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Time series forecasting based on a multidimensional Taylor network model with clustering of dynamic characteristics
Yan, Hong-Sen; Zheng, Xiao-Yi; Zhou, Bo; Zhang, Jiao-Jun - In: Journal of the Operational Research Society 73 (2022) 12, pp. 2660-2669
Persistent link: https://www.econbiz.de/10013533308
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Improving out-of-sample forecasts of stock price indexes with forecast reconciliation and clustering
Mattera, Raffaele; Athanasopoulos, George; Hyndman, Rob J. - In: Quantitative finance 24 (2024) 11, pp. 1641-1667
Persistent link: https://www.econbiz.de/10015196952
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Cash demand forecasting in ATMs by clustering and neural networks
Venkatesh, Kamini; Ravi, Vadlamani; Prinzie, Anita; Van … - In: European journal of operational research : EJOR 232 (2014) 2, pp. 383-392
Persistent link: https://www.econbiz.de/10010224693
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Tree-based methods for clustering time series using domain-relevant attributes
Ashouri, Mahsa; Shmueli, Galit; Sin, Chor-yiu - In: Journal of business analytics 2 (2019) 1, pp. 1-23
Persistent link: https://www.econbiz.de/10012170261
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A novel cluster HAR-type model for forecasting realized volatility
Yao, Xingzhi; Izzeldin, Marwan; Li, Zhenxiong - In: International journal of forecasting 35 (2019) 4, pp. 1318-1331
Persistent link: https://www.econbiz.de/10012305326
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Predicting the price of taxicabs using artificial intelligence : a hybrid approach based on clustering and ordinal regression models
Rathore, Bhawana; Sengupta, Pooja; Biswas, Baidyanath; … - In: Transportation research : an international journal 185 (2024), pp. 1-22
Persistent link: https://www.econbiz.de/10015078403
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Cluster-based cross layer-cross domain routing model with DNN-based energy prediction
Lahane, Shivaji R.; Lahane, Priti S. - In: Journal of information & knowledge management : JIKM 23 (2024) 3, pp. 1-37
Persistent link: https://www.econbiz.de/10014575745
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Improving out-of-sample forecasts of stock price indexes with forecast reconciliation and clustering
Mattera, Raffaele; Athanasopoulos, George; Hyndman, Rob J. - 2023
Persistent link: https://www.econbiz.de/10014452575
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unFEAR : unsupervised feature extraction clustering with an application to crisis regimes classification
Chan-Lau, Jorge A.; Wang, Ran - 2020
We introduce unFEAR, Unsupervised Feature Extraction Clustering, to identify economic crisis regimes. Given labeled …
Persistent link: https://www.econbiz.de/10012392653
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Data vs. information : using clustering techniques to enhance stock returns forecasting
Vásquez Sáenz, Javier; Quiroga, Facundo Manuel; … - In: International review of financial analysis 88 (2023), pp. 1-10
Persistent link: https://www.econbiz.de/10014462210