Medical imaging, network traffic analysis, environmental systems, and other sectors have benefited from the development of diverse data mining methods. The environment system is now the most essential topic of concern for individuals in today’s society, as it has a daily impact on human lives. ES elements such as earthquakes, soil erosion, deforestation, rising summer temperatures, rain fall density/intensity, flood occurrences, and the most significant is the impact of all of these ES factors on human people and their behaviour, both directly and indirectly. Data mining methods can be used to uncover patterns in data that is widely spread, heterogeneous, sparse, multidimensional, and heterogeneous, such as data from the Environment System. This study provides a brief overview of the key phases, techniques, and processes involved in developing and dealing with ES data, which are critical in the development of a data mining tool for detecting and understanding patterns in environmental system data sets. The data mining techniques used in the design of ES Tool span from processing crude data sets to translating them into patterns for examination.
Author (S) Details
M. S. Chaudhari
Department of Computer Science & Engineering, Priyadarshini Bhagwati College of Engineering, RTM Nagpur University, Nagpur, Maharashtra, India.
Priyadarshini Bhagwati College of Engineering, RTM Nagpur University, Nagpur, Maharashtra, India.
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