A5032359229- Transportation Planning and Optimization
- Air Quality Monitoring and Forecasting
- Energy, Environment, and Transportation Policies
- Traffic Prediction and Management Techniques
- Energy and Environment Impacts
- Air Quality and Health Impacts
- Traffic control and management
- Vehicle emissions and performance
- Environmental Impact and Sustainability
- Water Quality Monitoring and Analysis
- Traffic and Road Safety
- Granular flow and fluidized beds
- Energy, Environment, Economic Growth
- Mineral Processing and Grinding
- Energy Load and Power Forecasting
- Socioeconomic Development in MENA
- Hybrid Renewable Energy Systems
- Flood Risk Assessment and Management
- Marine and coastal ecosystems
- Urban Transport and Accessibility
- Sustainable Building Design and Assessment
- Solar Radiation and Photovoltaics
- Water-Energy-Food Nexus Studies
- Iron and Steelmaking Processes
- COVID-19 impact on air quality
King Fahd University of Petroleum and Minerals
2016-2025
University of Chittagong
2022
Bridge University
2022
Guy's and St Thomas' NHS Foundation Trust
2021
South Dakota State University
2017
Even though the contribution of aviation sector to global economy is very notable, it also has an adverse impact on climate change. Improvements have been made in different areas (i.e., technology, sustainable fuel, and design) mitigate these effects. However, rate improvement small compared increase demand for air transportation. Hence, greenhouse gas emissions are steadily increasing this trend expected continue unless adequately addressed. In context, study examined following: (i) factors...
Improved irradiance forecasting ensures precise solar power generation forecasts, resulting in smoother operation of the distribution grid. Empirical models are used to estimate irradiation using a wide range data and specific national or regional parameters. In contrast, algorithms based on Artificial Intelligence (AI) becoming increasingly popular effective for estimating irradiance. Although there has been significant development this area elsewhere, employing an AI model investigate...
Predicting crash injury severity is a crucial constituent of reducing the consequences traffic crashes. This study developed machine learning (ML) models to predict using 15 crash-related parameters. Separate ML for each cluster were obtained fuzzy c-means, which enhanced predicting capability. Finally, four developed: feed-forward neural networks (FNN), support vector (SVM), C-means clustering based network (FNN-FCM), and c-means (SVM-FCM). Features that easily identified with little...
Vehicle automation and communication technologies are considered promising approaches to improve operational driving behavior. The expected gradual implementation of autonomous vehicles (AVs) shortly will cause unique impacts on the traffic flow characteristics. This paper focuses reviewing under a mixed environment AVs regular (RVs) considering different AV includes policy implication discussion for possible actual future practice research interests. has positive flow, such as improved...
The growth of population, gross domestic product (GDP), and urbanization have led to an increase in greenhouse gas (GHG) emissions the Kingdom Saudi Arabia (KSA). leading GHG-emitting sectors are electricity generation, road transportation, cement, chemicals, refinery, iron, steel. However, KSA is working lead global energy sustainability campaign reach net zero GHG by 2060. In addition, country establish a framework for circular carbon economy (CCE), which hydrogen acts as transversal...
ABSTRACT Climate change poses a significant threat to the security and sustainability of global food systems, particularly in vulnerable regions such as Bangladesh. This paper comprehensively reviews impact climate on system Specifically, it examines country's and, climatic conditions endangering systems associated vulnerabilities. A systematic review methodology was adopted select relevant literature, based predefined inclusion criteria research questions. To mitigate selection bias, team...