Search Results - (( parameters variation method algorithm ) OR ( using data method algorithm ))
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Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications
Published 2018“…The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.…”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…The mMVO based method is then used for identifying the parameters of linear and nonlinear subsystems in the Hammerstein model using the given input and output data. …”
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3
Development Of An Algorithm To Reduce The Topographical Effects In Reflected Radiance
Published 2020“…These algorithms use data from extraterrestrial irradiance, atmospheric profiles, digital elevation models, and radiative transfer models to calculate the amount of irradiance on Earth’s surface to reduce distortions due to the topographic effect. …”
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Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method
Published 2016“…Then, design of experiments is used to examine the sensitivity of the parameters of each solving algorithm using Taguchi method. …”
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Modified least trimmed squares method for face recognition / Nur Azimah Abdul Rahim
Published 2018“…The genetic algorithm configuration for n (number of observations) and p (parameter) was changed to assess the performance of modified method. …”
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An improvement of back propagation algorithm using halley third order optimisation method for classification problems
Published 2020“…This algorithm utilises first order optimisation method namely Gradient Descent (GD) method which attempts to minimise the error of network. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…To overcome these ANN problems, the Genetic Algorithm (GA) has been most frequently used for this purpose, however, some drawbacks of GA include, slow search speed and dependence on initial parameters. …”
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Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar
Published 2019“…Several researchers have reported different optimization methods for blade parameters such as Blade Element Momentum theory (BEM), Computational Fluid Dynamics (CFD) and Supervisory Control and Data Acquisition (SCADA) system. …”
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Interpolation and extrapolation techniques based Neural Network in estimating the missing ionospheric TEC data
Published 2024“…The solar and magnetic indices, seasonal variation as well as diurnal variation are used as the input spaces in the NN to estimate the missing GPS TEC. …”
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Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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Scene illumination classification based on histogram quartering of CIE-Y component
Published 2014“…In scene illumination estimation dealing with large range of illumination and small variation of it is critical. Those algorithms which performed estimation carrying out lots of calculation that leads in expensive methods in terms of computing resources. …”
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Neural Network Model and Finite Element Simulation of Spring back in Plane-Strain Metallic Beam Bending
Published 2006“…The training data required to train the two-metamodeling techniques were generated using a verified nonlinear finite element algorithm developed in the current research. …”
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Analysis of robot localisation performance based on extended kalman filter
Published 2015“…First is the performance of the algorithm using different parameters in which different velocities and number of landmarks have been used to determine the accuracy of the localisation method. …”
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15
Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…The cumbersome numerical computation and rudimentary empirical solutions hinder faster analysis over a wide range of parameters. However, machine and deep learning methods have higher accuracy but rely heavily on the quality and amount of training data, and the solution may become inconclusive if data is sparse. …”
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Multivariate Based Analysis of Methane Adsorption Correlated to Toc and Mineralogy Impact from Different Shale Fabrics
Published 2021“…The analysis from machine learning SVR method shows the good predictability of the adsorption in the variation with shale fabric parameters. …”
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Gradient auto-tuned Takagi-Sugeno Fuzzy Forward control of a HVAC system using predicted mean vote index
Published 2023“…The TS model is first trained offline using Gauss-Newton Method for Nonlinear Regression (GNMNR) algorithm with data collected from both building and HVAC system equipments. …”
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Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO)
Published 2019“…This research proposed a swarm intelligence training algorithm, Improved African Buffalo Optimization algorithm (IABO) based on the Metaheuristic method called the African Buffalo Optimization algorithm (ABO). …”
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Interpolation and Extrapolation Techniques Based Neural Network in Estimating the Missing Ionospheric TEC Data
Published 2024Proceedings Paper -
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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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