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  1. 1
    Development of genetic algorithm-based fuzzy rules design for metal cutting data selection

    Development of genetic algorithm-based fuzzy rules design for metal cutting data selection by Wong, S.V, Hamouda, A.M.S

    Published 2002
    “…The authors have developed fuzzy models for machinability data selection (Int. …”
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  2. 2
    Fuzzy Rules Optimization in Fuzzy Expert System for Machinability Data Selection: Genetic Algorithms Approach

    Fuzzy Rules Optimization in Fuzzy Expert System for Machinability Data Selection: Genetic Algorithms Approach by Wong, Shaw Voon, Salem Hamouda, Abdel Magid

    Published 2001
    “…Genetic optimization is suggested in this paper to further optimizing the fuzzy rules optimization with genetic algorithms has been developed. …”
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  3. 3
    Improving explicit aspects extraction in sentiment analysis using optimized ruleset / Mohammad Ahmad Jomah Tubishat

    Improving explicit aspects extraction in sentiment analysis using optimized ruleset / Mohammad Ahmad Jomah Tubishat by Mohammad Ahmad, Jomah Tubishat

    Published 2019
    “…Finally, after the aspects list was obtained from the selected rules, a pruning algorithm (PA) is developed to remove the incorrect aspects and retain the correct aspects. …”
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  4. 4
    New Structural Evolving Algorithms For Fuzzy Systems

    New Structural Evolving Algorithms For Fuzzy Systems by Saad, Hisham Haider Yusef

    Published 2018
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  5. 5
    An adaptive ant colony optimization algorithm for rule-based classification

    An adaptive ant colony optimization algorithm for rule-based classification by Al-Behadili, Hayder Naser Khraibet

    Published 2020
    “…Various classification algorithms have been developed to produce classification models with high accuracy. …”
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  6. 6
    Optimization of fuzzy rules design using genetic algorithm

    Optimization of fuzzy rules design using genetic algorithm by Wong, S.V., Hamouda, A.M.S.

    Published 2000
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  7. 7
    Melanoma skin cancer recognition using negative selection algorithm / Muhammad Rushamir Hakimi Ruslan

    Melanoma skin cancer recognition using negative selection algorithm / Muhammad Rushamir Hakimi Ruslan by Ruslan, Muhammad Rushamir Hakimi

    Published 2017
    “…This study proposed and focused on the development of a prototype that uses the Negative Selection Algorithm to classify the input image whether it is belongs to melanoma skin cancer or benign mole. …”
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  8. 8
    Using fuzzy association rule mining in cancer classification

    Using fuzzy association rule mining in cancer classification by Mahmoodian, Sayed Hamid, Marhaban, Mohammad Hamiruce, Abdul Rahim, Raha, Rosli, Rozita, Saripan, M. Iqbal

    Published 2011
    “…A new algorithm has been developed to identify the fuzzy rules and significant genes based on fuzzy association rule mining. …”
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  9. 9
    Image recognition using Artificial Immune systems approach

    Image recognition using Artificial Immune systems approach by Hasnah, Ahmad, Puteh, Saad

    Published 2009
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  10. 10
    Building Fuzzy Inference Systems with Similarity Reasoning: NSGA II-based Fuzzy Rule Selection and Evidential Functions

    Building Fuzzy Inference Systems with Similarity Reasoning: NSGA II-based Fuzzy Rule Selection and Evidential Functions by Tze, Ling Jee, Kok, Chin Chai, Kai, Meng Tay, Chee, Peng Lim

    Published 2014
    “…The Non-Dominated Sorting Genetic Algorithms-II (NSGA-II) is adopted for fuzzy rule selection, in accordance with the Pareto optimal criterion. …”
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    Proceeding
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  11. 11
    Development of a rule-based fault diagnostic advisory system for precut fractionation column

    Development of a rule-based fault diagnostic advisory system for precut fractionation column by Heng, Han Yann

    Published 2005
    “…The advisory system algorithm used process history based method and presented by rule-based approach. …”
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  12. 12
    Comprehensive power restoration approach using rule-based method for 11kV distribution network

    Comprehensive power restoration approach using rule-based method for 11kV distribution network by Khalid A.R., Ahmad S.M.S., Shakil A., Pa N.N., Shafie R.M.

    Published 2023
    “…This paper presents a restoration algorithm based on a Rule-Based approach. The algorithm is computationally programmed to provide multiple solutions and to recommend the best option of switching for a dispatcher. …”
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  13. 13
    First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms

    First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms by Azwa, Abdul Aziz, Fadhilah, Ahmad

    Published 2014
    “…From the experiment, the models develop using Rule Based and Decision Tree algorithm shows the best result compared to the model develop from the Naïve Bayes algorithm. …”
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  14. 14
    A rough-fuzzy inference system for selecting team leader for software development teams

    A rough-fuzzy inference system for selecting team leader for software development teams by Jaafar, Jafreezal, Gilal, Abdul Rehman, Omar, Mazni, Basri, Shuib, Abdul Aziz, Izzatdin, Hasan, Mohd Hilmi

    Published 2017
    “…Moreover, the model development was divided into two portions: Decision Rules Development and Fuzzy Inference System (FIS) development. …”
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  15. 15
    A Rough-Fuzzy Inference System for Selecting Team Leader for Software Development Teams

    A Rough-Fuzzy Inference System for Selecting Team Leader for Software Development Teams by Jaafar, J., Gilal, A.R., Omar, M., Basri, S., Aziz, I.A., Hasan, M.H.

    Published 2018
    “…Moreover, the model development was divided into two portions: Decision Rules Development and Fuzzy Inference System (FIS) development. …”
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  16. 16
    A Rough-Fuzzy Inference System for Selecting Team Leader for Software Development Teams

    A Rough-Fuzzy Inference System for Selecting Team Leader for Software Development Teams by Jaafar, J., Gilal, A.R., Omar, M., Basri, S., Aziz, I.A., Hasan, M.H.

    Published 2018
    “…Moreover, the model development was divided into two portions: Decision Rules Development and Fuzzy Inference System (FIS) development. …”
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  17. 17
    Dengue classification system using clonal selection algorithm / Karimah Mohd

    Dengue classification system using clonal selection algorithm / Karimah Mohd by Mohd, Karimah

    Published 2012
    “…This project focused on three main objectives: to investigate dengue data and Clonal Selection Algorithm for classification of Dengue, to design and develops Clonal Selection Classification System (CSCS) and to evaluate Clonal Selection Classification System symptoms. …”
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  18. 18
    Optimization of operational policies for the Minab Reservoir, Southern Iran

    Optimization of operational policies for the Minab Reservoir, Southern Iran by Gholampoor, Mohammad

    Published 2012
    “…Through the hedging rule optimization an algorithm was developed to determine the benefit of water release and the water conserved in the reservoir. …”
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  19. 19
    A new standardisation and selection framework for real-time image dehazing algorithms from multi-foggy scenes based on fuzzy Delphi and hybrid multi-criteria decision analysis methods

    A new standardisation and selection framework for real-time image dehazing algorithms from multi-foggy scenes based on fuzzy Delphi and hybrid multi-criteria decision analysis meth... by Abdulkareem, Karrar Hameed, Arbaiy, Nureize, Zaidan, A. A., Zaidan, B. B., Albahri, O. S., Alsalem, M. A., M. Salih, Mahmood

    Published 2020
    “…Given the rapid development of dehazing image algorithms, selecting the optimal algorithm based on multiple criteria is crucial in determining the efficiency of an algorithm. …”
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  20. 20
    A New Monotone Fuzzy Rule Relabeling Framework With Application to Failure Mode and Effect Analysis Methodology

    A New Monotone Fuzzy Rule Relabeling Framework With Application to Failure Mode and Effect Analysis Methodology by Tay, Kai Meng, Pang, Lie Meng, Lim, Chee Peng, Ishibuchi, Hisao

    Published 2020
    “…In this paper, we further propose a new three-stage framework to develop a computationally efficient MFRR algorithm. …”
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