CN111626567A - Identification and calculation method for guaranteeing resource similarity - Google Patents
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Abstract
The invention belongs to the technical field of use and maintenance support, and relates to a support resource similarity identification and calculation method. The method for identifying and calculating the guaranteed resource similarity adopts a mode of fusing the Jaccard similarity coefficient and the vector space cosine similarity to calculate, commonly represents the guaranteed resource similarity of two devices by the common characteristic quantity represented by the Jaccard similarity coefficient and the common characteristic value represented by the cosine similarity, and carries out unified quantification operation. The computer rule for similarity of the abnormal security resources established by the invention is used for analyzing the similarity of the resources, intelligently identifying the security resources with different security tasks having the types and the similar key characteristics, and providing the merging suggestion of the similar resources.
Description
Technical Field
The invention belongs to the technical field of use and maintenance support, relates to a text data mining technology, and particularly relates to a support resource similarity identification and calculation method.
Background
At present, helicopter guarantee equipment still generally has the problems of multiple models, miscellaneous types, single function, large size and the like, is backward to helicopter equipment development on the whole, is contrary to the current guarantee concept of high strength, full territory and rapid deployment, and restricts the whole fighting capacity and the rapid maneuvering capacity of helicopter aviation soldier troops. Although the development requirements of "integration, generalization and miniaturization" (abbreviated as "three") of aviation support equipment are also provided, the generalization degree of support resources is low at present. For different guaranteed resources, when performing similarity calculation, the attributes of the resources themselves need to be considered, including: functional, weight, appearance geometry, etc., as well as the associated target subsystem/component for which it is intended, frequency of use, etc. Here we mainly discuss the data sparsity problem of the guaranteed resource similarity evaluation computation and the scalability problem caused thereby.
In the existing method for calculating similarity of guaranteed resources, there are mainly cosine similarity (cosine similarity), Pearson Correlation Coefficient (Pearson Correlation Coefficient), and Jaccard similarity Coefficient (Jaccard Correlation Coefficient).
The above method has the following problems:
1. cosine similarity uses a cosine value of an included angle between two vectors in a vector space as a measure for the difference between two individuals, the cosine similarity focuses more on the difference of the two vectors in the direction rather than on the good length of the distance, and in the calculation of the similarity of the security equipment, the cosine similarity distinguishes more differences from the direction and is insensitive to absolute numerical values;
2. the Pearson correlation coefficient is mainly used for finding a project set which is scored by two users together, then the correlation coefficient of the two vectors is calculated, and in the calculation of the similarity of the security equipment, the correlation coefficient is insensitive to absolute numerical values and only describes the variation trend of data;
3. the Jaccard similarity coefficient is mainly used for calculating the similarity between individuals with symbol measurement or Boolean value measurement, and because the characteristic attributes of the individuals are symbol measurement or Boolean value marks, the specific value of the difference cannot be measured, and only the result of 'whether the differences are the same' can be obtained.
Disclosure of Invention
The purpose of the invention is: the method for identifying and calculating the resource similarity is provided to solve the technical problem that the quantity and the numerical value of common characteristics cannot be considered simultaneously in the conventional single similarity calculation.
In order to solve the technical problem, the technical scheme of the invention is as follows:
a guaranteed resource similarity recognition and calculation method is characterized in that a mode of fusing a Jaccard similarity coefficient and a vector space cosine similarity is adopted for calculation, and the guaranteed resource similarity of two devices is represented by a common characteristic quantity represented by the Jaccard similarity coefficient and a common characteristic numerical value represented by the cosine similarity.
The method for identifying and calculating the similarity of the guaranteed resources further comprises the operation of uniformly quantizing the number of the common characteristics and the common characteristic value.
The method for identifying and calculating the similarity of the guarantee resources adopts the following fusion similarity formula:
in the formula, the similarity between the X equipment and the Y equipment is determined by two parts, namely the measurement of the quantity of the common characteristics represented by Jaccard, and the similarity of the common characteristic value represented by cosine cos. The similarity calculation is carried out by fusing the Jaccard and the cosine, the number and the numerical value of the common characteristics can be considered at the same time, the unified quantification is carried out, meanwhile, the Jaccard formula is regarded as the weight, the similarity attenuation can be considered to be carried out according to the number of the common characteristics, and under the condition of sparse data, the more accurate similarity of the special-shaped equipment characteristics can be obtained.
The method for identifying and calculating the similarity of the guarantee resources comprises the following steps:
step one, sorting all the guarantee resource feature vectors;
step two, calculating the value of each element of the similarity matrix by using the fusion similarity formula;
thirdly, based on threshold judgment, carrying out similarity analysis on the guaranteed resources;
preferably, the method for identifying and calculating the similarity of the safeguard resources further comprises the step of giving a resource merging suggestion according to the similarity.
Preferably, the guaranteed resource characteristics include weight, output power, number of users, and frequency of use.
Preferably, the similarity matrix is corrected in combination with the characteristics of the two devices in the value judgment.
The invention has the beneficial effects that: the similarity calculation method fusing the Jaccard and the cosine firstly provides a helicopter guarantee resource similarity recognition method for recognizing the similarity of each attribute of an abnormal guarantee resource and provides input for subsequent guarantee resource optimization. Due to the limitations of the guaranteed space and other conditions, the carrying of guaranteed resources for helicopter equipment is very limited. Therefore, the universal research on the guarantee resources is developed, the types and the number of the carried guarantee resources are reduced, and the method has very important significance for improving the guarantee efficiency of the helicopter. The computer rule for similarity of the abnormal security resources established by the invention is used for analyzing the similarity of the resources, intelligently identifying the security resources with different security tasks having the types and the similar key characteristics, and providing the merging suggestion of the similar resources.
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In order to more clearly illustrate the technical solution of the present invention, the drawings used in the embodiment of the present invention will be briefly explained. It is obvious that the drawings described below are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be obtained from these drawings without inventive effort.
FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Features of various aspects of embodiments of the invention will be described in detail below. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced without these specific details. The following description of the embodiments is merely intended to better understand the present invention by illustrating examples thereof. The present invention is not limited to any particular arrangement or method provided below, but rather covers all product structures, any modifications, alterations, etc. of the method covered without departing from the spirit of the invention.
In the drawings and the following description, well-known structures and techniques are not shown to avoid unnecessarily obscuring the present invention.
Aiming at the similarity identification and calculation method of the guarantee resource, which is disclosed by the invention, a similarity calculation method of Jaccard and cosine is fused, a similarity identification method of the guarantee resource of the helicopter is provided to identify the similarity of each attribute of the special-shaped guarantee resource, and the similarity is analyzed by taking a related guarantee tool of an electrical system of the helicopter as an example. According to the step flow chart shown in fig. 1, the specific steps are as follows:
firstly, determining equipment guarantee resources, and sorting guarantee resource feature vectors;
selecting a typical tool, 5 tool resources of a power supply vehicle, a universal meter, an electric brush extractor, a motor electric brush measuring tool and a storage battery charging and discharging station, and paying attention to several frequently used attributes of the tool in the selection of characteristics: weight, volume, function, frequency of use. And selecting equipment guarantee resource characteristics, expressing the characteristics in a vectorization manner, and calculating the value of each element of the similarity matrix by using the fusion similarity formula.
Step two, calculating the value of each element of the similarity matrix by using the fusion similarity formula;
5 tool resources of a power supply vehicle, a universal meter, a brush extractor, a motor brush measuring tool and a storage battery charging and discharging station are represented by T1, T2, T3, T4 and T5 respectively, each vector is composed of 4 dimensions and represents weight, output power, number of users and frequency (average daily use times). The method comprises the following specific steps:
T2＝{1，0.01，1，1}；
T5＝{1000，220，4，8}；
calculating by adopting the fused Jaccard cosine similarity to obtain a similarity matrix among 5 resources, wherein the similarity matrix is as follows:
thirdly, based on threshold judgment, carrying out similarity analysis on the guaranteed resources;
from the similarity matrix analysis, the highest similarity is that T3 and T4 reach 0.998. It is worth noting that the similarity between T1 and T5 is high according to the calculation of a common cosine formula, but through introducing Jaccard to carry out similarity correction, the quantity of similar guarantee characteristics is comprehensively considered, the similarity is punished, the similarity is more practical, and similar situations also exist between T2 and T3 and T4. In the similarity matrix, features for a certain dimension may be close, but actually may have two different features, such as electronic and mechanical, and the correction needs to be performed manually through a threshold.
Step four, providing a resource generalization suggestion according to the similarity
The highest similarity is that T3 and T4 reach 0.998, and the generalized merging is recommended.
The foregoing is merely a detailed description of the embodiments of the present invention, and some of the conventional techniques are not detailed. The scope of the present invention is not limited thereto, and any changes or substitutions that can be easily made by those skilled in the art within the technical scope of the present invention will be covered by the scope of the present invention. The protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (8)
1. A method for identifying and calculating the similarity of guarantee resources is characterized by comprising the following steps: the method for identifying and calculating the guaranteed resource similarity adopts a mode of fusing the Jaccard similarity coefficient and the vector space cosine similarity to calculate, and the guaranteed resource similarity of the two devices is represented by the common characteristic quantity represented by the Jaccard similarity coefficient and the common characteristic value represented by the cosine similarity.
2. The guaranteed resource similarity recognition computing method of claim 1, wherein: the method for identifying and calculating the similarity of the guaranteed resources further comprises the operation of uniformly quantizing the number of the common characteristics and the common characteristic value.
3. The guaranteed resource similarity recognition computing method of claim 2, wherein: the fusion similarity of the equipment X and the equipment Y in the method for identifying and calculating the resource similarity adopts the following formula:
wherein X represents XXXX, Y represents XXXX, X vector represents XXX, YX vector represents XXX, | X | | represents XXX, and | Y | | represents XXX.
4. The guaranteed resource similarity recognition computing method of claim 3, wherein: the Jaccard formula in the fusion formula is a weight.
5. The guaranteed resource similarity recognition computing method of claim 1, wherein: the method for identifying and calculating the similarity of the guarantee resources comprises the following steps:
step one, sorting all the guarantee resource feature vectors;
step two, calculating the value of each element of the similarity matrix by using the fusion similarity formula;
and thirdly, performing similarity analysis on the guaranteed resources based on threshold judgment.
6. The guaranteed resource similarity recognition computing method of claim 5, wherein: the method for identifying and calculating the similarity of the guarantee resources further comprises the step of giving a resource merging suggestion according to the similarity.
7. The guaranteed resource similarity recognition computing method of claim 5, wherein: the guaranteed resource characteristics comprise weight, output power, number of users and use frequency.
8. The guaranteed resource similarity recognition computing method of claim 5, wherein: and correcting the similarity matrix by combining the characteristics of the two devices during value judgment.
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Cited By (2)
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| CN112464991A (en) * | 2020-11-04 | 2021-03-09 | 西北工业大学 | Multi-sensor evidence evolution game fusion recognition method based on multi-population dynamics |
| CN113552496A (en) * | 2021-06-29 | 2021-10-26 | 哈尔滨理工大学 | Voltage cosine similarity-based diagnosis method for short circuit fault in battery series module |
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Cited By (3)
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| CN112464991A (en) * | 2020-11-04 | 2021-03-09 | 西北工业大学 | Multi-sensor evidence evolution game fusion recognition method based on multi-population dynamics |
| CN113552496A (en) * | 2021-06-29 | 2021-10-26 | 哈尔滨理工大学 | Voltage cosine similarity-based diagnosis method for short circuit fault in battery series module |
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