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Daily retail demand forecasting using machine learning with emphasis on calendric special days
Huber, Jakob; Stuckenschmidt, Heiner - In: International journal of forecasting 36 (2020) 4, pp. 1420-1438
Persistent link: https://www.econbiz.de/10012546798
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DeepAR : probabilistic forecasting with autoregressive recurrent networks
Salinas, David; Flunkert, Valentin; Gasthaus, Jan; … - In: International journal of forecasting 36 (2020) 3, pp. 1181-1191
Persistent link: https://www.econbiz.de/10012498611
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Data source combination for tourism demand forecasting
Hu, Mingming; Song, Haiyan - In: Tourism economics : the business and finance of tourism … 26 (2020) 7, pp. 1248-1265
Persistent link: https://www.econbiz.de/10012310080
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Electricity demand forecasting using fuzzy hybrid intelligence-based seasonal models
Khashei, Mehdi; Chahkoutahi, Fatemeh - In: Journal of modelling in management 17 (2022) 1, pp. 154-176
Persistent link: https://www.econbiz.de/10012886288
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A novel approach to model selection in tourism demand modeling
Akın, Melda - In: Tourism management : research, policies, practice 48 (2015), pp. 64-73
Persistent link: https://www.econbiz.de/10010508442
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Demand forecasting for fashion products : a systematic review
Swaminathan, Kritika; Venkitasubramony, Rakesh - In: International journal of forecasting 40 (2024) 1, pp. 247-267
Persistent link: https://www.econbiz.de/10014450269
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International tourism demand forecasting with machine learning models : the power of the number of lagged inputs
Bi, Jian-Wu; Han, Tian-Yu; Li, Hui - In: Tourism economics : the business and finance of tourism … 28 (2022) 3, pp. 621-645
Persistent link: https://www.econbiz.de/10013267939
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Supporting of manufacturing system based on demand forecasting tool
Kmiecik, Mariusz; Zangana, Hawre - In: LogForum : elektroniczne czasopismo naukowe z dziedziny … 18 (2022) 1, pp. 33-48
Persistent link: https://www.econbiz.de/10013164691
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AI, skill, and productivity : the case of taxi drivers
Kanazawa, Kyogo; Kawaguchi, Daiji; Shigeoka, Hitoshi; … - 2022
assists drivers with finding customers by suggesting routes along which the demand is predicted to be high. We find that AI …
Persistent link: https://www.econbiz.de/10013433210
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A comparative study of demand forecasting models for a multi-channel retail company : a novel hybrid machine learning approach
Mitra, Arnab; Jain, Arnav; Kishore, Avinash; Kumar, Pravin - In: Operations research forum 3 (2022) 4, pp. 1-22
Persistent link: https://www.econbiz.de/10013461968