International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 152 - Number 8 |
Year of Publication: 2016 |
Authors: Ahmed Mateen, Salman Afsar, Amir Waheed, Zulfiqar Ali |
10.5120/ijca2016911908 |
Ahmed Mateen, Salman Afsar, Amir Waheed, Zulfiqar Ali . Climate Modeling System with Adaptation of Neural Network and AI Data Mining Techniques. International Journal of Computer Applications. 152, 8 ( Oct 2016), 25-28. DOI=10.5120/ijca2016911908
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.