A New Neural-Based Market Prediction Computing Approach
Natural Computation, 2009. ICNC '09. Fifth International Conference（2009）
摘要
A new kind of neural-based market prediction computing approach for electronic commerce has been presented by our research group in this paper. Our purpose is to suggest a successful and efficient prediction method of risk assessment for the clients to get substantial profits in competitive commerce markets of electronic commerce. In this paper we study the benefits of combining two layered feed forward neural networks trained by back propagation on an identical data set. In this case, network diversity was achieved by the inherent randomness associated with the back-propagation algorithm's initialization of a network's weights. By case experiments of risk assessment of electronic commerce, our technique has been tested effectively.
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关键词
neural network,case studies,learning (artificial intelligence),information fusion,neural,market prediction,backpropagation,feedforward neural nets,backpropagation algorithm's,competitive commerce market,network diversity,computing approach,marketing,neural-based market prediction computing,case experiment,risk assessment,risk management,risk assessment prediction method,back-propagation algorithm,feedforward neural networks,electronic commerce,efficient prediction method,new neural-based market prediction,identical data,cognition,learning artificial intelligence,profitability,classification algorithms,cost function,feed forward neural network,artificial neural networks,bayesian methods,back propagation
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