Implementation of Data Mining Techniques for Meteorological Data Analysis (A case study for Gaza Strip)

Meteorological data mining is a form of data mining concerned with finding hidden patterns inside largely available meteorological data, so that the information retrieved can be transformed into usable knowledge. Weather is one of the meteorological data that is rich by important knowledge. In this paper we try to extract useful knowledge from weather daily historical data collected locally at Gaza Strip city. The data include nine years period [1977-1985]. After data preprocessing, we apply outlier analysis, clustering, prediction, classification and association rules mining techniques. For each mining technique, we present the extracted knowledge and describe its importance in meteorological field.

[1]  Jing Shi,et al.  On comparing three artificial neural networks for wind speed forecasting , 2010 .

[2]  Tasha R. Inniss.  Seasonal clustering technique for time series data , 2006, Eur. J. Oper. Res..

[3]  Jay P. Breidenbach,et al.  Real-Time Correction of Spatially Nonuniform Bias in Radar Rainfall Data Using Rain Gauge Measurements , 2002 .

[4]  Zahoor Jan,et al.  Seasonal to Inter-annual Climate Prediction Using Data Mining KNN Technique , 2008, IMTIC.

[5]  Sotiris Kotsiantis,et al.  Using Data Mining Techniques for Estimating Minimum, Maximum and Average Daily Temperature Values , 2007 .

[6]  Turgay Tugay Bilgin,et al.  A Data Mining Application on Air Temperature Database , 2004, ADVIS.

[7]  Ladislav Hluchý,et al.  Prediction of significant meteorological phenomena using advanced data mining and integration methods , 2010, 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery.

[8]  Li-Yen Shue,et al.  Data mining to aid policy making in air pollution management , 2004, Expert Syst. Appl..

[9]  Ladislav Hluchý,et al.  Data mining and integration for predicting significant meteorological phenomena , 2010, ICCS.

[10]  P. Rousseeuw.  Least Median of Squares Regression , 1984 .

[11]  Weili Wu,et al.  Mining dynamic interdimension association rules for local-scale weather prediction , 2004, Proceedings of the 28th Annual International Computer Software and Applications Conference, 2004. COMPSAC 2004..

[12]  Kourosh Mohammadi,et al.  Parameter estimation of an ARMA model for river flow forecasting using goal programming , 2006 .

[13]  Hui Lin,et al.  Application of Association Rule in Disaster Weather Forecasting , 2004, Ann. GIS.

[14]  Rahul Ramachandran,et al.  Real-time storm detection and weather forecast activation through data mining and events processing , 2008, Earth Sci. Informatics.

[15]  Witold Pedrycz,et al.  Classification of meteorological volumetric radar data using rough set methods , 2003, Pattern Recognit. Lett..

[16]  K. Qina,et al.  CLOUD MODEL AND HIERARCHICAL CLUSTERING BASED SPATIAL DATA MINING METHOD AND APPLICATION , 2008 .

[17]  Pavel Berkhin,et al.  A Survey of Clustering Data Mining Techniques , 2006, Grouping Multidimensional Data.

[18]  Thomas Nocke,et al.  Methods for the visualization of clustered climate data , 2004, Comput. Stat..

[19]  K. J. Siddiqui,et al.  Knowledge based system for weather information processing and forecasting , 1996, IGARSS '96. 1996 International Geoscience and Remote Sensing Symposium.