Artificial Intelligence-Based Method, System and Device for Transmitting Automotive Financial Transaction Data

Abstract

The present invention discloses an artificial intelligence-based method for transmitting automotive financial transaction data, which relates to the technical field of data processing. The method includes obtaining automotive financial transaction data and a transmission path, obtaining the automotive financial transaction time and the data volume value, and obtaining an initial transmission interval; generating a data transmission sequence queue; generating a basic bit value according to the number of digits and the highest bit of the data volume value; calculating the transmission resource occupancy ratio according to the basic bit value, and generating an actual transmission interval according to the transmission resource occupancy ratio; completing data transmission according to a plurality of actual transmission intervals and the data transmission sequence queue, and obtaining the transmission arrival time interval; obtaining the time difference according to the actual transmission interval and the transmission arrival time interval, obtaining a path correction factor according to the time difference, and generating a new initial transmission interval according to the path correction factor and the initial transmission interval. The present invention has the advantages of sequential transmission, high transmission efficiency, good stability, and dynamic correction and adjustment.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and particularly to a method, system and device for transmitting automotive financial transaction data based on artificial intelligence. Background Art

[0002] With the rapid development of the automotive industry and the deep integration of fintech, the automotive financial market is experiencing unprecedented growth. In this process, the transmission of automotive financial transaction data plays a crucial role. However, with the continuous increase in the volume of transaction data, the challenges faced by data transmission are becoming increasingly severe.

[0003] In the existing data transmission, the transmission of relatively large transaction data often takes a longer time. If the transmission interval is set improperly, it is very easy to cause network congestion, thereby affecting the real-time performance and reliability of data transmission. Especially during the peak hours of automotive financial transactions, a large amount of data floods into the transmission network simultaneously, posing extremely high requirements on the network's carrying capacity; at the same time, the processing of a large amount of data also brings a huge computational burden. In traditional data transmission methods, in order to ensure the accuracy and integrity of data, complex calculations and verifications are often required, which not only consumes a large amount of computing power resources but also increases the latency of data transmission; more critically, the carrying capacity of the same transmission path will also change significantly under different times, hardware performance changes or load conditions. It is very difficult to adapt to the requirements of the actual transmission environment and prone to network congestion or other abnormal situations only according to the logic that the data transmission interval is the same if the transmission paths are the same. Summary of the Invention

[0004] Aiming at the defects in the prior art, the present invention provides a method, system and device for transmitting automotive financial transaction data based on artificial intelligence.

[0005] A method for transmitting automotive finance transaction data based on artificial intelligence, comprising: obtaining a plurality of automotive finance transaction data and a transmission path, obtaining the corresponding automotive finance transaction time and data volume value according to the automotive finance transaction data, and obtaining the initial transmission interval corresponding to the transmission path; arranging a plurality of automotive finance transaction times in sequence to generate a data transmission sequence queue; generating a basic bit value according to the number of digits and the highest bit of the data volume value, so as to obtain a plurality of basic bit values; calculating the transmission resource ratio of each automotive finance transaction data according to the plurality of basic bit values, and generating an actual transmission interval corresponding to the automotive finance transaction data according to the transmission resource ratio and the initial transmission interval; sequentially completing data transmission according to the plurality of actual transmission intervals and the data transmission sequence queue, and obtaining the transmission arrival time interval of the plurality of automotive finance transaction data; obtaining a time difference according to the actual transmission interval and the corresponding transmission arrival time interval, obtaining a path correction factor according to the plurality of time differences, and generating a new initial transmission interval according to the path correction factor and the initial transmission interval, wherein the new initial transmission interval is applied to the transmission process of a new round of a plurality of automotive finance transaction data on the transmission path.

[0006] Preferably, generating a basic bit value according to the number of digits and the highest bit of the data volume value includes: generating a first string n1 according to the number of digits of the data volume value; generating a second string n2 according to the highest bit of the data volume value; splicing the first string and the second string to generate a basic bit value B, wherein, B = n1‖n2.

[0007] Preferably, obtaining a path correction factor according to a plurality of time differences includes: obtaining a stability index according to the plurality of time differences; obtaining a plurality of time differences less than the stability index and using them as a plurality of to-be-processed differences; taking the average of the plurality of to-be-processed differences and generating a path correction factor according to the average value.

[0008] Preferably, obtaining a stability index according to a plurality of time differences is expressed as: Wherein, W is the stability index, Δt max is the maximum value among the plurality of time differences, and α is a preset reduction coefficient.

[0009] Preferably, taking the average of the plurality of to-be-processed differences and generating a path correction factor is expressed as: Wherein, M is the path correction factor, Δt i is the i-th to-be-processed difference, m is the number of to-be-processed differences, and β is the transmission environment delay coefficient.

[0010] Preferably, calculating the transmission resource ratio of each automotive finance transaction data according to a plurality of basic bit values is expressed as: Wherein, R j is the transmission resource ratio of the j-th automotive finance transaction data, B jis the base value of the j-th automotive finance transaction data, B k is the base value of the k-th automotive finance transaction data, and n is the number of automotive finance transaction data.

[0011] Preferably, the actual transmission interval corresponding to the automotive finance transaction data is generated according to the transmission resource ratio and the initial transmission interval, which is expressed as: T j = R j ·t c ; where T j is the actual transmission interval between the j-th and the (j + 1)-th automotive finance transaction data, and t c is the initial transmission interval.

[0012] There is also provided an automotive finance transaction data transmission system based on artificial intelligence. The system is used to implement the automotive finance transaction data transmission method based on artificial intelligence. The system includes: a data and path acquisition module, configured to acquire a plurality of automotive finance transaction data and a transmission path, and acquire the corresponding automotive finance transaction time and data volume value according to the automotive finance transaction data, and acquire the initial transmission interval corresponding to the transmission path; a queue generation module, configured to arrange a plurality of automotive finance transaction times in sequence and generate a data transmission sequence queue; a data processing module, configured to generate a base value according to the number of digits and the highest digit of the data volume value, so as to obtain a plurality of base values; a calculation module, configured to calculate the transmission resource ratio of each automotive finance transaction data according to the plurality of base values, and generate the actual transmission interval corresponding to the automotive finance transaction data according to the transmission resource ratio and the initial transmission interval; a transmission module, configured to sequentially complete data transmission according to the plurality of actual transmission intervals and the data transmission sequence queue, and acquire the transmission arrival time interval of the plurality of automotive finance transaction data; a transmission feedback and update module, configured to obtain the time difference according to the actual transmission interval and the corresponding transmission arrival time interval, obtain the path correction factor according to the plurality of time differences, and generate a new initial transmission interval according to the path correction factor and the initial transmission interval, where the new initial transmission interval is applied to the transmission process of a new round of a plurality of automotive finance transaction data on the transmission path.

[0013] There is also provided an electronic device, including: a memory, on which a computer program is stored; a processor, configured to execute the computer program in the memory to implement the above-mentioned automotive finance transaction data transmission method based on artificial intelligence.

[0014] There is also provided a non-transitory computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, it implements the above-mentioned automotive finance transaction data transmission method based on artificial intelligence.

[0015] The beneficial effects of the present invention are reflected in:

[0016] In the entire artificial intelligence-based automotive financial transaction data transmission method, first, by accurately obtaining the transaction time, data volume value, and initial transmission interval of each automotive financial transaction data, this method can establish an orderly data transmission system, ensuring the accurate transmission of data in chronological order, and improving the reliability and real-time performance of data transmission; further, by introducing the concept of a basic bit value and generating the basic bit value according to the number of digits and the highest bit of the data volume value, this method simplifies the processing process of complex data volume values, improves the calculation efficiency, and reduces the computational burden on the system; further, based on the proportion of transmission resources calculated based on the basic bit value, the optimal allocation of transmission resources is achieved, ensuring that transaction data with large data volume values can obtain sufficient transmission bandwidth and time, effectively avoiding network congestion and data transmission delays; further, by dynamically adjusting the actual transmission interval, considering the changes in the carrying capacity of the transmission path at different times, hardware performance changes, or load conditions, the data transmission becomes more flexible and adapts to the requirements of the actual transmission environment. Among them, by calculating the time difference and the path correction factor, this method can adjust the initial transmission interval in real time, continuously iterate and optimize the transmission strategy, and further improve the transmission efficiency and accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts do not necessarily draw to actual scale.

[0018] Figure 1 It is a schematic diagram of the steps of the artificial intelligence-based automotive financial transaction data transmission method of the present invention;

[0019] Figure 2 It is a schematic diagram of the steps of S3 in the artificial intelligence-based automotive financial transaction data transmission method of the present invention;

[0020] Figure 3 It is a partial schematic diagram of the steps of S6 in the artificial intelligence-based automotive financial transaction data transmission method of the present invention;

[0021] Figure 4 It is a block diagram of an electronic device shown in an embodiment of the present invention.

[0022] Reference Numerals:

[0023] 700 - Electronic device, 701 - Processor, 702 - Memory, 703 - Multimedia component, 704 - Input / Output (I / O) interface, 705 - Communication component. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0024] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and illustrated herein can be arranged and designed in various different configurations.

[0025] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0026] It should be noted that like reference numerals and letters denote like items in the following drawings. Therefore, once an item is defined in one drawing, it does not require further definition and explanation in subsequent drawings. In addition, the terms "first", "second", etc. are only used for descriptive distinction and cannot be construed as indicating or implying relative importance.

[0027] As Figure 1 shown, a method for transmitting automotive finance transaction data based on artificial intelligence is provided, including:

[0028] S1. Obtain a plurality of automotive finance transaction data and transmission paths, obtain the corresponding automotive finance transaction time and data volume value according to the automotive finance transaction data, and obtain the initial transmission interval corresponding to the transmission path;

[0029] S2. Arrange a plurality of automotive finance transaction times in sequence and generate a data transmission sequence queue;

[0030] S3. Generate a base value according to the number of digits and the highest digit of the data volume value, and obtain a plurality of base values accordingly;

[0031] S4. Calculate the transmission resource ratio of each automotive finance transaction data according to the plurality of base values, and generate an actual transmission interval corresponding to the automotive finance transaction data according to the transmission resource ratio and the initial transmission interval;

[0032] S5. Complete data transmission in sequence according to the plurality of actual transmission intervals and the data transmission sequence queue, and obtain the transmission arrival time intervals of the plurality of automotive finance transaction data;

[0033] S6. Obtain the time difference based on the actual transmission interval and the corresponding transmission arrival time interval, obtain the path correction factor based on multiple time differences, and generate a new initial transmission interval based on the path correction factor and the initial transmission interval. The new initial transmission interval is applied to the transmission process of a new round of multiple automotive financial transaction data on the transmission path.

[0034] In this embodiment, it should be noted that in S1, first, collect multiple automotive financial transaction data to be transmitted. These data may include different types of transaction records, such as loan applications, insurance purchases, vehicle sales, etc. Each piece of data is accompanied by a specific transaction time. For each transaction data, record the generated transaction time and the data volume value. The transaction time is used to determine the order of data transmission, and the data volume value is used for subsequent calculation of the transmission resource requirements. Multiple transaction data will use the same transmission path, and it is necessary to identify and record the information of this transmission path. Finally, obtain the initial transmission interval corresponding to the selected transmission path. This initial transmission interval is obtained based on the historical transmission information of the transmission path. For example, the situation of the previous batch of data transmission (i.e., the new initial transmission interval output by S6 in the previous batch of transmission processes). If there is no historical transmission information for the transmission path, it can be artificially set based on factors such as the hardware performance of the path, bandwidth limitations, and maximum bearable data traffic. Among them, both automotive financial transaction data and transmission paths can achieve intelligent data acquisition and processing based on artificial intelligence, efficiently obtaining automotive financial transaction data and transmission path information from multiple sources. For example, using web crawler technology or API interfaces to collect data in real-time or periodically.

[0035] In S2, sort the transaction data according to the sequence of these transaction times and generate a data transmission sequence queue. Specifically, first, sort the transaction data according to the transaction time of each transaction data. The sorting rule is in the order of the transaction time from early to late. In this way, the earliest generated transaction data will be placed at the front of the queue, and the latest generated transaction data will be placed at the back of the queue. After sorting, put these transaction data into a data transmission sequence queue in the sorted order. This queue will be used as the basis for data transmission in the subsequent steps to ensure that the data is transmitted in the correct order. This ensures that the data can be transmitted in the correct order and time interval, thus avoiding data chaos and transmission errors.

[0036] In S3, according to the data volume value of each transaction data, the corresponding base bit value is generated; these base bit values will be used for subsequent calculations of the transmission resource ratio and the actual transmission interval. Specifically, first determine the number of digits of the data volume value of each transaction data. Generally, the data volume value is a binary or decimal number, which is achieved by calculating its number of digits. For example, for a transaction data with a data volume value of 546439 Bit, its number of digits is 6; then, extract the highest bit of each data volume value. The highest bit usually represents the size range of the data volume value and is of great significance for subsequent calculations of the transmission resource ratio. For example, the highest bit of the transaction data of 546439 Bit is 5, and in a binary number, the highest bit is 1 (assuming the data volume value is converted into a binary number long enough); finally, according to the number of digits and the highest bit of the data volume value, a base bit value corresponding to the data volume value is generated. This base bit value can be a number formed by string concatenation. For example, the base bit value of the transaction data of 546439 Bit is 65. In this way, the object of calculation is greatly simplified, and subsequent calculations and comparisons become more intuitive and efficient. By repeating the above steps for all transaction data, the base bit value corresponding to each transaction data is obtained, and these base bit values will form a list or array for subsequent calculations and processing.

[0037] In summary, the base bit value is usually closely related to the size of the data volume value. By extracting the highest bit and considering the number of digits, the base bit value can represent and reflect the size range of the data volume value, which helps to better allocate transmission resources in subsequent processing and ensure that transaction data with large data volume values obtain sufficient transmission bandwidth and time; further, by generating the base bit value, it is possible to avoid directly using complex data volume values in subsequent calculations, thereby improving the calculation efficiency and also helping to reduce the calculation burden.

[0038] In S4, first calculate the sum of the base bit values of all transaction data to obtain a total value. Then, for each transaction data, divide its base bit value by the total value to obtain the transmission resource ratio of this transaction data. This ratio reflects the required proportion of this transaction data in the overall transmission resources. Further, according to the transmission resource ratio and the initial transmission interval of each transaction data, calculate the actual transmission interval corresponding to this transaction data. This is usually achieved by multiplying the initial transmission interval by the number of data transmissions minus 1 and then multiplying by the transmission resource ratio, but the specific calculation method may vary according to the actual requirements.

[0039] In summary, the total value is obtained by calculating the sum of the base values of each transaction data, and the proportion of transmission resources occupied by each transaction data is further calculated to achieve the optimal allocation of transmission resources, which ensures that the transmission resources are allocated according to the actual requirements of the transaction data. Further, according to the proportion of transmission resources occupied by each transaction data and the initial transmission interval, the actual transmission interval corresponding to the transaction data is dynamically adjusted, which helps to minimize transmission delay and congestion as much as possible while maintaining the overall transmission efficiency, ensuring that the transaction data can be transmitted to the target node in a timely and accurate manner.

[0040] In S5, each automotive finance transaction data in the data transmission sequence queue corresponds to an actual transmission interval calculated previously. First, each transaction data is processed in sequence according to the data transmission sequence queue. Among them, for each automotive finance transaction data in the queue, the start and end times of data transmission are arranged according to its actual transmission interval. After each automotive finance transaction data is transmitted, its transmission arrival time needs to be recorded. By comparing the transmission arrival times of adjacent automotive finance transaction data, the transmission arrival time intervals between them can be calculated. These transmission arrival time intervals are of great significance for analyzing data transmission performance, optimizing resource allocation, etc.

[0041] In S6, first, the time difference is calculated based on the difference between the actual transmission interval and the corresponding transmission arrival time interval. This difference reflects the deviation between the actual transmission process and the expected transmission plan, which may be caused by various factors such as network latency and processing speed changes. Subsequently, based on these time differences, a path correction factor is derived through a certain algorithm or model. This path correction factor is a quantitative representation of the potential latency or acceleration effect on the transmission path, which helps to more accurately understand and predict the time changes in future transmission processes. Finally, the initial transmission interval is adjusted using the path correction factor to generate a new initial transmission interval. This new interval will be applied to the transmission process of multiple automotive finance transaction data in a new round on the transmission path, in order to achieve more efficient and accurate transmission control. In summary, by calculating the time difference and obtaining the path correction factor accordingly, the transmission strategy can be dynamically adjusted to cope with various uncertain factors that may occur on the transmission path. This not only helps to reduce transmission delays caused by network fluctuations, processing speed changes, etc., but also ensures that the transmission process is more stable and reliable. At the same time, by continuously iterating and optimizing the initial transmission interval, the optimal transmission scheme can be gradually approached, thereby further improving the transmission efficiency and accuracy.

[0042] In summary, in the entire method for transmitting automotive financial transaction data based on artificial intelligence, by accurately obtaining the transaction time, data volume value, and initial transmission interval of each automotive financial transaction data, an ordered data transmission system can be established, ensuring that data is accurately transmitted in chronological order, improving the reliability and real-time performance of data transmission; further, by introducing the concept of a basic bit value and generating the basic bit value based on the number of digits and the highest bit of the data volume value, the method simplifies the processing process of complex data volume values, improves the calculation efficiency, and reduces the calculation burden; further, based on the proportion of transmission resources calculated according to the basic bit value, the optimal allocation of transmission resources is realized, ensuring that transaction data with a large data volume value can obtain sufficient transmission bandwidth and time, effectively avoiding network congestion and data transmission delay; further, by dynamically adjusting the actual transmission interval, considering the change in the carrying capacity of the transmission path at different times, hardware performance changes, or under load conditions, the data transmission becomes more flexible and adapts to the requirements of the actual transmission environment. Among them, by calculating the time difference and path correction factor, the method can adjust the initial transmission interval in real time, continuously iterate and optimize the transmission strategy, and further improve the transmission efficiency and accuracy.

[0043] As Figure 2 shown, in one embodiment, generating the basic bit value according to the number of digits and the highest bit of the data volume value in S3 includes:

[0044] S31. Generate the first string n1 according to the number of digits of the data volume value;

[0045] S32. Generate the second string n2 according to the highest bit of the data volume value;

[0046] S33. Concatenate the first string and the second string and generate the basic bit value B, where B = n1 ‖ n2.

[0047] In this embodiment, it should be noted that in S31, the first string n1 is generated according to the number of digits of the data volume value. Among them, first determine the number of digits of the data volume value of each automotive financial transaction data. Once the number of digits is determined, then use this number of digits as a string, that is, the first string n1. For example, if the data volume value is 546439 Bit and its number of digits is 6, then the first string n1 is "6".

[0048] In S32, the second string n2 is generated according to the highest bit of the data volume value. Among them, it is necessary to extract the highest bit of the data volume value. In decimal numbers, this usually means finding the largest digit in the value; in binary numbers, the highest bit is usually the most significant bit 1. Then convert the extracted highest bit into a string, that is, the second string n2. For example, for 546439, the highest bit is 5, then the second string n2 is "5".

[0049] In S33, concatenate n1 and n2 to generate a basic bit value B. Specifically, concatenate the first string n1 and n2 to form a new string. The concatenation method can be simple string concatenation, such as B = n1‖n t ; The concatenated string B serves as the basic bit value of the trading volume data for subsequent calculations and processing.

[0050] In summary, by converting the number of digits and the highest bit of the data volume value into strings and concatenating them into a basic bit value, it is possible to avoid directly using complex data volume values in subsequent calculations. This simplifies the calculation object, makes subsequent calculations and comparisons more intuitive and efficient, reduces the calculation burden, and improves the data processing efficiency. Further, the basic bit value is usually closely related to the size of the data volume value, which helps to better allocate transmission resources in subsequent processing. Further, this method is applicable to data volume values of different sizes and types, has strong versatility and adaptability. Regardless of whether the data volume value is large or small, a corresponding basic bit value can be generated through this method for subsequent calculations and processing.

[0051] For example Figure 3 As shown, in one embodiment, obtaining the path correction factor according to multiple time differences in S6 includes:

[0052] S61. Obtain a stability index according to multiple time differences;

[0053] S62. Obtain multiple time differences less than the stability index and use them as multiple to-be-processed differences;

[0054] S63. Take the average of the multiple to-be-processed differences and generate a path correction factor according to the average value.

[0055] In this embodiment, it should be noted that in S61, a stability index is obtained according to multiple time differences. Specifically, it is first necessary to determine and calculate multiple time differences, which represent the time differences between different automotive finance transaction data in the actual transmission interval and the real transmission time. Different real transmission processes are affected by different network delays or response times, etc., so the actual transmission interval and the real transmission time generally do not match exactly. Further, use these time differences to calculate the stability index, and the stability index can be a measurement threshold calculated according to the time differences.

[0056] In S62, multiple time differences less than the stability index are obtained and used as multiple differences to be processed. Specifically, in this step, according to the previously calculated stability index, all time differences less than this index are screened out. These time differences are considered to be relatively stable or have less fluctuations, so they are more likely to represent normal path conditions. The screened time differences will be used as multiple differences to be processed for subsequent calculations and processing.

[0057] In S63, the average value of the multiple differences to be processed is taken and a path correction factor is generated based on this average value. Specifically, in this step, the average value of all differences to be processed is taken. This average value represents the central tendency of these relatively stable time differences, so it can be used as a reference point or benchmark value to generate the path correction factor. Finally, the path correction factor is generated based on this average value. The path correction factor is a parameter used to update the initial transmission interval of the iteration.

[0058] In summary, through S61, S62, and S63, it is possible to accurately identify which transmission conditions are relatively stable, which helps to exclude abnormal transmission situations caused by unstable factors such as network latency and response time. By screening out time differences less than the stability index as differences to be processed, a more representative set of time difference data can be obtained. These data are more likely to reflect normal path conditions, thus providing an accurate basis for subsequent calculations and processing. Further, the path correction factor can be used to update the initial transmission interval of the iteration, so as to optimize the data transmission path, improve the transmission efficiency, or reduce the transmission delay caused by unstable factors in the next batch of data transmission.

[0059] In one embodiment, the stability index obtained according to multiple time differences in S61 is expressed as:

[0060] Where,

[0061] W is the stability index, Δt max is the maximum value among multiple time differences, and α is a preset reduction coefficient.

[0062] In this embodiment, it should be noted that Δt max represents the maximum value among multiple time differences, which reflects the maximum deviation of the fluctuation range of the time differences. By using it as the numerator, it can ensure that the stability index W can sensitively capture large fluctuations in the time differences. Further, α is a preset reduction coefficient, and its function is to perform a reduction on Δt maxScale it to obtain a more appropriate stability index W. By adjusting the value of α, the sensitivity and threshold range of the stability index can be flexibly controlled. The value of α comprehensively considers multiple conditions such as transmission characteristics, network latency, response time, etc. Generally speaking, when determining the value of α, it is also necessary to consider that sufficient time differences can be screened out in S62 to meet specific application requirements.

[0063] In summary, by introducing Δt max and α, the stability can be evaluated more accurately. When the fluctuations of the time differences are large, the value of W will also increase accordingly, thus triggering subsequent stability processing measures; furthermore, the introduction of α enables adjustment according to different application scenarios and requirements. By modifying the value of α, the threshold range of the stability index can be flexibly changed to adapt to different transmission conditions and stability requirements. In practical applications, the value of α can be gradually adjusted according to the actual transmission situation and stability requirements to achieve the best stability and performance.

[0064] In one embodiment, in S63, the average value of multiple differences to be processed is taken and the path correction factor is generated, which is expressed as:

[0065] Wherein,

[0066] M is the path correction factor, Δt i is the i-th difference to be processed, m is the number of differences to be processed, and β is the transmission environment delay coefficient.

[0067] In this embodiment, it should be noted that means summing all m differences to be processed. Such a setting ensures that when calculating the path correction factor, all relevant difference data are considered, avoiding omission or bias; then by dividing the summation result by m (the number of differences to be processed), the average value of these differences can be obtained. The average value can reflect the central tendency of the overall data, helping to eliminate the influence of individual extreme values and making the path correction factor more stable and reliable; furthermore, β in the formula represents the transmission environment delay coefficient, which considers the influence of the transmission environment on the path correction factor. β is mainly a coefficient artificially set due to network latency; adding β to the average difference can comprehensively consider the contributions of the transmission environment and difference data to path correction, making the result more accurate and comprehensive. Finally, in S6, the initial transmission interval is added to the path correction factor and the sum of the two is obtained, which is the new initial transmission interval.

[0068] In summary, by considering all the differences to be processed and calculating their average value, the impact of fluctuations in individual data points on the final result can be reduced, thereby improving the accuracy of path correction. Further, the use of the average value helps to eliminate noise and outliers in the data, and contributes to better robustness against small fluctuations and unstable factors in data transmission. Further, by introducing the transmission environment delay coefficient β, the path correction factor can be made more in line with the actual transmission environment characteristics, which helps to achieve more accurate path correction under different transmission conditions.

[0069] In one embodiment, the calculation of the transmission resource occupancy ratio of each automotive finance transaction data based on multiple base values in S4 is expressed as:

[0070] Wherein,

[0071] R j is the transmission resource occupancy ratio of the j-th automotive finance transaction data, B j is the base value of the j-th automotive finance transaction data, B k is the base value of the k-th automotive finance transaction data, and n is the number of automotive finance transaction data.

[0072] In this embodiment, it should be noted that R j represents the transmission resource occupancy ratio of the j-th automotive finance transaction data, which is a value between 0 and 1, reflecting the demand ratio of this transaction data in the overall transmission resources; B j represents the base value of the j-th automotive finance transaction data, which is generated based on the number of digits and the highest digit of the data volume value, and is used to simplify subsequent calculations and comparisons; represents the sum of the base values of all automotive finance transaction data, that is, the total value, which is used to calculate the transmission resource occupancy ratio of each transaction data.

[0073] In summary, by calculating the transmission resource occupancy ratio through the base value, it can be ensured that each transaction data obtains corresponding transmission resources according to the size of its data volume value, which avoids the problem of uneven resource allocation caused by excessive differences in data volume values. Further, the introduction of the base value simplifies the processing process of complex data volume values. Compared with directly using the data volume value for calculation, the base value is more concise and easier to process, improving the calculation efficiency. Further, the calculation of the transmission resource occupancy ratio provides a basis for the subsequent calculation of the actual transmission interval. By dynamically adjusting the actual transmission interval, it can better adapt to changes in the carrying capacity of the transmission path and ensure the smooth progress of data transmission.

[0074] In one embodiment, the generation of the actual transmission interval corresponding to the automotive finance transaction data based on the transmission resource occupancy ratio and the initial transmission interval in S4 is expressed as:

[0075] T j = R j ·t c ; wherein,

[0076] T j is the actual transmission interval between the j-th and the (j + 1)-th auto finance transaction data, and t c is the initial transmission interval.

[0077] In this embodiment, it should be noted that the actual transmission interval T j is calculated by multiplying the transmission resource ratio R c by the initial transmission interval t j , which can ensure that each transaction data obtains corresponding transmission time according to its transmission resource requirements. This proportional allocation method can fairly utilize the transmission resources and avoid a certain transaction data occupying too much transmission time and causing delays to other data. Further, the calculation of the actual transmission interval takes into account the specific transmission resource requirements of each transaction data, which makes the transmission strategy more flexible and dynamic. When the initial transmission interval of the transmission path or the auto finance transaction data changes, the initial transmission interval t c can be adjusted or the transmission resource ratio R j can be recalculated to adapt to the new transmission environment.

[0078] It also provides an auto finance transaction data transmission system based on artificial intelligence. The system is used to implement the method for transmitting auto finance transaction data based on artificial intelligence in any of the above embodiments. The system includes:

[0079] A data and path acquisition module, configured to acquire multiple auto finance transaction data and transmission paths, obtain the corresponding auto finance transaction time and data volume value according to the auto finance transaction data, and obtain the initial transmission interval corresponding to the transmission path;

[0080] A queue generation module, configured to arrange multiple auto finance transaction times in sequence and generate a data transmission sequence queue;

[0081] A data processing module, configured to generate a base value according to the number of digits and the highest digit of the data volume value, and thereby obtain multiple base values;

[0082] A calculation module, configured to calculate the transmission resource ratio of each auto finance transaction data according to the multiple base values, and generate the actual transmission interval corresponding to the auto finance transaction data according to the transmission resource ratio and the initial transmission interval;

[0083] A transmission module, configured to sequentially complete data transmission according to the multiple actual transmission intervals and the data transmission sequence queue, and obtain the transmission arrival time intervals of multiple auto finance transaction data;

[0084] A transmission feedback and update module is configured to obtain a time difference according to an actual transmission interval and a corresponding transmission arrival time interval, obtain a path correction factor according to multiple time differences, and generate a new initial transmission interval according to the path correction factor and the initial transmission interval, wherein the new initial transmission interval is applied to the transmission process of a new round of multiple automotive finance transaction data on a transmission path.

[0085] In this embodiment, it should be noted that for the above automotive finance transaction data transmission system based on artificial intelligence, the specific manner of performing operations has been described in detail in the embodiment of the automotive finance transaction data transmission method based on artificial intelligence, and will not be elaborated here.

[0086] Figure 4 It is a block diagram of an electronic device for an automotive finance transaction data transmission method based on an exemplary embodiment. As Figure 4 shown, the electronic device 700 may include: a processor 701, a memory 702. The electronic device 700 may further include one or more of a multimedia component 703, an input / output (I / O) interface 704, and a communication component 705.

[0087] Among them, the processor 701 is used to control the overall operation of the electronic device 700 to complete all or part of the steps in the above-mentioned method for transmitting automotive financial transaction data based on artificial intelligence. The memory 702 is used to store various types of data to support the operation of the electronic device 700. Such data may include, for example, instructions for any application or method operating on the electronic device 700, as well as application-related data, such as contact data, messages sent and received, pictures, audio, video, and so on. The memory 702 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic memory, flash memory, a magnetic disk, or an optical disc. The multimedia component 703 may include a screen and an audio component. Among them, the screen can be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal can be further stored in the memory 702 or sent through the communication component 705. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 704 provides an interface between the processor 701 and other interface modules. The above-mentioned other interface modules can be a keyboard, a mouse, buttons, etc. These buttons can be virtual buttons or physical buttons. The communication component 705 is used for wired or wireless communication between the electronic device 700 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB-IOT, eMTC, or other 5G, etc., or a combination of one or several of them, is not limited herein. Therefore, correspondingly, the communication component 705 may include: a Wi-Fi module, a Bluetooth module, an NFC module, and so on.

[0088] In an exemplary embodiment, the electronic device 700 can be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components, and is used to execute the above-mentioned artificial intelligence-based automotive financial transaction data transmission method.

[0089] In another exemplary embodiment, a computer-readable storage medium including program instructions is further provided. When the program instructions are executed by a processor, the steps of the above-mentioned artificial intelligence-based automotive financial transaction data transmission method are implemented. For example, the computer-readable storage medium can be the above-mentioned memory 702 including program instructions, and the above-mentioned program instructions can be executed by the processor 701 of the electronic device 700 to complete the above-mentioned artificial intelligence-based automotive financial transaction data transmission method.

[0090] In another exemplary embodiment, a computer program product is further provided. The computer program product includes a computer program that can be executed by a programmable device, and the computer program has a code part for executing the above-mentioned artificial intelligence-based automotive financial transaction data transmission method when executed by the programmable device.

[0091] The preferred embodiments of the present disclosure have been described in detail above in conjunction with the accompanying drawings. However, the present disclosure is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present disclosure, various simple modifications can be made to the technical solutions of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.

[0092] In addition, it should be noted that, in the above specific embodiments, the various specific technical features described can be combined in any suitable manner without conflict. To avoid unnecessary repetition, the present disclosure does not separately describe various possible combination methods.

[0093] In addition, any combination can be made between various different embodiments of the present disclosure as long as it does not violate the idea of the present disclosure, and it should also be regarded as the content disclosed by the present disclosure.

[0094] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the various embodiments of the present invention, and they should all be covered by the scope of the claims and the specification of the present invention.

Claims

1. A method for transmitting automotive financial transaction data based on artificial intelligence, characterized in that, including: Obtain multiple automotive finance transaction data and transmission paths, obtain the corresponding automotive finance transaction time and data volume value according to the automotive finance transaction data, and obtain the initial transmission interval corresponding to the transmission path; Arrange multiple automotive finance transaction times in sequence and generate a data transmission sequence queue; Generate a basic bit value according to the number of digits and the highest bit of the data volume value, and thus obtain multiple basic bit values; Among them, generating a basic bit value according to the number of digits and the highest bit of the data volume value includes: generating a first string according to the number of digits of the data volume value ; generating a second string according to the highest bit of the data volume value ; concatenating the first string and the second string and generating a basic bit value , where ; Calculate the transmission resource occupancy ratio of each automotive finance transaction data according to multiple basic bit values, and generate an actual transmission interval corresponding to the automotive finance transaction data according to the transmission resource occupancy ratio and the initial transmission interval; Among them, the calculation of the transmission resource ratio of each auto finance transaction data based on multiple basic bit values is expressed as: ; among them, is the transmission resource ratio of the j-th auto finance transaction data, is the basic bit value of the j-th auto finance transaction data, is the basic bit value of the k-th auto finance transaction data, and n is the number of auto finance transaction data; Generate the actual transmission interval corresponding to the auto finance transaction data based on the proportion of transmission resources and the initial transmission interval, which is expressed as: ; where is the actual transmission interval between the j-th and the (j + 1)-th auto finance transaction data, is the initial transmission interval Complete data transmission in sequence according to multiple actual transmission intervals and the data transmission sequence queue, and obtain the transmission arrival time intervals of multiple automotive finance transaction data; Obtain a time difference according to the actual transmission interval and the corresponding transmission arrival time interval, obtain a path correction factor according to multiple time differences, and generate a new initial transmission interval according to the path correction factor and the initial transmission interval, wherein the new initial transmission interval is applied to the transmission process of a new round of multiple automotive finance transaction data on the transmission path.

2. The method for transmitting automotive financial transaction data based on artificial intelligence according to claim 1, wherein The obtaining the path correction factor according to multiple time differences includes: Obtain a stability index according to multiple time differences; Obtain multiple time differences less than the stability index and use them as multiple to-be-processed differences; Take the average of multiple to-be-processed differences and generate a path correction factor according to the average value.

3. The method for transmitting automotive financial transaction data based on artificial intelligence according to claim 2, wherein The obtaining the stability index according to multiple time differences is expressed as: ; wherein, is a stability index, is the maximum value among multiple time differences, is a preset reduction coefficient.

4. The method for transmitting automotive financial transaction data based on artificial intelligence according to claim 3, wherein The taking the average of multiple to-be-processed differences and generating a path correction factor is expressed as: ; wherein, is the path correction factor, is the i-th difference to be processed, is the number of differences to be processed, is the transmission environment delay coefficient.

5. An artificial intelligence-based automotive finance transaction data transmission system, characterized in that, The system is used to implement the artificial intelligence-based automotive finance transaction data transmission method described in any one of claims 1 to 4. The system includes: A data and path acquisition module, configured to obtain multiple automotive finance transaction data and transmission paths, obtain the corresponding automotive finance transaction time and data volume value according to the automotive finance transaction data, and obtain the initial transmission interval corresponding to the transmission path; A queue generation module, configured to arrange multiple automotive finance transaction times in sequence and generate a data transmission sequence queue; A data processing module, configured to generate a basic bit value according to the number of digits and the highest bit of the data volume value, and thus obtain multiple basic bit values; A calculation module, configured to calculate the transmission resource occupancy ratio of each automotive finance transaction data according to multiple basic bit values, and generate an actual transmission interval corresponding to the automotive finance transaction data according to the transmission resource occupancy ratio and the initial transmission interval; A transmission module, configured to complete data transmission in sequence according to multiple actual transmission intervals and the data transmission sequence queue, and obtain the transmission arrival time intervals of multiple automotive finance transaction data; A transmission feedback and update module, configured to obtain a time difference according to the actual transmission interval and the corresponding transmission arrival time interval, obtain a path correction factor according to multiple time differences, and generate a new initial transmission interval according to the path correction factor and the initial transmission interval, wherein the new initial transmission interval is applied to the transmission process of a new round of multiple automotive finance transaction data on the transmission path.

6. An electronic device, characterized in that, including: A memory, on which a computer program is stored; A processor for executing the computer program in the memory to implement the method for transmitting automotive financial transaction data based on artificial intelligence according to any one of claims 1 to 4.

7. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method for transmitting automotive financial transaction data based on artificial intelligence according to any one of claims 1 to 4.

Images