Collection of Weather Data from Authentic Websites and Secondary Data Sources for Rainfall Prediction
Creators
- 1. Department of Computer Science & Applications, Maharshi Dayanand University, Rohtak (Haryana), India.
- 1. Department of Computer Science & Applications, Maharshi Dayanand University, Rohtak (Haryana), India.
- 2. Assistant Professor, Department of Computer Science & Applications, Maharshi Dayanand University, Rohtak (Haryana), India.
Description
Abstract: The field of data mining and machine learning has been grown many folds from the last two decades. Almost every other problem can be solved using data mining and this becomes the most tempting part of it for the scientist and researchers all over the world. Data mining can be viewed as a process of discovering knowledge. This discovery of knowledge starts with the collection of data and ends with the acquired knowledge in the form of patterns. Data collection lays the foundation for the process of knowledge discovery. In this paper, various secondary data sources from where data can be collected for rainfall prediction are deeply studied and analyzed. Some of these authentic websites and secondary data sources are NCDC (National climate data center), Kaggle, Datahub.io, UCI machine learning repository, Earth Data etc. The data collected from these secondary data sources for rainfall prediction have been critically analyzed and compared on the parameters of Accuracy, Completeness, reliability, relevance, and timeliness.
Files
B1626113223.pdf
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Additional details
Identifiers
- DOI
- 10.54105/ijdm.B1626.113223
- ISSN
- 2582-9246
Dates
- Accepted
-
2023-11-15Manuscript received on 09 May 2023 | Revised Manuscript received on 19 May 2023 | Manuscript Accepted on 15 November 2023 | Manuscript published on 30 November 2023
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