Intelligent Evaluation Method of Engineering Cost Feasibility Model Based on Internet of Things

Abstract

In order to solve the problem of low accuracy of high-rise building cost evaluation, the author proposes an intelligent evaluation method of engineering cost feasibility model based on the Internet of Things. According to the overall investment composition of the construction project, this paper classifies the cost index, determines the overall cost correction coefficient, and uses the gray correlation analysis method to build the evaluation index system; according to the structure of BP neural network, the network error is calculated, and the error signals of output layer and hidden layer are defined by gradient descent method to obtain the network weight adjustment formula; finally, this paper uses the adaptive learning rate adjustment formula to set the network parameters, introduces the key parameters in the construction project to the input layer, and establishes the final cost evaluation model. Experimental results show that the error rate of this system is controlled within 10%, which meets the requirements of investment estimation. Conclusion. The proposed method can accurately and quickly evaluate the best solution for the cost of high-rise buildings with less information and has strong nonlinear information processing capabilities.