Bayes classification-based method for fusing traditional meteorological data with perception data

A Bayesian classification and meteorological data technology, applied in data processing applications, electrical digital data processing, special data processing applications, etc., can solve problems such as increasing computational overhead, wasting useful frequent itemsets for classification, and achieving avoidance of probability The effects of inaccurate valuation, high classification accuracy, and improved computational efficiency

Inactive Publication Date: 2013-03-06
NANJING UNIV OF INFORMATION SCI & TECH
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Problems solved by technology

This model selection increases computational overhead and wastes many frequent itemsets that are useful for classification

Method used

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  • Bayes classification-based method for fusing traditional meteorological data with perception data
  • Bayes classification-based method for fusing traditional meteorological data with perception data

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Embodiment Construction

[0030] The technical solutions provided by the present invention will be described in detail below in conjunction with specific examples. It should be understood that the following specific embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention.

[0031] Such as figure 1 , figure 2 As shown, the traditional meteorological data provided by the present invention and the method for user participation perception data fusion specifically include the following steps:

[0032] Step 1, first preprocess the data: the data to be processed includes training samples and samples to be classified , the training samples are a large number of weather instance data, and the samples to be classified It is the current data that needs to be classified and judged.

[0033] The sample data to be classified includes traditional data information and perception data. For example, the temperature, wind speed, light and other...

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Abstract

The invention provides a Bayes classification-based method for fusing traditional meteorological data with perception data. On the basis of a Naive Bayes classifier, the invention discloses a One-Dependence Attribute Weighted Naive Bayes method, to improve a conventional Naive Bayes algorithm, appropriately release the limit that attributes need to be independent from each other, and find a compromising point between the efficiency and the classification efficiency, so as to accomplish the fusion of radar data with user perception data. The method comprises the following steps of: preprocessing the data; constructing the classifier according to training sample data; and classifying samples to be classified by using the constructed classifier.

Description

[0001] technical field [0002] The invention relates to the technical field of meteorological observation and early warning, in particular to a method for fusing traditional meteorological data and user participation perception data. [0003] Background technique [0004] Meteorological observation is a discipline that studies the methods and means of measuring and observing the physical and chemical properties of the earth's atmosphere and atmospheric phenomena. The observed objects mainly include the concentration of atmospheric gas components, aerosol, temperature, humidity, pressure, wind, atmospheric turbulence, evaporation, cloud, precipitation, radiation, atmospheric visibility, atmospheric electric field, atmospheric conductivity, and phenomena such as lightning, rainbow, halo, etc. parameter. The development of atmospheric detection technology provides conditions for reducing or avoiding losses caused by natural disasters. Meteorological observation records and ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q50/26G06F17/30
Inventor 杜景林孙晓燕周杰
Owner NANJING UNIV OF INFORMATION SCI & TECH
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