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  1. 1

    Classification and detection of intelligent house resident activities using multiagent by ,, Mohd. Marufuzzaman, M. B. I., Raez, M. A. M., Ali, Rahman, Labonnah F.

    Published 2013
    “…Result shows that, the algorithm can successfully identify 135 unique tasks of different lengths.This algorithm is surely being an alternate way of pattern recognition in intelligent home.…”
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  2. 2

    Swarm intelligence algorithms’ solutions to the travelling salesman’s problem by Odili, Julius Beneoluchi, Noraziah, Ahmad, Roslina, Mohd Sidek

    Published 2020
    “…This paper presents research findings on the application of swarm intelligence techniques in computational intelligence to solve the travelling salesman’s problem. …”
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    Swarm intelligence algorithms' solutions to the travelling salesman's problem by Odili, Julius Beneoluchi, Noraziah, Ahmad, Roslina, Mohd Sidek

    Published 2020
    “…This paper presents research findings on the application of swarm intelligence techniques in computational intelligence to solve the travelling salesman's problem. …”
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  5. 5

    Backpropagation neural network based on local search strategy and enhanced multi-objective evolutionary algorithm for breast cancer diagnosis by Ashraf Osman, Ibrahim, Siti Mariyam, Shamsuddin, Abdulrazak, Yahya Saleh, Ahmed, Ali, Mohd Arfian, Ismail, Shahreen, Kasim

    Published 2019
    “…However, the performance of such methods is based on the algorithms or technique. In this paper, we develop an intelligent technique using multiobjective evolutionary method hybrid with a local search approach to enhance the backpropagation neural network. …”
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  6. 6

    Computational intelligence in steganalysis environment by Din, Roshidi, Samsudin, Azman

    Published 2008
    “…Three (3) major methods have also been identified in the computational intelligence based on these steganalysis domains which are bayesian, neural network, and genetic algorithm. …”
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  7. 7

    African Buffalo Optimization (ABO): A New Metaheuristic Algorithm by Odili, Julius Beneoluchi, M. N. M., Kahar

    Published 2015
    “…The African Buffalo Optimization (A.B.0) algorithm simulates the African buffalos' behaviour by encapsulation in a mathematical model; which solves a number of discrete optimization problems using graph-based route planning, job scheduling and it extends Swarm Intelligence paradigms. …”
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  8. 8

    Designing and Developing an Intelligent Congkak by Muhammad Safwan, Mohd Shahidan

    Published 2011
    “…This issues can solved by programming the Congkak system based on previous work on Mancala and NN system, and then recording the performance of the related algorithm. …”
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  9. 9

    Bats echolocation-inspired algorithms for global optimisation problems by Nafrizuan, Mat Yahya

    Published 2016
    “…The aim of the research is to introduce novel form of swarm intelligence algorithms based on real echolocation behaviour of bats. …”
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  10. 10

    Experimental analysis of firefly algorithms for divisive clustering of web documents by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

    Published 2014
    “…This paper studies two clustering algorithms that are based on the Firefly Algorithm (FA) which is a recent swarm intelligence approach.We perform experiments utilizing the Newton’s Universal Gravitation Inspired Firefly Algorithm (GFA) and Weight-Based Firefly Algorithm (WFA) on the 20_newsgroups dataset.The analysis is undertaken on two parameters.The first is the alpha (α) value in the Firefly algorithms and latter is the threshold value required during clustering process. …”
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  11. 11

    Malaysia Constitutional Law System, Study On The Use Advanced Searching Algorithm (Rule-Based And Horspool Algorithm) by Abd Razak, Nuur Farhani

    Published 2017
    “…In this research, we study about the concept of advanced searching algorithm to build an intelligent web based system. …”
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    Nature-inspired parameter controllers for ACO-based reactive search by Sagban, Rafid, Ku-Mahamud, Ku Ruhana, Abu Bakar, Muhamad Shahbani

    Published 2015
    “…This study proposes machine learning strategies to control the parameter adaptation in ant colony optimization algorithm, the prominent swarm intelligence metaheuristic.The sensitivity to parameters’ selection is one of the main limitations within the swarm intelligence algorithms when solving combinatorial problems.These parameters are often tuned manually by algorithm experts to a set that seems to work well for the problem under study, a standard set from the literature or using off-line parameter tuning procedures. …”
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    Product assembly and disassembly sequence optimization based on genetic algorithm and design for assembly methodologies by Yasin, Azman, Puteh, Nurnasran, Daud, Ruslizam

    Published 2009
    “…In this paper, an Artificial Intelligence (AI) technique, namely Genetic Algorithm (GA) is proposed to optimize product components assembly and disassembly sequences.The proposed methodology is developed and tested on an industrial product made of plastics with no integrated assembly and permanent joint parts.GA method is applied to determine the accuracy and optimum results based on 20 assembly and disassembly sequence solutions that was generated by the Design for Assembly methodology.The results indicated that GA based approach is able to obtain a near optimal solution for assembly and disassembly sequences.…”
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  17. 17

    Natural-based underwater image color enhancement through fusion of swarm-intelligence algorithm by Kamil Zakwan, Mohd Azmi, Ahmad Shahrizan, Abdul Ghani, Zulkifli, Md. Yusof, Zuwairie, Ibrahim

    Published 2019
    “…Through the fusion of swarm intelligence algorithm, the mean values of inferior color channels are adjusted to be closed to the mean value of superior color channel. …”
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  18. 18

    A Survey of Stochastic processes in Wireless Sensor Network: a Power Management Prospective by Ul haq, Riaz, Norrozila, Sulaiman, Muhammad, Alam

    Published 2013
    “…This survey is focusing on the stochastic process based power management algorithms for the WSN field. …”
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  19. 19

    Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield. by Md. Sap, Mohd. Noor, Awan, A. Majid

    Published 2005
    “…Intelligent systems based on machine learning techniques, such as classification, clustering, are gaining wide spread popularity in real world applications. …”
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  20. 20

    Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management by Julius, Beneoluchi Odili, M. N. M., Kahar, Noraziah, Ahmad, M., Zarina, Riaz, Ul Haq

    Published 2017
    “…After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and Firefly Algorithm) in solving the 60 popular and complex benchmark symmetric Travelling Salesman’s optimization problems out of the total 118 as well as all the 18 asymmetric Travelling Salesman’s Problems test cases available in TSPLIB91. …”
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