Method and device for detecting carbon isotope shift period, electronic equipment and storage medium

Abstract

The invention provides a method and a device for detecting a carbon isotope shift period, electronic equipment and a storage medium. The method comprises the following steps: processing original test data of carbon isotopes by adopting a sliding window to obtain smooth data; calculating a difference value between the original test data and the smooth data, and obtaining a salient point sequence set based on the difference value and a quartering difference value method; presetting a maximum interval threshold value, and sequentially judging the distance between two adjacent offset points in the salient point sequence set based on the maximum interval threshold value to obtain a salient offset interval; and enabling the significant migration interval to correspond to original test data and smooth data to obtain a carbon isotope migration period. According to the method, the sliding window threshold processing is adopted to accurately, efficiently and universally identify the carbon isotope shift, the method is an automatic detection method which is objective and high in adaptability, better robustness is achieved, and the accuracy and consistency of CIEs boundary identification can be improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of artificial intelligence and geoscience big data, and specifically relates to a method, device, electronic equipment and storage medium for detecting a carbon isotope shift period. Background Art

[0002] Carbon isotope excursions (CIEs) are important landmark events in geological history, and are often closely related to environmental disasters such as global climate change, mass extinction, and ocean anoxic events (OAEs). CIEs reflect major disturbances in the Earth's carbon cycle at different times. These changes are reflected in the δ 13 C values ​​are recorded as key chemical signals in the geological record. 13 Changes in C represent the production, burial, and oxidation of organic carbon, and can reveal carbon exchange between the atmosphere and the ocean. Studying CIEs not only helps scientists reveal the evolution of paleoclimate and paleo-ecosystems, but also identifies the profound impact of carbon cycle disturbance events on global ecosystems.

[0003] Carbon isotope excursion events can provide important comparative tools for chronostratigraphy, especially in addressing the causal relationship between paleoclimate transitions and species extinctions. 13 CIEs provide a basis for the precise comparison of stratigraphic relationships, allowing the geological history of different regions to be more consistently compared. In addition, the definition of CIEs is crucial for calculating the duration of these events and their lag or lead relationship with environmental factors. For example, the occurrence and duration of carbon isotope shifts often have a certain time difference with important environmental events such as climate change, marine environmental changes and biological extinction events, which provides a deeper perspective on revealing the driving mechanism of climate change.

[0004] At present, there are several shortcomings in the methods for defining the boundaries of carbon isotope shifts, mainly manifested in the lack of standardization and strong subjectivity of the methods. The traditional approach usually relies on visual inspection of the inflection point position in the isotope data (i.e., "visual inspection"), which can lead to inconsistencies in the division of CIEs boundaries due to different experiences of researchers. The change point detection methods used in many studies, such as Bayesian analysis, piecewise regression, and sequence t-test, can identify significant changes in isotope curves to a certain extent, but these methods show limitations when dealing with data with large noise or subtle changes. For example, in data sets with large variations in sedimentation rates and obvious regional differences, these methods may find it difficult to accurately capture the start and end times of CIEs, resulting in deviations in the estimation of duration. Therefore, the present application contemplates a method for detecting carbon isotope shift cycles. Summary of the invention

[0005] In view of the problems existing in the prior art, the present invention provides a method, system, device and storage medium for detecting the carbon isotope shift period, so as to solve the technical problem that the start and end time of CIEs cannot be accurately and objectively captured in the prior art.

[0006] In a first aspect, an embodiment of the present invention provides a method for detecting a carbon isotope shift period, comprising the following steps:

[0007] The original experimental data of carbon isotopes were processed using a sliding window to obtain smoothed data;

[0008] Calculating the difference between the original test data and the smoothed data, and obtaining a significant point sequence set based on the difference and the quarterback difference method;

[0009] Presetting a maximum interval threshold, and determining the distance between two adjacent offset points in the significant point sequence set in sequence based on the maximum interval threshold to obtain a significant offset interval;

[0010] The significant shift interval is mapped to the original test data and the smoothed data to obtain the carbon isotope shift period.

[0011] Furthermore, the process of using a sliding window to process the original experimental data of carbon isotopes to obtain smoothed data is as follows:

[0012] The original test data is smoothed by a sliding window. For each data point, the mean of its adjacent points is used as the original value, where the number of adjacent points is the size of the sliding window:

[0013]

[0014] Where w is the size of the sliding window, i is the index of the data point, and s i is the smoothed data sequence, x j is the jth value in the original test data sequence, ranging from i-[w / 2] to i+[w / 2];

[0015] The original test data is where x i is the i-th data point, and N is the total number of sample points.

[0016] Furthermore, when the sliding window is used to process the original experimental data of carbon isotopes, the ring filling method is used at the beginning and end of the original experimental data sequence, and the front window value of the first data is used as the end of the sequence, and the back window value of the last data is used as the beginning of the sequence.

[0017] Further, the difference between the original test data and the smoothed data is calculated, and the trend slope of the smoothed data is obtained based on adjacent differences;

[0018] Based on the quarterback difference method, an offset threshold and a trend change threshold are preset. If the difference is greater than the offset threshold, the point has a significant offset and is marked as a significant offset point; if the trend slope is greater than the trend change threshold, the point has a significant change trend and is marked as a significant change trend point;

[0019] All points that meet the requirements of offset significance and trend change significance are taken as a set to obtain a significant point set, and the significant point set is sorted to obtain a significant point sequence set.

[0020] Furthermore, the difference between the original test data and the smoothed data is:

[0021] o i =x i -s i

[0022] Among them, i Represents the original data point x i With smoothed data points s i The difference between i If the deviation is positive, the data is above the trend. i If it is a negative offset, the data is below the trend;

[0023] The trend slope of the smoothed data is:

[0024] slope i =s i -s i-1

[0025] Among them, slope i represents the trend slope of the ith data point, s i is the i-th value of the smoothed data, s i-1 is the previous value of the i-th smoothed data.

[0026] Furthermore, the set of salient point sequences is:

[0027]

[0028] Among them, {i||o i |>θ offset} is a set of significant offset points that meet the offset threshold, {i||slope i |>θ slope} is a set of significant change points that meet the slope threshold, and the sort function is used to sort the merged points in index order.

[0029] Furthermore, the process of obtaining the significant deviation interval is as follows:

[0030] A maximum interval threshold max_gap is preset, and the distance between two adjacent offset points in the salient point sequence set is determined in sequence based on the maximum interval threshold max_gap. If the distance between two adjacent offset points is less than or equal to the maximum interval, they are taken as the starting point of the same interval. If the distance between two adjacent offset points is greater than the maximum interval, they are taken as the end point of the interval. This is done until all adjacent offset points in the salient point sequence set are determined to obtain a continuous interval R. k :

[0031] R k ={(P start ,P end )|P end -P start <= max_gap}

[0032] Among them, P start is the starting point of the interval, P end The end point of the interval.

[0033] In a second aspect, an embodiment of the present invention provides a system for detecting a carbon isotope shift period, comprising:

[0034] The preprocessing unit is configured as follows:

[0035] Used to process the original experimental data of carbon isotopes using a sliding window to obtain smooth data;

[0036] The computing unit is configured as:

[0037] Used to calculate the difference between the original test data and the smoothed data, and obtain a significant point sequence set based on the difference and the quarterback difference method;

[0038] The judgment unit is configured as follows:

[0039] used to preset a maximum interval threshold, and to sequentially determine the distance between two adjacent offset points in the significant point sequence set based on the maximum interval threshold to obtain a significant offset interval;

[0040] Output unit, configured as:

[0041] It is used to correspond the significant shift interval to the original test data and the smoothed data to obtain the carbon isotope shift period.

[0042] In a third aspect, an embodiment of the present disclosure provides an electronic device, the electronic device comprising:

[0043] at least one processor; and,

[0044] a memory communicatively connected to the at least one processor; wherein,

[0045] The memory stores instructions that can be executed by the at least one processor. The instructions are executed by the at least one processor so that the at least one processor can perform the above-mentioned method for detecting the carbon isotope shift period.

[0046] In a fourth aspect, an embodiment of the present disclosure provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the above-mentioned method for detecting a carbon isotope shift period.

[0047] Other optional features and technical effects of the embodiments of the present invention are partially described below, and partially can be understood by reading this document.

[0048] Compared with the prior art, the present invention has the following beneficial technical effects:

[0049] The present invention provides a method for detecting the carbon isotope shift period, comprising the following steps: using a sliding window to process the original test data of the carbon isotope to obtain smoothed data; calculating the difference between the original test data and the smoothed data, and obtaining a significant point sequence set based on the difference and the quarterback difference method; presetting a maximum interval threshold, and judging the distance between two adjacent offset points in the significant point sequence set in turn based on the maximum interval threshold to obtain a significant offset interval; corresponding the significant offset interval to the original test data and the smoothed data to obtain the carbon isotope shift period. The present application uses sliding window threshold processing to accurately, efficiently, and universally identify carbon isotope shifts, which is an objective and adaptable automated detection method with better robustness, and can improve the accuracy and consistency of CIEs boundary recognition. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 A schematic flow chart of a method for detecting a carbon isotope shift period according to an embodiment of the present disclosure is shown;

[0051] Figure 2 One of the offset interval identification results of the embodiment of the present disclosure is shown;

[0052] Figure 3 The second offset interval identification result of the embodiment of the present disclosure is shown;

[0053] Figure 4 The third offset interval identification result of the embodiment of the present disclosure is shown;

[0054] Figure 5 A device for detecting a carbon isotope shift period according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0055] The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0056] The following describes the embodiments of the present disclosure through specific examples, and those skilled in the art can easily understand other advantages and effects of the present disclosure from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all of the embodiments. The present disclosure can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present disclosure. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present disclosure.

[0057] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein may be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on the present disclosure, it should be understood by those skilled in the art that an aspect described herein may be implemented independently of any other aspect, and two or more of these aspects may be combined in various ways. For example, any number of aspects described herein may be used to implement the device and / or practice the method. In addition, other structures and / or functionalities other than one or more of the aspects described herein may be used to implement this device and / or practice this method.

[0058] It should also be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present disclosure. The drawings only show components related to the present disclosure rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0059] Additionally, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, it will be understood by those skilled in the art that the aspects described may be practiced without these specific details.

[0060] Figure 1 A flow chart 100 of a method for detecting a carbon isotope shift period disclosed in a first embodiment of the present invention is shown. Figure 1 As shown, the embodiment of the present disclosure includes the following steps:

[0061] In step S101, the original experimental data of carbon isotopes are processed using a sliding window to obtain smoothed data;

[0062] Specifically, the process of using a sliding window to process the original experimental data of carbon isotopes to obtain smoothed data is as follows:

[0063] The original test data is smoothed by a sliding window. For each data point, the mean of its adjacent points is used as the original value, where the number of adjacent points is the size of the sliding window:

[0064]

[0065] Where w is the size of the sliding window, i is the index of the data point, and s i is the smoothed data sequence, x j is the jth value in the original test data sequence, ranging from i-[w / 2] to i+[w / 2];

[0066] It should be noted that the original test data is where x i is the i-th data point, and N is the total number of sample points.

[0067] It should be further explained that the sliding window smoothing technology reduces the fluctuation or noise of the data by averaging each data point and its adjacent points in the original test data, thereby obtaining a smoother data sequence. That is, in the embodiment of the present disclosure, a fixed-size window, that is, a set of adjacent data points, is used to slide on the data, and for each position in the window, the mean of all points in the window is calculated, and this mean is used as the new data value of the position. In this way, a data sequence that is smoother than the original data can be obtained, which can effectively reduce random fluctuations in the data.

[0068] In some embodiments, when the original experimental data of carbon isotopes are processed using a sliding window, a ring filling method is used at the beginning and end of the original experimental data sequence, and the front window value of the first data is used as the end of the sequence, and the back window value of the last data is used as the beginning of the sequence. Specifically, when performing sliding window smoothing, it is assumed that the data sequence is periodic, or only for data located near the boundary. This means that when the window slides to the beginning of the data, it will "wrap around" to the end of the data to obtain missing adjacent points, and vice versa.

[0069] Next, go to step S102;

[0070] At step S102, the difference between the original test data and the smoothed data is calculated, and a significant point sequence set is obtained based on the difference and the quarterback difference method;

[0071] Specifically, the difference between the original test data and the smoothed data is calculated, and the trend slope of the smoothed data is obtained based on adjacent differences;

[0072] Based on the quarterback difference method, an offset threshold and a trend change threshold are preset. If the difference is greater than the offset threshold, the point has a significant offset and is marked as a significant offset point; if the trend slope is greater than the trend change threshold, the point has a significant change trend and is marked as a significant change trend point;

[0073] All points that meet the requirements of offset significance and trend change significance are taken as a set to obtain a significant point set, and the significant point set is sorted to obtain a significant point sequence set.

[0074] It should be noted that, in the disclosed embodiment, the quarterback difference method (IQR) is a method for measuring the degree of data dispersion. IQR is the difference between the 75th percentile (Q3) and the 25th percentile (Q1) of the data:

[0075] IQR=Q 3 -Q 1

[0076] If the data point exceeds Q 3 +1.5×IQR, the point is considered an outlier, so the offset threshold θ offset and trend change threshold θ slope Set them according to this rule respectively.

[0077] In some embodiments, the difference between the original test data and the smoothed data is:

[0078] o i =x i -s i

[0079] Among them, i Represents the original data point x i With smoothed data points s i The difference between i If the deviation is positive, the data is above the trend. i If it is a negative offset, the data is below the trend;

[0080] The trend slope of the smoothed data is:

[0081] slope i =s i -s i-1

[0082] Among them, slope i represents the trend slope of the ith data point, s i is the i-th value of the smoothed data, s i-1 is the previous value of the i-th smoothed data.

[0083] In some embodiments, the set of salient point sequences is:

[0084]

[0085] Among them, {i||o i |>θ offset} is a set of significant offset points that meet the offset threshold, {i||slope i |>θ slope} is a set of significant change points that meet the slope threshold, and the sort function is used to sort the merged points in index order.

[0086] Next, go to step S103;

[0087] In step S103, a maximum interval threshold is preset, and the distance between two adjacent offset points in the significant point sequence set is determined in sequence based on the maximum interval threshold to obtain a significant offset interval;

[0088] Specifically, the process of obtaining the significant offset interval is:

[0089] A maximum interval threshold max_gap is preset, and the distance between two adjacent offset points in the salient point sequence set is determined in sequence based on the maximum interval threshold max_gap. If the distance between two adjacent offset points is less than or equal to the maximum interval, they are taken as the starting point of the same interval. If the distance between two adjacent offset points is greater than the maximum interval, they are taken as the end point of the interval. This is done until all adjacent offset points in the salient point sequence set are determined to obtain a continuous interval R. k :

[0090] R k ={(P start ,P end )|P end -P start <= max_gap}

[0091] Among them, P start is the starting point of the interval, P end The end point of the interval.

[0092] Next, go to step S104;

[0093] In step S104, the significant shift interval is mapped to the original test data and the smoothed data to obtain the carbon isotope shift period.

[0094] Specifically, the original test data and the smoothed data are plotted on the same graph, and the significant shift intervals are mapped to the original test data and the smoothed data and highlighted. The highlighted area is the significant shift interval, and the significant shift interval is the carbon isotope shift period. Figure 2 It shows only one offset interval recognition result of the embodiment of the present disclosure, that is, a single offset recognition result, and the shaded part is the offset interval; Figure 3 FIG. 4 shows the interval recognition result including positive offset and negative offset in the embodiment of the present disclosure, and the shaded part is the offset interval. Figure 4 The embodiment of the present disclosure shows the recognition result of a continuous positive offset and a negative offset, as well as an offset interval that suddenly occurs after being stabilized, and the shaded part is the offset interval.

[0095] The second embodiment of the present invention further provides a system for detecting a carbon isotope shift period, comprising:

[0096] The preprocessing unit is configured as follows:

[0097] Used to process the original experimental data of carbon isotopes using a sliding window to obtain smooth data;

[0098] The computing unit is configured as:

[0099] Used to calculate the difference between the original test data and the smoothed data, and obtain a significant point sequence set based on the difference and the quarterback difference method;

[0100] The judgment unit is configured as follows:

[0101] used to preset a maximum interval threshold, and to sequentially determine the distance between two adjacent offset points in the significant point sequence set based on the maximum interval threshold to obtain a significant offset interval;

[0102] Output unit, configured as:

[0103] It is used to correspond the significant shift interval to the original test data and the smoothed data to obtain the carbon isotope shift period.

[0104] A third embodiment of the present invention further provides an electronic device, the electronic device comprising:

[0105] at least one processor; and,

[0106] a memory communicatively connected to the at least one processor; wherein,

[0107] The memory stores instructions that can be executed by the at least one processor. The instructions are executed by the at least one processor so that the at least one processor can perform the method for detecting a carbon isotope shift period according to any of the aforementioned embodiments.

[0108] The fourth embodiment of the present invention further provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method for detecting the carbon isotope shift period described in any of the aforementioned embodiments.

[0109] The fifth embodiment of the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer executes the method for detecting the carbon isotope shift period of any of the aforementioned embodiments.

[0110] The sixth embodiment of the present invention further provides a computer program, which includes program instructions. When the program instructions are executed by a computer, the computer is caused to execute the method for detecting the carbon isotope shift period of any of the aforementioned embodiments.

[0111] Figure 5 A schematic diagram of a method or device 1000 that can implement an embodiment of the present invention is shown, which may include more or fewer devices than shown in the figure in some embodiments. In some embodiments, it can be implemented using a single or multiple devices. In some embodiments, it can be implemented using cloud or distributed devices.

[0112] like Figure 5 As shown, the device 1000 includes a processor 1001, which can perform various appropriate operations and processes according to the program and / or data stored in the read-only memory (ROM) 1002 or the program and / or data loaded from the storage part 1008 to the random access memory (RAM) 1003. Processor 1001 can be a multi-core processor or can include multiple processors. In some embodiments, processor 1001 can include a general main processor and one or more special coprocessors, such as a central processing unit (CPU), a graphics processing unit (GPU), a neural network processor (NPU), a digital signal processor (DSP), etc. In RAM 1003, various programs and data required for the operation of device 1000 are also stored. Processor 1001, ROM 1002 and RAM 1003 are connected to each other via bus 1004. Input / output (I / O) interface 1005 is also connected to bus 1004.

[0113] The processor and the memory are used together to execute the program stored in the memory. When the program is executed by the computer, the methods, steps or functions described in the above embodiments can be implemented.

[0114] The following components are connected to the I / O interface 1005: an input section 1006 including a keyboard, a mouse, a touch screen, etc.; an output section 1007 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 1008 including a hard disk, etc.; and a communication section 1009 including a network interface card such as a LAN card, a modem, etc. The communication section 1009 performs communication processing via a network such as the Internet. A drive 1010 is also connected to the I / O interface 1005 as needed. A removable medium 1011, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 1010 as needed, so that a computer program read therefrom is installed into the storage section 1008 as needed. Figure 5 Only some components are schematically shown in the figure, which does not mean that the device 1000 only includes Figure 5 Components shown.

[0115] The systems, devices, modules or units described in the above embodiments may be implemented by a computer or its associated components. The computer may be, for example, a mobile terminal, a smart phone, a personal computer, a laptop computer, a vehicle-mounted human-computer interaction device, a personal digital assistant, a media player, a navigation device, a game console, a tablet computer, a wearable device, a smart TV, an Internet of Things system, a smart home, an industrial computer, a server or a combination thereof.

[0116] Although not shown, in an embodiment of the present invention, a computer-readable storage medium is provided, on which a computer program / instruction is stored. When the computer program / instruction is executed by a processor, the method for detecting a carbon isotope shift period described in the embodiment is implemented.

[0117] Storage media in embodiments of the present invention include permanent and non-permanent, removable and non-removable items that can be used to store information by any method or technology. Examples of storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission medium that can be used to store information that can be accessed by a computing device.

[0118] Although not shown, an embodiment of the present invention further provides a computer program product, including: a computer program / instruction, which, when executed by a processor, implements the method for detecting a carbon isotope shift period described in the embodiment.

[0119] The methods, programs, systems, devices, etc. of the embodiments of the present invention may be executed or implemented in a single or multiple networked computers, or may be practiced in a distributed computing environment. In the embodiments of this specification, in these distributed computing environments, tasks may be performed by remote processing devices connected via a communication network.

[0120] Those skilled in the art should understand that the embodiments of the present specification may be provided as methods, systems or computer program products. Therefore, those skilled in the art may imagine that the functional modules / units or controllers and related method steps described in the above embodiments may be implemented in software, hardware or a combination of software / hardware.

[0121] Unless explicitly stated, the actions or steps of the methods, programs, and embodiments of the present invention do not have to be performed in a specific order and can still achieve the desired results. In some implementations, multitasking and parallel processing are also possible or may be advantageous.

[0122] In this article, multiple embodiments of the present invention are described, but for the sake of brevity, the description of each embodiment is not exhaustive, and the same or similar features or parts between the embodiments may be omitted. In this article, "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" are meant to be applicable to at least one embodiment or example according to the present invention, but not all embodiments. The above terms do not necessarily mean to refer to the same embodiment or example. In the absence of contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples.

[0123] The exemplary systems and methods of the present invention have been specifically shown and described with reference to the above embodiments, which are merely examples of the best modes for implementing the present systems and methods. It will be appreciated by those skilled in the art that various changes may be made to the embodiments of the systems and methods described herein when implementing the present systems and / or methods without departing from the spirit and scope of the present invention as defined in the appended claims.

[0124] In addition, the method, system, device, and medium for detecting carbon isotope shift period according to the present invention can also be implemented in the following manner:

[0125] (1) A method for detecting a carbon isotope shift period, characterized in that it comprises the following steps:

[0126] The original experimental data of carbon isotopes were processed using a sliding window to obtain smoothed data;

[0127] Calculating the difference between the original test data and the smoothed data, and obtaining a significant point sequence set based on the difference and the quarterback difference method;

[0128] Presetting a maximum interval threshold, and determining the distance between two adjacent offset points in the significant point sequence set in sequence based on the maximum interval threshold to obtain a significant offset interval;

[0129] The significant shift interval is mapped to the original test data and the smoothed data to obtain the carbon isotope shift period.

[0130] (2) The method for detecting the carbon isotope shift period according to (1) is characterized in that the process of using a sliding window to process the original test data of the carbon isotope to obtain smoothed data is as follows:

[0131] The original test data is smoothed by a sliding window. For each data point, the mean of its adjacent points is used as the original value, where the number of adjacent points is the size of the sliding window:

[0132]

[0133] Where w is the size of the sliding window, i is the index of the data point, and s i is the smoothed data sequence, x j is the jth value in the original test data sequence, ranging from i-[w / 2] to i+[w / 2];

[0134] The original test data is where x i is the i-th data point, and N is the total number of sample points.

[0135] (3) The method for detecting the carbon isotope shift period according to (2) is characterized in that when the original experimental data of the carbon isotope is processed by using a sliding window, a ring filling method is used at the beginning and end of the original experimental data sequence, and the front window value of the first data is used as the end of the sequence, and the back window value of the last data is used as the beginning of the sequence.

[0136] (4) The method for detecting the carbon isotope shift period according to (1) is characterized in that the difference between the original test data and the smoothed data is calculated, and the trend slope of the smoothed data is obtained based on adjacent differences;

[0137] Based on the quarterback difference method, an offset threshold and a trend change threshold are preset. If the difference is greater than the offset threshold, the point has a significant offset and is marked as a significant offset point; if the trend slope is greater than the trend change threshold, the point has a significant change trend and is marked as a significant change trend point;

[0138] All points that meet the requirements of offset significance and trend change significance are taken as a set to obtain a significant point set, and the significant point set is sorted to obtain a significant point sequence set.

[0139] (5) The method for detecting carbon isotope shift period according to (4) is characterized in that the difference between the original test data and the smoothed data is:

[0140] o i =x i -s i

[0141] Among them, i Represents the original data point x i With smoothed data points s i The difference between i If the deviation is positive, the data is above the trend. i If it is a negative offset, the data is below the trend;

[0142] The trend slope of the smoothed data is:

[0143] slope i =s i -s i-1

[0144] Among them, slope i represents the trend slope of the ith data point, s i is the i-th value of the smoothed data, s i-1 is the previous value of the i-th smoothed data.

[0145] (6) The method for detecting carbon isotope shift period according to (4), characterized in that the set of significant point sequences is:

[0146]

[0147] Among them, {i||o i |>θ offset} is a set of significant offset points that meet the offset threshold, {i||slope i |>θ slope} is a set of significant change points that meet the slope threshold. The sort function is used to sort the merged points in index order.

[0148] (7) The method for detecting the carbon isotope shift period according to (1) is characterized in that the process of obtaining the significant shift interval is:

[0149] A maximum interval threshold max_gap is preset, and the distance between two adjacent offset points in the salient point sequence set is determined in sequence based on the maximum interval threshold max_gap. If the distance between two adjacent offset points is less than or equal to the maximum interval, they are taken as the starting point of the same interval. If the distance between two adjacent offset points is greater than the maximum interval, they are taken as the end point of the interval. This is done until all adjacent offset points in the salient point sequence set are determined to obtain a continuous interval R. k :

[0150] R k ={(P start ,P end )|P end -P start <= max_gap}

[0151] Among them, P start is the starting point of the interval, P end The end point of the interval.

[0152] (8) A system for detecting a carbon isotope shift period, based on the method for detecting a carbon isotope shift period described in any one of (1) to (7), comprising:

[0153] The preprocessing unit is configured as follows:

[0154] Used to process the original experimental data of carbon isotopes using a sliding window to obtain smooth data;

[0155] The computing unit is configured as:

[0156] Used to calculate the difference between the original test data and the smoothed data, and obtain a significant point sequence set based on the difference and the quarterback difference method;

[0157] The judgment unit is configured as follows:

[0158] used to preset a maximum interval threshold, and to sequentially determine the distance between two adjacent offset points in the significant point sequence set based on the maximum interval threshold to obtain a significant offset interval;

[0159] Output unit, configured as:

[0160] It is used to correspond the significant shift interval to the original test data and the smoothed data to obtain the carbon isotope shift period.

[0161] (9) The preprocessing unit according to (8) is further configured to:

[0162] The process for processing the original experimental data of carbon isotopes using a sliding window to obtain smoothed data is:

[0163] The original test data is smoothed by a sliding window. For each data point, the mean of its adjacent points is used as the original value, where the number of adjacent points is the size of the sliding window:

[0164]

[0165] Where w is the size of the sliding window, i is the index of the data point, and s i is the smoothed data sequence, x j is the jth value in the original test data sequence, ranging from i-[w / 2] to i+[w / 2];

[0166] The original test data is where x i is the i-th data point, and N is the total number of sample points.

[0167] (10) The preprocessing unit according to (8) is further configured to:

[0168] When the sliding window is used to process the original experimental data of carbon isotopes, the ring filling method is used at the beginning and end of the original experimental data sequence, and the front window value of the first data is used as the end of the sequence, and the back window value of the last data is used as the beginning of the sequence.

[0169] (11) The computing unit according to (8) is further configured to:

[0170] Used to calculate the difference between the original test data and the smoothed data, and obtain the trend slope of the smoothed data based on adjacent differences;

[0171] Based on the quarterback difference method, an offset threshold and a trend change threshold are preset. If the difference is greater than the offset threshold, the point has a significant offset and is marked as a significant offset point; if the trend slope is greater than the trend change threshold, the point has a significant change trend and is marked as a significant change trend point;

[0172] All points that meet the requirements of offset significance and trend change significance are taken as a set to obtain a significant point set, and the significant point set is sorted to obtain a significant point sequence set.

[0173] (12) The computing unit according to (8), further configured to:

[0174] The difference between the original test data and the smoothed data is processed as follows:

[0175] o i =x i -s i

[0176] Among them, iRepresents the original data point x i With smoothed data points s i The difference between i If the deviation is positive, the data is above the trend. i If it is a negative offset, the data is below the trend;

[0177] The trend slope of the smoothed data is:

[0178] slope i =s i -s i-1

[0179] Among them, slope i represents the trend slope of the ith data point, s i is the i-th value of the smoothed data, s i-1 is the previous value of the i-th smoothed data.

[0180] (13) The computing unit according to (8) is further configured to:

[0181] Used to output the salient point sequence set:

[0182]

[0183] Among them, {i||o i |>θ offset} is a set of significant offset points that meet the offset threshold, {i||slope i |>θ slope} is a set of significant change points that meet the slope threshold. The sort function is used to sort the merged points in index order.

[0184] (14) The determination unit according to (8) is further configured to:

[0185] A maximum interval threshold max_gap is preset, and the distance between two adjacent offset points in the salient point sequence set is determined in sequence based on the maximum interval threshold max_gap. If the distance between two adjacent offset points is less than or equal to the maximum interval, they are taken as the starting point of the same interval. If the distance between two adjacent offset points is greater than the maximum interval, they are taken as the end point of the interval. This is done until all adjacent offset points in the salient point sequence set are determined to obtain a continuous interval R. k :

[0186] R k ={(P start ,P end )|P end -P start <= max_gap}

[0187] Among them, Pstart is the starting point of the interval, P end The end point of the interval.

[0188] (15) An electronic device, characterized in that the electronic device comprises:

[0189] at least one processor; and,

[0190] a memory communicatively connected to the at least one processor; wherein,

[0191] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method for detecting the carbon isotope shift period described in any one of (1) to (14).

[0192] (16) A non-transitory computer-readable storage medium, characterized in that the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method for detecting the carbon isotope shift period described in any one of (1) to (14).

Claims

1. A method for detecting a carbon isotope shift period, characterized in that: The following steps are involved: The original experimental data of carbon isotopes were processed using a sliding window to obtain smoothed data; Calculating the difference between the original test data and the smoothed data, and obtaining a significant point sequence set based on the difference and the quarterback difference method; Presetting a maximum interval threshold, and determining the distance between two adjacent offset points in the significant point sequence set in sequence based on the maximum interval threshold to obtain a significant offset interval; The significant shift interval is mapped to the original test data and the smoothed data to obtain the carbon isotope shift period.

2. The method for detecting carbon isotope shift period according to claim 1, characterized in that: The process of using a sliding window to process the original experimental data of carbon isotopes to obtain smoothed data is as follows: The original test data is smoothed by a sliding window. For each data point, the mean of its adjacent points is used as the original value, where the number of adjacent points is the size of the sliding window: Where w is the size of the sliding window, i is the index of the data point, and s i is the smoothed data sequence, x j is the jth value in the original test data sequence, ranging from i-[w / 2] to i+[w / 2]; The original test data is where x i is the i-th data point, and N is the total number of sample points.

3. The method for detecting carbon isotope shift period according to claim 2, characterized in that: When the sliding window is used to process the original experimental data of carbon isotopes, the ring filling method is used at the beginning and end of the original experimental data sequence, and the front window value of the first data is used as the end of the sequence, and the back window value of the last data is used as the beginning of the sequence.

4. The method for detecting carbon isotope shift period according to claim 1, characterized in that: Calculating the difference between the original test data and the smoothed data, and obtaining the trend slope of the smoothed data based on adjacent differences; Based on the quarterback difference method, an offset threshold and a trend change threshold are preset. If the difference is greater than the offset threshold, the point has a significant offset and is marked as a significant offset point; if the trend slope is greater than the trend change threshold, the point has a significant change trend and is marked as a significant change trend point; All points that meet the requirements of offset significance and trend change significance are taken as a set to obtain a significant point set, and the significant point set is sorted to obtain a significant point sequence set.

5. The method for detecting carbon isotope shift period according to claim 4, characterized in that: The difference between the original test data and the smoothed data is: o i =x i -s i Among them, i Represents the original data point x i With smoothed data points s i The difference between i If the deviation is positive, the data is above the trend. i If it is a negative offset, the data is below the trend; The trend slope of the smoothed data is: slope i =s i -s i-1 Among them, slope i represents the trend slope of the ith data point, s i is the i-th value of the smoothed data, s i-1 is the previous value of the i-th smoothed data.

6. The method for detecting carbon isotope shift period according to claim 4, characterized in that: The set of salient point sequences is: Among them, {i||o i |>θ offset } is a set of significant offset points that meet the offset threshold, {i||slope i |>θ slope } is a set of significant change points that meet the slope threshold, and the sort function is used to sort the merged points in index order.

7. The method for detecting carbon isotope shift period according to claim 1, characterized in that: The process of obtaining the significant offset interval is as follows: A maximum gap threshold max_gap is preset, and the distance between two adjacent offset points in the set of significant point sequences is determined in sequence based on the maximum gap threshold max_gap. If the distance between two adjacent offset points is less than or equal to the maximum gap, they are regarded as the starting point of the same interval. If the distance between two adjacent offset points is greater than the maximum gap, they are regarded as the end point of the interval. Until all adjacent offset points of the significant point sequence set are determined, the continuous interval R is obtained. k : R k ={(P start ,P end )|P end -P start <=max_gap} Among them, P start is the starting point of the interval, P end The end point of the interval.

8. A device for detecting carbon isotope shift period, characterized in that: Based on the method for detecting the carbon isotope shift period according to any one of claims 1 to 7, the device comprises: The preprocessing unit is configured as follows: Used to process the original experimental data of carbon isotopes using a sliding window to obtain smooth data; The computing unit is configured as: Used to calculate the difference between the original test data and the smoothed data, and obtain a significant point sequence set based on the difference and the quarterback difference method; The judgment unit is configured as follows: used to preset a maximum interval threshold, and to sequentially determine the distance between two adjacent offset points in the significant point sequence set based on the maximum interval threshold to obtain a significant offset interval; Output unit, configured as: It is used to correspond the significant shift interval to the original test data and the smoothed data to obtain the carbon isotope shift period.

9. An electronic device, characterized in that: The electronic device includes: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method for detecting a carbon isotope shift period as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that: The non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method for detecting the carbon isotope shift period according to any one of claims 1 to 7.

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