Rainfall event typical weather day selection method applied to cave hot and humid environment simulation

Abstract

The embodiment of the invention provides a rainfall event typical weather day selection method applied to cave hot and humid environment simulation. The method comprises the following steps: acquiring meteorological data when a rainfall event occurs in a region where a grotto temple is located in a historical time period; performing change trend analysis and mutation detection on the various meteorological data to obtain trend change rates, correlation coefficients and mutation time points corresponding to the various meteorological data; according to the trend change rate, the correlation coefficient and the sudden change time point corresponding to various meteorological data, determining a rainfall event typical meteorological day selection time period from a historical time period; and selecting the rainfall event typical weather day from the rainfall event typical weather day selection time period. In this way, the change trend and the sudden change condition of the rainfall event in the region where the grotto temple is located can be comprehensively considered, the relatively stable time period of the rainfall event is selected as the typical weather day selection time period of the rainfall event, and then the representative typical weather day of the rainfall event is selected from the typical weather day selection time period of the rainfall event.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental simulation, and in particular to a method for selecting typical meteorological days of rainfall events for simulating thermal and humid environments of caves. Background Art

[0002] The thermal and humid environment of caves is crucial to the preservation of cave temple cultural relics. Rainfall is the main influencing factor of the thermal and humid environment of caves, and the fluctuation of the thermal and humid environment of caves caused by rainfall is the key cause of the disease of cave temple cultural relics. In recent years, numerical simulation methods have been increasingly used in the study of thermal and humid environment of cultural heritage buildings. It has many advantages such as short cycle and low cost. However, the prerequisite for simulation is to obtain typical meteorological data that can represent the climate characteristics of the area where the building is located, which is the boundary condition for thermal and humid simulation. Therefore, the meteorological data of typical meteorological days of rainfall events are the key information for simulating the thermal and humid environment of cave temples under rainfall events.

[0003] As global climate change intensifies, climate instability increases, and extreme rainfall events occur frequently, the existing methods for selecting typical meteorological days for rainfall events do not take into account the changing trends and mutations of rainfall events under the background of climate change. The selected time period of typical meteorological days is not representative enough for the characteristics of rainfall events under climate change, resulting in poor results in selecting typical meteorological days for rainfall events. Summary of the invention

[0004] In a first aspect, an embodiment of the present invention provides a method for selecting a typical meteorological day for a rainfall event applied to a cave thermal and humid environment simulation, the method comprising:

[0005] Obtain meteorological data when rainfall events occurred in the area where the cave temples are located during the historical period;

[0006] Analyze the changing trends of various meteorological data to obtain the trend changing rates and correlation coefficients corresponding to various meteorological data;

[0007] Perform mutation detection on various meteorological data to obtain the mutation time points corresponding to various meteorological data;

[0008] According to the trend change rate, correlation coefficient and mutation time point corresponding to various meteorological data, a typical meteorological day selection period of rainfall events is determined from the historical period;

[0009] A typical meteorological day for a rainfall event is selected from the typical meteorological day selection period for the rainfall event.

[0010] In some possible implementations of the first aspect, performing change trend analysis on various meteorological data to obtain trend change rates and correlation coefficients corresponding to the various meteorological data includes:

[0011] For any kind of meteorological data, a univariate linear regression is performed on the meteorological data to obtain a regression coefficient, a regression constant and a correlation coefficient. The regression coefficient is used as the trend change rate corresponding to the meteorological data, and the correlation coefficient is used as the correlation coefficient corresponding to the meteorological data.

[0012] In some possible implementations of the first aspect, performing mutation detection on various meteorological data to obtain mutation time points corresponding to the various meteorological data includes:

[0013] For any kind of meteorological data, mutation detection is performed on the meteorological data to obtain candidate mutation time points, and credibility verification is performed on the detected candidate mutation time points. The candidate mutation time points that pass the credibility verification are used as credible mutation time points and are used as the mutation time points corresponding to the meteorological data.

[0014] In some implementable embodiments of the first aspect, determining a typical meteorological day selection period for rainfall events from the historical period according to trend change rates, correlation coefficients, and mutation time points corresponding to various meteorological data includes:

[0015] For any kind of meteorological data, a significance test is performed on the correlation coefficient corresponding to the meteorological data. If the significance test is passed, the trend change level corresponding to the meteorological data is determined to be a significant change. If the significance test is not passed, the trend change level corresponding to the meteorological data is determined to be a non-significant change.

[0016] In the case where the trend change levels corresponding to various meteorological data are all significant changes or non-significant changes, for any kind of meteorological data, if the trend change rate corresponding to the meteorological data is positive, it is determined that the change trend of the meteorological data is rising, and then the rising mutation time point closest to the end time point of the historical period is selected from the mutation time points corresponding to the meteorological data as the target mutation time point; if the trend change rate corresponding to the meteorological data is negative, it is determined that the change trend of the meteorological data is falling, and then the falling mutation time point closest to the end time point of the historical period is selected from the mutation time points corresponding to the meteorological data as the target mutation time point, and the target mutation time point closest to the end time point of the historical period is selected from the target mutation time points corresponding to various meteorological data as the starting time point of the typical meteorological day selection period for rainfall events, and the end time point of the historical period is taken as the end time point of the typical meteorological day selection period for rainfall events, based on which the typical meteorological day selection period for rainfall events is determined;

[0017] In the case where there is a significant change or non-significant change in the trend change levels corresponding to various meteorological data, for any meteorological data with a significant change in trend change level, if the trend change rate corresponding to the meteorological data is positive, it is determined that the change trend of the meteorological data is rising, and then the rising mutation time point closest to the end time point of the historical period is selected from the mutation time points corresponding to the meteorological data as the target mutation time point; if the trend change rate corresponding to the meteorological data is negative, it is determined that the change trend of the meteorological data is falling, and then the falling mutation time point closest to the end time point of the historical period is selected from the mutation time points corresponding to the meteorological data as the target mutation time point; the target mutation time point closest to the end time point of the historical period is selected from the target mutation time points corresponding to various meteorological data with significant change in trend change levels as the starting time point of the typical meteorological day selection period for rainfall events, and the end time point of the historical period is taken as the end time point of the typical meteorological day selection period for rainfall events, based on which the typical meteorological day selection period for rainfall events is determined.

[0018] In some implementable embodiments of the first aspect, selecting a typical meteorological day for a rainfall event from a typical meteorological day selection period for a rainfall event includes:

[0019] The principal component analysis is performed on the meteorological data of rainfall days with different levels of rainfall events that occur within the selected period of typical meteorological days of rainfall events to obtain the principal component coefficient matrix corresponding to rainfall events of different levels;

[0020] For any level of rainfall event, the meteorological data of the rainfall day of the level of rainfall event is converted according to the principal component coefficient matrix corresponding to the level of rainfall event to obtain the principal component data of the rainfall day of the level of rainfall event, and the rainfall days of the level of rainfall event are clustered according to the principal component data of the rainfall day of the level of rainfall event to obtain multiple categories, and the rainfall day closest to the center of each category is selected as the typical meteorological day of the rainfall event of that level.

[0021] In some implementations of the first aspect, the method further includes:

[0022] Based on the meteorological data of a typical meteorological day with selected rainfall events, the thermal and humid environment of the cave temple was simulated.

[0023] In a second aspect, an embodiment of the present invention provides a typical meteorological day selection device for rainfall events applied to cave thermal and humid environment simulation, the device comprising:

[0024] The acquisition module is used to obtain the meteorological data of the area where the grotto temple is located when rainfall events occurred during the historical period;

[0025] The analysis module is used to analyze the change trend of various meteorological data and obtain the trend change rate and correlation coefficient corresponding to various meteorological data;

[0026] The detection module is used to perform mutation detection on various meteorological data to obtain the mutation time points corresponding to various meteorological data;

[0027] A determination module is used to determine a typical meteorological day selection period for rainfall events from the historical period according to the trend change rate, correlation coefficient and mutation time point corresponding to various meteorological data;

[0028] The selection module is used to select a typical meteorological day for a rainfall event from the typical meteorological day selection period for a rainfall event.

[0029] In a third aspect, an embodiment of the present invention provides an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method described above.

[0030] In a fourth aspect, an embodiment of the present invention provides a non-transitory computer-readable storage medium storing computer instructions, where the computer instructions are used to enable a computer to execute the method described above.

[0031] In an embodiment of the present invention, the changing trend and mutation of rainfall events in the area where the grotto temple is located can be comprehensively considered, and a period of relatively stable rainfall events can be selected as a period for selecting typical meteorological days for rainfall events, and then representative typical meteorological days for rainfall events can be selected therefrom, thereby greatly improving the effect of selecting typical meteorological days for rainfall events.

[0032] It should be understood that the contents described in the summary of the invention are not intended to limit the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The above and other features, advantages and aspects of the embodiments of the present invention will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present invention. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, wherein:

[0034] Figure 1 A flowchart of a method for selecting a typical meteorological day for a rainfall event applied to a cave thermal and humid environment simulation provided by an embodiment of the present invention;

[0035] Figure 2A structural diagram of a typical meteorological day selection device for rainfall events applied to cave thermal and humid environment simulation provided by an embodiment of the present invention;

[0036] Figure 3 The figure is a structural diagram of an exemplary electronic device capable of implementing an embodiment of the present invention. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] In addition, the term "and / or" in the present invention is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in the present invention generally indicates that the associated objects before and after are in an "or" relationship.

[0039] In order to solve the technical problems arising from the background technology, the embodiments of the present invention provide a method, device, equipment and storage medium for selecting typical meteorological days for rainfall events applied to cave thermal and humid environment simulation. Specifically, the meteorological data of the area where the grotto temple is located when a rainfall event occurs in a historical period is obtained; the trend analysis and mutation detection of various meteorological data are performed to obtain the trend change rate, correlation coefficient and mutation time point corresponding to various meteorological data; according to the trend change rate, correlation coefficient and mutation time point corresponding to various meteorological data, the typical meteorological day selection period of rainfall events is determined from the historical period; the typical meteorological day of rainfall events is selected from the typical meteorological day selection period of rainfall events.

[0040] In this way, the changing trend and mutation of rainfall events in the area where the grotto temples are located can be comprehensively considered, and the period of relatively stable rainfall events can be selected as the period for selecting typical meteorological days for rainfall events, and then representative typical meteorological days for rainfall events can be selected from them, which greatly improves the effect of selecting typical meteorological days for rainfall events.

[0041] In conjunction with the accompanying drawings, a method, device, equipment and storage medium for selecting a typical meteorological day for a rainfall event for simulating a thermal and humid environment in a cave provided by an embodiment of the present invention will be described in detail through specific embodiments.

[0042] Figure 1A flowchart of a method for selecting a typical meteorological day for a rainfall event applied to a cave thermal and humid environment simulation provided by an embodiment of the present invention is shown in FIG. Figure 1 As shown, the method 100 for selecting a typical meteorological day for a rainfall event may include the following steps:

[0043] S110, obtaining meteorological data of rainfall events occurring in the area where the grotto temple is located during a historical period.

[0044] Among them, the historical period can be selected according to actual conditions, such as 30 years, 40 years, 50 years, etc.; the meteorological data is meteorological data related to rainfall events, such as rainfall intensity, rainfall days, rainfall amount, etc., and there is no restriction here.

[0045] S120, analyzing the change trends of various meteorological data to obtain trend change rates and correlation coefficients corresponding to the various meteorological data.

[0046] In some embodiments, for any type of meteorological data, a univariate linear regression can be performed on the meteorological data to obtain a regression coefficient, a regression constant and a correlation coefficient. The regression coefficient is used as the trend change rate corresponding to the meteorological data, and the correlation coefficient is used as the correlation coefficient corresponding to the meteorological data.

[0047] The algorithm used for univariate linear regression may be the least square method of linear tendency estimation or other linear regression algorithms, which are not limited here; the univariate linear regression equation may be as follows:

[0048] y=at+b (1)

[0049] In the formula, y represents a certain type of meteorological data; t represents the year; a represents the regression coefficient, that is, the trend change rate (also known as the tendency value) corresponding to the meteorological data, which is mainly used to quantitatively describe the trend change characteristics of the meteorological data series. A positive value indicates an increase, and a negative value indicates a decrease. The size of a reflects the rate of increase or decrease; b represents the regression constant.

[0050] It is worth noting that the formula does not express the correlation coefficient r, which represents the closeness of the linear correlation between y and t. The smaller |r| is, the smaller the linear correlation between y and t is, and the larger |r| is, the greater the linear correlation between y and t is.

[0051] S130, performing mutation detection on various meteorological data to obtain mutation time points corresponding to various meteorological data.

[0052] In some embodiments, for any type of meteorological data, mutation detection can be performed on the meteorological data to obtain candidate mutation time points, and the detected candidate mutation time points can be subjected to a credibility check. The candidate mutation time points that pass the credibility check are used as credible mutation time points, and are used as mutation time points corresponding to the meteorological data.

[0053] The algorithm used for mutation detection may be the cumulative deviation method, the Mann-Kendall method, etc.; the algorithm used for credibility test may be the sliding t test method and other credibility test algorithms, etc., which are not limited here. For example, mutation detection algorithms and credibility test algorithms suitable for meteorological data may be selected according to the characteristics of meteorological data for mutation detection and credibility test.

[0054] For ease of understanding, the cumulative deviation method, Mann-Kendall method, and sliding t-test method are described in detail below:

[0055] The cumulative anomaly method is a commonly used method to determine the trend of meteorological data series. The cumulative anomaly curve is drawn by the cumulative anomaly method. According to the trend of the curve, the specific change process of meteorological data is analyzed, the stage change of meteorological data is determined, and the approximate time point of mutation is diagnosed. For a meteorological data series x, the cumulative anomaly at a certain time point t is expressed as:

[0056]

[0057] Here, the cumulative anomaly values ​​of n time points are all calculated, and the cumulative anomaly curve can be drawn for analysis. The cumulative anomaly curve shows an upward trend, indicating an increase in the anomaly value, and a downward trend indicates a decrease in the anomaly value. The obvious ups and downs of the curve can be used to determine its long-term significant evolution trend and continuous changes, and even the approximate time point of the mutation can be diagnosed. The small fluctuations of the curve can be used to examine its short-term anomaly value changes. The possible mutation time points of the meteorological data series, that is, the candidate mutation time points, are tested using the sliding t test method to verify the authenticity of the mutation time points and enhance the credibility of the mutation detection results.

[0058] The Mann-Kendall method is a nonparametric mutation detection method that does not require samples to follow a certain distribution and is not affected by a small number of outliers. It has the advantages of a wide detection range, high degree of quantification, and low artificiality. It is currently a mutation detection method with a strong theoretical basis and is widely used. Under the assumption that the time series is random and independent, the statistic is defined as:

[0059]

[0060] Where, UF1 = 0, E(s k ) and Var(s k ) represent the cumulative number s k The mean and variance of all UF kA curve UF is formed, and the same algorithm is applied to the reverse sequence to obtain another curve UB. In the test curve, if the UF and UB lines change within the critical line, it indicates that the change trend and mutation are not obvious; if the value of UF or UB is greater than 0, it indicates that the sequence is on an upward trend, and if it is less than 0, it indicates a downward trend; when they exceed the critical value confidence line, it indicates that the rise or fall is significant. Under the premise that the UF curve exceeds the critical value confidence line, if the UF and UB curves have only one obvious intersection point, and the intersection point is between the confidence lines, then the intersection point is the mutation time point; if the intersection point appears outside the confidence line, or there are multiple obvious intersection points, it is uncertain whether it is the mutation time point. After the Mann-Kendall method test, the mutation time point and possible mutation time point (collectively referred to as candidate mutation time point) of the meteorological data series are tested with the same test method as the cumulative deviation method results, namely the sliding t test method, to enhance the credibility of the mutation detection results.

[0061] The sliding t-test method determines the mutation of the sequence by continuously changing the length of the subsequence before and after the reference point and testing whether there is a significant difference in the average values ​​of the two groups of samples. The algorithm is simple to calculate, the results are intuitive, and it avoids human interference in the selection of subsequences, thereby increasing the reliability of the results. Here, the candidate mutation time points detected by the cumulative deviation method and the Mann-Kendall method are used as the reference points, and the significance levels are α=0.05, 0.01, and 0.001 respectively. The length of the sub-meteorological data sequence before and after the reference point is continuously changed, and the minimum value of the sub-meteorological data sequence is 3 years, and the sliding t test is performed year by year. If the sliding t-test result is significant, the point is determined to be a significant mutation time point, that is, a credible mutation time point.

[0062] S140, determining a typical meteorological day selection period for rainfall events from a historical period according to the trend change rate, correlation coefficient and mutation time point corresponding to various meteorological data.

[0063] In some embodiments, for any type of meteorological data, a significance test is performed on the correlation coefficient corresponding to the meteorological data. If the significance test passes, the trend change level corresponding to the meteorological data is determined to be a significant change. If the significance test fails, the trend change level corresponding to the meteorological data is determined to be a non-significant change.

[0064] Exemplarily, the significance test described here is specifically as follows:

[0065] Determine the significance level α, if |r|>r α , it indicates that the changing trend of y with t is significant, that is, it passes the significance test; otherwise, it indicates that the changing trend is not significant, that is, it fails the significance test.

[0066] When the trend change levels corresponding to various meteorological data are all significant changes or non-significant changes, for any kind of meteorological data, if the trend change rate corresponding to the meteorological data is positive, it is determined that the change trend of the meteorological data is rising, and then the rising mutation time point closest to the end time point of the historical period is selected from the mutation time points corresponding to the meteorological data (the meteorological data fluctuations decreased in the period before it, and the meteorological data fluctuations increased in the period after it) as the target mutation time point; if the trend change rate corresponding to the meteorological data is negative, it is determined that the change trend of the meteorological data is falling, and then the falling mutation time point closest to the end time point of the historical period is selected from the mutation time points corresponding to the meteorological data (the meteorological data fluctuations increased in the period before it, and the meteorological data fluctuations decreased in the period after it) as the target mutation time point; the target mutation time point closest to the end time point of the historical period is selected from the target mutation time points corresponding to various meteorological data as the starting time point of the typical meteorological day selection period for rainfall events, and the end time point of the historical period is taken as the end time point of the typical meteorological day selection period for rainfall events, based on which the typical meteorological day selection period for rainfall events is determined.

[0067] In the case where there are significant changes or non-significant changes in the trend change levels corresponding to various meteorological data, for any meteorological data with a significant change level, if the trend change rate corresponding to this meteorological data is positive, it is determined that the change trend of this meteorological data is rising, and then the rising mutation time point closest to the end time point of the historical period is selected from the mutation time points corresponding to this meteorological data as the target mutation time point; if the trend change rate corresponding to this meteorological data is negative, it is determined that the change trend of this meteorological data is falling, and then the falling mutation time point closest to the end time point of the historical period is selected from the mutation time points corresponding to this meteorological data as the target mutation time point; the target mutation time point closest to the end time point of the historical period is selected from the target mutation time points corresponding to various meteorological data with significant change levels as the starting time point of the typical meteorological day selection period for rainfall events, and the end time point of the historical period is taken as the end time point of the typical meteorological day selection period for rainfall events, based on which the typical meteorological day selection period for rainfall events is determined.

[0068] S150, selecting a typical meteorological day for a rainfall event from a typical meteorological day selection period for a rainfall event.

[0069] In some embodiments, a principal component analysis method and a clustering method may be used to select a typical meteorological day for a rainfall event from a typical meteorological day selection period for a rainfall event.

[0070] For example, the meteorological data of rainfall days of rainfall events of different levels occurring within the typical meteorological day selection period of rainfall events (for example, meteorological factors such as rainfall day temperature, rainfall day humidity, rainfall day radiation, rainfall day wind speed, etc.) can be subjected to principal component analysis to obtain the principal component coefficient matrix corresponding to rainfall events of different levels. It is worth noting that before this, the meteorological data of rainfall days of rainfall events of each level need to be tested for the suitability of principal component analysis, and only the meteorological data of rainfall days of rainfall events of the level that pass the test can be subjected to principal component analysis.

[0071] For any level of rainfall event, the meteorological data of the rainfall day of the rainfall event of this level is converted according to the principal component coefficient matrix corresponding to the rainfall event of this level to obtain the principal component data of the rainfall day of the rainfall event of this level; the rainfall days of the rainfall event of this level are clustered according to the principal component data of the rainfall day of the rainfall event of this level to obtain multiple categories; and the rainfall day closest to the center of each category is selected as the typical meteorological day of the rainfall event of this level.

[0072] For example, taking the light rain event as an example, the meteorological data of the rainy day of the light rain event is converted according to the principal component coefficient matrix corresponding to the light rain event, and the principal component data of the rainy day of the light rain event, that is, the principal component score, is obtained. The rainy day of the light rain event is clustered by K-means according to the principal component data of the rainy day of the light rain event to obtain multiple categories, and the rainy day closest to the center of each category is selected as the typical meteorological day of the light rain event. It is worth noting that before K-means clustering, the number of clusters needs to be determined first, and the number of clusters can be determined by the "elbow method".

[0073] To sum up, the embodiments of the present invention can comprehensively consider the changing trends and mutations of rainfall events in the area where the grotto temples are located, select a period of relatively stable rainfall events as the period for selecting typical meteorological days for rainfall events, and then select representative typical meteorological days for rainfall events therefrom, thereby greatly improving the effect of selecting typical meteorological days for rainfall events.

[0074] In some embodiments, the method 100 for selecting a typical meteorological day for a rainfall event may further include:

[0075] Based on the meteorological data of a typical meteorological day with selected rainfall events, the thermal and humid environment of the cave temple was simulated.

[0076] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should know that the present invention is not limited by the described order of actions, because according to the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0077] The above is an introduction to a method embodiment. The following is a further explanation of the solution of the present invention through an apparatus embodiment.

[0078] Figure 2 The structure diagram of a typical meteorological day selection device for rainfall events applied to cave thermal and humid environment simulation provided by an embodiment of the present invention is as follows: Figure 2 As shown, the typical meteorological day selection device 200 for rainfall events may include:

[0079] The acquisition module 210 is used to obtain meteorological data when rainfall events occurred in the area where the grotto temple is located during a historical period;

[0080] The analysis module 220 is used to analyze the change trend of various meteorological data to obtain the trend change rate and correlation coefficient corresponding to the various meteorological data;

[0081] The detection module 230 is used to perform mutation detection on various meteorological data to obtain mutation time points corresponding to various meteorological data;

[0082] A determination module 240 is used to determine a typical meteorological day selection period for rainfall events from a historical period according to trend change rates, correlation coefficients, and mutation time points corresponding to various meteorological data;

[0083] The selection module 250 is used to select a typical meteorological day for a rainfall event from within a typical meteorological day selection period for a rainfall event.

[0084] Understandably, Figure 2 Each module / unit in the typical meteorological day selection device 200 for rainfall events shown in the figure has the function of realizing Figure 1 The functions of the various steps in the typical meteorological day selection method 100 for rainfall events shown can achieve their corresponding technical effects, and for the sake of brevity, they will not be repeated here.

[0085] Figure 3300 is a block diagram of an exemplary electronic device capable of implementing an embodiment of the present invention. Electronic device 300 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic device 300 may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown in the present invention, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required in the present invention.

[0086] like Figure 3 As shown, the electronic device 300 may include a computing unit 301, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 302 or a computer program loaded from a storage unit 308 into a random access memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the electronic device 300 may also be stored. The computing unit 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0087] A number of components in the electronic device 300 are connected to the I / O interface 305, including: an input unit 306, such as a keyboard, a mouse, etc.; an output unit 307, such as various types of displays, speakers, etc.; a storage unit 308, such as a disk, an optical disk, etc.; and a communication unit 309, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 309 allows the electronic device 300 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0088] The computing unit 301 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 301 performs the various methods and processes described above, such as method 100. For example, in some embodiments, the method 100 may be implemented as a computer program product, including a computer program, which is tangibly contained in a computer-readable medium, such as a storage unit 308. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 300 via the ROM 302 and / or the communication unit 309. When the computer program is loaded into the RAM 303 and executed by the computing unit 301, one or more steps of the method 100 described above may be performed. Alternatively, in other embodiments, the computing unit 301 may be configured to perform the method 100 in any other appropriate manner (e.g., by means of firmware).

[0089] The various embodiments described above in the present invention can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs, which may be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general programmable processor, which may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0090] The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0091] In the context of the present invention, a computer-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. A computer-readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. A more specific example of a computer-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0092] It should be noted that the present invention also provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable a computer to execute method 100 and achieve the corresponding technical effect achieved by executing the method in an embodiment of the present invention. For the sake of concise description, they will not be repeated here.

[0093] In addition, the present invention also provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the method 100 is implemented.

[0094] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution disclosed in the present invention can be achieved, and the present invention is not limited here.

[0095] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for selecting typical meteorological days for rainfall events applied to cave thermal and humid environment simulation, characterized in that: The method comprises: Obtain meteorological data when rainfall events occurred in the area where the cave temples are located during the historical period; Analyze the changing trends of various meteorological data to obtain the trend changing rates and correlation coefficients corresponding to various meteorological data; Perform mutation detection on various meteorological data to obtain the mutation time points corresponding to various meteorological data; According to the trend change rate, correlation coefficient and mutation time point corresponding to various meteorological data, a typical meteorological day selection period of rainfall events is determined from the historical period; A typical meteorological day for a rainfall event is selected from the typical meteorological day selection period for the rainfall event.

2. The method according to claim 1, characterized in that The change trend analysis of various meteorological data is performed to obtain the trend change rate and correlation coefficient corresponding to various meteorological data, including: For any kind of meteorological data, a univariate linear regression is performed on the meteorological data to obtain a regression coefficient, a regression constant and a correlation coefficient. The regression coefficient is used as the trend change rate corresponding to the meteorological data, and the correlation coefficient is used as the correlation coefficient corresponding to the meteorological data.

3. The method according to claim 1, characterized in that The mutation detection is performed on various meteorological data to obtain the mutation time points corresponding to various meteorological data, including: For any kind of meteorological data, mutation detection is performed on the meteorological data to obtain candidate mutation time points, and credibility verification is performed on the detected candidate mutation time points. The candidate mutation time points that pass the credibility verification are used as credible mutation time points, and are used as the mutation time points corresponding to the meteorological data.

4. The method according to claim 1, characterized in that: The method of determining a typical meteorological day selection period for rainfall events from the historical period according to the trend change rate, correlation coefficient and mutation time point corresponding to various meteorological data includes: For any kind of meteorological data, a significance test is performed on the correlation coefficient corresponding to the meteorological data. If the significance test is passed, the trend change level corresponding to the meteorological data is determined to be a significant change. If the significance test is not passed, the trend change level corresponding to the meteorological data is determined to be a non-significant change. In the case where the trend change levels corresponding to various meteorological data are all significant changes or non-significant changes, for any kind of meteorological data, if the trend change rate corresponding to the meteorological data is positive, it is determined that the change trend of the meteorological data is rising, and then the rising mutation time point closest to the end time point of the historical period is selected from the mutation time points corresponding to the meteorological data as the target mutation time point; if the trend change rate corresponding to the meteorological data is negative, it is determined that the change trend of the meteorological data is falling, and then the falling mutation time point closest to the end time point of the historical period is selected from the mutation time points corresponding to the meteorological data as the target mutation time point, and the target mutation time point closest to the end time point of the historical period is selected from the target mutation time points corresponding to various meteorological data as the starting time point of the typical meteorological day selection period for rainfall events, and the end time point of the historical period is taken as the end time point of the typical meteorological day selection period for rainfall events, based on which the typical meteorological day selection period for rainfall events is determined; In the case where there is a significant change or non-significant change in the trend change levels corresponding to various meteorological data, for any meteorological data with a significant change in trend change level, if the trend change rate corresponding to the meteorological data is positive, it is determined that the change trend of the meteorological data is rising, and then the rising mutation time point closest to the end time point of the historical period is selected from the mutation time points corresponding to the meteorological data as the target mutation time point; if the trend change rate corresponding to the meteorological data is negative, it is determined that the change trend of the meteorological data is falling, and then the falling mutation time point closest to the end time point of the historical period is selected from the mutation time points corresponding to the meteorological data as the target mutation time point; the target mutation time point closest to the end time point of the historical period is selected from the target mutation time points corresponding to various meteorological data with significant change in trend change levels as the starting time point of the typical meteorological day selection period for rainfall events, and the end time point of the historical period is taken as the end time point of the typical meteorological day selection period for rainfall events, based on which the typical meteorological day selection period for rainfall events is determined.

5. The method according to claim 1, characterized in that The selecting a typical meteorological day for a rainfall event from the typical meteorological day selection period for the rainfall event includes: Performing principal component analysis on the meteorological data of rainfall events of different levels occurring within the selected period of the typical meteorological day of the rainfall event to obtain the principal component coefficient matrix corresponding to the rainfall events of different levels; For any level of rainfall event, the meteorological data of the rainfall day of the rainfall event of said level is converted according to the principal component coefficient matrix corresponding to the rainfall event of said level to obtain the principal component data of the rainfall day of the rainfall event of said level; the rainfall days of the rainfall event of said level are clustered according to the principal component data of the rainfall day of the rainfall event of said level to obtain multiple categories; and the rainfall day closest to the center of each category is selected as the typical meteorological day of the rainfall event of said level.

6. The method according to claim 1, characterized in that The method further comprises: Based on the meteorological data of a typical meteorological day of a selected rainfall event, a thermal and humid environment simulation of the cave temple is carried out.

7. A typical meteorological day selection device for rainfall events applied to cave thermal and humid environment simulation, characterized in that: The device comprises: The acquisition module is used to obtain the meteorological data of the area where the grotto temple is located when rainfall events occurred during the historical period; The analysis module is used to analyze the change trend of various meteorological data and obtain the trend change rate and correlation coefficient corresponding to various meteorological data; The detection module is used to perform mutation detection on various meteorological data to obtain the mutation time points corresponding to various meteorological data; A determination module is used to determine a typical meteorological day selection period for rainfall events from the historical period according to the trend change rate, correlation coefficient and mutation time point corresponding to various meteorological data; The selection module is used to select a typical meteorological day for a rainfall event from the typical meteorological day selection period for a rainfall event.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can perform the method according to any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 6.

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