Intelligent diagnosis of mechanical faults of in-wheel motor based on improved artificial hydrocarbon networks
H Xue, M Wu, Z Zhang, H Wang - ISA transactions, 2022 - Elsevier
For the driving safety of electric vehicle (EV), intelligent diagnosis based on artificial
hydrocarbon networks (AHNs) is proposed to detect mechanical faults of in-wheel motor …
hydrocarbon networks (AHNs) is proposed to detect mechanical faults of in-wheel motor …
A novel wearable sensor-based human activity recognition approach using artificial hydrocarbon networks
Human activity recognition has gained more interest in several research communities given
that understanding user activities and behavior helps to deliver proactive and personalized …
that understanding user activities and behavior helps to deliver proactive and personalized …
Non-contact breathing rate estimation using machine learning with an optimized architecture
The breathing rate monitoring is an important measure in medical applications and daily
physical activities. The contact sensors have shown their effectiveness for breathing …
physical activities. The contact sensors have shown their effectiveness for breathing …
Estimation of low nutrients in tomato crops through the analysis of leaf images using machine learning
H Ponce, C Cevallos, R Espinosa… - Journal of Artificial …, 2021 - ojs.istp-press.com
Tomato crops are considered the most important agricultural products worldwide. However,
the quality of tomatoes depends mainly on the nutrient levels. Visual inspection is made by …
the quality of tomatoes depends mainly on the nutrient levels. Visual inspection is made by …
Doubly fed induction generator (DFIG) wind turbine controlled by artificial organic networks
The main goal of this paper is to show the control capabilities of artificial organic networks
when they are applied to variable speed wind generators. Since doubly fed induction …
when they are applied to variable speed wind generators. Since doubly fed induction …
Stochastic parallel extreme artificial hydrocarbon networks: An implementation for fast and robust supervised machine learning in high-dimensional data
Artificial hydrocarbon networks (AHN)–a supervised learning method inspired on organic
chemical structures and mechanisms–have shown improvements in predictive power and …
chemical structures and mechanisms–have shown improvements in predictive power and …
Scientific argumentation in chemistry education: implications and suggestions
LY Hong, CA Talib - Asian Social Science, 2018 - journal.251news.co.in
The Malaysia Education Blueprint 2012-2025 reveals the aspiration of government to
prepare Malaysian children to meet the challenges of a 21st century economy. Nonetheless …
prepare Malaysian children to meet the challenges of a 21st century economy. Nonetheless …
A hybrid approach of intelligent systems to help predict absenteeism at work in companies
VS Araujo, TS Rezende, AJ Guimarães, VJS Araujo… - SN Applied …, 2019 - Springer
In recent years, several surveys have been conducted on absenteeism and how this affects
the routine of conducting productive operations in companies. Therefore, having criteria for …
the routine of conducting productive operations in companies. Therefore, having criteria for …
A flexible approach for human activity recognition using artificial hydrocarbon networks
Physical activity recognition based on sensors is a growing area of interest given the great
advances in wearable sensors. Applications in various domains are taking advantage of the …
advances in wearable sensors. Applications in various domains are taking advantage of the …
An indoor predicting climate conditions approach using Internet-of-Things and artificial hydrocarbon networks
H Ponce, S Gutiérrez - Measurement, 2019 - Elsevier
The prediction and understanding of environmental conditions are of great importance to
prevent and analyze changes in environment, supporting meteorological based sectors …
prevent and analyze changes in environment, supporting meteorological based sectors …