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  1. 1
    Parallel distributed genetic algorithm development based on microcontrollers framework

    Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

    Published 2023
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  2. 2
    Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage

    Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage by Nor Azlina, Ab. Aziz, Zuwairie, Ibrahim, Kamarulzaman, Ab Aziz, Nor Hidayati, Abdul Aziz

    Published 2019
    “…It had been successfully used for optimization of many engineering problems. …”
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  3. 3
    Vector Evaluated Gravitational Search Algorithm (VEGSA) for multi-objective optimization problems

    Vector Evaluated Gravitational Search Algorithm (VEGSA) for multi-objective optimization problems by Zuwairie, Ibrahim, Badaruddin, Muhammad, Kamarul Hawari, Ghazali, Lim, Kian Sheng, Sophan Wahyudi, Nawawi, Zulkifli, Md. Yusof

    Published 2012
    “…This paper presents a novel algorithm, which is based on Gravitational Search Algorithm (GSA), for multiobjective optimization problems. …”
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  4. 4
    Improved expectation maximization algorithm for Gaussian mixed model using the kernel method

    Improved expectation maximization algorithm for Gaussian mixed model using the kernel method by Mohd Yusoff, Mohd Izhan, Mohamed, Ibrahim, Abu Bakar, Mohd Rizam

    Published 2013
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  5. 5
    Pre-emptive resource-constrained multimode project scheduling using genetic algorithm: a dynamic forward approach

    Pre-emptive resource-constrained multimode project scheduling using genetic algorithm: a dynamic forward approach by Delgoshaei, Aidin, Mohd Ariffin, Mohd Khairol Anuar, Baharudin, B. T. Hang Tuah

    Published 2016
    “…For this purpose, a Genetic Algorithm is applied to solve.Findings: The findings show that the proposed method is an effective way to maximize NPV in MRCPSP-DCF problems while activity splitting is allowed. …”
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  6. 6
    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Clustering is one of the means in data mining of predicting the class based on separating the data categories from similar features. Expectation maximization (EM) is one of the representatives clustering algorithms which have broadly applied in solving classification problems by improving the density of data using the probability density function. …”
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  7. 7
    Hybrid multi-objective optimization methods for in silico biochemical system production

    Hybrid multi-objective optimization methods for in silico biochemical system production by Mohd Arfian, Ismail

    Published 2016
    “…The use of Newton method is for dealing with biochemical system, Strength Pareto approach is for the multi-objective problem, GA is to maximize the production, and CooCA is to minimize the total component concentrations involved. …”
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  8. 8
    A new approach for optimum DG placement and sizing based on voltage stability maximization and minimization of power losses

    A new approach for optimum DG placement and sizing based on voltage stability maximization and minimization of power losses by Aman, M.M., Jasmon, G.B., Bakar, A.H.A., Mokhlis, Hazlie

    Published 2013
    “…Particle Swarm Optimization (PSO) algorithm is used in this paper to solve the multi-objective problem. …”
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  9. 9
    Using artificial intelligence search in solving the camera placement problem

    Using artificial intelligence search in solving the camera placement problem by Altahir, A.A., Asirvadam, V.S., Hamid, N.H.B., Sebastian, P.

    Published 2022
    “…Two case studies are used to evaluate those algorithms, and the camera placement problem is formulated as a coverage maximization problem. …”
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  10. 10
    Shuffled Frog Leaping Algorithm (SFLA) for solving profit based unit commitment problem / Nurul Izzati Mohd Hanapiah

    Shuffled Frog Leaping Algorithm (SFLA) for solving profit based unit commitment problem / Nurul Izzati Mohd Hanapiah by Mohd Hanapiah, Nurul Izzati

    Published 2016
    “…This thesis presents the Shuffled Frog Leaping Algorithm (SFLA) technique is used to solve the Profit Based Unit Commitment Problem (PBUCP). …”
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  11. 11
    Performance Evaluation of Vector Evaluated Gravitational Search Algorithms Based on ZDT Test Functions

    Performance Evaluation of Vector Evaluated Gravitational Search Algorithms Based on ZDT Test Functions by Badaruddin, Muhammad, Zuwairie, Ibrahim, Kamarul Hawari, Ghazali, Mohd Riduwan, Ghazali, Kian, Sheng Lim, Sophan Wahyudi, Nawawi, Nor Azlina, Ab. Aziz, Marizan, Mubin, Norrima, Mokhtar

    Published 2014
    “…The VEGSA algorithms use a number of populations of particles. …”
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  12. 12
    Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari

    Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari by Mohammed , Heydari

    Published 2017
    “…An improved particle swarm algorithm (HPSOGA) is used to solve complex problems of water resources optimization. …”
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  13. 13
    Performance evaluation of vector evaluated gravitational search algorithm II

    Performance evaluation of vector evaluated gravitational search algorithm II by Muhammad, B., Ibrahim, Z., Ghazali, K.H., Ghazali, M.R., Mubin, M., Mokhtar, M.

    Published 2014
    “…The VEGSAII algorithm uses a number of populations of particles. …”
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  14. 14
    Indoor comfort and energy consumption optimization using an inertia weight artificial bee colony algorithm

    Indoor comfort and energy consumption optimization using an inertia weight artificial bee colony algorithm by Farah Nur Arina, Baharudin, Nor Azlina, Ab. Aziz, Mohamad Razwan, Abdul Malek, Anith Khairunnisa, Ghazali, Zuwairie, Ibrahim

    Published 2022
    “…Comfort level maximization and energy consumption minimization are optimization problems. …”
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  15. 15
    Indoor comfort and energy consumption optimization using an inertia weight artificial bee colony algorithm

    Indoor comfort and energy consumption optimization using an inertia weight artificial bee colony algorithm by Farah Nur Arina, Baharudin, Nor Azlina, Ab. Aziz, Mohamad Razwan, Abdul Malek, Anith Khairunnisa, Ghazali, Zuwairie, Ibrahim

    Published 2022
    “…Comfort level maximization and energy consumption minimization are optimization problems. …”
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  16. 16
    Development of optimization Alghorithm for uncertain non-linear dynamical system

    Development of optimization Alghorithm for uncertain non-linear dynamical system by Abdul Aziz, Mohd. Ismail, Yaacob, Nazeeruddin, Mohd. Said, Norfarizan, Hamzah, Nor Hazadura

    Published 2004
    “…Algorithms used to solve these problems are expected to satisfy the objectives consistently and since time translates into cost, must also be fast. …”
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  17. 17
    Efficient radio resource management algorithms for downlink long term evolution networks

    Efficient radio resource management algorithms for downlink long term evolution networks by Mamman, Maharazu

    Published 2018
    “…The algorithm is based on the idea of the optimization problem in which resource allocation problem is formulated as an optimization problem. …”
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  18. 18
    Multi-objective constrained algorithm (MCA) and non-dominated sorting genetic algorithm (NSGA-ii) for solving multi-objective crop planning problem

    Multi-objective constrained algorithm (MCA) and non-dominated sorting genetic algorithm (NSGA-ii) for solving multi-objective crop planning problem by Jarin, Sams, Khatun, Mst Khaleda, Shafie, Amir Akramin

    Published 2016
    “…In this paper, we formulate a crop planning problem as a multiobjective optimization model and try to solve two different versions of the problem using two different optimization algorithms MCA and NSGA. …”
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  19. 19
    Influence maximization towards target users on social networks for information diffusion

    Influence maximization towards target users on social networks for information diffusion by Temitope, Olanrewaju Abdus-Samad, Ahmad, Rahayu, Mahmuddin, Massudi

    Published 2018
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  20. 20
    Evaluation and optimization of frequent, closed and maximal association rule based classification

    Evaluation and optimization of frequent, closed and maximal association rule based classification by Mohd Shaharanee, Izwan Nizal, Hadzic, Fedja

    Published 2014
    “…Real world applications of association rule mining have well-known problems of discovering a large number of rules, many of which are not interesting or useful for the application at hand.The algorithms for closed and maximal item sets mining significantly reduce the volume of rules discovered and complexity associated with the task, but the implications of their use and important differences with respect to the generalization power, precision and recall when used in the classification problem have not been examined.In this paper, we present a systematic evaluation of the association rules discovered from frequent, closed and maximal item set mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriate sequence of usage.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data/items, and detailed evaluation of rule sets is provided as a whole and w.r.t individual classes. …”
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