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Research on stock company comprehensive assessment has always been an important focus for economists and computer experts. In this paper, the financial indexes reflecting the comprehensive capability of stock companies as main research objects including income per thigh, clean asset per thigh, profit rate of clean asset, Kohonen network with the advantage of clustering is applied to assess for stock companies. In order to improve the precision of solutions, a tabu-mapping method is also used to avoid the same output node to be mapped by more than one input in this paper. Experimental results show that Kohonen network is feasible and effective to assess stock companies, it could provide a new reference basis for government and investors, which has potential applications in the financial field.

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