Based On The Characteristics Of Sound Credit-shaped Deep Cobalt Crusts Recognition

Along with the fast development of economy and science in the world, the need of mineral resources is growing day by day. However, the land resources are becoming less and less. In this situation, people tend to mine the resources in the ocean. Oceanic cobalt crust resource has been a commercial foreground strategically resource in 21 century and the head developed countries in the world have been doing the work of investigati-on and exploitation. In order to mine the new resources by our country independently, the investigation is done of the identification and classifiction of the cobalt-crust in the dissertation, imbursed by the national natural science fund item "study on the Abyssalbenthic Cobalt-rich Crusts Tiny terrain Detecting Technology and the Best collection deepness model".A classifiction method of deep-sea cobalt-crust was proposed based on the application of fractal theory in feature extraction. The questions of feature extraction, feature optimization and classifier design were sutdy. As provide more information than individual dimension, the generalized dimensions of echo signals were used for cobalt-crust classifiction based on the assumption that the sonar echo signals have a fractal structure. To deal with the problem of original features with the characteristic of large dimension and nonlinear relationship among them, Kernel Fisher discriminant analysis is adopted to extract the optimal nonlinear discriminant features. At the end, the Probability Neural Network was used as the classifier. Based on the theory mentioned above, the classification experiments of 23 kinds of seabed materials were done. The experimental results indicated that the exactness identification rate of cobalt-crust was about 79.6 percents and the error rate of mistaking the non-cobalt-crust as cobalt-crust was only 23 percents. Look from the results, this method was effective and reliable.The research of the dissertation affords favorable theoretic value for the identification and classification of the abyssalbenthic cobalt-crust. The important is that the research furnishes effective technique sustain for the country abyssal mining.