A GA-BP neural network for nonlinear time-series forecasting and its application in cigarette sales forecast-Reference-Cited by-同舟云学术

A GA-BP neural network for nonlinear time-series forecasting and its application in cigarette sales forecast

Published:2022-01-01 Issue:1 Volume:11 Page:223-231
ISSN:2192-8029
Container-title:Nonlinear Engineering
language:en
Short-container-title:

Author:

Sun Zheng¹,Li XiNa¹,Zhang HongTao¹,Ikbal Mohammad Asif²,Farooqi Ataur Rahman³

Affiliation:

1. Information center, China Tobacco Henan Industrial Co., Ltd , Zhengzhou , Henan, 450000 , China

2. School of Electrical and Electronics Engineering, Lovely Professional University , Phagwara , Punjab , India

3. Department of Business Administration, College of Applied Sciences UTAS Nizwa , Nizwa , Oman

Abstract

Abstract Neural network modeling for nonlinear time series predicts modeling speed and computational complexity. An improved method for dynamic modeling and prediction of neural networks is proposed. Simulations of the nonlinear time series are performed, and the idea and theory of optimizing the initial weights and threshold of the GA algorithm are discussed in detail. It has been proved that the use of GA-BP neural network in cigarette sales forecast is 80% higher than before, and this method has higher accuracy and accuracy than the gray system method.

Publisher

Walter de Gruyter GmbH

Subject

Computer Networks and Communications,General Engineering,Modeling and Simulation,General Chemical Engineering

Link

https://www.degruyter.com/document/doi/10.1515/nleng-2022-0025/pdf

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