{"title":"基于时间序列成像的库存控制深度学习方法","authors":"Yu-Xin Tian, Chuan Zhang","doi":"10.1080/03081079.2024.2379360","DOIUrl":null,"url":null,"abstract":"Data-driven newsvendor methods offer promising solutions for estimating replenishment quantity within complex markets by leveraging demand-related features. However, most features utilized by these...","PeriodicalId":50322,"journal":{"name":"International Journal of General Systems","volume":"245 1","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Time series imaging-based deep learning method for inventory control\",\"authors\":\"Yu-Xin Tian, Chuan Zhang\",\"doi\":\"10.1080/03081079.2024.2379360\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Data-driven newsvendor methods offer promising solutions for estimating replenishment quantity within complex markets by leveraging demand-related features. However, most features utilized by these...\",\"PeriodicalId\":50322,\"journal\":{\"name\":\"International Journal of General Systems\",\"volume\":\"245 1\",\"pages\":\"\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-07-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of General Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1080/03081079.2024.2379360\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of General Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1080/03081079.2024.2379360","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
Time series imaging-based deep learning method for inventory control
Data-driven newsvendor methods offer promising solutions for estimating replenishment quantity within complex markets by leveraging demand-related features. However, most features utilized by these...
期刊介绍：
International Journal of General Systems is a periodical devoted primarily to the publication of original research contributions to system science, basic as well as applied. However, relevant survey articles, invited book reviews, bibliographies, and letters to the editor are also published.
The principal aim of the journal is to promote original systems ideas (concepts, principles, methods, theoretical or experimental results, etc.) that are broadly applicable to various kinds of systems. The term “general system” in the name of the journal is intended to indicate this aim–the orientation to systems ideas that have a general applicability. Typical subject areas covered by the journal include: uncertainty and randomness; fuzziness and imprecision; information; complexity; inductive and deductive reasoning about systems; learning; systems analysis and design; and theoretical as well as experimental knowledge regarding various categories of systems. Submitted research must be well presented and must clearly state the contribution and novelty. Manuscripts dealing with particular kinds of systems which lack general applicability across a broad range of systems should be sent to journals specializing in the respective topics.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
