基于布谷鸟搜索优化的小波神经网络股票市场预测

2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS) Pub Date : 2017-11-01 DOI:10.1109/ICSESS.2017.8342977

Hua Zhi, Jinghua Zhang, Zhengbo Xue, Yan Zhang

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引用次数: 1

摘要

股票市场作为一个典型的非线性确定性动力系统，可以用小波神经网络进行预测。布谷鸟搜索是一种新型的启发式仿生群智能优化算法，可广泛应用于各种优化问题。本文采用布谷鸟搜索法对小波神经网络的初始参数进行优化。实验结果表明，优化后的CS-WNN在股市预测中比传统的WNN具有更高的预测精度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Stock market forecast based on wavelet neural network optimized by Cuckoo search

As a typical nonlinear deterministic dynamical system, stock market can be predicted by Wavelet Neural Network. Since Cuckoo Search is a new heuristic bionic group intelligent optimization algorithm, it can be widely used in various optimization problems. In this paper, we use Cuckoo Search (CS) to optimize the initial parameters of wavelet neural network. Results of the experiment show that the optimized CS-WNN has higher prediction accuracy than the traditional WNN in stock market forecast.

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2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)

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