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Application of multiple regression and adaptive neuro fuzzy inference system for the prediction of surface roughness

Kumanan, Somasundaram; Jesuthanam, C. P.; Kumar, R. Ashok - In: The international journal of advanced manufacturing … 35 (2008) 7/8, pp. 778-788

Persistent link: https://www.econbiz.de/10003681489

Business failure prediction using decision trees

Gepp, Adrian; Kumar, Kuldeep; Bhattacharya, Sukanto - In: Journal of forecasting 29 (2010) 6, pp. 536-555

Persistent link: https://www.econbiz.de/10008935466

On forecasting using VARMA models

Kumar, Kuldeep; Bhattacharya, Abhijeet - In: The Asian economic review : journal of the Indian … 47 (2005) 2, pp. 269-275

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An empirical study of modelling and forecasting macroeconomic time series data

Gill, Dilbagh S.; Kumar, Kuldeep - In: The Indian journal of economics 80 (2000) 4, pp. 451-457

Persistent link: https://www.econbiz.de/10001533269

Some recent developments in non-linear time series modelling, testing, and forecasting

Gooijer, Jan G. de - In: International journal of forecasting 8 (1992) 2, pp. 135-156

Persistent link: https://www.econbiz.de/10001135281

On forecasting unemployment rate

Kumar, Kuldeep - In: The Asian economic review : journal of the Indian … 42 (2000) 3, pp. 480-483

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Using cutting-edge tree-based stochastic models to predict credit risk

Halteh, Khaled; Kumar, Kuldeep; Gepp, Adrian - In: Risks : open access journal 6 (2018) 2, pp. 1-13

Credit risk is a critical issue that affects banks and companies on a global scale. Possessing the ability to accurately predict the level of credit risk has the potential to help the lender and borrower. This is achieved by alleviating the number of loans provided to borrowers with poor...

Persistent link: https://www.econbiz.de/10011867384