caa a22 4500 605469792 CHVBK 20210128100324.0 cr unu---uuuuu 210128e20151001xx s 000 0 eng 10.1007/s00500-014-1445-z doi (NATIONALLICENCE)springer-10.1007/s00500-014-1445-z Novel method of flatness pattern recognition via cloud neural network [Elektronische Daten] [Xiu-ling Zhang, Liang Zhao, Wen-bao Zhao, Teng Xu] Aiming at the weakness of the existing cloud neural network on training and practicality, a new improved structure of cloud neural network is designed. A hidden layer is added prior to the inverse cloud layer. Threshold level is set to zero and a simple training method is designed. In addition, considering the ignorance of signal randomness and fuzziness in the existing method of the flatness signal recognition, the cloud neural network combines the advantages of the fuzziness and randomness of cloud model and the learning and memory ability of neural network. Thus it is applied in the flatness signal recognition. The simulation contrast results demonstrate that the improved structure is able to identify common defects in shape with higher identity precision. Springer-Verlag Berlin Heidelberg, 2014 Neural network nationallicence Cloud model nationallicence Flatness pattern recognition nationallicence Fuzziness nationallicence Randomness nationallicence Zhang Xiu-ling Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, 066004, Qinhuangdao, China aut Zhao Liang Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, 066004, Qinhuangdao, China aut Zhao Wen-bao Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, 066004, Qinhuangdao, China aut Xu Teng Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, 066004, Qinhuangdao, China aut Soft Computing Springer Berlin Heidelberg 19/10(2015-10-01), 2837-2843 1432-7643 19:10<2837 2015 19 500 https://doi.org/10.1007/s00500-014-1445-z text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1445-z text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Zhang Xiu-ling Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, 066004, Qinhuangdao, China aut NATIONALLICENCE 700 1- Zhao Liang Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, 066004, Qinhuangdao, China aut NATIONALLICENCE 700 1- Zhao Wen-bao Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, 066004, Qinhuangdao, China aut NATIONALLICENCE 700 1- Xu Teng Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, 066004, Qinhuangdao, China aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/10(2015-10-01), 2837-2843 1432-7643 19:10<2837 2015 19 500