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Neural networks for business decision making

Citation

Xu, S and Liu, Y, Neural networks for business decision making, International Journal of Advancements in Computing Technology, 6, (2) pp. 49-58. ISSN 2005-8039 (2014) [Refereed Article]

Copyright Statement

Copyright 2014 Advanced Institute of Convergence Information Technology

Official URL: http://www.aicit.org/ijact/home/index.html

Abstract

In the current big-data era, business decision making usually involves mining large datasets for finding hidden patterns which can be used for predictions. Such data analytical tasks are far beyond the capabilities of human experts. Artificial Neural Networks (ANNs) are non-linear models that resemble biological neural networks in structure and learn through training. ANNs learn from examples in a way similar to how the human brain learns. Then ANNs take complex and noisy data as input and make educated guesses based on what they have learned from historical data. This paper presents a new learning algorithm for Higher Order Neural Networks (HONNs) which are ANNs in which the net input to a computational neuron is a weighted sum of its inputs plus products of its inputs. The novel learning algorithm is based on Extreme Learning Machine (ELM) algorithm which randomly chooses hidden layer neurons and analytically determines output weights. The experimental results demonstrate that HONN models with the new algorithm offer significant advantages over standard HONN models and traditional ANNs (including Multilayer Perceptrons and RBF Networks), such as faster training and improved generalization abilities.

Item Details

Item Type:Refereed Article
Keywords:neural network, higher order neural network, extreme learning machine, learning algorithm, machine learning
Research Division:Information and Computing Sciences
Research Group:Artificial Intelligence and Image Processing
Research Field:Neural, Evolutionary and Fuzzy Computation
Objective Division:Information and Communication Services
Objective Group:Computer Software and Services
Objective Field:Information Processing Services (incl. Data Entry and Capture)
Author:Xu, S (Dr Shuxiang Xu)
ID Code:90560
Year Published:2014
Deposited By:Computing and Information Systems
Deposited On:2014-04-10
Last Modified:2015-05-22
Downloads:5 View Download Statistics

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