Method for performing rainfall prediction using machine learning, involves collecting historical weather data from weather stations or remote sensing systems, and preprocessing collected data before training machine learning models
	SIVARAMAN K; SAI S P; AJAY P; KUMAR K P; RAJABHUSHANAM C; PRADA J S P
	2023-10-17
专利权人	BHARATH HIGHER EDUCATION & RES INST (BHAR-Non-standard)
申请日期	2023-10-17
专利号	IN202341070491-A
成果简介	NOVELTY - The method involves gathering historical weather data including rainfall measurements, temperature, humidity, wind speed, atmospheric pressure, and other relevant variables. The data is collected from weather stations or remote sensing systems including satellites. The collected data needs to be cleaned and preprocessed before can be used for training machine learning models. Outliers are removed, missing values are handled for normalizing or scaling the data, and feature engineering is performed if necessary. The historical rainfall data and various meteorological factors are leveraged to make accurate predictions about future precipitation patterns. USE - Rainfall prediction method using machine learning for forecasting amount and timing of rainfall in particular area. ADVANTAGE - The method enables leveraging historical rainfall data and various meteorological factors to make accurate predictions about future precipitation patterns. The method enables providing service delivery model for enabling convenient on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or interaction with a service provider.
IPC 分类号	G06K-009/62 ; G06N-020/00 ; G06Q-010/04 ; G06Q-010/06 ; G06Q-050/06
国家	印度
专业领域	信息技术
语种	英语
成果类型	专利
文献类型	科技成果
条目标识符	http://119.78.100.226:8889/handle/3KE4DYBR/19511
专题	中国科学院新疆生态与地理研究所
作者单位	BHARATH HIGHER EDUCATION & RES INST (BHAR-Non-standard)
推荐引用方式 GB/T 7714	SIVARAMAN K,SAI S P,AJAY P,et al. Method for performing rainfall prediction using machine learning, involves collecting historical weather data from weather stations or remote sensing systems, and preprocessing collected data before training machine learning models. IN202341070491-A[P]. 2023.

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