Search Results - (( model application a algorithm ) OR ( panel classification system algorithm ))
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Identifying Damage Types in Solar Panels Through Surface Image Analysis with Naive Bayes
Published 2024“…Statistical criteria, including recall, specificity, and area under the curve (AUC), are employed to assess model performance. The findings indicate that the GNB algorithm surpasses BNB, with a mean average precision (mAP) of 39.83% with an 85:15 training-test ratio, whereas BNB reaches a maximum mAP of 29.25% at a 90:10 ratio. …”
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Development of electronic nose for classification of aromatic herbs using Artificial Intelligent techniques
Published 2018“…Two classification methods, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) were used in order to investigate the performance of classification accuracy for this E-nose system. …”
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Defect Detection And Classification Of Silicon Solar Wafer Featuring Nir Imaging And Improved Niblack Segmentation
Published 2016“…In this thesis, an automatic and efficient defect detection system, utilising advanced classification and clustering strategies are proposed. …”
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Orthogonal least square algorithm and its application for modelling suspension system
Published 2001“…The derivation of the algorithm is presented and its application to the modelling of a car suspension system is included to demonstrate the effectiveness of the algorithm.…”
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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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Real time nonlinear filtered-x lms algorithm for active noise control
Published 2012“…The NLFXLMS algorithm is a stochastic gradient algorithm that incorporates the derivative of a nonlinear plant model which is represented by the scaled error function (SEF) in the controller design. …”
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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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Adaptive Spiral Dynamics Metaheuristic Algorithm for Global Optimisation with Application to Modelling of a Flexible System
Published 2016“…This paper presents a nature-inspired metaheuristic algorithm namely linear adaptive spiral dynamics algorithm (LASDA) and its application to modelling of a flexible system. …”
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SURE-Autometrics algorithm for model selection in multiple equations
Published 2016“…However, most model selection algorithms such as Autometrics only concentrate on single equation modelling which has limited application. …”
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Hybrid DE-PEM algorithm for identification of UAV helicopter
Published 2014“…Originality/value – This study presents a novel hybrid algorithm for system identification of an autonomous helicopter model.…”
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An Improved Spiral Dynamic Optimization Algorithm with Engineering Application
Published 2015“…This paper presents the development of an improved spiral dynamic optimization algorithm with application to nonparametric fuzzy logic modeling of a twin rotor system (TRS). …”
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Assessing the simulation performances of multiple model selection algorithm
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Optimisation of Environmental Risk Assessment Architecture using Artificial Intelligence Techniques
Published 2024“…Fuzzy arithmetic operations on fuzzy numbers and artificial neural networks with a back-propagation learning algorithm were used to represent the structure of the neuro-fuzzy risk assessment model, whereas genetic algorithms were used to develop the safe path selection model. …”
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