Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/68014
Title: Stock trading using RBF neural networks
Authors: Hu, Donglin
Keywords: DRNTU::Engineering
Issue Date: 2016
Abstract: Stock market comprises of complex sample of data in time series. It has unique characteristics like non-linearity, high noise and uncertainties. In order to gain profit, prediction of stock price becomes a hot topic all the time. According to the characteristics of financial time series, BP neural network prediction model with the minimum standard of empirical risk has poor generalization ability, which easy to fall into the optimal and disadvantages of local presence, we come up with RBF neural network.
URI: http://hdl.handle.net/10356/68014
Schools: School of Electrical and Electronic Engineering 
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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