Search Results - (( variable learning based algorithm ) OR ( using simulation method algorithm ))
Search alternatives:
- simulation method »
- method algorithm »
- variable »
-
1
Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…In order to validate the proposed algorithm, a number of experiments using various datasets were conducted and compared the outcomes with different�state-of-the-art algorithms. …”
Article -
2
Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)
“…The designed algorithm was structured in k-fold cross-validation in attempt to minimise the biasness of the classification performance, measured using error rate. …”
Get full text
Get full text
Monograph -
3
Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. …”
Get full text
Get full text
Get full text
Thesis -
4
Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…The second test evaluates IFS in a controlled study using simulated datasets. Moreover, the third test used ten natural domain datasets obtained from UCI Repository, in about fifteen different experiments, using three to four different Machine Learning Algorithms for performance evaluation. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
5
Effects of user selected conditions on modeling of dynamic systems using adaptive fuzzy model
Published 2001“…The method of selection of the input variables, the number of rules, and the learning rate are briefly discussed. …”
Get full text
Get full text
Get full text
Article -
6
-
7
Random forest algorithm for co2 water alternating gas incremental recovery factor prediction
Published 2020“…Based on literature review, Random Forest (RF) learning method was selected to predict the WAG incremental recovery factor and rank the input vector based on their importance. …”
Get full text
Get full text
Article -
8
A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…Additionally, the Wilcoxon rank test was used to perform the significance analysis between the proposed SCSOKNN method and six other algorithms for a p-value less than 5.00E-02. …”
Get full text
Get full text
Article -
9
Machine Learning Based Optimal Design of On-Road Charging Lane for Smart Cities Applications
Published 2025“…This article proposes an effective machine learning (ML) approach to achieve the optimal design of the charging track, considering the cross-coupling effect. The algorithm not only aids in estimating the infrastructure cost of the charging lane but also predicts optimal design parameters using trained data. …”
Article -
10
Feedback error learning control for underactuated acrobat robot with radial basis funtion based FIR filter
Published 2009“…Simulation results on a two link acrobat robot with nonzero initial angular momentum in achieving a final desired posture angle are presented to show the validity of the proposed algorithm.…”
Get full text
Get full text
Get full text
Proceeding Paper -
11
Fuzzy subtractive clustering (FSC) with exponential membership function for heart failure disease clustering
Published 2022“…Objective: Fuzzy clustering algorithm is a partition method used to assign objects from a data set to a cluster by marking the average location. …”
Get full text
Get full text
Article -
12
A simple model-free butterfly shape-based detection (BSD) method integrated with deep learning CNN for valve stiction detection and quantification
Published 2020“…This simple model-free butterfly shape-based detection (BSD) method uses Stenman's one parameter stiction model, which results in a distinctive â��butterflyâ�� pattern in the presence of stiction. …”
Get full text
Get full text
Article -
13
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. …”
Get full text
Get full text
Thesis -
14
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. …”
Get full text
Get full text
Get full text
Thesis -
15
-
16
Sensorless induction motor speed control for electric vehicles using enhanced hybrid flux estimator with ann-ifoc controller
Published 2022“…The sensorless ANN-IFOC was modelled, simulated, and tested using MATLAB/Simulink for a 20Hp EV motor based on a small Renault Twizy EV model and triggered by the space-vector pulse-width modulation (SVPWM). …”
Get full text
Get full text
Get full text
Get full text
Thesis -
17
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. …”
Get full text
Get full text
Conference or Workshop Item -
18
Development of robust procedures for partial least square regression with application to near infrared spectral data
Published 2021“…To fill-in the gap in the literature, a new robust procedure in wavelength selection based on input scaling method is developed using Filter-Wrapper method. …”
Get full text
Get full text
Thesis -
19
Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy
Published 2020“…In addition, the ranked order of the variables based on their importance differed across the ML algorithms. …”
Get full text
Get full text
Get full text
Conference or Workshop Item -
20
