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Dormitory electric apparatus type determination device

A technology for judging devices and electrical appliances, applied in measuring devices, instruments, measuring electricity and other directions, can solve the problems of single judgment means, inability to completely accurately judge, single characteristic properties, etc., and achieve simple acquisition methods, generalization ability and accurate judgment. The effect of high rate and rich feature information

Inactive Publication Date: 2016-08-24
HUNAN UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Various methods can realize the judgment of the nature of the electrical load to a certain extent, but due to the single characteristic and single judgment method, there are generally problems of insufficient generalization ability and incomplete and accurate judgment.

Method used

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  • Dormitory electric apparatus type determination device
  • Dormitory electric apparatus type determination device
  • Dormitory electric apparatus type determination device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 2

[0076] Example 2 selects the NBC classifier as the auxiliary classifier. Naive Bayes classification is defined as follows:

[0077] ⑴ Let x={a 1 ,a 2 ,...,a m} is an item to be classified, and each a is a characteristic attribute of x;

[0078] ⑵There is a category set C={y 1 ,y 2 ,...,y n};

[0079] (3) Calculate P(y 1 |x),P(y 2 |x),...,P(y n |x);

[0080] ⑷If P(y k |x)=max{P(y 1 |x),P(y 2 |x),...,P(y n |x)}, then x∈y k .

[0081] The specific method of calculating each conditional probability in step (3) is:

[0082] ① Find a set of items to be classified with known classification as the training sample set;

[0083] ②Statistically obtain the conditional probability estimates of each feature attribute under each category;

[0084] P(a 1 |y 1 ),P(a 2 |y 1 ),…,P(a m |y 1 );

[0085] P(a 1 |y 2 ),P(a 2 |y 2 ),…,P(a m |y 2 );

[0086] ...;

[0087] P(a 1 |y n ),P(a 2 |y n ),…,P(a m |y n ).

[0088] ③According to Bayes' theorem, there are:...

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PUM

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Abstract

A dormitory electric apparatus type determination device comprises an information acquisition module, an information processing module and a communication device, is abundant in characteristic information by simultaneously adopting the electric appliance starting current characteristics containing a starting impulse current, a starting average current and a starting current impulse and the load current frequency spectrum characteristics of the electric appliances as the identification characteristics, and is high in accuracy by adopting a combined classifier containing a decision tree classifier and a Bayes classifier to identify, determine and classify, and simultaneously considering the characteristics of the decision tree classifier and the Bayes classifier to identify and determine comprehensively. The provided starting current characteristic and load current frequency spectrum characteristic obtaining methods are simple and reliable. The dormitory electric apparatus type determination device can be used at some collective public places needing to carry out the power consumption electric appliance management, such as the dormitories, etc., and also can be used at other occasions needing to carry out the electric appliance type identification and statistics and the power consumption equipment management.

Description

technical field [0001] The invention relates to a device for judging and classifying equipment, in particular to a device for judging the type of electric appliances used in student dormitories. Background technique [0002] At present, the mainstream methods for judging the properties of electrical appliances include the electrical load judging method based on the load power comprehensive coefficient algorithm, the electrical load judging method based on electromagnetic induction, the electrical load judging method based on neural network algorithm, and the electrical load judging method based on periodic discrete transform algorithm Judgment method, etc. Various methods can realize the judgment of the nature of electrical load to a certain extent, but due to the single characteristic and single judgment method, there are generally problems of insufficient generalization ability and incomplete and accurate judgment. Contents of the invention [0003] The object of the pr...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/00
CPCG01R31/00
Inventor 凌云郭艳杰孔玲爽聂辉
Owner HUNAN UNIV OF TECH
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