Author(s)

Jue Wang ¹

Affiliation(s)

¹ School of Construction Engineering, Chengdu Vocational & Technical College of Industry, Chengdu, Sichuan, 610000, China

Corresponding Author

Jue Wang

ABSTRACT

With the continuous development of computer science, intelligent optimization techniques have penetrated into various research fields. It can help solve the shortcomings of large error and long preparation time in the estimation of construction project cost. This study focuses on the application of artificial intelligence methods in the field of construction cost estimation. By utilizing the data fitting ability of neural networks, an artificial intelligence estimation model is established to predict construction cost estimates. The theoretical basis and basic principles of the BP neural network are elucidated, and the MATLAB software is used to validate its excellent function approximation capability. A construction cost estimation model based on PSO-optimized BP neural network is developed, and through MATLAB programming for sample training and testing, the results demonstrate that both models have errors within acceptable ranges. The establishment of the construction cost estimation model enables the prediction of engineering costs, proving the practical value of the model.

KEYWORDS

Artificial Intelligence; BP Neural Network; PSO Optimization

CITE THIS PAPER

Jue Wang, Research on Construction Project Valuation Based on Artificial Intelligence Technology. Journal of Civil Engineering and Urban Planning (2024) Vol. 6: 16-23. DOI: http://dx.doi.org/10.23977/jceup.2024.060203.

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