IJBTT

Disaster Prediction System Using IBM SPSS Data Mining Tool

	International Journal of Engineering Trends and Technology (IJETT)
	© 2013 by IJETT Journal
	Volume-4 Issue-8
	Year of Publication : 2013
	Authors : B.Renuka Devi , Dr.K.Nageswara Rao , Dr.S.Pallam Setty , Dr.M.Nagabhushana Rao

Citation 

B.Renuka Devi , Dr.K.Nageswara Rao , Dr.S.Pallam Setty , Dr.M.Nagabhushana Rao. "Disaster Prediction System Using IBM SPSS Data Mining Tool". International Journal of Engineering Trends and Technology (IJETT). V4(8):3352-3357 Jul 2013. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group.

Abstract

Data mining, or knowledge discovery in databases, refers to the discovery of interesting , implicit, and previously unknown knowledge from large databases. Spatial data mining presents new challenges due to the large size of spatial data, the complexity of spatial data types, and the special nature of spatial access methods. Spatial data mining is the task of unfolding the knowledge hidden in the spatial databases. By collecting spatial data i.e patients’ data, we analyze, predict and interpret the data to the health organizations for conducting Campaigns. The spatial Databases contain both spatial and non - spatial attributes .In this paper we focus effectively in designing disaster prediction system to identify the Dengue disease using Data mining tools i.e SPSS Modeler and Data mining algorithms

References

1. Alan T.Murray, Ingrid McGuffog, John S.Western and Patrick Mul lins, Exploratory Spatial Data Analysis for Examining Urban Crime, 2001 . www.gegraphy.hunter.cuny.edu
2. Bavani Arunasalam, Sanjay Chawla, Pei Sun and Robert M unro, M ining Complex Relationships in the SDSS SkyServer Spatial Database, School of Information Tec hnologies, University of Sydney, proceedings of 28th annual international computer software and application conference (CONPSAC - 04), 2004, IEEE.
3. Chawla , S he kkar, Spatial Databases: A Tour, 2003, Prentice all. ( ISBN – 013 – 017 480 – 7 )
4. Hardy Pundt, Evaluating t he relevance of spatial dat a in time critical situations, U niversity of Applied Sciences and Research, Faculty of Automatisation and Computer Scienc e , wernigerode (DE), pp 779 – 788, 2005, www.springer.com/3 - 540 - 249988 - 5.
5. Huang , Shekkar, Xiong, Discovery Collocation Patterns fro m Spatial Data Sets: A General Approach , IEEE - KDE , volume 16 , No: 12 , dec 2004.
6. Knorr and Ng, Extraction of Spatial Proximit y Patterns by Concept Generalization , proceedings second international conference of KDD, pp. 347 – 350, aug 1996.
7. Koperski and Han, Discovery of Spatial Association Rules in GI Databases , proceedings 4th international symposium large spatial databases, p p. 44 - 66, aug 1995.
8. Munro , Chawla , Complex Spatial Relationships, proceedings of IEEE international conference on data mining, 2003.
9. Martin Ester, Hans - Peter Kriegel, Jörg Sander, Spatial Data Mining: A Database Approach, Institute for Computer Science, University of Munich , proceedings of 5th international symposium of large special databases, 2007.
10. Masaharu Yoshioka, Yasuhiro Shamoto, Tetsuo Tomiyama, an Application of the Knowledge Intensive Engineering Framework to Architectural Design , a research p roject of GNOSIS, IMS Program, 1998.
11. Naresh Raheja, Ruby Ojha, Sunil R Mallik, Role of internet - based GIS in effective natural disaster m anagement,R. M. S.I. www.development.net/technology/gis/
12. Nagab hushana Rao, Ramesh babu , Sangameswar , Spatia l Knowledge Algorithm For epidemics Using Data Mining Techniques. International conference - ICSCI - 2008, Hyderabad , Jan 2008.
13. Nagabhushana Rao M , S.V.V.D.Venugopal, Disaster Management System for Dengue , IJCST /33/4/A - 1021 http://ijcst.com/?page_id=2618
14. Shaw C. Feng, Y. Zhang: Conceptual Process Planning - A Definition and Functional Decomposition, Manufacturing Engineering Laboratory, National Institute of Stand ards and T echnology 1997 .
15. Yan Huang, Hui Xiong, Shashi Shekhar, Jain Pei, “Mining Confident Collocation Rules without A support Threshold” . Symposium on applied computing, proceeding of the 2003 ACM Symposium on Applied Computing, Florida, PP: 497 - 501, 2003, ISBN: 1 - 58113 - 624 - 2.
16. New Initiatives in Deng ue Control in Singapore byTan Boon Teng. Dengue Bulletin – Vol 25, 2001
17. Vector Densities That Potentiate Dengue Outbreaks in A Brazilian City , Ricardo J. S. Pontes, Jonathan Freeman, Jose ? Wellington Olive ira - Lima, J. Christina Hodgson, And Andrew Spielman, Am. J. Trop. Med. Hyg., 62(3), 2000, pp. 378 – 383
18. Argyrous, G. Statistics for Research: With a Guide to SPSS, SAGE, London .
19. Pete Chapman, Julian Clinton, Randy Kerber, Thomas Khabaza, Thomas Reinartz, Colin Shearer, and Rüdiger Wirth (2000); CRISP - DM 1.0 Step - by - step data mining guide
20. http://pu blic.dhe.ibm.com/common/ssi/ecm/en/ytw03085usen/Y TW03085USEN.PDF

Keywords
C5.0 Algorithm, Dengue Fever, Spatial Data Mining, SPSS Modeler, SPSS Statistics