000 03930nam a22005295i 4500
001 978-3-642-39869-8
003 DE-He213
005 20200420211738.0
007 cr nn 008mamaa
008 131129s2014 gw | s |||| 0|eng d
020 _a9783642398698
_9978-3-642-39869-8
024 7 _a10.1007/978-3-642-39869-8
_2doi
050 4 _aHF54.5-54.56
072 7 _aKJQ
_2bicssc
072 7 _aUF
_2bicssc
072 7 _aBUS083000
_2bisacsh
072 7 _aCOM039000
_2bisacsh
082 0 4 _a650
_223
082 0 4 _a658.05
_223
245 1 0 _aIntelligent Fashion Forecasting Systems: Models and Applications
_h[electronic resource] /
_cedited by Tsan-Ming Choi, Chi-Leung Hui, Yong Yu.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2014.
300 _aVIII, 194 p. 76 illus., 39 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aPart 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.      .
520 _aForecasting 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.
650 0 _aBusiness.
650 0 _aProduction management.
650 0 _aInformation technology.
650 0 _aBusiness
_xData processing.
650 1 4 _aBusiness and Management.
650 2 4 _aIT in Business.
650 2 4 _aInformation Systems Applications (incl. Internet).
650 2 4 _aOperations Management.
700 1 _aChoi, Tsan-Ming.
_eeditor.
700 1 _aHui, Chi-Leung.
_eeditor.
700 1 _aYu, Yong.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642398681
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-39869-8
912 _aZDB-2-SBE
942 _cEBK
999 _c50500
_d50500