Work

Extreme Rainfall Time Series Prediction: A Comparative Analysis of SARIMA, Random Forest, LSTM and Prophet Models

Year: 2024

Type: conference-paper

Source: International Conference on Software Process Improvement (CIMPS)

DOI: 10.1109/cimps65195.2024.11095938

Authors: Martin Antonio Santos-Romero, José Manuel Camacho Sanabria, Juan Antonio Álvarez Trinidad, Rosalía Chávez Alvarado, Alicia G. Robertos Pinto

Institutions: Instituto Tecnológico de Chetumal, Secretaría de Ciencia, Humanidades, Tecnología e Innovación, Universidad Autónoma de Chiapas

Language: English

Topic: Hydrological Forecasting Using AI

Subfield: Environmental Engineering

Field: Environmental Science

Domain: Physical Sciences

SDGs: Climate action, Clean water and sanitation, Sustainable cities and communities

Open Access status: closed

OpenAlex ID: W4412934156

FWCI: 1.103

Cites: 23

Cited by: 1

Related to: 10