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基于Sugeno模糊积分神经网络分类器融合方法在手写数字识别中的应用

Neural Network Multiple Classifier Fusion Method to Handwritten Numeral Recognition Based on Sugeno Fuzzy Integral
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摘要 神经网络是模式识别中一种常见的分类器。针对同一个分类问题,构建多个分类器并把多个分类器进行融合可以提高分类系统的分类正确率、改善系统的稳健性。首先介绍了Sugeno模糊积分及Sugeno模糊积分神经网络分类器融合方法的一般原理,而后将其应用于手写数字识别,通过实际的案例验证了该融合方法的有效性和可行性。 The Neural Network is a common kind of classifier of pattern recognition.The accuracy and robustness of classification system can be improved through fusion of multiple classifiers.This paper,firstly,introduces Sugeno fuzzy integral and the theory of the multiple classifiers fusion method which is based on Sugeno fuzzy integral.Then the method is used to solve the handwritten numeral recognition problems.
出处 《工业控制计算机》 2011年第3期45-46,共2页 Industrial Control Computer
关键词 关神经网络 Sugeno模糊积分 多分类器融合 手写数字 Neural Network Sugeno fuzzy integral multiple classifier fusion Handwritten numeral
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  • 1张海燕,胡光锐,张东红.多层前向神经网络的一种改进BP算法[J].通信技术,2003,36(11):6-7. 被引量:15
  • 2吕志南.模糊积分在综合评判方面的应用[J].山西农业大学学报,1994,14(2):201-203. 被引量:4
  • 3王英健,戎丽霞.基于遗传BP算法的神经网络及其在模式识别中的应用[J].长沙交通学院学报,2005,21(1):53-56. 被引量:12
  • 4许延伟,刘希玉.神经网络用于模式识别的几种主要方法及比较[J].信息技术与信息化,2005(4):120-123. 被引量:4
  • 5Baum E B, Lang K J. Constructing hidden units using examples and queries[C]//Neural Information Processing. Lippman R P, et al, ed. San Mateo, CA: Morgan Kaufmann, 2003: 904-910.
  • 6Chen Q C. Generating-shrinking algorithm for learning arbitrary classification[J]. Neural Networks, 2004, 5(7): 1477-1489.
  • 7Fahlman S E, Lebiere C. The cascade-correlation learning architecture[J]. Advances in Neural Information Processing Systems, 2000, 2: 524-532.
  • 8van Den B F, Engelbrecht A E A cooperative approach to particle swarm optimization evolutionary computation[J]. IEEE Transactions on Evolutionary Computation, 2004, 8(3): 225-239.
  • 9Gen M, Yun Y S. Soft computing approach for reliability optimization: State-of-the-art survey[J]. Reliability Engineering & System Safety, 2006, 91(9): 1008-1026.
  • 10HE Qie, WANG Ling. An effective co-evolutionary particle swarm optimization for constrained engineering design problems[J]. Engineering Applications of Artificial Intelligence, 2007, 20(1): 89-99.

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