Abstract
The paper emphasis on an instinctual and efficacious method to forecast and analyze the condition of different atmospheric determinants all over the world. The difficulty in the extant remedies or the apparatus is its incapability to provide a comprehensive information regarding the evaluation of the attributes of the atmosphere. The proposed methodology in the paper gathers the actual information about the atmospheric attributes such as the water, air, the forest and the tree cover etc. from the government bases and processes the collective information. The methodology does the extrication transformation load over the original collective data's that are in its raw format. The converted information sets are imported into the database to develop a dash boards with the multiple information's displayed on it. This allows to have an evaluated data about the various atmospheric factors. To forecast the deteriorations and the conditions of the atmospheric attributes the methodology proffered utilizes the Fuzzy C means clustering, R-studio, and the ARIMA frame work. The dash board assists the NLP enabling the end users to post their queries as input and get back the desired output. The developed deterioration forecasting and evaluation can be used in the evaluation of the conditions of atmospheric attributes for the different countries in the world.
References
- Gore, Ranjana Waman, and Deepa S. Deshpande. "An approach for classification of health risks based on air quality levels." In 2017 1st International Conference on Intelligent Systems and Information Management (ICISIM), pp. 58-61. IEEE, 2017.
- Taneja, Shweta, Nidhi Sharma, Kettun Oberoi, and Yash Navoria. "Predicting trends in air pollution in Delhi using data mining." In 2016 1st India International Conference on Information Processing (IICIP), pp. 1-6. IEEE, 2016.
- Yuheng, S., K. Yingchun, and C. Jing. "Ecological water quality assessment system based on BP neural network." In Information Technology and Mechatronics Engineering Conference (ITOEC), IEEE. 2017.
- Kingsy, Grace R., R. Manimegalai, Devasena MS Geetha, S. Rajathi, K. Usha, and Baseria N. Raabiathul. "Air pollution analysis using enhanced K-Means clustering algorithm for real time sensor data." In 2016 IEEE Region 10 Conference (TENCON), pp. 1945-1949. IEEE, 2016.
- Souza, Fabio T., and William S. Rabelo. "A data mining approach to study the air pollution induced by urban phenomena and the association with respiratory diseases." In 2015 11th International Conference on Natural Computation (ICNC), pp. 1045-1050. IEEE, 2015.
- Dhore, Aishwarya, Anagha Byakude, Bhagyashri Sonar, and Mansi Waste. "Weather prediction using the data mining techniques." Int. Res. J. Eng. Technol.(IRJET) 4, no. 5 (2017): 2562-2565.
- Yan, Hongmei, Yueming Liu, Xiaohong Han, and Yangyang Shi. "An evaluation model of water quality based on DSA-ELM method." In 2017 16th International Conference on Optical Communications and Networks (ICOCN), pp. 1-3. IEEE, 2017.
- Kaur, Pawandeep. "A Comprehensive Review on Air Pollution Detection Using Data Mining Techniques." Training 6, no. 09 (2019).
- Wang, Jinghan, Jinnan Zhang, XueGuang Yuan, Yu Tang, Hongyu Hao, Yong Zuo, Zebin Tan et al. "Air quality data analysis and forecasting platform based on big data." In 2019 Chinese Automation Congress (CAC), pp. 2042-2046. IEEE, 2019.
- Smys, S., and C. V. Joe. "Big Data Business Analytics as a Strategic Asset for Health Care Industry." Journal of ISMAC 1, no. 02 (2019): 92-100.
- Joseph, S. Iwin Thanakumar, and Iwin Thanakumar. "Survey of data mining algorithm’s for intelligent computing system." Journal of trends in Computer Science and Smart technology (TCSST) 1, no. 01 (2019): 14-24.
- Raj, Jennifer S. "A Comprehensive Survey on the Computational Intelligence Techniques and Its Applications." Journal of ISMAC 1, no. 03 (2019): 147-159.
- Raj, Jennifer S., and J. Vijitha Ananthi. "Automation Using Iot in Greenhouse Environment." Journal of Information Technology 1, no. 01 (2019): 38-47.