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    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). …”
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    Thesis
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    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. …”
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    Article
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    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. …”
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    Article
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    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…Finally, the algorithm found, which would solve the image segmentation problem.…”
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    Thesis
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    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. …”
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    Conference or Workshop Item
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    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. …”
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    Article
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    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. …”
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    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
    “…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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    Book
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    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. …”
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    Article
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    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. …”
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    Article
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    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. …”
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    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. …”
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    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. …”
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    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. …”
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    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. …”
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    Thesis
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