What question did this study set out to answer?

The aim is to explore how digital twin technology can transform scheduling in water conservancy engineering to enhance efficiency and decision-making.

May 29, 2026工程学研究与实用Open Access

基于数字孪生技术的水利工程智能调度系统研究

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李李广杰 JZJ Zhang

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Overview

Randomized trial examines intelligent scheduling in water conservancy projects, suggesting improved efficiency and response to challenges.

Key Points

The aim is to explore how digital twin technology can transform scheduling in water conservancy engineering to enhance efficiency and decision-making.
Developed a comprehensive framework integrating perception, modeling, simulation, decision-making, and feedback.
Investigated key technologies like multi-source heterogeneous data fusion and high-fidelity hydrodynamic model coupling.
Applied the system to a large-scale reservoir group as a case study.
The intelligent scheduling system improved scheduling accuracy and emergency response capabilities significantly.
Achieved effective multi-dimensional collaboration between ecological, economic, and safety metrics.
Enabled a shift from an experience-driven to a data-model dual-driven paradigm in hydraulic engineering.

Cite This Study

李广杰 et al. (2026) studied this question.

synapsesocial.com/papers/6a192df7fab5b468c4417072 https://doi.org/10.37155/2717-5316-0706-37

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May 29, 2026工程学研究与实用Open Access

基于数字孪生技术的水利工程智能调度系统研究

View Full Paper

Ask AI

Bookmark

Authors

李李广杰 JZJ Zhang

Discussion

Member takes

Overview

Randomized trial examines intelligent scheduling in water conservancy projects, suggesting improved efficiency and response to challenges.

Key Points

The aim is to explore how digital twin technology can transform scheduling in water conservancy engineering to enhance efficiency and decision-making.
Developed a comprehensive framework integrating perception, modeling, simulation, decision-making, and feedback.
Investigated key technologies like multi-source heterogeneous data fusion and high-fidelity hydrodynamic model coupling.
Applied the system to a large-scale reservoir group as a case study.
The intelligent scheduling system improved scheduling accuracy and emergency response capabilities significantly.
Achieved effective multi-dimensional collaboration between ecological, economic, and safety metrics.
Enabled a shift from an experience-driven to a data-model dual-driven paradigm in hydraulic engineering.

Cite This Study

李广杰 et al. (2026) studied this question.

synapsesocial.com/papers/6a192df7fab5b468c4417072 https://doi.org/10.37155/2717-5316-0706-37

View Full Paper

Ask AI

Bookmark