Exploring research on ecotechnology through artificial intelligence and bibliometric maps

IF 14 1区环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES

Environmental Science and Ecotechnology Pub Date : 2024-01-04 DOI:10.1016/j.ese.2023.100386

Ricardo Ruiz-Sánchez , Ricardo Arencibia-Jorge , Julia Tagüeña , José Luis Jiménez-Andrade , Humberto Carrillo-Calvet

引用次数: 0

Abstract

Ecotechnology, quintessential for crafting sustainable socio-environmental strategies, remains tantalizingly uncharted. Our analysis, steered by the nuances of machine learning and augmented by bibliometric insights, delineates the expansive terrain of this domain, elucidates pivotal research themes and conundrums, and discerns the vanguard nations in this field. Furthermore, we deftly connect our discoveries to the United Nations' 2030 Sustainable Development Goals, thereby accentuating the profound societal ramifications of ecotechnology.

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通过人工智能和文献计量图探索生态技术研究

生态技术是制定可持续社会环境战略的关键所在，但这一领域仍然充满诱惑和未知。我们的分析以机器学习的细微差别为指导，以文献计量学的洞察力为辅助，勾勒出这一领域的广阔地域，阐明了关键的研究主题和难题，并辨析了这一领域的先锋国家。此外，我们还巧妙地将我们的发现与联合国 2030 年可持续发展目标联系起来，从而强调了生态技术的深远社会影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Environmental Science and Ecotechnology Multiple-

CiteScore

20.40

自引率

6.30%

发文量

审稿时长

18 days

期刊介绍： Environmental Science & Ecotechnology (ESE) is an international, open-access journal publishing original research in environmental science, engineering, ecotechnology, and related fields. Authors publishing in ESE can immediately, permanently, and freely share their work. They have license options and retain copyright. Published by Elsevier, ESE is co-organized by the Chinese Society for Environmental Sciences, Harbin Institute of Technology, and the Chinese Research Academy of Environmental Sciences, under the supervision of the China Association for Science and Technology.