Research and Analysis of Securities Market based on Multi-Fractal Generator

Zhu, Zhiliang; Song, Jingping; Dong, Aoshuang; Yu, Hai; Yang, Yuesuo

doi:10.1109/icycs.2008.520

Cited by 1 publication

(2 citation statements)

References 11 publications

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“…e self-similarity of fractal theory can achieve this process well, so the fractal theory can be used to predict the microscopic parameters. Because we have to judge whether the time series data have fractal characteristics, in this paper, we use R/S analysis to calculate Hurst index H [10].…”

Section: Fractal Analysis Of Microparametersmentioning

confidence: 99%

“…en, we construct a three-layer neural network and use the sigmoid function as the hidden layer function to select the optimal hidden layer number with the lowest error. e evaluation index of the predictable step estimation model is similar to that of the microparameter prediction model, which uses the average absolute percentage error MAPE, and the formula is shown in equation (10). e process of the predictable step number of the microscopic parameter is roughly divided into three steps.…”

Section: Predictable Step Estimation Model Of Microscopicmentioning

confidence: 99%

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Study on Fractal Multistep Forecast for the Prediction of Driving Behavior

Yang

Zhang

et al. 2020

Journal of Advanced Transportation

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The application and development of new technology make it possible to acquire real-time data of vehicles. Based on these real-time data, the behavior of vehicles can be analyzed. The prediction of vehicle behavior provides data support for the fine management of traffic. This paper proposes speed and acceleration have fractal features by R/S analysis of the time series data of speed and acceleration. Based on the characteristic analysis of microscopic parameters, the characteristic indexes of parameters are quantified, the fractal multistep prediction model of microparameters is established, and the BP (back propagation neural networks) model is established to estimate predictable step of fractal prediction model. The fractal multistep prediction model is used to predict speed acceleration in the predictable step. NGSIM trajectory data are used to test the multistep prediction model. The results show that the proposed fractal multistep prediction model can effectively realize the multistep prediction of vehicle speed.

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Section: Fractal Analysis Of Microparametersmentioning

confidence: 99%

Section: Predictable Step Estimation Model Of Microscopicmentioning

confidence: 99%