Search Results - (( parameter deviation between algorithm ) OR ( parameter optimization model algorithm ))

Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA) by Ponnalagu, Dharswini, Mohd Ashraf, Ahmad, Jui, Julakha Jahan

“…Acquired results which demonstrate lower values of RMSE and parameter deviation index against the standard SMA and other preceding algorithms such as particle swarm optimization, sine cosine algorithm, moth flame optimizer and ant lion optimizer ultimately verified ESMA’s efficacy as an effective approach for accurate model identification.…”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

“…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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Investigation of firefly algorithm and chaos firefly algorithm for load prequency control / Zaid Najid by Zaid, Najid

“…In order to obtain the best controller parameter values for LFC, Firefly Algorithm (FA) and Chaos Firefly Algorithm (CFA) are used. …”
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Optimization of process parameters for rapid adsorption of Pb(II), Ni(II), and Cu(II) by magnetic/talc nanocomposite using wavelet neural network by Darajeh, Negisa, Masoumi, Hamid Reza Fard, Kalantari, Katayoon, Ahmad @ Ayob, Mansor, Shameli, Kamyar, Basri, Mahiran, Khandanlou, Roshanak

“…The network was trained by the IBP and four other algorithms as a model. To determine the number of hidden-layer nodes in the model, the root-mean-square error of a testing set was minimized. …”
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Identification of continuous-time hammerstein model using improved archimedes optimization algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad, Cho, Bo Wen

“…Therefore, this article identified various continuous-time Hammerstein models based on an improved Archimedes optimization algorithm (IAOA) to address these concerns. …”
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Neural Network Model and Finite Element Simulation of Spring back in Plane-Strain Metallic Beam Bending by Abu Khadra, Fayiz Y. M.

“…To validate the finite element model physical experiments were conducted. A neural network algorithm based on the backpropagation algorithm has been developed. …”
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Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model by Selva A.M., Yahaya M.S., Azis N., Ab Kadir M.Z.A., Jasni J., Yang Ghazali Y.Z.

“…Electric transformers; Health; Hidden Markov models; Nonlinear programming; Probability distributions; Quality control; Viterbi algorithm; Condition parameters; Dissolved gas analysis; Distribution transformer; Emission probabilities; Health indices; Non-linear optimization; Remaining useful lives; Transition probabilities; Parameter estimation…”

Multivariate Optimization of Biosynthesis of Triethanolamine-Based Esterquat Cationic Surfactant Using Statistical Algorithms by Fard Masoumi, Hamid Reza

“…All process parameters are selected to conduct the optimization by using some statistical algorithms such as Artificial Neural networks (ANNs), Response Surface Methodology (RSM), Wavelet Neural Network (WNN) and Partial Least Squares (PLS). …”
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Estimation of transformers health index based on condition parameter factor and hidden Markov model by Mohd Selva, Amran, Yahaya, Muhammad Sharil, Azis, Norhafiz, Ab Kadir, Mohd Zainal Abidin, Jasni, Jasronita, Yang Ghazali, Young Zaidey

“…Subsequently, the future states probability distribution was computed based on the HMM prediction model and viterbi algorithm was applied to find the best optimal path sequence of HI for the respective observable condition. …”
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Prediction and investigation of surface response in high speed end milling of Ti-6Al-4V and optimization by genetic algorithm by Alam, Md. Shah, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah, Konneh, Mohamed

“…The developed quadratic prediction model on surface roughness was coupled with the genetic algorithm to optimize the cutting parameters for the minimum surface roughness.…”
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Hybridization of modified sine cosine algorithm with tabu search for solving quadratic assignment problem by Nurdiyana, Jamil

“…Sine Cosine Algorithm (SCA) is a population-based metaheuristic method that widely used to solve various optimization problem due to its ability in stabilizing between exploration and exploitation. …”
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Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network by Mohamad Afiq, Mohd Asrul

“…Single-objective optimization improves the validity of the model by minimizing the mean square error (MSE) between the experimental data and the prediction with the adjustment of the input values of the model parameters. …”
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Multi-parametric optimization of aerodynamic performance and pedestrian crash in sedan front-end profiles by Nor Azman, Afzatul Najwa

“…A multiobjective optimization framework was developed using computational simulations, mathematical modelling, and evolutionary algorithms. …”
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Optimization of transesterification process for Ceiba pentandra oil: A comparative study between kernel-based extreme learning machine and artificial neural networks by Kusumo F., Silitonga A.S., Masjuki H.H., Ong H.C., Siswantoro J., Mahlia T.M.I.

“…Ant colony optimization; Artificial intelligence; Biodiesel; Esters; Knowledge acquisition; Mean square error; Neural networks; Transesterification; Ant Colony Optimization (ACO); Artificial neural network models; Ceiba pentandra oil; Coefficient of determination; Effect of parameters; Extreme learning machine; Root mean squared errors; Transesterification process; Learning systems; algorithm; artificial neural network; biofuel; catalysis; chemical reaction; comparative study; machine learning; optimization; vegetable oil; Ceiba pentandra…”

Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

“…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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Enhanced segment particle swarm optimization for large-scale kinetic parameter estimation of escherichia coli network model by Mohammed Adam, Kunna Azrag

“…However, the large-scale kinetic parameters estimation using optimization algorithms is still not applied to the main metabolic pathway of the E. coli model, and they’re a lack of accuracy result been reported for current parameters estimation using this approach. …”
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Advancements in crop water modelling: algorithmic developments and parameter optimization strategies for sustainable agriculture: a review by Sulaiman, Ahmad S. S., Wayayok, Aimrun, Aziz, Samsuzana A., Yun, Wong Mui, Leifeng, Guo

“…This paper presents a review on algorithm development and crop water modelling with a focus on optimizing significant parameters related to crop factors, soil factors, and weather factors. …”
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An Improved Hybrid of Particle Swarm Optimization and the Gravitational Search Algorithm to Produce a Kinetic Parameter Estimation of Aspartate Biochemical Pathways by Ahmad Muhaimin, Ismail, Mohd Saberi, Mohamad, Hairudin, Abdul Majid, Khairul Hamimah, Abas, Safaai, Deris, Zaki, Nazar, Siti Zaiton, Mohd Hashim, Zuwairie, Ibrahim, Muhammad Akmal, Remli

“…The results show that the proposed algorithm outperformed other standard optimization algorithms in terms of accuracy and near-optimal kinetic parameter estimation. …”
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A new metaphor-less algorithms for the photovoltaic cell parameter estimation by Premkumar M., Babu T.S., Umashankar S., Sowmya R.

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

“…In this study, an Enhanced Segment Particle Swarm Optimization algorithm (ESe-PSO) was proposed for kinetic parameters estimation. …”
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