Search Results - (( variable learning models algorithm ) OR ( simulation optimization based algorithm ))
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance
Published 2019“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Enhancing reservoir simulation models with genetic algorithm optimized neural networks across diverse climatic zones / Saad Mawlood Saab
Published 2025“…The optimizer algorithm (i.e., GA) determines the optimal input variables and internal parameters in the prediction models. …”
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…Moreover, K-Nearest Neighbor (KNN) classifier was used to evaluate the effectiveness of the features identified by the proposed SCSO algorithm. The performance of the proposed SCSO algorithm was compared with six state-of-the-art and recent wrapper-based optimization algorithms using the validation metrics of classification accuracy, optimum feature size, and computational cost in seconds. …”
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To develop an efficient variable speed compressor motor system
Published 2007“…To achieve a robust controller from variation of motor parameters, a real-time or on-line learning algorithm based on a second order optimization Levenberg-Marquardt is employed. …”
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Design of Optimal Pitch Controller for Wind Turbines Based on Back-Propagation Neural Network
Published 2024“…Finally, real-time changes in wind speed are applied to evaluate and adjust controller parameters using the trained back-propagation neural network. The model is simulated in MATLAB 2019b, real-time data are observed, and the control effect is compared with that of a Takagi–Sugeno optimal controller, firefly algorithm optimal controller and fuzzy controller. …”
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches
Published 2018“…Therefore, this was not incorporated in BBN models. Based on cross-validation analysis, the score-based algorithm outperformed the constraint-based algorithms in the structural learning. …”
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Rank-based optimal neural network architecture for dissolved oxygen prediction in a 200L bioreactor
Published 2017“…Thus it is beneficial to model the relationship of DO concentration with these variables based on real process data for further use in controller design. …”
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Vehicular traffic noise prediction and propagation modelling using artificial neural network
Published 2018“…The measurement was carried out four times a day (morning, afternoon, evening, and midnight) all through two-days of the week (Sunday and Monday). The optimal radial basis function NN model was used which comprised of 17 hidden layers with a back-propagation algorithm. …”
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A highly interpretable fuzzy rule base using ordinal structure for obstacle avoidance of mobile robot
Published 2011“…The ordinal structure model of fuzzy reasoning has an advantage of managing high-dimensional problem with multiple input and output variables ensuring the interpretability of the rule set. …”
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Grid-based remotely sensed hydrodynamic surface runoff model using emissivity coefficient / Jurina Jaafar
Published 2015“…The results from the model are promising and it is limited by its ability to model all the variables then are involved in the development of surface model. …”
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Development of robust procedures for partial least square regression with application to near infrared spectral data
Published 2021“…In the in-processing, the PLSR model is very sensitive to the optimal number of PLS components used in the model fitting process. …”
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Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems
Published 2022“…In this case, the effectiveness and reliability of RMS is increase by combining the simulation with the optimization algorithm.…”
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Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm
Published 2016“…In this paper, a new population-based metaheuristic optimization algorithm, named Simulated Kalman Filter (SKF) is introduced. …”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…In this research, two novel estimation-based metaheuristic optimization algorithms, named as Simulated Kalman Filter (SKF), and single-solution Simulated Kalman Filter (ssSKF) algorithms are introduced for global optimization problems. …”
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Angle Modulated Simulated Kalman Filter Algorithm for Combinatorial Optimization Problems
Published 2016“…Inspired by the estimation capability of Kalman filter, we have recently introduced a novel estimation-based optimization algorithm called simulated Kalman filter (SKF). …”
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