The Applications of Neural Networks in the Engineering Cost of Transmission Line

Abstract:

With the rapid development of the electric power industry in recent years, the strengthening of the power construction market and the diversification of the main body of power investment, there appears a prominent question in front of the project owners——How to control and reduce construction costs There are many methods to estimate the cost quickly and accurately. Among the common methods and some new ways which have appeared in recent years, people can find about seven types out of them, in which, neural network model is known for its versatility and adaptability. It does not exclude new sample. On the contrary, it improves its ability to generalize and forecast with the increasing number of samples. Therefore this paper establish a cost estimation model by introducing neural network which is based on the optimization of genetic algorithm, and expresses the relationship implied in the interior of data by using the network topology and parameters by studying a large number of samples so as to fit the conventional non-linear mapping relationship between the amount and cost of a transmission line project. The results show that the artificial neural network model has a significant effect on the project cost estimation. The introduction of neural network model will certainly promote the development of informatization of power project costs management.

• Periodical: Applied Mechanics and Materials (Volume 319)
• Pages: 485-490
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.319.485
• Online since: May 2013
• Authors: Hong Fei Sun, Qing Song Tang, Yu Ling Li
• Keywords: Neural Network (NN), Power Engineering Cost, Sample Training, Transmission Line

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