Search Results - (( java implementation force algorithm ) OR ( swarm activation function algorithm ))

Search alternatives:

Refine Results
  1. 1
    Particle swarm optimization and spiral dynamic algorithm-based interval type-2 fuzzy logic control of triple-link inverted pendulum system : a comparative assessment

    Particle swarm optimization and spiral dynamic algorithm-based interval type-2 fuzzy logic control of triple-link inverted pendulum system : a comparative assessment by M. F., Masrom, N. M. A., Ghani, M. O., Tokhi

    Published 2021
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  2. 2
    Particle swarm optimization for neural network learning enhancement

    Particle swarm optimization for neural network learning enhancement by Abdull Hamed, Haza Nuzly

    Published 2006
    “…Two programs have been developed; Particle Swarm Optimization Feedforward Neural Network (PSONN) and Genetic Algorithm Backpropagation Neural Network (GANN). …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  3. 3
    Optimal power flow using hybrid firefly and particle swarm optimization algorithm

    Optimal power flow using hybrid firefly and particle swarm optimization algorithm by Khan, Abdullah, Hizam, Hashim, Abdul Wahab, Noor Izzri, Othman, Mohammad Lutfi

    Published 2020
    “…In this paper, a novel, effective meta-heuristic, population-based Hybrid Firefly Particle Swarm Optimization (HFPSO) algorithm is applied to solve different non-linear and convex optimal power flow (OPF) problems. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  4. 4
    A comparative study of multi-objective optimal power flow based on particle swarm, evolutionary programming, and genetic algorithm

    A comparative study of multi-objective optimal power flow based on particle swarm, evolutionary programming, and genetic algorithm by Kahourzade, S., Mahmoudi, A., Mokhlis, Hazlie

    Published 2015
    “…This paper compares the performance of three population-based algorithms including particle swarm optimization (PSO), evolutionary programming (EP), and genetic algorithm (GA) to solve the multi-objective optimal power flow (OPF) problem. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  5. 5
    Dynamic control and performance of dual active bridge converter based particle swarm optimization

    Dynamic control and performance of dual active bridge converter based particle swarm optimization by Suliana, Ab Ghani, Hamdan, Daniyal, Norazila, Jaalam, Norhafidzah, Mohd Saad, Nur Huda, Ramlan

    Published 2022
    “…This paper presents analysis of the dynamic response of the isolated bidirectional dual active bridge (DAB) DC-DC converter using particle swarm optimization (PSO) algorithm. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  6. 6
    Particle swarm optimisation for reactive power compensation on Oman 6 bus electrical grid

    Particle swarm optimisation for reactive power compensation on Oman 6 bus electrical grid by Al Mamari, Adnan Saif, Toha, Siti Fauziah, Ahmad, Salmiah, Al Mamari, Ali Salim

    Published 2021
    “…Reduction of system active power loss is the goal of the function in the projected algorithm. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  7. 7
    Forecasting of photovoltaic output using hybrid particle swarm optimization-artificial neural network model / Muhamad Faizol Adli Abdullah

    Forecasting of photovoltaic output using hybrid particle swarm optimization-artificial neural network model / Muhamad Faizol Adli Abdullah by Abdullah, Muhamad Faizol Adli

    Published 2010
    “…In Backpropagation Neural Network (BPNN), there are many elements to be considered such as the number of input, hidden and output nodes, learning rate, momentum rate, bias, minimum error and activation/transfer functions. These entire elements will affect the speed of natural network learning. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  8. 8
    Advanced Pareto front non-dominated sorting multi-objective particle swarm optimization for optimal placement and sizing of distributed generation

    Advanced Pareto front non-dominated sorting multi-objective particle swarm optimization for optimal placement and sizing of distributed generation by Mahesh, K., Nallagownden, P., Elamvazuthi, I.

    Published 2016
    “…The distributed generation consists of single and multiple numbers of active power DG, reactive power DG and simultaneous placement of active-reactive power DG. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  9. 9
    Advanced Pareto front non-dominated sorting multi-objective particle swarm optimization for optimal placement and sizing of distributed generation

    Advanced Pareto front non-dominated sorting multi-objective particle swarm optimization for optimal placement and sizing of distributed generation by Mahesh, K., Nallagownden, P., Elamvazuthi, I.

    Published 2016
    “…The distributed generation consists of single and multiple numbers of active power DG, reactive power DG and simultaneous placement of active-reactive power DG. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  10. 10
    Multi leader particle swarm optimization for optimal placement and sizing of multiple distributed generation for a micro grid

    Multi leader particle swarm optimization for optimal placement and sizing of multiple distributed generation for a micro grid by Ariya Sinhalage Buddhika Eshan Karunarathne

    Published 2023
    “…Initially, the Particle Swarm Optimization was implemented to establish the optimal sizes of DGs and the performance of the implemented algorithm was analyzed and quantified. …”
    text::Thesis
    Save to List
    Saved in:
  11. 11
    An improved grey wolf with whale algorithm for optimization functions

    An improved grey wolf with whale algorithm for optimization functions by Asgher, Hafiz Maaz

    Published 2022
    “…The performance of the proposed algorithm is tested and evaluated on five benchmarked unimodal and five multimodal functions. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  12. 12
    An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction

    An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction by Shah, Habib

    Published 2014
    “…Most of the training algorithms focus on weight values, activation functions, and network structures for providing optimal outputs. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  13. 13
    Predicting evaporation with optimized artificial neural network using multi-objective salp swarm algorithm

    Predicting evaporation with optimized artificial neural network using multi-objective salp swarm algorithm by Ehteram M., Panahi F., Ahmed A.N., Huang Y.F., Kumar P., Elshafie A.

    Published 2023
    Article
    Save to List
    Saved in:
  14. 14
    Y-type Random 2-satisfiability In Discrete Hopfield Neural Network

    Y-type Random 2-satisfiability In Discrete Hopfield Neural Network by Guo, Yueling

    Published 2024
    “…During the retrieval phase, a new activation function and Swarm Mutation were proposed to ensure the diversity of the neuron states. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  15. 15
    An improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-PID controller for multi-input–multi-output gantry crane system

    An improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-PID controller for multi-input–multi-output gantry crane system by Mohd Zaidi, Mohd Tumari, Mohd Ashraf, Ahmad, Mohd Helmi, Suid, Mohd Riduwan, Ghazali, M Osman, Tokhi

    Published 2023
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  16. 16
    Differential evolution for neural networks learning enhancement

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  17. 17
    Optimal coordinated voltage control in active distribution networks using backtracking search algorithm

    Optimal coordinated voltage control in active distribution networks using backtracking search algorithm by Hashim T.J.T., Mohamed A.

    Published 2023
    Article
    Save to List
    Saved in:
  18. 18
    Optimization of assembly line balancing with energy efficiency by using tiki-taka algorithm

    Optimization of assembly line balancing with energy efficiency by using tiki-taka algorithm by Ariff Nijay, Ramli

    Published 2023
    “…Then, the TTA is developed before undergoing functionality tests by benchmarking with Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA). …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  19. 19
    Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar

    Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar by Md. Rasel, Sarkar

    Published 2019
    “…There have two most uses activation function namely tansig and logsig. The essence of this study is that it compares the effect of activation functions (tansig and logsig) in the performance of time series forecasting since activation function is the core element of any artificial neural network model. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  20. 20
    Optimal power flow incorporating stochastic wind and solar generation by metaheuristic optimizers

    Optimal power flow incorporating stochastic wind and solar generation by metaheuristic optimizers by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2021
    “…In this paper, recent metaheuristic algorithms namely Grasshopper Optimization Algorithm (GOA), Black Widow Optimization Algorithm, Grey Wolves Optimizer, Ant Lion Optimizer, Particles Swarm Optimization, Gravitational Search Algorithm, Moth-Flame Optimization and Barnacles Mating Optimizer (BMO) will be used to solve three objective functions of OPF problem viz. (1) cost minimization of the power generation that consists of thermal, stochastic wind and solar power generations, (2) power loss minimization, and (3) combined cost and emission minimization of power generations. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:

Search Tools: