In macro investment, an investment decision model is established by using an improved back propagation (BP) artificial neural network (ANN). In this paper, the relations between elements of investment and output of products are determined, and then the optimal distribution of investment is determined by adjusting the distributions rationally. This model can reflect the highly nonlinear mapping relations among each element of investment by using nonlinear utility functions to improve the architecture of artificial neural network, which can be widely applied in investment problems. ©2010 IEEE
This paper deals with the application of a well-known neural network technique, multilayer back-prop...
Stock is becoming a significant investment tools that contributes towards Malaysia economic growth. ...
by Lam King Wan.Thesis (M.B.A.)--Chinese University of Hong Kong, 1999.Includes bibliographical refe...
After production and operations, finance and investments are one of the most frequent areas of neura...
To determine the influence of the weight of the economic effectiveness evaluation criteria of the ma...
Based on systematic analysis of BP neural network, a back-propagation neural network predicting mode...
This paper explored the process of investment management in both theory and practice in China's mutu...
The present paper has the objective to inform the public regarding the use of new techniques for the...
Neural networks demonstrate great potential for discovering non-linear relationships in time-series ...
Artificial neural networks are a robust, effective complement to traditional statistical methods in ...
Machine language is a sequence of algorithm assign to do a particular task. Neural Networking is ins...
Tactical asset allocation (T AA) is an investment strategy that switches an investment among differe...
Model of neuro-expert system was developed. The main idea is to integrate both artificial intelligen...
In the last decade, neural networks have drawn noticeable attention from many computer and operation...
Neural networks (NN) architectures can be effectively used to classify, forecast and recognize quant...
This paper deals with the application of a well-known neural network technique, multilayer back-prop...
Stock is becoming a significant investment tools that contributes towards Malaysia economic growth. ...
by Lam King Wan.Thesis (M.B.A.)--Chinese University of Hong Kong, 1999.Includes bibliographical refe...
After production and operations, finance and investments are one of the most frequent areas of neura...
To determine the influence of the weight of the economic effectiveness evaluation criteria of the ma...
Based on systematic analysis of BP neural network, a back-propagation neural network predicting mode...
This paper explored the process of investment management in both theory and practice in China's mutu...
The present paper has the objective to inform the public regarding the use of new techniques for the...
Neural networks demonstrate great potential for discovering non-linear relationships in time-series ...
Artificial neural networks are a robust, effective complement to traditional statistical methods in ...
Machine language is a sequence of algorithm assign to do a particular task. Neural Networking is ins...
Tactical asset allocation (T AA) is an investment strategy that switches an investment among differe...
Model of neuro-expert system was developed. The main idea is to integrate both artificial intelligen...
In the last decade, neural networks have drawn noticeable attention from many computer and operation...
Neural networks (NN) architectures can be effectively used to classify, forecast and recognize quant...
This paper deals with the application of a well-known neural network technique, multilayer back-prop...
Stock is becoming a significant investment tools that contributes towards Malaysia economic growth. ...
by Lam King Wan.Thesis (M.B.A.)--Chinese University of Hong Kong, 1999.Includes bibliographical refe...