Search Results - addition _ differentiated evolutionary algorithm

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  1. 1

    Exploring dynamic self-adaptive populations in differential evolution by Teo, Jason Tze Wi

    Published 2006
    “…Although the Differential Evolution (DE) algorithm has been shown to be a simple yet powerful evolutionary algorithm for optimizing continuous functions, users are still faced with the problem of preliminary testing and hand-tuning of the evolutionary parameters prior to commencing the actual optimization process. …”
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    Article
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    Data driven hybrid evolutionary analytical approach for multi objective location allocation decisions: Automotive green supply chain empirical evidence by Doolun, Ian Shivraj, Ponnambalam, S. G., Subramanian, Nachiappan, Kanagaraj, G.

    Published 2018
    “…Data driven hybrid evolutionary analytical approach is proposed by integrating Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) to handle multiple objectives into Differential Evolution (DE) algorithm. …”
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    Article
  6. 6

    Forecasting solar power generation using evolutionary mating algorithm-deep neural networks by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2024
    “…This paper proposes an integration of recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) in optimizing the weights and biases of deep neural networks (DNN) for forecasting the solar power generation. …”
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  7. 7

    Artificial Neural Controller Synthesis in Autonomous Mobile Cognition by Kim On Chin, Jason Teo

    Published 2009
    “…This paper describes a new approach in using multi-objective evolutionary algorithms in evolving the neural network that acts as a controller for the phototaxis and radio frequency localization behaviors of a virtual Khepera robot simulated in a 3D, physics-based environment. …”
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  8. 8

    Artificial Neural Controller Synthesis in Autonomous Mobile Cognition by Chin Kim On, Jason Teo

    Published 2009
    “…This paper describes a new approach in using multi-objective evolutionary algorithms in evolving the neural network that acts as a controller for the phototaxis and radio frequency localization behaviors of a virtual Khepera robot simulated in a 3D, physics-based environment. …”
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    Control of an inverted pendulum using MODE-based optimized LQR controller by Tijani, Ismaila B., Akmeliawati, Rini, Abdullateef, Ayodele I.

    Published 2013
    “…Hence, a Multiobjective differential evolution algorithm is proposed to design an LQR controller with optimal compromise between the conflicting control objectives. …”
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    Proceeding Paper
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    Multi-objective Optimization of Biochemical System Production Using an Improve Newton Competitive Differential Evolution Method by Mohd Arfian, Ismail, Mezhuyev, Vitaliy, Safaai, Deris, Mohd Saberi, Mohamad, Shahreen, Kasim, Saedudin, Rd Rohmat

    Published 2017
    “…Due to that, this study proposed and improved a method that comprises with Newton method, differential evolution algorithm (DE) and competitive co-evolutionary algorithm(ComCA). …”
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    Improved whale optimization algorithm for feature selection in Arabic sentiment analysis by Tubishat, Mohammad, Abushariah, Mohammad A.M., Idris, Norisma, Aljarah, Ibrahim

    Published 2019
    “…The second improvement involves the incorporation of evolutionary operators from Differential Evolution algorithm at the end of each WOA iteration including mutation, crossover, and selection operators. …”
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    Prediction of Alzheimer disease using improved MMSE ensemble regressor based on magnetic resonance images by Farzan, Ali

    Published 2015
    “…A minimal set of feature who passed the above criteria and can differentiate all of cognitive score pairs is selected by using a genetic search algorithm. …”
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    Thesis
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    Design of intelligent control system and its application on fabricated conveyor belt grain dryer by Lutfy, Omar F.

    Published 2011
    “…This controller has several advantages over its conventional ANFIS counterpart, particularly the reduction in processing time. Moreover, three evolutionary algorithms (EAs), in particular a real-coded genetic algorithm (GA), a particle swarm optimization (PSO), and a global-best harmony search (GHS), were separately used to train the proposed controller and to determine its scaling factors. …”
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    Thesis