人工智能与能源效率的服务贸易：基于 QUBO 模型的量子计算：绿色城市数字经济的乘数效应

IF 13.6 2区经济学 Q1 ECONOMICS

Energy Economics Pub Date : 2024-11-02 DOI:10.1016/j.eneco.2024.107976

Da Huo , Wenjia Gu , Dongmei Guo , Aidi Tang

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引用次数: 0

摘要

本研究通过 Malmquist-DEA 模型考察了城市地区的能源效率，并研究了服务贸易和数字经济对城市绿色发展中能源效率的空间效应。研究还深入探讨了人工智能服务贸易的具体背景，以深入了解并与新兴的数字智能产业接轨。服务贸易与数字经济以及人工智能服务贸易与创新的相互作用，大大提高了城市能效，并显示出积极的外部效应。在实证研究结果的基础上，本研究采用集群分析方法探索城市各区的绿色发展，并利用人工智能技术，在QUBO建模的基础上，运用量子计算，对各区集群的绿色交流与合作机制进行编程。这项研究有助于深入理解服务贸易和数字经济在能源效率方面的共同作用，并通过基于量子的人工智能进步，帮助绿色城市开发新的优质产品。这项研究对绿色人工智能技术在社会计算科学领域的前沿跨学科应用具有明确的意义。

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The service trade with AI and energy efficiency: Multiplier effect of the digital economy in a green city by using quantum computation based on QUBO modeling

This research examines the energy efficiency of city districts through the Malmquist–DEA model and investigates the spatial effects of the service trade and the digital economy on energy efficiency in urban green development. The study also delves into the specific context of the AI service trade to gain insights into and align with the emerging digital intelligence industry. The interplay of the service trade with the digital economy, alongside the AI service trade with innovation, significantly enhances urban energy efficiency and demonstrates positive externalities. Building on the empirical findings, this research employs cluster analysis to explore the green development of city districts and uses AI technology to program green communication and cooperation mechanisms across district clusters, employing quantum computation based on QUBO modeling. This study contributes to a deeper understanding of the cofunction of the service trade and the digital economy in terms of energy efficiency and aids in developing new quality productivities for green cities through quantum-based AI advancements. This research has clear implications for cutting-edge interdisciplinary applications of green AI technologies in social computing science.

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来源期刊

Energy Economics ECONOMICS-

CiteScore

18.60

自引率

12.50%

发文量

524

期刊介绍： Energy Economics is a field journal that focuses on energy economics and energy finance. It covers various themes including the exploitation, conversion, and use of energy, markets for energy commodities and derivatives, regulation and taxation, forecasting, environment and climate, international trade, development, and monetary policy. The journal welcomes contributions that utilize diverse methods such as experiments, surveys, econometrics, decomposition, simulation models, equilibrium models, optimization models, and analytical models. It publishes a combination of papers employing different methods to explore a wide range of topics. The journal's replication policy encourages the submission of replication studies, wherein researchers reproduce and extend the key results of original studies while explaining any differences. Energy Economics is indexed and abstracted in several databases including Environmental Abstracts, Fuel and Energy Abstracts, Social Sciences Citation Index, GEOBASE, Social & Behavioral Sciences, Journal of Economic Literature, INSPEC, and more.