A Neural Network-Based Interval Pattern Matcher
School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing 210044, China
Shanxi Meteorological Administration, Taiyuan 030006, China
National Meteorological Center of China Meteorological Administration, Beijing 100081, China
Environmental Modeling Center, NOAA/NWS/National Centers for Environmental Prediction, College Park, MD 20740, USA
School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
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
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.
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MDPI and ACS Style
Lu, J.; Xue, S.; Zhang, X.; Han, Y. A Neural Network-Based Interval Pattern Matcher. Information 2015, 6, 388-398.
Lu J, Xue S, Zhang X, Han Y. A Neural Network-Based Interval Pattern Matcher. Information. 2015; 6(3):388-398.
Lu, Jing; Xue, Shengjun; Zhang, Xiakun; Han, Yang. 2015. "A Neural Network-Based Interval Pattern Matcher." Information 6, no. 3: 388-398.
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