CN105703777A - Refrigerator reported data compressing method and device - Google Patents
Refrigerator reported data compressing method and device Download PDFInfo
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- CN105703777A CN105703777A CN201610074990.2A CN201610074990A CN105703777A CN 105703777 A CN105703777 A CN 105703777A CN 201610074990 A CN201610074990 A CN 201610074990A CN 105703777 A CN105703777 A CN 105703777A
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- H—ELECTRICITY
- H03—ELECTRONIC CIRCUITRY
- H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
- H03M7/00—Conversion of a code where information is represented by a given sequence or number of digits to a code where the same, similar or subset of information is represented by a different sequence or number of digits
- H03M7/30—Compression; Expansion; Suppression of unnecessary data, e.g. redundancy reduction
Abstract
The invention relates to a refrigerator reported data compressing method and device. The method comprises the following steps: original message data are obtained, a binary tree database is built according to the original message data, reported message data are classified after being received, and whether all classified data items of the reported message data has corresponding compression values is checked in the binary tree database; if yes, the data items of the reported message data are replaced with the corresponding compression values and the corresponding compression values can form compressed message data. According to the refrigerator reported data compressing method and device, by finding the corresponding compression values of all classified data items of the reported message data in the binary tree database and replacing the data times of the reported message data with the corresponding compression values, data compressing operation can be finished, and storage space can be saved.
Description
Technical field
The present invention relates to refrigerator art, particularly relate to a kind of method and apparatus compressing refrigerator reported data。
Background technology
Reported data currently for refrigerator is made directly storage, does not do any compression and processes, so can produce googol according to amount, brings huge pressure for storage。If only the wherein data in reported data is compressed, the compression stroke caused is little, and Normal squeezing is not over 20%, thus, also can bring immense pressure for storage。
Summary of the invention
The present invention provides a kind of method and apparatus compressing refrigerator reported data, to solve the storage problem of the mass data that refrigerator reports。
The technical scheme is that a kind of method compressing refrigerator reported data, including:
Obtain original message data；
According to described original message data construct b-tree data storehouse；
When receive report message data time, report message data to classify by described；
That searches each classification from described b-tree data storehouse reports whether the data item in message data exists the compressed value of correspondence；
If it is present the described data item reported in message data to be replaced with the compressed value of described correspondence；
The compressed value of described correspondence is constituted the message data of compression。
The invention has the beneficial effects as follows: by searching the compressed value reporting the data item in message data corresponding of each classification from b-tree data storehouse, and the compressed value that the data item in message data will be reported to replace with correspondence, thus completing the compression of data, save memory space。
On the basis of technique scheme, the present invention can also do following improvement。
Further, described include according to described original message data construct b-tree data storehouse:
Described original message data are carried out classification and obtains multiple categorical data；
Obtain historical baseline data；
According to the probability of occurrence of each data item in described each categorical data of historical baseline data statistics；
Described probability of occurrence is arranged according to order from big to small；
Compressed value is given successively with the order of 16 incremental to the probability of occurrence arranged by descending order；
Binary tree structure is generated according to each data item in each categorical data described and described compressed value；
Described binary tree structure is stored in described b-tree data storehouse。
Above-mentioned further scheme is adopted to provide the benefit that: by original message data carry out classifying, add up probability of occurrence and give compressed value, thus constituting b-tree data storehouse, b-tree data storehouse can store the compressed value that all original message data are corresponding, so that when existence reports message data, from b-tree data storehouse, search the compressed value of correspondence, and be replaced。
Further, described original message data include switching load data, actual temperature data, reserved data, state load data, operational mode data, arrange temperature data and internal data, wherein, described actual temperature data includes multiple actual temperature data item, and the described temperature data that arranges includes multiple arranging temperature data item。
Adopt above-mentioned further scheme to provide the benefit that: original message data include various data, it is possible to learn which type is the original message data in refrigerator all include, and conveniently report message data to search the compressed value of correspondence from the original message data of classification。
Further, described described original message data are carried out classification obtain multiple categorical data and include:
The plurality of actual temperature data item is carried out classification and obtains multiple actual temperature categorical data；
The plurality of temperature data item that arranges is carried out classification obtains multiple arranging temperature classifications data；
Described switching load data, the plurality of actual temperature categorical data, described reserved data, described state load data, described operational mode data, described temperature classifications data and the internal data of arranging constitute the plurality of categorical data。
Above-mentioned further scheme is adopted to provide the benefit that: by the data in original message data being classified, it is possible to make the compressed value reporting message data more easily to find correspondence from b-tree data storehouse。
Further, each data item in each categorical data described in described basis and described compressed value generation binary tree structure include:
Calculate n item data item before in each categorical data described probability and, wherein, n is positive integer；
If the probability of described front n item data item and be not less than default probability threshold value, and n is not more than default data item threshold value, then compressed value corresponding with described front n item for described front n item data item is generated described binary tree structure；
Or,
If the probability of described front n item data item and less than described default probability threshold value, and n is equal to described default data item threshold value, then compressed value corresponding with described whole n item data item for whole n item data items is generated described binary tree structure。
Adopt above-mentioned further scheme to provide the benefit that: by the probability of front n item data item and and the judgement of item number of data item, constitute binary tree structure, and, the minor matters point of front n item data item correspondence binary tree, the leaf node of compressed value correspondence binary tree, thus more clearly showing binary tree structure。
The technical scheme is that a kind of device compressing refrigerator reported data, including:
Original message data capture unit, is used for obtaining original message data；
B-tree data storehouse construction unit, for according to described original message data construct b-tree data storehouse；
Taxon, for when receive report message data, report message data to classify by described；
Search unit, for search from described b-tree data storehouse each classification report the data item in message data whether exist correspondence compressed value；
Replacement unit, deposits in case for the compressed value in described correspondence, the described data item reported in message replaces with the compressed value of described correspondence；
Compressed packet data composing unit, for constituting the message data of compression by the compressed value of described correspondence。
The invention has the beneficial effects as follows: from b-tree data storehouse, search the compressed value reporting the data item in message data corresponding of each classification by searching unit, and the data item in message data will be reported to replace with corresponding compressed value by replacement unit, thus completing the compression of data, save memory space。
On the basis of technique scheme, the present invention can also do following improvement。
Further, described b-tree data storehouse construction unit includes:
Described original message data are carried out classification and obtain multiple categorical data by original message data sorting unit；
Historical baseline data capture unit, is used for obtaining historical baseline data；
Statistic unit, for according to the probability of occurrence of each data item in described each categorical data of historical baseline data statistics；
Sequencing unit, for arranging described probability of occurrence according to order from big to small；
Give unit, for giving compressed value to the probability of occurrence arranged by descending order successively with the order of 16 incremental；
Generate unit, generate binary tree structure according to each data item in each categorical data described and described compressed value；
Memory element, for being stored in described binary tree structure in described b-tree data storehouse。
Above-mentioned further scheme is adopted to provide the benefit that: by original message data carry out classifying, add up probability of occurrence and give compressed value, thus constituting b-tree data storehouse, b-tree data storehouse can store the compressed value that all original message data are corresponding, so that when existence reports message data, from b-tree data storehouse, search the compressed value of correspondence, and be replaced。
Further, described original message data include switching load data, actual temperature data, reserved data, state load data, operational mode data, arrange temperature data and internal data, wherein, described actual temperature data includes multiple actual temperature data item, and the described temperature data that arranges includes multiple arranging temperature data item。
Adopt above-mentioned further scheme to provide the benefit that: original message data include various data, it is possible to learn which type is the original message data in refrigerator all include, and conveniently report message data to search the compressed value of correspondence from the original message data of classification。
Further, described original message data sorting unit includes:
Actual temperature data item taxon, obtains multiple actual temperature categorical data for the plurality of actual temperature data item is carried out classification；
Temperature data item taxon is set, for being carried out classification and obtain multiple arranging temperature classifications data by the plurality of temperature data item that arranges；
Multiple categorical data Component units, constitute the plurality of categorical data for described switching load data, the plurality of actual temperature categorical data, described reserved data, described state load data, described operational mode data, described temperature classifications data and the internal data of arranging。
Above-mentioned further scheme is adopted to provide the benefit that: by the data in original message data being classified, it is possible to make the compressed value reporting message data more easily to find correspondence from b-tree data storehouse。
Further, described generation unit includes:
Calculate n item data item before in each categorical data described probability and, wherein, n is positive integer；
If the probability of described front n item data item and be not less than default probability threshold value, and n is not more than default data item threshold value, then compressed value corresponding with described front n item for described front n item data item is generated described binary tree structure；
Or,
If the probability of described front n item data item and less than described default probability threshold value, and n is equal to described default data item threshold value, then compressed value corresponding with described whole n item data item for whole n item data items is generated described binary tree structure。
Adopt above-mentioned further scheme to provide the benefit that: by the probability of front n item data item and and the judgement of item number of data item, constitute binary tree structure, and, the minor matters point of front n item data item correspondence binary tree, the leaf node of compressed value correspondence binary tree, thus more clearly showing binary tree structure。
Accompanying drawing explanation
A kind of method flow diagram compressing refrigerator reported data that Fig. 1 provides for the embodiment of the present invention；
The switching load data item probability of occurrence distribution schematic diagram that Fig. 2 provides for the embodiment of the present invention；
The ambient temperature probability of occurrence distribution schematic diagram that Fig. 3 provides for the embodiment of the present invention；
The original message data classification schematic diagram that Fig. 4 provides for the embodiment of the present invention；
The switching load data item binary tree structural representation that Fig. 5 provides for the embodiment of the present invention；
A kind of device schematic diagram compressing refrigerator reported data that Fig. 6 provides for the embodiment of the present invention。
In accompanying drawing, the list of parts representated by each label is as follows:
10, original message data capture unit, 20, b-tree data storehouse construction unit, 30, taxon, 40, search unit, 50, replacement unit, 60, compressed packet data composing unit。
Detailed description of the invention
Below in conjunction with accompanying drawing, principles of the invention and feature being described, example is served only for explaining the present invention, is not intended to limit the scope of the present invention。
A kind of method flow diagram compressing refrigerator reported data that Fig. 1 provides for the embodiment of the present invention。
With reference to Fig. 1, step S101, obtain original message data。
Step S102, according to described original message data construct b-tree data storehouse。
Step S103, when receive report message data time, report message data to classify by described。
Step S104, that searches each classification from described b-tree data storehouse reports whether the data item in message data exists the compressed value of correspondence, if it is present perform step S105；If it does not exist, then perform step S106。
Here, binary tree structure is stored in b-tree data storehouse, and wherein, what data item was corresponding is the minor matters point of binary tree structure, and what compressed value was corresponding is the leaf node of binary tree structure。When searching the compressed value reporting the data item in message data corresponding of each classification from b-tree data storehouse, first search the minor matters point reporting the data item in message data corresponding of each classification, obtain the leaf node that minor matters point is corresponding again, thus obtaining the compressed value that leaf node is corresponding。
Step S105, replaces with the compressed value of described correspondence by the described data item reported in message data。
Step S106, retains the data item reported in message data。
Step S107, constitutes the message data of compression by the compressed value of described correspondence。
In one embodiment of the invention, described include according to described original message data construct b-tree data storehouse:
Described original message data are carried out classification and obtains multiple categorical data；
Obtain historical baseline data；
According to the probability of occurrence of each data item in described each categorical data of historical baseline data statistics；
Described probability of occurrence is arranged according to order from big to small；
Compressed value is given successively with the order of 16 incremental to the probability of occurrence arranged by descending order；
Binary tree structure is generated according to each data item in each categorical data described and described compressed value；
Described binary tree structure is stored in described b-tree data storehouse。
Here, original message data are carried out classification and obtains switching load data the probability of occurrence of each data item in statistic switch load data, the probability of occurrence of data item each in switching load data is arranged according to order from big to small, specifically as shown in table 1:
Table 1
Specifically, in switching load data, the probability of occurrence of each data item can as in figure 2 it is shown, when the data item in switching load data is 01,01,03,10,00, probability of occurrence be 33%；When the data item in switching load data is 01,01,13,00,00, probability of occurrence is 4%。The probability of occurrence of each data item in switching load data can be obtained by Fig. 2。
Original message data being carried out classification and can obtain ambient temperature data, the probability of occurrence of each data item in ambient temperature data is as it is shown on figure 3, when the data item in ambient temperature data is 18.5 degree, probability of occurrence is 0.5%；When the data item in ambient temperature data is 19 degree, probability of occurrence is 0.7%。Can obtaining the probability of occurrence of each data item in ambient temperature data by Fig. 3, probability of occurrence is normal distribution, and the data item of more than 95% all concentrates in certain region。
In one embodiment of the invention, described original message data include switching load data, actual temperature data, reserved data, state load data, operational mode data, arrange temperature data and internal data, wherein, described actual temperature data includes multiple actual temperature data item, and the described temperature data that arranges includes multiple arranging temperature data item。
In one embodiment of the invention, described described original message data are carried out classification obtain multiple categorical data and include:
The plurality of actual temperature data item is carried out classification and obtains multiple actual temperature categorical data；
The plurality of temperature data item that arranges is carried out classification obtains multiple arranging temperature classifications data；
Described switching load data, the plurality of actual temperature categorical data, described reserved data, described state load data, described operational mode data, described temperature classifications data and the internal data of arranging constitute the plurality of categorical data。
Specifically, original message data include switching load data, actual temperature data, reserved data, state load data, operational mode data, temperature data and internal data are set, wherein, described actual temperature data includes multiple actual temperature data item, can be such as, but it is not limited to, it is specially 17 actual temperature data items, arrange temperature data to include multiple arranging temperature data item, can be such as, but it is not limited to, it is specially 10 and temperature data item is set, specifically can refer to original message data classification schematic diagram as shown in Figure 4, as shown in Figure 4, 17 actual temperature data items are carried out classification and obtains 17 actual temperature categorical datas, be equivalent to the secondary classification to actual temperature data item；Arranging temperature data item to carry out classification and obtain 10 by 10 and arrange temperature classifications data, being equivalent to the secondary classification arranging temperature data item, thus constituting 32 categorical datas。
In one embodiment of the invention, each data item in each categorical data described in described basis and described compressed value generation binary tree structure include:
Calculate n item data item before in each categorical data described probability and, wherein, n is positive integer；
If the probability of described front n item data item and be not less than default probability threshold value, and n is not more than default data item threshold value, then compressed value corresponding with described front n item for described front n item data item is generated described binary tree structure；
Or,
If the probability of described front n item data item and less than described default probability threshold value, and n is equal to described default data item threshold value, then compressed value corresponding with described whole n item data item for whole n item data items is generated described binary tree structure。
Here, for switching load data item, by table 1 it can be seen that the probability of switching load data item and be 95.64%, wherein, n is 12。Probability and more than 95%, and n is less than 16, then directly 12 item data items are generated binary tree structures, specifically can refer to switching load data binary tree structural representation as shown in Figure 5, be 01,01 in switching load data item, 03,10,00,00,00, c0,00, when 00, probability of occurrence is 35.8443%, and compressed value is 0。What switching load data item was corresponding is the minor matters point of binary tree structure, and what compressed value was corresponding is the leaf node of binary tree structure。
If n is 16, probability and less than 95%, then directly 16 item data items are generated binary tree structures。
A kind of method compressing refrigerator reported data that the embodiment of the present invention provides, by original message data construct b-tree data storehouse, if finding the compressed value reporting the data item in message data corresponding of each classification from b-tree data storehouse, the compressed value that then data item in message data will be reported to replace with correspondence, and constitute the message data of compression, thus saving memory space。
A kind of device schematic diagram compressing refrigerator reported data that Fig. 6 provides for the embodiment of the present invention。
With reference to Fig. 6, the device of compression refrigerator reported data includes original message data capture unit 10, b-tree data storehouse construction unit 20, taxon 30, searches unit 40, replacement unit 50 and compressed packet data composing unit 60。
Original message data capture unit 10, is used for obtaining original message data。
B-tree data storehouse construction unit 20, for according to described original message data construct b-tree data storehouse。
Taxon 30, for when receive report message data, report message data to classify by described。
Search unit 40, for search from described b-tree data storehouse each classification report the data item in message data whether exist correspondence compressed value。
Replacement unit 50, deposits in case for the compressed value in described correspondence, the described data item reported in message replaces with the compressed value of described correspondence。
Compressed packet data composing unit 60, for constituting the message data of compression by the compressed value of described correspondence。
In one embodiment of the invention, described b-tree data storehouse construction unit 20 includes:
Described original message data are carried out classification and obtain multiple categorical data by original message data sorting unit 21 (not shown)；
Historical baseline data capture unit 22 (not shown), is used for obtaining historical baseline data；
Statistic unit 23 (not shown), for according to the probability of occurrence of each data item in described each categorical data of historical baseline data statistics；
Sequencing unit 24 (not shown), for arranging described probability of occurrence according to order from big to small；
Give unit 25 (not shown), for giving compressed value to the probability of occurrence arranged by descending order successively with the order of 16 incremental；
Generate unit 26 (not shown), generate binary tree structure according to each data item in each categorical data described and described compressed value；
Memory element 27 (not shown), for being stored in described binary tree structure in described b-tree data storehouse。
In one embodiment of the invention, described original message data include switching load data, actual temperature data, reserved data, state load data, operational mode data, arrange temperature data and internal data, wherein, described actual temperature data includes multiple actual temperature data item, and the described temperature data that arranges includes multiple arranging temperature data item。
In one embodiment of the invention, described original message data sorting unit 21 includes:
Actual temperature data item taxon 211 (not shown), obtains multiple actual temperature categorical data for the plurality of actual temperature data item is carried out classification；
Temperature data item taxon 212 (not shown) is set, for being carried out classification and obtain multiple arranging temperature classifications data by the plurality of temperature data item that arranges；
Multiple categorical data Component units 213 (not shown), constitute the plurality of categorical data for described switching load data, the plurality of actual temperature categorical data, described reserved data, described state load data, described operational mode data, described temperature classifications data and the internal data of arranging。
In one embodiment of the invention, described generation unit 26 includes:
Calculate n item data item before in each categorical data described probability and, wherein, n is positive integer；
If the probability of described front n item data item and be not less than default probability threshold value, and n is not more than default data item threshold value, then compressed value corresponding with described front n item for described front n item data item is generated described binary tree structure；
Or,
If the probability of described front n item data item and less than described default probability threshold value, and n is equal to described default data item threshold value, then compressed value corresponding with described whole n item data item for whole n item data items is generated described binary tree structure。
A kind of device compressing refrigerator reported data that the embodiment of the present invention provides, by original message data construct b-tree data storehouse, if finding the compressed value reporting the data item in message data corresponding of each classification from b-tree data storehouse, the compressed value that then data item in message data will be reported to replace with correspondence, and constitute the message data of compression, thus saving memory space。
The foregoing is only presently preferred embodiments of the present invention, not in order to limit the present invention, all within the spirit and principles in the present invention, any amendment of making, equivalent replacement, improvement etc., should be included within protection scope of the present invention。
Claims (10)
1. the method compressing refrigerator reported data, it is characterised in that including:
Obtain original message data；
According to described original message data construct b-tree data storehouse；
When receive report message data time, report message data to classify by described；
That searches each classification from described b-tree data storehouse reports whether the data item in message data exists the compressed value of correspondence；
If it is present the described data item reported in message data to be replaced with the compressed value of described correspondence；
The compressed value of described correspondence is constituted the message data of compression。
2. a kind of method compressing refrigerator reported data according to claim 1, it is characterised in that described include according to described original message data construct b-tree data storehouse:
Described original message data are carried out classification and obtains multiple categorical data；
Obtain historical baseline data；
According to the probability of occurrence of each data item in described each categorical data of historical baseline data statistics；
Described probability of occurrence is arranged according to order from big to small；
Compressed value is given successively with the order of 16 incremental to the probability of occurrence arranged by descending order；
Binary tree structure is generated according to each data item in each categorical data described and described compressed value；
Described binary tree structure is stored in described b-tree data storehouse。
3. a kind of method compressing refrigerator reported data according to claim 2, it is characterized in that, described original message data include switching load data, actual temperature data, reserved data, state load data, operational mode data, arrange temperature data and internal data, wherein, described actual temperature data includes multiple actual temperature data item, and the described temperature data that arranges includes multiple arranging temperature data item。
4. a kind of method compressing refrigerator reported data according to claim 3, it is characterised in that described described original message data are carried out classification obtain multiple categorical data and include:
The plurality of actual temperature data item is carried out classification and obtains multiple actual temperature categorical data；
The plurality of temperature data item that arranges is carried out classification obtains multiple arranging temperature classifications data；
Described switching load data, the plurality of actual temperature categorical data, described reserved data, described state load data, described operational mode data, described temperature classifications data and the internal data of arranging constitute the plurality of categorical data。
5. a kind of method compressing refrigerator reported data according to claim 2, it is characterised in that each data item and described compressed value in each categorical data described in described basis generate binary tree structure and include:
Calculate n item data item before in each categorical data described probability and, wherein, n is positive integer；
If the probability of described front n item data item and be not less than default probability threshold value, and n is not more than default data item threshold value, then compressed value corresponding with described front n item for described front n item data item is generated described binary tree structure；
Or,
If the probability of described front n item data item and less than described default probability threshold value, and n is equal to described default data item threshold value, then compressed value corresponding with described whole n item data item for whole n item data items is generated described binary tree structure。
6. the device compressing refrigerator reported data, it is characterised in that including:
Original message data capture unit, is used for obtaining original message data；
B-tree data storehouse construction unit, for according to described original message data construct b-tree data storehouse；
Taxon, for when receive report message data, report message data to classify by described；
Search unit, for search from described b-tree data storehouse each classification report the data item in message data whether exist correspondence compressed value；
Replacement unit, deposits in case for the compressed value in described correspondence, the described data item reported in message replaces with the compressed value of described correspondence；
Compressed packet data composing unit, for constituting the message data of compression by the compressed value of described correspondence。
7. a kind of device compressing refrigerator reported data according to claim 6, it is characterised in that described b-tree data storehouse construction unit includes:
Described original message data are carried out classification and obtain multiple categorical data by original message data sorting unit；
Historical baseline data capture unit, is used for obtaining historical baseline data；
Statistic unit, for according to the probability of occurrence of each data item in described each categorical data of historical baseline data statistics；
Sequencing unit, for arranging described probability of occurrence according to order from big to small；
Give unit, for giving compressed value to the probability of occurrence arranged by descending order successively with the order of 16 incremental；
Generate unit, generate binary tree structure according to each data item in each categorical data described and described compressed value；
Memory element, for being stored in described binary tree structure in described b-tree data storehouse。
8. a kind of device compressing refrigerator reported data according to claim 7, it is characterized in that, described original message data include switching load data, actual temperature data, reserved data, state load data, operational mode data, arrange temperature data and internal data, wherein, described actual temperature data includes multiple actual temperature data item, and the described temperature data that arranges includes multiple arranging temperature data item。
9. a kind of device compressing refrigerator reported data according to claim 8, it is characterised in that described original message data sorting unit includes:
Actual temperature data item taxon, obtains multiple actual temperature categorical data for the plurality of actual temperature data item is carried out classification；
Temperature data item taxon is set, for being carried out classification and obtain multiple arranging temperature classifications data by the plurality of temperature data item that arranges；
Multiple categorical data Component units, constitute the plurality of categorical data for described switching load data, the plurality of actual temperature categorical data, described reserved data, described state load data, described operational mode data, described temperature classifications data and the internal data of arranging。
10. a kind of device compressing refrigerator reported data according to claim 7, it is characterised in that described generation unit includes:
Calculate n item data item before in each categorical data described probability and, wherein, n is positive integer；
If the probability of described front n item data item and be not less than default probability threshold value, and n is not more than default data item threshold value, then compressed value corresponding with described front n item for described front n item data item is generated described binary tree structure；
Or,
If the probability of described front n item data item and less than described default probability threshold value, and n is equal to described default data item threshold value, then compressed value corresponding with described whole n item data item for whole n item data items is generated described binary tree structure。
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20010053963A1 (en) * | 2000-06-16 | 2001-12-20 | Lg Electronics Inc. | Refrigerator and method for controlling the same |
| CN103379136A (en) * | 2012-04-17 | 2013-10-30 | 中国移动通信集团公司 | Compression method and decompression method of log acquisition data, compression apparatus and decompression apparatus of log acquisition data |
| CN105135591A (en) * | 2015-07-01 | 2015-12-09 | 西安理工大学 | Train air conditioning unit fault diagnosing method based on multi-classification strategy |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20010053963A1 (en) * | 2000-06-16 | 2001-12-20 | Lg Electronics Inc. | Refrigerator and method for controlling the same |
| CN103379136A (en) * | 2012-04-17 | 2013-10-30 | 中国移动通信集团公司 | Compression method and decompression method of log acquisition data, compression apparatus and decompression apparatus of log acquisition data |
| CN105135591A (en) * | 2015-07-01 | 2015-12-09 | 西安理工大学 | Train air conditioning unit fault diagnosing method based on multi-classification strategy |
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