Huizhou resident population, Guangdong resident population and elderly population forecast based on the NAR neural network Markov model

Huizhou resident population, Guangdong resident population and elderly population forecast based on the NAR neural network Markov model

We propose a nonlinear auto regressive neural network Markov model (NARMKM) to predict the annual Huizhou resident population, Guangdong resident population and elderly population in China, and improve the accuracy of population forecasting. The new model is built upon the traditional neural network...

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Bibliographic Details
Main Authors: Dewang Li, Meilan Qiu, Zhongliang Luo
Format: Article
Language:English
Published: AIMS Press 2024-01-01
Series:AIMS Mathematics
Subjects:
nar
neural network
fractional grey models
machine learning
parameter estimation and prediction
stochastic markov process
time series
Online Access:https://aimspress.com/article/doi/10.3934/math.2024157?viewType=HTML

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https://aimspress.com/article/doi/10.3934/math.2024157?viewType=HTML

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