[HTML][HTML] A survey of artificial intelligence methods for renewable energy forecasting: Methodologies and insights
The efforts to revolutionize electric power generation and produce clean and sustainable
electricity have led to the exploration of renewable energy systems (RES). This form of …
electricity have led to the exploration of renewable energy systems (RES). This form of …
[HTML][HTML] Machine learning for road traffic accident improvement and environmental resource management in the transportation sector
M Megnidio-Tchoukouegno, JA Adedeji - Sustainability, 2023 - mdpi.com
Despite the measures put in place in different countries, road traffic fatalities are still
considered one of the leading causes of death worldwide. Thus, the reduction of traffic …
considered one of the leading causes of death worldwide. Thus, the reduction of traffic …
[HTML][HTML] Short-term traffic congestion prediction using hybrid deep learning technique
M Anjaneyulu, M Kubendiran - Sustainability, 2022 - mdpi.com
A vital problem faced by urban areas, traffic congestion impacts wealth, climate, and air
pollution in cities. Sustainable transportation systems (STSs) play a crucial role in traffic …
pollution in cities. Sustainable transportation systems (STSs) play a crucial role in traffic …
[PDF][PDF] Shaping smart city transportation with traffic congestion solutions: Bhubaneswar, Odisha
Transportation and connectivity are of the most domineering aspects of developing cities
and is necessary for ensuring the growth of urban areas. The perplexing, perpetual and …
and is necessary for ensuring the growth of urban areas. The perplexing, perpetual and …
A Comparison of ML models for predicting congestion in urban cities
Deepika, G Pandove - International Journal of Intelligent Transportation …, 2024 - Springer
This study predicts traffic congestion in four US cities using various machine learning
models. The research utilizes different regression-based models to predict congestion …
models. The research utilizes different regression-based models to predict congestion …
[HTML][HTML] Ensemble Learning Traffic Model for Sofia: A Case Study
Featured Application Optimizing urban traffic/logistics; estimating pollution due to
combustion engines; studying the relation between urban pollution and respiratory …
combustion engines; studying the relation between urban pollution and respiratory …
The Traffic Jam Phenomenon at Traditional Village: A Case of User Perception in Batam, Indonesia
T Resinta, AI Rifaâ - LEADER: Civil Engineering and …, 2023 - ojs.digitalartisan.co.id
The development of transportation is increasing day by day. Increased transportation can
cause a problem, especially land transportation; the problem is traffic congestion. The road …
cause a problem, especially land transportation; the problem is traffic congestion. The road …
Precision in Insurance Forecasting: Enhancing Potential with Ensemble and Combination Models based on the Adaptive Neuro-Fuzzy Inference System in the …
Enhancing the precision of retention ratio predictions holds profound significance for
insurance industry decision-makers and those vested in advancing insurance services …
insurance industry decision-makers and those vested in advancing insurance services …
Integrated Artificial Intelligence in Data Science
JCW Lin, S Tomasiello, G Srivastava - Applied Sciences, 2023 - mdpi.com
Artificial Intelligence (AI) is increasingly pervading everyday life since it can be used to solve
high-complexity problems, as well as determine optimal solutions, in various domains and …
high-complexity problems, as well as determine optimal solutions, in various domains and …
Traffic prediction in smart cities based on hybrid feature space
In smart cities of the future, data will be generated, integrated, processed and utilized from
heterogeneous sources and at varying levels of complexity. For urban traffic planning in …
heterogeneous sources and at varying levels of complexity. For urban traffic planning in …