This contribution delves into the pioneering deployment of intelligent methodologies in the realm of electrical engineering expenditure administration, spotlighting a BIM (Building Information Modeling)-facilitated electrical engineering expenditure oversight framework. The architecture amalgamates a genetic algorithm to enhance engineering cost forecasting and fiscal restraint. Through system simulation, people scrutinize the fiscal implications and advantages of diverse construction blueprints. Simulation outcomes reveal that, post-adoption of intelligent methodologies, the precision of electrical engineering expenditure management experiences a substantial uplift, with a mean error diminution of 15%. Precisely, embedding a genetic algorithm within model simulation accelerates the system's convergence towards the optimal solution, effectively mitigating the uncertainties inherent in cost estimation. Moreover, the integration of BIM technology actualizes real-time data refreshment and visualization, augmenting the clarity and efficacy of expenditure governance. The research findings not only proffer a novel intelligent resolution for electrical engineering's expenditure administration but also furnish a valuable benchmark for associated academic explorations.

Yu Mao, Lijie Ye. Application Analysis of Intelligent Technology in Power Engineering Cost Management. International Journal of New Developments in Engineering and Society (2024) Vol.8, Issue 4: 43-49. https://doi.org/10.25236/IJNDES.2024.080406.

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