Artificial Intelligence for Fashion Industry in the Big Data Era [[electronic resource] /] / edited by Sébastien Thomassey, Xianyi Zeng

• Record Nr.: UNINA9910349478503321
• Pubbl/distr/stampa: Singapore : , : Springer Singapore : , : Imprint : Springer, , 2018
• ISBN: 9789811300806; 981-13-0080-1
• Edizione: [1st ed. 2018.]
• Descrizione fisica: 1 online resource (288 pages)
• Collana: Springer Series in Fashion Business, , 2366-8776
• Disciplina: 687.0285
• Soggetti: Market research; Textile industry; Artificial intelligence; Market Research/Competitive Intelligence; Textile Engineering; Artificial Intelligence
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: AI based fashion sales forecasting methods in big data era -- Enhanced Predictive Models for Purchasing in the Fashion Field by Applying Regression Trees Equipped with Ordinal Logistic Regression -- A Data Mining Based Framework for Multi-Item Markdown Optimization -- Social Media Analytics for decision support in Fashion Buying Processes -- Review of Artificial Intelligence Applications in Garment Manufacturing -- AI for Apparel Manufacturing in Big Data Era: A Focus on Cutting and Sewing -- A Discrete Event Simulation Model with Genetic Algorithm Optimization for Customized Textile Production Scheduling -- An intelligent fashion replenishment system based on data analytics and expert judgement -- Blockchain based secured traceability system for textile and clothing supply chain -- Artificial intelligence applied to multisensory studies of textile products -- Evaluation of Fashion Design Using Artificial Intelligence Tools -- Garment wearing comfort analysis using data mining technology -- Garment fit evaluation using machine learning technology.
• Sommario/riassunto: This book provides an overview of current issues and challenges in the ; fashion industry and an update on data-driven artificial intelligence (AI) techniques and their potential implementation in response to those challenges. Each chapter starts off with an example of a data-driven AI technique on a particular sector of the fashion industry (design, manufacturing, supply or retailing), before moving on to illustrate its implementation in a real-world application.