Search Results - (( based optimization methods algorithm ) OR ( model validation tools algorithm ))
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1
Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…Secondly, the modeling method of the proposed PV module is validated by experimental data. …”
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2
Fractional Stochastic Gradient Descent Based Learning Algorithm For Multi-layer Perceptron Neural Networks
Published 2021“…The performance is highly subjective to the optimization of learning parameters. In this study, we propose a learning algorithm for the training of MLP models. …”
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3
Discrete-time system identification using genetic algorithm with single parent-based mating technique
Published 2024“…The SPM technique offers researchers and practitioners a powerful tool for achieving faster convergence, better optimization, and more accurate models. …”
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4
Chemometrics analysis for the detection of dental caries via ultraviolet absorption spectroscopy / Katrul Nadia Basri
Published 2023“…Model 2 of CNN has maximum performance of validation in terms of accuracy, precision, sensitivity and specificity but the calibration model requires more optimization. …”
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5
Modeling of Optimizing Multi-hole Drilling Toolpath Distance with Multiple Tool Dimension
Published 2024“…Note that the algorithms were evaluated based on their solution quality, with lower fitness values indicating better performance. …”
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6
Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…In order to validate the proposed algorithm, a number of experiments using various datasets were conducted and compared the outcomes with different�state-of-the-art algorithms. …”
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Modeling And Optimization Of Physical Vapour Deposition Coating Process Parameters For Tin Grain Size Using Combined Genetic Algorithms With Response Surface Methodology
Published 2015“…Additionally,analysis of variance(ANOVA) was used to determine the significant factors influencing resultant TiN coating grain size.Based on that,a quadratic polynomial model equation was developed to represent the process variables and coating grain size.Then,in order to optimize the coating process parameters, genetic algorithms (GAs) were combined with the RSM quadratic model and used for optimization work.Finally,the models were validated using actual testing data to measure model performances in terms of residual error and prediction interval (PI).The result indicated that for RSM,the actual coating grain size of validation runs data fell within the 95% (PI) and the residual errors were less than 10 nm with very low values, the prediction accuracy of the model is 96.09%.In terms of optimization and reduction the experimental data,GAs could get the best lowest value for grain size then RSM with reduction ratio of ≈6%, ≈5%, respectively.…”
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8
A study on model-free approach for liquid slosh suppression based on stochastic approximation
“…In addition, the performance of the SPSA based methods is compared to the other stochastic optimization based approaches, which also includes the variants of SPSA based method, such as Global SPSA. …”
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9
Optimization Of Fractional-Slot Permanent Magnet Synchronous Machine Using Analytical Sub-Domain Model And Differential Evolution
Published 2019“…Three multi-objective optimizations based on Analytical Sub-Domain (ASD) and Differential Evolution Algorithm (DEA), Analytical Sub-Domain (ASD) and Particle Swarm Optimization (PSO), Analytical Sub-Domain (ASD) and Genetic Algorithm (GA), for fractionalslot Permanent Magnet Synchronous Machines (PMSM) are formulated, computed and optimized. …”
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10
Electricity distribution network for low and medium voltages based on evolutionary approach optimization
Published 2015“…The test network is generated by fractal based distribution network generation model software tool. …”
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11
Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain
Published 2014“…Finally to present the model validity of a real case study in automotive industrial was studied. …”
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12
Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying
Published 2019“…To classify image noise type, the CNN trained with Backpropagation (BP) algorithm and Stochastic Gradient Descent (SGD) optimization technique are implemented. …”
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13
Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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15
Development of a systematic method in lean tool selection for automotive industry
Published 2012“…The developed software probably assists manufacturers in applying the systematic lean tool selection. Based on the systematic features of this algorithm, the efficiency and effectiveness of the model in presenting optimizing techniques for lean tool selection with the automotive industry seems reasonable and useful. …”
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16
Sustainable optimization of dry turning of stainless steel based on energy consumption and machining cost
Published 2018“…Finally, a confirmation validation test is conducted to validate the proposed model. …”
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Development of data-driven controller for slosh suppression in liquid cargo vehicles
“…For the past decades, various control strategies of liquid slosh motion are based on model-based control schemes. Nevertheless, these methods are difficult to apply in practice. …”
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18
Inter-cell and intra-cell facility layout models under different demand environments in cellular manufacturing systems
Published 2012“…In order to validate the models several cases are generated and demonstrated by two methods, Lingo 12.0 optimization software and an enumeration algorithm which is developed in C/C++. …”
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19
Optimal short term load forecasting using LSSVM and improved BFOA considering Malaysia pandemic disrupted situation
Published 2024“…Due to that reason, in this study, the hybrid forecasting model based on the Least Square Support Vector Machine (LSSVM) and Improved Bacterial Foraging Optimization Algorithm (IBFOA) is developed to perform an accurate STLF and applied to load in Peninsular Malaysia during the pandemic disrupted situation. …”
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20
Analysis the effectiveness of cryogenic treatment through roughness and temperature prediction using bonn technique / Manjunath.S and Ajay Kumar
Published 2017“…For the optimization process, the cutting tool is initially subjected to cryogenic treatment for the improvement in the tool property. …”
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