Search Results - (( variable operation during algorithm ) OR ( using optimization based algorithm ))

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  1. 1

    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
    “…To examine the optimized model performance, the simulation of a dam and reservoir system is usually carried out for a particular period utilizing the generated operation rule. During the simulation procedure, although reservoir inflow and evaporation are stochastic variables that are required to be forecasted during simulation, they are considered deterministic variables. …”
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  2. 2

    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

    Published 2025
    “…The effectiveness of the proposed LSA + LSTM model is assessed using battery aging data from the NASA dataset. In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
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    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 fuel�cells�(FCs) involve multiple variable quantities with complex non-linear behaviours, demanding accurate modelling to ensure optimal operation. …”
    Article
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    New global maximum power point tracking and modular voltage equalizer topology for partially shaded photovoltaic system / Immad Shams by Immad , Shams

    Published 2022
    “…In terms of controller-based, in this work, a new global maximum power point tracking (GMPPT) algorithm based on a modified butterfly optimization algorithm (MBOA) has been proposed. …”
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    Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks by Mubarak, Mohammed Awadh Ahmed Ben

    Published 2013
    “…Cell selection is a key element that insures that the QoS and user requirements during and after handover process is met. In the proposed HATSC scheme, the AHP method is uese for criteria weighting, while the TOPSIS method uses for the selection technique based on a multi-criteria decision-making algorithm is proposed. …”
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    Design of Optimal Pitch Controller for Wind Turbines Based on Back-Propagation Neural Network by Shengsheng, Qin, Zhipeng, Cao, Feng, Wang, Ngu, Sze Song, Kho, Lee Chin, Hui, Cai

    Published 2024
    “…To ensure the stable operation of a wind turbine generator system when the wind speed exceeds the rated value and address the issue of excessive rotor speed during high wind speeds, this paper proposes a novel variable pitch controller strategy based on a back-propagation neural network and optimal control theory to solve this problem. …”
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    Control of polystyrene batch reactors using neural network based model predictive control (NNMPC): an experimental investigation by Hosen, M.A., Hussain, Mohd Azlan, Mjalli, F.S.

    Published 2011
    “…The usual practice for operating polymerization reactors is to optimize the reactor temperature profile since the end use properties of the product polymer depend highly on temperature. …”
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    Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail by Sh. Ismail, Faridah

    Published 2015
    “…An intelligent predictive model will replace the lengthy procedures by predicting the properties using known fiberboard characteristics. Back-propagation algorithm is a training method widely used in a multilayer perceptron Neural Network model. …”
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    Constant lock circuit for DC micro-grid system by Mohammed, Asaad Abduljabbar

    Published 2017
    “…Three modes come into view during DC micro-grid operations. These operational scenarios are the standalone scenario, grid scenario, and feedback scenario. …”
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    Dynamic two phase modelling and anfis-based control of ethylene copolymerization in catalytic Fluidized Bed Reactor / Mohammad Reza Abbasi by Mohammad Reza , Abbasi

    Published 2019
    “…Nonetheless, since the model is dynamic, it can be used in control studies as well and it was utilized as a base to control two of the most important process variables namely polymer Melt Flow Index (MFI) and the temperature. …”
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  17. 17

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…The proposed population-based SKF algorithm and the single solution-based SKF algorithm use the scalar model of discrete Kalman filter algorithm as the search strategy to overcome these flaws. …”
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    Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan by Rosselan, Muhammad Zakyizzuddin

    Published 2018
    “…Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods. …”
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    Dynamic Stability Studies Of Generators In Power System Using Fuzzy Logic Controller Based Power System Stabilizer by Hasan, Hayfaa Mohammed Hussein

    Published 2018
    “…Excitation systems are affected by low frequency oscillation (LFO)when they are subjected to small perturbations.Damping during the LFOis enhanced via the addition of power system stabilizer (PSS) to the excitation system.This research entails a study on fuzzy logic controller power system stabilizer (FLCPSS) for the purpose of enhancing the stability of a single machine power system.In order to accomplish the stability enhancement,two approaches were used to design fuzzy logic controller (FLC).The first approach includes the use ofgenetic algorithm (GA) to design the PSS.The second approach entails the use of particle swarm optimization (PSO) to design the PSS.The performance of these two approaches is compared with the systemand without PSS.The stabilizing signals were computed using the fuzzy membership functions depending on these variables.The simulations were tested under different operating conditions and also tested with different membership functions.The simulation is implemented using Matlab /Simulink and the results have been found to be quite good and satisfactory.Electro-mechanical oscillations were created in the event of trouble or when there was high power transfer through weak tie-line in the machines of an interrelated power network.This research presents an analysis on the change of speed (Δω), change of angle position (Δδ) and tie-line power flow (Δp).FLC which includes two areas of symmetrical systems are connected via tie-line to identify the performance of the controllers.Simulation results of the fuzzy logic based controller indicate dual inputs of rotor speed deviation and generator’s accelerating power.Two generators have been used to control the arrangement in the tie-line system.The single fuzzy logic controller (S-FLC) has been used as a primary controller and the double fuzzy logic controller(D-FLC) has been used as a secondary controller.Additionally,the system shows a comparison between the two controllers,namely the S-FLC and D-FLC which have been used to achieve the best results.Notably, the double fuzzy controller has been found to have a greater effect on the multi-machine system and it is smoother than the single fuzzy controller as it increased the damping of the speed Δω and rotorangle (degree) Δδ. …”
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    An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

    Published 2022
    “…The algorithms involved were Genetic Algorithm, Differential Evolution Algorithm, Particle Swarm Optimization, Butterfly Optimization Algorithm, Teaching-Learning-Based Optimization Algorithm, Harmony Search Algorithm and Gravitational Search Algorithm. …”
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