Journal of Engineering and Applied Sciences

Year: 2017
Volume: 12
Issue: 10 SI
Page No. 8844 - 8850

An Optimal Stream Prediction Using Adaptive Regression Neural Network

Authors : Nabeel Al-A`araji, Eman Al-Shamery and Alyaa Abdul-Hussein

References

Agarkar, P., P. Hajare and N. Bawane, 2016. Optimization of generalized regression neural networks using PSO and GA for non-performer particles. Proceedinsg of the 2016 IEEE International Conference on Recent Trends in Electronics Information and Communication Technology (RTEICT’16), May 20-21, 2016, IEEE, Bangalore, India, ISBN:978-1-5090-0775-2, pp: 103-107.

Al-A’araji, N.H., E. Al-Shamery and A.H. Alyaa, 2016. A new polynomial curve fitting based on segmentation of variable point and variable modes for reconstructing missing values. Res. J. Appl. Sci., 11: 1089-1094.
Direct Link  |  

Alzghoul, A., M. Lofstrand and B. Backe, 2012. Data stream forecasting for system fault prediction. Comput. Ind. Eng., 62: 972-978.
Direct Link  |  

Chen, A.S. and M.T. Leung, 2004. Regression neural network for error correction in foreign exchange forecasting and trading. Comput. Oper. Res., 31: 1049-1068.
CrossRef  |  Direct Link  |  

Chen, K., Y.S. Koh and P. Riddle, 2016. Proactive drift detection: Predicting concept drifts in data streams using probabilistic networks. Proceedings of the 2016 International Joint Conference on Neural Networks (IJCNN’16), July 24-29, 2016, IEEE, Vancouver, British Columbia, Canada, ISBN:978-1-5090-0621-2, pp: 780-787.

Dias, G.M., B. Bellalta and S. Oechsner, 2016. A survey about prediction-based data reduction in wireless sensor networks. ACM. Comput. Surv., Vol. 49, 10.1145/2996356

Diez, D., C. Barr and M. Cetinkaya-Rundel, 2015. OpenIntro Statistics. 3rd Edn., OpenIntro Inc., Rumford, Maine, ISBN:9781943450053, Pages: 436.

Draper, N.R. and H. Smith, 1998. Applied Regression Analysis. Vol. 1, John Wiley & Sons, Hoboken, New Jersey, ISBN:9780471170822, Pages: 706.

Johnson, R.A. and D.W. Wichern, 2007. Applied Multivariate Statistical Analysis. 6th Edn., Prentice Hall, Upper Saddle River, New Jersey, ISBN:9780131877153, Pages: 773.

Kong, Y., Y. Shi and J. Yuan, 2008. Prediction method of time series data stream based on wavelet transform and least squares support vector machine. Proceedings of the 4th International Conference on Natural Computation (ICNC'08) Vol. 2, October 18-20, 2008, IEEE, Jinan, China, ISBN:978-0-7695-3304-9, pp: 120-124.

Lian, X. and L. Chen, 2006. Efficient methods on predictions for similarity search over stream time series. Proceedings of the 18th International Conference on Scientific and Statistical Database Management, July 3-5, 2006, IEEE, Vienna, Austria, ISBN:0-7695-2590-3, pp: 241-250.

Meng, F. and P. Zhuang, 2009. Stream prediction model based on tendency correction. Proceedings of the 6th Conference on Web Information Systems and Applications (WISA’09), September 18-20, 2009, IEEE, Xuzhou, China, ISBN:978-0-7695-3874-7, pp: 189-193.

Tian, L. and P. Zou, 2006. Prediction models over distributed data streams. Proceedings of the International Conference On Web Information Systems Engineering (WISE’06), October 23-26, 2006, Springer, Wuhan, China, pp: 25-36.

Villa, A.E.P., P. Masulli and A.J.P. Rivero, 2016. Artificial Neural Networks and Machine Learning-ICANN 2016: 25th International Conference on Artificial Neural Networks, Barcelona, Spain, September 6-9, 2016, Proceedings. Springer, Berlin, Germany, ISBN:978-3-319-44780-3, Pages: 557.

Yi, W., I.V. Gerasimov, S.A. Kuzmin and H. He, 2016. An intelligent algorithm of Support Vector Regression parameters Optimization in soft measurements. Proceedings of the 19th IEEE International Conference on Soft Computing and Measurements (SCM’16), May 25-27, 2016, IEEE, St. Petersburg, Russia, ISBN:978-1-4673-8920-4, pp: 404-406.

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