CN110082116B - Evaluation method and evaluation device for vehicle four-wheel positioning data and storage medium - Google Patents
Evaluation method and evaluation device for vehicle four-wheel positioning data and storage medium Download PDFInfo
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Abstract
The application discloses an evaluation method, an evaluation device and a storage medium for vehicle four-wheel positioning data, wherein the evaluation method comprises the following steps: acquiring a plurality of groups of four-wheel positioning sample data, wherein each group of four-wheel positioning sample data comprises at least two different attributes; converting the state of the attribute into a corresponding numerical value, wherein the state of the attribute comprises a first state and a second state, and the numerical value comprises a first numerical value and a second numerical value; calculating the probability that the state of each attribute is the first state according to the first numerical value and the second numerical value; obtaining the influence degree of each attribute according to the probability; obtaining evaluation attributes influencing the effectiveness of the multi-group four-wheel positioning sample data according to the influence degree; when a set of four-wheel positioning data is acquired, the effectiveness of the set of four-wheel positioning data is evaluated according to the evaluation attribute.
Description
Technical Field
The application relates to the technical field of vehicle state data validity evaluation, in particular to an evaluation method, an evaluation device and a storage medium for vehicle four-wheel positioning data.
Background
With the rapid development of economy in China and the continuous improvement of the living standard of people, an automobile as a travel vehicle becomes an important component in the life of people.
In order to provide better service for the life of people, the automobile needs to be inspected and maintained before leaving the factory and after running for a period of time. The four-wheel positioning of the automobile is a very important work in the automobile delivery or detection and maintenance links, the stable straight line driving and the convenient steering of the automobile can be kept through the four-wheel positioning, and the abrasion of tires and steering parts of the automobile in the driving process is reduced.
When the four-wheel alignment is carried out on the automobile, the four-wheel alignment attribute detected by the four-wheel alignment instrument is mainly utilized, namely the four-wheel alignment parameter, and the four-wheel alignment parameter at least comprises any one of a kingpin caster angle, a wheel camber angle, a kingpin inclination angle or a toe-in angle. And the technical expert comprehensively analyzes the acquired attribute parameters of the four-wheel positioning to judge whether the parameters of the four-wheel positioning belong to effective parameters.
At present, a certain degree of error exists when the validity of the four-wheel positioning parameters is classified manually, and therefore, how to evaluate and classify the validity of the four-wheel positioning parameters quickly and accurately is a technical problem to be solved urgently by those skilled in the art.
Disclosure of Invention
The application mainly aims to provide an evaluation method, an evaluation device and a storage medium for vehicle four-wheel positioning data, and aims to realize rapid evaluation and classification of the vehicle four-wheel positioning data.
In order to achieve the above object, the present application provides an evaluation method of vehicle four-wheel positioning data, the evaluation method including: acquiring a plurality of groups of four-wheel positioning sample data, wherein each group of four-wheel positioning sample data comprises at least two different attributes; converting the state of the attribute into a corresponding numerical value, wherein the state of the attribute comprises a first state and a second state, and the numerical value comprises a first numerical value and a second numerical value corresponding to the first state and the second state; calculating the probability that the state of each attribute is the first state according to the first numerical value and the second numerical value; obtaining the influence degree of each attribute according to the probability, wherein the influence degree is used for expressing the influence degree on the effectiveness of the multi-group four-wheel positioning sample data; obtaining evaluation attributes influencing the effectiveness of the multi-group four-wheel positioning sample data according to the influence degree; when a set of four-wheel positioning data is acquired, the effectiveness of the set of four-wheel positioning data is evaluated according to the evaluation attribute.
Preferably, said calculating the probability that each of said attributes is in the first state according to said first numerical value and said second numerical value comprises: calculating an information entropy value of each attribute by using an information entropy formula, wherein the size of the information entropy value is opposite to the probability that the attribute is in the first state; the information entropy formula is
Wherein i and n are positive integers, i is less than or equal to n, and H represents information entropy value，P(xi) Indicating a probability that the value is the first value or the second value.
Preferably, the evaluation attribute includes a first evaluation attribute, and the first evaluation attribute is an attribute having the largest influence.
Preferably, the evaluating the effectiveness of the set of four-wheel positioning data according to the evaluation attribute includes: judging whether the value corresponding to the first evaluation attribute is a first value or a second value; and if the value corresponding to the first evaluation attribute is a first value, judging that the group of four-wheel positioning data is valid four-wheel positioning data.
Preferably, the evaluation attribute further includes a second evaluation attribute that is an influence degree of which the influence degree is lower than that of the first evaluation attribute only.
Preferably, the evaluating the effectiveness of the set of four-wheel positioning data according to the evaluation attribute includes: judging whether the value corresponding to the first evaluation attribute is a first value or a second value; if the value corresponding to the first evaluation attribute is a first value, judging that the group of four-wheel positioning data is valid four-wheel positioning data; if the numerical value corresponding to the first evaluation attribute is a second numerical value, judging that the numerical value corresponding to the second evaluation attribute is a first numerical value or a second numerical value; if the value corresponding to the second evaluation attribute is the first value, judging that the group of four-wheel positioning data is valid four-wheel positioning data; and if the value corresponding to the second evaluation attribute is a second value, judging that the group of four-wheel positioning data is invalid four-wheel positioning data.
Preferably, the first value is 1 and the second value is 0.
In order to achieve the above object, the present application further provides an evaluation device, where the evaluation device includes a data acquisition module, configured to acquire multiple sets of four-wheel positioning sample data, where each set of four-wheel positioning sample data includes at least two different attributes; a state conversion module, configured to convert the state of the attribute into a corresponding numerical value, where the state of the attribute includes a first state and a second state, and the numerical value includes a first numerical value and a second numerical value corresponding to the first state and the second state; the probability calculation module is used for calculating the probability that the state of each attribute is the first state according to the first numerical value and the second numerical value; the influence degree obtaining module is used for obtaining the influence degree of each attribute according to the probability, and the influence degree is used for representing the influence degree on the effectiveness of the multi-group four-wheel positioning sample data; the evaluation attribute acquisition module is used for acquiring evaluation attributes influencing the effectiveness of the multiple groups of four-wheel positioning sample data according to the influence degrees; and the evaluation module is used for evaluating the effectiveness of the group of four-wheel positioning data according to the evaluation attribute when the group of four-wheel positioning data is acquired.
To achieve the above object, the present application also provides an evaluation apparatus comprising: a memory for storing a computer-executable evaluation method program; and a processor for executing the evaluation method when the processor calls the evaluation method program.
To achieve the above object, a storage medium having stored thereon an evaluation method program executable by one or more processors to implement the aforementioned evaluation method.
Compared with the existing design, the application provides an evaluation method, an evaluation device and a storage medium for vehicle four-wheel positioning data. The method and the device have the advantages that multiple groups of four-wheel positioning sample data are obtained and analyzed, wherein each group of four-wheel positioning sample data comprises at least two different attributes. The attribute state of the four-wheel positioning sample data is converted into a corresponding numerical value for the evaluation device to identify. Wherein each attribute comprises a first state and a second state, and the values comprise a first value and a second value corresponding to the first state and the second state. Calculating the probability of each attribute being in a first state through the first numerical value and the second numerical value, and acquiring the influence degree of each attribute according to the probability; obtaining an attribute influencing the effectiveness of the multiple groups of four-wheel positioning sample data according to the influence degree to serve as an evaluation attribute for evaluating the effectiveness of each group of four-wheel positioning sample data; when a group of four-wheel positioning data is acquired, the effectiveness of the group of four-wheel positioning data is evaluated according to the evaluation attribute, so that the effectiveness of the newly added group or groups of four-wheel positioning data can be judged quickly and accurately.
Drawings
Fig. 1 is a flowchart illustrating steps of a method for evaluating vehicle four-wheel positioning data according to a first embodiment of the present application.
Fig. 2 is a flowchart illustrating the detailed steps of step S105 in fig. 1.
Fig. 3 is a block diagram of an evaluation device according to a second embodiment of the present application.
Fig. 4 is a schematic block diagram of an evaluation apparatus according to a third embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims of the present application and in the drawings described above, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be noted that the descriptions in this application referring to "first", "second", etc. are for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In addition, technical solutions between various embodiments may be combined with each other, but must be realized by a person skilled in the art, and when the technical solutions are contradictory or cannot be realized, such a combination should not be considered to exist, and is not within the protection scope of the present application.
The application provides an evaluation method and an evaluation device for vehicle four-wheel positioning data and a storage medium. The method and the device have the advantages that multiple groups of four-wheel positioning sample data are obtained and analyzed, wherein each group of four-wheel positioning sample data comprises at least two different attributes. The attribute state of the four-wheel positioning sample data is converted into a corresponding numerical value for the evaluation device to identify. Wherein each attribute comprises a first state and a second state, and the values comprise a first value and a second value corresponding to the first state and the second state. Calculating the probability of each attribute being in a first state through the first numerical value and the second numerical value, and acquiring the influence degree of each attribute according to the probability; obtaining an attribute influencing the effectiveness of the multiple groups of four-wheel positioning sample data according to the influence degree to serve as an evaluation attribute for evaluating the effectiveness of each group of four-wheel positioning sample data; when a group of four-wheel positioning data is acquired, the effectiveness of the group of four-wheel positioning data is evaluated according to the evaluation attribute, so that the effectiveness of the newly added group or groups of four-wheel positioning data can be judged quickly and accurately.
Referring to fig. 1, fig. 1 shows an evaluation method for vehicle four-wheel positioning data, applied to an evaluation device, the evaluation method includes steps S101 to S106.
Wherein, step S101: and acquiring multiple groups of four-wheel positioning sample data, wherein each group of four-wheel positioning sample data comprises at least two different attributes.
Specifically, by collecting and storing four-wheel positioning data, a plurality of groups of four-wheel positioning data are extracted as samples, and four-wheel positioning sample data are formed through analysis of experienced technical experts.
Step S102: converting the state of the attribute to a corresponding value, wherein the state of the attribute comprises a first state and a second state, and the value comprises a first value and a second value corresponding to the first state and the second state.
Each set of four-wheel positioning sample data comprises at least two different attributes, the state of each attribute of the four-wheel positioning sample data is converted into a corresponding numerical value according to a preset relation, wherein the state of each attribute comprises a first state and a second state, the numerical value comprises a first numerical value and a second numerical value corresponding to the first state and the second state, the preset relation is the relation between the first state and the first numerical value, the corresponding relation between the second state and the second numerical value is the relation, and the first state can be converted into the corresponding first numerical value or the corresponding second numerical value only by identifying that the state of the attribute is the first state or the second state.
For convenience of description, the four-wheel positioning sample data is arranged and described in the form of a table in the present embodiment, and only three attributes of the four-wheel positioning sample data are shown in the table, but the attributes of the four-wheel positioning data are not limited to the three attributes.
As shown in table 1 below:
table 1 above includes 16 sets of four-wheel positioning sample data, where each set of four-wheel positioning sample data includes 3 different attributes, namely, the first attribute and the caster validity; a second attribute, toe angle effectiveness; the third attribute, camber symmetry. Through the analysis of the four-wheel positioning sample data attributes, whether the group of data belongs to valid data can be obtained.
Wherein the state of each attribute includes a first state and a second state, e.g., the first state of caster validity is valid and the second state is invalid. The first state of camber symmetry is symmetric and the second state is asymmetric.
And converting the attribute of the four-wheel positioning sample data into a corresponding numerical value, namely converting the first state and the second state of the attribute into a corresponding first numerical value and a corresponding second numerical value. And after the attribute state is identified, the first state is corresponding to a first numerical value and the second state is corresponding to a second numerical value through the preset relation. Thereby converting table 1 to table 2 below.
As shown in table 2 below:
step S103: and calculating the probability that the state of each attribute is the first state according to the first numerical value and the second numerical value.
In some embodiments, the calculating, according to the first numerical value and the second numerical value, a probability that the state of each of the attributes is the first state specifically includes: calculating the information entropy value of each attribute by using an information entropy formula, wherein the size of the information entropy value is opposite to the probability size that the attribute is in the first state, and the information entropy formula is
Wherein i and n are positive integers, i is less than or equal to n, H represents information entropy value, P (x)i) Indicating a probability that the value is the first value or the second value.
Information entropy value H with calculation attribute as kingpin caster angle1For illustration purposes.
In 16 groups of four-wheel positioning sample data, the first numerical value quantity of attributes of the king pin caster angle is 6, the second numerical value quantity is 10, and the information entropy of the data is
And calculating the information entropy value corresponding to each attribute, wherein the larger the information entropy value corresponding to the attribute is, the smaller the probability that the state of the attribute is the first state is.
Step S104: and obtaining the influence degree of each attribute according to the probability, wherein the influence degree is used for expressing the influence degree on the effectiveness of the multi-group four-wheel positioning sample data.
The influence degree sequencing of the attributes can be obtained by sequencing the probabilities corresponding to the attributes in a descending or ascending manner.
Step S105: and obtaining evaluation attributes influencing the effectiveness of the multi-group four-wheel positioning sample data according to the influence degree.
In some embodiments, obtaining an evaluation attribute that affects the validity of the multiple sets of four-wheel positioning sample data according to the influence degree specifically includes that the evaluation attribute includes a first evaluation attribute, and the first evaluation attribute is an attribute with the largest influence degree, that is, an attribute with the largest influence degree is selected as the first evaluation attribute. For example, after sorting the information entropy values corresponding to the attributes of the multiple sets of four-wheel positioning sample data, it is known that the information entropy value corresponding to the camber symmetry is the smallest for the third attribute, that is, the third attribute, and the degree of influence of the camber symmetry is the highest, that is, the third attribute is selected, and the evaluation attribute of the validity of each set of four-wheel positioning sample data for the camber symmetry is selected.
In some embodiments, obtaining an evaluation attribute that affects the validity of the multiple sets of four-wheel positioning sample data according to the influence degree specifically includes that the evaluation attribute includes a first evaluation attribute and a second evaluation attribute, where the first evaluation attribute is an attribute with the largest influence degree, and the second evaluation attribute is an influence degree with an influence degree lower than that of the first evaluation attribute.
And sequencing the influence degrees corresponding to the attributes to obtain whether the corresponding attribute is a first evaluation attribute or a second evaluation attribute.
Step S106: when a set of four-wheel positioning data is acquired, the effectiveness of the set of four-wheel positioning data is evaluated according to the evaluation attribute.
Referring to fig. 2, in some embodiments, the step S106 of evaluating the effectiveness of the set of four-wheel positioning data according to the evaluation attribute includes:
step S1061: judging whether the value corresponding to the first evaluation attribute is a first value or a second value;
step S1062: if the value corresponding to the first evaluation attribute is a first value, judging that the group of four-wheel positioning data is valid four-wheel positioning data; and if the value corresponding to the first evaluation attribute is the second value, judging that the group of four-wheel positioning data is invalid four-wheel positioning data.
Preferably, the first value is 1 and the second value is 0.
Preferably, the attribute is any one of caster symmetry, camber symmetry or caster symmetry.
Specifically, when a set of four-wheel positioning data is acquired as the 17 th set of four-wheel positioning data, as shown in table 3 below:
for example, if the third attribute is a camber symmetry, the camber symmetry is an evaluation attribute of the validity of each set of four-wheel positioning sample data. When the newly added group of four-wheel positioning sample data is the 17 th group of data, only the numerical value corresponding to the camber symmetry of the 17 th group of data is judged to be 0 or 1; if the numerical value corresponding to the camber symmetry is 1, judging that the group of four-wheel positioning data is effective four-wheel positioning data; if the value corresponding to the camber symmetry is 0, the set of four-wheel positioning data is determined to be invalid four-wheel positioning data.
In some embodiments, in step S105, evaluating the validity of the set of four-wheel positioning data according to the evaluation attribute specifically includes:
judging whether the value corresponding to the first evaluation attribute is a first value or a second value;
if the value corresponding to the first evaluation attribute is a first value, judging that the group of four-wheel positioning data is valid four-wheel positioning data;
if the numerical value corresponding to the first evaluation attribute is a second numerical value, judging that the numerical value corresponding to the second evaluation attribute is a first numerical value or a second numerical value;
if the value corresponding to the second evaluation attribute is the first value, judging that the group of four-wheel positioning data is valid four-wheel positioning data;
and if the value corresponding to the second evaluation attribute is a second value, judging that the group of four-wheel positioning data is invalid four-wheel positioning data.
Specifically, when one set of four-wheel positioning data is acquired as the 17 th set of four-wheel positioning data, as shown in table 4 below:
for example, if the camber symmetry is a first evaluation attribute of validity of each group of four-wheel positioning sample data and the first attribute is a second evaluation attribute of validity of the king pin caster angle, when the validity of each group of four-wheel positioning sample data is the second evaluation attribute, firstly, the numerical value corresponding to the camber symmetry of the 17 th group of data is judged to be 0 or 1; if the numerical value corresponding to the camber symmetry is 1, judging that the group of four-wheel positioning data is effective four-wheel positioning data; if the numerical value corresponding to the camber symmetry is 0, judging that the numerical value corresponding to the caster angle validity of the kingpin is 0 or 1; if the numerical value corresponding to the caster angle validity of the kingpin is 1, judging that the group of four-wheel positioning data is valid four-wheel positioning data; and if the value corresponding to the caster angle validity is 0, judging that the group of four-wheel positioning data is invalid four-wheel positioning data.
Referring to fig. 3, in some embodiments, the evaluation apparatus 10 includes a memory 101, a processor 102, and a bus 103, wherein the memory 101 is electrically connected to the processor 102 through the bus 103.
The memory 101 includes at least one type of readable storage medium, which includes a flash memory, a hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, and the like. The memory 101 may in some embodiments be an internal storage unit of the evaluation device 10, for example a hard disk of the evaluation device 10. The memory 101 may also be an external storage device of the evaluation apparatus 10 in other embodiments, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), etc., provided on the evaluation apparatus 10. The memory 101 may be used not only to store application software installed in the evaluation apparatus 10 and various types of data, such as codes of computer-readable programs, etc., but also to temporarily store data that has been output or is to be output.
acquiring a plurality of groups of four-wheel positioning sample data, wherein each group of four-wheel positioning sample data comprises at least two different attributes;
converting the state of the attribute into a corresponding numerical value, wherein the state of the attribute comprises a first state and a second state, and the numerical value comprises a first numerical value and a second numerical value corresponding to the first state and the second state;
calculating the probability that the state of each attribute is the first state according to the first numerical value and the second numerical value;
obtaining the influence degree of each attribute according to the probability, wherein the influence degree is used for expressing the influence degree on the effectiveness of the multi-group four-wheel positioning sample data;
obtaining evaluation attributes influencing the effectiveness of the multi-group four-wheel positioning sample data according to the influence degree;
when a set of four-wheel positioning data is acquired, the effectiveness of the set of four-wheel positioning data is evaluated according to the evaluation attribute.
In some embodiments, the processor 102 may be further configured to:
calculating an information entropy value of each attribute by using an information entropy formula, wherein the size of the information entropy value is opposite to the probability that the attribute is in the first state;
the information entropy formula is
Wherein i and n are positive integers, i is less than or equal to n, H represents information entropy value, P (x)i) Indicating a probability that the value is the first value or the second value.
In some embodiments, the evaluation attribute includes a first evaluation attribute, and the first evaluation attribute is an attribute with the largest influence.
In some embodiments, the processor 102 may be further configured to:
judging whether the value corresponding to the first evaluation attribute is a first value or a second value;
and if the value corresponding to the first evaluation attribute is a first value, judging that the group of four-wheel positioning data is valid four-wheel positioning data.
In some embodiments, the evaluation attribute further includes a second evaluation attribute, and the second evaluation attribute is an influence degree of which the influence degree is only lower than that of the first evaluation attribute.
In some embodiments, the processor 102 may be further configured to:
judging whether the value corresponding to the first evaluation attribute is a first value or a second value;
if the value corresponding to the first evaluation attribute is a first value, judging that the group of four-wheel positioning data is valid four-wheel positioning data;
if the numerical value corresponding to the first evaluation attribute is a second numerical value, judging that the numerical value corresponding to the second evaluation attribute is a first numerical value or a second numerical value;
if the value corresponding to the second evaluation attribute is the first value, judging that the group of four-wheel positioning data is valid four-wheel positioning data;
and if the value corresponding to the second evaluation attribute is a second value, judging that the group of four-wheel positioning data is invalid four-wheel positioning data.
In some embodiments, the first value is 1 and the second value is 0.
Referring to fig. 4, in some embodiments, the present application further provides an evaluation apparatus 20, where the evaluation apparatus 20 includes:
the data acquisition module 201 is configured to acquire multiple sets of four-wheel positioning sample data, where each set of four-wheel positioning sample data includes at least two different attributes;
a state conversion module 202, configured to convert the state of the attribute into a corresponding numerical value, where the state of the attribute includes a first state and a second state, and the numerical value includes a first numerical value and a second numerical value corresponding to the first state and the second state;
a probability calculation module 203, configured to calculate a probability that the state of each attribute is the first state according to the first numerical value and the second numerical value;
an influence obtaining module 204, configured to obtain an influence of each attribute according to the probability, where the influence is used to represent the influence on the validity of the multiple sets of four-wheel positioning sample data;
an evaluation attribute obtaining module 205, configured to obtain, according to the influence degree, an evaluation attribute that affects validity of the multiple groups of four-wheel positioning sample data; and
an evaluation module 206, configured to evaluate, when a set of four-wheel positioning data is acquired, validity of the set of four-wheel positioning data according to the evaluation attribute.
Preferably, the probability calculation module 203 calculates an information entropy value of each attribute by using an information entropy formula, wherein the size of the information entropy value is opposite to the size of the probability that the attribute is in the first state; the information entropy formula is
Wherein i and n are positive integers, i is less than or equal to n, H represents information entropy value, P (x)i) Indicating a probability that the value is the first value or the second value.
Preferably, the evaluation attribute includes a first evaluation attribute, the first evaluation attribute is an attribute with the largest influence, and the evaluation module 206 is configured to determine that a value corresponding to the first evaluation attribute is a first value or a second value; and if the value corresponding to the first evaluation attribute is a first value, judging that the group of four-wheel positioning data is valid four-wheel positioning data.
Preferably, the evaluation attributes further include a second evaluation attribute, where the second evaluation attribute is an influence degree that the influence degree is only lower than that of the first evaluation attribute, and the evaluation module 206 is configured to determine that a value corresponding to the first evaluation attribute is a first value or a second value; if the value corresponding to the first evaluation attribute is a first value, judging that the group of four-wheel positioning data is valid four-wheel positioning data; if the numerical value corresponding to the first evaluation attribute is a second numerical value, judging that the numerical value corresponding to the second evaluation attribute is a first numerical value or a second numerical value; if the value corresponding to the second evaluation attribute is the first value, judging that the group of four-wheel positioning data is valid four-wheel positioning data; and if the value corresponding to the second evaluation attribute is a second value, judging that the group of four-wheel positioning data is invalid four-wheel positioning data.
In some embodiments, the present application further provides a storage medium having a program for an evaluation method of four-wheel positioning data stored thereon, where the program for the evaluation method of four-wheel positioning data is executable by one or more processors to perform the following steps:
calculating an information entropy value of each attribute by using an information entropy formula, wherein the size of the information entropy value is opposite to the probability that the attribute is in the first state;
the information entropy formula is
Wherein i and n are positive integers, i is less than or equal to n, H represents information entropy value, P (x)i) Indicating a probability that the value is the first value or the second value.
In some embodiments, the evaluation attribute includes a first evaluation attribute, and the first evaluation attribute is an attribute with the largest influence.
In some embodiments, the processor 102 may be further configured to:
judging whether the value corresponding to the first evaluation attribute is a first value or a second value;
and if the value corresponding to the first evaluation attribute is a first value, judging that the group of four-wheel positioning data is valid four-wheel positioning data.
In some embodiments, the evaluation attribute further includes a second evaluation attribute, and the second evaluation attribute is an influence degree of which the influence degree is only lower than that of the first evaluation attribute.
In some embodiments, the processor 102 may be further configured to:
judging whether the value corresponding to the first evaluation attribute is a first value or a second value;
if the value corresponding to the first evaluation attribute is a first value, judging that the group of four-wheel positioning data is valid four-wheel positioning data;
if the numerical value corresponding to the first evaluation attribute is a second numerical value, judging that the numerical value corresponding to the second evaluation attribute is a first numerical value or a second numerical value;
if the value corresponding to the second evaluation attribute is the first value, judging that the group of four-wheel positioning data is valid four-wheel positioning data;
and if the value corresponding to the second evaluation attribute is a second value, judging that the group of four-wheel positioning data is invalid four-wheel positioning data.
In some embodiments, the first value is 1 and the second value is 0.
The above description is only a preferred embodiment of the present application, and not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings of the present application, or which are directly or indirectly applied to other related technical fields, are also included in the scope of the present application.
Claims (7)
1. An evaluation method of vehicle four-wheel positioning data, characterized by comprising:
acquiring a plurality of groups of four-wheel positioning sample data, wherein each group of four-wheel positioning sample data comprises at least two different attributes;
converting the state of the attribute into a corresponding numerical value, wherein the state of the attribute comprises a first state and a second state, and the numerical value comprises a first numerical value and a second numerical value corresponding to the first state and the second state;
calculating the probability that the state of each attribute is the first state according to the first numerical value and the second numerical value;
obtaining the influence degree of each attribute according to the probability, wherein the influence degree is used for expressing the influence degree on the effectiveness of the multi-group four-wheel positioning sample data;
obtaining evaluation attributes influencing the effectiveness of the multi-group four-wheel positioning sample data according to the influence degree;
when a group of four-wheel positioning data is acquired, evaluating the effectiveness of the group of four-wheel positioning data according to the evaluation attribute;
wherein the calculating the probability that each attribute is in the first state according to the first numerical value and the second numerical value comprises:
calculating an information entropy value of each attribute by using an information entropy formula, wherein the size of the information entropy value is opposite to the probability that the attribute is in the first state;
the information entropy formula is that i and n are positive integers, i is not more than n, H represents an information entropy value, and P (xi) represents the probability that the value is a first value or a second value;
the evaluation attributes comprise a first evaluation attribute, and the first evaluation attribute is an attribute with the largest influence degree;
wherein the evaluating the validity of the set of four-wheel positioning data according to the evaluation attribute comprises:
judging whether the value corresponding to the first evaluation attribute is a first value or a second value;
and if the value corresponding to the first evaluation attribute is a first value, judging that the group of four-wheel positioning data is valid four-wheel positioning data.
2. The evaluation method according to claim 1, wherein the evaluation attribute further includes a second evaluation attribute that is an influence degree of which influence degree is lower than only the first evaluation attribute.
3. The evaluation method of claim 2, wherein the evaluating the validity of the set of four-wheel positioning data according to the evaluation attribute comprises:
if the value corresponding to the first evaluation attribute is a first value, judging that the group of four-wheel positioning data is valid four-wheel positioning data;
if the numerical value corresponding to the first evaluation attribute is a second numerical value, judging that the numerical value corresponding to the second evaluation attribute is a first numerical value or a second numerical value;
if the value corresponding to the second evaluation attribute is the first value, judging that the group of four-wheel positioning data is valid four-wheel positioning data;
and if the value corresponding to the second evaluation attribute is a second value, judging that the group of four-wheel positioning data is invalid four-wheel positioning data.
4. The evaluation method according to any one of claims 1 to 3, wherein; the first value is 1 and the second value is 0.
5. An evaluation apparatus, characterized in that the evaluation apparatus comprises:
the data acquisition module is used for acquiring a plurality of groups of four-wheel positioning sample data, and each group of four-wheel positioning sample data comprises at least two different attributes;
a state conversion module, configured to convert the state of the attribute into a corresponding numerical value, where the state of the attribute includes a first state and a second state, and the numerical value includes a first numerical value and a second numerical value corresponding to the first state and the second state;
the probability calculation module is used for calculating the probability that the state of each attribute is the first state according to the first numerical value and the second numerical value; wherein the calculating the probability that each attribute is in the first state according to the first numerical value and the second numerical value comprises: calculating an information entropy value of each attribute by using an information entropy formula, wherein the size of the information entropy value is opposite to the probability that the attribute is in the first state; the information entropy formula is that i and n are positive integers, i is not more than n, H represents an information entropy value, and P (xi) represents the probability that the value is a first value or a second value;
the influence degree obtaining module is used for obtaining the influence degree of each attribute according to the probability, and the influence degree is used for representing the influence degree on the effectiveness of the multi-group four-wheel positioning sample data;
the evaluation attribute acquisition module is used for acquiring evaluation attributes influencing the effectiveness of the multiple groups of four-wheel positioning sample data according to the influence degrees; and
the evaluation module is used for evaluating the effectiveness of the group of four-wheel positioning data according to the evaluation attribute when the group of four-wheel positioning data is acquired;
the evaluation attributes comprise a first evaluation attribute, and the first evaluation attribute is an attribute with the largest influence degree;
wherein the evaluating the validity of the set of four-wheel positioning data according to the evaluation attribute comprises:
judging whether the value corresponding to the first evaluation attribute is a first value or a second value;
and if the value corresponding to the first evaluation attribute is a first value, judging that the group of four-wheel positioning data is valid four-wheel positioning data.
6. An evaluation apparatus, characterized in that the evaluation apparatus comprises:
a memory for storing a computer-executable evaluation method program; and
a processor that executes the evaluation method of any one of claims 1-4 when the processor invokes the evaluation method program.
7. A storage medium, characterized by: the storage medium has stored thereon an evaluation method program executable by one or more processors to implement the evaluation method of any one of claims 1-4.
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