Time series missing filling method, device, equipment and readable storage medium

Abstract

The present invention provides a method, device, equipment and readable storage medium for filling missing time series. The method for filling missing time series includes: if the event time of the data received from the terminal is missing, the received data with missing event time is used as the data to be filled; a reference data set of the data to be filled is selected from the multiple data received; the reference data set is used as a reference to obtain the delay time of the data to be filled by calculation; based on the delay time of the data to be filled, combined with the receiving time of the data to be filled, the missing time of the data to be filled is calculated; and the event time of the data to be filled is filled using the missing time of the data to be filled. Through the present invention, the reference data set of the data to be filled is selected from the received data, the delay time of the data to be filled is calculated, and the missing time is obtained in combination with the receiving time of the data to be filled, so that high-precision filling of missing time series can be achieved.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and in particular to a time series missing filling method, device, equipment and readable storage medium. Background Art

[0002] The vehicle big data system is a vehicle big data analysis and mining platform that takes the data of terminal vehicles as the core, and realizes the networking access, analysis and processing, cloud storage, intelligent analysis and visualization of multi-source massive vehicle data information. The quality of data determines the availability of data and is the basis for the platform to conduct subsequent analysis and mining. Among them, the data of terminal vehicles are typical time series data. In the actual operation process, due to various reasons, the event time of the received terminal vehicle data (that is, the time when the event of the terminal vehicle is recorded in the data) is missing, resulting in the missing and incomplete time series (that is, a collection of a series of data in chronological order), such as terminal failure, network signal, access system failure, etc., which will lead to the distortion of the calculation of various indicators of the platform in the subsequent data processing process. Summary of the invention

[0003] The main purpose of the present invention is to provide a method, device, equipment and readable storage medium for filling missing time series, aiming to solve the technical problem that the time series of data is missing and cannot be filled with high precision.

[0004] In a first aspect, the present invention provides a time series missing filling method, the time series missing filling method comprising:

[0005] If the event time of the data received from the terminal is missing, the received data with missing event time is used as the data to be filled;

[0006] Selecting a reference data set of the data to be filled from the received multiple pieces of data;

[0007] Taking the reference data set as a reference, obtaining the delay time of the data to be filled by calculation;

[0008] Based on the delay time of the data to be filled and the reception time of the data to be filled, the missing time of the data to be filled is calculated;

[0009] The event time of the data to be filled is filled using the missing time of the data to be filled.

[0010] Optionally, selecting a reference data set of the data to be filled from the received multiple pieces of data includes:

[0011] Determine the data quantity N of the reference data set to be filled based on the frequency of data sent by the terminal;

[0012] In the real-time data processing scenario, the first N complete time series data adjacent to the data to be filled are selected from the received multiple data as the reference data set of the data to be filled;

[0013] In an offline data processing scenario, the first N and last N complete time series data adjacent to the data to be filled are selected from the multiple received data as reference data sets for the data to be filled.

[0014] Optionally, the determining, based on the frequency at which the terminal sends data, the data quantity N of the reference data set to be filled includes:

[0015] According to the data to be filled, obtaining the frequency of the terminal sending data by querying;

[0016] Based on the frequency of data transmission by the terminal, the data quantity N of the reference data set to be filled is determined by a formula, and the determination formula is:

[0017]

[0018] Among them, t is the interval time for the terminal to send each piece of data, and m is the number of data sent by the terminal within 1 second.

[0019] Optionally, taking the reference data set as a reference and obtaining the delay time of the data to be filled by calculation includes:

[0020] The reference data set is used as a reference, and based on the generation time and reception time of the data in the reference data set, the delay time of the data to be filled is obtained by calculation, and the calculation formula is:

[0021]

[0022] Wherein, δ is the delay time of the data to be filled, T i is the occurrence time of data i in the reference data set, C i is the receiving time of data i in the reference data set, and N is the number of data in the reference data set of the data to be filled.

[0023] Optionally, the calculating the missing time of the data to be filled based on the delay time of the data to be filled and the receiving time of the data to be filled includes:

[0024] Based on the delay time of the data to be filled and the reception time of the data to be filled, the missing time of the data to be filled is calculated, and the calculation formula is:

[0025] T f =C f -δ

[0026] Among them, T f is the missing time of the data to be filled, C f is the receiving time of the data to be filled, and δ is the delay time of the data to be filled.

[0027] In a second aspect, the present invention further provides a time series missing filling device, the time series missing filling device comprising:

[0028] A receiving module, configured to use the received data with missing event time as data to be filled if the event time of the data received from the terminal is missing;

[0029] A selection module, used for selecting a reference data set of the data to be filled from the received multiple data;

[0030] A first calculation module, configured to use the reference data set as a reference and obtain the delay time of the data to be filled by calculation;

[0031] A second calculation module, configured to calculate the missing time of the data to be filled based on the delay time of the data to be filled and the receiving time of the data to be filled;

[0032] A filling module is used to fill the event time of the data to be filled with the missing time of the data to be filled.

[0033] Optionally, the selection module is used to:

[0034] Determine the data quantity N of the reference data set to be filled based on the frequency of data sent by the terminal;

[0035] In the real-time data processing scenario, the first N complete time series data adjacent to the data to be filled are selected from the received multiple data as the reference data set of the data to be filled;

[0036] In an offline data processing scenario, the first N and last N complete time series data adjacent to the data to be filled are selected from the multiple received data as reference data sets for the data to be filled.

[0037] Optionally, the first computing module is used to:

[0038] The reference data set is used as a reference, and based on the generation time and reception time of the data in the reference data set, the delay time of the data to be filled is obtained by calculation, and the calculation formula is:

[0039]

[0040] Wherein, δ is the delay time of the data to be filled, T i is the occurrence time of data i in the reference data set, C i is the receiving time of data i in the reference data set, and N is the number of data in the reference data set of the data to be filled.

[0041] In the third aspect, the present invention also provides a time series missing filling device, which includes a processor, a memory, and a time series missing filling program stored on the memory and executable by the processor, wherein when the time series missing filling program is executed by the processor, the steps of the time series missing filling method described above are implemented.

[0042] In a fourth aspect, the present invention further provides a readable storage medium, on which a time series missing filling program is stored, wherein when the time series missing filling program is executed by a processor, the steps of the time series missing filling method as described above are implemented.

[0043] In the present invention, if the event time of the data received from the terminal is missing, the received data with missing event time is used as the data to be filled; a reference data set of the data to be filled is selected from the multiple data received; the reference data set is used as a reference to obtain the delay time of the data to be filled by calculation; based on the delay time of the data to be filled and combined with the reception time of the data to be filled, the missing time of the data to be filled is calculated; and the event time of the data to be filled is filled using the missing time of the data to be filled. Through the present invention, in the process of the data processing center receiving data from the terminal, the received data with missing event time is used as the data to be filled, and a reference data set of the data to be filled is selected from the multiple data received, and the reference data set is used as a reference to calculate the delay time of the data to be filled. Because the delay time represents the time difference between the receiving time and the occurrence time of the data, and the receiving time of the data is filled by the data processing center and is generally not missing, therefore, combined with the receiving time of the data to be filled, the missing time of the data to be filled can be calculated, and the event time of the data to be filled is filled using the missing time, so that the data with a complete time series after filling can be obtained. The present invention selects the reference data set of the data to be filled from the received data, and then calculates the delay time of the data to be filled, and obtains the missing time of the data to be filled in combination with the receiving time of the data to be filled, so as to achieve high-precision filling of the missing time series. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 This is a schematic diagram of the hardware structure of an embodiment of a time series missing filling device of the present invention;

[0045] Figure 2It is a flow chart of an embodiment of a method for filling missing time series information of the present invention;

[0046] Figure 3 for Figure 2 Detailed flow chart of step S20;

[0047] Figure 4 This is a schematic diagram of the functional modules of an embodiment of a time series missing filling device of the present invention;

[0048] Figure 5 for Figure 4 A schematic diagram of the detailed functional modules of the selection module 20.

[0049] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0050] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0051] In a first aspect, an embodiment of the present invention provides a time series missing filling device, which may be a device having a data processing function, such as a personal computer (PC), a notebook computer, or a server.

[0052] Reference Figure 1 , Figure 1 The hardware structure diagram of an embodiment of a time series missing filling device of the present invention. In an embodiment of the present invention, the time series missing filling device may include a processor 1001 (e.g., a central processing unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components; the user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard); the network interface 1004 may optionally include a standard wired interface, a wireless interface (such as a wireless fidelity WIreless-FIdelity, WI-FI interface); the memory 1005 may be a high-speed random access memory (random access memory, RAM), or a stable memory (non-volatile memory), such as a disk storage, and the memory 1005 may optionally be a storage device independent of the aforementioned processor 1001. Those skilled in the art will understand that Figure 1 The hardware structure shown in the figure does not constitute a limitation of the present invention, and may include more or less components than those shown in the figure, or combine certain components, or arrange the components differently.

[0053] Continue to refer to Figure 1 , Figure 1 The memory 1005 as a computer storage medium may include an operating system, a network communication module, a user interface module, and a time series missing filling program. The processor 1001 may call the time series missing filling program stored in the memory 1005 and execute the time series missing filling method provided in the embodiment of the present invention.

[0054] In a second aspect, an embodiment of the present invention provides a method for filling missing parts in a time series.

[0055] In order to more clearly demonstrate the time series missing filling method provided by the embodiment of the present application, the application scenario of the time series missing filling method provided by the embodiment of the present application is first introduced.

[0056] The time series missing filling method provided in the embodiment of the present application is applied to the data processing center of the vehicle's big data system, which receives massive terminal data information from the terminal vehicle for processing. The time series of the terminal data may be missing due to terminal failure, network signal, access system failure, etc., and the quality of the data will affect the calculation of various subsequent indicators of the platform. Therefore, it is necessary to fill the missing data in the time series with high precision. In this embodiment, the data processing center is divided into two scenarios: real-time data processing and offline data processing according to the actual situation.

[0057] In one embodiment, referring to Figure 2 , Figure 2 FIG. 1 is a flow chart of an embodiment of a method for filling missing time series information of the present invention. Figure 2 As shown, the time series missing filling method includes:

[0058] Step S10: If the event time of the data received from the terminal is missing, the received data with missing event time is used as data to be filled.

[0059] In this embodiment, the data processing center of the vehicle big data system receives terminal data information from the terminal vehicle for processing. If the event time of a certain data is missing, the data is used as data to be filled.

[0060] Step S20: selecting a reference data set of the data to be filled from the received multiple pieces of data.

[0061] In this embodiment, the data processing center selects a reference data set of the data to be filled from the multiple pieces of data received, for use in the subsequent calculation of the missing time.

[0062] Step S30: using the reference data set as a reference, obtaining the delay time of the data to be filled by calculation.

[0063] In this embodiment, the reference data set selected above is used as a reference, and the delay time of the data to be filled is obtained by calculation. The delay time represents the time difference between the receiving time and the generating time of the data to be filled.

[0064] Step S40: Based on the delay time of the data to be filled and the reception time of the data to be filled, the missing time of the data to be filled is calculated.

[0065] In this embodiment, in step S30, the delay time of the data to be filled is obtained by calculation. Because the delay time represents the time difference between the reception time and the occurrence time of the data to be filled, and the reception time of the data to be filled is filled by the data processing center and is generally not missing, the missing time of the data to be filled can be calculated using the reception time of the data to be filled. The missing time here refers to the occurrence time of the data to be filled.

[0066] Step S50: Fill the event time of the data to be filled using the missing time of the data to be filled.

[0067] In this embodiment, the missing time of the data to be filled is used to fill the event time of the data to be filled, that is, the data with a complete time series after filling is obtained. Because there are two data processing scenarios, real-time and offline, in this embodiment, the filled data can be marked accordingly while filling, and the marked data is "real-time filling" or "offline filling" as a reference for subsequent data processing.

[0068] In this embodiment, the data processing center of the vehicle big data system receives data from the terminal vehicle, takes the data with missing event time as the data to be filled, selects the reference data set of the data to be filled from the multiple data received, and then calculates the delay time of the data to be filled, and obtains the missing time of the data to be filled in combination with the reception time of the data to be filled. The missing time of the data to be filled is used to fill the event time of the data to be filled, which can achieve high-precision filling of the missing time series, and at the same time mark the filled data, thereby improving the availability of the data, and then can improve the accuracy of various indicator calculations in subsequent data processing.

[0069] Further, in one embodiment, referring to Figure 3 , Figure 3 for Figure 2 The detailed flow chart of step S20 is as follows: Figure 3 As shown, step S20 includes:

[0070] Step S201, determining the data quantity N of the reference data set to be filled based on the frequency of data sent by the terminal;

[0071] Step S202, in a real-time data processing scenario, selecting, from the received multiple pieces of data, the first N pieces of complete time series data adjacent to the data to be filled as a reference data set for the data to be filled;

[0072] Step S203, in an offline data processing scenario, selecting the first N and last N complete time series data adjacent to the data to be filled from the received multiple data as reference data sets for the data to be filled.

[0073] In this embodiment, firstly, the number of data N of the reference data set of the data to be filled is determined according to the frequency of data sent by the terminal, and then the data processing scenarios are divided into real-time and offline. The data with complete time series are selected from the received data as the reference data set of the data to be filled. In the real-time data processing scenario, because it is real-time processing, only the first N pieces of complete time series data adjacent to the data to be filled can be selected as the reference data set of the data to be filled. In the offline data processing scenario, the first N and last N pieces of complete time series data adjacent to the data to be filled can be selected as the reference data set of the data to be filled. It can be seen that in the offline data processing scenario, the number of data in the selected reference data set is larger, which meets the requirements of higher accuracy of offline filling.

[0074] Furthermore, in one embodiment, step S201 includes:

[0075] According to the data to be filled, obtaining the frequency of the terminal sending data by querying;

[0076] Based on the frequency of data transmission by the terminal, the data quantity N of the reference data set to be filled is determined by a formula, and the determination formula is:

[0077]

[0078] Among them, t is the interval time for the terminal to send each piece of data, and m is the number of data sent by the terminal within 1 second.

[0079] In this embodiment, relevant information about the frequency of data sending by terminal vehicles can be stored in the database of the data processing center. According to the data to be filled, the interval time t for each data sent by the terminal and the number of data sent by the terminal within 1 second can be obtained by querying the database. The data quantity N of the reference data set of the data to be filled can be determined according to the above formula.

[0080] Furthermore, in one embodiment, step S30 includes:

[0081] The reference data set is used as a reference, and based on the generation time and reception time of the data in the reference data set, the delay time of the data to be filled is obtained by calculation, and the calculation formula is:

[0082]

[0083] Wherein, δ is the delay time of the data to be filled, T i is the occurrence time of data i in the reference data set, C i is the receiving time of data i in the reference data set, and N is the number of data in the reference data set of the data to be filled.

[0084] In this embodiment, the delay time represents the time difference between the receiving time and the generating time of the data. The delay time δ of the data to be filled is obtained by adding up the delay time of the data from 1 to N in the reference data set and dividing it by the number of data N in the reference data set to be filled, where δ is a calculated estimated value.

[0085] Furthermore, in one embodiment, step S40 includes:

[0086] Based on the delay time of the data to be filled and the reception time of the data to be filled, the missing time of the data to be filled is calculated, and the calculation formula is:

[0087] T f =C f -δ

[0088] Among them, T f is the missing time of the data to be filled, C f is the receiving time of the data to be filled, and δ is the delay time of the data to be filled.

[0089] In this embodiment, the receiving time C of the data to be filled f The data is filled by the data processing center and is generally not missing. The receiving time is the time when the data processing center receives the data from the terminal vehicle. The delay time δ of the data to be filled has been calculated in the above step S30. Subtracting the two, the missing time T of the data to be filled is obtained. f .

[0090] In a third aspect, an embodiment of the present invention further provides a time series missing filling device.

[0091] Reference Figure 4 , Figure 4 Schematic diagram of functional modules of an embodiment of a time series missing filling device of the present invention.

[0092] In this embodiment, the time series missing filling device includes:

[0093] The receiving module 10 is used for, if the event time of the data received from the terminal is missing, using the received data with missing event time as data to be filled;

[0094] A selection module 20, configured to select a reference data set of the data to be filled from the received multiple pieces of data;

[0095] A first calculation module 30, configured to use the reference data set as a reference and obtain the delay time of the data to be filled by calculation;

[0096] A second calculation module 40 is used to calculate the missing time of the data to be filled based on the delay time of the data to be filled and the receiving time of the data to be filled;

[0097] The filling module 50 is used to fill the event time of the data to be filled with the missing time of the data to be filled.

[0098] Further, in one embodiment, referring to Figure 5 , Figure 5 for Figure 4 A detailed functional module diagram of the selected module 20 is shown in FIG. Figure 5 As shown, the selection module 20 includes:

[0099] A determining unit 201, configured to determine the data quantity N of the reference data set to be filled based on the frequency of data sent by the terminal;

[0100] A real-time selection unit 202 is used to select, from the received multiple pieces of data, the first N pieces of complete time series data adjacent to the data to be filled as a reference data set for the data to be filled;

[0101] The offline selection unit 203 is used to select the first N and last N complete time series data adjacent to the data to be filled from the received multiple data in the offline data processing scenario as the reference data set of the data to be filled.

[0102] Furthermore, in one embodiment, the determination module 201 is used to:

[0103] According to the data to be filled, obtaining the frequency of the terminal sending data by querying;

[0104] Based on the frequency of data transmission by the terminal, the data quantity N of the reference data set to be filled is determined by a formula, and the determination formula is:

[0105]

[0106] Among them, t is the interval time for the terminal to send each piece of data, and m is the number of data sent by the terminal within 1 second.

[0107] Furthermore, in one embodiment, the first calculation module 30 is used to:

[0108] The reference data set is used as a reference, and based on the generation time and reception time of the data in the reference data set, the delay time of the data to be filled is obtained by calculation, and the calculation formula is:

[0109]

[0110] Wherein, δ is the delay time of the data to be filled, T i is the occurrence time of data i in the reference data set, C i is the receiving time of data i in the reference data set, and N is the number of data in the reference data set of the data to be filled.

[0111] Furthermore, in one embodiment, the second calculation module 40 is used to:

[0112] Based on the delay time of the data to be filled and the reception time of the data to be filled, the missing time of the data to be filled is calculated, and the calculation formula is:

[0113] T f =C f -δ

[0114] Among them, T f is the missing time of the data to be filled, C f is the receiving time of the data to be filled, and δ is the delay time of the data to be filled.

[0115] Among them, the functional implementation of each module in the above-mentioned time series missing filling device corresponds to the various steps in the above-mentioned time series missing filling method embodiment, and its functions and implementation processes will not be repeated here one by one.

[0116] In a fourth aspect, an embodiment of the present invention further provides a readable storage medium.

[0117] A time series missing filling program is stored on a readable storage medium of the present invention, wherein when the time series missing filling program is executed by a processor, the steps of the time series missing filling method as described above are implemented.

[0118] Among them, the method implemented when the time series missing filling program is executed can refer to the various embodiments of the time series missing filling method of the present invention, and will not be repeated here.

[0119] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0120] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0121] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for a terminal device to execute the methods described in each embodiment of the present invention.

[0122] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A time series missing filling method, characterized in that: The time series missing filling method comprises: If the event time of the data received from the terminal is missing, the received data with missing event time is used as the data to be filled; Selecting a reference data set of the data to be filled from the received multiple pieces of data; Taking the reference data set as a reference, obtaining the delay time of the data to be filled by calculation; Based on the delay time of the data to be filled and the reception time of the data to be filled, the missing time of the data to be filled is calculated; Filling the event time of the data to be filled using the missing time of the data to be filled; The step of using the reference data set as a reference and obtaining the delay time of the data to be filled by calculation includes: The reference data set is used as a reference, and based on the generation time and reception time of the data in the reference data set, the delay time of the data to be filled is obtained by calculation, and the calculation formula is: Wherein, δ is the delay time of the data to be filled, T i is the occurrence time of data i in the reference data set, C i is the receiving time of data i in the reference data set, and N is the number of data in the reference data set of the data to be filled.

2. The time series missing filling method according to claim 1, characterized in that: The step of selecting the reference data set of the data to be filled from the received multiple pieces of data includes: Determine the data quantity N of the reference data set to be filled based on the frequency of data sent by the terminal; In the real-time data processing scenario, the first N complete time series data adjacent to the data to be filled are selected from the received multiple data as the reference data set of the data to be filled; In an offline data processing scenario, the first N and last N complete time series data adjacent to the data to be filled are selected from the multiple received data as reference data sets for the data to be filled.

3. The time series missing filling method according to claim 2, characterized in that: The determining, based on the frequency at which the terminal sends data, the data quantity N of the reference data set to be filled with data comprises: According to the data to be filled, obtaining the frequency of the terminal sending data by querying; Based on the frequency of data transmission by the terminal, the data quantity N of the reference data set to be filled is determined by a formula, and the determination formula is: Among them, t is the interval time for the terminal to send each piece of data, and m is the number of data sent by the terminal within 1 second.

4. The time series missing filling method according to claim 1, characterized in that: The calculating the missing time of the data to be filled based on the delay time of the data to be filled and the receiving time of the data to be filled comprises: Based on the delay time of the data to be filled and the reception time of the data to be filled, the missing time of the data to be filled is calculated, and the calculation formula is: T f =C f -d Among them, T f is the missing time of the data to be filled, C f is the receiving time of the data to be filled, and δ is the delay time of the data to be filled.

5. A time series missing filling device, characterized in that: The time series missing filling device comprises: A receiving module, configured to use the received data with missing event time as data to be filled if the event time of the data received from the terminal is missing; A selection module, used to select a reference data set of the data to be filled from the received multiple data; A first calculation module, configured to use the reference data set as a reference and obtain the delay time of the data to be filled by calculation; A second calculation module, configured to calculate the missing time of the data to be filled based on the delay time of the data to be filled and the receiving time of the data to be filled; A filling module, used to fill the event time of the data to be filled with the missing time of the data to be filled; The first computing module is used for: The reference data set is used as a reference, and based on the generation time and reception time of the data in the reference data set, the delay time of the data to be filled is obtained by calculation, and the calculation formula is: Wherein, δ is the delay time of the data to be filled, T i is the occurrence time of data i in the reference data set, C i is the receiving time of data i in the reference data set, and N is the number of data in the reference data set of the data to be filled.

6. The time series gap filling device according to claim 5, characterized in that: The selection module is used to: Determine the data quantity N of the reference data set to be filled based on the frequency of data sent by the terminal; In the real-time data processing scenario, the first N complete time series data adjacent to the data to be filled are selected from the received multiple data as the reference data set of the data to be filled; In an offline data processing scenario, the first N and last N complete time series data adjacent to the data to be filled are selected from the multiple received data as reference data sets for the data to be filled.

7. A time series missing filling device, characterized in that: The time series gap filling device includes a processor, a memory, and a time series gap filling program stored in the memory and executable by the processor, wherein when the time series gap filling program is executed by the processor, the steps of the time series gap filling method as described in any one of claims 1 to 4 are implemented.

8. A readable storage medium, characterized in that: The readable storage medium stores a time series missing filling program, wherein when the time series missing filling program is executed by a processor, the steps of the time series missing filling method as described in any one of claims 1 to 4 are implemented.

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