Search Results - (( parameter optimization method algorithm ) OR ( pattern design modelling algorithm ))

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  1. 1

    Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm by Farzin, Saeed, Singh, Vijay, Karami, Hojat, Farahani, Nazanin, Ehteram, Mohammad, Kisi, Ozgur, Allawi, Mohammed Falah, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

    Published 2018
    “…A common hydrologic method of flood routing is the Muskingum method. The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). …”
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    Article
  2. 2

    Computational dynamic support model for social support assignments around stressed individuals among graduate students by Al-Shorman, Roqia Rateb

    Published 2020
    “…Hence, this study aims to develop the dynamic configuration algorithm to provide an optimal support assignment based on information generated from both social support recipient and provision computational models. …”
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    Thesis
  3. 3

    Optimization and prediction of battery electric vehicle driving range using adaptive fuzzy technique by Abulifa, Abdulhadi Abdulsalam

    Published 2022
    “…The study also developed an algorithm for predictive EMS using fuzzy model predictive control technique based on regression algorithm. …”
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    Thesis
  4. 4

    Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network by Sivarao, Subramonian

    Published 2009
    “…The model was then fed with new sets of machining parameters to experimentally validate the model’s ability in predicting the cut quality. …”
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    Article
  5. 5

    Enhancing reservoir simulation models with genetic algorithm optimized neural networks across diverse climatic zones / Saad Mawlood Saab by Saad Mawlood , Saab

    Published 2025
    “…The optimizer algorithm (i.e., GA) determines the optimal input variables and internal parameters in the prediction models. …”
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    Thesis
  6. 6

    Distributed joint power control, beamforming and spectrum leasing for cognitive two-way relay networks by Iranpanah, Havzhin

    Published 2017
    “…A search method with numerous advantages over conventional algorithms, has been designed to solve the optimization problems with an enhanced global optimality and convergence speed. …”
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    Thesis
  7. 7

    Improving neural networks training using experiment design approach by Chong, Wei Kean

    Published 2005
    “…This data is selected by two methods: random and Experiment Design Approach (D-optimal and Maxmin Distance). …”
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    Thesis
  8. 8

    Enhancing time series prediction with Hybrid AFSA-TCN: A unified approach to temporal data and optimization by Nur Alia Shahira, Mohd Zaidi, Zuriani, Mustaffa, Muhammad Arif, Mohamad

    Published 2025
    “…The study introduces a hybrid model that integrates TCN with Artificial Fish Swarm Algorithm (AFSA), a bio-inspired optimization technique designed to fine-tune TCN parameters. …”
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    Article
  9. 9

    Chemometric approaches in the evaluation of trace metals in commercially raised tilapia and preliminary health risk assessment of its consumption / Low Kah Hin by Low, Kah Hin

    Published 2012
    “…The most significant microwave parameters were further evaluated by Box–Behnken design, while others were kept constant. …”
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    Thesis
  10. 10

    Development of switchable planar reflectors for beam shaping realization by Abbasi, Muhammad Inam

    Published 2016
    “…A comprehensive mathematical model based on Finite Element Method (FEM) was proposed for progressive phase distribution to develop a novel design technique to create a reconfigurable reflectarray antenna based on strategic slot configurations. …”
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    Thesis
  11. 11

    Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

    Published 2025
    “…The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
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    Thesis
  12. 12

    Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

    Published 2008
    “…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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    Undergraduates Project Papers
  13. 13

    Mathematical modelling and hybrid ACO-PSO technique for PV performance improvement by Ali Mahmood, Humada

    Published 2016
    “…Secondly, a hybrid Ant Colony Optimisation-Particle Swarm Optimisation (ACO-PSO) algorithm was proposed to optimally determine the MPPT parameters. …”
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    Thesis
  14. 14

    Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis by Asrul, Adam

    Published 2018
    “…The efficiency of the three algorithms are evaluated and compared with previous results obtained by other optimization methods on similar studies. …”
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    Conference or Workshop Item
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    Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization by Nur Iffah, Mohamed Azmi

    Published 2014
    “…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
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    Thesis
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    Optimization of turning parameters using ant colony optimization by Mohamad Nazri, Semoin

    Published 2008
    “…The project objectives are to develop Ant Colony Optimization (ACO) algorithm for CNC turning process and to optimize turning parameters for minimized production cost per unit. …”
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    Undergraduates Project Papers
  17. 17

    Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail by Foo, Fong Yeng, Lau, Gee Choon, Ismail, Zuhaimy

    Published 2014
    “…Trial and error often serves as the best method to determine the parameter. Therefore, a good optimization technique is required for identify the best parameter in minimizing the forecast errors. …”
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    Research Reports
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    Application Of Genetic Algorithms For Robust Parameter Optimization by Belavendram, N.

    Published 2010
    “…Genetic algorithms (GA) are fairly recent in this respect but afford a novel method of parameter optimization. …”
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    Article
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