00763nas a2200241 i 450099100273031970753620231114121034.0011205m19791985fr || | |fre 0240-9453b11700208-39ule_instPERLE006313ExLCDU 396PenelopePenelope :pour l'histoire des femmes. - 1979-1985Paris,1979-1985Codice CNR: E 00000133LE009 1979-1985;.b1170020818-01-1108-07-02991002730319707536LE009 Per. St. 1741le009-E0.00-no 180000.i1193293408-07-02Penelope894117UNISALENTOle00901-01-01sa -frefr 0104586nam 22006495 450 991029853520332120200920170828.03-642-39869-310.1007/978-3-642-39869-8(CKB)3710000000074939(EBL)1592467(SSID)ssj0001066624(PQKBManifestationID)11593804(PQKBTitleCode)TC0001066624(PQKBWorkID)11068025(PQKB)10952157(MiAaPQ)EBC1592467(DE-He213)978-3-642-39869-8(PPN)176113819(EXLCZ)99371000000007493920131129d2014 u| 0engur|n|---|||||txtccrIntelligent Fashion Forecasting Systems: Models and Applications /edited by Tsan-Ming Choi, Chi-Leung Hui, Yong Yu1st ed. 2014.Berlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,2014.1 online resource (199 p.)Description based upon print version of record.3-642-39868-5 Includes bibliographical references.Part I: Introduction, review and exploratory studies -- 1.1 Introduction: Intelligent Fashion Forecasting -- 1.2  Sales forecasting in Apparel and Fashion Industry: a review -- Collaborative Planning Forecasting Replenishment Schemes in Apparel Supply Chain Systems: Cases and Research Opportunities -- Part II: Theoretical modeling research -- 2.1  Measuring Forecasting Accuracy: Problems and Recommendations (by the example of SKU-level judgmental adjustments) -- 2.2 Forecasting Demand for Fashion Goods: A Hierarchical Bayesian Approach -- Forecasting Fashion Store Reservations: Booking Horizon Forecasting with Dynamic Updating -- Part III: Intelligent fashion forecasting: applications and analysis -- 3.1 Fuzzy Forecast Combining for Apparel Demand Forecasting -- 3.2 Intelligent Fashion Colour Trend Forecasting Schemes: A Comparative Study -- 3.3 Neural Networks Based for Romanian Clothing Sector.      .Forecasting is a crucial function for companies in the fashion industry, but for many real-life forecasting applications, the data patterns are notorious for being highly volatile and it is very difficult, if not impossible, to analytically learn about the underlying patterns. As a result, many traditional methods (such as pure statistical models) will fail to make a sound prediction. Over the past decade, advances in artificial intelligence and computing technologies have provided an alternative way of generating precise and accurate forecasting results for fashion businesses. Despite being an important and timely topic, there is currently an absence of a comprehensive reference source that provides up-to-date theoretical and applied research findings on the subject of intelligent fashion forecasting systems. This three-part handbook fulfills this need and covers materials ranging from introductory studies and technical reviews, theoretical modeling research, to intelligent fashion forecasting applications and analysis. This book is suitable for academic researchers, graduate students, senior undergraduate students and practitioners who are interested in the latest research on fashion forecasting.Information technologyBusiness—Data processingApplication softwareProduction managementIT in Businesshttps://scigraph.springernature.com/ontologies/product-market-codes/522000Information Systems Applications (incl. Internet)https://scigraph.springernature.com/ontologies/product-market-codes/I18040Operations Managementhttps://scigraph.springernature.com/ontologies/product-market-codes/519000Information technology.Business—Data processing.Application software.Production management.IT in Business.Information Systems Applications (incl. Internet).Operations Management.003.2Choi Tsan-Mingedthttp://id.loc.gov/vocabulary/relators/edtHui Chi-Leungedthttp://id.loc.gov/vocabulary/relators/edtYu Yongedthttp://id.loc.gov/vocabulary/relators/edtBOOK9910298535203321Intelligent Fashion Forecasting Systems: Models and Applications2505897UNINA