Call for Paper - January 2023 Edition
IJCA solicits original research papers for the January 2023 Edition. Last date of manuscript submission is December 20, 2022. Read More

Climate Modeling System with Adaptation of Neural Network and AI Data Mining Techniques

Print
PDF
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Ahmed Mateen, Salman Afsar, Amir Waheed, Zulfiqar Ali
10.5120/ijca2016911908

Ahmed Mateen, Salman Afsar, Amir Waheed and Zulfiqar Ali. Climate Modeling System with Adaptation of Neural Network and AI Data Mining Techniques. International Journal of Computer Applications 152(8):25-28, October 2016. BibTeX

@article{10.5120/ijca2016911908,
	author = {Ahmed Mateen and Salman Afsar and Amir Waheed and Zulfiqar Ali},
	title = {Climate Modeling System with Adaptation of Neural Network and AI Data Mining Techniques},
	journal = {International Journal of Computer Applications},
	issue_date = {October 2016},
	volume = {152},
	number = {8},
	month = {Oct},
	year = {2016},
	issn = {0975-8887},
	pages = {25-28},
	numpages = {4},
	url = {http://www.ijcaonline.org/archives/volume152/number8/26341-2016911908},
	doi = {10.5120/ijca2016911908},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

The purpose of this study is to develop a climate modeling system by using data mining techniques which are the process of extracting needed information’s from the large database. Thus, the fetching information can be used into practical knowledge for future prediction in climate scenario. It is a powerful and new technology which helps to analyze the hidden predictive information and define the rules for different group of peoples which are working like flood management, hurricane experts, scientists, farmers, weather belonging, social networking etc. to properly manage their needs according to spatial data analysis and plan their coming goals accordingly. In this paper, data mining procedures are used with generalized Neural Network technique which is useful for weather forecasting quickly with the help of data clustering and screening. Giving that investigative instrument to view and utilize this information for decision making processes by taking examples from real life. It is difficult to manage and handle huge data manually. This study gives us number of facilities for inserting, deleting, editing and saving data. This research improves the system performance and information search services which can enhance the quality by regularities in the behavior analysis with respect to time and seasonal data management with Artificial Intelligence with machine learning and pattern analysis.

References

  1. Camilli, R., and Vivoni, E. R., 2003. Real-time streaming of environmental field data. Journal of Computers and Geosciences, 29(4): 457-468.
  2. Armoush, A., Salewski, F., and Kowalewski, S., 2009. Design Pattern representation for Safety-Critical Embedded Systems. Journal of Software Engineering & Applications, 2(1): 1-12.
  3. Halder, R., Pal, S., and Cortesi, A., 2010. Watermarking Techniques for Relational Databases. Journal of Universal Computer Science, 16(21): 3164-3190.
  4. Kusiak, A., Zheng H., and Song, Z., 2009.  Wind farm power prediction: a data-mining approach. Journal of Wind Energy, 12(3): 275-293.
  5. https://docs.oracle.com/cd/B10500_01/server.920/a96520/concept.htm
  6. Sreehari1, E., Velmuruganv, J., and Venkatesan, M., 2016. A survey paper on climate changes prediction using data mining.
  7. http://www.oxfordjornals.org/our_journals/tropej/online/ma_chap2.pdf
  8. Sethi, N., and Garg, K., 2014. Exploiting data mining technique for rainfall prediction. International Journal of Computer Science and Information Technologies. Vol. 5 (3) , 3982-3984
  9. Olaiya, F., and Adeyemo, A. B., 2012. Application of data mining techniques in weather prediction and climate change studies. International Journal of Information Engineering and Electronic Business, 1: 51-59 MECS (http://www.mecs-press.org/) DOI: 10.5815/ijieeb.2012. 01.07.
  10. Kumar, V., and Chadha, A., 2011. An Empirical Study of the Applications of Data Mining Techniques in Higher Education. International Journal of Advanced Computer Science and Applications, 2(3): 80-84.
  11. Muhammad,A,C., Muhammad,F., Rashid,A and Hassan M., 2006. Climatic trends in Faisalabad (Pakistan) over the last 60 years. Journal of Agricultural Sociology and Sciences, 2(1): 42-45.

Keywords

Data Mining, Forecasting, Prediction, Neural Network, Artificial Intelligence, Machine learning