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Sea clutter optimal soft measuring instrument and method based on wavelet neural network optimized by fruit fly optimization algorithm

A technology of wavelet neural network and fruit fly optimization algorithm, applied in biological neural network models, design optimization/simulation, instruments, etc., can solve the problems of poor generalization performance, low sensitivity to noise, and low measurement accuracy

Inactive Publication Date: 2018-03-20
ZHEJIANG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In order to overcome the shortcomings of existing radars such as low measurement accuracy, low sensitivity to noise, and poor generalization performance, the present invention provides an on-line measurement, fast calculation speed, automatic model update, strong anti-noise ability, and good generalization performance. Drosophila optimization algorithm optimizes sea clutter optimal soft sensor instrument and method for wavelet neural network

Method used

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  • Sea clutter optimal soft measuring instrument and method based on wavelet neural network optimized by fruit fly optimization algorithm
  • Sea clutter optimal soft measuring instrument and method based on wavelet neural network optimized by fruit fly optimization algorithm
  • Sea clutter optimal soft measuring instrument and method based on wavelet neural network optimized by fruit fly optimization algorithm

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Embodiment 1

[0078] refer to figure 1 , figure 2 and image 3 , an optimal soft measurement instrument for sea clutter based on fruit fly optimization algorithm to optimize wavelet neural network, including radar 1, on-site intelligent instrument for measuring easily measurable variables 2, control station for measuring operating variables 3, storing data The on-site database 4 and the sea clutter soft measurement value display instrument 6, the on-site intelligent instrument 2, the control station 3 are connected to the radar 1, the on-site intelligent instrument 2, the control station 3 are connected to the on-site database 4, the soft sensor The instrument also includes the optimal soft sensor host computer 5 optimized by the fruit fly optimization algorithm to optimize the wavelet neural network, and the on-site database 4 is connected to the input end of the optimal soft sensor host computer 5 based on the fruit fly optimization algorithm optimized wavelet neural network, The outpu...

Embodiment 2

[0112] refer to figure 1 , figure 2 and image 3 , a sea clutter optimal soft sensor method based on the fruit fly optimization algorithm to optimize the wavelet neural network, the soft sensor method comprises the following steps:

[0113] 1) For the radar object, according to the process analysis and operation analysis, select the operational variables and easily measurable variables as the input of the model, and the operational variables and easily measurable variables are obtained from the on-site database;

[0114] 2) Preprocess the model training samples input from the on-site database, and centralize the training samples, that is, subtract the average value of the samples, and then standardize them so that the mean value is 0 and the variance is 1. This processing is accomplished using the following algorithmic procedure:

[0115] 2.1) Calculate the mean:

[0116] 2.2) Calculate the variance:

[0117] 2.3) Standardization:

[0118] Among them, TX is the tr...

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Abstract

The invention discloses a sea clutter optimal soft measuring instrument and method based on the wavelet neural network optimized by the fruit fly optimization algorithm. The instrument comprises a radar, an on-site intelligent instrument, a control station, an on-site database for storing data, an optimal soft measuring upper computer based on the wavelet neural network optimized by the fruit flyoptimization algorithm and a prediction soft measurement value displayer. The optimal soft measuring upper computer based on the wavelet neural network optimized by the fruit fly optimization algorithm comprises a data preprocessing module, a wavelet neural network module and a model update module. The invention realizes on-line optimal soft measuring of sea clutter, overcomes the random influencecaused by human factors, improves the stability of model prediction and reduces the possibility of model prediction falling into local optimization.

Description

technical field [0001] The invention relates to the field of optimal soft measuring instruments and methods, in particular to a sea clutter optimal soft measuring instrument and method based on fruit fly optimization algorithm to optimize wavelet neural network. Background technique [0002] In the radar field, the echo signal reflected from the seawater surface is called sea clutter, which is related to various factors such as sea conditions, wind tides, and radar parameters. For coastal warning radars, shipboard radars and other radars working in the marine environment, serious sea surface reflection echoes will affect the detection and tracking performance of sea surface targets. It is important to grasp the nature of sea clutter and establish an accurate sea clutter model. A prerequisite for analyzing and improving radar performance. The statistical properties of sea clutter include amplitude properties and correlation properties. Correlation properties of sea clutter ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06N3/00G06N3/02
CPCG06F30/20G06N3/006G06N3/02
Inventor 刘兴高王文川王志诚朱宇张泽银余渝生宋政吉张天键
Owner ZHEJIANG UNIV