Search Results - (( using equations using algorithm ) OR ( parameter optimization means algorithm ))

A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA) by Ponnalagu, Dharswini, Mohd Ashraf, Ahmad, Jui, Julakha Jahan

“…Competency of the proposed algorithm in generating the optimal parameters for TEMs was appraised based on 21 benchmarked design parameters, following the objective of root mean square error (RMSE) minimization between the temperature of both actual and estimated models. …”
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Rock brittleness prediction through two optimization algorithms namely particle swarm optimization and imperialism competitive algorithm by Hussain, Azham, Surendar, A., Clementking, A., Kanagarajan, Sujith, Ilyashenko, Lubov K.

“…For this aim, two forms of equations, i.e., linear and power are considered and the weights of these equations are optimized by PSO and ICA. …”
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

“…In this research, a novel algorithm (Herschel Bulkley Network) is introduced to simulate the non-Newtonian fluid flow in a pipe using data redundant deep neural network (DNN) for fully developed, laminar, and incompressible flow conditions. …”
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Improved bacterial foraging optimization algorithm with machine learning-driven short-term electricity load forecasting: a case study in peninsular Malaysia by Zaini, Farah Anishah, Sulaima, Mohamad Fani, Wan Abdul Razak, Intan Azmira, Othman, Mohammad Lutfi, Mokhlis, Hazlie

“…Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. …”
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Improved bacterial foraging optimization algorithm with machine learning driven short term electricity load forecasting: A case study in Peninsular Malaysia by Sulaima, Mohamad Fani, Zaini, Farah Anishah, Wan Abdul Razak, Intan Azmira, Othman, Mohammad Lutfi, Mokhlis, Hazlie

“…Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. …”
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Parameter estimation of stochastic differential equation by Haliza Abd. Rahman, Arifah Bahar, Norhayati Rosli, Madihah Md. Salleh

“…The results showed that the Mean Square Errors (MSE) for stochastic model with parameters estimated using optimal knot for 1,000, 5,000 and 10,000 runs of Brownian motions are smaller than the SDE models with estimated parameters using knot selected heuristically. …”
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Kinetic parameters estimation of the Escherichia coli (E. coli) model by Garra Rufa-inspired Optimization Algorithm (GRO) by Jasni, Mohamad Zain, Azrag, Mohammed Adam Kunna, Saiful Farik, Mat Yatin, Aldehim, Ghadah, Zuhaira, Muhammad Zain, Shaiba, Hadil, Alturki, Nazik, Sapiah, Sakri, Azlinah, Mohamed, Jaber, Aqeel S.

“…So, Garra Rufa-inspired Optimization (GRO) Algorithm is applied to the primary metabolic network of E. coli as a model to estimate small-scale kinetic parameters and increase the kinetic accuracy. …”
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The Effects Of Weightage Values With Two Objective Functions In iPSO For Electro-Hydraulic Actuator System by Ghazali, Rozaimi, Ghani, Muhamad Fadli, Chai, Mau Shern, Chong, Shin Horng, Chong, Chee Soon, Md Sam, Yahaya, Has, Zulfatman

“…The PID controller parameters will be tuned by using the iPSO algorithm to get the lowest overshoot percentage and steady-state error. …”
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3D prediction of tunneling-induced ground movements based on a hybrid ANN and empirical methods by Hajihassani, M., Kalatehjari, R., Marto, A., Mohamad, H., Khosrotash, M.

“…To overcome these problems, the use of optimization algorithms to train ANNs is of advantage. …”
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3D prediction of tunneling-induced ground movements based on a hybrid ANN and empirical methods by Hajihassani, M., Kalatehjari, R., Marto, A., Mohamad, H., Khosrotash, M.

“…To overcome these problems, the use of optimization algorithms to train ANNs is of advantage. …”
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Analysis of parallel flow type internally cooled membrane-based liquid desiccant dehumidifier using a neural networks approach by Quadros, Jaimon Dennis, Khan, Sher Afghan, T., Prashanth

“…Backpropagation algorithm (BP), artificial bee colony (ABC), and genetic algorithm (GA) models were used to train the neural network (NN) parameters using the data collected from the CCD-based response equation. …”
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Modelling transmission dynamics of covid-19 during Pre-vaccination period in Malaysia: a predictive guiseird model using streamlit by Zulkarnain, Norsyahidah, Abdul Hadi, Muhammad Salihi, Mohammad, Nurul Farahain, Shogar, Ibrahim

“…The mathematical model is solved using Scipy odeint function, which uses Livermore Solver for Ordinary Differential Equations with an Automatic method switching (LSODA) algorithm. …”
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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

“…The model reliability describes the second sub-objective, which is to determine the feasible operating window of the MEC using multiple-objective optimization based on the nonlinear convex method using gradient descent algorithm as the objective function in maximizing the percentage efficiency of the MEC after validating the mathematical model. …”
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Optimization of hydropower reservoir system using genetic algorithm for various climatic scenarios by Tayebiyan, Aida

“…In order to increase the system efficiency and maximize the power generation, constructed operation models were optimized. To determine the optimum solution in each policy, real coded genetic algorithm is used as an optimization technique. …”
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Impact of evolutionary algorithm on optimization of nonconventional machining process parameters by B V, Raghavendra, R Annigiri, Anandkumar, Srikatamurthy, JS

“…This paper presents the optimization of laser beam machining in additive manufacturing of polymer-based material parameters, specifically focusing on cutting speed, gas pressure of nitrogen, and focal point locations, to achieve optimal mean surface roughness. …”
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A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting by Mohammed, Athraa Jasim, Ghathwan, Khalil Ibrahim, Yusof, Yuhanis

“…However, its operation relies on two important parameters (regularization and kernel). Pre-determining the values of parameters will affect the results of the forecasting model; hence, to find the optimal value of these parameters, this study investigates the adaptation of Bat and Cuckoo Search algorithms to optimize LSSVM parameters. …”
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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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Efficient Time-Varying q-Parameter Design for q-Incremental Least Mean Square Algorithm with Noisy Links by Arif, M., Khan, S.S., Qadri, S.S.U., Naseem, I., Moinuddin, M.

“…Moreover, for the proposed NL-qILMS, we also devised various time-varying techniques for the selection of the optimal q-parameter to improve the performance. Furthermore, the closed-form solutions for the steady-state mean square deviation, excess mean square deviation and mean square error are derived. …”
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Robust Portfolio Mean-Variance Optimization for Capital Allocation in Stock Investment Using the Genetic Algorithm: A Systematic Literature Review by Diandra Chika Fransisca, Sukono, Diah Chaerani, Nurfadhlina Abdul Halim