Calculation of golf course environmental cost based on BP neural network

Abstract

Golf is an elegant outdoor sport, but it is not popular with the Chinese people, largely because the construction of golf courses will cause a series of environmental problems. In this paper, the Cost-significant(CS) is introduced to calculate the environmental cost of golf course construction. According to the data of 14 golf course constructions consulted and sorted, the Cost-significant Items(CSIs) in golf course construction project is identified, and innovatively integrate data into the index of the project. Using the strong nonlinear mapping ability of Back-Propagation Neural Network(BPNN) Algorithm, a general environmental cost estimation model for golf course construction is trained. The comparison between the model fitting results and the original data shows that the model not only has high fitting accuracy, but also avoids involving complex data operation and complicated processing steps, which greatly simplifies the calculation process.