Instantaneous CO2 emission modelling for a Euro 6 start-stop vehicle based on portable emission measurement system data and artificial intelligence methods
M Mądziel - Environmental Science and Pollution Research, 2024 - Springer
One of the increasingly common methods to counteract the increased fuel consumption of
vehicles is start-stop technology. This paper introduces a methodology which presents the …
vehicles is start-stop technology. This paper introduces a methodology which presents the …
Corn grain yield prediction using UAV-based high spatiotemporal resolution imagery, machine learning, and spatial cross-validation
Food demand is expected to rise significantly by 2050 due to the increase in population;
additionally, receding water levels, climate change, and a decrease in the amount of …
additionally, receding water levels, climate change, and a decrease in the amount of …
[HTML][HTML] Protection scheme for multi-terminal HVDC system with superconducting cables based on artificial intelligence algorithms
This paper presents the development of a novel data-driven fault detection and classification
scheme for DC faults in multi-terminal HVDC transmission system which incorporates …
scheme for DC faults in multi-terminal HVDC transmission system which incorporates …
Exploring wind speed for energy considerations in eastern Jerusalem-Palestine using machine-learning algorithms
S Salah, HR Alsamamra, JH Shoqeir - Energies, 2022 - mdpi.com
Wind energy is one of the fastest growing sources of energy worldwide. This is clear from the
high volume of wind power applications that have been increased in recent years. However …
high volume of wind power applications that have been increased in recent years. However …
[HTML][HTML] Adapting machine learning for environmental spatial data-A review
Large-scale modeling of environmental variables is an increasingly complex but necessary
task. In this paper, we review the literature on using machine learning to cope with …
task. In this paper, we review the literature on using machine learning to cope with …
A data-driven approach for the prediction of coal seam gas content using machine learning techniques
A new data-driven approach to interpreting the nonlinear problem of total desorbed gas
content analysis of coal seams is presented in this study. The study focuses on a low-rank …
content analysis of coal seams is presented in this study. The study focuses on a low-rank …
Axial strength prediction of seawater sea sand concrete-filled circular FRP tubes under alkaline environment based on ensemble learning algorithms
The rapid development of marine and urban infrastructure led to the extensive studies on
seawater sea sand concrete (SWSSC) filled fiber reinforced polymer (FRP)/steel tubes. The …
seawater sea sand concrete (SWSSC) filled fiber reinforced polymer (FRP)/steel tubes. The …
Machine learning approach to residential valuation: a convolutional neural network model for geographic variation
Geographic location and neighbourhood attributes are major contributors to residential
property values. Automated valuation models (AVM) often use hedonic pricing with location …
property values. Automated valuation models (AVM) often use hedonic pricing with location …
Impact of geostatistical nonstationarity on convolutional neural network predictions
Convolutional neural networks (CNNs) are gaining tremendous attention in subsurface
studies due to their ability to learn from spatial image data. However, most deep learning …
studies due to their ability to learn from spatial image data. However, most deep learning …
Herbal plants leaf image classification using deep learning models based on augmentation approach
As the world grows daily, people are shifting towards renewable energy sources and natural
resources for healthcare as remedies. Herbs are the natural source of medicine in place of …
resources for healthcare as remedies. Herbs are the natural source of medicine in place of …