从技术融合的角度预测建筑领域的绿色技术创新:基于可解释机器学习的两阶段预测方法
Shuai Feng1, Guiwen Liu1, Tianlong Shan1
1School of Management Science and Real Estate, Chongqing University, No.174, Shazheng Street, Shapingba District, Chongqing, 400044, PR China.
Journal of environmental management
|November 16, 2024
概括
本研究确定了305个高潜力的绿色技术融合机会,用于建筑行业使用机器学习. 它有助于制定可持续发展和绿色创新战略的决策.
科学领域:
- 建筑工程技术 建筑工程技术
- 绿色创新是一种绿色创新.
- 可持续发展 可持续发展 可持续发展
背景情况:
- 建筑行业是全球主要的能源消费者和碳排放者,需要绿色转型.
- 促进绿色技术创新是建设可持续发展的关键.
- 在识别和评估建筑研发的绿色技术创新机会方面存在差距.
研究的目的:
- 提出一种两阶段的机器学习方法,用于预测建筑业的技术机会.
- 识别和评估潜在的绿色技术融合机会.
- 预测这些趋同机会的技术影响.
主要方法:
- 使用了两阶段可解释的机器学习方法.
- 分析了来自绿色和建筑领域的600442份专利文件.
- 专注于技术融合,以确定创新机会.
主要成果:
- 确定了305个具有高潜力的技术融合机会.
- 突出了碳捕获,污染报警,太阳能和风能,节能方法以及水处理中的废物等方面的融合潜力.
- 发现的技术相似性和接近性是融合创新的关键影响因素.
结论:
- 为政府和行业利益相关者提供关于绿色技术创新的决策支持.
- 加快建筑行业向可持续发展的绿色转型.
- 提供了一种新的方法,通过融合来预测技术机会及其影响.
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