Passenger Travel Path Estimation Algorithm Based on High Accuracy Location Data

Author(s):  
Huali Xiao ◽  
Li Sun ◽  
Shaohong Kong ◽  
Guiwei Gong ◽  
Fan Zhang
2012 ◽  
Vol 195-196 ◽  
pp. 599-602
Author(s):  
Dong Ling Zhang ◽  
Lin Dong Ge

In this paper a high accuracy estimation algorithm of carrier frequency offset for MPSK signals in Gaussian white noise is proposed. Like the conventional practice, first the algorithm employs nonlinear processing to convert the MPSK signal to single sinusoidal signal, followed by windowed FFT, and then a method based on energy center correction is used to achieve accurate estimation. Simulation results have proved the feasibility,easiness of implementation, and the performance improvements in terms of accuracy and data length needed.


2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Yifan Tan ◽  
Haixu Liu ◽  
Yun Pu ◽  
Xuemei Wu ◽  
Yubo Jiao

As the passenger flow distribution center cooperating with various modes of transportation, the comprehensive passenger transport hub brings convenience to passengers. With the diversification of passenger travel modes, the passenger flow scale gradually increases, which brings significant challenges to the integrated passenger hub. Therefore, it is urgent to solve the problem of early warning and response to the future passenger flow to avoid congestion accidents. In this paper, the passenger flow GRNN prediction model is proposed, based on the K-means cluster algorithm, and an improved index named BWPs (Between-Within Proportion-Similarity) is proposed to improve the clustering effect of K-means so that the clustering effect of the new index is verified. In addition, the passenger flow data are studied and trained by combining with the GRNN neural network model based on parameter optimization (GA); the passenger flow prediction model is obtained. Finally, the passenger flow of Chengdu East Railway Station has been taken as an example, which is divided into 16 models, and each type of passenger flow is predicted, respectively. Compared with the traditional method, the results show that the model can predict the passenger flow with high accuracy.


2016 ◽  
Vol 45 (10) ◽  
pp. 1006004
Author(s):  
毕美华 BI Mei-hua ◽  
李洁炜 LI Jie-wei ◽  
杨国伟 YANG Guo-wei ◽  
曾然 ZENG Ran ◽  
李齐良 LI Qi-liang ◽  
...  

Author(s):  
K. İleri ◽  
A. Duru ◽  
İ. R. Karaş

Abstract. Alzheimer’s is a degenerative disease meaning that it gets worse with time. Memory loss, speaking problems, wandering, and getting lost are some of the signs of the disease. The risk of wandering results in high demand for extensive monitoring solutions for the patients suffering from the disease. Tracking solutions are crucial, especially for family members and caregivers, so researchers develop new wearable tracking devices to overcome missing patients. GPS technology can provide location data with high accuracy, but it is not sufficient to use only by itself. Thus, a more extensive solution should be provided. In this paper, a mobile wearable tracking device that can provide data to the mobile application through internet has been developed for patient tracking purposes.


Author(s):  
Sei Nagashima ◽  
Koichi Ito ◽  
Takafumi Aoki ◽  
Hideaki Ishii ◽  
Koji Kobayashi

2021 ◽  
pp. 126-131
Author(s):  
Oleg V. Chernoyarov ◽  
◽  
Vladimir A. Ivanov ◽  
Maksim I. Maksimov ◽  
Serguei Dachian

This paper examines estimating the frequency of the information signal based on the analysis of the probability characteristics of the phase fluctuations when a mix of signal and narrowband noise is observed. The new estimation algorithm is described while the shortcomings of the commonly applied methods are specified. The performance of the proposed approach is illustrated by a number of examples. In particular, it is demonstrated that the application of the introduced procedure allows high accuracy measurements of the carrier frequency of the non-modulated, the multilevel phase and quadrature keyed signals.


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