How to cite this paper
Sudha, M. (2017). Intelligent decision support system based on rough set and fuzzy logic approach for efficacious precipitation forecast.Decision Science Letters , 6(1), 95-106.
Refrences
Alcala-Fdez, J., Alcala, R., & Herrera, F. (2011). A fuzzy association rule-based classification model for high-dimensional problems with genetic rule selection and lateral tuning. Fuzzy Systems, IEEE Transactions on, 19(5), 857-872.
Bardossy, A., Duckstein, L., & Bogardi, I. (1995). Fuzzy rule‐based classification of atmospheric circulation patterns. International Journal of Climatology, 15(10), 1087-1097.
Dai, J., & Xu, Q. (2013). Attribute selection based on information gain ratio in fuzzy rough set theory with application to tumor classification. Applied Soft Computing, 13(1), 211-221.
González, A., & Pérez, R. (2001). Selection of relevant features in a fuzzy genetic learning algorithm. Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, 31(3), 417-425.
Greco, S., Matarazzo, B., & Slowinski, R. (2001). Rough sets theory for multicriteria decision analysis. European journal of operational research, 129(1), 1-47.
AliKhashashneh, E., & Al-Radaideh, Q. (2013, March). Evaluation of discernibility matrix based reduct computation techniques. In Computer Science and Information Technology (CSIT), 2013 5th International Conference on (pp. 76-81). IEEE.
Kusiak, A., Zhang, Z., & Verma, A. (2013). Prediction, operations, and condition monitoring in wind energy. Energy, 60, 1-12.
Lee, J., Kim, J., Lee, J. H., Cho, I. H., Lee, J. W., Park, K. H., & Park, J. (2012, November). Feature selection for heavy rain prediction using genetic algorithms. In Soft Computing and Intelligent Systems (SCIS) and 13th International Symposium on Advanced Intelligent Systems (ISIS), 2012 Joint 6th International Conference on (pp. 830-833). IEEE.
Liu, J. N., Li, B. N., & Dillon, T. S. (2001). An improved naive Bayesian classifier technique coupled with a novel input solution method [rainfall prediction]. Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, 31(2), 249-256.
Li, K., & Liu, Y. S. (2005, August). A rough set based fuzzy neural network algorithm for weather prediction. In Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on (Vol. 3, pp. 1888-1892). IEEE.
Al-Matarneh, L., Sheta, A., Bani-Ahmad, S., Alshaer, J., & Al-oqily, I. (2014). Development of Temperature-based Weather Forecasting Models Using Neural Networks and Fuzzy Logic. International Journal of Multimedia and Ubiquitous Engineering, 9(12), 343-366.
Olaiya, F., & Adeyemo, A. B. (2012). Application of data mining techniques in weather prediction and climate change studies. International Journal of Information Engineering and Electronic Business (IJIEEB), 4(1), 51.
Pant, L. M., & Ganju, A. (2004). Fuzzy rule-based system for prediction of direct action avalanches. Current science, 87(1), 99-104.
Pawlak, Z., & Skowron, A. (2007). Rough sets: Some extensions, Information Sciences, 177, 28-40.
Pawlak, Z. (2002). Rough Sets and its Applications, Journal of Telecommunications and Information Technology, 3, 7-10.
Pawlak, Z., Grzymala-Busse, J., Slowinski, R., & Ziarko, W. (1995). Rough sets. Communications of the ACM, 38(11), 88-95.
Pawlak, Z. & Slowinski, R. (1994). Rough set approach to multi-attribute decision analysis. European Journal of Operational Research,72 (3),443-459.
Pawlak, Z. & Slowinski, R. (1995). Decision Analysis using Rough Sets, International Transactions on Operational Research, 1,107-114.
Pawlak, Z. (1982). Rough sets. International Journal of Computer & Information Sciences, 11(5), 341-356.
Qablan, T., Al-Radaidehl, Q. A., & Abu Shuqeir, S. (2012). A reduct computation approach based on ant colony optimization. Basic Science Engineering, 21(1), 29-40.
Seo, J. H., & Kim, Y. H. (2012). Genetic feature selection for very short-term heavy rainfall prediction. In Convergence and Hybrid Information Technology (pp. 312-322). Springer Berlin Heidelberg.
Shen, Q., & Jensen, R. (2007). Rough sets, their extensions and applications. International Journal of Automation and Computing, 4(3), 217-228.
Sudha, M., & Valarmathi, B. (2014). Rainfall Forecast Analysis using Rough Set Attribute Reduction and Data Mining Methods. AGRIS on-line Papers in Economics and Informatics, 6(4), 131-140.
Sudha, M., & Valarmathi, B. (2013). Exploration on Rough Set Approach for Feature Selection Based Reduction. International Journal of Applied Engineering Research, 8(13), 1555-1568.
Sharma, A., & Manoria, M. (2006, December). A Weather Forecasting System using concept of Soft Computing: A new approach. In Advanced Computing and Communications, 2006. ADCOM 2006. International Conference on (pp. 353-356). IEEE.
Talei, A., Chua, L. H. C., & Quek, C. (2010). A novel application of a neuro-fuzzy computational technique in event-based rainfall–runoff modeling. Expert Systems with Applications, 37(12), 7456-7468.
Witten, I. H., & Frank, E. (2005). Data Mining: Practical machine learning tools and techniques. Morgan Kaufmann.
Wong, K.W., Wong, P.M., Gedeon T.D., & Fung, C.C.(2003). Rainfall prediction model using soft computing technique. Soft Computing - A Fusion of Foundations, Methodologies and Applications, 7(6), 1433-7479.
Yao, Y., & Zhao, Y. (2009). Discernibility matrix simplification for constructing attribute reducts. Information sciences, 179(7), 867-882.
Zadeh, L.A (1965). Fuzzy Set. Information and Control, 8,338-353.
Bardossy, A., Duckstein, L., & Bogardi, I. (1995). Fuzzy rule‐based classification of atmospheric circulation patterns. International Journal of Climatology, 15(10), 1087-1097.
Dai, J., & Xu, Q. (2013). Attribute selection based on information gain ratio in fuzzy rough set theory with application to tumor classification. Applied Soft Computing, 13(1), 211-221.
González, A., & Pérez, R. (2001). Selection of relevant features in a fuzzy genetic learning algorithm. Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, 31(3), 417-425.
Greco, S., Matarazzo, B., & Slowinski, R. (2001). Rough sets theory for multicriteria decision analysis. European journal of operational research, 129(1), 1-47.
AliKhashashneh, E., & Al-Radaideh, Q. (2013, March). Evaluation of discernibility matrix based reduct computation techniques. In Computer Science and Information Technology (CSIT), 2013 5th International Conference on (pp. 76-81). IEEE.
Kusiak, A., Zhang, Z., & Verma, A. (2013). Prediction, operations, and condition monitoring in wind energy. Energy, 60, 1-12.
Lee, J., Kim, J., Lee, J. H., Cho, I. H., Lee, J. W., Park, K. H., & Park, J. (2012, November). Feature selection for heavy rain prediction using genetic algorithms. In Soft Computing and Intelligent Systems (SCIS) and 13th International Symposium on Advanced Intelligent Systems (ISIS), 2012 Joint 6th International Conference on (pp. 830-833). IEEE.
Liu, J. N., Li, B. N., & Dillon, T. S. (2001). An improved naive Bayesian classifier technique coupled with a novel input solution method [rainfall prediction]. Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, 31(2), 249-256.
Li, K., & Liu, Y. S. (2005, August). A rough set based fuzzy neural network algorithm for weather prediction. In Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on (Vol. 3, pp. 1888-1892). IEEE.
Al-Matarneh, L., Sheta, A., Bani-Ahmad, S., Alshaer, J., & Al-oqily, I. (2014). Development of Temperature-based Weather Forecasting Models Using Neural Networks and Fuzzy Logic. International Journal of Multimedia and Ubiquitous Engineering, 9(12), 343-366.
Olaiya, F., & Adeyemo, A. B. (2012). Application of data mining techniques in weather prediction and climate change studies. International Journal of Information Engineering and Electronic Business (IJIEEB), 4(1), 51.
Pant, L. M., & Ganju, A. (2004). Fuzzy rule-based system for prediction of direct action avalanches. Current science, 87(1), 99-104.
Pawlak, Z., & Skowron, A. (2007). Rough sets: Some extensions, Information Sciences, 177, 28-40.
Pawlak, Z. (2002). Rough Sets and its Applications, Journal of Telecommunications and Information Technology, 3, 7-10.
Pawlak, Z., Grzymala-Busse, J., Slowinski, R., & Ziarko, W. (1995). Rough sets. Communications of the ACM, 38(11), 88-95.
Pawlak, Z. & Slowinski, R. (1994). Rough set approach to multi-attribute decision analysis. European Journal of Operational Research,72 (3),443-459.
Pawlak, Z. & Slowinski, R. (1995). Decision Analysis using Rough Sets, International Transactions on Operational Research, 1,107-114.
Pawlak, Z. (1982). Rough sets. International Journal of Computer & Information Sciences, 11(5), 341-356.
Qablan, T., Al-Radaidehl, Q. A., & Abu Shuqeir, S. (2012). A reduct computation approach based on ant colony optimization. Basic Science Engineering, 21(1), 29-40.
Seo, J. H., & Kim, Y. H. (2012). Genetic feature selection for very short-term heavy rainfall prediction. In Convergence and Hybrid Information Technology (pp. 312-322). Springer Berlin Heidelberg.
Shen, Q., & Jensen, R. (2007). Rough sets, their extensions and applications. International Journal of Automation and Computing, 4(3), 217-228.
Sudha, M., & Valarmathi, B. (2014). Rainfall Forecast Analysis using Rough Set Attribute Reduction and Data Mining Methods. AGRIS on-line Papers in Economics and Informatics, 6(4), 131-140.
Sudha, M., & Valarmathi, B. (2013). Exploration on Rough Set Approach for Feature Selection Based Reduction. International Journal of Applied Engineering Research, 8(13), 1555-1568.
Sharma, A., & Manoria, M. (2006, December). A Weather Forecasting System using concept of Soft Computing: A new approach. In Advanced Computing and Communications, 2006. ADCOM 2006. International Conference on (pp. 353-356). IEEE.
Talei, A., Chua, L. H. C., & Quek, C. (2010). A novel application of a neuro-fuzzy computational technique in event-based rainfall–runoff modeling. Expert Systems with Applications, 37(12), 7456-7468.
Witten, I. H., & Frank, E. (2005). Data Mining: Practical machine learning tools and techniques. Morgan Kaufmann.
Wong, K.W., Wong, P.M., Gedeon T.D., & Fung, C.C.(2003). Rainfall prediction model using soft computing technique. Soft Computing - A Fusion of Foundations, Methodologies and Applications, 7(6), 1433-7479.
Yao, Y., & Zhao, Y. (2009). Discernibility matrix simplification for constructing attribute reducts. Information sciences, 179(7), 867-882.
Zadeh, L.A (1965). Fuzzy Set. Information and Control, 8,338-353.