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

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.