal that ABC-βHC and ABC-βHC-DFA obtained significant results in terms of success rate,required time,iterations,and function evaluations number compared to other well-known algorithms.Significantly,the optimization results from this study are better than the results from the original work of the collected dataset.…”
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  15. 15
    Sensitivity-based fuzzy multi-objective portfolio model with Value-at-Risk

    Sensitivity-based fuzzy multi-objective portfolio model with Value-at-Risk by Zhang, H., Watada, J., Wang, B.

    Published 2019
    “…The results show that the fuzzy VaR multi-objective portfolio model based on the sensitivity analysis method can effectively identify and quantitatively analyze the sensitivity of individual stocks to yield changes, i.e. that can identify which stock has more stable yields and that can calculate the degree of stability, then to obtain stable portfolio solutions. …”
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  16. 16
    Feature fusion using a modified genetic algorithm for face and signature recognition system

    Feature fusion using a modified genetic algorithm for face and signature recognition system by Suryanti, Awang

    Published 2015
    “…Results show that the proposed method yield optimal recognition with the highest accuracy of 97.50%. …”
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  17. 17
    Comparison of Conjugate Gradient methods for developing the multiple linear regression model for rubber yield in Malaysia / Anis Shahida Rohimi Ozeman

    Comparison of Conjugate Gradient methods for developing the multiple linear regression model for rubber yield in Malaysia / Anis Shahida Rohimi Ozeman by Rohimi Ozeman, Anis Shahida

    Published 2018
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  18. 18
    Development Of Machine Learning User Interface For Pump Diagnostics

    Development Of Machine Learning User Interface For Pump Diagnostics by Lee, Zhao Yang

    Published 2022
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    Monograph
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  19. 19
    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…The comparison results between BBSI and JM-distance showed that, both algorithms accurately selected the best four-band combination that yielded the highest overall accuracy classification map with value of 91% in the Landsat TM dataset. …”
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  20. 20
    elopment of Neural Network Model for Predicting Crucial Product Properties or Yield for Optimisation of Refinery Operation

    elopment of Neural Network Model for Predicting Crucial Product Properties or Yield for Optimisation of Refinery Operation by Mohamad, Sharliza

    Published 2005
    “…The project is an extension of a previous research conducted by the university on product yield and properties prediction using non-linear regression method. …”
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