Search Results - (( variable estimation using algorithm ) OR ( simulation optimization model algorithm ))
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Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi
Published 2018“…In the next step, the parameter identification as an optimization problem is solved by Moth-flame optimization, which is a novel nature-inspired heuristic 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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Hybrid optimization approach to estimate random demand
Published 2012“…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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Conference or Workshop Item -
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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. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”
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Automatic control of flotation process using computer vision
Published 2015“…A froth model correlating the image variables to process variables and a prediction system estimating the metallurgical parameters based on image variables were then developed by using a neural network structure. …”
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Maximizing power generation in variable speed micro-hydro with power point tracking
Published 2022“…This research first introduces a mathematical model for an experimental variable speed micro-hydro platform and then simulates the microhydro in MATLAB. …”
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Proceedings -
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Determination of tree stem volume : A case study of Cinnamomum
Published 2013“…Simulations of the best models are done using the Maple software.…”
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Conceptual Design And Dynamical Analysis Of Aerostat System
Published 2020“…The optimized design obtained using this approach can operate with lesser static lift that reduces the aerostat size making it cost effective and compact.The aerostat design approach that includes aerostatics, mass estimation, aerodynamics, static stability and blow-by is used to develop a design algorithm in MATLAB®. …”
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10
Robust correlation feature selection based support vector machine approach for high dimensional datasets
Published 2025“…The second step utilizes the estimates of weights from the first step to select the most important variables for the model. …”
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Synthesis and optimization of multilevel refrigeration systems using generalized disjunctive programming
Published 2022“…The model is solvable using advanced solution algorithms such as the Logic-based branch and bound because of it's disjunctive nature. …”
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Maximum 2-satisfiability in radial basis function neural network
Published 2020“…We utilize Dev C++ as the platform of training and testing our proposed algorithm. In this study, the effectiveness of RBFNN-MAX2SAT can be estimated by evaluating the proposed models with testing data sets. …”
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Grid-based remotely sensed hydrodynamic surface runoff model using emissivity coefficient / Jurina Jaafar
Published 2015“…The process from the satellite information allows an optimal judgment to decide the most appropriate Manning roughness to be used in the simulation of surface runoff. …”
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches
Published 2018“…The optimal model based on the parsimony principles was obtained from the hill climbing algorithm with score metrics. …”
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Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data
Published 2018“…BRF algorithm combines the strengths of random subset and greedy selection procedures in creating new maximal ordered variable relevance weights. …”
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18
Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani
Published 2018“…To obtain the unknown vector of parameters of the MHTan, three heuristic optimization algorithms are employed to minimize the sum of squared residuals. …”
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19
Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid
Published 2012“…The fault detection algorithm identifies the time and location of each fault. …”
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20
Design of fuzzy based controller for modern elevator group with floor priority constraints
Published 2011“…In order to manifest the work with actual elevator service, a computer simulation of a four-cars-elevator controller in a twenty storied building is accomplished by using MATLABTM fuzzy logic toolbox and implements the prototype experimental model.…”
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Proceeding Paper
