A digital information processing method for port operation and maintenance business

Abstract

The present invention relates to the field of industrial information and data processing technology, and in particular to a method for processing digital information of port operation and maintenance business. The method comprises obtaining port operation and maintenance data, determining the principal component direction of the port operation and maintenance data; determining the field association between two operation and maintenance record fields according to the character difference and principal component direction of the operation and maintenance record fields in the port operation and maintenance data; obtaining an association group according to the field association of adjacent operation and maintenance record fields; determining the acceptable degree of data error according to the field association and position between the operation and maintenance record fields in the association group; making consistent adjustments to the operation and maintenance record fields to obtain adjustment fields; determining the adjusted operation and maintenance data; and compressing the adjusted operation and maintenance data to obtain an optimized compression result. The present invention can reduce the space required for storing the optimized compression result, improve the data compression efficiency and access efficiency, and facilitate the subsequent calling and extraction of the optimized compression result.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial information and data processing, and in particular to a method for processing digital information of port operation and maintenance services. Background Art

[0002] Industrial ports need to collect various types of port operation and maintenance data during operation. Through the analysis and digital information processing of port operation and maintenance data, it can support intelligent decision-making of industrial ports and promote the sustainable development of the industrial port industry. However, the amount of port operation and maintenance data is huge, and the data storage space of port operation and maintenance data is high.

[0003] In the related technology, compression algorithms are used to compress and store port operation and maintenance data. In this way, since the port operation and maintenance data itself has a small data fluctuation range but a large fluctuation frequency, more storage space will be occupied when compressing the data, resulting in low data compression efficiency and access efficiency, which is not conducive to the subsequent call and extraction of optimized compression results, and the digital and intelligent storage and processing effect of port operation and maintenance data is insufficient. Summary of the invention

[0004] In order to solve the problem that the related technology occupies more storage space when compressing data, resulting in low data compression efficiency and access efficiency, which is not conducive to the subsequent call and extraction of the optimized compression results, and the digital and intelligent storage and processing effect of port operation and maintenance data is insufficient, the present invention provides a method for digital information processing of port operation and maintenance business, and the technical scheme adopted is as follows:

[0005] The present invention proposes a method for processing digital information of port operation and maintenance services, the method comprising:

[0006] Acquire at least two types of port operation and maintenance data, wherein the port operation and maintenance data includes an operation and maintenance record field; construct a multidimensional sample space with each operation and maintenance record field as a feature dimension, and determine the principal component direction of the port operation and maintenance data in the multidimensional sample space;

[0007] Determine the similarity between any two operation and maintenance record fields according to the character differences between any two operation and maintenance record fields in the same type of port operation and maintenance data; take the dimensional plane corresponding to any two operation and maintenance record fields in the multidimensional sample space as the plane to be measured, and determine the field correlation between the two operation and maintenance record fields according to the angle between the principal component direction and the plane to be measured and the similarity between the two operation and maintenance record fields;

[0008] According to the field association degree of the two operation and maintenance record fields that are closest to each other, the operation and maintenance record fields are combined to obtain an association group; according to the field association degree between two operation and maintenance record fields in the same association group and the position of all operation and maintenance record fields in the port operation and maintenance data, the data error acceptance degree of the association group is determined; according to the data error acceptance degree, the operation and maintenance record fields in the association group are adjusted to be consistent to obtain an adjusted field;

[0009] The adjustment field is used to replace the corresponding operation and maintenance record field in the port operation and maintenance data to obtain the adjusted operation and maintenance data; and the adjusted operation and maintenance data is compressed to obtain an optimized compression result.

[0010] Furthermore, the determining the similarity between any two operation and maintenance record fields in the same type of port operation and maintenance data according to the character difference between the two operation and maintenance record fields includes:

[0011] Based on the binary coding algorithm, each operation and maintenance record field is encoded into a binary field, and the same bits in the binary fields of any two operation and maintenance record fields are XORed to obtain the binary difference;

[0012] The number of bits that are 0 in the binary difference is taken as the number of similar bits, and the ratio of the number of similar bits to the total number of bits of the binary field is calculated as the degree of similarity between the two operation and maintenance record fields.

[0013] Further, determining the field correlation between the two operation and maintenance record fields according to the angle between the principal component direction and the plane to be measured and the similarity between the two operation and maintenance record fields includes:

[0014] Calculate the cosine value of the angle between the principal component direction and the plane to be measured based on the cosine formula to obtain an angle similarity factor;

[0015] The field correlation degree between the two operation and maintenance record fields is determined according to the similarity between the angle similarity factor and the two operation and maintenance record fields.

[0016] Further, determining the field correlation between the two operation and maintenance record fields according to the similarity between the angle similarity factor and the two operation and maintenance record fields includes:

[0017] The normalized value of the product of the angle similarity factor and the similarity degree is calculated to obtain the field correlation between the two operation and maintenance record fields.

[0018] Furthermore, the operation and maintenance record fields are combined according to the field association degree of the two operation and maintenance record fields that are closest to each other to obtain an association group, including:

[0019] Combine adjacent operation and maintenance record fields whose field correlation is greater than or equal to a preset correlation threshold to obtain an operation and maintenance group;

[0020] The closest operation and maintenance record field outside the operation and maintenance group is used as the field to be added;

[0021] When the field correlation between the field to be added and all the operation and maintenance record fields in the operation and maintenance group is greater than or equal to a preset correlation threshold, the field to be added is added to the operation and maintenance group, and the operation and maintenance group is updated to obtain a new operation and maintenance group;

[0022] Otherwise, the operation and maintenance group is taken as an associated group, and all operation and maintenance record fields are traversed to obtain all associated groups, wherein the operation and maintenance record fields in different associated groups do not overlap.

[0023] Further, determining the acceptable degree of data error of the association group according to the field association between two operation and maintenance record fields in the same association group and the positions of all operation and maintenance record fields in the port operation and maintenance data includes:

[0024] Any two different operation and maintenance record fields in the association group are used as the first analysis segment and the second analysis segment;

[0025] Performing inverse proportional normalization processing on the number of operation and maintenance record fields between the first analysis segment and the second analysis segment to obtain a distance impact weight;

[0026] Calculating a normalized value of the product of the distance influence weight and the field association degree of the first analysis segment and the second analysis segment to obtain an error acceptance factor;

[0027] The acceptable degree of data error of the associated group is determined according to the error acceptance factors of any two different operation and maintenance record fields in the associated group.

[0028] Further, determining the acceptable degree of data error of the association group according to the error acceptance factors of any two different operation and maintenance record fields in the association group includes:

[0029] Calculating the mean of the error acceptance factors of the first analysis segment and all other operation and maintenance record fields in the association group as the segment error coefficient of the first analysis segment;

[0030] The normalized value of the mean of the segment error coefficients of all operation and maintenance record fields in the association group is calculated to obtain the data error acceptability of the association group.

[0031] Furthermore, the operation and maintenance record fields in the association group are adjusted to be consistent according to the acceptable degree of data error to obtain the adjusted fields, including:

[0032] When the data error acceptability of the associated group is greater than a preset acceptability threshold, the mean of the operation and maintenance record data in the associated group is calculated to obtain the data mean, and the operation and maintenance record data is adjusted to the data mean to obtain an adjustment field.

[0033] Further, compressing the adjusted operation and maintenance data to obtain an optimized compression result includes:

[0034] The adjustment operation and maintenance data is compressed and encoded based on the LZ77 algorithm, and the encoding value obtained by the compression encoding is used as the optimized compression result.

[0035] Furthermore, the determining the principal component direction of the port operation and maintenance data in the multidimensional sample space includes:

[0036] Based on the principal component analysis algorithm, principal component analysis is performed on the port operation and maintenance data to obtain the principal component directions in the multidimensional sample space.

[0037] The present invention has the following beneficial effects:

[0038] The present invention obtains port operation and maintenance data, and determines the direction of the principal component according to the numerical distribution of the operation and maintenance record field in the port operation and maintenance data, and then determines the degree of similarity according to the character difference of the operation and maintenance record field in the port operation and maintenance data, and determines the field association degree between two operation and maintenance record fields in combination with the principal component direction and the degree of similarity, wherein the field association degree is the degree of association between the two operation and maintenance record fields, and the larger the value, the higher the degree of association between the two operation and maintenance record fields, and the higher the numerical similarity. Afterwards, an association group is determined according to the field association degree, so that data with high similarity are gathered together, and the acceptable degree of data error of the association group is determined in combination with the field association degree and position of the operation and maintenance record field in the same association group, and the acceptable degree of data error is the degree of influence of data changes in the operation and maintenance record field in the association group, and the higher the value, the smaller the influence of data changes, and the more data can be modified, thereby performing consistency adjustment on the association group, obtaining the adjustment field, and obtaining the adjusted operation and maintenance data, and the adjusted operation and maintenance data is the data that has been adjusted by data consistency, and the data repeatability is high, which is convenient for subsequent encoding and compression of the adjusted operation and maintenance data to obtain an optimized compression result. The present invention adjusts the consistency of fields with high similarity and small error impact by means of data consistency adjustment, thereby improving the repeatability of the adjusted operation and maintenance data. When the adjusted operation and maintenance data is compressed, the space required for storing the optimized compression results is reduced, further improving the data compression efficiency and access efficiency, facilitating the subsequent calling and extraction of the optimized compression results, and realizing the digital and intelligent storage and processing of port operation and maintenance data. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0040] Figure 1 A flow chart of a method for digital information processing of port operation and maintenance services provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0041] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, features and effects of a digital information processing method for port operation and maintenance business proposed by the present invention in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0042] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0043] The specific scheme of the digital information processing method for port operation and maintenance business provided by the present invention is described in detail below with reference to the accompanying drawings.

[0044] See also Figure 1 , which shows a flow chart of a method for digital information processing of port operation and maintenance services provided by an embodiment of the present invention, the method comprising:

[0045] S101: Acquire at least two types of port operation and maintenance data, wherein the port operation and maintenance data includes an operation and maintenance record field; construct a multidimensional sample space with each operation and maintenance record field as a feature dimension, and determine the principal component direction of the port operation and maintenance data in the multidimensional sample space.

[0046] Among them, port operation and maintenance data is the data generated by the industrial port during its operation. Port operation and maintenance data can include multiple types, such as equipment monitoring data, cargo loading and unloading data, ship queuing data, etc. Since the overall operation of the industrial port has a relatively obvious regularity, the throughput of the port in different time periods is within a smaller range, and the operation of the industrial port changes less. Therefore, the same type of port operation and maintenance data has a smaller data fluctuation range, but a larger data fluctuation frequency, and a lower requirement for data error. The embodiment of the present invention can encode and compress the data based on this feature to improve the compression rate and enhance the compression effect. A specific application scenario of the present invention includes encoding and compressing the collected port operation and maintenance data to facilitate the management of the port operation and maintenance data and improve the efficiency, quality and safety of the industrial port operation and maintenance business.

[0047] In an embodiment of the present invention, port operation and maintenance data can be extracted from a corresponding database or cloud. The port operation and maintenance data is an operation and maintenance record field in time series. For example, taking cargo loading and unloading data as a specific example, the cargo loading and unloading volume from 8:00 to 9:00 on a certain day is 50 tons, and 50 is used as the corresponding operation and maintenance record field. Similarly, the cargo loading and unloading volume of each hour of the day is counted to obtain 24 operation and maintenance record fields, which are composed of the cargo loading and unloading data of the day in time series. Of course, the port operation and maintenance data can also be other types of data, and the corresponding time period is not limited. However, under the same time period, due to the operation load planning of the port itself, the data fluctuation range of the port operation and maintenance data is relatively small.

[0048] In the embodiment of the present invention, a multidimensional sample space can be constructed based on different operation and maintenance record fields, and each operation and maintenance record field can be used as a dimension to perform principal component analysis on the port operation and maintenance data.

[0049] Furthermore, in some embodiments of the present invention, determining the principal component direction of the port operation and maintenance data in the multidimensional sample space includes: performing principal component analysis on the port operation and maintenance data based on a principal component analysis algorithm to obtain the principal component direction in the multidimensional sample space.

[0050] Among them, the principal component analysis algorithm can be specifically, for example, a principal component dimensionality reduction analysis (PCA) algorithm, that is, high-dimensional data is cleaned in the form of linear transformation to obtain the projection of the high-dimensional data in a low-dimensional space, thereby realizing principal component analysis. The PCA algorithm is an algorithm well known to those skilled in the art. Of course, the present invention also supports the use of a variety of other possible principal component analysis algorithms, or optimization algorithms of the principal component analysis algorithm, without limitation.

[0051] In the embodiment of the present invention, by performing principal component analysis, the principal component direction of the port operation and maintenance data can be obtained, and the principal component direction represents the main numerical characteristics of the corresponding port operation and maintenance data, which facilitates subsequent specific data analysis according to the principal component direction.

[0052] S102: Determine the similarity between any two operation and maintenance record fields based on the character differences between the two operation and maintenance record fields in the same type of port operation and maintenance data; take the dimensional plane corresponding to any two operation and maintenance record fields in the multidimensional sample space as the plane to be tested, and determine the field correlation between the two operation and maintenance record fields based on the angle between the principal component direction and the plane to be tested and the similarity between the two operation and maintenance record fields.

[0053] It is understandable that the same type of port operation and maintenance data has a smaller range of data variation, that is, during the port operation and maintenance process, the time series fluctuation range is smaller. For example, the number of cargo ships received each day has corresponding plans to enable the port to operate more efficiently.

[0054] Among them, the character difference, that is, the character difference of the operation and maintenance record field during the storage process, it can be understood that the operation and maintenance record field is stored using binary machine code. Therefore, the character difference of the present invention is mainly a binary encoding difference.

[0055] Furthermore, in some embodiments of the present invention, the degree of similarity between two operation and maintenance record fields is determined based on the character differences between any two operation and maintenance record fields in the same type of port operation and maintenance data, including: based on a binary coding algorithm, encoding each operation and maintenance record field into a binary field, performing an XOR operation on the same number of bits in the binary fields of any two operation and maintenance record fields to obtain a binary difference; taking the number of bits that are 0 in the binary difference as the number of similar bits, and calculating the ratio of the number of similar bits to the total number of bits in the binary field as the degree of similarity between the two operation and maintenance record fields.

[0056] In the embodiment of the present invention, the operation and maintenance record fields may be binary-coded to obtain the binary fields corresponding to each operation and maintenance record field, thereby performing similarity analysis on the binary fields of two operation and maintenance record fields.

[0057] For example, when the two operation and maintenance record fields are "153" and "120" respectively, the binary field corresponding to "153" is "10011001", and the binary field corresponding to "120" is "1111000", then the same digits in the binary fields of the two operation and maintenance record fields are subjected to an XOR operation, wherein the XOR operation, that is, when the numbers corresponding to the same digits are different, the output is "1", and when the numbers corresponding to the same digits are the same, the output is "0", thus, the binary difference between "10011001" and "1111000" is calculated to be "01101001", wherein There are 4 0 bits, that is, the similarity bit number of the operation and maintenance record fields "153" and "120" is 4. Similarly, the similarity bit number of "153" and "152" can be calculated to be 7. Since the numerical fluctuation of the port operation and maintenance data is small, that is, the fluctuation process of the port during operation is small, the difference in the number of similar bits can effectively characterize the similarity between the two operation and maintenance record fields. In this embodiment of the present invention, the ratio of the number of similar bits to the total number of bits of the binary field can be calculated, that is, when the number of similar bits is 4 and the total number of bits of the binary field is 8, the corresponding similarity is 0.5, which is convenient for subsequent coding analysis based on the similarity.

[0058] In an embodiment of the present invention, the dimensional plane corresponding to any two operation and maintenance record fields in the multidimensional sample space is used as the plane to be measured, that is, the dimensions corresponding to the two operation and maintenance record fields are combined into a plane, and the plane is the plane to be measured. The two operation and maintenance record fields can be correlated and analyzed based on the angle characteristics between the principal component direction and the plane to be measured.

[0059] Furthermore, in some embodiments of the present invention, the field correlation between two operation and maintenance record fields is determined based on the angle between the principal component direction and the plane to be measured and the similarity between the two operation and maintenance record fields, including: calculating the cosine value of the angle between the principal component direction and the plane to be measured based on the cosine formula to obtain the angle similarity factor; determining the field correlation between the two operation and maintenance record fields based on the angle similarity factor and the similarity between the two operation and maintenance record fields.

[0060] It can be understood that the larger the angle between the principal component direction and the corresponding plane, the greater the difference between the operation and maintenance record field and the principal component, that is, the more the two operation and maintenance record fields deviate from the main distribution of the port operation and maintenance data, and the lower the correlation between the operation and maintenance record fields. Therefore, the present invention calculates the cosine value of the angle between the principal component direction and the plane to be measured. When the cosine value is larger, the angle similarity factor is larger, and the corresponding angle between the principal component direction and the corresponding plane is smaller.

[0061] Then, the field correlation can be analyzed by combining the angle similarity factor with the similarity between the two operation and maintenance record fields.

[0062] Furthermore, in some embodiments of the present invention, the field correlation between two operation and maintenance record fields is determined based on the angle similarity factor and the degree of similarity between the two operation and maintenance record fields, including: calculating the normalized value of the product of the angle similarity factor and the degree of similarity to obtain the field correlation between the two operation and maintenance record fields.

[0063] Since the larger the angle similarity factor, the smaller the angle between the corresponding principal component direction and the corresponding plane, that is, the higher the correlation between the operation and maintenance record fields, and the similarity represents the similarity of the binary field of the two operation and maintenance record fields, the higher the value, the higher the correlation between the corresponding two operation and maintenance record fields. Therefore, it can be determined that the angle similarity factor and the similarity are positively correlated with the field correlation. The product of the angle similarity factor and the similarity is calculated, and the product is normalized to obtain the field correlation.

[0064] In one embodiment of the present invention, the normalization processing can be specifically, for example, maximum and minimum value normalization processing, and the normalization in subsequent steps can all adopt maximum and minimum value normalization processing. In other embodiments of the present invention, other normalization methods can be selected according to the specific range of numerical values, which will not be described in detail.

[0065] S103: According to the field correlation between the two closest operation and maintenance record fields, the operation and maintenance record fields are combined to obtain an associated group; according to the field correlation between two operation and maintenance record fields in the same associated group and the position of all operation and maintenance record fields in the port operation and maintenance data, the acceptable degree of data error of the associated group is determined; according to the acceptable degree of data error, the operation and maintenance record fields in the associated group are adjusted to be consistent to obtain an adjusted field.

[0066] In the embodiment of the present invention, after determining the field correlation between any two operation and maintenance record fields, the operation and maintenance record fields may be merged in combination with the distribution of the operation and maintenance record fields in the port operation and maintenance data.

[0067] Furthermore, in some embodiments of the present invention, the operation and maintenance record fields are combined according to the field correlation of the two closest operation and maintenance record fields to obtain an associated group, including: combining adjacent operation and maintenance record fields whose field correlation is greater than or equal to a preset correlation threshold to obtain an operation and maintenance group; taking the closest operation and maintenance record fields outside the operation and maintenance group as fields to be added; when the field correlation between the field to be added and all operation and maintenance record fields in the operation and maintenance group is greater than or equal to the preset correlation threshold, adding the field to be added to the operation and maintenance group, updating the operation and maintenance group, and obtaining a new operation and maintenance group; otherwise, taking the operation and maintenance group as an associated group, traversing all operation and maintenance record fields to obtain all associated groups, wherein the operation and maintenance record fields in different associated groups do not overlap.

[0068] It is understandable that since the port operation and maintenance data are time-series data such as cargo loading and unloading data and ship queuing data, and during the port operation and maintenance process, the time-series data corresponding to adjacent moments change little, that is to say, the same type of operation and maintenance record fields corresponding to adjacent moments have a very small probability of numerical fluctuations or even no numerical changes. Based on this, the present invention combines adjacent operation and maintenance record fields for unified analysis.

[0069] Among them, the preset association threshold is the threshold value of the field association degree. Optionally, the preset association threshold can be specifically, for example, 0.85, that is, adjacent operation and maintenance record fields with a field association degree greater than or equal to 0.85 are combined to obtain an operation and maintenance group. It can be understood that the present invention needs to analyze all operation and maintenance record fields, and the analysis process is a regional growth process. For example, there are 5 operation and maintenance record fields in the port operation and maintenance data, namely field 1, field 2, field 3, field 4 and field 5. The present invention can first analyze whether the field association degree between field 1 and field 2 is greater than or equal to 0.85. When it is greater than or equal to 0.85, field 1 and field 2 are combined into an operation and maintenance group, and then field 3 is used as a field to be added. When the field association degree between field 3 and field 1 and the field association degree between field 3 and field 2 are both greater than or equal to 0.85, field 3 is added to the operation and maintenance group to obtain a new operation and maintenance group. At this time, the operation and maintenance group includes field 1, field 2 and field 3, and then field 4 is used as a field to be added and the analysis continues. When the field correlation between field 3 and at least one of field 1 or field 2 is less than 0.85, the operation and maintenance group composed of field 1 and field 2 is used as the association group, and the field correlation between field 3 and field 4 is determined, so as to analyze the new operation and maintenance group, thereby traversing all operation and maintenance record fields and dividing all operation and maintenance record fields into association groups. It can be understood that there is no overlap between association groups, that is, an operation and maintenance record field can only belong to one association group.

[0070] Furthermore, in some embodiments of the present invention, the acceptable degree of data error of the association group is determined based on the field correlation between two operation and maintenance record fields in the same association group and the positions of all operation and maintenance record fields in the port operation and maintenance data, including: taking any two different operation and maintenance record fields in the association group as the first analysis segment and the second analysis segment; performing inverse proportional normalization processing on the number of operation and maintenance record fields between the first analysis segment and the second analysis segment to obtain the distance impact weight; calculating the normalized value of the product of the distance impact weight of the first analysis segment and the second analysis segment and the field correlation to obtain the error acceptance factor; and determining the acceptable degree of data error of the association group based on the error acceptance factor of any two different operation and maintenance record fields in the association group.

[0071] In an embodiment of the present invention, it is necessary to analyze two different operation and maintenance record fields in an associated group. It can be understood that the larger the interval between the two operation and maintenance record fields, that is, the larger the interval in the record time sequence, the smaller the degree of influence. Therefore, the present invention characterizes the influence between the operation and maintenance record fields through the distance influence weight.

[0072] In an embodiment of the present invention, an inversely proportional normalized value of the number of operation and maintenance record fields between the first analysis segment and the second analysis segment can be calculated as the distance impact weight, that is, the more operation and maintenance record fields there are between the first analysis segment and the second analysis segment, the smaller the corresponding distance impact weight, wherein the inversely proportional normalization is an inversely correlated normalization, indicating that the dependent variable will decrease as the independent variable increases, and the dependent variable will increase as the independent variable decreases, which can be a subtraction relationship, a division relationship, etc., then an embodiment of the present invention can calculate the negative number of the number of operation and maintenance record fields between the first analysis segment and the second analysis segment, and normalize the negative number to obtain the distance impact weight.

[0073] The present invention also calculates the normalized value of the product of the distance influence weight and the field correlation between the first analysis segment and the second analysis segment to obtain the error acceptance factor. Because the larger the distance influence weight, the greater the influence effect between the first analysis segment and the second analysis segment, and the higher the field correlation, the higher the degree of correlation between the first analysis segment and the second analysis segment. Therefore, the field correlation can be weighted based on the distance influence weight, and then normalized to obtain the error acceptance factor.

[0074] The error acceptance factor is the error acceptance capacity of the corresponding operation and maintenance record field. The higher the correlation between the first analysis segment and the second analysis segment, the smaller the impact of subsequent data changes on them. The higher the error acceptance capacity, the larger the error acceptance factor.

[0075] Furthermore, in some embodiments of the present invention, the data error acceptability of the associated group is determined based on the error acceptance factors of any two different operation and maintenance record fields in the associated group, including: calculating the mean of the error acceptance factors of the first analysis segment and all other operation and maintenance record fields in the associated group as the segment error coefficient of the first analysis segment; calculating the normalized value of the mean of the segment error coefficients of all operation and maintenance record fields in the associated group to obtain the data error acceptability of the associated group.

[0076] The acceptable degree of data error refers to the degree of impact of data changes in the operation and maintenance record fields in the associated group. When the data consistency of the operation and maintenance record fields in the associated group is higher, the corresponding data change impact is smaller and the acceptable degree of data error is higher.

[0077] Therefore, the present invention calculates the mean of the error acceptance factors of the first analysis segment and all other operation and maintenance record fields in the associated group as the segment error coefficient of the first analysis segment; calculates the normalized value of the mean of the segment error coefficients of all operation and maintenance record fields in the associated group, that is, performs a total analysis on all the operation and maintenance record fields in the associated group, thereby obtaining the acceptability of data errors.

[0078] For example, there are three operation and maintenance record fields, namely field 1, field 2 and field 3, in the associated group. The mean of the corresponding error acceptance factor of field 1, field 2 and field 3 is calculated as the segment error coefficient of field 1, and then the segment error coefficients of field 2 and field 3 are obtained in the same way. The segment error coefficients of field 1, field 2 and field 3 are averaged and normalized to obtain the data error acceptability of the associated group.

[0079] After obtaining the data error acceptability of the associated group, consistency analysis may be performed based on the data error acceptability.

[0080] Furthermore, in some embodiments of the present invention, the operation and maintenance record fields in the associated group are adjusted to be consistent according to the acceptable degree of data error to obtain the adjusted field, including: when the acceptable degree of data error in the associated group is greater than a preset acceptable degree threshold, calculating the mean of the operation and maintenance record data in the associated group to obtain the data mean, and adjusting the operation and maintenance record data to the data mean to obtain the adjusted field.

[0081] In an embodiment of the present invention, the preset acceptability threshold is a threshold value of the acceptability of data errors, wherein the preset acceptability threshold may be specifically, for example, 0.8, that is, when the acceptability of the data error of the associated group is greater than, the associated group is regarded as being able to accept the corresponding data error, thereby obtaining convenience in data compression.

[0082] Since the data in the same association group differs little, the present invention can use the mean value to unify, that is, update all operation and maintenance record data in the corresponding association group to the data mean value, thereby obtaining the adjustment field. Thus, all association groups are analyzed and adjusted to improve the repeatability of the overall operation and maintenance record data.

[0083] S104: using the adjustment field to replace the corresponding operation and maintenance record field in the port operation and maintenance data to obtain the adjusted operation and maintenance data; and compressing the adjusted operation and maintenance data to obtain an optimized compression result.

[0084] In an embodiment of the present invention, an adjustment field can be used to replace the corresponding operation and maintenance record field in the port operation and maintenance data, that is, the port operation and maintenance data is updated. It can be understood that since the adjustment fields in the same association group are the same fields, the repeatability of the adjusted operation and maintenance data can be effectively improved.

[0085] Furthermore, in some embodiments of the present invention, the operation and maintenance data is compressed to obtain an optimized compression result, including: compressing and encoding the operation and maintenance data based on the LZ77 algorithm, and using the encoding value obtained by the compression encoding as the optimized compression result.

[0086] It can be understood that the LZ77 algorithm is a dictionary-based coding compression algorithm. The higher the repeatability of the data, the greater the compression rate of the LZ77 algorithm, that is, the smaller the bytes occupied by the compressed data. Therefore, based on the small changes in the port operation and maintenance process, that is, the small data fluctuations of the port operation and maintenance data, the present invention performs consistency processing and compression on the port operation and maintenance data, thereby obtaining an optimized compression result. The optimized compression result can be used for subsequent port operation and maintenance data recording, storage and query, so as to improve the digital information service effect of the port operation and maintenance data.

[0087] The present invention obtains port operation and maintenance data, and determines the direction of the principal component according to the numerical distribution of the operation and maintenance record field in the port operation and maintenance data, and then determines the degree of similarity according to the character difference of the operation and maintenance record field in the port operation and maintenance data, and determines the field association degree between two operation and maintenance record fields in combination with the principal component direction and the degree of similarity, wherein the field association degree is the degree of association between the two operation and maintenance record fields, and the larger the value, the higher the degree of association between the two operation and maintenance record fields, and the higher the numerical similarity. Afterwards, an association group is determined according to the field association degree, so that data with high similarity are gathered together, and the acceptable degree of data error of the association group is determined in combination with the field association degree and position of the operation and maintenance record field in the same association group, and the acceptable degree of data error is the degree of influence of data changes in the operation and maintenance record field in the association group, and the higher the value, the smaller the influence of data changes, and the more data can be modified, thereby performing consistency adjustment on the association group, obtaining the adjustment field, and obtaining the adjusted operation and maintenance data, and the adjusted operation and maintenance data is the data that has been adjusted by data consistency, and the data repeatability is high, which is convenient for subsequent encoding and compression of the adjusted operation and maintenance data to obtain an optimized compression result. The present invention adjusts the consistency of fields with high similarity and small error impact by means of data consistency adjustment, thereby improving the repeatability of the adjusted operation and maintenance data. When the adjusted operation and maintenance data is compressed, the space required for storing the optimized compression results is reduced, further improving the data compression efficiency and access efficiency, facilitating the subsequent calling and extraction of the optimized compression results, and realizing the digital and intelligent storage and processing of port operation and maintenance data.

[0088] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0089] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A method for digital information processing of port operation and maintenance business, characterized in that: The method comprises: Acquire at least two types of port operation and maintenance data, wherein the port operation and maintenance data includes an operation and maintenance record field; construct a multidimensional sample space with each operation and maintenance record field as a feature dimension, and determine the principal component direction of the port operation and maintenance data in the multidimensional sample space; Determine the similarity between any two operation and maintenance record fields according to the character differences between any two operation and maintenance record fields in the same type of port operation and maintenance data; take the dimensional plane corresponding to any two operation and maintenance record fields in the multidimensional sample space as the plane to be measured, and determine the field correlation between the two operation and maintenance record fields according to the angle between the principal component direction and the plane to be measured and the similarity between the two operation and maintenance record fields; According to the field association degree of the two operation and maintenance record fields that are closest to each other, the operation and maintenance record fields are combined to obtain an association group; according to the field association degree between two operation and maintenance record fields in the same association group and the position of all operation and maintenance record fields in the port operation and maintenance data, the data error acceptance degree of the association group is determined; according to the data error acceptance degree, the operation and maintenance record fields in the association group are adjusted to be consistent to obtain an adjusted field; Using the adjustment field to replace the corresponding operation and maintenance record field in the port operation and maintenance data to obtain adjusted operation and maintenance data; compressing the adjusted operation and maintenance data to obtain an optimized compression result; Determining the acceptable degree of data error of the association group according to the field association between two operation and maintenance record fields in the same association group and the positions of all operation and maintenance record fields in the port operation and maintenance data includes: Any two different operation and maintenance record fields in the association group are used as the first analysis segment and the second analysis segment; Performing inverse proportional normalization processing on the number of operation and maintenance record fields between the first analysis segment and the second analysis segment to obtain a distance impact weight; Calculating a normalized value of the product of the distance influence weight and the field association degree of the first analysis segment and the second analysis segment to obtain an error acceptance factor; The acceptable degree of data error of the associated group is determined according to the error acceptance factors of any two different operation and maintenance record fields in the associated group.

2. A method for digital information processing of port operation and maintenance services as claimed in claim 1, characterized in that: Determining the similarity of two operation and maintenance record fields according to the character difference between any two operation and maintenance record fields in the same type of port operation and maintenance data includes: Based on the binary coding algorithm, each operation and maintenance record field is encoded into a binary field, and the same bits in the binary fields of any two operation and maintenance record fields are XORed to obtain the binary difference; The number of bits that are 0 in the binary difference is taken as the number of similar bits, and the ratio of the number of similar bits to the total number of bits of the binary field is calculated as the degree of similarity between the two operation and maintenance record fields.

3. A method for digital information processing of port operation and maintenance services as claimed in claim 1, characterized in that: The determining the field correlation between the two operation and maintenance record fields according to the angle between the principal component direction and the plane to be measured and the similarity between the two operation and maintenance record fields includes: Calculate the cosine value of the angle between the principal component direction and the plane to be measured based on the cosine formula to obtain an angle similarity factor; The field correlation degree between the two operation and maintenance record fields is determined according to the similarity between the angle similarity factor and the two operation and maintenance record fields.

4. A method for digital information processing of port operation and maintenance services as claimed in claim 3, characterized in that: Determining the field association degree between the two operation and maintenance record fields according to the similarity between the angle similarity factor and the two operation and maintenance record fields includes: The normalized value of the product of the angle similarity factor and the similarity degree is calculated to obtain the field correlation between the two operation and maintenance record fields.

5. A method for digital information processing of port operation and maintenance services as claimed in claim 1, characterized in that: The operation and maintenance record fields are combined according to the field association degree of the two operation and maintenance record fields that are closest to each other to obtain an association group, including: Combine adjacent operation and maintenance record fields whose field correlation is greater than or equal to a preset correlation threshold to obtain an operation and maintenance group; The closest operation and maintenance record field outside the operation and maintenance group is used as the field to be added; When the field correlation between the field to be added and all the operation and maintenance record fields in the operation and maintenance group is greater than or equal to a preset correlation threshold, the field to be added is added to the operation and maintenance group, and the operation and maintenance group is updated to obtain a new operation and maintenance group; Otherwise, the operation and maintenance group is taken as an associated group, and all operation and maintenance record fields are traversed to obtain all associated groups, wherein the operation and maintenance record fields in different associated groups do not overlap.

6. A method for digital information processing of port operation and maintenance services as claimed in claim 1, characterized in that: The determining the acceptable degree of data error of the association group according to the error acceptance factors of any two different operation and maintenance record fields in the association group includes: Calculating the mean of the error acceptance factors of the first analysis segment and all other operation and maintenance record fields in the association group as the segment error coefficient of the first analysis segment; The normalized value of the mean of the segment error coefficients of all operation and maintenance record fields in the association group is calculated to obtain the data error acceptability of the association group.

7. A method for digital information processing of port operation and maintenance services as claimed in claim 1, characterized in that: The step of adjusting the operation and maintenance record fields in the association group to be consistent according to the acceptable degree of data error to obtain the adjustment fields includes: When the data error acceptability of the associated group is greater than a preset acceptability threshold, the mean of the operation and maintenance record data in the associated group is calculated to obtain the data mean, and the operation and maintenance record data is adjusted to the data mean to obtain an adjustment field.

8. A method for digital information processing of port operation and maintenance services as claimed in claim 1, characterized in that: The compressing the adjusted operation and maintenance data to obtain an optimized compression result includes: The adjustment operation and maintenance data is compressed and encoded based on the LZ77 algorithm, and the encoding value obtained by the compression encoding is used as the optimized compression result.

9. A method for digital information processing of port operation and maintenance services as claimed in claim 1, characterized in that: Determining the principal component direction of the port operation and maintenance data in the multidimensional sample space includes: Based on the principal component analysis algorithm, principal component analysis is performed on the port operation and maintenance data to obtain the principal component directions in the multidimensional sample space.

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