人工智能在服装行业的敏捷应用

Q1 Multidisciplinary

International Journal of Agile Systems and Management Pub Date : 2023-01-01 DOI:10.1504/ijasm.2023.134012

Rui Gonçalves, Renato Lopes d, a Costa, Leandro Pereira, Álvaro Dias, Rui Vinhas d, a Silva, Natália Teixeira

引用次数: 0

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Agile applications of artificial intelligence to apparel industry

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

International Journal of Agile Systems and Management Multidisciplinary-Multidisciplinary

CiteScore

2.70

自引率

0.00%

发文量

期刊介绍： The objective of IJASM is to establish an effective channel of communication between academia, industry and persons concerned with the design and development of systems. Change is eternal and perpetual, irrespective of type of system. Systems created in the course of the advance of human civilization need to be functionally and operationally sustainable amid changes in technological, political, socio-economical, financial, cultural and other environmental challenges. IJASM aims to promote and harmonize knowledge developments in the emerging fields of agile systems research, sustainability and vulnerability analysis, risk assessments methodologies, complex systems science, e-organisation and e-supply chain management, with emphasis on the international dimension, particularly breaking cultural barriers, and on national contexts, globalisation and new business practices. As such, we aim to publish papers presenting new research, innovative theoretical approaches, changes in agile management paradigms, and action (both examples of successes and failures as long as there are important lessons to be learned) from leading scholars and practitioners. Papers generally fall into two broad categories: those grounded in theory and/or papers using scientific research methods (e.g., reports of original empirical studies, models, critical reviews of existing empirical research, theory pieces that clearly extend current thinking); and those focusing on innovative agile approaches that are based on well reasoned extensions of existing research, experiential knowledge, or exemplary cases (e.g., thought pieces, case studies, etc).