Construction of Dynamic Cost Control Model and Cost Optimization Research for Green Buildings Empowered by Low-Carbon Technology
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Abstract
To address the drawbacks of traditional cost control, such as static management and insufficient adaptability, this study focuses on low-carbon technology-enabled green buildings and constructs a dynamic cost control model to reveal the bidirectional impact mechanism of low-carbon technologies on project costs throughout the whole life cycle. As intelligent green buildings increasingly integrate electromagnetic sensing and wireless monitoring technologies for realtime operation management, dynamic cost evaluation has become an important component of sustainable infrastructure optimization. Based on whole-life-cycle theory and system dynamics, a dynamic control framework is established, and the integrated mechanism of “system dynamics (SD) + BP neural network” is developed to improve prediction accuracy. In addition, a full-life-cycle cost optimization strategy covering the design, construction, and operation stages is proposed, together with policy- and market-oriented supporting measures. Empirical validation using a university student cultural and sports center demonstrates that the model reduces the design-stage cost prediction deviation to 3.5% and achieves a 90% risk early-warning rate. After optimization, the whole-life-cycle cost is reduced by 9.8%, while carbon emission reduction increases by 18%. The proposed framework enriches the integration of low-carbon technologies and dynamic cost management, providing practical guidance for intelligent green buildings and electromagnetic-assisted infrastructure monitoring.
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