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Empirical comparison to predictive clustering between a bio-mimetic methodology and a non connectionist approach
Cucchi, Alain; Thebault, Marinette - In: Fuzzy economic review : the review of the International … 5 (2000) 2, pp. 27-48
Persistent link: https://www.econbiz.de/10001780053
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Incorporating statistical clustering methods into mortality models to improve forecasting performances
Tsai, Cary Chi-Liang; Cheng, Echo Sihan - In: Insurance / Mathematics & economics 99 (2021), pp. 42-62
Persistent link: https://www.econbiz.de/10012649207
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Improving time series forecasting: an approach combining bootstrap aggregation, clusters and exponential smoothing
Dantas, Tiago Mendes; Oliveira, Fernando Luiz Cyrino - In: International journal of forecasting 34 (2018) 4, pp. 748-761
Persistent link: https://www.econbiz.de/10012031097
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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 hybrid PSO-SVM model based on clustering algorithm for short-term atmospheric pollutant concentration forecasting
Chen, Shuixia; Wang, Jian-qiang; Zhang, Hong-yu - In: Technological forecasting & social change : an … 146 (2019), pp. 41-54
Persistent link: https://www.econbiz.de/10012134647
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Revealing cluster structures based on mixed sampling frequencies
Rho, Yeonwoo; Liu, Yun; Ahn, Hie Joo - 2020
Persistent link: https://www.econbiz.de/10012389465
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A combined algorithm for selection of optimal bidder(s)
Ravichandran, J.; Vanishree, B. - In: Journal of revenue and pricing management 23 (2024) 2, pp. 179-193
Persistent link: https://www.econbiz.de/10014536757
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A hierarchical agglomerative clustering for product sales forecasting
Ruitenbeek, R. E. van; Koole, Ger M.; Bhulai, S. - In: Decision analytics journal 8 (2023), pp. 1-12
Many forecasting methods perform poorly when dealing with intermittent demand patterns and large variations in demand quantity. The presence of significant fluctuations within the time series, coupled with a substantial proportion of zero observations, complicates the extraction of trend and...
Persistent link: https://www.econbiz.de/10014520564
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Vacant technology forecasting using new Bayesian patent clustering
Choi, Seongyong; Jun, Sunghae - In: Technology analysis & strategic management 26 (2014) 3, pp. 241-251
Persistent link: https://www.econbiz.de/10010338521
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Cluster and Forecasting Analysis of the Residential Market in Turkey : An Autoregressive Model-Based Fuzzy Clustering Approach
Vatansever, Metin - 2020
Purpose – The main purpose of this study is to detect homogeneous housing market areas among 196 districts of 5 major cities of Turkey in terms of house sale price indices. The second purpose is to forecast these 196 house sale price indices.Design/methodology/approach – In this paper, the...
Persistent link: https://www.econbiz.de/10012830430