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Neural networks for business decision making


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]

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Copyright 2014 Advanced Institute of Convergence Information Technology

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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:Machine learning
Research Field:Neural networks
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Information systems, technologies and services not elsewhere classified
UTAS Author:Xu, S (Dr Shuxiang Xu)
ID Code:90560
Year Published:2014
Deposited By:Information and Communication Technology
Deposited On:2014-04-10
Last Modified:2017-11-13
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