Neural Network Algorithm Optimization for Financial Budget of Universities

Abstract

Efficient budget management is crucial for the successful execution of construction projects. To achieve this, the design of a Construction Project Audit Budget Management System based on combinatorial optimization offers significant advantages. Combinatorial optimization techniques focus on finding optimal solutions from a vast number of possible combinations, making them well-suited for complex budget management scenarios. This system employs advanced algorithms to analyze and optimize various factors such as resource allocation, cost estimation, risk assessment, and scheduling. This paper focused on the construction of the Project Fuzzy Audit System in China.  The developed model computes total investment decision, preliminary design, design, contracting, construction, completion acceptance and other stages of the investment/cost, namely investment estimation, budget estimate, control price, contract price and settlement price. According to the project total investment/cost control needs in China Project. The constructed model uses the combinatorial Optimization model for the estimation of the investment estimation of the Construction Project for the cost index. Through the Fuzzy Audit System new method abolishes the "maximum price" in the bidding document with the limit as the unit, and gradually terminates the preparation of the budget quota, highlighting the market price, so there is an urgent need for a set of cost index in line with the actual needs. The results demonstrated that with the fuzzy Audit system new method abolishes the "maximum price" in the bidding document with the limit as the unit, and gradually terminates the preparation of the budget quota, highlighting the market price, Through analysis it is concluded that with fuzzy based optimization model effectively accumulate fast and accurate calculation of the Project cost.