Decision Model for Cost Control of Transmission and Transformation Projects Considering Uncertainty: A GAN Algorithm

The article aims to propose an analysis model based on the GAN (General Adversarial Network) algorithm to address the impact of uncertain factors on cost control decisions in power transmission and transformation projects (PTTP). This article deeply analyzes the uncertainty factors of power transmission and transformation engineering (PTTE), identifies the key factors that affect cost control, and uses GAN algorithm to simulate and predict them, improving the accuracy and reliability of the decision-making process. The research results indicate that the uncertainty cost control decision analysis model based on GAN algorithm can effectively improve the cost prediction accuracy of PTTP, with a maximum of 96.5%. This provides an important reference basis for engineering management and decision-making. Therefore, the article provides a new idea and method for cost control of PTTP, which has important theoretical and practical significance.