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  1. 1

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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    Thesis
  2. 2

    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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  3. 3

    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
  4. 4

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

    Published 2016
    “…Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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    Thesis
  5. 5

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

    Published 2013
    “…Two techniques were developed. The first technique is to encode the logic programming in radial basis function neural networks. …”
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    Smart energy meter with adaptive communication data transfer algorithm for electrical energy monitoring by Ab Halim, Haizum Hanim

    Published 2021
    “…The prototype is constructed through software and hardware development and has been programmed using Arduino IDE software. …”
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    Data mining in network traffic using fuzzy clustering by Mohamad, Shamsul

    Published 2003
    “…The network traffic model is very important to know whether that particular network traffic is normal or abnormal. In this project, I have developed a program to capture and filter the packets based on the application. …”
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  14. 14

    Data mining in network traffic using fuzzy clustering by Mohamad, Shamsul

    Published 2003
    “…The network traffic model is very important to know whether that particular network traffic is normal or abnormal. In this project, I have developed a program to capture and filter the packets based on the application. …”
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    Thesis
  15. 15

    Multi -Objective Economic Dispatch Using Evolutionary Programming by Noor Azlan Bin Adnan

    Published 2023
    “…The designated algorithm of MOEP used MATLAB to run the simulations. …”
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    Agent-based extraction algorithm for computational problem solving by Rajabi, Maryam

    Published 2015
    “…Modeling Computational Problem Solving (CPS) is the main issue in teaching programming where the given text is needed to be transformed into a model then later into a programming language. …”
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    Thesis
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    Enhanced dynamic security assessment for power system under normal and fake tripping contingencies. by A. Salih, Qusay

    Published 2019
    “…The hybrid logistic model tree (hybrid LMT) approach proposed in this study combines the symmetrical uncertainties (SU) algorithm and the logistic model tree (LMT) algorithm. …”
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    Thesis
  20. 20

    Neural network based model predictive control for a steel pickling process by Kittisupakorn, P., Thitiyasook, P., Hussain, Mohd Azlan, Daosud, W.

    Published 2009
    “…The Levenberg-Marquardt algorithm is used to train the process models. In the control (MPC) algorithm, the feedforward neural network models are used to predict the state variables over a prediction horizon within the model predictive control algorithm for searching the optimal control actions via sequential quadratic programming. …”
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