Data mining for environmental analysis and effect of weather on agriculture

Abstract

The present study deals with “Data mining for environmental analysis and effect of weather on agriculture.” A government platform's cluster largest sample on the shifting climate toward agriculture has been gathered. The question of whether agriculture has been impacted by the changing climate was examined. In practically every economy, the use of data mining techniques for environmental analysis in agriculture is important. Thus, it can be concluded from the statistics that agriculture generates enormous amounts of data per second at a high pace and variety. It is quite challenging to analyze these data and make judgments based on the data using conventional tools and procedures.

As a result, a significant quantity of goods as well as labor, fertilizers, and other resources are squandered. To study the data, big data analysis is the most effective method. The government's statistics clearly demonstrates the huge impact that data mining techniques have on weather and agriculture. The primary goal of this paper is to present the discussion of big data analytics and how its tools are used in the agricultural sector. The analysis revealed that the algorithm (data base technology) is a major factor in the weather information provided by agricultural platforms. The idea is supported by the findings.