Search Results - (( variable identification based algorithm ) OR ( parameter optimization based algorithm ))
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Identification of continuous-time hammerstein model using improved archimedes optimization algorithm
Published 2024“…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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Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi
Published 2018“…In the next step, the parameter identification as an optimization problem is solved by Moth-flame optimization, which is a novel nature-inspired heuristic algorithm. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
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4
Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025“…In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
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Modelling of cupping suction system based on system identification method
Published 2022“…The detection of cupped suction system plants using a standard model based on a modified Sine Cosine Algorithm (mSCA) is presented in this research. …”
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Modeling of cupping suction system based on system identification method
Published 2022“…Cupping suction plant identification utilizing a nonlinear model based on the modified Sine Cosine Algorithm (mSCA). …”
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Undergraduates Project Papers -
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Fuzzy modelling and control for a nonlinear reboiler system of a distillation column
Published 2006“…Genetic algorithm (GA) is used to tune the parameters of the Fuzzy controller. …”
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An optimized ensemble for predicting reservoir rock properties in petroleum industry
Published 2013“…However, identification of these parameters which relies on core data analyses is expensive and time consuming. …”
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Model input and structure selection in multivariable dynamic modeling of batch distillation column pilot plant / Ilham Rustam
Published 2015“…There are several recorded control approaches that have been successfully employed to meet with the end product quality requirement however the current study put the bulk of its focus on a control approach performed based on the reflux ratio as manipulated variable with the top tray temperature as the controlled variable. …”
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Modeling of flood water level prediction using NNARX / Fazlina Ahmat Ruslan
Published 2015“…There are several recorded control approaches that have been successfully employed to meet with the end product quality requirement however the current study put the bulk of its focus on a control approach performed based on the reflux ratio as manipulated variable with the top tray temperature as the controlled variable. …”
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11
Determination of tree stem volume : A case study of Cinnamomum
Published 2013“…Illustrations and algorithms are incorporated into the procedures. Non-normal and nonlinear data variables are addressed, hence data characterization is presented. …”
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12
Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis
Published 2011“…The synthetic reaction was optimized by Taguchi method based on orthogonal array to evaluate the effect of each parameters and interactive effects of reaction parameters including temperature, time, amount of enzyme, amount of molecular sieve, amount of solvent, and molar ratio of substrates (xylitol: fatty acid). …”
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Identification of debris flow initiation zones using topographic model and airborne laser scanning data
Published 2017“…Conditioning parameters were numerically optimized to identify the arbitrarily maximum model basis function for eleven variables, using MARSplines analysis (algorithm). …”
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Hospital site suitability assessment using three machine learning approaches: evidence from the Gaza strip in Palestine
Published 2021“…Identification of the most significant parameters (conditioning factors) that influence a suitable hospital location was achieved by employing correlation-based feature selection (CFS) with the search algorithm (greedy stepwise). …”
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Simulation and characterization of indium gallium arsenide thermophotovoltaic cell for harvesting waste heat with different spectral irradiances
Published 2023“…Single-variable optimization is defined as changing one design variable (thicknesses and doping concentrations) of the cap, front surface field, emitter, base, back surface field and buffer layers. …”
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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
Published 2011“…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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On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing
Published 2015“…In doing so, this paper reviews two existing parameter free optimization algorithms involving Teaching Learning Based Optimization (TLBO) and Fruitfly Optimization Algorithm (FOA) in an effort to promote their adoption for CIT.…”
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Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…System identification is a method of determining a mathematical relation between variables and terms of a process based on observed input-output data. …”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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