Search Results - (( _ optimisation method algorithm ) OR ( using (evolutionary OR evolution) method algorithm ))

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  1. 1

    Sensitivity analysis of GA parameters for ECED problem by Kamil K., Razali N.M.M., Teh Y.Y.

    Published 2023
    Subjects: “…Genetic algorithms…”
    Conference paper
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    A review: Use of evolutionary algorithm for optimisation of machining parameters by Zolpakar, N. A., Mohd Fuad, Yasak, Pathak, Sunil

    Published 2021
    “…Lately, evolutionary algorithm, statistical approaches such as genetic algorithm (GA), particle swarm optimisation (PSO), and cuckoo search algorithm (CSA) have been utilised in simultaneous optimisation of the parameters of the desired outputs and its great potential in optimising machining processes is recognisable.…”
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    Article
  4. 4

    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse) by Jia, Xing Yeoh, Chuii, Khim Chong, Mohd Saberi, Mohamad, Yee, Wen Choon, Lian, En Chai, Safaai, Deris, Zuwairie, Ibrahim

    Published 2015
    “…The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimisation method implemented to obtain the best kinetic parameter value. …”
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  5. 5

    Optimized Cover Selection for Audio Steganography Using Multi-Objective Evolutionary Algorithm by Noor Azam, Muhammad Harith, Ridzuan, Farida, Mohd Sayuti, M Norazizi Sham

    Published 2023
    “…One of the search methods commonly used to find solutions for the trade-off problem in various fields is the Multi-Objective Evolutionary Algorithm (MOEA). …”
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  6. 6

    Dual-head marking performance optimisation via evolutionary solutions by Koh J., Tiong S.K., Aris I.B., Mahmoud S.

    Published 2023
    “…This paper presents a new approach to optimise the performance of a multi-head marking system in terms of its marking speed This processing method named as MMA (Molecular Marking Optimisation algorithm) will adopt the use of Genetic Algorithm. …”
    Conference paper
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    Optimisation of neural network with simultaneous feature selection and network prunning using evolutionary algorithm by WK Wong, Ali Chekima, Wong, Kii Ing, Law, Kah Haw, Lee, Vincent

    Published 2015
    “…Most advances on the Evolutionary Algorithm optimisation of Neural Network are on recurrent neural network using the NEAT optimisation method. …”
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  8. 8

    Modelling of biogas production process with evolutionary artificial neural network and genetic algorithm by Fakharudin, Abdul Sahli

    Published 2017
    “…The application of artificial neural network (ANN) to generate the production model is used to improve the modelling accuracy. The model output optimisation by genetic algorithm (GA) produces higher biogas production compared to the optimisation using statistical methods. …”
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    Thesis
  9. 9

    Optimisation of PID controller for load frequency control in two-area power system using evolutionary particle swarm optimisation by Illias, Hazlee Azil, Zahari, A.F.M., Mokhlis, Hazlie

    Published 2016
    “…Hence, by implementing an optimisation method, the performance of the LFC can be optimised through optimising the PID controller parameters.…”
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  10. 10

    An improvement of back propagation algorithm using halley third order optimisation method for classification problems by Abdul Hamid, Norhamreeza

    Published 2020
    “…This algorithm utilises first order optimisation method namely Gradient Descent (GD) method which attempts to minimise the error of network. …”
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    Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation by Illias, Hazlee Azil, Wee, Zhao Liang

    Published 2018
    “…Dissolved Gas Analysis (DGA) technique is commonly used to identify oil-filled power transformer fault type but utilisation of artificial intelligence method with optimisation methods has shown convincing results. …”
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    Article
  12. 12

    Optimisation of automatic generation control performance in two-area power system with pid controllers using mepso / Lu Li by Lu , Li

    Published 2018
    “…The AGC in two-area power system was constructed and simulated by using MATLAB R2017b software. From the simulation results, it was found that with the same number of PID controllers, the performance of AGC optimised by using MEPSO-TVAC algorithm is better in terms of overshoot and fitness value than using EPSO and PSO algorithms. …”
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    Optimization of zinc oxide surge arrester design in reducing leakage current / Nurul Ain Abdul Latiff by Nurul Ain , Abdul Latiff

    Published 2018
    “…Evolutionary computation methods, imperialist competitive algorithm (ICA) and gravitational search algorithm (GSA) were employed to optimise the arrester designs, which can minimise the leakage current. …”
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    Social spider optimisation algorithm for dimension reduction of electroencephalogram signals in human emotion recognition by Al-Qammaz, Abdullah Yousef, Ahmad, Farzana Kabir, Yusof, Yuhanis

    Published 2018
    “…Due to some limitations of current heuristics and evolutionary algorithms, this paper proposed a new swarm based algorithm for feature selection method called Social Spider Optimization (SSO-FS). …”
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    Differential evolution algorithm for linear frequency modulation radar signal denoising by Al-Dabbagh, Mohanad Dawood Hasan, Raja Abdullah, Raja Syamsul Azmir, Al-Dabbagh, Rawaa Dawoud Hassan, Hashim, Fazirulhisyam

    Published 2013
    “…These factors influence the output signal voltage, thus creating detectable noise. Differential Evolution (DE) is an effectual, competent, and robust optimisation method used to solve different problems in the engineering and scientific domains, such as in signal processing. …”
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    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

    Published 2023
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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