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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 …
Persistent link: https://www.econbiz.de/10012302458
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Is artificial intelligence really more accurate in predicting bankruptcy?
Letkovský, Stanislav; Jeňcová, Sylvia; … - In: International Journal of Financial Studies : open … 12 (2024) 1, pp. 1-19
aims to develop bankruptcy prediction models for the chemical industry in Slovakia and to compare their effectiveness …. The selection of eleven financial indicators used for bankruptcy prediction was grounded in prior research and existing …
Persistent link: https://www.econbiz.de/10014502270
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The predictability of the exchange rate when combining machine learning and fundamental models
Zhang, Yuchen; Hamori, Shigeyuki - In: Journal of risk and financial management : JRFM 13 (2020) 3/48, pp. 1-16
prediction performance of random walk without drift. More specifically, this paper applies the random forest, support vector …
Persistent link: https://www.econbiz.de/10012174126
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The predictability of the exchange rate when combining machine learning and fundamental models
Zhang, Yuchen; Hamori, Shigeyuki - In: Journal of Risk and Financial Management 13 (2020) 3, pp. 1-16
prediction performance of random walk without drift. More specifically, this paper applies the random forest, support vector …
Persistent link: https://www.econbiz.de/10012611273
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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 13 (2020) 3, pp. 1-15
Bankruptcy prediction is always a topical issue. The activities of all business entities are directly or indirectly …
Persistent link: https://www.econbiz.de/10012611289
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China's missing pigs : correcting China's hog inventory data using a machine learning approach
Shao, Yongtong; Li, Minghao; Hayes, Dermot James; … - 2020
Persistent link: https://www.econbiz.de/10012387933
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Modern prediction methods : new perspectives on a common problem
Putka, Dan J.; Beatty, Adam S.; Reeder, Matthew C. - In: Organizational research methods : ORM 21 (2018) 3, pp. 689-732
Persistent link: https://www.econbiz.de/10011880167
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The impact of COVID-19 on unemployment rate : an intelligent based unemployment rate prediction in selected countries of Europe
Ahmad, Muneeb; Khan, Yousaf Ali; Jiang, Chonghui; … - In: International journal of finance & economics : IJFE 28 (2023) 1, pp. 528-543
Persistent link: https://www.econbiz.de/10014253227
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PREDICTING FINANCIAL DISTRESS OF CHINESE LISTED COMPANIES USING ROUGH SET THEORY AND SUPPORT VECTOR MACHINE
CAO, YU; WAN, GUANGYU; WANG, FUQIANG - In: Asia-Pacific Journal of Operational Research (APJOR) 28 (2011) 01, pp. 95-109
), in order to find a better early warning method and enhance the prediction accuracy. After several comparative experiments … prediction. …
Persistent link: https://www.econbiz.de/10008852562
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PREDICTION OF SEVERE THUNDERSTORMS WITH MINIMAL A PRIORI INFORMATION
CHAUDHURI, SUTAPA; CHATTOPADHYAY, SURAJIT - In: Advances in Complex Systems (ACS) 08 (2005) 01, pp. 75-86
A genetic algorithm (GA) is introduced to fix ranges of parameters, in a quantitative manner, pertaining to forecasting the genesis of severe thunderstorms in the pre-monsoon season over Calcutta (22°32′, 88°20′) in the northeastern part of India (20°–24°N latitude, 85°–93°E...
Persistent link: https://www.econbiz.de/10005080948