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An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems
Published 2019“…The algorithm is tested using a largescale metabolic model of Chinese Hamster Ovary (CHO) cells. …”
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An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems
Published 2019“…The algorithm is tested using a large-scale metabolic model of Chinese Hamster Ovary (CHO) cells. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…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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Lithium-ion Battery State of Charge Estimation Method Using Optimized Deep Recurrent Neural Network Algorithm
Published 2023Conference Paper -
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”
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Parameter estimation in computational systems biology models: a comparative study of initialization methods in global optimization
Published 2022“…This paper compares different initialization methods and investigates their performance and effects on estimating kinetic parameters’ value in models of biological systems. …”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…In particular, the search capacity of the MVO algorithm has been improved using the sine and cosine functions of the Sine Cosine Algorithm (SCA) that will be able to balance the processes of exploration and exploitation. …”
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Modified anfis architecture with less computational complexities for classification problems
Published 2018“…The proposed ANFIS model is trained by one of the metaheuristics approach instead of standard two pass learning algorithm. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…Firefly algorithm outperformed the other metaheuristic algorithms used to solve this proposed hybrid artificial intelligence model regarding parameter sensitivity. …”
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Development of a hybrid PSO-ANN model for estimating glucose and xylose yields for microwave-assisted pretreatment and the enzymatic hydrolysis of lignocellulosic biomass
Published 2018“…The PSO algorithm suggested an optimum number of neurons in the hidden layer as 15 and a learning rate of 0.761 these consequently used to construct the ANN model. …”
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Time series modeling of water level at Sulaiman Station, Klang River, Malaysia
Published 2010“…The estimation of parameters of the model is accomplished using the hybrid learning algorithm consisting of standard neural network backpropagation algorithm and least squares method. …”
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Modelling of various meteorological effects on leakage current level for suspension type of high voltage insulators using HMLP neural network
Published 2023“…Hence, it triggering to insulator flashover and finally the hot power arc will damage the bushing. This paper estimates leakage current level by modeling it as a function of various meteorological parameters using Hybrid Multilayered Perceptron Networks (HMLP) with Modified Recursive Prediction Error (MRPE) learning algorithms. …”
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Adaptive complex neuro-fuzzy inference system for non linear modeling and time series prediction
Published 2013“…Second part has been done by proposing a novel learning rule containing genetic algorithm, Levenberg-Marquardt technique and least square estimation. …”
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A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis
Published 2025“…To further enhance COVID-19 lesion estimation, novel optimization strategies, including a hybrid simulated annealing-cuckoo search (SA-CS) algorithm, are introduced alongside the original SA method. …”
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Prediction Of Petroleum Reservoir Properties Using Nonlinear Feature Selection And Ensembles Of Computational Intelligence Techniques
Published 2015“…In this thesis, new non-linear feature-selection assisted methods and ensemble learning models are proposed. The algorithms were implemented with optimized tuning parameters and validated with real-life porosity and permeability datasets obtained from diverse and heterogeneous petroleum reservoirs after they have passed on testing them with a benchmark dataset from the UCI Machine Learning Repository. …”
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Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network
Published 2017“…General linear model (GLM) is used to find the unknown parameters of every individual voxel and the classification is done using multi-class support vector machine (SVM). …”
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