Machine learning in supply chain: prediction of real-time e-order arrivals using ANFIS
Author:
Publisher
Springer Science and Business Media LLC
Subject
Strategy and Management,Safety, Risk, Reliability and Quality
Link
https://link.springer.com/content/pdf/10.1007/s13198-022-01851-7.pdf
Reference63 articles.
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2. Akbari M, Do TNA (2021) A systematic review of machine learning in logistics and supply chain management: current trends and future directions. Benchmarking Int J 28(10):2977–3005. https://doi.org/10.1108/BIJ-10-2020-0514
3. Alenezy AH, Ismail MT, Wadi SA, Tahir M, Hamadneh NN, Jaber JJ, Khan WA (2021) Forecasting stock market volatility using hybrid of adaptive network of fuzzy inference system and wavelet functions. J Math. https://doi.org/10.1155/2021/9954341
4. AlRassas AM, Al-qaness MAA, Ewees AA, Ren S, Abd Elaziz M, Damaševičius R, Krilavičius T (2021) Optimized ANFIS model using aquila optimizer for oil production forecasting. Processes 9(7):1194. https://doi.org/10.3390/pr9071194
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