Search Results - (( using optimization method algorithm ) OR ( case selection process algorithm ))

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  1. 1

    Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

    Published 2018
    “…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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  2. 2

    Product assembly sequence optimization based on genetic algorithm by Yasin, Azman, Puteh, Nurnasran, Daud, Ruslizam, Omar, Mazni, Syed-Abdullah, Sharifah Lailee

    Published 2010
    “…Genetic algorithm (GA) is a search technique used in computing to find approximate solution to optimization and search problem based on the theory of natural selection. …”
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    Article
  3. 3

    Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach by Pourdaryaei, Alireza, Mokhlis, Hazlie, Illias, Hazlee Azil, Kaboli, S. Hr. Aghay, Ahmad, Shameem

    Published 2019
    “…In addition, to prove the superiority of the proposed hybrid forecasting method the simulation results obtained using ANN and ANFIS models optimized by other well-known optimization methods have been compared with that of proposed method. © 2019 IEEE.…”
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    Article
  4. 4

    Optimizing the placement of fire department in Kulim using greedy heuristic and simplex method / Muhammad Abu Syah Mohd Suzaly by Mohd Suzaly, Muhammad Abu Syah

    Published 2023
    “…The first method is greedy heuristic method. Greedy heuristics is a type of optimization algorithm that makes decisions based on locally optimal solutions. …”
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  5. 5

    Regression test case selection & prioritization using dependence graph and genetic algorithm by Musa, Samaila, Md Sultan, Abu Bakar, Abd Ghani, Abdul Azim, Baharom, Salmi

    Published 2014
    “…The approach is based on optimization of selected test case from dependency analysis of the source codes. …”
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    A genetic algorithm to minimise the maximum lateness on a single machine family scheduling problem by Lee, Lai Soon, Nazif, Habibeh

    Published 2009
    “…The OCGA is compared with other well known local search method namely dynamic length tabu search, randomised steepest descent method, and other variants of genetic algorithms using extensive data sets collected from the literatures. …”
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    Taguchi's T-method with nearest integer-based binary bat algorithm for prediction by Marlan Z.M., Jamaludin K.R., Ramlie F., Harudin N.

    Published 2023
    “…In this paper, a swarm-based binary bat optimization algorithm with a nearest integer discretization approach is integrated with the Taguchi�s T-method. …”
    Article
  10. 10

    A fuzzy case-based reasoning model for software requirements specifications quality assessment by Mostafa S.A., Gunasekaran S.S., Khaleefah S.H., Mustapha A., Jubair M.A., Hassan M.H.

    Published 2023
    “…Additionally, for efficient cases retrieval in the CBR, relevant cases selection and nearest cases selection heuristic search algorithms are used in the system. …”
    Article
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    Energy-Efficient Low-Complexity Algorithm in 5G Massive MIMO Systems by Salh, Adeeb, Audah, Lukman, Abdullah, Qazwan, M. Shah, Nor Shahida, A. Hamzah, Shipun, Nordin, Shahilah, Farah, Nabil

    Published 2021
    “…This formulates the optimization problem of joint optimal antenna selection, transmits power allocation and joint user selection to mitigate inter-cellinterference in downlink multi-cell massiveMIMO systems under minimized reuse of pilot sequences based on a novel iterative low-complexity algorithm (LCA) for Newton’s methods and Lagrange multipliers. …”
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    Multi-objective scientific workflow scheduling algorithm in multi-cloud environment for satisfying QoS requirements by Ramadhan, Mazen Farid Ebrahim

    Published 2022
    “…Moreover, the improvements of different QoS metrics values achieved by using a minimum-weight-based multi-objective algorithm (MOS-MWO) for scheduling scientific workflows are better than those of the previous work which used the Pareto optimization method. …”
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  16. 16

    Detection of corneal arcus using rubber sheet and machine learning methods by Ramlee, Ridza Azri

    Published 2019
    “…The benchmark of the classification algorithm for CA is needed to analyze the optimal output of the algorithm. …”
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  17. 17

    Neural Network Model and Finite Element Simulation of Spring back in Plane-Strain Metallic Beam Bending by Abu Khadra, Fayiz Y. M.

    Published 2006
    “…The training data required to train the two-metamodeling techniques were generated using a verified nonlinear finite element algorithm developed in the current research. …”
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  18. 18

    An enhanced supplier selection model based on optimized analytic network process towards sustainable information technology outsourcing by Fusiripong, Prashaya

    Published 2022
    “…Essentially, ITO is a complex process in which selecting the right supplier involves evaluation of multi criteria. …”
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  19. 19

    Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

    Published 2015
    “…Several algorithms, methods and spreadsheets are being proposed by various researchers in this field to improve materials selection. …”
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  20. 20

    Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

    Published 2018
    “…Also, six techniques: Ant Colony Optimization (ACO), Gain Ratio (GR), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), Random forest (RF), and Correlation-based Feature Selection (CFS) were used for the feature selection. …”
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