Search Results - (( parameter optimization based algorithm ) OR ( variable selection techniques algorithm ))
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1
A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…These models are developed by integrating multilayer perceptron neural network and evolutionary optimization techniques. Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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2
CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…In the hybrid scheme, the initial parameters of the modified BP neural network are optimized by using the global search ability of genetic algorithm, improved by cat chaotic mapping to enrich its optimization capability. …”
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3
Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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4
A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments
Published 2013“…Afterward, a genetic algorithm-based optimization framework was designed to improve the interpretability and accuracy of the proposed fuzzy-tabu controller by optimizing the parameters of the FLC and also some of the planner’s parameters in order to improve the quality of the generated paths and runtimes of the planner and also to decrease the variation of the results in different runs of the planner. …”
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5
Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio...
Published 2023“…Unlike the existing optimization algorithm, VL-WIDE features the capability of searching different lengths of solutions to cover the variable number of cloudlets for deployment. …”
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6
Fuzzy Adaptive Tuning of a Particle Swarm Optimization Algorithm for Variable-Strength Combinatorial Test Suite Generation
Published 2018“…Research has shown that stochastic population-based algorithms such as particle swarm optimization (PSO) can be efficient compared to alternatives for VS-CIT problems. …”
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Book Chapter -
7
Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization
Published 2022“…The ANN model is further improved using GA and PSO. Each algorithm has its own parameters and is further optimized using RSM. …”
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8
Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…Furthermore, a systematic feature selection approach was proposed in which search algorithms (Ant-Search, Best First-Search and Particle Swamp Optimization (PSO) - Search) performance were evaluated to select the most significant features. …”
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9
Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. …”
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10
Mobile data gathering algorithms for wireless sensor networks
Published 2014“…The selection of this parameter is based on the application requirements. …”
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11
Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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12
Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks
Published 2013“…In the proposed HATSC scheme, the AHP method is uese for criteria weighting, while the TOPSIS method uses for the selection technique based on a multi-criteria decision-making algorithm is proposed. …”
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13
Multivariate Optimization of Biosynthesis of Triethanolamine-Based Esterquat Cationic Surfactant Using Statistical Algorithms
Published 2011“…All process parameters are selected to conduct the optimization by using some statistical algorithms such as Artificial Neural networks (ANNs), Response Surface Methodology (RSM), Wavelet Neural Network (WNN) and Partial Least Squares (PLS). …”
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14
A Stepper Motor Design Optimization Using
Published 2005“…GAs approach is selected because it is a powerful and broadly applicable stochastic search and optimization techniques that works for many problems that are very difficult to solve by conventional methods. …”
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Monograph -
15
Determination of tree stem volume : A case study of Cinnamomum
Published 2013“…A modeling approach is developed which focuses on the phases in the model-building procedures, effects of interactions variables on the model, minimizing the effects of multicollinearity on the variables and recommending remedial techniques to overcome them, identification of the significant variables by removing insignificant variables, selecting the best model using the eight selection criteria (8SCs), and finally using the residual analysis to validate the chosen best model. …”
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16
Model input and structure selection in multivariable dynamic modeling of batch distillation column pilot plant / Ilham Rustam
Published 2015“…Comparison results have shown that the pre-screening method has an essential role in determining an effective process representation especially in real-time multivariable identification framework where a priori knowledge is not available and would help in resultant model generalization performance as opposed to simply using all available model input variables. Further, after a careful investigation into the OLS algorithm, it was shown that the ERR technique which is an essential part of the algorithm to reach model parsimony, has led the resultant model to select an incorrect model terms albeit some improvement in model selection criteria and validation method adopted in this study. …”
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17
Modeling of flood water level prediction using NNARX / Fazlina Ahmat Ruslan
Published 2015“…Comparison results have shown that the pre-screening method has an essential role in determining an effective process representation especially in real-time multivariable identification framework where a priori knowledge is not available and would help in resultant model generalization performance as opposed to simply using all available model input variables. Further, after a careful investigation into the OLS algorithm, it was shown that the ERR technique which is an essential part of the algorithm to reach model parsimony, has led the resultant model to select an incorrect model terms albeit some improvement in model selection criteria and validation method adopted in this study. …”
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18
Conceptual Design And Dynamical Analysis Of Aerostat System
Published 2020“…The baseline configuration for the desired mission has been obtained using a design algorithm. The statistical values of the selected design variables that include hull fineness ratio, fin area and fin position of the existing aerostat are used to obtain the baseline configuration. …”
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19
Rank-based optimal neural network architecture for dissolved oxygen prediction in a 200L bioreactor
Published 2017“…While the number of neurons in input and output layers are determined based on the number of respective input and output parameters, there is no straightforward method to determine the optimal number of neurons in hidden layer. …”
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Conference or Workshop Item -
20
Groundwater quality assessment and optimization of monitored wells using multivariate geostatistical techniques in Amol-Babol Plain, Iran
Published 2015“…A new optimization approach was proposed for redesign monitoring network wells using optimization algorithm based on the vulnerability of aquifer to contaminations, estimation error of sampling wells, nearest distance between wells, and source of contamination in the study area. …”
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