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Management accounting and the concepts of exploratory data analysis and unsupervised machine learning : a literature study and future directions

Nielsen, Steen - In: Journal of accounting & organizational change : JAOC 18 (2022) 5, pp. 811-853

Persistent link: https://www.econbiz.de/10013454831

Uncovering the identity of electronic markets research through text mining techniques

Nahr, Nora; Heikkilä, Marikka - In: Electronic markets : EM ; the international journal of … 32 (2022) 3, pp. 1257-1277

Persistent link: https://www.econbiz.de/10013463380

Monetary integration in South America : election of candidates through unsupervised machine learning

Padilla, León; Marín Nicolalde, Eduardo - In: Revista de economía mundial : REM ; revista de la … 61 (2022), pp. 63-89

Persistent link: https://www.econbiz.de/10013488645

European low-carbon policy : impact on fossil energy markets

Minlend, Jacques - 2023 - This version: February 2023

Persistent link: https://www.econbiz.de/10014334454

Stock market forecasting accuracy of asymmetric GARCH models during the COVID-19 pandemic

Caiado, Jorge; Lúcio, Francisco - In: The North American journal of economics and finance : a … 68 (2023), pp. 1-14

Persistent link: https://www.econbiz.de/10014485321

An unsupervised learning-based generalization of Data Envelopment Analysis

Moragues, Raul; Aparicio, Juan; Esteve, Miriam - In: Operations research perspectives 11 (2023), pp. 1-14

In this paper, we introduce an unsupervised machine learning method for production frontier estimation. This new approach satisfies fundamental properties of microeconomics, such as convexity and free disposability (shape constraints). The new method generalizes Data Envelopment Analysis (DEA)...

Persistent link: https://www.econbiz.de/10014448520

Towards a precise understanding of social entrepreneurship : an integrated bibliometric-machine learning based review and research agenda

Kaushik, Vineet; Tewari, Shobha; Sahasranamam, Sreevas; … - In: Technological forecasting & social change : an … 191 (2023), pp. 1-18

Persistent link: https://www.econbiz.de/10014287759

Robust estimation of conditional risk measures using machine learning algorithm for commodity futures prices in the presence of outliers

Byers, John W.; Popova, I.; Simkins, Betty J. - In: Journal of commodity markets 24 (2021), pp. 1-18

Persistent link: https://www.econbiz.de/10013392402

The Empirics of Financial Development and Economic Growth: Using Unsupervised Learning to Detect Multiple Steady States

Birchenhall, Chris; Bree, David S.; Lakha, Rahim - Society for Computational Economics - SCE - 2002

Persistent link: https://www.econbiz.de/10005132828

Comparison of deep learning models for multivariate prediction of time series wind power generation and temperature

Mishra, Sambeet; Bordin, Chiara; Taharaguchi, Kota; … - In: Energy reports 6 (2020) 3, pp. 273-286

Wind power experienced a substantial growth over the past decade especially because it has been seen as one of the best ways towards meeting climate change and emissions targets by many countries. Since wind power is not fully dispatchable, the accuracy of wind forecasts is a key element for the...

Persistent link: https://www.econbiz.de/10012183091