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Tide Time Forecasting Method of Qiantang River Based on Support Vector Machine

A support vector machine and tide time technology, applied in the field of measurement and control, can solve problems such as unsatisfactory forecast accuracy, and achieve the effects of easy programming, high generalization ability, and easy mastery

Active Publication Date: 2021-02-09
HANGZHOU DIANZI UNIV
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  • Abstract
  • Description
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  • Application Information

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Problems solved by technology

The main disadvantage of this type of method is that it is affected by natural factors such as river topography, tidal flow velocity, wind direction and size, and upstream floods on the day of the forecast, which makes the forecast accuracy not ideal

Method used

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  • Tide Time Forecasting Method of Qiantang River Based on Support Vector Machine
  • Tide Time Forecasting Method of Qiantang River Based on Support Vector Machine
  • Tide Time Forecasting Method of Qiantang River Based on Support Vector Machine

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Embodiment Construction

[0035] The method of the present invention will be further described below in conjunction with the accompanying drawings.

[0036] Such as figure 1 As shown, it is a flow chart of the Qiantang River tide time forecast method based on support vector machine, and the specific implementation steps are as follows:

[0037] Step 1: Read the historical tidal surge arrival time t d (n), the previous high tide level of the corresponding site and Wenjiayan g(n-1), g w (n-1), calculate the time difference data dt(n) of the next day based on the arrival time of the tide in two consecutive days, in minutes,

[0038] dt(n)=t d (n+1)-t d (n) n=1,2,3,... (1)

[0039] Step 2: Normalize the historical high tide level data and the time difference data of two consecutive days every other day

[0040] According to formula (2), the historical high tide level data is normalized,

[0041]

[0042] where x max is the maximum value in historical high tide level data, x min It is the minimu...

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Abstract

The invention discloses a method for forecasting tide time of the Qiantang River based on a support vector machine. The specific steps of the invention are: reading the historical tide arrival time and high tide level data, and calculating the time difference of the next day; The data is normalized; according to the forecast date, the data under the same conditions are selected from the historical data to construct the training samples; the training samples are used to train the support vector machine model; the support vector machine model is combined with the input parameters to obtain the forecast data. The invention is a Qiantang River tidal time forecasting method with strong generalization ability and high calculation efficiency. The prediction reliability is higher than that of the traditional method. The whole analysis process is fast and convenient, and is easy to be mastered by users.

Description

technical field [0001] The invention belongs to the technical field of measurement and control, in particular to a method for forecasting tide time of the Qiantang River based on a support vector machine. Background technique [0002] When the East China Sea tide enters Hangzhou Bay, the estuary suddenly narrows from the width, which promotes the sudden rise of the water level, forming an obvious tide head, and as the tide continues to pour in, it finally forms a magnificent tide with turbulent waves and galloping horses. The wonder is the tidal surge of Qiantang River, which is well-known both at home and abroad. With the rapid economic development of the Qiantang River Basin, the number of foreign tourists and residents has increased year by year. In order to ensure the safety of residents along the river, the safety of ships and coastal engineering facilities, accurate tide forecasting has attracted more and more attention. [0003] In practical application, the tidal su...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06K9/62
CPCG06Q10/04G06F18/2411
Inventor 章国稳孙映宏姬战生邱超李留东王英英胡其美汪华平车弘书
Owner HANGZHOU DIANZI UNIV
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