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  1. 1
    Different mutation and crossover set of genetic programming in an automated machine learning

    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
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  2. 2
    Different mutation and crossover set of genetic programming in an automated machine learning

    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
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  3. 3
    Efficient genetic partitioning-around-medoid algorithm for clustering

    Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

    Published 2019
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  4. 4
    Case Slicing Technique for Feature Selection

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…All these approaches are implemented with RELIEF feature selection approach. The classification accuracy obtained from the CST method is compared to other selected classification methods such as Value Difference Metric (VDM), Pre-Category Feature Importance (PCF), Cross-Category Feature Importance (CCF), Instance-Based Algorithm (IB4), Decision Tree Algorithms such as Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5), Rough Set methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) and Neural Network methods such as the Multilayer method.…”
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  5. 5
    Parallel computation of maass cusp forms using mathematica

    Parallel computation of maass cusp forms using mathematica by Chan, Kar Tim

    Published 2013
    “…We find that the parallel programming is about 5.75 times faster than the normal programming while its efficiency is capped at 0.443.…”
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  6. 6
    A hybrid intelligent algorithm for solving the bilevel programming models

    A hybrid intelligent algorithm for solving the bilevel programming models by Shamsul Bahar, Yaakob, Prof. Madya, Watada, Junzo

    Published 2011
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  7. 7
    Logic Programming In Radial Basis Function Neural Networks

    Logic Programming In Radial Basis Function Neural Networks by Hamadneh, Nawaf

    Published 2013
    “…To do that I used the root mean square error function and Schwarz bayesian criterion as model selection criteria. I used real data sets of different sizes in the computational results. …”
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  8. 8
    IP algorithms in compact rough classification modeling

    IP algorithms in compact rough classification modeling by Bakar, Azuraliza Abu, Sulaiman, Md Nasir, Othman, Mohamed, Selamat, Mohd Hasan

    Published 2001
    “…The algorithm is based on creating a 0-1 integer programming model from a rough discernibility relations of a decision system (DS) to find minimum selection of important attributes which is called reduct in rough set theory. …”
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  9. 9
    Traditional marble game using ant colony optimization / Muhammad Izzat Imran Che Isa

    Traditional marble game using ant colony optimization / Muhammad Izzat Imran Che Isa by Che Isa, Muhammad Izzat Imran

    Published 2017
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  10. 10
    Application of genetic algorithm and JFugue in an evolutionary music generator

    Application of genetic algorithm and JFugue in an evolutionary music generator by Tang, Jia Rou

    Published 2025
    “…This project explores the application of Genetic Algorithms (GA) with JFugue, which is a Java-based music programming library to develop an Evolutionary Music Generator. …”
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  11. 11
    Genetic Algorithm for Web Data Mining

    Genetic Algorithm for Web Data Mining by Loo, Kevin Teow Aik

    Published 2001
    “…This study used a prototype program based on genetic algorithm to manipulate the initial set of data. …”
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  12. 12
    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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  13. 13
    Airline flight delay prediction using Naïve Bayes algorithm / Ahmad Adib Baihaqi Shukri

    Airline flight delay prediction using Naïve Bayes algorithm / Ahmad Adib Baihaqi Shukri by Shukri, Ahmad Adib Baihaqi

    Published 2024
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  14. 14
    Firefly algorithm for optimal sizing of Standalone Photovoltaic System / Nurizzati Abdul Aziz

    Firefly algorithm for optimal sizing of Standalone Photovoltaic System / Nurizzati Abdul Aziz by Abdul Aziz, Nurizzati

    Published 2016
    “…In addition, sizing algorithm with FA was also discovered to outperform sizing algorithm with selected computational intelligence, i.e. …”
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  15. 15
    Firefly algorithm for optimal sizing of stand-alone photovoltaic system / Nur Izzati Abdul Aziz

    Firefly algorithm for optimal sizing of stand-alone photovoltaic system / Nur Izzati Abdul Aziz by Abdul Aziz, Nur Izzati

    Published 2016
    “…In addition, sizing algorithm with FA was also discovered to outperform sizing algorithm with selected computational intelligence, i.e. …”
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  16. 16
    Prediction of UPSR Result using clonal selection algorithm (PUR) / Muhammed Khaleeq Shafii

    Prediction of UPSR Result using clonal selection algorithm (PUR) / Muhammed Khaleeq Shafii by Shafii, Muhammed Khaleeq

    Published 2012
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  17. 17
    Evaluation of robot path planning algorithms in global static environments: genetic algorithm vs ant colony optimization algorithm / Nohaidda Sariff and Norlida Buniyamin

    Evaluation of robot path planning algorithms in global static environments: genetic algorithm vs ant colony optimization algorithm / Nohaidda Sariff and Norlida Buniyamin by Sariff, Nohaidda, Buniyamin, Norlida

    Published 2010
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  18. 18
    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem

    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

    Published 2016
    “…The proposed classifier is called Support Vector Genetic Programming Machine, SVGPM. In order to evaluate the performance of SVGPM against current methods in solving imbalanced classification task, three experiments are conducted such as on selected standard class imbalanced benchmark data sets, intrusion detection system (IDS) data set and remote sensing data set. …”
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  19. 19
    Classification model for hotspot occurrences using spatial decision tree algorithm

    Classification model for hotspot occurrences using spatial decision tree algorithm by Sitanggang, Imas Sukaesih, Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin

    Published 2013
    “…As the ID3 algorithm that uses information gain in the attribute selection, the proposed algorithm uses spatial information gain to choose the best splitting layer from a set of explanatory layers. …”
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  20. 20
    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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