Abstract:

Cost estimation is the core content of complex equipment cost management. In the case that only a small amount of sample information is available for the same type of complex equipment, in order to improve the estimation and prediction accuracy, and to solve the problems of difficult screening of cost-influencing elements under poor information, unreasonable weight distribution among elements due to synergistic effects, and large cost prediction errors, a method for allocating element weights based on the contribution of grey relational synergistic effects is proposed. Firstly, similar samples and key cost influencing elements are screened by grey relational analysis. Secondly, based on the contribution of each element to the improvement of grey relational grade under the synergistic effect, the grey comparative relational importance of each element with reference to the idea of Shapley value is calculated, and thus the weights are determined. Finally, the corresponding heterogeneous order parameter grey fractional order prediction model is constructed for cost prediction of target equipment. By comparing with the existing methods in the literatures, the comparison results show that the proposed method has a high prediction accuracy and certain applicability, indicating that the proposed method can explore the potential information among the cost-influencing elements in a small amount of sample, assign the element weights more reasonably and improve the accuracy of cost prediction.

Key words: complex equipment costs, synergistic effect, Shapley value, grey relational analysis, grey fractional order GM (0, N) model