Search Results - (( parameter identification system algorithm ) OR ( variable optimization techniques algorithm ))
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…In the hybrid scheme, the initial parameters of the modified BP neural network are optimized by using the global search ability of genetic algorithm, improved by cat chaotic mapping to enrich its optimization capability. …”
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Thesis -
2
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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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025“…Moreover, the LSA optimization technique is introduced to optimally determine the LSTM deep neural model hyperparameters including the number of hidden neurons, learn rate, epoch, learn rate drop factor, learn rate drop period, and gradient decay factor. …”
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Modeling of cupping suction system based on system identification method
Published 2022“…By minimizing integral square errors, fractional order model parameters were optimized (ISE). The results reveal that the better the precision of the modelling cupping system parameter, the lower the error. …”
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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. According to the findings, the mSCA-based technique can produce optimal parameters of model that provides an identified output response comparable to the actual experiment's cupping suction system output, with an integral square error for various random input surfaces and its objective function. …”
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Model input and structure selection in multivariable dynamic modeling of batch distillation column pilot plant / Ilham Rustam
Published 2015“…It is established that a valid nonlinear multivariable case study is presented by the process plant via a systematic experiment conducted to justify the adopted nonlinear system identification. The implementation of Nonlinear Auto-Regressive with exogenous input (NARX) technique was then explored in this study to prove its reliability as a comprehensive system identification approach which has been cited across various recorded process identification platforms. …”
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Modeling of flood water level prediction using NNARX / Fazlina Ahmat Ruslan
Published 2015“…It is established that a valid nonlinear multivariable case study is presented by the process plant via a systematic experiment conducted to justify the adopted nonlinear system identification. The implementation of Nonlinear Auto-Regressive with exogenous input (NARX) technique was then explored in this study to prove its reliability as a comprehensive system identification approach which has been cited across various recorded process identification platforms. …”
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8
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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Simultaneous Computation of Model Order and Parameter Estimation for System Identification Based on Gravitational Search Algorithm
Published 2015“…System identification is a technique used to obtain a mathematical model of a system by performing analysis of input-output characteristic of the system. …”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…These models are developed by integrating multilayer perceptron neural network and evolutionary optimization techniques. Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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Identification of continuous-time hammerstein system using sine cosine algorithm
Published 2019“…This paper presents the development of identification of continuous-time Hammerstein systems based on Sine Cosine Algorithm (SCA). …”
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Study of nature inspired computing (NIC) technique for optimal reactive power dispatch problems
Published 2017“…In this research, new nature-inspired meta-heuristic optimization algorithms namely moth-flame optimizer (MFO) and Ant Lion Optimizer (ALO) were implemented to address the optimal reactive power dispatch (ORPD) problems. …”
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Research Report -
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Identification of non-linear dynamic systems using fuzzy system with constrained membership functions
Published 2004“…This study deals with the use of the rule-based fuzzy system for the identification of non-linear dynamic systems. …”
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Thesis -
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MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD
Published 2017“…In this thesis. iterative Leaky Least Mean Squares (LLMS) based methods are proposed to address the limitations ofLS method in MultiInput Multi-Output (MIMO) closed-loop system identification. In this research. novel algorithms have been developed to: (I) isolate the less interacting channe Is using a modified partial correlation algorithm. (2) achieve unbiased and consistent parameter estimates using an iterative LLMS algorithm and (3) develop parsimonious models for closed-loop MIMO systems. …”
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Hybrid intelligent methods for parameter identification and load frequency control in power system
Published 2014“…The accuracy of the parameter identification of power system model and efficiency of frequency control are part of the challenging work in power system operation and control area. …”
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Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane
Published 2021“…The HMVOSCA algorithm is used to tune the linear and nonlinear parameters to reduce the gap between the estimated results and the actual results. …”
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Orthogonal least square algorithm and its application for modelling suspension system
Published 2001“…Modelling based on input and output data is known as system identification. One of the issues in system identification is the parameter estimation and model structure selection where various methods have been studied including the orthogonal least square algorithm. …”
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A hybrid metaheuristic algorithm for identification of continuous-time Hammerstein systems
Published 2021“…This paper presents a new hybrid identification algorithm called the Average Multi-Verse Optimizer and Sine Cosine Algorithm for identifying the continuous-time Hammerstein system. …”
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Simultaneous computation of model order and parameter estimation for system identification based on opposition-based simulated Kalman filter
Published 2018“…Simultaneous Model Order and Parameter Estimation (SMOPE) has been proposed to address system identification problem efficiently using optimization algorithms. …”
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