Neuron Learning Mechanism on China Construction Enterprises Knowledge Gap Compensation

The compensation for construction enterprise knowledge gap is an important guarantee for the enterprise to make rapid and stable development. This paper defines the connotation of knowledge gap in construction enterprises from the knowledge supplies and demands point of view, and analyzes the causes of construction enterprise knowledge gaps and their remedy forces in China. Based on this, the paper, with the integration of learning theories and neurons thoughts, puts forward three learning mechanisms on self-evolutionary knowledge gap neuron, benchmarking knowledge gap neuron, and mixed knowledge neuron in construction enterprises to establish a predictive learning system for the enterprises´ knowledge gaps based on discrete time dynamic process, thus fully describing a diachronic process of knowledge gaps in the construction enterprises from self-evolutionary learning, benchmarking learning, a combination of self-evolutionary and benchmarking learning to self-prediction learning to help the enterprises to set up a learning mechanism corresponding and effectively predict its transferring state on the basis of identifying the knowledge gaps in the construction enterprises.