[HTML][HTML] Advances in electric two-wheeler technologies
Cost effective modes of transport keeping in conjunction with sustainable outlooks for the
future have ensured new technologies and initiatives being taken across the globe. Lighter …
future have ensured new technologies and initiatives being taken across the globe. Lighter …
Forecasting GRACE data over the African watersheds using artificial neural networks
The GRACE-derived terrestrial water storage (TWSGRACE) provides measurements of the
mass exchange and transport between continents, oceans, and ice sheets. In this study, a …
mass exchange and transport between continents, oceans, and ice sheets. In this study, a …
A novel electrohydraulic brake system with tire–road friction estimation and continuous brake pressure control
JJ Castillo, JA Cabrera, AJ Guerra… - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
The braking system is the main active safety equipment of vehicles. This paper presents a
new brake system architecture based on the use of proportional servovalves. The use of …
new brake system architecture based on the use of proportional servovalves. The use of …
Parameter optimization of support vector regression using Harris hawks optimization
Abstract Support Vector Regression (SVR) is often used in forecasting. Adjustment of
parameters in the SVR affects the results of forecasting. This study aims to analyze the SVR …
parameters in the SVR affects the results of forecasting. This study aims to analyze the SVR …
Climatic data analysis for groundwater level simulation in drought prone Barind Tract, Bangladesh: Modelling approach using artificial neural network
R Hasda, MF Rahaman, CS Jahan, KI Molla… - Groundwater for …, 2020 - Elsevier
This study presents implementation of non-linear autoregressive model with exogenous
inputs (NARX) of Artificial neural network (ANN), used for groundwater level (GWL) …
inputs (NARX) of Artificial neural network (ANN), used for groundwater level (GWL) …
Machine learning-based dynamic modeling for process engineering applications: a guideline for simulation and prediction from perceptron to deep learning
CM Rebello, PH Marrocos, EA Costa, VV Santana… - Processes, 2022 - mdpi.com
A misusage of machine learning (ML) strategies is usually observed in the process systems
engineering literature. This issue is even more evident when dynamic identification is …
engineering literature. This issue is even more evident when dynamic identification is …
Artificial neural network architecture for prediction of contact mechanical response
Predicting the contact mechanical response for various types of surfaces is and has long
been a subject, where many researchers have made valuable contributions. This is because …
been a subject, where many researchers have made valuable contributions. This is because …
Adaptive neuro-fuzzy wheel slip control
V Ćirović, D Aleksendrić - Expert Systems with Applications, 2013 - Elsevier
Due to complex and nonlinear dynamics of a braking process and complexity in the tire–
road interaction, the control of automotive braking systems performance simultaneously with …
road interaction, the control of automotive braking systems performance simultaneously with …
[HTML][HTML] Meta-modeling of the curing process of thermoset matrix composites by means of a FEM–ANN approach
Thermal curing is a common practice to manufacture high temperature thermosetting matrix
composites, in order to improve the mechanical properties of the final product. The cycle …
composites, in order to improve the mechanical properties of the final product. The cycle …
Longitudinal wheel slip control using dynamic neural networks
V Ćirović, D Aleksendrić, D Smiljanić - Mechatronics, 2013 - Elsevier
The control of automotive braking systems performance and a wheel slip is a challenging
problem due to nonlinear dynamics of a braking process and a tire–road interaction. When …
problem due to nonlinear dynamics of a braking process and a tire–road interaction. When …