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Movement scope of strata based on fuzzy BP neural network in underground metal mines 被引量:1
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作者 YanhuiWang SijingCai WeidongSong 《Journal of University of Science and Technology Beijing》 CSCD 2005年第1期6-11,共6页
A prediction method of strata movement in underground metal mines is put forward, in which fuzzy BP neural network is applied. The results show that there is a strong nonlinear relation between the selected factors an... A prediction method of strata movement in underground metal mines is put forward, in which fuzzy BP neural network is applied. The results show that there is a strong nonlinear relation between the selected factors and strata movement angle, the anticipant and the actual output results are very similar. It is proved that the numerical value of movement angle is correlated with the selected factors in theory. The scope of strata and surface movement due to mining can be predicted. This research provides a thought to study the movement scope of strata due to mining. 展开更多
关键词 fuzzy bp neural network strata movement underground metal mine
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Research on Recognition Method of Handwritten Numerals Segmentation based on B-P Neural Network
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作者 Ningfang Wei 《International Journal of Technology Management》 2013年第7期64-66,共3页
We propose a binarization method based pigment in the ZIP code of 24 bmp image simulation and digital identification by CCD sensors, were extracted the grid binary image of zip code box and message of the two characte... We propose a binarization method based pigment in the ZIP code of 24 bmp image simulation and digital identification by CCD sensors, were extracted the grid binary image of zip code box and message of the two characters binary image; analyze the image processing, which includes code frame edge detection and separation of the image binarization, denoising smoothing, tilt correction, the extraction code number, position, normalization processing, digital image thinning, character recognition feature extraction. Through testing, the recognition rate of this method can be over 90%. The recognition time of characters for character is less than 1.3 second, which means the method is of more effective recognition ability and can better satisfy the real system requirements. 展开更多
关键词 fuzzy recognition: bp neural network zip code
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