A data separation and processing method and system for petroleum map images

Abstract

The present application provides a data separation and processing method and system applied to petroleum map graphics, belonging to the technical field of petroleum map data processing; wherein, a data separation and processing method applied to petroleum map graphics comprises: obtaining enterprise user demand data; analyzing multiple supply time nodes of each graphics and the number of enterprise users corresponding to each supply time node according to the enterprise user demand data; the supply time nodes correspond one-to-one with the demand time nodes; calculating quantity impact data based on the supply time nodes and the number of enterprise users; the quantity impact data is positively correlated with the number of enterprise users; determining graphics processing priority data according to the quantity impact data and the enterprise user demand data; the graphics processing priority data is positively correlated with the quantity impact data; adopting this method can improve data classification processing efficiency.

Description

Technical Field

[0001] The present application relates to the technical field of petroleum map data processing, and in particular to a data separation and processing method and system applied to petroleum map graphics. Background Art

[0002] Various maps are produced in the process of oil exploration and development. These maps are used to display and explain underground geological structures, stratigraphic distribution, oil and gas reservoir characteristics, etc., to help professionals understand and analyze underground geological research situations. Maps are professional data information drawn in the form of primitives. A map is composed of multiple primitives, which contain primitive data and primitive styles. The primitive style is a style used to display primitive data. Generally speaking, oil maps are stored in the cloud platform database, and enterprise users select maps from the database according to their own needs. However, different enterprise users use different primitive styles, so when enterprise users select maps, they actually need the primitive data. After obtaining the needs of enterprise users, the cloud platform database needs to separate the map data and provide the separated primitive data to enterprise users. However, when there are many enterprise users and the enterprise users require more primitive data, it is very important to determine the separation priority of the maps. Summary of the invention

[0003] The present application provides a data separation processing method and system applied to petroleum map images, which can determine the data separation priority of the images, which is conducive to the reasonable allocation of data separation computing resources and the improvement of data separation processing efficiency when there are many map demands from enterprise users.

[0004] In a first aspect, the present application provides a data separation and processing method for petroleum map images. The method comprises:

[0005] Acquire enterprise user demand data; the enterprise user demand data includes demand map data, demand time data and demand style data; the demand time data is the demand time node for each map in the demand map data; the demand style data is the graphic element style for each map in the demand map data;

[0006] Analyzing multiple supply time nodes of each map and the number of enterprise users corresponding to each supply time node according to the enterprise user demand data; the supply time nodes correspond to the demand time nodes one by one; the supply time nodes are time nodes for providing the map in response to the demand time data to the enterprise users;

[0007] Calculating quantity impact data based on the supply time node and the number of enterprise users; the quantity impact data is positively correlated with the number of enterprise users;

[0008] The drawing processing priority data is determined according to the quantity impact data and the enterprise user demand data; the drawing processing priority data is positively correlated with the quantity impact data.

[0009] Further, the calculation of quantity impact data based on the supply time node and the number of enterprise users includes:

[0010] Determine the total number of enterprise users of each map based on the enterprise user demand data;

[0011] Determine a first time node of each drawing based on the supply time node; the first time node is the supply time node closest to the current time node;

[0012] Determine a first quantity corresponding to the first time node; the first quantity is the number of enterprise users whose demand time data includes the first time node;

[0013] Determine the number of supply time nodes for each map, and calculate the delivery frequency data based on the total number of enterprise users and the number of supply time nodes for each map;

[0014] Calculate quantity impact data based on the total number of enterprise users, the first number and the delivery frequency data.

[0015] Furthermore, the calculation method of the quantity impact data includes:

[0016] ;

[0017] In the formula, For the quantity impact data, is the total number of enterprise users, is the first quantity, To deliver frequency data, The number of supply time nodes; The first conversion coefficient, the second conversion coefficient and the third conversion coefficient are preset respectively; are respectively a preset first weight, a preset second weight and a preset third weight; wherein, .

[0018] Furthermore, the determining of the drawing processing priority data according to the quantity impact data and the enterprise user demand data includes:

[0019] Determine the required style ratio of each map according to the enterprise user demand data; the required style ratio is the ratio of the number of enterprise users who have style requirements for the same map to the total number of enterprise users of the map;

[0020] Acquire historical enterprise user demand data, and analyze the style preference data of each historical enterprise user according to the historical enterprise user demand data;

[0021] Calculating style influence data according to the demand style ratio and the style tendency data;

[0022] The drawing processing priority data is determined according to the quantity impact data and the style impact data.

[0023] Furthermore, the method for calculating the image processing priority data includes:

[0024] ;

[0025] In the formula, Processing priority data for drawings, For the quantity impact data, Influence data for styles; are quantity weight and style weight respectively; among them, .

[0026] In a second aspect, the present application provides a data separation and processing system applied to petroleum map images, the system comprising:

[0027] An acquisition module is used to acquire enterprise user demand data; the enterprise user demand data includes demand map data, demand time data and demand style data; the demand time data is the demand time node for each map in the demand map data; the demand style data is the graphic element style for each map in the demand map data;

[0028] An analysis module, for analyzing a plurality of supply time nodes of each map and the number of enterprise users corresponding to each supply time node according to the enterprise user demand data; the supply time nodes correspond one to one with the demand time nodes; the supply time nodes are time nodes for providing the map in response to the demand time data to the enterprise users;

[0029] A calculation module, used for calculating quantity impact data based on the supply time node and the number of enterprise users; the quantity impact data is positively correlated with the number of enterprise users;

[0030] A determination module is used to determine the drawing processing priority data according to the quantity impact data and the enterprise user demand data; the drawing processing priority data is positively correlated with the quantity impact data.

[0031] Furthermore, the calculation module is further configured to calculate the quantity impact data based on the supply time node and the number of enterprise users, including:

[0032] Determine the total number of enterprise users of each map based on the enterprise user demand data;

[0033] Determine a first time node of each drawing based on the supply time node; the first time node is the supply time node closest to the current time node;

[0034] Determine a first quantity corresponding to the first time node; the first quantity is the number of enterprise users whose demand time data includes the first time node;

[0035] Determine the number of supply time nodes for each map, and calculate the delivery frequency data based on the total number of enterprise users and the number of supply time nodes for each map;

[0036] Calculate quantity impact data based on the total number of enterprise users, the first number and the delivery frequency data.

[0037] Furthermore, the calculation module is further configured such that the calculation method of the quantity impact data includes:

[0038] ;

[0039] In the formula, For the quantity impact data, is the total number of enterprise users, is the first quantity, To deliver frequency data, The number of supply time nodes; The first conversion coefficient, the second conversion coefficient and the third conversion coefficient are preset respectively; are respectively a preset first weight, a preset second weight and a preset third weight; wherein, .

[0040] Furthermore, the determination module is further configured to determine the drawing processing priority data according to the quantity impact data and the enterprise user demand data, including:

[0041] Determine the required style ratio of each map according to the enterprise user demand data; the required style ratio is the ratio of the number of enterprise users who have style requirements for the same map to the total number of enterprise users of the map;

[0042] Acquire historical enterprise user demand data, and analyze the style preference data of each historical enterprise user according to the historical enterprise user demand data;

[0043] Calculating style influence data according to the demand style ratio and the style tendency data;

[0044] The drawing processing priority data is determined according to the quantity impact data and the style impact data.

[0045] Furthermore, the determination module is further configured such that the calculation method of the image processing priority data includes:

[0046] ;

[0047] In the formula, Processing priority data for drawings, For the quantity impact data, Influence data for styles; are quantity weight and style weight respectively; among them, .

[0048] It should be understood that the contents described in the summary of the invention are not intended to limit the key or important features of the embodiments of the present application, nor are they intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The above and other features, advantages and aspects of the embodiments of the present application will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, wherein:

[0050] Figure 1 A flow chart showing a data separation and processing method applied to a petroleum map in an embodiment of the present application is shown;

[0051] Figure 2 A block diagram of a data separation and processing system applied to petroleum map images in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0053] In addition, the term "and / or" in this article is only a description of the association relationship between the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0054] The present application provides a data separation and processing method and system applied to petroleum map images, which can.

[0055] In a first aspect, the present application provides a data separation and processing method for petroleum map images. Figure 1 The specific steps included in the method are as follows.

[0056] Step S110: Acquire enterprise user demand data; the enterprise user demand data includes demand map data, demand time data and demand style data; the demand time data is the demand time node for each map in the demand map data; the demand style data is the graphic element style for each map in the demand map data.

[0057] In an embodiment of the present application, the enterprise user demand data is the enterprise user demand received from the current time node; in the enterprise user demand, the enterprise user will mention the image metadata or the image component data; and in the cloud platform database, the image component contains multiple image metadata, and the image component and the image metadata are bound. Therefore, after determining the enterprise user's needs, whether it is image metadata demand or image component demand, the corresponding image component stored in the cloud platform database can be directly found; it can be understood that the demand time node here refers to the time point when the enterprise user needs the image metadata or the image component data; because the enterprise user demand may contain multiple image metadata or image component data, different image metadata or image component data correspond to different demand time nodes; the demand style data here is not necessarily obtainable data. After receiving the enterprise user demand, the enterprise user demand may contain demand style data, and the enterprise user requires image metadata and combines them according to the demand style to obtain the required image component; it may also not contain demand style data, and only require image metadata or image component data.

[0058] Step S120: Analyze multiple supply time nodes of each map and the number of enterprise users corresponding to each supply time node according to the enterprise user demand data; the supply time nodes correspond one-to-one to the demand time nodes; the supply time nodes are time nodes for providing maps to enterprise users in response to the demand time data.

[0059] It can be understood that the enterprise user demand data is data based on the enterprise; and after receiving the enterprise user demand data, the data needs to be converted into data based on drawings; it is the same data, but the corresponding angles are different; for example, enterprise user A requires drawing a, and enterprise user B requires drawing a; then the conversion means that the number of enterprise users of drawing a is 2; it can be understood that the method embodied in this step is relatively conventional and will not be elaborated here.

[0060] Step S130: Calculate quantity impact data based on the supply time node and the number of enterprise users; the quantity impact data is positively correlated with the number of enterprise users.

[0061] In an embodiment of the present application, calculating the quantity impact data based on the supply time nodes and the number of enterprise users specifically includes: determining the total number of enterprise users for each map based on the enterprise user demand data; determining the first time node for each map based on the supply time nodes; the first time node is the supply time node closest to the current time node; determining the first quantity corresponding to the first time node; the first quantity is the number of enterprise users whose demand time data includes the first time node; determining the number of supply time nodes for each map, and calculating the delivery frequency data based on the total number of enterprise users and the number of supply time nodes for each map; calculating the quantity impact data based on the total number of enterprise users, the first quantity and the delivery frequency data.

[0062] It is understandable that, for a map, the more corporate users that require it, the more important the map is, and the higher the priority of its processing should be; therefore, in the above analysis process, the larger the total number of corporate users, the greater the quantity impact data; the larger the first number, the greater the quantity impact data, and the larger the delivery frequency data, the greater the quantity impact data; it is understandable that the first number reflects the corporate users who require each map at the first time node; that is, among all the demand time nodes, the time node closest to the current time node, that is, the delivery node of the map, corresponds to the most urgent map delivery task; then the more corporate users corresponding to the time node, the higher the priority of the map should be.

[0063] Furthermore, the calculation method of the quantity impact data specifically includes:

[0064] ;

[0065] In the formula, For the quantity impact data, is the total number of enterprise users, is the first quantity, To deliver frequency data, The number of supply time nodes; The first conversion coefficient, the second conversion coefficient and the third conversion coefficient are preset respectively; are respectively a preset first weight, a preset second weight and a preset third weight; wherein, .

[0066] Step S140: determining the drawing processing priority data according to the quantity impact data and the enterprise user demand data; the drawing processing priority data is positively correlated with the quantity impact data.

[0067] In an embodiment of the present application, determining the map processing priority data based on the quantity impact data and the enterprise user demand data specifically includes: determining the demand style ratio of each map based on the enterprise user demand data; the demand style ratio is the ratio of the number of enterprise users who have style requirements for the same map to the total number of enterprise users of the map; obtaining historical enterprise user demand data, and analyzing the style tendency data of each historical enterprise user based on the historical enterprise user demand data; calculating style impact data based on the demand style ratio and the style tendency data; and determining the map processing priority data based on the quantity impact data and the style impact data.

[0068] It can be understood that the demand style ratio here can be seen from step S110. In step S110, it is mentioned that among all the enterprise user demand data, some enterprise users do not mention style requirements in their demands, while some enterprise users do mention style requirements in their demands; then the demand style ratio is obtained by dividing the number of enterprise users who mention style requirements by the total number of enterprise users; it should be noted that when calculating the demand style ratio here, the calculation is performed from the perspective of a single drawing; that is, the demand style ratio of a drawing = the number of enterprise users who include the drawing in their enterprise user demands and mention style requirements / the total number of enterprise users who include the drawing in their enterprise user demands; it can be further seen that the larger the demand style ratio, the more enterprise users have clear and accurate enterprise user demands, then the easier it is for the final delivered drawing to meet the needs of enterprise users, reducing the occurrence of secondary workload, and accordingly, the higher the priority of this type of drawing; that is, the larger the demand style ratio, the larger the style impact data, and the larger the drawing processing priority data.

[0069] For a single drawing, the style requirements of enterprise users who have not mentioned any style requirements among all enterprise users of the drawing in the enterprise user requirements need to be obtained through analysis of historical enterprise user demand data; by analyzing the historical enterprise user demand data, the number of times the style is mentioned most by enterprise users / the number of times the style is mentioned by enterprise users = style tendency data; the proportion of required styles * style tendency data = style influence data.

[0070] Furthermore, the method for calculating the image processing priority data specifically includes:

[0071] ;

[0072] In the formula, Processing priority data for drawings, For the quantity impact data, Influence data for styles; are quantity weight and style weight respectively; among them, .

[0073] By adopting the solution of the present application, the analysis of the enterprise users' demand for drawings is realized, and the priority of each drawing is determined; then the drawings are sorted from high to low according to the drawing priority data; the time node closest to the current time node among all the first time nodes mentioned above is used as the boundary, and according to the preset drawing separation processing time, the number of drawings that can be processed before the boundary is calculated and determined; then, starting from the first drawing according to the drawing priority sorting, drawings of this number are selected to perform the first batch of drawing separation data processing tasks; the preset drawing separation processing time here is the separation processing time of a single drawing, and it can be understood that in the solution of the present application, the separation processing time of each drawing is the same by default.

[0074] Through the above solution, the calculation of image processing priority is realized, the rational allocation of computing resources is ensured, the work efficiency of data analysis and processing is improved, and the satisfaction of enterprise users is improved.

[0075] It can be understood that the method of the present application is actually a machine learning model. The parameters in the model can be trained by feedback on the results of the image processing priority data continuously calculated in actual work. The trainable parameters include a preset first conversion coefficient, a preset second conversion coefficient, a preset third conversion coefficient, a preset first weight, a preset second weight, a preset third weight, a quantity weight, a style weight, etc.; through continuous training of the above parameters, the calculation results of the image processing priority data are more accurate and more in line with the actual situation, thereby making the allocation of computing power resources more reasonable and improving the work efficiency of data separation and processing.

[0076] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the embodiments of the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present application.

[0077] In the second aspect, the present application provides a data separation and processing system for petroleum map images. Figure 2As shown, the system includes an acquisition module 210 for acquiring enterprise user demand data; the enterprise user demand data includes demand map data, demand time data and demand style data; the demand time data is the demand time node for each map in the demand map data; the demand style data is the graphic element style for each map in the demand map data; an analysis module 220 is used to analyze multiple supply time nodes of each map and the number of enterprise users corresponding to each supply time node according to the enterprise user demand data; the supply time node corresponds to the demand time node one by one; the supply time node is the time node for providing the map in response to the demand time data to the enterprise user; a calculation module 230 is used to calculate quantity impact data based on the supply time node and the number of enterprise users; the quantity impact data is positively correlated with the number of enterprise users; a determination module 240 is used to determine map processing priority data according to the quantity impact data and the enterprise user demand data; the map processing priority data is positively correlated with the quantity impact data.

[0078] The calculation module 230 is further configured such that the calculation of quantity impact data based on the supply time nodes and the number of enterprise users includes: determining the total number of enterprise users for each map based on the enterprise user demand data; determining the first time node for each map based on the supply time nodes; the first time node being the supply time node closest to the current time node; determining the first quantity corresponding to the first time node; the first quantity being the number of enterprise users whose demand time data includes the first time node; determining the number of supply time nodes for each map, and calculating the delivery frequency data based on the total number of enterprise users and the number of supply time nodes for each map; and calculating the quantity impact data based on the total number of enterprise users, the first quantity and the delivery frequency data.

[0079] Furthermore, the calculation module 230 is further configured such that the calculation method of the quantity impact data includes:

[0080] ;

[0081] In the formula, For the quantity impact data, is the total number of enterprise users, is the first quantity, To deliver frequency data, The number of supply time nodes; The first conversion coefficient, the second conversion coefficient and the third conversion coefficient are preset respectively; are respectively a preset first weight, a preset second weight and a preset third weight; wherein, .

[0082] Furthermore, the determination module 240 is further configured such that the determination of the drawing processing priority data according to the quantity impact data and the enterprise user demand data includes: determining the demand style ratio of each drawing according to the enterprise user demand data; the demand style ratio is the ratio of the number of enterprise users who have style requirements for the same drawing to the total number of enterprise users of the drawing; obtaining historical enterprise user demand data, and analyzing the style tendency data of each historical enterprise user according to the historical enterprise user demand data; calculating the style impact data according to the demand style ratio and the style tendency data; and determining the drawing processing priority data according to the quantity impact data and the style impact data.

[0083] Furthermore, the determination module 240 is further configured such that the calculation method of the image processing priority data includes:

[0084] ;

[0085] In the formula, Processing priority data for drawings, For the quantity impact data, Influence data for styles; are quantity weight and style weight respectively; among them, .

[0086] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the described device can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0087] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the aforementioned disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in this application (but not limited to) by each other to form a technical solution.

Claims

1. A data separation and processing method applied to petroleum map images, characterized in that: include: Acquire enterprise user demand data; the enterprise user demand data includes demand drawing data, demand time data and demand style data; The demand time data is a demand time node for each drawing in the demand drawing data; The required style data is a graphic element style for each graphic element in the required graphic element data; Analyze multiple supply time nodes of each map and the number of enterprise users corresponding to each supply time node according to the enterprise user demand data; The supply time nodes correspond to the demand time nodes one by one; the supply time nodes are time nodes for providing graphics corresponding to the demand time data to enterprise users; Calculate quantity impact data based on the supply time node and the number of enterprise users; The quantity impact data is positively correlated with the number of enterprise users; Determine the drawing processing priority data according to the quantity impact data and the enterprise user demand data; The image processing priority data is positively correlated with the quantity impact data; The calculating of the quantity impact data based on the supply time node and the number of enterprise users includes determining the total number of enterprise users of each map based on the enterprise user demand data; Determine a first time node of each map based on the supply time node; the first time node is the supply time node closest to the current time node; determine a first quantity corresponding to the first time node; the first quantity is the number of enterprise users whose demand time data includes the first time node; Determine the number of supply time nodes for each map, and calculate the delivery frequency data based on the total number of enterprise users and the number of supply time nodes for each map; Calculate quantity impact data based on the total number of enterprise users, the first number, and the delivery frequency data; The calculation method of the quantity impact data includes: ； In the formula, For the quantity impact data, is the total number of enterprise users, is the first quantity, To deliver frequency data, The number of supply time nodes; The first conversion coefficient, the second conversion coefficient and the third conversion coefficient are preset respectively; are respectively a preset first weight, a preset second weight and a preset third weight; wherein, .

2. The data separation and processing method for petroleum map images according to claim 1 is characterized in that: The determining of the drawing processing priority data according to the quantity impact data and the enterprise user demand data comprises: Determine the required style ratio of each map according to the enterprise user demand data; the required style ratio is the ratio of the number of enterprise users who have style requirements for the same map to the total number of enterprise users of the map; Acquire historical enterprise user demand data, and analyze the style tendency data of each historical enterprise user according to the historical enterprise user demand data; Calculating style influence data according to the demand style ratio and the style tendency data; The drawing processing priority data is determined according to the quantity impact data and the style impact data.

3. The data separation and processing method for petroleum map images according to claim 2 is characterized in that: The method for calculating the image processing priority data includes: ； In the formula, Processing priority data for drawings, For the quantity impact data, Influence data for styles; are quantity weight and style weight respectively; among them, .

4. A data separation and processing system for petroleum map images, characterized in that: include: The acquisition module (210) is used to acquire enterprise user demand data; the enterprise user demand data includes demand map data, demand time data and demand style data; the demand time data is the demand time node for each map in the demand map data; the demand style data is the graphic element style for each map in the demand map data; An analysis module (220) is used to analyze multiple supply time nodes of each map and the number of enterprise users corresponding to each supply time node according to the enterprise user demand data; the supply time nodes correspond to the demand time nodes one by one; the supply time nodes are time nodes for providing the map in response to the demand time data to the enterprise users; A calculation module (230), configured to calculate quantity impact data based on the supply time node and the number of enterprise users; The quantity impact data is positively correlated with the number of enterprise users; A determination module (240) is used to determine the image processing priority data according to the quantity impact data and the enterprise user demand data; the image processing priority data is positively correlated with the quantity impact data; The calculation module (230) is further configured to calculate the quantity impact data based on the supply time node and the number of enterprise users, including determining the total number of enterprise users of each map based on the enterprise user demand data; Determine a first time node of each map based on the supply time node; the first time node is the supply time node closest to the current time node; determine a first quantity corresponding to the first time node; the first quantity is the number of enterprise users whose demand time data includes the first time node; Determine the number of supply time nodes for each map, and calculate the delivery frequency data based on the total number of enterprise users and the number of supply time nodes for each map; Calculate quantity impact data based on the total number of enterprise users, the first number, and the delivery frequency data; The calculation module (230) is further configured such that the calculation method of the quantity impact data includes: ； In the formula, For the quantity impact data, is the total number of enterprise users, is the first quantity, To deliver frequency data, The number of supply time nodes; The first conversion coefficient, the second conversion coefficient and the third conversion coefficient are preset respectively; are respectively a preset first weight, a preset second weight and a preset third weight; wherein, .

5. The data separation and processing system for petroleum map images according to claim 4 is characterized in that: The determination module (240) is further configured to determine the drawing processing priority data according to the quantity impact data and the enterprise user demand data, including: Determine the required style ratio of each map according to the enterprise user demand data; the required style ratio is the ratio of the number of enterprise users who have style requirements for the same map to the total number of enterprise users of the map; Acquire historical enterprise user demand data, and analyze the style tendency data of each historical enterprise user according to the historical enterprise user demand data; Calculating style influence data according to the demand style ratio and the style tendency data; The drawing processing priority data is determined according to the quantity impact data and the style impact data.

6. The data separation and processing system for petroleum map images according to claim 5 is characterized in that: The determination module (240) is further configured such that the method for calculating the image processing priority data includes: ； In the formula, Processing priority data for drawings, For the quantity impact data, Influence data for styles; are quantity weight and style weight respectively; among them, .

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