基于人工智能的绿色技术实施模拟,以实现碳中和:探索补贴和知识管理的作用
Jifan Ren1, Qasir Abbas2, Jafar Hussain3,4,5
1School of Economics and Management, Harbin Institute of Technology, Shenzhen, China.
Environmental science and pollution research international
|September 17, 2024
概括
这项研究表明,教育可能会降低家庭对基于人工智能的绿色技术实施 (GTI) 的热情. 最佳的补贴是平衡绿色行为和采用碳中和性的关键.
科学领域:
- 环境科学 环境科学
- 技术政策 技术政策
- 行为经济学是一种行为经济学.
背景情况:
- 现有研究在理解家庭级人工智能 (AI) 绿色技术实施 (GTI) 实现碳中和方面存在差距.
- 教育和消费偏好对基于AI的GTI决策的影响需要进一步调查.
- 量化行为因素对排放的影响以及补贴在促进可持续转型中的作用至关重要.
研究的目的:
- 调查基于人工智能的GTI在家庭层面的作用,以实现碳中和.
- 分析教育,绿色消费偏好和排放影响如何影响基于AI的GTI决策.
- 通过行为分析,提出最佳的补贴水平,以加速碳中和转型.
主要方法:
- 用简单的随机抽样对巴基斯坦旁遮普省大约1000个家庭进行行为分析.
- 回归分析和基于模拟的优化以量化影响并确定最佳补贴水平.
- 验证方法与以前的方法相比,以确保稳定性.
主要成果:
- 发现更高的教育水平与对基于AI的GTI的热情较低相关.
- 模拟确定了最佳的补贴水平,以平衡鼓励绿色行为与技术采用.
- 为了推进基于AI的GTI和可持续的家庭实践,定义了教育和补贴的关键门.
结论:
- 教育和补贴在推进基于人工智能的绿色技术和可持续的家庭实践方面发挥着关键作用.
- 了解基于人工智能的GTI决策与教育影响之间的复杂关系对于环境可持续性至关重要.
- 这项研究为优化家庭碳中和战略提供了重要的见解.
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