Artificial neural networks in business: Two decades of research

M Tkáč, R Verner - Applied Soft Computing, 2016 - Elsevier
In recent two decades, artificial neural networks have been extensively used in many
business applications. Despite the growing number of research papers, only few studies …

Credit scoring, statistical techniques and evaluation criteria: a review of the literature

HA Abdou, J Pointon - Intelligent systems in accounting …, 2011 - Wiley Online Library
Credit scoring has been regarded as a core appraisal tool of different institutions during the
last few decades and has been widely investigated in different areas, such as finance and …

Data mining applications in accounting: A review of the literature and organizing framework

FA Amani, AM Fadlalla - International Journal of Accounting Information …, 2017 - Elsevier
This paper explores the applications of data mining techniques in accounting and proposes
an organizing framework for these applications. A large body of literature reported on …

Neural networks and statistical techniques: A review of applications

M Paliwal, UA Kumar - Expert systems with applications, 2009 - Elsevier
Neural networks are being used in areas of prediction and classification, the areas where
statistical methods have traditionally been used. Both the traditional statistical methods and …

Forecasting wind speed with recurrent neural networks

Q Cao, BT Ewing, MA Thompson - European Journal of Operational …, 2012 - Elsevier
This research presents a comparative analysis of the wind speed forecasting accuracy of
univariate and multivariate ARIMA models with their recurrent neural network counterparts …

Big data and artificial intelligence in the fields of accounting and auditing: a bibliometric analysis

MA Agustí, M Orta-Pérez - Spanish Journal of Finance and …, 2023 - Taylor & Francis
ABSTRACT The importance of Big Data and Artificial Intelligence in the fields of accounting
and auditing is beyond doubt. However, to date, the influence of these technologies on …

[HTML][HTML] Sparse regression for large data sets with outliers

L Bottmer, C Croux, I Wilms - European Journal of Operational Research, 2022 - Elsevier
The linear regression model remains an important workhorse for data scientists. However,
many data sets contain many more predictors than observations. Besides, outliers, or …

Neural network earnings per share forecasting models: A comparison of backward propagation and the genetic algorithm

Q Cao, ME Parry - Decision Support Systems, 2009 - Elsevier
Zhang, Cao, and Schniederjans [W. Zhang, Q. Cao, M. Schniederjans, Neural Network
Earnings Per Share Forecasting Models: A Comparative Analysis of Alternative Methods …

An improved back propagation neural network algorithm on classification problems

NM Nawi, RS Ransing, MNM Salleh, R Ghazali… - … 2010, Held as Part of the …, 2010 - Springer
The back propagation algorithm is one the most popular algorithms to train feed forward
neural networks. However, the convergence of this algorithm is slow, it is mainly because of …

Forecasting incoming call volumes in call centers with recurrent neural networks

ME Jalal, M Hosseini, S Karlsson - Journal of Business Research, 2016 - Elsevier
Abstract Researchers apply Neural Networks widely in model prediction and data mining
because of their remarkable approximation ability. This study uses a prediction model based …