Evolving neural networks for Hang Seng stock index forecast

Yong LIU; Xin YAO

doi:10.1109/CEC.2001.934398

Evolving neural networks for Hang Seng stock index forecast

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Abstract

This paper describes an evolutionary neural network approach to Hang Seng stock index forecast. In this approach, a feedforward neural network is evolved using an evolutionary programming algorithm. Both the weights and architectures (i.e., connectivity of the network) are evolved in the same evolutionary process. The network may grow as well as shrink. The experimental results show that the evolutionary neural network approach can produce very compact neural networks with good prediction.

Original language	English
Title of host publication	Proceedings of the IEEE Conference on Evolutionary Computation, ICEC
Pages	256-260
Number of pages	5
Volume	1
DOIs	https://doi.org/10.1109/CEC.2001.934398
Publication status	Published - 2001
Externally published	Yes

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10.1109/CEC.2001.934398

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title = "Evolving neural networks for Hang Seng stock index forecast",

abstract = "This paper describes an evolutionary neural network approach to Hang Seng stock index forecast. In this approach, a feedforward neural network is evolved using an evolutionary programming algorithm. Both the weights and architectures (i.e., connectivity of the network) are evolved in the same evolutionary process. The network may grow as well as shrink. The experimental results show that the evolutionary neural network approach can produce very compact neural networks with good prediction.",

author = "Yong LIU and Xin YAO",

year = "2001",

doi = "10.1109/CEC.2001.934398",

language = "English",

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AU - YAO, Xin

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AB - This paper describes an evolutionary neural network approach to Hang Seng stock index forecast. In this approach, a feedforward neural network is evolved using an evolutionary programming algorithm. Both the weights and architectures (i.e., connectivity of the network) are evolved in the same evolutionary process. The network may grow as well as shrink. The experimental results show that the evolutionary neural network approach can produce very compact neural networks with good prediction.

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DO - 10.1109/CEC.2001.934398

M3 - Conference paper (refereed)

SN - 0780366573

VL - 1

SP - 256

EP - 260

BT - Proceedings of the IEEE Conference on Evolutionary Computation, ICEC

ER -

Evolving neural networks for Hang Seng stock index forecast

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