9 Predict Future Climate Change Using Artificial Neural Networks
63
Table 9.1 Performance result Training
90.172%
Validation
84.859%
Test
81.697%
All
87.945%
References
Abellatif M, Vatner SF, Vatner DE, Sadoshima J (2015) U.S. Patent No. 9,051,568. Washington,
DC, U.S. Patent and Trademark Office
Baboo DSS, Shereef IK (2011) An efficient temperature prediction system using BPN neural
network. Int J Environ Sci Develop 2(1):2010–2264
Cawley GC, Talbot NL, Girolami M (2007) Sparse multinomial logistic regression via bayesian l1
regularisation. In: Advances in neural information processing systems, pp 209–216
Chauhan S, Shrivastava RK (2009) Performance evaluation of reference evapotranspiration estimation using climate based methods and artificial neural networks. Water Resour Manage
23(5):825
Choudhary PR, Thakur H, Murade A, Venkatesan M (2016) Climate change prediction using
artificial neural network. Int J Appl Eng Res 11(3):1954–1959
Das D, Bakshi S, Bhattacharya P (2014) Dyeing of sericin-modified cotton with reactive dyes. J
Textile Inst 105(3):314–320
Ferrari S, Ruggieri P, Cefalo G, Tamburini A, Capanna R, Fagioli F, Alberghini M (2012) Neoadjuvant chemotherapy with methotrexate, cisplatin, and doxorubicin with or without ifosfamide
in nonmetastatic osteosarcoma of the extremity: an Italian sarcoma group trial ISG/OS-1. J Clin
Oncol 30(17):2112–2118
Ghorbani MA, Khatibi R, Hosseini B, Bilgili M (2013) Relative importance of parameters affecting
wind speed prediction using artificial neural networks. Theoret Appl Climatol 114(1–2):107–114
Joseph J, Ratheesh TK (2013) Rainfall prediction using data mining techniques. Int J Comput Appl
83(8)
Karpatne A, Khandelwal A, Boriah S, Kumar V (2014) Predictive learning in the presence of heterogeneity and limited training data. In: Proceedings of the 2014 SIAM international conference on
data mining, Society for industrial and applied mathematics, pp 253–261
Mehra P, Wah BW (1992) Adaptive load-balancing strategies for distributed systems. In:
Proceedings of the second international conference on systems integration, IEEE, pp 666–675
Nikam VB, Meshram BB (2013) Modeling rainfall prediction using data mining method: a Bayesian
approach. In: 2013 Fifth international conference on computational intelligence, modelling and
simulation, IEEE, pp 132–136
Raje D, Mujumdar PP (2010) Reservoir performance under uncertainty in hydrologic impacts of
climate change. Adv Water Resour 33(3):312–326
Sencan H, Chen Z, Hendrix W, Pansombut T, Semazzi F, Choudhary A, Samatova NF (2011)
Classification of emerging extreme event tracks in multivariate Spatio-temporal physical systems
using dynamic network structures: application to hurricane track prediction. In: Twenty-second
international joint conference on artificial intelligence
63
Table 9.1 Performance result Training
90.172%
Validation
84.859%
Test
81.697%
All
87.945%
References
Abellatif M, Vatner SF, Vatner DE, Sadoshima J (2015) U.S. Patent No. 9,051,568. Washington,
DC, U.S. Patent and Trademark Office
Baboo DSS, Shereef IK (2011) An efficient temperature prediction system using BPN neural
network. Int J Environ Sci Develop 2(1):2010–2264
Cawley GC, Talbot NL, Girolami M (2007) Sparse multinomial logistic regression via bayesian l1
regularisation. In: Advances in neural information processing systems, pp 209–216
Chauhan S, Shrivastava RK (2009) Performance evaluation of reference evapotranspiration estimation using climate based methods and artificial neural networks. Water Resour Manage
23(5):825
Choudhary PR, Thakur H, Murade A, Venkatesan M (2016) Climate change prediction using
artificial neural network. Int J Appl Eng Res 11(3):1954–1959
Das D, Bakshi S, Bhattacharya P (2014) Dyeing of sericin-modified cotton with reactive dyes. J
Textile Inst 105(3):314–320
Ferrari S, Ruggieri P, Cefalo G, Tamburini A, Capanna R, Fagioli F, Alberghini M (2012) Neoadjuvant chemotherapy with methotrexate, cisplatin, and doxorubicin with or without ifosfamide
in nonmetastatic osteosarcoma of the extremity: an Italian sarcoma group trial ISG/OS-1. J Clin
Oncol 30(17):2112–2118
Ghorbani MA, Khatibi R, Hosseini B, Bilgili M (2013) Relative importance of parameters affecting
wind speed prediction using artificial neural networks. Theoret Appl Climatol 114(1–2):107–114
Joseph J, Ratheesh TK (2013) Rainfall prediction using data mining techniques. Int J Comput Appl
83(8)
Karpatne A, Khandelwal A, Boriah S, Kumar V (2014) Predictive learning in the presence of heterogeneity and limited training data. In: Proceedings of the 2014 SIAM international conference on
data mining, Society for industrial and applied mathematics, pp 253–261
Mehra P, Wah BW (1992) Adaptive load-balancing strategies for distributed systems. In:
Proceedings of the second international conference on systems integration, IEEE, pp 666–675
Nikam VB, Meshram BB (2013) Modeling rainfall prediction using data mining method: a Bayesian
approach. In: 2013 Fifth international conference on computational intelligence, modelling and
simulation, IEEE, pp 132–136
Raje D, Mujumdar PP (2010) Reservoir performance under uncertainty in hydrologic impacts of
climate change. Adv Water Resour 33(3):312–326
Sencan H, Chen Z, Hendrix W, Pansombut T, Semazzi F, Choudhary A, Samatova NF (2011)
Classification of emerging extreme event tracks in multivariate Spatio-temporal physical systems
using dynamic network structures: application to hurricane track prediction. In: Twenty-second
international joint conference on artificial intelligence