Ant Colony Algorithm-Based Audit Supervision to Promote the Optimization of New Infrastructure Investment Environment

Abstract

Infrastructure investment has the characteristics of high start-up cost, high initial cost, long cycle, slow recovery, high risk, and high public welfare. Maintenance after completion requires stable financial support, maintenance costs are easily affected by government agencies, and investment efficiency is significantly reduced. This article focuses on the ant colony algorithm audit and supervision to promote the optimization of the new infrastructure investment environment and understands the relevant theories of infrastructure investment on the basis of literature data, and then, the audit supervision based on the ant colony algorithm promotes the optimization of the new infrastructure investment environment. The model is constructed, and the constructed model is tested. The test results show that, first, there is a dynamic equilibrium relationship between total infrastructure investment and GDP, even if it cannot explain the potential relationship between the two. In essence, infrastructure investment has a positive impact on economic growth. As the economic level increases, the demand for infrastructure will increase and infrastructure investment will inevitably increase. Second, the level values of the first order are all nonstationary sequences; after the difference, they are all stable and have the same single integral order. The model meets the preconditions of the cointegration test.