Search Results - (( based optimization system algorithm ) OR ( parameter simulation model algorithm ))

Search alternatives:

Refine Results
  1. 1
    Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter

    Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter by Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Pebrianti, Dwi, Mohd Saberi, Mohamad

    Published 2017
    “…Simultaneous Model Order and Parameter Estimation (SMOPE) and Simultaneous Model Order and Parameter Estimation based on Multi Swarm (SMOPE-MS) are two techniques of implementing meta-heuristic algorithm to iteratively establish an optimal model order and parameters simultaneously for an unknown system. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  2. 2
    Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance

    Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Koting, Suhana, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

    Published 2019
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  3. 3
    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models

    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

    Published 2017
    “…Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  4. 4
    DESIGN OPTIMIZATION OF A BLDC MOTOR BY GENETIC ALGORITHM AND SIMULATED ANNEALING

    DESIGN OPTIMIZATION OF A BLDC MOTOR BY GENETIC ALGORITHM AND SIMULATED ANNEALING by K. S. , Rama Rao, Azrul, Hisham Bin Othman

    Published 2007
    “…Single and multi-objective functions of the motor are derived based on the steady state mathematical model. A constrained optimization on the objective function is performed using Genetic Algorithm (GA) and Simulated Annealing (SA), and optimal parameters are obtained. …”
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  5. 5
    Modeling and Simulation of Swarm Intelligence Algorithms for Parameters Tuning of PID Controller in Industrial Couple Tank System

    Modeling and Simulation of Swarm Intelligence Algorithms for Parameters Tuning of PID Controller in Industrial Couple Tank System by Ismail, Mohd Khairuddin, Amira Sarayati, Ahmad Dahalan, Amar Faiz, Zainal Abidin, Yee, Yang Lai, Nur Anis, Nordin, Siti Fatimah, Sulaiman, Hazriq Izzuan, Jaafar, Syahrul Hisham, Mohamad, Noor Hafizah, Amer

    Published 2014
    “…These swarm intelligence algorithms are Particle Swarm Optimization (PSO) and Firefly Algorithm (FA). …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  6. 6
    Modeling and Simulation of Swarm Intelligence Algorithms for Parameters Tuning Of PID Controller in Industrial Couple Tank System

    Modeling and Simulation of Swarm Intelligence Algorithms for Parameters Tuning Of PID Controller in Industrial Couple Tank System by Mohd Khairuddin, Ismail, Ahmad Dahalan, Amira Sarayati, Zainal Abidin, Amar Faiz, Yee, Yang Lai, Nordin, Nur Anis, Siti Fatimah, Sulaiman, Jaafar, Hazriq Izzuan, Mohamad, Syahrul Hisham, Amer, Noor Hafizah

    Published 2014
    “…These swarm intelligence algorithms are Particle Swarm Optimization (PSO) and Firefly Algorithm (FA). …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  7. 7
    Genetic algorithm based method for optimal location placement of flexible ac transmission system devices for voltage profile improvement

    Genetic algorithm based method for optimal location placement of flexible ac transmission system devices for voltage profile improvement by Karami, Mahdi

    Published 2011
    “…The modeling of power systems, FACTS devices and genetic algorithms are performed through MATLAB/PSAT simulation. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  8. 8
    OPTIMAL DESIGN AND ANALYSIS OF A DC–DC SYNCHRONOUS CONVERTER USING GENETIC ALGORITHM AND SIMULATED ANNEALING

    OPTIMAL DESIGN AND ANALYSIS OF A DC–DC SYNCHRONOUS CONVERTER USING GENETIC ALGORITHM AND SIMULATED ANNEALING by K., S. Rama Rao., C. , -K, Chew

    Published 2009
    “…Abstract This paper presents the application of Genetic Algorithm (GA) and Simulated Annealing (SA) techniques for optimal design and analysis of a DC–DC converter with synchronous rectification normally used in battery charge/discharge circuits in DC uninterruptible power supply systems. …”
    Get full text
    Get full text
    Citation Index Journal
    Save to List
    Saved in:
  9. 9
    OPTIMAL DESIGN AND ANALYSIS OF A DC–DC SYNCHRONOUS CONVERTER USING GENETIC ALGORITHM AND SIMULATED ANNEALING

    OPTIMAL DESIGN AND ANALYSIS OF A DC–DC SYNCHRONOUS CONVERTER USING GENETIC ALGORITHM AND SIMULATED ANNEALING by K.S., Rama Rao, C. K., Chew

    Published 2009
    “…This paper presents the application of Genetic Algorithm (GA) and Simulated Annealing (SA) techniques for optimal design and analysis of a DC–DC converter with synchronous rectification normally used in battery charge/discharge circuits in DC uninterruptible power supply systems. …”
    Get full text
    Get full text
    Citation Index Journal
    Save to List
    Saved in:
  10. 10
    Design optimization of a bldc motor by genetic algorithm and simulated annealing

    Design optimization of a bldc motor by genetic algorithm and simulated annealing by K.S.R., Rao, A.H.B., Othman

    Published 2007
    “…Single and multi-objective functions of the motor are derived based on the steady state mathematical model. A constrained optimization on the objective function is performed using Genetic Algorithm (GA) and Simulated Annealing (SA), and optimal parameters are obtained. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  11. 11
    An Intelligent Voltage Controller for a PV Inverter System Using Simulated Annealing Algorithm-Based PI Tuning Approach

    An Intelligent Voltage Controller for a PV Inverter System Using Simulated Annealing Algorithm-Based PI Tuning Approach by Najeeb, Mushtaq, Muhamad, Mansor, Ramdan, Razali, Hamdan, Daniyal, Ali, Mahmood

    Published 2017
    “…This study associates an intelligent voltage controller based PI approach for PV electrical inverter by employing a meta-heuristic optimization algorithmic called a Simulated Annealing (SA) algorithm. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  12. 12
    An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli

    An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli by Mohammed Adam, Kunna, Tuty Asmawaty, Abdul Kadir, Muhammad Akmal, Remli, Noorlin, Mohd Ali, Kohbalan, Moorthy, Noryanti, Muhammad

    Published 2020
    “…In this study, an Enhanced Segment Particle Swarm Optimization algorithm (ESe-PSO) was proposed for kinetic parameters estimation. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  13. 13
    Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling

    Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling by Shimailawi, Shatha Abdulhadi Muthana

    Published 2022
    “…Friedman test using GRG metric shows significant better performance (p-values<0.05) for PACS algorithm compared to benchmark algorithms. The proposed models and algorithm can be used to solve the multi-objective GMS problem while the new parameters’ values can be used to obtain optimal or near optimal maintenance scheduling of generators. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  14. 14
    Simultaneous computation of model order and parameter estimation for system identification based on opposition-based simulated Kalman filter

    Simultaneous computation of model order and parameter estimation for system identification based on opposition-based simulated Kalman filter by Badaruddin, Muhammad, Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Ahmad Afif, Mohd Faudzi, Pebrianti, Dwi

    Published 2018
    “…Simultaneous Model Order and Parameter Estimation (SMOPE) has been proposed to address system identification problem efficiently using optimization algorithms. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  15. 15
    Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)

    Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA) by Mohiuddin, A. K. M., Ashour, Ahmed Aly Ibrahim Shaaban, Yap, Haw Shin

    Published 2008
    “…Majority of the research works in this project were in CAE software environment and method to implement optimization to 1D engine simulation. The paper conducts design optimization of CAMPRO 1.6L (S4PH) engine valve timing at various engine speeds using multi-objective genetic algorithm (MOGA) for the future variable valve timing (VVT) system research and development. …”
    Get full text
    Get full text
    Proceeding Paper
    Save to List
    Saved in:
  16. 16
    Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm

    Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

    Published 2025
    “…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”
    Article
    Save to List
    Saved in:
  17. 17
    Optimal parameters of an ELM-based interval type 2 fuzzy logic system: a hybrid learning algorithm

    Optimal parameters of an ELM-based interval type 2 fuzzy logic system: a hybrid learning algorithm by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

    Published 2018
    “…In order to overcome this limitation in an ELM-based IT2FLS, artificial bee colony optimization algorithm is utilized to obtain its antecedent parts parameters. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  18. 18
    Modelling of multi-robot system for search and rescue

    Modelling of multi-robot system for search and rescue by Poy, Yi Ler

    Published 2023
    “…This report focusses on developing a novel multi-robot path planning algorithm based on the Modified Particles Swarm Optimization (MPSO) algorithm for dynamic environments. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
    Save to List
    Saved in:
  19. 19
    Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi

    Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi by Dejamkhooy, Abdolmajid, Asefi, Sajjad

    Published 2018
    “…Precision of model parameters is vital in a permanent magnet synchronous motor high performance and controllability. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  20. 20
    Hybridization of nonlinear sine cosine and safe experimentation dynamics algorithms for solving control engineering optimization problems

    Hybridization of nonlinear sine cosine and safe experimentation dynamics algorithms for solving control engineering optimization problems by Mohd Helmi, Suid

    Published 2024
    “…The empirical assessment of these proposed methods encompasses a diverse set of 23 benchmark functions, demonstrating their efficacy comparable to well-established metaheuristic algorithms such as as the Grey Wolf Optimizer (GWO), Multi-Verse Optimization (MVO), Sine Cosine Algorithm (SCA), Ant Lion Optimizer (ALO), Moth-Flame Optimization Algorithm (MFO), and Grasshopper Optimization Algorithm (GOA). …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:

Search Tools: