Search Results - (( parameter estimation using algorithm ) OR ( parameters variation learning algorithm ))*
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Restoration of blurred images using geometric and chebichef moments / Ahlad Kumar
Published 2016“…Once the blur parameters are estimated, image restoration of the proposed method is carried out using split Bregman 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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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…Multi-Verse Optimizer (MVO) is one of the most recent robust nature-inspired metaheuristic algorithm. It has been successfully implemented and used in various areas such as machine learning applications, engineering applications, network applications, parameter control, and other similar applications to solve optimization problems. …”
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4
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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5
Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines
Published 2020“…These parameters are used to develop a standalone intelligently machine learning adaptive distance relay (ML-ADR) modification. …”
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6
Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…The detailed parametric analysis exhibits the competency of the proposed algorithm to explain the rheological features. Monte-Carlo simulation is performed by propagating uncertainty to investigate the dominant parameters affecting simulated results. …”
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Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line
Published 2020“…The hybrid Wavelet Multiresolution Analysis and Machine learning algorithm (WMRA-ML) is used to extracts the useful hidden knowledge from decomposed one-cycle fault transient signals (voltage & current) from four Matlab/Simulink CIGRE models. …”
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Sensorless induction motor speed control for electric vehicles using enhanced hybrid flux estimator with ann-ifoc controller
Published 2022“…The results of the ANN-IFOC hybrid estimator were obtained in four cases, which were 1) constant high and low speeds, 2) constant speed against parameter variation, 3) variable speed, and 4) variable load torque disturbances. …”
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Grid-based remotely sensed hydrodynamic surface runoff model using emissivity coefficient / Jurina Jaafar
Published 2015“…Since soil surface is the primary order that control the hydrological and hydraulic processes, the topographic of the land use sensed by the satellite is used to describe the spatial variations of the ground surface. …”
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Short-term Gini coefficient estimation using nonlinear autoregressive multilayer perceptron model
Published 2024“…In this study, we introduce a NAR Multi-Layer Perceptron (MLP) approach for brief term estimation of the Gini coefficient. Several parameters were tested to discover the optimal model for Malaysia's Gini coefficient within 1987–2015, namely the output lag space, hidden units, and initial random seeds. …”
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Forecasting of meteorological drought using ensemble and machine learning models
Published 2025“…After that, the active input parameters were used for forecasting of SPI-3 and SPI-6 values to understanding of drought in semi-arid area. …”
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Three-dimensional craniometrics identification model and cephalic index classification of Malaysian sub-adults: A multi-slice computed tomography study / Sharifah Nabilah Syed Mohd...
Published 2024“…Discriminant function analysis (DFA), binary logistic regression (BLR), and several machine learning (ML) algorithms (random forest (RF), support vector machines (SVM), and linear discriminant analysis (LDA)) were used to statistically analyse the data. …”
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14
Estimation in spot welding parameters using genetic algorithm
Published 2007“…By using Genetic algorithm (GA) the spot welding parameters can be estimated.…”
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Optimal variational mode decomposition and integrated extreme learning machine for network traffic prediction
Published 2021“…However, most of the existing evolutionary algorithms have some adjustable parameters which depend on subjective experience or prior knowledge. …”
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Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)
Published 2015“…The results from this experiment show estimated optimal kinetic parameters values, shorter computation time, and better accuracy of simulated results compared with other estimation algorithms.…”
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Enhanced segment particle swarm optimization for large-scale kinetic parameter estimation of escherichia coli network model
Published 2021“…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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The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm
Published 2020“…Metaheuristic parameter estimation is an algorithm framework that is processed using some technique to generate a pattern or graph. …”
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An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems
Published 2019“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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Identifying and estimating solar cell parameters using an enhanced slime mould algorithm
Published 2024“…The proposed ESMA was used to resolve the problem of estimating PV parameters based on the empirical current-voltage (I-V) data. …”
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