Search Results - (evolutionary OR evolution) ((optimization technique) OR (learning techniques))

Search alternatives:

Refine Results
  1. 1

    Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Nor Farizan, Zakaria, Mohd Mawardi, Saari

    Published 2023
    “…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  2. 2

    Feature selection optimization using hybrid relief-f with self-adaptive differential evolution by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Ahmad Nazri, Azree Shahrel, Mohamed, Raihani, Abd Manaf, Syaifulnizam

    Published 2017
    “…The performance of proposed method is compared with several feature selection techniques in order to prove their superiority using ten datasets obtained from UCI machine learning repository.…”
    Get full text
    Get full text
    Get full text
    Article
  3. 3

    Comparative study of optimal power flow using evolutionary programming and immune evolutionary programming technique in power system / Mohd Khairil Izwan Md Daim by Md Daim, Mohd Khairil Izwan

    Published 2006
    “…This project presents a new technique for solving the optimal power flow problem, in a power system using an Evolutionary Programming and Immune Evolution Programming optimization technique. …”
    Get full text
    Get full text
    Thesis
  4. 4

    Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

    Published 2020
    “…ECHT is considered to be a flagship ensemble technique till date for constrained optimization problems, whereas SRDE employs a parent selection mechanism for constrained optimization. …”
    Get full text
    Get full text
    Article
  5. 5

    Comparison of Artificial Immune System (AIS) and Multiagent Immune Evolutionary Programming (MAIEP) in solving economic dispatch problem: article / Noor Aziela Mat Zin by Mat Zin, Noor Aziela

    Published 2012
    “…In this research, two optimization techniques, known as Artificial Immune System (AIS) and Multiagent Immune Evolutionary Programming (MAIEP) were engaged to solve the economic dispatch problem. …”
    Get full text
    Get full text
    Article
  6. 6

    Comparison of Artificial Immune System (AIS) and Multiagent Immune Evolutionary Programming (MAIEP) in solving economic dispatch problem / Noor Aziela Mat Zin by Mat Zin, Noor Aziela

    Published 2012
    “…In this research, two optimization techniques, known as Artificial Immune System (AIS) and Multiagent Immune Evolutionary Programming (MAIEP) were engaged to solve the economic dispatch problem. …”
    Get full text
    Get full text
    Thesis
  7. 7

    Hybrid evolutionary programming-artificial neural network-based lightning prediction system / Dalina Johari by Johari, Dalina

    Published 2009
    “…It involved the development of ANN design and embedding EP optimization technique for optimizing selected ANN parameters in order to improve the system's generalization capability.ANN, an intelligent machine learning technique, is inspired by the way our biological nervous systems process information. …”
    Get full text
    Get full text
    Thesis
  8. 8

    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    Published 2011
    “…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  9. 9

    Application of optimal reactive power dispatch using evolutionary computation for IEEE 30-bus test system by Mohd Noor Ridzuan Husin

    Published 2009
    “…The project objective is to reduce losses and determine the optimal size of reactive power dispatch. Technique that used to find the optimal size is the evolutionary programming (EP). …”
    Get full text
    Learning Object
  10. 10

    Implementation of embedded generation in distribution system using Evolutionary Programming (EP) by Wan Noorhana Wan Nordin

    Published 2009
    “…In order to determine the optimal output of the embedded generators, an evolutionary programming optimization technique was developed with an objective to minimize the distribution losses while satisfying the voltage constraint in the system. …”
    Get full text
    Learning Object
  11. 11
  12. 12

    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 proposed algorithm is compared with six well-known optimization algorithms and two deep learning algorithms. …”
    Get full text
    Get full text
    Article
  13. 13

    Software testing optimization for large systems using agent-based and NSGA-II algorithms by Jamil, Muhammad Abid, Nour, Mohamed Kidher, Awang Abu Bakar, Normi Sham

    Published 2023
    “…The multiobjective optimization problem is addressed in this article using a novel evolutionary technique to find a global solution in the Pareto form. …”
    Get full text
    Get full text
    Get full text
    Article
  14. 14
  15. 15

    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…Also, fed batch fermentation problems in winery wastewater treatment and biogas generation from sewage sludge are developed for optimization. Though DE traditionally performs better than other evolutionary algorithms and swarm intelligence techniques in optimization of fed-batch fermentation, BSA edged DE and other recent metaheuristics to emerge as superior optimization method in this work. …”
    Get full text
    Get full text
    Thesis
  16. 16
  17. 17

    Tap changer optimisation using embedded differential evolutionary programming technique for loss control in power system by Faris A., Musirin I., Jelani S., Ismail S.A., Mansor M.H., Senthil Kumar A.V.

    Published 2023
    “…A new optimization technique termed as embedded differential evolutionary programming (EDEP) is proposed, which integrates the traditional differential evolution (DE) and evolutionary programming (EP). …”
    Article
  18. 18
  19. 19

    Two level Differential Evolution algorithms for ARMA parameters estimatio by Salami, Momoh Jimoh Emiyoka, Tijani, Ismaila, Aibinu, Abiodun Musa

    Published 2013
    “…The problem of determining simultaneously the model order and coefficient of an Autoregressive Moving Average (ARMA) model is examined in this paper. An Evolutionary Algorithm (EA) comprising two-level Differential Evolution (DE) optimization scheme is proposed. …”
    Get full text
    Get full text
    Get full text
    Proceeding Paper
  20. 20

    An efficient anomaly intrusion detection method with evolutionary neural network by Sarvari, Samira

    Published 2020
    “…In recent years, detection methods based on machine learning techniques are widely deployed in order to improve the efficiency of anomaly-based detection. …”
    Get full text
    Get full text
    Thesis