Modeling, diagnostics, optimization, and control of internal combustion engines via modern machine learning techniques: A review and future directions
A critical review of the existing Internal Combustion Engine (ICE) modeling, optimization,
diagnosis, and control challenges and the promising state-of-the-art Machine Learning (ML) …
diagnosis, and control challenges and the promising state-of-the-art Machine Learning (ML) …
A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization
Integration of photovoltaics into power grids is difficult as solar energy is highly dependent
on climate and geography; often fluctuating erratically. This causes penetrations and voltage …
on climate and geography; often fluctuating erratically. This causes penetrations and voltage …
[HTML][HTML] Flood susceptibility modelling using advanced ensemble machine learning models
ARMT Islam, S Talukdar, S Mahato, S Kundu… - Geoscience …, 2021 - Elsevier
Floods are one of nature's most destructive disasters because of the immense damage to
land, buildings, and human fatalities. It is difficult to forecast the areas that are vulnerable to …
land, buildings, and human fatalities. It is difficult to forecast the areas that are vulnerable to …
Machine learning in disaster management: recent developments in methods and applications
Recent years include the world's hottest year, while they have been marked mainly, besides
the COVID-19 pandemic, by climate-related disasters, based on data collected by the …
the COVID-19 pandemic, by climate-related disasters, based on data collected by the …
Predictive modeling for sustainable high-performance concrete from industrial wastes: A comparison and optimization of models using ensemble learners
The cementitious matrix of high-performance concrete (HPC) is highly complex, and
ambiguity exists with its mix design. Compressive strength can vary with the composition …
ambiguity exists with its mix design. Compressive strength can vary with the composition …
Performance of machine learning methods in predicting water quality index based on irregular data set: application on Illizi region (Algerian southeast)
Groundwater quality appraisal is one of the most crucial tasks to ensure safe drinking water
sources. Concurrently, a water quality index (WQI) requires some water quality parameters …
sources. Concurrently, a water quality index (WQI) requires some water quality parameters …
An intelligent healthcare monitoring framework using wearable sensors and social networking data
Wearable sensors and social networking platforms play a key role in providing a new
method to collect patient data for efficient healthcare monitoring. However, continuous …
method to collect patient data for efficient healthcare monitoring. However, continuous …
Applications of artificial intelligence for disaster management
Natural hazards have the potential to cause catastrophic damage and significant
socioeconomic loss. The actual damage and loss observed in the recent decades has …
socioeconomic loss. The actual damage and loss observed in the recent decades has …
[HTML][HTML] Landslide susceptibility prediction using slope unit-based machine learning models considering the heterogeneity of conditioning factors
To perform landslide susceptibility prediction (LSP), it is important to select appropriate
mapping unit and landslide-related conditioning factors. The efficient and automatic multi …
mapping unit and landslide-related conditioning factors. The efficient and automatic multi …
[HTML][HTML] Landslide susceptibility mapping using machine learning: A literature survey
Landslide is a devastating natural disaster, causing loss of life and property. It is likely to
occur more frequently due to increasing urbanization, deforestation, and climate change …
occur more frequently due to increasing urbanization, deforestation, and climate change …