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Artificial networks and aggregate consumption patterns in New Zealand
Farhat, Dan - 2012
Persistent link: https://www.econbiz.de/10009656231
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Recognition and classification of single and concurrent unnatural patterns in control charts via neural networks and fitted of samples
Lesany, S. A.; Koochakzadeh, A.; Fatemi Ghomi, S. M. T. - In: International journal of production research 52 (2014) 6, pp. 1771-1786
Persistent link: https://www.econbiz.de/10010257293
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Combination forecasts of tourism demand with machine learning models
Claveria, Oscar; Monte, Enric; Torra, Salvador - In: Applied economics letters 23 (2016) 4/6, pp. 428-431
Persistent link: https://www.econbiz.de/10011430763
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Machine learning applications in activity-travel behaviour research : a review
Koushik, Anil; Manoj, M.; Nezamuddin, N. - In: Transport reviews : a transnational transdisciplinary … 40 (2020) 3, pp. 288-311
Persistent link: https://www.econbiz.de/10012198300
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Improving customer loyalty evaluation methods in the grocery retail industry : a data mining approach
Khodabandehlou, Samira; NikNafs, Ali Akbar - In: International journal of electronic customer … 10 (2016) 2/4, pp. 158-178
Persistent link: https://www.econbiz.de/10011688029
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Two-dimensional face surface analysis using facial feature points detection approaches
Ahdid, Rachid; Azougaghe, Es-said; Safi, Said; Manaut, … - In: Journal of electronic commerce in organizations : the … 16 (2018) 1, pp. 57-71
Persistent link: https://www.econbiz.de/10011809544
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An investigation of the effect of variable reduction on classification accuracy rates of consumer loans
Zurada, Jozef - In: Review of business information systems 17 (2013) 4, pp. 135-139
Persistent link: https://www.econbiz.de/10010231895
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Application of machine learning in quantitative investment strategies on global stock markets
Grudniewicz, Jan; Ślepaczuk, Robert - 2021
Persistent link: https://www.econbiz.de/10012816704
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Predicting bank insolvencies using machine learning techniques
Petropoulos, Anastasios; Siakoulis, Vasilis; … - In: International journal of forecasting 36 (2020) 3, pp. 1092-1113
Persistent link: https://www.econbiz.de/10012497724
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Support vector machine methods and artificial neural networks used for the development of bankruptcy prediction models and their comparison
Horák, Jakub; Vrbka, Jaromir; Suler, Petr - In: Journal of risk and financial management : JRFM 13 (2020) 3/60, pp. 1-15
Bankruptcy prediction is always a topical issue. The activities of all business entities are directly or indirectly affected by various external and internal factors that may influence a company in insolvency and lead to bankruptcy. It is important to find a suitable tool to assess the future...
Persistent link: https://www.econbiz.de/10012302458