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In this study, a novel machine learning approach was used to classify three types of synoptic weather events in Taiwan area from 2001 to 2010. We used reanalysis data with three machine learning algorithms to recognize weather systems and…

Atmospheric and Oceanic Physics · Physics 2019-05-22 Shih-Hao Su , Jung-Lien Chu , Ting-Shuo Yo , Lee-Yaw Lin

Floods are one of the most common natural disasters, with a disproportionate impact in developing countries that often lack dense streamflow gauge networks. Accurate and timely warnings are critical for mitigating flood risks, but…

Prediction of the extent and probability of debris flow under rainfall conditions can contribute to precautionary activities through risk quantification. To this end, quantifying the debris-flow risk against rainfall involves three…

Applications · Statistics 2022-11-15 Kazuki Yamanoi , Satoru Oishi , Kenji Kawaike

This paper proposes a novel framework to predict traffic flows' bandwidth ahead of time. Modern network management systems share a common issue: the network situation evolves between the moment the decision is made and the moment when…

Networking and Internet Architecture · Computer Science 2021-12-07 Maxime Labonne , Jorge López , Claude Poletti , Jean-Baptiste Munier

Floods are one of nature's most catastrophic calamities which cause irreversible and immense damage to human life, agriculture, infrastructure and socio-economic system. Several studies on flood catastrophe management and flood forecasting…

Nowadays, many cities are equipped with surveillance systems and traffic control centers to monitor vehicular traffic for road safety and efficiency. The monitoring process is mostly done manually which is inefficient and expensive. In…

Machine Learning · Computer Science 2021-08-30 Sepehr Sabour , Sanjeev Rao , Majid Ghaderi

Rainfall prediction is one of the challenging and uncertain tasks which has a significant impact on human society. Timely and accurate predictions can help to proactively reduce human and financial loss. This study presents a set of…

Machine Learning · Computer Science 2019-10-31 Nikhil Oswal

Human activities accelerate consumption of fossil fuels and produce greenhouse gases, resulting in urgent issues today: global warming and the climate change. These indirectly cause severe natural disasters, plenty of lives suffering and…

In the monsoon season, sudden flood events occur frequently in urban areas, which hamper the social and economic activities and may threaten the infrastructure and lives. The use of an efficient large-scale waterlogging sensing and…

Computer Vision and Pattern Recognition · Computer Science 2021-08-17 Shi-Wei Lo , Jyh-Horng Wu , Jo-Yu Chang , Chien-Hao Tseng , Meng-Wei Lin , Fang-Pang Lin

Environmental disasters such as flash floods are becoming more and more prevalent and carry an increasing burden on human civilization. They are usually unpredictable, fast in development, and extend across large geographical areas. The…

Systems and Control · Electrical Eng. & Systems 2020-10-30 Kun Qian , Christian G. Claudel

The prevention of domestic violence (DV) have aroused serious concerns in Taiwan because of the disparity between the increasing amount of reported DV cases that doubled over the past decade and the scarcity of social workers. Additionally,…

Computers and Society · Computer Science 2017-10-19 Ya-Yun Chen , Chia-Kai Liu , Yu-Hsiu Wang , Sue-Chuan Chen , Yi-Shan Hsieh , Jing-Tai Ke , T. C. Hsieh

Floods are the most common form of natural disaster and accurate flood forecasting is essential for early warning systems. Previous work has shown that machine learning (ML) models are a promising way to improve flood predictions when…

Machine Learning · Computer Science 2025-04-18 Emil Ryd , Grey Nearing

Post-wildfire mudflows are increasingly hazardous due to the prevalence of wildfires, including those on the wildland-urban interface. Upon burning, soil on the surface or immediately beneath becomes hydrophobic, a phenomenon that occurs…

Machine Learning · Computer Science 2026-02-13 Mahta Movasat , Ingrid Tomac

Urban rail transit provides significant comprehensive benefits such as large traffic volume and high speed, serving as one of the most important components of urban traffic construction management and congestion solution. Using real…

Machine Learning · Computer Science 2023-05-05 Yiming Hu , Yangchuan Huang , Shuying Liu , Yuanyang Qi , Danhui Bai

Water supplies are crucial for the development of living beings. However, change in the hydrological process i.e. climate and land usage are the key issues. Sustaining water level and accurate estimating for dynamic conditions is a critical…

Neural and Evolutionary Computing · Computer Science 2019-06-27 Sadaqat ur Rehman , Zhongliang Yang , Muhammad Shahid , Nan Wei , Yongfeng Huang , Muhammad Waqas , Shanshan Tu , Obaid ur Rehman

Floods are among the most destructive natural disasters, which are highly complex to model. The research on the advancement of flood prediction models contributed to risk reduction, policy suggestion, minimization of the loss of human life,…

Machine Learning · Computer Science 2020-08-10 Amir Mosavi , Pinar Ozturk , Kwok-wing Chau

The ability to predict traffic flow over time for crowded areas during rush hours is increasingly important as it can help authorities make informed decisions for congestion mitigation or scheduling of infrastructure development in an area.…

Machine Learning · Computer Science 2023-04-03 Zann Koh , Yan Qin , Yong Liang Guan , Chau Yuen

Taiwan's high population and heavy dependence on fossil fuels have led to severe air pollution, with the most prevalent greenhouse gas being carbon dioxide (CO2). There-fore, this study presents a reproducible and comprehensive case study…

Artificial Intelligence · Computer Science 2025-10-08 Gordon Hung , Salinna Abdullah

Rainfall-induced landslides pose a growing risk worldwide as climate change intensifies extreme rainfall events. To provide sufficient evacuation time, landslide early warning systems (LEWS) for real-time disaster monitoring must estimate…

Machine Learning · Computer Science 2026-05-19 Ren Ozeki , Hamada Rizk , Hirozumi Yamaguchi

Despite the progress within the last decades, weather forecasting is still a challenging and computationally expensive task. Current satellite-based approaches to predict thunderstorms are usually based on the analysis of the observed…

Machine Learning · Computer Science 2019-12-04 Christian Schön , Jens Dittrich , Richard Müller
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