Open Access Open Access  Restricted Access Subscription or Fee Access

SLGAS: Supervised Learning Using Gain Ratio as Attribute Selection Measure to Nowcast Snow/No-Snow


(*) Corresponding author


Authors' affiliations


DOI: https://doi.org/10.15866/irecos.v10i2.4841

Abstract


Considering the weather nowcasting, which has no prospect of intervention, they cause the vital results in human life and animal life, accurate analysis and estimation of these variables is very important and crucial. There is an increased interest in nowcasting the bad weather conditions, among which presence of snow/no-snow is crucial, in order to fully capture the global atmospheric water cycle. This paper introduces an efficient decision tree algorithm named Supervised Learning using Gain Ratio as Attribute Selection measure (SLGAS), expanded to our previous algorithm Supervised Learning Using Entropy as Attribute Selection Measure (SLEAS), for the prediction of snow/no-snow using 31 international locations historical datasets, collected from various meteorological departments. The algorithm has been validated extensively with five performance measures namely accuracy, specificity, precision, dice and error rate respectively. Further, we compared our proposed method with the SLIQ and SLEAS decision tree algorithms in terms of the overall classification performance measures and it is clearly showing that the SLGAS algorithm is outperforming with an average accuracy of 85.92%, error rate of 14.07%.
Copyright © 2015 Praise Worthy Prize - All rights reserved.

Keywords


Classification; Decision Tree; SLGAS; Snow; No-Snow

Full Text:

PDF


References


Robert A. Houze: Cloud Dynamics. Academic Press (1994).
http://dx.doi.org/10.1002/qj.49712051918

Nabilah Filzah Mohd Radzuan, Andi Putra, Zalinda Othman, Azuraliza Abu Bakar and Abdul Razak Hamdan: Comparative Study – Three Artificial Intelligence Techniques for Rain Domain in Precipitation Forecast. International Journal of Environmental, Ecological, Geological and Mining Engineering (2013) 898-903.

http://en.wikipedia.org/wiki/Weather_forecasting.

http://en.wikipedia.org/wiki/Quantitative_precipitation_forecast.

J. Han: Data Mining: Concepts and Techniques. Morgan Kaufmann Publishers. (2001)

Irene Y.H. Gu, Unai Sistiaga, Sonja M. Berlijn and Anders Fahlstrom: Online Detection of Snow Coverage and Swing Angles of Electrical Insulators on Power Transmission Lines Using Videos. IEEE International Conference on Image Processing (2009) 3249 – 3252.
http://dx.doi.org/10.1109/icip.2009.5413984

Jinmei Pan, Lingmei Jiang and Lixin Zhang: Wet Snow Detection in the South of China by Passive Microwave Remote Sensing. IEEE International Geo Science and Remote Sensing Symposium (2012) 4863-4866.
http://dx.doi.org/10.1109/igarss.2012.6352523

Yajaira Mejia, Hosni Ghedira, Shayesteh Mahani and Reza Khanbilvardi: A Neural Network Based Approach for Multi-Spectral Snowfall Detection and Estimation, IEEE International Geo Science and Remote Sensing Symposium (2007) 2276 – 2279.
http://dx.doi.org/10.1109/igarss.2007.4423295

Melanie Wetzel, Michael Meyers, Randolph Borys, Ray Mcanelly, William Cotton, Andrew Rossi, Paul Frisbie, David Nadler, Douglas Lowenthal, Stephen Cohn, and William Brown: Mesoscale Snowfall Prediction And Verification In Mountainous Terrain. AMS Journal Of Weather And Forecasting (2004) 806-828.
http://dx.doi.org/10.1175/1520-0434(2004)019%3C0806:mspavi%3E2.0.co;2

Pascal Sirguey, Renaud Mathieu Yves Arnaud, Muhammad M. Khan and Jocelyn Chanussot: Improved Resolution For The Detection Of Snow With Modis Using Wavelet Fusion. IEEE International Geo Science and Remote Sensing Symposium (2007) 3975-3978.
http://dx.doi.org/10.1109/igarss.2007.4423719

Michael A. Rotondi: Estimating Transition Matrices to Predict Tomorrow’s Snowfall Using Real Data. Journal of Statistics Education (2010) 1-14.

Gail M. Sko Fronick Jackson, Benjamin T. Johnson, and S. Joseph Munchak: Detection Thresholds of Falling Snow From Satellite-Borne Active And Passive Sensors, IEEE Transactions On Geo Science and Remote Sensing (2013) 4177-4189.
http://dx.doi.org/10.1109/tgrs.2012.2227763

Gail M. Skofronick Jackson and Benjamin T. Johnson: Thresholds Of Detection For Falling Snow From Satellite-Borne Active And Passive Sensors, IEEE International Geo Science And Remote Sensing Symposium (2007) 2637-2640.
http://dx.doi.org/10.1109/igarss.2011.6049744

Andrea Spisni, Fausto Tomei, Sara Pignone, Enrico Muzzi, Alessandro Panzacchi, Gabriele Antolini: Snow Cover Analysis in Emilia-Romagna. European Journal of Remote Sensing (2011) 59-73.
http://dx.doi.org/10.5721/itjrs20114315

Alberto Martinez Vazquez and Joaquim Fortuny Guasch: Snow Avalanche Detection and Classification Algorithm for GB-SAR Imagery, IEEE International Geo Science and Remote Sensing Symposium (2007) 3740-3743.
http://dx.doi.org/10.1109/igarss.2007.4423656

Jeremie Bossu, Nicolas Hautière and Jean Philippe Tarel: Rain or Snow Detection in Image Sequences through Use of a Histogram of Orientation of Streaks, International Journal of Computer Vision (2011) 348-367.
http://dx.doi.org/10.1007/s11263-011-0421-7

Noel Dacruz Evora, Ddominique Tapsoba and Danielle De Seve: Combining Artificial Neural Network Models, Geo statistics, and Passive Microwave Data for Snow Water Equivalent Retrieval and Mapping. IEEE Transactions on Geo Science and Remote Sensing (2008) 1925-1939.
http://dx.doi.org/10.1109/tgrs.2008.916632

Hossein Zeinivand and Florimond De Smedt: Simulation of Snow Covers area by a Physical Based Model. World Academy of Science, Engineering and Technology (2009) 428-433.

Xiaolan Xu, Ding Liang, Leung Tsang, Konstantinos M. Andreadis, Edward G. Josberger, Dennis P. Lettenmaier, Donald W. Cline and Simon H. Yueh: Active Remote Sensing of Snow Using NMM3D/DMRT and Comparison With Clpx Ii Airborne Data, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2010) 689-697.
http://dx.doi.org/10.1109/jstars.2010.2053919

B. B. Fitzharris and B. P. Mcalevey: Remote Sensing of Seasonal Snow Cover in the Mountains of New Zealand Using Satellite Imagery. Taylor and Francis Geocarto International (1999) 35-44.
http://dx.doi.org/10.1080/10106049908542115

Ashok N. Srivastava and Julienne Stroeve: Onboard Detection of Snow, Ice, Clouds and Other Geophysical Processes Using Kernel Methods. Proceedings of the ICML Workshop on Machine Learning Technologies for Autonomous Space Applications (2003) 1-5.

G. Singh, Y. Yamaguchi, S. E. Park and G. Venkataraman: Identification of Snow Using SAR Polarimetry Techniques. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science (2010) 146-149.

Fan Ke and Tian Baoqiang: Prediction of Wintertime Heavy Snow Activity in North East China. Springer Chinese Science Bulletin (2013) 1420-1426.
http://dx.doi.org/10.1007/s11434-012-5502-7

Folorunsho Olaiya: Application of Data Mining Techniques in Weather Prediction and Climate Change Studies, International Journal of Information Engineering and Electronic Business (2012) 51-59.
http://dx.doi.org/10.5815/ijieeb.2012.01.07

Manjeet Singh, V. D. Mishra, N. K. Hakur and Jyoti Dhar Sharma: Remote Sensing GIS Based Statistical Modelling for the Prediction of Natural Hazards. International Journal of Engineering Research and Technology, (2012) 1-7.

J.R. Quinlan: Induction of Decision Trees. Journal of Machine Learning (1986) 81-106.
http://dx.doi.org/10.1007/bf00116251

B. Chandra and P. Paul Varghese: Fuzzy Sliq Decision Tree Algorithm: IEEE Transactions on Systems, Man and Cybernetics (2008) 1294-1301.
http://dx.doi.org/10.1109/tsmcb.2008.923529

Anuja Priyama, Abhijeeta, Rahul Guptaa, Anju Ratheeb and Saurabh Srivastavab: Comparative Analysis of Decision Tree Classification Algorithms, International Journal of Current Engineering and Technology (2013) 334-337.

Masud Karim and Rashedur M. Rahman: Decision Tree and Naive Bayes Algorithm for Classification and Generation of Actionable Knowledge for Direct Marketing. Journal of Software Engineering and Applications (2013) 196-206.
http://dx.doi.org/10.4236/jsea.2013.64025

Pedro Domingos and Michael J. Pazzani: Beyond Independence: Conditions for the Optimality of the Simple Bayesian Classifier. International Conference on Machine Learning (1996) 105-112.

Manish Mehta, Rakesh Agarwal and Jorma Rissanen: SLIQ: A Fast Scalable Classifier for Data Mining. International Conference on Extending Database Technology (1996) 18-32.
http://dx.doi.org/10.1007/bfb0014141

Rodrigo Coelho Barros, Marcio Porto Basgalupp, Andre C.P.L.F. De Carvalho and Alex A. Freitas: A Survey of Evolutionary Algorithms for Decision Tree Induction, IEEE Transactions on Systems, Man and Cybernetics (2012) 291-312.
http://dx.doi.org/10.1109/tsmcc.2011.2157494

J.R. Quinlan: C4.5: Programs for Machine Learning, Morgan Kaufmann Publishers, (1993).
http://dx.doi.org/10.1007/bf00993309

S. Safavian and D. Landgrebe: A Survey of Decision Tree Classifier Methodology, IEEE Transactions on Systems, Man And Cybernetics (1991) 660 -674.
http://dx.doi.org/10.1109/21.97458

Arun k pujari: Data Mining Techniques. Universities Press (2004).

http://www.wunderground.com/.

Powers and M. W. David: Evolution: From Precision, Recall and F-Measure to Roc, Informedness, Markedness and Correlation. Journal of Machine Learning Technologies (2011) 37-63.

Kishor Kumar Reddy C, Vijaya Babu B and Rupa C H: SLEAS: Supervised Learning Using Entropy as Attribute Selection Measure. International Journal of Engineering and Technology (2014) 2053-2060.

Kishor Kumar Reddy C, Rupa C H and Vijaya Babu B: A Pragmatic Methodology to Predict the Presence of Snow/No-Snow using Supervised Learning Methodologies. International Journal of Applied Engineering Research (2014) 11381-11393.

Kishor Kumar Reddy C, Rupa C H and Vijaya Babu: SPM: A Fast and Scalable Model for Predicting Snow/No-Snow. World Applied Sciences Journal (2014) 1561-1570.

Meenakshi, S., Venkatachalam, V., A modified decision tree algorithm for uncertain data classification, (2014) International Review on Computers and Software (IRECOS), 9 (1), pp. 188-196.


Refbacks

  • There are currently no refbacks.



Please send any question about this web site to info@praiseworthyprize.com
Copyright © 2005-2024 Praise Worthy Prize