Year: 2023
Type: article
Abstract: These days, climate change is accelerating due to global warming, which has a major influence on humanity. Sea levels are rising, the atmosphere and ocean are warming, and there are more floods and droughts as a result. Uneven rainfall or precipitation is one of the main effects of it. Today, most of the important global authorities are taking into consideration the laborious problem of precipitation forecasting. One climatic factor that has an impact on the many human activities is precipitation. like manufacturing, production, and tourism in the agricultural sector. Rainfall becomes extremely problematic as a result, necessitating more accurate forecasts. Accurate rainfall forecasting is crucial for all of these reasons. There are several ways to forecast it, but the one that is chosen for the objective of this assignment is to analyze and compile rainfall data from the past 12 months, gathered over a period of 5 years. The goal is to utilize this data to forecast rainfall for the following day. To achieve this, the project aims to optimize the results by employing a random forest classifier as a machine learning model for predicting rainfall.
Source: Vidhyayana
DOI: 10.58213/knbqvm64
Authors: Aditya Nikhade, Rahul Khetale
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: diamond
OpenAlex ID: W7214488223