Search Results - (( evolution extraction method algorithm ) OR ( variable training based algorithm ))
Search alternatives:
- extraction method »
- variable training »
- method algorithm »
- training based »
- evolution »
-
1
Parameter extraction of photovoltaic module using hybrid evolutionary algorithm
Published 2023“…Algorithms; Diodes; Extraction; Iterative methods; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Different evolutions; Differential Evolution; Diode modeling; Electromagnetism-like algorithm; Extracting parameter; Hybrid evolutionary algorithm; Photovoltaic model; Photovoltaic modules; Evolutionary algorithms…”
Conference Paper -
2
-
3
Parameters extraction of double diode photovoltaic module's model based on hybrid evolutionary algorithm
Published 2023“…Algorithms; Diodes; Errors; Extraction; Iterative methods; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Differential evolution algorithms; Diode modeling; Electromagnetism-like algorithm; Fast convergence speed; Hybrid evolutionary algorithm; IV characteristics; Photovoltaic model; Root mean square errors; Evolutionary algorithms…”
Article -
4
A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model
Published 2023“…Algorithms; Diodes; Errors; Iterative methods; Least squares approximations; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Coefficient of determination; Differential Evolution; Electromagnetism-like algorithm; Hybrid evolutionary algorithm; Photovoltaic; Photovoltaic modules; Root mean square errors; Single-diode models; Evolutionary algorithms; algorithm; comparative study; electromagnetic method; estimation method; experimental design; numerical method; parameterization; performance assessment; photovoltaic system…”
Article -
5
Parameter extraction of solar photovoltaic modules using penalty-based differential evolution
Published 2012“…The two diode model of a solar cell is used as the basis for the extraction problem. The analyses carried out using synthetic current-voltage (I-V) data set showed that the proposed P-DE outperforms other Evolutionary Algorithm methods, namely the simulated annealing (SA), genetic algorithm (GA), and particle swarm optimization (PSO). …”
Get full text
Get full text
Article -
6
A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…The focus of the paper is to propose a hybrid approach for the selection of the most influential input variables for the training and testing of neural network based hybrid models. …”
Get full text
Get full text
Article -
7
Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks
Published 2015“…The efficacy of these models depends upon many factors such as, neural network architecture, type of training algorithm, input training and testing data set and initial values of synaptic weights. …”
Get full text
Get full text
Article -
8
-
9
A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat
Published 2021“…Readability was detected using a free online optical character recognition application called Aeosoft. Size was extracted using Extreme Point Detection algorithm and Hit or Miss Transformation method was used to extract the stroke formation pattern. …”
Get full text
Get full text
Thesis -
10
Power plant energy predictions based on thermal factors using ridge and support vector regressor algorithms
Published 2021“…Initially, the Ridge algorithm-based modeling is performed in detail, and then SVR-based LR, named as SVR (LR), SVR-based radial basis function—SVR (RBF), and SVR-based polynomial regression—SVR (Poly.) algorithms, are applied. …”
Get full text
Get full text
Get full text
Get full text
Article -
11
-
12
Modeling 2D appearance evolution for 3D object categorization
Published 2016“…Using rank pooling, we propose two methods to learn the appearance evolution of the 2D views. …”
Get full text
Get full text
Get full text
Get full text
Proceeding Paper -
13
-
14
Multidimensional Minimization Training Algorithms for Steam Boiler Drum Level Trip Using Artificial Intelligence Monitoring System
Published 2010“…The selection of the relevant variables for the neural networks is based on merging between theoretical analysis base and the plant operator experience. …”
Get full text
Get full text
Get full text
Article -
15
Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation
Published 2019“…In order to train Ridgelet probabilistic neural network, a modified differential evolution algorithm with new mutation phase, crossover process, and selection mechanism is introduced. …”
Get full text
Get full text
Thesis -
16
Grey wolf optimization and differential evolution-based maximum power point tracking controller for photovoltaic systems under partial shading conditions
Published 2022“…The simulation results disclose that the hybrid GWO-DE approach shows a greater performance as compared to other studied methods with respect to convergence time, accuracy, extracted power, and efficiency. …”
Get full text
Get full text
Get full text
Get full text
Article -
17
Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)
Published 2008“…The primary concern is to acquire the clear picture of the implementation of Multi-Objective Genetic Algorithm and the essential of variable valve timing effects on the engine performances in various engine speeds. …”
Get full text
Get full text
Proceeding Paper -
18
-
19
Neural network based model predictive control for a steel pickling process
Published 2009“…The Levenberg-Marquardt algorithm is used to train the process models. In the control (MPC) algorithm, the feedforward neural network models are used to predict the state variables over a prediction horizon within the model predictive control algorithm for searching the optimal control actions via sequential quadratic programming. …”
Get full text
Get full text
Article -
20
Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network
Published 2021“…Prior to the development of ANN-based WQI prediction model, the BR algorithm was chosen with two-, three-, four-, five- and six-neuron architectures for 60% and 70% training. …”
Get full text
Get full text
Monograph
