Practical index calculation method for WEB system in enterprise

Abstract

The invention discloses a practical index calculation method for a WEB system in an enterprise, and the method comprises the following steps: 1, collecting business process access times, business process response duration, business process page size and business process stay duration information, and carrying out the system practical index division according to a time dimension through employing a K-means clustering method; step 2, measuring conflicts among practical indexes of different systems by using a CRITIC method, and realizing scientific and reasonable distribution of practical index weights of the systems; step 3, realizing standardization and continuous tracking on the practical index of the system by using a control chart in 6 sigma; the method has the beneficial effects that a system practical index weight distribution method is provided, theoretical guidance is provided for distribution of system practical index weights, stable operation of the system is facilitated, and the positive degree of the system practical level is improved; the method not only meets the industrial general standard of the internet trend, but also has high flexibility and adaptability, and can provide powerful support for digital transformation of enterprises.

Description

Technical Field

[0001] The invention belongs to the technical field of computer control, and in particular relates to a method for calculating practicality indexes of an enterprise's internal WEB system. Background Art

[0002] Establishing a scientific and systematic methodology to guide enterprises in effectively promoting digital transformation has become a key issue that needs to be addressed urgently. In particular, as an important carrier of digital transformation, the practicality of the internal WEB system of an enterprise is directly related to the smooth operation of the enterprise's business processes and the improvement of management efficiency. Therefore, scientific calculation and evaluation of the practical indicators of the WEB system are of great significance for guiding the digital transformation of enterprises, optimizing resource allocation, and improving operational efficiency.

[0003] Traditional WEB system evaluation methods often focus on the measurement of a single indicator, ignoring the correlation and conflict between indicators, making it difficult to fully reflect the overall performance and practicality of the system. In addition, due to the lack of unified industry standards and continuous tracking mechanisms, companies are prone to blind trial and error and waste of resources during the digital transformation process. Summary of the invention

[0004] The purpose of the present invention is to provide a method for calculating the practical indicators of an enterprise's internal WEB system, integrating multi-dimensional indicator information such as the number of business process visits, business process response time, business process page size, and business process residence time, and through advanced data analysis tools and models such as K-means clustering method, CRITIC method, and 6σ control charts, to achieve scientific division, reasonable allocation, and continuous tracking of system practical indicators.

[0005] To achieve the above object, the present invention provides the following technical solution: a method for calculating the practicality index of an enterprise internal WEB system, comprising the following steps:

[0006] Step 1: Collect information on the number of business process visits, business process response time, business process page size, and business process stay time, and use the K-means clustering method to divide the system practicality indicators according to the time dimension;

[0007] Step 2: Use the CRITIC method to measure the conflicts between different system practical indicators and achieve scientific and reasonable allocation of system practical indicator weights;

[0008] Step 3: Use the control charts in 6σ to standardize and continuously track the system's practical indicators.

[0009] As a preferred technical solution of the present invention, it also includes system practical feature calculation, and the corresponding steps are as follows:

[0010] ① Arrange the basic data of the system's practical indicators using a spatial rectangular coordinate system;

[0011] ② Select an initial cluster center for each cluster, initialize K cluster centers, and the maximum number of iterations is n;

[0012] ③ Assign the sample set D to the nearest neighbor cluster according to the minimum distance principle, and calculate the Euclidean distance from each object to each cluster center;

[0013] ④ Update the cluster center using the sample mean of each cluster;

[0014] ⑤ Repeat steps ② and ③ until the cluster center no longer changes;

[0015] ⑥Output the final cluster center and k clusters.

[0016] As a preferred technical solution of the present invention, the CRITIC method is used to measure the conflicts between different system practical indicators to achieve scientific and reasonable allocation of system practical indicator weights. The corresponding steps are as follows:

[0017] ①Data standardization

[0018] Suppose there are m objects to be evaluated and n evaluation indicators, which can form a data matrix X = (x ij ) m×n , let the element after the standardized processing of the data matrix be x′ ij ;

[0019] For positive indicators:

[0020]

[0021] For negative indicators:

[0022]

[0023] ② Calculate the information carrying capacity

[0024] First, calculate the contrast strength of the jth indicator:

[0025]

[0026] Then calculate the conflict between the evaluation indicators:

[0027] The conflict reflects the correlation between different indicators. If there is a significant positive correlation, the smaller the conflict value is. Let the conflict between indicator j and the other indicators be f. j ,but

[0028]

[0029] where rij represents the correlation coefficient between indicator i and indicator j;

[0030] Then calculate the information carrying capacity:

[0031] Calculate weights:

[0032]

[0033] It can be seen that the greater the information carrying capacity, the greater the weight;

[0034] Calculate the score:

[0035]

[0036] As a preferred technical solution of the present invention, the correlation coefficient adopts the Pearson correlation coefficient.

[0037] As a preferred technical solution of the present invention, the control chart is a tool for dynamically controlling the process, which is established on the basis of mathematical statistics and uses effective data to establish the boundary line.

[0038] As a preferred technical solution of the present invention, it also includes the function of the control diagram, which includes:

[0039] Analyze whether the production process is in a state of statistical control;

[0040] Determine when process adjustments are needed to control the production process and maintain the corresponding stable state;

[0041] Confirm whether a production process has been improved.

[0042] As a preferred technical solution of the present invention, it also includes three basic stages of control chart application: collection; control; analysis and improvement.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] A method for allocating weights of system practicality indicators is proposed to provide theoretical guidance for the allocation of weights of system practicality indicators, which is conducive to the stable operation of the system and improves the positive degree of system practicality level;

[0045] It not only conforms to the industry's general standards of the Internet trend, but also has a high degree of flexibility and adaptability, and can provide strong support for the digital transformation of enterprises. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is the diagram of the elbow method of the present invention;

[0047] Figure 2 For the present invention Control charts;

[0048] Figure 3 The figure is a flow chart of the calculation method of the present invention. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] See also Figure 1-Figure 3 The present invention provides a method for calculating the practicality index of an enterprise internal WEB system, comprising the following steps:

[0051] Step 1: Collect information such as the number of business process accesses, business process response time, business process page size, and business process dwell time, and use the K-means clustering method to divide the system practicality indicators according to the time dimension;

[0052] Step 2: Use the CRITIC method to measure the conflicts between different system practical indicators and achieve scientific and reasonable allocation of system practical indicator weights;

[0053] Step 3: Use the control charts in 6σ to standardize and continuously track the system's practical indicators.

[0054] In this embodiment, preferably, the K-means clustering algorithm is used to calculate the system practicality characteristics of the system on that day;

[0055] The practical features of the system are the number of business process accesses, the response time of the business process, the size of the business process page, the duration of the business process stay, etc., set the K value cluster, and take the industry general standards or system preset values ​​of the above four features as the k initial cluster center points; for example, the number of business process accesses A1 is clustered into 5 categories (<800 times, 800-1200 times, 1200-1500 times, 1500-2000 times, >2000 times);

[0056] The practical characteristic calculation of the system, the corresponding steps are as follows:

[0057] ① Arrange the basic data of the system's practical indicators using a spatial rectangular coordinate system;

[0058] The Y axis is the feature (such as times, seconds, kb), y>0, the X axis is time, m∈(0, 24), and the Z axis is the business process, z>0, which constitutes the system practical feature sample of each day

[0059] X={X1,X2,X3,...,X n}

[0060] ② Select an initial cluster center for each cluster, initialize K cluster centers, and the maximum number of iterations is n;

[0061] {C1, C2, C3, ..., C K},1 <j≤n

[0062] ③ Assign the sample set D to the nearest neighbor cluster according to the minimum distance principle, and calculate the Euclidean distance from each object to each cluster center;

[0063]

[0064]

[0065] ④ Update the cluster center using the sample mean of each cluster;

[0066] ⑤ Repeat steps ② and ③ until the cluster center no longer changes;

[0067] Introducing the Elbow method; Figure 1 It can be seen that the larger the K value is, the smaller the distance and the sum are. Moreover, when K=3, there is an inflection point, just like a person's elbow. When K(1,3), the curve drops rapidly. When K>3, the curve tends to be stable. The elbow method believes that the inflection point is the optimal value of J.

[0068] ⑥Output the final cluster center and k clusters.

[0069] In this embodiment, preferably, the CRITIC method is used to measure the conflicts between different system practicality indicators to achieve a scientific and reasonable allocation of system practicality indicator weights. The corresponding steps are as follows:

[0070] ①Data standardization

[0071] Suppose there are m objects to be evaluated and n evaluation indicators, which can form a data matrix X = (x ij ) m×n , let the element after the standardized processing of the data matrix be x′ ij ;

[0072] For positive indicators:

[0073]

[0074] For negative indicators:

[0075]

[0076] ② Calculate the information carrying capacity

[0077] First, calculate the contrast strength of the jth indicator:

[0078]

[0079] Then calculate the conflict between the evaluation indicators:

[0080] The conflict reflects the correlation between different indicators. If there is a significant positive correlation, the smaller the conflict value is. Let the conflict between indicator j and the other indicators be f. j ,but

[0081]

[0082] where r ij It represents the correlation coefficient between indicator i and indicator j. The correlation coefficient here adopts the Pearson correlation coefficient;

[0083] Then calculate the information carrying capacity:

[0084] Calculate weights:

[0085]

[0086] It can be seen that the greater the information carrying capacity, the greater the weight;

[0087] Calculate the score:

[0088]

[0089] In this embodiment, preferably, the control chart, also called the management chart, is a tool used to distinguish between fluctuations caused by abnormal reasons (system reasons) or fluctuations caused by random reasons inherent in the process; the control chart is a tool for dynamic control of the process, which is based on mathematical statistics and uses valid data to establish boundaries.

[0090] In this embodiment, preferably, the function of the control diagram is:

[0091] Used to analyze whether the production process is in a state of statistical control (stable state);

[0092] Used to determine when the process needs to be adjusted to control the production process and maintain the corresponding stable state;

[0093] Used to confirm whether a production process has been improved.

[0094] In this embodiment, preferably, three basic stages of control diagram application are also included:

[0095] Collect: collect data and draw it on the graph;

[0096] Control: Calculate test control limits based on process data; identify special causes of variation and take action;

[0097] Analysis and Improvement: Determine the magnitude of common cause variation and take steps to reduce it;

[0098] Control chart (mean-range management chart) specific steps:

[0099] Step 1: Take 25 sets of preliminary data;

[0100] Step 2: Calculate the mean of each sample group

[0101] Step 3: Calculate the range R of each sample group;

[0102] Step 4: Calculate the sample mean The sample mean range

[0103] Step 5: Calculate R graph and Parameters of the graph;

[0104] R chart calculation formula:

[0105]

[0106] The R graph is considered stable, so we then build picture:

[0107]

[0108] Finally, a control chart is obtained.

[0109] Although the embodiments of the present invention have been shown and described, as detailed above, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for calculating the practicality index of an enterprise internal WEB system, characterized by: The steps include: Step 1: Collect information on the number of business process visits, business process response time, business process page size, and business process stay time, and use the K-means clustering method to divide the system practicality indicators according to the time dimension; Step 2: Use the CRITIC method to measure the conflicts between different system practical indicators and achieve scientific and reasonable allocation of system practical indicator weights; Step 3: Use the control charts in 6σ to standardize and continuously track the system's practical indicators.

2. The method for calculating the practicality index of an enterprise internal WEB system according to claim 1 is characterized in that: It also includes the calculation of system practical characteristics, and the corresponding steps are as follows: ① Arrange the basic data of the system's practical indicators using a spatial rectangular coordinate system; ② Select an initial cluster center for each cluster, initialize K cluster centers, and the maximum number of iterations is n; ③ Assign the sample set D to the nearest neighbor cluster according to the minimum distance principle, and calculate the Euclidean distance from each object to each cluster center; ④ Update the cluster center using the sample mean of each cluster; ⑤ Repeat steps ② and ③ until the cluster center no longer changes; ⑥Output the final cluster center and k clusters.

3. The method for calculating the practicality index of an enterprise internal WEB system according to claim 1 is characterized in that: The CRITIC method is used to measure the conflicts between different system practical indicators and to achieve a scientific and reasonable allocation of the weights of system practical indicators. The corresponding steps are as follows: ①Data standardization Suppose there are m objects to be evaluated and n evaluation indicators, we can construct a data matrix X = (X ij ) m×n , let the element after the standardized processing of the data matrix be x′ ij ; For positive indicators: For negative indicators: ② Calculate the information carrying capacity First, calculate the contrast strength of the jth indicator: Then calculate the conflict between the evaluation indicators: The conflict reflects the correlation between different indicators. If there is a significant positive correlation, the smaller the conflict value is. Let the conflict between indicator j and the other indicators be f. j ,but where r ij represents the correlation coefficient between indicator i and indicator j; Then calculate the information carrying capacity: Calculate weights: It can be seen that the greater the information carrying capacity, the greater the weight; Calculate the score:

4. The method for calculating the practicality index of an enterprise internal WEB system according to claim 3 is characterized in that: The correlation coefficient adopts the Pearson correlation coefficient.

5. The method for calculating the practicality index of an enterprise internal WEB system according to claim 1 is characterized in that: The control chart is a tool for dynamically controlling a process, which is based on mathematical statistics and uses valid data to establish control lines.

6. The method for calculating the practicality index of an enterprise internal WEB system according to claim 5, characterized in that: It also includes the role of control charts, which include: Analyze whether the production process is in a state of statistical control; Determine when process adjustments are needed to control the production process and maintain the corresponding stable state; Confirm whether a production process has been improved.

7. The method for calculating the practicality index of an enterprise internal WEB system according to claim 6 is characterized by: It also includes the three basic stages of control chart application: collection; control; analysis and improvement.

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