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Sea clutter optimal soft-sensor instrument and method based on wavelet neural network optimized by adaptive mutation fruit fly optimization algorithm

A technology of wavelet neural network and fruit fly optimization algorithm, which is applied in the direction of radio wave measurement systems and instruments, can solve the problems of poor promotion performance, low measurement accuracy, and low sensitivity to noise

Inactive Publication Date: 2018-04-20
ZHEJIANG UNIV
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  • Abstract
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  • Application Information

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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. Adaptive Mutation Drosophila Optimization Algorithm Optimizing Wavelet Neural Network Sea Clutter Optimal Soft Sensing Instrument and Method

Method used

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  • Sea clutter optimal soft-sensor instrument and method based on wavelet neural network optimized by adaptive mutation fruit fly optimization algorithm
  • Sea clutter optimal soft-sensor instrument and method based on wavelet neural network optimized by adaptive mutation fruit fly optimization algorithm
  • Sea clutter optimal soft-sensor instrument and method based on wavelet neural network optimized by adaptive mutation fruit fly optimization algorithm

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Embodiment 1

[0101] refer to figure 1 , figure 2 and image 3 , an optimal soft-sensing instrument for sea clutter based on adaptive mutation fruit fly optimization algorithm to optimize wavelet neural network, including radar 1, on-site intelligent instrument 2 for measuring easy-to-measure variables, and control station 3 for measuring manipulated variables , the on-site database 4 for storing data and the sea clutter soft measurement value display instrument 6, the on-site intelligent instrument 2, the control station 3 are connected with the radar 1, and the on-site intelligent instrument 2, the control station 3 are connected with the on-site database 4, so The soft sensor instrument also includes an optimal soft sensor host computer 5 for optimizing the wavelet neural network by an adaptive variation fruit fly optimization algorithm, and the on-site database 4 is connected with the optimal software for optimizing the wavelet neural network based on the adaptive variation fruit fly ...

Embodiment 2

[0146] refer to figure 1 , figure 2 and image 3 , a sea clutter optimal soft sensor method based on adaptive variation fruit fly optimization algorithm to optimize wavelet neural network, said soft sensor method comprising the following steps:

[0147] 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;

[0148] 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:

[0149] 2.1) Calculate the mean:

[0150] 2.2) Calculate the variance:

[0151] 2.3) Standardization:

[0152] Among them, T...

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Abstract

The invention discloses a sea clutter optimal soft-sensing instrument and method based on a wavelet neural network optimized by an adaptive mutation fruit fly optimization algorithm. The sea clutter optimal soft-sensing instrument comprises a radar, an on-site intelligent instrument, a control station, an on-site database for storing data, an optimal soft-sensing upper computer based on an improved wavelet neural network optimized by the fruit fly optimization algorithm, and a forecasting soft-sensing value display instrument. The on-site intelligent instrument is connected with the control station and the radar and connected with the on-site database. The optimal soft-sensing upper computer is connected with the on-site database and the soft-sensing valve display instrument. The optimal soft-sensing upper computer based on the wavelet neural network optimized by the adaptive mutation fruit fly optimization algorithm includes a data preprocessing module, a wavelet neural network moduleand a model updating module. According to the invention, the on-line optimal soft-sensing of the sea clutter is realized, the random effect caused by human factors is overcome, the stability of the model forecasting is improved, and the probability that the model forecasting falls into a local optimum is reduced.

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 an adaptive variation fruit fly optimization algorithm to optimize wavelet neural networks. 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 pro...

Claims

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Application Information

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IPC IPC(8): G01S7/41
CPCG01S7/417
Inventor 刘兴高王文川
Owner ZHEJIANG UNIV
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