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Information 2015, 6(3), 388-398; doi:10.3390/info6030388

A Neural Network-Based Interval Pattern Matcher

1
School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing 210044, China
2
Shanxi Meteorological Administration, Taiyuan 030006, China
3
National Meteorological Center of China Meteorological Administration, Beijing 100081, China
4
Environmental Modeling Center, NOAA/NWS/National Centers for Environmental Prediction, College Park, MD 20740, USA
5
School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
6
Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Willy Susilo
Received: 7 May 2015 / Revised: 13 July 2015 / Accepted: 14 July 2015 / Published: 17 July 2015
View Full-Text   |   Download PDF [835 KB, uploaded 17 July 2015]   |  

Abstract

One of the most important roles in the machine learning area is to classify, and neural networks are very important classifiers. However, traditional neural networks cannot identify intervals, let alone classify them. To improve their identification ability, we propose a neural network-based interval matcher in our paper. After summarizing the theoretical construction of the model, we take a simple and a practical weather forecasting experiment, which show that the recognizer accuracy reaches 100% and that is promising. View Full-Text
Keywords: neural network; interval; pattern matcher; weather forecasting neural network; interval; pattern matcher; weather forecasting
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Lu, J.; Xue, S.; Zhang, X.; Han, Y. A Neural Network-Based Interval Pattern Matcher. Information 2015, 6, 388-398.

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