Search Results - (( evolution optimization using algorithm ) OR ( using factor _ algorithm ))

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  1. 1

    Optimal HE-PWM inverter switching patterns using differential evolution algorithm by Muhammad Ikram, Mohd Rashid, Hiendro, Ayong, Anwari, Makbul

    Published 2012
    “…The comparison of some common variants in the DE shows that all variants may generate the same precision results by using their best specific crossover rate and mutation factor values. …”
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    Conference or Workshop Item
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    A comprehensive comparison of evolutionary optimization limited by number of evaluations against time constraints by Jia, Hui Ong, Teo, Jason Tze Wi

    Published 2016
    “…Practically allevolutionary optimization studies have focused exclusively on the use of number of fitness evaluations as the constraining factor when comparing different evolutionary algorithms (EAs). …”
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    Article
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    Application Of Genetic Algorithms For Robust Parameter Optimization by Belavendram, N.

    Published 2010
    “…In this paper, a genetic algorithm is used to study a seven factor non-linear equation for a Wheatstone bridge as the equation to be optimized. …”
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    Article
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    Identification and predictive control of spray tower system using artificial neural network and differential evolution algorithm by Danzomo, Bashir A., Salami, Momoh Jimoh Eyiomika, Khan, Md. Raisuddin

    Published 2015
    “…The control process was implemented using MATLAB code by considering two DE optimization strategies; DE/best/1/bin and DE/rand/1/bin. …”
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    Proceeding Paper
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    LEMABE: a novel framework to Improve analogy-based software cost estimation using learnable evolution model by Dashti, Maedeh, Gandoman, Taghi Javdani, Adeh, Dariush Hasanpoor, Zulzalil, Hazura, Md Sultan, Abu Bakar

    Published 2021
    “…Then, MMRE, PRED (0.25), and MdMRE criteria have been used to evaluate and compare the proposed method against other evolutionary algorithms. …”
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    Article
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    Artificial neural controller synthesis for TORCS by Shi, Jun Long

    Published 2015
    “…As a conclusion, this research has shown that the DE hybrid FFNN algorithm and PDE hybrid FFNN algorithm are useful and promising in evolving autonomous car racing controller.…”
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    Thesis
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    Reservoir system modelling using nondominated sorting genetic algorithm in the framework of climate change by Nurul Nadrah Aqilah, Tukimat

    Published 2014
    “…In conclusion, this finding contributes toward the development of models using evolution algorithm and statistical methods for sustainable water resources planning and management in the context of future climate change…”
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    Thesis
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    Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

    Published 2018
    “…In the OGC framework, the exhibited explorative search behavior of the Gravitational Clustering (GC) algorithm has been addressed by (i) eliminating the agent velocity accumulation, and (ii) integrating an initialization method of agents using variance and median to subrogate the exploration process. …”
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    Thesis
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    Automated Student Timetable Scheduling System based on Genetic Algorithm by Amirul Azuani, Romlee, Noor Ain, Rosly, Meng, Chuan Haw

    Published 2019
    “…Genetic algorithm works based on natural evolutions that comprises of several iterations. …”
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    Article
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    Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

    Published 2016
    “…The rationale behind developing algorithms using real encoding of chromosome representations is the limitations of binary encoding. …”
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    Thesis
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    Optimal placement of unified power flow controller by dynamic implementation of system-variable-based voltage-stability indices to enhance voltage stability by Ahmad, S., Albatsh, F.M., Mekhilef, Saad, Mokhlis, Hazlie

    Published 2016
    “…Furthermore, to verify the suitability of the explored locations, a comparative study has been conducted after placing UPFC in the present locations and other locations obtained using optimization techniques like particle swarm optimization (PSO), differential evolution (DE), genetic algorithm (GA), and bacteria foraging algorithm (BFA). …”
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    Article
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    A refined differential evolution algorithm for improving the performance of optimization process by A. R., Yusoff, Nafrizuan, Mat Yahya

    Published 2011
    “…Various Artificial Intelligent (AI) algorithms can be applied in solving optimization problems. …”
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    Conference or Workshop Item
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    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

    Published 2006
    “…We presented hybrid genetic algorithm for optimizing weights as well as the topology of artificial neural networks, by introducing the concepts of Lamarckian and Baldwin evolution effects. …”
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    Article
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    Two level Differential Evolution algorithms for ARMA parameters estimatio by Salami, Momoh Jimoh Emiyoka, Tijani, Ismaila, Aibinu, Abiodun Musa

    Published 2013
    “…The first level searches for the appropriate model order while the second level computes the optimal/sub-optimal corresponding parameters. The performance of the algorithm is evaluated using both simulated ARMA models and practical rotary motion system. …”
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    Proceeding Paper
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    Hybrid algorithm for NARX network parameters' determination using differential evolution and genetic algorithm by Salami, Momoh Jimoh Eyiomika, Tijani, Ismaila, Isqeel , Abdullateef Ayodele, Aibinu, Abiodun Musa

    Published 2013
    “…A hybrid optimization algorithm using Differential Evolution (DE) and Genetic Algorithm (GA) is proposed in this study to address the problem of network parameters determination associated with the Nonlinear Autoregressive with eXogenous inputs Network (NARX-network). …”
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    Article
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    Crossover-first differential evolution for improved global optimization in non-uniform search landscapes by Teo, Jason Tze Wi, Mohd Hanafi Ahmad Hijazi, Hui, Keng Lau, Salmah Fattah, Aslina Baharum

    Published 2015
    “…The differential evolution (DE) algorithm is currently one of the most widely used evolutionary-based optimizers for global optimization due to its simplicity, robustness and efficiency. …”
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    Article
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