Environments, Journal Year: 2024, Volume and Issue: 12(1), P. 1 - 1

Published: Dec. 25, 2024

Circular Economy (CE) and circular cities are recognized as essential approaches for achieving sustainability fostering sustainable urban development. Given the diverse definitions principles, multidimensional complexities, lack of a comprehensive list CE indicators, this study aims to propose an innovative method identifying macro-level indicators assess circularity. This methodology combines systematic literature review (SLR) with advanced machine learning (ML) natural language processing (NLP) techniques. A multi-algorithmic approach, incorporating BERT, TF-IDF, Word2Vec, graph-based clustering models, is employed extract set from reputable scientific articles reports compare frequency similarly based on each model. The overlap accuracy results these five methods analyzed produce refined high precision alignment core principles. curated collection serves valuable tool policymakers, planners, designers, enabling prediction future trends in Additionally, it provides guidance research practical projects at various scales, buildings neighborhoods entire cities, facilitating more precise assessment circularity modern environments.

Language: Английский