The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Adaptive Higher Order Neural Network Models and Their Applications in Business
Abstract
Business is a diversified field with general areas of specialisation such as accounting, taxation, stock market, and other financial analysis. Artificial Neural Networks (ANN) have been widely used in applications such as bankruptcy prediction, predicting costs, forecasting revenue, forecasting share prices and exchange rates, processing documents and many more. This chapter introduces an Adaptive Higher Order Neural Network (HONN) model and applies the adaptive model in business applications such as simulating and forecasting share prices. This adaptive HONN model offers significant advantages over traditional Standard ANN models such as much reduced network size, faster training, as well as much improved simulation and forecasting errors, due to their ability to better approximate complex, non-smooth, often discontinuous training data sets. The generalisation ability of this HONN model is explored and discussed.
Related Content
|
Dankan Gowda V., Anjali Sandeep Gaikwad, Pilli Lalitha Kumari, Erdal Buyukbicakci, Sengul Ibrahimoglu.
© 2025.
32 pages.
|
|
Debasish Banerjee, Ranjit Barua, Sudipto Datta, Dileep Pathote.
© 2025.
18 pages.
|
|
Kok Yeow You, Man Seng Sim.
© 2025.
96 pages.
|
|
Man Seng Sim, Kok Yeow You, Fahmiruddin Esa, Raimi Dewan, DiviyaDevi Paramasivam, Rozeha A. Rashid.
© 2025.
38 pages.
|
|
Mandeep Kaur.
© 2025.
24 pages.
|
|
Ganesh Khekare, Priya Dasarwar, Ajay Kumar Phulre, Urvashi Khekare, Gaurav Kumar Ameta, Shashi Kant Gupta.
© 2025.
22 pages.
|
|
Manoj Kumar Elipey, P. S. Kishore, Ratna Sunil Buradagunta.
© 2025.
14 pages.
|
|
|