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  1. 1
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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  2. 2
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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  3. 3
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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  4. 4
    Development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory

    Development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory by Rusli, Julie Roslita

    Published 2011
    “…The algorithms used in this generator are based on March algorithm. …”
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  5. 5
    Genetic Algorithm for Forecasting Bioinformatic Outcomes of Mutation-induced Cowpeas for Sustainable Development

    Genetic Algorithm for Forecasting Bioinformatic Outcomes of Mutation-induced Cowpeas for Sustainable Development by Kehinde, Okewu, Emmanuel, Okewu, Wong, Ling Shing, Siti Sarah, Maidin

    Published 2023
    “…To demonstrate the practicality of using artificial intelligence (AI) to address these problems, the genetic algorithm is applied to genetic engineering (genetic mutation) of cowpea in a crop improvement program to generate useful bioinformatic information for further improvement of the crop. …”
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  6. 6
    Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots

    Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots by Hanafi Ahmad Hijazi, Patricia Anthony

    Published 2006
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  7. 7
    Development of efficient t-way test data generation algorithm and execution strategies

    Development of efficient t-way test data generation algorithm and execution strategies by Khandakar Fazley, Rabbi

    Published 2012
    “…An executable prototype tool is also developed for auto test execution besides efficient test data generation. …”
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  8. 8
    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing

    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

    Published 2015
    “…Genetic Algorithm (GA), Ant Colony (AC), Simulated Annealling (SA), Particle Swarm Optimization, and Harmony Search Algorithm (HS) as their basis in an effort to generate the most optimal solution. …”
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  9. 9
    Sequence t-way test generation using the barnacles mating optimizer algorithm

    Sequence t-way test generation using the barnacles mating optimizer algorithm by Kamal Z., Zamli, Kader, Md. Abdul

    Published 2021
    “…More precisely, we focus on the generation of test cases due to the ordering of inputs (or sequence) using the newly developed Barnacles Mating Optimizer (BMO) Algorithm. …”
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  10. 10
    Backtracking search algorithm for optimal power dispatch in power system / Mostafa Modiri Delshad

    Backtracking search algorithm for optimal power dispatch in power system / Mostafa Modiri Delshad by Mostafa, Modiri Delshad

    Published 2016
    “…The goal is to determine the most optimal power sharing among the generating units in a power system. The practical power dispatch problems consider the technical operating constraints of generators such as ramp-up and ramp-down limits, lower and upper limits of generators, and prohibited operating zones. …”
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  11. 11
    A test case generation framework based on UML statechart diagram

    A test case generation framework based on UML statechart diagram by Salman, Yasir Dawood

    Published 2018
    “…Furthermore, the algorithms used for test case generation are not provided or well described. …”
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  12. 12
    Benchmark simulator with dynamic environment for job scheduling in grid computing

    Benchmark simulator with dynamic environment for job scheduling in grid computing by Ku-Mahamud, Ku Ruhana

    Published 2014
    “…Characteristics of jobs and resources to be used in evaluating the performance of the scheduling algorithm must reflect the dynamic nature of real grid environment.Static models of jobs and resources cannot be used to generate jobs and resources in simulating the grid environment because of the dynamic nature of the grid.This paper presents a new graph representation of jobs and resources which is practical for hybrid metaheuristic model implementation such as ant colony optimization and genetic algorithm.A dynamic model that can generate jobs and resources similar to the jobs and resources in the real grid environment is also proposed.Jobs and resources may join in or drop out from the grid.Stochastic analysis is performed on the characteristics of jobs and resources.A simulator based on the dynamic expected time to compute, has been developed and can be used as a benchmark.The simulator can generate jobs and resources with the characteristics of jobs and resources in the real grid environment.This will facilitates the evaluation of dynamic job scheduling algorithm.…”
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  13. 13
    Effort Estimation Model for Function Point Measurement

    Effort Estimation Model for Function Point Measurement by Koh, Tieng Wei

    Published 2007
    “…This research work has generated an algorithmic effort estimation model for function points measurement. …”
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  14. 14
    PhABC: A Hybrid Artificial Bee Colony Strategy for Pairwise test suite Generation with Constraints Support

    PhABC: A Hybrid Artificial Bee Colony Strategy for Pairwise test suite Generation with Constraints Support by Alazzawi, A.K., Rais, H.M., Basri, S., Alsariera, Y.A.

    Published 2019
    “…Pairwise testing is one of a powerful Combinatorial Testing Technique (CTT) that used widely for test data generation. Various existing research works were developed using a meta-heuristic algorithm as a basis for pairwise testing strategies. …”
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  15. 15
    PhABC: A Hybrid Artificial Bee Colony Strategy for Pairwise test suite Generation with Constraints Support

    PhABC: A Hybrid Artificial Bee Colony Strategy for Pairwise test suite Generation with Constraints Support by Alazzawi, A.K., Rais, H.M., Basri, S., Alsariera, Y.A.

    Published 2019
    “…Pairwise testing is one of a powerful Combinatorial Testing Technique (CTT) that used widely for test data generation. Various existing research works were developed using a meta-heuristic algorithm as a basis for pairwise testing strategies. …”
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  16. 16
    Software product line test list generation based on harmony search algorithm with constraints support

    Software product line test list generation based on harmony search algorithm with constraints support by Alsewari, Abdulrahman A., Kabir, M. Nomani, Kamal Z., Zamli, Alaofi, Khalid S.

    Published 2019
    “…Thus, the current study is aimed to develop a new SPL test list generation strategy based on Harmony Search (HS) algorithm, namely SPL-HS. …”
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  17. 17
    Monotone Fuzzy Rule Interpolation for Practical Modeling of the Zero-Order TSK Fuzzy Inference System

    Monotone Fuzzy Rule Interpolation for Practical Modeling of the Zero-Order TSK Fuzzy Inference System by Kai Meng, Tay, Yi Wen, Kerk, Chee Peng, Lim

    Published 2022
    “…However, such a complete and monotone fuzzy rule-base is not always available in practice. In this article, we develop an MFRI modeling scheme for generating a monotone zero-order TSK FIS from a monotone and incomplete fuzzy rule-base. …”
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  18. 18
    A Hybrid ant colony optimization algorithm for solving a highly constrained nurse rostering problem

    A Hybrid ant colony optimization algorithm for solving a highly constrained nurse rostering problem by Ramli, Razamin, Abd Rahman, Rosshairy, Rohim, Nurdalila

    Published 2019
    “…Specifically, three main phases were involved in developing the hybrid model, which are generating an initial roster, updating the roster through the ACO algorithm, and implementing the hill climbing to further search for a refined solution. …”
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  19. 19
    Sustainable energy management: Artificial intelligence-based electricity consumption prediction in limited dataset environment for industry applications

    Sustainable energy management: Artificial intelligence-based electricity consumption prediction in limited dataset environment for industry applications by Chuan, Zun Liang, Tan, Lit Ken, Wee, Angel Chi Chyin, Yim Hin, Tham, Shao, Jie Ong, Jia, Yi Low, Chong, Yeh Sai

    Published 2024
    “…Electricity has been a key driver of global socioeconomic development and sustainability for both developed and developing nations. …”
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  20. 20
    Automatic generation of neural game controller using single and bi-objective evolutionary optimization algorithms for RTS Game

    Automatic generation of neural game controller using single and bi-objective evolutionary optimization algorithms for RTS Game by Chang, Kee Tong

    Published 2015
    “…In the last experiment, the results showed that DE and EP algorithms can generate superior controllers whilst PDE is only capable to generate sub-optimal controllers. …”
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