Search Results - (( using factor using algorithm ) OR ( parameter optimization means algorithm ))
Search alternatives:
- parameter optimization »
- optimization means »
- using algorithm »
- means algorithm »
- using factor »
- factor using »
-
1
Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm
Published 2021“…A comparison was done against particle swarm optimization, genetic algorithm, and sine–cosine algorithm, where the modified cuckoo search algorithm showed the lowest root mean square error and fastest convergence rate among the three algorithms.…”
Get full text
Get full text
Get full text
Article -
2
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. …”
Get full text
Get full text
Thesis -
3
Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…Factor analysis using principle component analysis (PCA) with an orthogonal rotation method, varimax factor rotation have resulted in 4 out of 15 parameters namely area, mean elevation, Gravelius factor and shape factor. …”
Get full text
Get full text
Thesis -
4
The Use of Artificial Neural Networks and Genetic Algorithms for Effectively Optimizing Production from Multiphase Flow Wells
Published 2010“…Moreover, the output from the ANNs will be utilized plus selected other input parameters as controlling variables for optimizing the production from a multiphase producing field using Genetic Algorithms (GA).…”
Get full text
Get full text
Get full text
Conference or Workshop Item -
5
Identification of continuous-time hammerstein model using improved archimedes optimization algorithm
Published 2024“…This proposed algorithm produced solutions with superior accuracy and consistency compared to various established metaheuristic strategies, including particle swarm optimizer, grey wolf optimizer, multi-verse optimizer, AOA, and a hybrid optimizer (average multi-verse optimizer-sine-cosine algorithm).…”
Get full text
Get full text
Get full text
Get full text
Article -
6
A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…Firefly algorithm outperformed the other metaheuristic algorithms used to solve this proposed hybrid artificial intelligence model regarding parameter sensitivity. …”
Get full text
Get full text
Get full text
Thesis -
7
Extraction of photovoltaic module model's parameters using an improved hybrid differential evolution/electromagnetism-like algorithm
Published 2023“…Algorithms; Evolutionary algorithms; Mean square error; Optimization; Parameter estimation; Photovoltaic cells; Coefficient of determination; DEAM; Five parameters; Hybrid differential evolution; Improved differential evolutions; IV characteristics; Photovoltaic modules; Root mean square errors; Iterative methods; algorithm; artificial intelligence; electromagnetic method; error analysis; experimental study; photovoltaic system…”
Article -
8
Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025Subjects:Article -
9
Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models
Published 2024“…This study proposes ensemble models for predicting LDC based on multilayer perceptron (MULP) methods and optimization algorithms. The honey badger optimization algorithm (HBOA), salp swarm algorithm (SASA), firefly algorithm (FIFA), and particle swarm optimization algorithm (PASOA) are used to adjust the MULP parameters. …”
Article -
10
Metaheuristic approach for optimizing neural networks parameters in battery state of charge estimation
Published 2023“…EMA is the recent evolutionary algorithm based on mating theory and environmental factor will be used in this paper to optimize the weights and biases of FNN on a common Li-ion battery, multiple data measurements, drive cycles and training repetitions. …”
Get full text
Get full text
Get full text
Get full text
Conference or Workshop Item -
11
Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model
Published 2023Conference Paper -
12
Optimization of super twisting sliding mode control gains using Taguchi method
Published 2018“…Two gain parameters in super twisting algorithm, that is L and W were identified as two factors with three levels respectively. …”
Get full text
Get full text
Get full text
Article -
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). …”
Get full text
Get full text
Thesis -
14
Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia
Published 2019“…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
Get full text
Get full text
Thesis -
15
-
16
-
17
Diameter prediction and optimization of hot extrusion-synthesized polypropylene filament using statistical and soft computing techniques
Published 2019“…Predictive models of response surface methodology (RSM) and radial basis function neural network(RBFNN)were applied to predict the diameter of extruded filament. The optimal process parameters to maintain the diameter of the filament closest to the target value were identified using the cuckoo search algorithm (CSA), and particle swarm optimization (PSO). …”
Get full text
Get full text
Get full text
Article -
18
Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr...
Published 2024“…A coati optimization algorithm is introduced to select input scenarios. …”
Article -
19
PREDICTIVE MODELING OF DIMENSIONAL ACCURACIES IN 3D PRINTING USING ARTIFICIAL NEURAL NETWORK
Published 2024“…The ANN model was developed using MATLAB software, employing training functions and learning algorithms to optimize the neural network architecture. …”
Article -
20
Modeling of vanillin adsorption from aqueous solution using resin H103 by artificial neural network
Published 2019“…The neural network was trained using backpropagation (BP) algorithm. The result shows that the Levenberg-Marquardt algorithm was best suited the training function and the optimized ANN involved seven neurons at the hidden layer. …”
Get full text
Get full text
Get full text
Conference or Workshop Item
