BP neural network recognition algorithm for scour monitoring of subsea pipelines based on active thermometry

Zhao, Xuefeng; Ba, Qin; Zhou, Lei; Li, Weijie; Ou, Jinping

doi:10.1016/j.ijleo.2014.06.018

Cited by 16 publications

(10 citation statements)

References 5 publications

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“…Conventional artificial neural network algorithms such as the BP [11], RBF [12] and Support Vector Machine (SVM) [13] developed in recent years have optimized network structure through new algorithms to improve the final calibration precision. Through these attempts, the ultimate accuracy and speed of the calibration algorithm is greatly improved.…”

Section: The Structure Of Annmentioning

confidence: 99%

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Development of a calibrating algorithm for Delta Robot’s visual positioning based on artificial neural network

Ding

Tang

et al. 2016

Optik

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Section: The Structure Of Annmentioning

confidence: 99%

“…The transformational projection matrix between the image coordinate system and robot coordinate system is as shown in the following formula: 11 12 13 …”

mentioning

confidence: 99%

Development of a calibrating algorithm for Delta Robot’s visual positioning based on artificial neural network

Ding

Tang

et al. 2016

Optik

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“…BPNN is a commonly used method to carry out forecasting; however, it still has some limitations, such as the determination of weight and threshold value, which could have a large influence on the accuracy of forecasting [34]. Therefore, this paper applies MFA to optimize the weight and threshold values of BPNN to reduce the forecasting errors.…”

Section: Hybrid E-mfa-bp Modelmentioning

confidence: 99%

A New Hybrid Model Based on Data Preprocessing and an Intelligent Optimization Algorithm for Electrical Power System Forecasting

Jiang

Liu

2015

Mathematical Problems in Engineering

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The establishment of electrical power system cannot only benefit the reasonable distribution and management in energy resources, but also satisfy the increasing demand for electricity. The electrical power system construction is often a pivotal part in the national and regional economic development plan. This paper constructs a hybrid model, known as the E-MFA-BP model, that can forecast indices in the electrical power system, including wind speed, electrical load, and electricity price. Firstly, the ensemble empirical mode decomposition can be applied to eliminate the noise of original time series data. After data preprocessing, the back propagation neural network model is applied to carry out the forecasting. Owing to the instability of its structure, the modified firefly algorithm is employed to optimize the weight and threshold values of back propagation to obtain a hybrid model with higher forecasting quality. Three experiments are carried out to verify the effectiveness of the model. Through comparison with other traditional well-known forecasting models, and models optimized by other optimization algorithms, the experimental results demonstrate that the hybrid model has the best forecasting performance.

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“…Furthermore, a BP neural network recognition algorithm was introduced by X.F. Zhao [26] which was used to monitor scour which is based on the heating transfer properties between the sand bed and the sediment. It can be used in detecting free span movement under pipelines.…”

Section: Reviewmentioning

confidence: 99%

Literature review of research on scour propagation below the submarine pipeline

Zhang¹,

Shi²,

Baruch³

2015

Proceedings of the 5th International Conference on Civil Engineering and Transportation 2015

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The scour process is closely related to the damage and failure of pipelines, so the study of the flow field around pipelines and the sediment transport below pipelines is especially important. Furthermore, the effects of scour propagation below submarine pipelines especially around span shoulders have significant meaning for the study of hydraulics and sediment transport in the ocean. In this paper, investigations in this area are considered and summarized with respect to the different methods of studying the mechanisms: experiment and numerical simulation. The main achievements are presented and compared. The majority of these achievements were derived from experiments because of the lack of a precise theory of sediment transport below pipelines and the difficulties of generating numerical simulations. The different devices used to monitor the scour process are discussed in this paper, and a new way of measuring the scour process is proposed which can be used in laboratory experiments.

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BP neural network recognition algorithm for scour monitoring of subsea pipelines based on active thermometry

Cited by 16 publications

References 5 publications

Development of a calibrating algorithm for Delta Robot’s visual positioning based on artificial neural network

Development of a calibrating algorithm for Delta Robot’s visual positioning based on artificial neural network

A New Hybrid Model Based on Data Preprocessing and an Intelligent Optimization Algorithm for Electrical Power System Forecasting

Literature review of research on scour propagation below the submarine pipeline

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