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Measuring the Board Governance Capability in China by Means of Neural Networks and Genetic Algorithms

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1 Author(s)
Jian Deng ; Changchun Taxation Coll., Changchun, China

This paper took a research on the Board of governance capacity measurement using the neural networks and genetic algorithms method. After constructing a measurement indicator system about Board of governance capacity, the paper took a empirical rearch on Chinese companypsilas board governance capacity using the listed companies as the data sample. The results show that NNGA model improved the networks' performance comparing with traditional NN model. This paper took a research on the Board of governance capacity measurement using the neural networks and genetic algorithms method. After constructing a measurement indicator system about Board of governance capacity, the paper took a empirical rearch on Chinese companypsilas board governance capacity using the listed companies as the data sample. The results show that NNGA model improved the networks' performance comparing with traditional NN model. The stochastic nature of NNGA networks' structures develop more heterogeneous structures than NN model which were chosen through a fixed procedure.

Published in:

Intelligent Systems, 2009. GCIS '09. WRI Global Congress on  (Volume:4 )

Date of Conference:

19-21 May 2009