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  1. 1

    Strategies of Handling Different Variables Reduction for LDA by Hamid, Hashibah, Mahat, Nor Idayu

    Published 2012
    “…This paper discusses the strategy of conducting variable reduction processes such that they contribute to optimise the performance of linear discriminant analysis (LDA). …”
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  2. 2

    Enhancing Harmony Search Metaheuristic Algorithm for Coverage Efficiency, Test Suite Reduction, and Running Time in Combinatorial Interaction Testing by Muazu, Aminu Aminu, Hashim, Ahmad Sobri

    Published 2025
    “…The experimental results demonstrate that eHS outperforms the other algorithms for CIT in terms of coverage efficiency and test suite reduction. …”
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  3. 3

    Minimizing power loss using modified artificial bee colony algorithm / Nur Azlin Ashiqin Mohd Amin ...[et al.] by Mohd Amin, Nur Azlin Ashiqin, Jamaluddin, Siti Hafawati, Muhammat Pazil, Nur Syuhada, Mahmud, Norwaziah, Kimpol, Norhanisa

    Published 2021
    “…Generator bus voltages, transformer tap positions, and settings of switched shunt of compensators are used as decision variables to control the reactive power flow. These control variable values are adjusted for loss reduction. …”
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  4. 4

    Thin Film Roughness Optimization In The Tin Coatings Using Genetic Algorithms by Fauzi, Nur Faiqah, Mohamad Jaya, Abdul Syukor, Mohammad Jarrah, Mu’ath Ibrahim, Akbar, Habibullah

    Published 2017
    “…In order to represent the process variables and coating roughness, a quadratic polynomial model equation was developed. …”
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  5. 5

    The Improvement of the Image by Using MATLAB by Hariza, Haimi

    Published 2006
    “…Image enhancement through noise reduction is a fundamental problem in image processing. …”
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    Final Year Project Report / IMRAD
  6. 6

    Modeling And Optimization Of Physical Vapour Deposition Coating Process Parameters For Tin Grain Size Using Combined Genetic Algorithms With Response Surface Methodology by Mohamad Jaya, Abdul Syukor, Muhamad, Mohd Razali, Abd Rahman, Md Nizam, Mohammad Jarrah, Mu'ath Ibrahim, Hasan Basari, Abd Samad

    Published 2015
    “…Additionally,analysis of variance(ANOVA) was used to determine the significant factors influencing resultant TiN coating grain size.Based on that,a quadratic polynomial model equation was developed to represent the process variables and coating grain size.Then,in order to optimize the coating process parameters, genetic algorithms (GAs) were combined with the RSM quadratic model and used for optimization work.Finally,the models were validated using actual testing data to measure model performances in terms of residual error and prediction interval (PI).The result indicated that for RSM,the actual coating grain size of validation runs data fell within the 95% (PI) and the residual errors were less than 10 nm with very low values, the prediction accuracy of the model is 96.09%.In terms of optimization and reduction the experimental data,GAs could get the best lowest value for grain size then RSM with reduction ratio of ≈6%, ≈5%, respectively.…”
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  7. 7
  8. 8

    Fast adaptive motion estimation search algorithm for H.264 encoder by Patwary, Md Anwarul Kaium

    Published 2012
    “…Simulation result shows that as compared to previous research, this algorithm achieves up to average 60% reduction in motion estimation time without degrading the video quality.…”
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    Thesis
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    Low Complexity Error Correction in Low Density Parity Check (LDPC) Code Decoder and Encoder for Decode and Forward Cooperative Wireless Communication by JAM'AAH, SUUD

    Published 2021
    “…This algorithm only applies the optimization scaling factor at the bit node processing of the variable node operation. …”
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  12. 12

    Analysis of Traffic Accident Patterns Using Association Rule Mining by Yudy, Pranata, Tri Basuki, Kurniawan, Edi Surya, Negara, Ahmad Haidar, Mirza

    Published 2024
    “…The application of the apriori algorithm facilitated the identification of frequent itemsets and rules that reveal patterns across accident variables, such as road conditions, road functions, accident types, weather conditions, and victim statuses. …”
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  13. 13

    Model input and structure selection in multivariable dynamic modeling of batch distillation column pilot plant / Ilham Rustam by Rustam, Ilham

    Published 2015
    “…The pilot plant used as reference process platform in this study is a binary mixture, batch process bubble cap distillation column that suffers from the time-varying nature of its process. …”
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  14. 14

    Modeling of flood water level prediction using NNARX / Fazlina Ahmat Ruslan by Ahmat Ruslan, Fazlina

    Published 2015
    “…The pilot plant used as reference process platform in this study is a binary mixture, batch process bubble cap distillation column that suffers from the time-varying nature of its process. …”
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  15. 15

    Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management by almahameed, Bader aldeen, Bisharah, Majdi

    Published 2024
    “…Particle Swarm Optimization (PSO) has demonstrated its efficacy in addressing the issue of construction waste reduction and enhancing the accuracy of cost estimation through the identification of optimal combinations of variables. …”
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  16. 16

    Cost reduction in bottom-up hierarchical-based VLSI floorplanning designs by Hoo, C.S., Kanesan, J., Ramiah, H.

    Published 2015
    “…From the industrial perspective, floorplanning is a crucial step in the VLSI physical design process as its efficiency determines the quality and the time-to-market of the product. …”
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    Design of intelligent Qira’at identification algorithm by Kamarudin, Noraziahtulhidayu

    Published 2017
    “…The process of the SPAP Algorithm is to extend parameters of the Affine Projection Block with two different selections of windowing length that affect the final accuracy on pattern classification. …”
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  19. 19

    Intelligence Integration Of Particle Swarm Optimization And Physical Vapour Deposition For Tin Grain Size Coating Process Parameters by Abdul Syukor, Mohamad Jaya, Mu*ath Ibrahim, Mohammad Jarrah, Mohd Asyadi Azam, Mohd Abid, Mohd Razali, Muhamad

    Published 2016
    “…Additionally,analysis of variance (ANOVA) was used to determine the significant factors influencing resultant TiN coating grain size.Based on that,a quadratic polynomial model equation was developed to represent the process variables and coating grain size.Then,in order to optimize the coating process parameters,genetic algorithms (GAs) were combined with the RSM quadratic model and used for optimization work.Finally,the models were validated using actual testing data to measure model performances in terms of residual error and prediction interval (PI).The result indicated that for RSM,the actual coating grain size of validation runs data fell within the 95% (PI) and the residual errors were less than 10 nm with very low values, the prediction accuracy of the model is 96.09%.In terms of optimization and reduction the experimental data,GAs could get the best lowest value for grain size then RSM with reduction ratio of ≈6%, ≈5%, respectively.…”
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    Article
  20. 20

    Switching Time Optimization via Time Optimal Control for Natural Gas Vehicle Refueling by Mahidzal Dahari, Mahidzal

    Published 2007
    “…In this thesis, a refueling algorithm using Time Optimal Control (TOC) technique is proposed as a basis for determining the optimal switching time in NGV refueling using the mass and mass flowrate as the state variables, measured using Coriolis flowmeter. …”
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