Ship motion attitude prediction method based on GRU optimized by sparrow search algorithm
A search algorithm and ship motion technology, applied in the field of ship motion attitude, can solve the problems of algorithm prediction accuracy increase, weight optimization, etc., and achieve the effects of improved prediction accuracy and efficiency, strong fitting ability, and good generalization ability
Pending Publication Date: 2021-08-10
JIANGSU UNIV OF SCI & TECH
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However, this algorithm does not optimize the weights, and the prediction accuracy of the algorithm still has a lot of room for improvement.
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[0044] Below in conjunction with accompanying drawing and specific embodiment, further illustrate the present invention, should be understood that these embodiments are only for illustrating the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various aspects of the present invention Modifications in equivalent forms all fall within the scope defined by the appended claims of this application.
[0045] The present invention provides a kind of prediction method based on the GRU of the GRU optimized by the sparrow search algorithm, such as figure 1 As shown, it includes the following steps:
[0046] S1: Collect historical data (rolling, pitching, heave) of the ship's motion attitude, normalize the collected data, and obtain the processed modeling data, which is used for training sample data sets:
[0047]
[0048] Among them, x is the collected data, x' is the...
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The invention discloses a sparrow search algorithm optimized GRU-based ship motion attitude prediction method, which comprises the following steps of collecting historical data of a ship motion attitude, and performing normalization processing on the collected data to obtain processed modeling data; initializing parameters of a sparrow search algorithm and a structure of a GRU network; searching an optimal parameter through a sparrow search algorithm; assigning a connection weight of the GRU network by using the obtained optimal parameter, and training a GRU network prediction model by using modeling data; and according to the monitored ship motion attitude data, predicting the ship motion attitude by using the trained GRU network prediction model. By introducing the sparrow search algorithm, a prediction model which is more accurate and better in adaptability is established, the fitting capability is high, the generalization capability is good, the prediction result is more excellent, the prediction precision and efficiency of the ship motion attitude are improved, and thus the high-precision and high-efficiency ship motion attitude prediction is realized.
Description
technical field [0001] The invention belongs to the field of ship motion attitude, relates to a prediction technology of ship motion attitude, in particular to a prediction method of ship motion attitude based on a GRU optimized by a sparrow search algorithm. [0002] It involves the use of gated recurrent neural network to realize the prediction of ship motion attitude. The invention is applicable to the prediction of various equipment attitudes related to six degrees of freedom. Background technique [0003] my country is a big ocean country, and the development of sea resources is gradually stepping up to a new level. In the actual marine environment, due to the effects of environmental factors such as ocean wind, waves, and currents, swaying motions with six degrees of freedom will continue to occur. pose a serious threat. At the same time, the safety of offshore operations cannot be effectively guaranteed, which is extremely unsafe for offshore operators. It is neces...
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IPC IPC(8): G06F3/027G06N3/00G06N3/04G06N3/08
CPCG06F3/027G06N3/006G06N3/08G06N3/045Y02T90/00
Inventor 左思雨张冰赵强周萌萌潘梦婷
Owner JIANGSU UNIV OF SCI & TECH