{"id":"W4388878700","doi":"10.2139/ssrn.4640557","title":"Safety Stock Estimation Based on Forecasted Demand Distribution Using Recurrent Mixture Density Networks","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Estimation; Density estimation; Econometrics; Stock (firearms); Distribution (mathematics); Statistics; Economics; Mathematics; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":{"n_in":0,"stratum":"aff_core","weight":5595.2375,"opus":{"tier":"OUT","genre":"empirical","about_ca":false,"confidence":"high","reason":"Operations research on safety stock estimation using recurrent mixture density networks; a supply chain forecasting method for inventory, not a study of research."},"gpt":{"tier":"OUT","genre":"empirical","about_ca":false,"confidence":"high","reason":"This work develops a demand-forecasting approach for safety-stock estimation, not a study of research."},"grok":{"tier":"OUT","genre":"empirical","about_ca":false,"confidence":"low","reason":"Operations/forecasting title on safety stock estimation; domain application, abstract missing."}}}