Search Results - (( model validation a algorithm ) OR ( spider optimization search algorithm ))
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Social Spider Optimization On Pid Controller
Published 2017“…Among them, Social Spider Optimization (SSO) was chosen for this research. …”
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Monograph -
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Social spider optimisation algorithm for dimension reduction of electroencephalogram signals in human emotion recognition
Published 2018“…Due to some limitations of current heuristics and evolutionary algorithms, this paper proposed a new swarm based algorithm for feature selection method called Social Spider Optimization (SSO-FS). …”
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Optimization of assembly line balancing with energy efficiency by using tiki-taka algorithm
Published 2023“…Lastly, a study of the industrial case was performed as a validation of the developed model and algorithm. …”
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Implementation of New Improved Round Robin (NIRR) CPU scheduling algorithm using discrete event simulation
Published 2015“…The main objective of this research is to validate the NIRR algorithm by developing a comprehensive simulation model using Discrete Event Simulation (DES). …”
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Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA)
Published 2024“…System identification is a method to build a model for a dynamic system from the experimental data. …”
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Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score
Published 2021“…However, the conversion of a complex form of ML algorithms into a simple statistical model is the prime concern. …”
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Implementation of New Improved Round Robin (NIRR) CPU scheduling algorithm using discrete event simulation
Published 2016“…The main objective of this research is to validate the NIRR algorithm by developing a comprehensive simulation model using Discrete Event Simulation (DES). …”
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Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA)
Published 2018“…System identification is a method to build a model for a dynamic system from the experimental data. …”
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Simplified approach to validate constitutive model formulation of orthotropic materials undergoing finite strain deformation
Published 2016“…The validation process was performed by conducting a series of a single element analysis of a uniaxial strain test and uniaxial stress test. …”
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Performance of Semi Active Lateral Control (SALC) algorithm for semi active suspension system in multibody co-simulation method / M. M. Abdul Majid ...[et al.]
Published 2018“…The experimental data used for simulation model correlation and validation. New controller algorithm (SALC) was than developed in Matlab/Simulink and integrate with correlated vehicle plant model for handling performance validation against passive suspension and Skyhook. …”
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Dynamic modelling of a flexible beam structure using feedforward neural networks for active vibration control
Published 2019“…Correlation tests were used to validate the obtained model. Based on the proposed method, a small mean squared error value has been achieved in the validation phase. …”
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Prediction of Machine Failure by Using Machine Learning Algorithm
Published 2019“…Validation for the model is analyzed by using validation testing data and cross validation. …”
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Final Year Project -
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System identification using Extended Kalman Filter
Published 2017“…In order to evaluate the performance of the EKF learning algorithm, the proposed algorithm validation were analyzed using model validation methods as a checker such as One Step Ahead (OSA) and correlation coefficient (R2). …”
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Student Project -
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Model structure selection for a discrete-time non-linear system using genetic algorithm
Published 2004“…First the effect of different combinations of GA operators on the performance of the model developed is studied. A proposed algorithm called modified GA, or MGA, is presented and a comparison between a simple GA and a modified GA is carried out. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…First the effect of different combinations of GA operators on the performance of the model developed is studied. A proposed algorithm called modified GA, or MGA, is presented and a comparison between a simple GA and a modified GA is carried out. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…First the effect of different combinations of GA operators on the performance of the model developed is studied. A proposed algorithm called modified GA, or MGA, is presented and a comparison between a simple GA and a modified GA is carried out. …”
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Landslide susceptibility mapping at VAZ watershed (Iran) using an artificial neural network model: a comparison between multilayer perceptron (MLP) and radial basic function (RBF)...
Published 2013“…In this study, both MLP and RBF algorithms were used in artificial neural network model. …”
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A deep reinforcement learning hybrid algorithm for the computational discovery and characterization of small proteins utilizing mycobacterium tuberculosis as a model
Published 2025“…This study presents the development and evaluation of a novel hybrid machine learning algorithm that integrates the strengths of Random Forest and Gradient Boosting models to enhance the prediction of smORFs. …”
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