CN117014519B - Data transmission method and intelligent hospital transmission system - Google Patents
Data transmission method and intelligent hospital transmission system Download PDFInfo
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- H—ELECTRICITY
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- H—ELECTRICITY
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- H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
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Abstract
The invention relates to the technical field of electric digital data processing, and provides a data transmission method and a hospital intelligent transmission system, comprising the following steps: acquiring a character string to be compressed according to patient treatment data; according to the character strings to be compressed, redundant character strings are obtained, each redundant character string is matched with the character strings to be compressed, redundant character strings and matching points on the character strings to be compressed are obtained, and the global compression necessity of the character strings to be compressed is calculated; acquiring the window length of a search buffer zone of the character string to be compressed according to the information entropy of the character string to be compressed, the global compression necessity and the distance between adjacent matching points on the character string to be compressed; and according to the window length of the search buffer zone, compressing the patient treatment data by using a compression algorithm, obtaining a compression result of the patient treatment data, and transmitting the compression result of the patient treatment data. The invention aims to solve the problem of low compression efficiency caused by improper window length setting of a search buffer.
Description
Technical Field
The invention relates to the technical field of electric digital data processing, in particular to a data transmission method and an intelligent hospital transmission system.
Background
With the development of medical technology and the popularization of digital medical systems, the amount of patient treatment data generated by medical institutions is increasing, doctors, nurses and other medical workers need to frequently share and transmit the patient treatment data in a medical information system, and a hospital intelligent system gives preliminary diagnosis advice or provides reference for auxiliary decision making by analyzing the patient treatment data so as to help doctors to perform accurate diagnosis. Therefore, the real-time performance of the patient treatment data transmission is important for the diagnosis and treatment of the patient, the time and the network bandwidth required by the data transmission can be reduced by compressing the data, the data transmission efficiency is improved, and currently, the data compression technology is often used for reducing the size of the data so as to improve the transmission efficiency.
The existing LZ77 compression algorithm is used as a common data compression algorithm, so that the advantage of data locality is fully exerted, but for the patient treatment data with higher global repeatability, the similarity among character strings is not considered, the window length of a search buffer is improperly set, and the compression efficiency is lower. Thus, patient visit data is not efficient to transmit in a hospital intelligence system.
Disclosure of Invention
In order to solve the technical problems, the invention aims to provide a data transmission method and a hospital intelligent transmission system, and the adopted technical scheme is as follows:
in a first aspect, an embodiment of the present invention provides a data transmission method, including the steps of:
acquiring a character string to be compressed according to patient treatment data;
obtaining a matching character string according to the character string to be compressed, and constructing a global matching character string set; according to the length and the repetition number of the matching character strings in the global matching character string set, calculating the similarity redundancy of the matching character strings, and obtaining redundant character strings; matching each redundant character string with the character string to be compressed to obtain redundant character strings and matching points on the character strings to be compressed; calculating the global repetition rate of the character strings to be compressed according to the lengths of the character strings to be compressed and the lengths of all redundant character strings on the character strings to be compressed;
calculating the global compression necessity of the character strings to be compressed according to the global repetition rate of the character strings to be compressed and the similarity redundancy of all the redundant character strings on the character strings to be compressed; according to the information entropy of the character string to be compressed and the global compression necessity, determining the self-adaptive coefficient of the character string to be compressed; acquiring the initial window length of the character string to be compressed according to the distance between two adjacent matching points on the character string to be compressed;
acquiring the window length of a search buffer zone of the character string to be compressed according to the self-adaptive coefficient and the initial window length of the character string to be compressed;
and according to the window length of the search buffer zone of the character string to be compressed, compressing the patient treatment data by using an LZ77 compression algorithm, obtaining a compression result of the patient treatment data, and transmitting the compression result of the patient treatment data.
Preferably, the obtaining the matching string according to the string to be compressed, and constructing a global matching string set includes:
and matching any two character strings to be compressed by using a character string matching algorithm to obtain matching character strings, and recording a set containing all the matching character strings as a global matching character string set.
Preferably, the calculating similarity redundancy of the matching strings according to the length and the repetition number of the matching strings in the global matching string set, to obtain a redundant string, includes:
the product of the length of the matching character string and the repeated times of the matching character string in the global matching character string set is recorded as a first product;
marking the normalized value of the first product as the similarity redundancy of the matching character string;
and marking the matching character strings with the similarity redundancy greater than a preset first threshold value as redundant character strings.
Preferably, the matching each redundant string with the string to be compressed to obtain the redundant string and the matching point on the string to be compressed includes:
and respectively taking each character string to be compressed as a main string, and sequentially taking each redundant character string as a mode string to be matched with the main string, so as to obtain the redundant character string and the matching point on the character string to be compressed.
Preferably, the calculating the global repetition rate of the character string to be compressed according to the length of the character string to be compressed and the lengths of all the redundant character strings on the character string to be compressed includes:
the sum of the lengths of all redundant character strings on the character string to be compressed is recorded as a first length;
and recording the ratio of the first length to the length of the character string to be compressed as the global repetition rate of the character string to be compressed.
Preferably, the calculating the global compression necessity of the character string to be compressed according to the global repetition rate of the character string to be compressed and the similarity redundancy of all the redundant character strings on the character string to be compressed includes:
the average value of the similarity redundancies of all the redundant character strings on the character strings to be compressed is recorded as the average value of the similarity redundancies of the character strings to be compressed;
the product of the global repetition rate of the character string to be compressed and the average value of the similarity redundancy is recorded as a second product;
the normalized value of the second product is noted as the global compression necessity of the string to be compressed.
Preferably, the determining the adaptive coefficient of the character string to be compressed according to the information entropy of the character string to be compressed and the global compression necessity includes:
the sum of the information entropy of the character string to be compressed and a preset minimum value is recorded as a first denominator;
the ratio of the global compression necessity of the character string to be compressed to the first denominator is marked as a first partial formula;
the power taking the natural constant as the bottom and the inverse number of the first partial formula as the exponent is marked as the first exponent;
and recording the difference between the value 2 and the first index as the adaptive coefficient of the character string to be compressed.
Preferably, the obtaining the initial window length of the character string to be compressed according to the distance between two adjacent matching points on the character string to be compressed includes:
and taking the maximum value of the distance between two adjacent matching points on the character string to be compressed as the initial window length of the character string to be compressed.
Preferably, the obtaining the window length of the search buffer area of the character string to be compressed according to the adaptive coefficient and the initial window length of the character string to be compressed includes:
the product of the adaptive coefficient of the character string to be compressed and the initial window length is recorded as a third product;
the down-rounded value of the third product is noted as the search buffer window length of the string to be compressed.
In a second aspect, an embodiment of the present invention further provides a hospital intelligent transmission system, including a memory, a processor, and a computer program stored in the memory and running on the processor, where the processor implements the steps of any one of the methods described above when executing the computer program.
The invention has at least the following beneficial effects:
preprocessing patient treatment data to obtain character strings to be compressed, converting the treatment data of each patient into a binary code character string by using ASCII character coding standard, unifying the data types of the patient treatment data, solving the problem of inconsistent data types of the patient treatment data, and improving the reliability of window length setting of a search buffer zone of a compression algorithm;
according to the character strings to be compressed, obtaining matching character strings, calculating similarity redundancy of the matching character strings according to the lengths and the repetition times of the matching character strings, marking the similarity redundancy larger than a certain threshold value as redundant character strings, and then analyzing only the redundant character strings on the character strings to be compressed, so that the reliability of the window length setting of the search buffer area of the compression algorithm is further improved;
matching each redundant character string with the character string to be compressed, obtaining the redundant character string and the matching points on the character string to be compressed, calculating the global repetition rate of the character string to be compressed, calculating the global compression necessity of the character string to be compressed according to the global repetition rate of the character string to be compressed and the similarity redundancy of all the redundant character strings on the character string to be compressed, combining the information entropy of the character string to be compressed, obtaining the self-adaptive coefficient of the character string to be compressed, determining the window length of the search buffer of the character string to be compressed according to the self-adaptive coefficient of the character string to be compressed and the distance between two adjacent matching points, improving the compression efficiency when the patient visit data is compressed, and solving the problem that the window length of the search buffer of the existing compression algorithm is set improperly, so that the compression efficiency is lower.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions and advantages of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a data transmission method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of redundant string matching compression.
Detailed Description
In order to further describe the technical means and effects adopted by the present invention to achieve the preset purpose, the following detailed description refers to a specific implementation, structure, characteristics and effects of a data transmission method and a hospital intelligent transmission system according to the present invention with reference to the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
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.
The following specifically describes a data transmission method and a specific scheme of a hospital intelligent transmission system provided by the invention with reference to the accompanying drawings.
Referring to fig. 1, a flowchart of steps of a data transmission method according to an embodiment of the invention is shown, the method includes the following steps:
and S001, preprocessing the patient treatment data to obtain a character string to be compressed.
Specifically, the patient treatment data in the electronic medical record of the patient is firstly obtained from the database, including the name, the height, the weight, the age, the past medical history and the like, and it is required to be explained that the patient treatment data is required to be processed because a plurality of data types such as Chinese characters, numbers, english letters and the like exist in the patient treatment data, and the patient treatment data of each patient is converted into a binary code character string by using an ASCII character code standard so as to ensure the consistency of the character types and further obtain the character string to be compressed.
So far, the character string to be compressed is obtained.
Step S002, according to the character string to be compressed, obtaining a matching character string, calculating the similarity redundancy of the matching character string according to the length and the repetition number of the matching character string, and obtaining a redundant character string and the arrangement sequence number of the redundant character string.
The principle of the LZ77 compression algorithm is to use a shorter code instead of a repeated character combination in one character string, thereby realizing data compression. Since there are a large number of similar cases in the patient's visit data, such as data of small variations in height, weight, and age, there is a high likelihood of similarity, and there are a large number of repeated character combinations between character strings as well. If character combinations with high similarity and long length are encoded before data compression, the length of part of character strings can be reduced, and compression efficiency is improved.
Specifically, using kmp character string matching algorithm to match any two character strings to be compressed to obtain matching character strings in all character strings to be compressed, sequencing all matching character strings according to the length and the size, and deleting repeated matching character strings to obtain a global matching character string set.
Further, the length and the repetition number of each matching character string in the global matching character string set are counted, the firstThe length of the matching strings is +.>Repeating for +.>. Calculating the +.f. in the global matching string set according to the length and repetition number of the matching string>Similarity redundancy of the individual matching strings +.>：
Wherein,for the +.>Similarity redundancy of the individual matching strings; />For the +.>The lengths of the matching strings; />Is->The number of repetitions of the matching string; />Is a linear normalization function.
The longer the matching character string is, the more the repetition times are, the higher the redundancy of the matching character string in all character strings to be compressed is, the larger the similarity redundancy value of the matching character string is, and the more the matching character string is required to be encoded and compressed; the shorter the length of the matching character string, the fewer the repetition times, which means that the lower the redundancy of the matching character string in all character strings to be compressed, the smaller the similarity redundancy value of the matching character string, and the less need to compress the matching character string in a coding way.
Further, a first threshold is set according to the similarity redundancy of all the matching character stringsFirst threshold->An empirical value of 0.6, and the similarity redundancy is greater than a first threshold +.>As redundant strings. Arranging the redundant character strings from large to small according to the similarity redundancy of the redundant character strings to obtain the arrangement sequence number of each redundant character string>。
Thus, the redundant character strings and the arrangement sequence numbers of the redundant character strings are obtained.
Step S003, each redundant character string is matched with the character string to be compressed, redundant character strings and matching points on the character string to be compressed are obtained, and the global repetition rate of the character string to be compressed is calculated.
It should be noted that, if one character string to be compressed includes a larger number of redundant character strings, the character strings to be compressed have higher repeatability in all character strings to be compressed, and global compression is required. The repeatability of the character strings to be compressed in all the character strings to be compressed can be obtained according to the lengths of the character strings to be compressed and the lengths of all the redundant character strings on the character strings to be compressed.
Specifically, the character strings to be compressed are used as main strings, each redundant character string is sequentially used as a mode string to be matched with the main string, and matching points on the character strings to be compressed and the corresponding redundant character strings are obtained. Character string to be compressedGlobal repetition rate of (a)Can be expressed as follows:
wherein,for character strings to be compressed->Global repetition rate of (a); />For character strings to be compressed->Go up to->The length of the individual redundant strings; />For compressing character strings->The number of upper redundant strings; />For character strings to be compressed->Is a length of (c).
Note that, the character string to be compressedThe larger the sum of the lengths of the upper redundant strings is, the string to be compressed is +.>The smaller the length of the character string, the larger the ratio of the redundant character string to the character string to be compressed, the +.>The greater the global repetition rate, the more it is required to be globally compressed; character string to be compressed->The more the sum of the lengths of the upper redundant stringsSmall, character string to be compressed +.>The larger the length of the character string, the smaller the ratio of the redundant character string to the character string to be compressed, the +.>The smaller the global repetition rate, the less need to globally compress it.
So far, the global repetition rate of the character string to be compressed is obtained.
Step S004, calculating the global compression necessity of the character strings to be compressed according to the global repetition rate of the character strings to be compressed and the similarity redundancy of all the redundant character strings on the character strings to be compressed.
It should be noted that, the LZ77 compression algorithm performs local repetition comparison according to the front and rear local characters of the character string, if the global repetition rate of one character string to be compressed is higher, and the higher the similarity redundancy corresponding to the redundant character string of the character string is, the global repeatability of the character string to be compressed is far higher than the local repeatability, and the global-based compression effect is better.
Specifically, the character string to be compressed is calculated according to the global repetition rate of the character string to be compressed and the similarity redundancy corresponding to all the redundant character strings on the character string to be compressedGlobal compression necessity->：
Wherein,for character strings to be compressed->Is not limited by the global compression necessity;/>for character strings to be compressed->Global repetition rate of (a); />For character strings to be compressed->Go up to->Similarity redundancy of the individual redundant strings; />For compressing character strings->The number of upper redundant strings; />Is a linear normalization function.
Note that, the character string to be compressedThe larger the average value of the similarity redundancy of the upper redundancy character string is, the larger the global repetition rate is, and the character string to be compressed is described as +.>The more the redundant character strings are and the greater the similarity redundancy is, the greater the global compression necessity is, and the better the global compression effect is; character string to be compressed->The smaller the average value of the similarity redundancy of the upper redundancy character string is, the smaller the global repetition rate is, and the character string to be compressed is described as +.>Redundancy onThe fewer the strings and the smaller the similarity redundancy, the less the global compression is necessary and the worse the effect of the global compression.
So far, the global compression necessity of the character string to be compressed is obtained.
Step S005, calculating information entropy of the character string to be compressed, acquiring self-adaptive coefficients of the character string to be compressed according to the information entropy of the character string to be compressed and the global compression necessity, and determining the window length of a search buffer zone of the character string to be compressed according to the self-adaptive coefficients of the character string to be compressed and the distance between two adjacent matching points.
It should be noted that, after global compression, partial local repeatability results of the character string may be damaged, and performing global compression on the character string with low global compression necessity may instead reduce the final compression efficiency.
Specifically, the second threshold is set according to the global compression necessity of all the character strings to be compressedSecond threshold->An empirical value of 0.7, the necessity of global compression is greater than the second threshold value only +.>And performing global compression on the character strings to be compressed.
In the process of compressing the character string to be compressed by using the LZ77 compression algorithm, when the sliding window slides to the matching point corresponding to the redundant character string, the invention does not acquire the triples any more, and the triples are directly obtainedAs a result of the compression of the redundant string, +.>For the arrangement sequence number of redundant character strings, +.>For matching point positions, a redundant string matching compression diagram is shown in fig. 2.
It should be further noted that, the conventional LZ77 compression algorithm sets a uniform search buffer window length for all the strings to be compressed, where the search buffer window length is too small to sufficiently match the strings with higher local repeatability, so that a good compression effect cannot be obtained; while too large a search buffer window length can greatly increase compression time for strings with lower local repeatability. The information entropy of the character string can reflect the repeatability of the character string, if the information entropy of the character string is lower, more repeated modes exist, and the window length of the search buffer area can be properly increased to obtain more matching times. The character string to be compressed with larger global compression necessity is greatly reduced in character string length after global compression, and a smaller window should be selected to improve compression speed.
Specifically, the information entropy of each character string to be compressed is calculated, and the information entropy is calculated according to the character strings to be compressedSetting the character string to be compressed +.>Adaptive coefficient of->：
Wherein,is an exponential function with a natural constant as a base; />For character strings to be compressed->Is a self-adaptive coefficient of (2);for character strings to be compressed->Is an information entropy of (a); />For character strings to be compressed->Is not limited by the global compression necessity; />The empirical value was 0.01.
Note that, the character string to be compressedThe smaller the global compression necessity, the larger the information entropy, illustrating the character string to be compressed +.>The fewer the repetition patterns and the greater the global compression necessity, the smaller the search buffer window length should be to increase the matching compression speed, the smaller the adaptation coefficient should be; character string to be compressed->The greater the global compression necessity, the smaller the information entropy, indicating the string to be compressed +.>The more repeating patterns and the less global compression is necessary, the longer the search buffer window length should be increased to increase the number of matches, the larger the adaptation coefficient should be.
It should be further noted that, for each string to be compressed, when the redundant strings corresponding to two adjacent matching points are identical, the window size should be at least the distance between the two adjacent matching points.
Specifically, the invention leads the character strings to be compressed to be adjacent to each otherThe maximum distance between the matching points is used as the initial window length of the character string to be compressed, and the character string to be compressed is used as the initial window lengthThe adaptive coefficients and the initial window length of (a) to obtain the character string to be compressed +.>Is>：
Wherein,for character strings to be compressed->Is a search buffer window length; />For character strings to be compressed->Is a self-adaptive coefficient of (2); />Is->Matching points->And->Matching points->Euclidean distance between, wherein ∈>；/>Is a maximum function; />For compressing character strings->The number of upper redundant strings;is a round down function.
Note that, the character string to be compressedThe larger the adaptive coefficient of (a) is, the larger the distance between two adjacent matching points is, which means that the character string to be compressed is +.>The larger the local repeatability of the (a) is, the longer the window length of the corresponding search buffer area is, the more the matching times are, and the higher the compression degree is; character string to be compressed->The smaller the adaptive coefficient of (a) is, the smaller the distance between two adjacent matching points is, which means that the character string to be compressed is +.>The smaller the local repeatability of (c), the smaller the corresponding search buffer window length, the fewer the number of matches, and the faster the compression speed.
So far, the window length of the search buffer area of the character string to be compressed is obtained.
Step S006, according to the window length of the search buffer, the LZ77 compression algorithm is used for compressing the patient treatment data, the compression result of the patient treatment data is obtained, and the compression result of the patient treatment data is transmitted.
According to the window length of the search buffer zone, the LZ77 compression algorithm is used for compressing patient treatment data, the compressed patient treatment data is used as transmission data and encrypted by using an SSL security protocol so as to protect personal health information of a patient, and then the HTTP transmission protocol is used for transmitting the data.
So far, the transmission of the patient treatment data in the intelligent hospital system is completed.
Based on the same inventive concept as the above method, the embodiment of the invention further provides a hospital intelligent transmission system, which comprises a memory, a processor and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to realize the steps of any one of the above data transmission methods.
In summary, the embodiment of the invention solves the problem of lower compression efficiency caused by improper setting of the window length of the search buffer of the existing compression algorithm, evaluates the similarity between the character strings to be compressed from different aspects by analyzing the similarity between the character strings to be compressed to obtain the global compression necessity index of the character strings to be compressed, determines the self-adaptive coefficient of the character strings to be compressed by combining the information entropy of the character strings to be compressed, further obtains the window length of the search buffer of the character strings to be compressed, compresses the patient treatment data by using the LZ77 compression algorithm according to the window length of the search buffer of the character strings to be compressed, obtains the compression result of the patient treatment data, and transmits the compression result of the patient treatment data.
It should be noted that: the sequence of the embodiments of the present invention is only for description, and does not represent the advantages and disadvantages of the embodiments. And the foregoing description has been directed to specific embodiments of this specification. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments.
The foregoing description of the preferred embodiments of the present invention is not intended to be limiting, but rather, any modifications, equivalents, improvements, etc. that fall within the principles of the present invention are intended to be included within the scope of the present invention.
Claims (9)
1. A method of data transmission, the method comprising the steps of:
acquiring a character string to be compressed according to patient treatment data;
obtaining a matching character string according to the character string to be compressed, and constructing a global matching character string set; according to the length and the repetition number of the matching character strings in the global matching character string set, calculating the similarity redundancy of the matching character strings, and obtaining redundant character strings; according to the length and the repetition number of the matching character strings in the global matching character string set, the similarity redundancy of the matching character strings is calculated, and the redundant character strings are obtained, including:
the product of the length of the matching character string and the repeated times of the matching character string in the global matching character string set is recorded as a first product; marking the normalized value of the first product as the similarity redundancy of the matching character string; recording the matching character strings with the similarity redundancy larger than a preset first threshold value as redundant character strings;
matching each redundant character string with the character string to be compressed to obtain redundant character strings and matching points on the character strings to be compressed; calculating the global repetition rate of the character strings to be compressed according to the lengths of the character strings to be compressed and the lengths of all redundant character strings on the character strings to be compressed;
calculating the global compression necessity of the character strings to be compressed according to the global repetition rate of the character strings to be compressed and the similarity redundancy of all the redundant character strings on the character strings to be compressed; according to the information entropy of the character string to be compressed and the global compression necessity, determining the self-adaptive coefficient of the character string to be compressed; acquiring the initial window length of the character string to be compressed according to the distance between two adjacent matching points on the character string to be compressed;
acquiring the window length of a search buffer zone of the character string to be compressed according to the self-adaptive coefficient and the initial window length of the character string to be compressed;
and according to the window length of the search buffer zone of the character string to be compressed, compressing the patient treatment data by using an LZ77 compression algorithm, obtaining a compression result of the patient treatment data, and transmitting the compression result of the patient treatment data.
2. The method for data transmission according to claim 1, wherein the obtaining the matching string according to the string to be compressed, and constructing the global matching string set, includes:
and matching any two character strings to be compressed by using a character string matching algorithm to obtain matching character strings, and recording a set containing all the matching character strings as a global matching character string set.
3. The method for data transmission according to claim 1, wherein the step of matching each redundant string with the string to be compressed to obtain the redundant string and the matching point on the string to be compressed includes:
and respectively taking each character string to be compressed as a main string, and sequentially taking each redundant character string as a mode string to be matched with the main string, so as to obtain the redundant character string and the matching point on the character string to be compressed.
4. The method for data transmission according to claim 1, wherein calculating the global repetition rate of the character string to be compressed according to the length of the character string to be compressed and the lengths of all the redundant character strings on the character string to be compressed comprises:
the sum of the lengths of all redundant character strings on the character string to be compressed is recorded as a first length;
and recording the ratio of the first length to the length of the character string to be compressed as the global repetition rate of the character string to be compressed.
5. The method for data transmission according to claim 1, wherein the calculating the global compression necessity of the character string to be compressed according to the global repetition rate of the character string to be compressed and the similarity redundancy of all the redundant character strings on the character string to be compressed comprises:
the average value of the similarity redundancies of all the redundant character strings on the character strings to be compressed is recorded as the average value of the similarity redundancies of the character strings to be compressed;
the product of the global repetition rate of the character string to be compressed and the average value of the similarity redundancy is recorded as a second product;
the normalized value of the second product is noted as the global compression necessity of the string to be compressed.
6. The method according to claim 1, wherein the determining the adaptive coefficient of the character string to be compressed according to the information entropy of the character string to be compressed and the global compression necessity comprises:
the sum of the information entropy of the character string to be compressed and a preset minimum value is recorded as a first denominator;
the ratio of the global compression necessity of the character string to be compressed to the first denominator is marked as a first partial formula;
the power taking the natural constant as the bottom and the inverse number of the first partial formula as the exponent is marked as the first exponent;
and recording the difference between the value 2 and the first index as the adaptive coefficient of the character string to be compressed.
7. The method for transmitting data according to claim 1, wherein the obtaining the initial window length of the character string to be compressed according to the distance between two adjacent matching points on the character string to be compressed comprises:
and taking the maximum value of the distance between two adjacent matching points on the character string to be compressed as the initial window length of the character string to be compressed.
8. The method for transmitting data according to claim 1, wherein the obtaining the window length of the search buffer of the character string to be compressed according to the adaptive coefficient and the initial window length of the character string to be compressed comprises:
the product of the adaptive coefficient of the character string to be compressed and the initial window length is recorded as a third product;
the down-rounded value of the third product is noted as the search buffer window length of the string to be compressed.
9. A hospital intelligent transmission system comprising a memory, a processor and a computer program stored in said memory and running on said processor, characterized in that said processor implements the steps of the method according to any of claims 1-8 when said computer program is executed.
Priority Applications (1)
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