Traffic flow prediction model based on improved variational mode decomposition and error correction

Li, Guohui; Deng, Haonan; Yang, Huirong

doi:10.1016/j.aej.2023.06.008

Cited by 20 publications

(1 citation statement)

References 53 publications

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“…There are many existing studies on the recognition and processing of acoustic sensor signals, such as wavelet transform [15][16][17], support vector machine [18], and particle swarm optimization [19]. In [19], Jiang et al employed the wavelet transform filtering technique to process the output signal from acoustic sensors.…”

Section: Related Workmentioning

confidence: 99%

An Acoustic Array Sensor Signal Recognition Algorithm for Low-Altitude Targets Using Multiple Five-Element Acoustic Positioning Systems with VMD

Song,

2024

Applied Sciences

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To solve the problem in target acoustic signal processing and recognition when the target flies at a low altitude based on the acoustic positioning system, which is often affected by external interference and brings false information, this paper proposes a target signal processing and recognition algorithm for low-altitude target acoustic positioning based on variational modal decomposition and the test method of multiple five-element acoustic arrays. This algorithm uses VMD to decompose the target signal into modal components with different central frequencies and then performs wavelet threshold processing on the low-frequency part of the signal. After determining the remaining signal components and the low-frequency part’s threshold, the residual component is reconstructed. Based on the test principle and calculation model of the five-element acoustic positioning system, following processing of the low-altitude target acoustic positioning signal using variational modal decomposition, the cross-correlation function method is introduced to perform correlation operations on the basic array of five acoustic sensors and then obtain the time value and time difference of the target acoustic information in each acoustic sensor, ultimately determining the spatial position of the target. Finally, we used the data fusion processing method for target coordinates in multi-acoustic basic arrays to determine the actual target position. By comparing the results obtained using the high-speed camera method with those of the proposed approach, it was found that the average error in the test area of 100 × 100 m was less than 1 m.

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Section: Related Workmentioning

confidence: 99%

An Acoustic Array Sensor Signal Recognition Algorithm for Low-Altitude Targets Using Multiple Five-Element Acoustic Positioning Systems with VMD

Song,

2024

Applied Sciences

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A variable‐speed‐condition fault diagnosis method for crankshaft bearing in the RV reducer with WSO‐VMD and ResNet‐SWIN

Qiu,

Nie,

Peng

et al. 2024

Quality & Reliability Eng

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Due to the noise interference and the weak characterization ability of the fault vibration signal of rotation vector (RV) reducer crankshaft bearing, it is difficult to obtain satisfactory results for the available fault diagnosis methods. For that, this paper proposes a variable‐speed‐condition fault diagnosis method with WSO‐VMD and ResNet‐SWIN. A signal reconstruction method with WSO‐VMD was carried out, Firstly, the performance of VMD algorithm is improved by using war strategy optimization algorithm to select parameters adaptively. Then the signal is reconstructed considering the fault characteristic frequency, so as to realize the noise reduction of the signal. By using the residual network module and attention mechanism to replace the first stage of the original SWIN model, a novel ResNet‐SWIN fault diagnosis model is established to enhance the feature extraction ability for the weak signal. The experiments with the constant‐operating‐condition and the variable‐operating‐condition are carried out to verify the effectiveness of the proposed method. The results show that, whether at variable‐speed or constant‐speed conditions, WSO algorithm has been proven to be the fastest convergence speed compared with WOA, SSA, and NGO optimization algorithms, and by the signal reconstruction with WSO‐VMD, the variance evaluation indicator of the reconstructed signal has 36%, 21%, 46%, and 40%, respectively. ResNet‐SWIN model has achieved the optimal diagnosis accuracy compared with SWIN, VIT, and CNN‐SVM models in both variable‐speed and constant‐speed conditions.

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A novel hybrid model for air quality prediction via dimension reduction and error correction techniques

Huang,

Hu,

Chen

2024

Environ Monit Assess

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Traffic flow prediction model based on improved variational mode decomposition and error correction

Cited by 20 publications

References 53 publications

An Acoustic Array Sensor Signal Recognition Algorithm for Low-Altitude Targets Using Multiple Five-Element Acoustic Positioning Systems with VMD

An Acoustic Array Sensor Signal Recognition Algorithm for Low-Altitude Targets Using Multiple Five-Element Acoustic Positioning Systems with VMD

A variable‐speed‐condition fault diagnosis method for crankshaft bearing in the RV reducer with WSO‐VMD and ResNet‐SWIN

A novel hybrid model for air quality prediction via dimension reduction and error correction techniques

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