Predicting Rainfall by Fuzzy Logic DOI
Jaime Santos‐Reyes,

Yunue Garcia-Pimentel

Advances in computational intelligence and robotics book series, Journal Year: 2024, Volume and Issue: unknown, P. 99 - 117

Published: April 29, 2024

Water is vital to all living things; water life. According the UNDP scarcity affects more than two billion people and it projected rise as temperatures do due climate change. The chapter presents some preliminary results of rainfall prediction for case Mexico City by considering input variables, temperature (T) wind speed (WS). A fuzzy logic rule-based approach was employed in analysis. presented model has potential not only predict but also drought. Moreover, been highlighted that becomes necessary address droughts designing implementing drought disaster management systems mitigate impact such events. Therefore, prediction, an early warning, plays a key role measures achieve this. More generally, hoped approaches herein may contribute better understanding impacts regions, cities, communities prone hazard.

Language: Английский

Solving flood problems with deep learning technology: Research status, strategies, and future directions DOI
Hongyang Li,

Mingxin Zhu,

Fangxin Li

et al.

Sustainable Development, Journal Year: 2024, Volume and Issue: unknown

Published: June 8, 2024

Abstract As a frequent and devastating natural disaster worldwide, floods are influenced by complex factors. Building flood models for simulating, monitoring, forecasting is crucial to reduce the risk of disasters minimize damage people property. With advancements in computing power impressive capabilities deep learning such areas as classification prediction, there has been growing interest using this technology research. There also body research into building data‐driven with learning. Based on this, study adopts mixed‐method approach bibliometric qualitative analyses provide an overview The status revealed visualization, where objects defined from perspective, strategies explained perspective comprehensive in‐depth understanding problem how apply solve it. In addition, reflects future direction improvement innovation needed promote further development exploration

Language: Английский

Citations

1
Predicting Rainfall by Fuzzy Logic DOI
Jaime Santos‐Reyes,

Yunue Garcia-Pimentel

Advances in computational intelligence and robotics book series, Journal Year: 2024, Volume and Issue: unknown, P. 99 - 117

Published: April 29, 2024

Water is vital to all living things; water life. According the UNDP scarcity affects more than two billion people and it projected rise as temperatures do due climate change. The chapter presents some preliminary results of rainfall prediction for case Mexico City by considering input variables, temperature (T) wind speed (WS). A fuzzy logic rule-based approach was employed in analysis. presented model has potential not only predict but also drought. Moreover, been highlighted that becomes necessary address droughts designing implementing drought disaster management systems mitigate impact such events. Therefore, prediction, an early warning, plays a key role measures achieve this. More generally, hoped approaches herein may contribute better understanding impacts regions, cities, communities prone hazard.

Language: Английский

Citations

0