Grey theory–based BP-NN co-training for dense sequence long-term tendency prediction

Hong, Yuling; Yang, Yingjie; Qishan, Zhang

doi:10.1108/gs-02-2020-0024

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…Based on the imperfect backpropagation method, a layered feed-forward neural network is known as a BP neural network training [22]. It uses a linear arrangement of nonlinear kernel function to perform nonlinear translation from input to output space, and approximate arbitrary nonlinear mapping through training, and it has a better processing ability for nonlinear time series predicting problems.…”

Section: Bp Neural Networkmentioning

confidence: 99%

A Combined Prediction Model Composed of the GM (1,1) Model and the BP Neural Network for Major Road Traffic Accidents in China

Qing-wen

Guo

Wang

et al. 2022

Mathematical Problems in Engineering

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This paper compared the expected accuracy of the gray GM (1, 1) model and the combined GMBP model using a data set for major road traffic accidents. A combined GMBP prediction model composed of the very first parameter gray model GM (1, 1) is able to make exact predictions for forecasting dreary type of processes, and BP (back-propagation) neural network for a major traffic accident is proposed to overcome the limitations of a single prediction model for a major traffic accident. The method first obtains predicted data using the gray GM (1, 1) model, then trains the BP neural network using the GM (1, 1) model’s predicted data and the original data as input and output data, respectively, and finally the trained BP neural network can be considered a combined GMBP prediction model. The predicted data of the digit of major traffic accidents, the digit of fatalities, and the digit of damages from 2008 to 2020 were obtained using the combined GMBP prediction model, and it is compared with the expected data of the single gray GM (1, 1) model. The grades showed that the exactitude of the combined GMBP prediction model was significantly higher than that of the single gray GM (1, 1) model. Finally, from 2021 to 2033, the combined GMBP prediction model is used to forecast the number of significant road traffic incidents, mortalities, and damages. The prediction results show that the number of accidents, faculties, and injuries is on the decline in the future years.

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Section: Bp Neural Networkmentioning

confidence: 99%

A Combined Prediction Model Composed of the GM (1,1) Model and the BP Neural Network for Major Road Traffic Accidents in China

Qing-wen

Guo

Wang

et al. 2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

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The application of a novel grey model in the prediction of China’s aging population

et al. 2023

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The dramatic increase of the aging population is a current and primary livelihood issue in China. It is very important to accurately predict the aging population for policy-makers such as governments and insurance companies. To explore the future development trend of China's aging population, a novel grey prediction FPTGM(1,1,α) model is established in this paper. The data from 2003 to 2012 are used to build the model, and the data from 2013 to 2018 are used to assess the modelling accuracy. The results show that the fitting and forecasting accuracy of the proposed FPTGM(1,1,α) model are higher than those of other models. This indicates that the novel grey model is more suitable for predicting the aging population in China. Combined with the idea of metabolism, the FPTGM(1,1,α) model is applied to predict China's aging population from 2019 to 2042. Finally, some reasonable suggestions for dealing with the aging population are put forward to the government and other decision-makers.

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Grey theory–based BP-NN co-training for dense sequence long-term tendency prediction

Cited by 2 publications

References 12 publications

A Combined Prediction Model Composed of the GM (1,1) Model and the BP Neural Network for Major Road Traffic Accidents in China

A Combined Prediction Model Composed of the GM (1,1) Model and the BP Neural Network for Major Road Traffic Accidents in China

The application of a novel grey model in the prediction of China’s aging population

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