Water drainage and noise reduction asphalt pavement construction planning method and system based on multi-source data

Abstract

The invention discloses a drainage and noise reduction asphalt pavement construction planning method and system based on multi-source data, and relates to the technical field of pavement construction management, and the method comprises the steps: obtaining a parameter training database; obtaining the construction requirement of the current drainage and noise reduction asphalt pavement, and screening out initial parameter training data; calculating to obtain construction process parameters of the drainage and noise reduction asphalt pavement; the drainage and noise reduction asphalt pavement is constructed; acquiring real-time construction process parameter data under current drainage and noise reduction asphalt pavement construction, and updating parameter training data of the drainage and noise reduction asphalt pavement; and calculating according to the updated parameter training data to obtain the updated construction process parameters of the drainage and noise reduction asphalt pavement. The method has the advantages that dynamic planning updating is adopted for asphalt pavement construction, it is effectively guaranteed that pavement construction conforms to the real-time environment of a road section area, stability of asphalt pavement construction is guaranteed, and the performance of the drainage and noise reduction asphalt pavement is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of pavement construction management, and in particular to a drainage and noise reduction asphalt pavement construction planning method and system based on multi-source data. Background Art

[0002] Asphalt pavement refers to various types of pavement paved with road asphalt materials mixed into mineral materials. Asphalt binder improves the ability of paving aggregate to resist damage to the road surface caused by traffic and natural factors, making the road surface smooth, dust-free, impermeable and durable. Therefore, asphalt pavement is the most widely used high-grade pavement in road construction. The asphalt structural layer of asphalt pavement itself belongs to the category of flexible pavement, but its base layer can also use rigid cement concrete or semi-rigid hydraulic materials in addition to flexible materials.

[0003] During the construction of asphalt pavement, the construction process parameters of asphalt pavement are the decisive factors that determine the performance and construction cost of asphalt pavement. In the prior art, the construction process parameters of asphalt pavement are usually determined manually based on experience. Once the parameters are determined, they will not be updated and learned according to the actual construction status. In the actual pavement construction process, due to the different actual environmental parameters of each section, the construction process parameters required for each section are also different. The fixed process parameters of the prior art easily lead to the difficulty in ensuring the best pavement performance of drainage and noise reduction asphalt pavement. Summary of the invention

[0004] In order to solve the above technical problems, a drainage and noise reduction asphalt pavement construction planning method and system based on multi-source data are provided. This technical solution solves the problem that the fixed process parameters of the above-mentioned prior art method easily lead to the difficulty in ensuring the optimal pavement performance of the drainage and noise reduction asphalt pavement.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] A drainage and noise reduction asphalt pavement construction planning method based on multi-source data, comprising:

[0007] Acquire a parameter training database, wherein the parameter training database includes pavement performance parameters and cost parameters under different pavement construction processes;

[0008] Obtain the current construction requirements of drainage and noise reduction asphalt pavement, and select initial parameter training data from the parameter training database according to the current construction requirements of drainage and noise reduction asphalt pavement;

[0009] Calculate and obtain drainage and noise reduction asphalt pavement construction process parameters based on parameter training data;

[0010] The drainage and noise reduction asphalt pavement is constructed according to the construction process parameters of the drainage and noise reduction asphalt pavement;

[0011] Obtain the real-time construction process parameter data of the current drainage and noise reduction asphalt pavement construction, and update the parameter training data of the drainage and noise reduction asphalt pavement;

[0012] Calculate and obtain updated drainage and noise reduction asphalt pavement construction process parameters based on updated parameter training data;

[0013] When constructing drainage and noise reduction asphalt pavement on new road sections, updated drainage and noise reduction asphalt pavement construction process parameters are used.

[0014] Preferably, the obtaining of the current construction requirements of the drainage and noise reduction asphalt pavement and screening out parameter training data from the parameter training database according to the current construction requirements of the drainage and noise reduction asphalt pavement specifically include:

[0015] Based on the current construction requirements of drainage and noise reduction asphalt pavement, determine the performance requirements and cost requirements of drainage and noise reduction asphalt pavement, the performance requirements include drainage performance, noise reduction performance and pavement strength performance, and the cost requirements include construction cost and construction efficiency;

[0016] Set a training sample number, denoted as N;

[0017] Filter out several parameter data that meet the current construction requirements of drainage and noise reduction asphalt pavement from the parameter training database as the initial screening parameter data;

[0018] Based on the feedback training model, N parameter data are screened out from the initial screening parameter data as initial parameter training data.

[0019] Preferably, the feedback training model is used to screen out N pieces of parameter data from the initial screening parameter data, and the initial parameter training data specifically include:

[0020] Based on the parameter feedback calculation formula, calculate the feedback value of each initial screening parameter data;

[0021] Filter out N pieces of initial screening parameter data with the largest feedback values ​​as initial parameter training data;

[0022] The parameter feedback calculation formula is specifically:

[0023]

[0024] Among them, Z fb is the feedback value of the initial screening parameter data, α i is the emphasis weight of the i-th construction data, x i0 is the demand value of the i-th construction data, x iis the parameter value of the i-th construction data in the initial screening parameter data, and n is the total number of types of construction data.

[0025] Preferably, the obtaining of real-time construction process parameter data of the current drainage and noise reduction asphalt pavement construction and updating of parameter training data of the drainage and noise reduction asphalt pavement specifically includes:

[0026] The pavement performance and construction cost parameters corresponding to the real-time construction process parameter data under the current drainage and noise reduction asphalt pavement construction are input into the parameter feedback calculation formula to obtain the real-time feedback value under the real-time construction process parameter data;

[0027] Compare the real-time feedback value with the feedback value in the parameter training data to determine whether there is data with a feedback value smaller than the real-time feedback value in the current parameter training data;

[0028] If so, determine whether the number of data in the current parameter training data is less than N. If so, directly add the real-time construction process parameter data corresponding to the real-time feedback value to the parameter training data. If not, delete the data with the smallest feedback value in the parameter training data, and add the real-time construction process parameter data corresponding to the real-time feedback value to the parameter training data.

[0029] If not, the data with the smallest feedback value in the parameter training data is deleted, and the remaining data is retained as the parameter training data.

[0030] Preferably, the method of calculating and obtaining the drainage and noise reduction asphalt pavement construction process parameters according to the parameter training data specifically includes:

[0031] Obtain the feedback values ​​of all data in the parameter training data, and calculate the training weight of each data based on the feedback values ​​of all data;

[0032] Based on the training weight of each piece of data and the construction process parameters corresponding to each piece of data, the construction process parameters of the drainage and noise reduction asphalt pavement are calculated based on the process parameter calculation formula;

[0033] The process parameter calculation formula is specifically:

[0034]

[0035] Where Y is the calculated drainage and noise reduction asphalt pavement construction process parameter, β j is the training weight of the jth data in the parameter training data, y j is the drainage and noise reduction asphalt pavement construction process parameter corresponding to the j-th data in the parameter training data, and M is the total number of data in the parameter training data.

[0036] Preferably, the calculation of the training weight of each piece of data based on the feedback value of all data specifically includes:

[0037] Get the feedback values ​​of all data and summarize them into a feedback value set E, E = {e1…e j …e M}, where is the feedback value of the jth data in the parameter training data;

[0038] The specific training weights are:

[0039]

[0040] Furthermore, a drainage and noise reduction asphalt pavement construction planning system based on multi-source data is proposed, which is used to implement the drainage and noise reduction asphalt pavement construction planning method based on multi-source data as mentioned above, including:

[0041] A storage module, wherein the storage module is used to store a parameter training database;

[0042] A sample data acquisition and update module, the sample data acquisition and update module is electrically connected to the storage module, and the sample data acquisition and update module is used to obtain the current construction requirements of the drainage and noise reduction asphalt pavement, filter out initial parameter training data from the parameter training database according to the current construction requirements of the drainage and noise reduction asphalt pavement, obtain real-time construction process parameter data under the current drainage and noise reduction asphalt pavement construction, and update the parameter training data of the drainage and noise reduction asphalt pavement;

[0043] A construction process planning module, wherein the construction process planning module is electrically connected to the sample data acquisition and update module, and the construction process planning module is used to calculate and obtain drainage and noise reduction asphalt pavement construction process parameters according to parameter training data.

[0044] Optionally, the sample data acquisition and update module includes:

[0045] A primary screening unit, which is used to screen out a number of parameter data that meet the current construction requirements of drainage and noise reduction asphalt pavement from the parameter training database as primary screening parameter data;

[0046] A feedback analysis unit, wherein the feedback analysis unit is used to calculate a feedback value;

[0047] An initial parameter determination unit, the initial parameter determination unit is used to screen out N pieces of initial screening parameter data with the largest feedback values ​​as initial parameter training data;

[0048] The updating unit is used to obtain the real-time construction process parameter data of the current drainage and noise reduction asphalt pavement construction, and to update the parameter training data of the drainage and noise reduction asphalt pavement.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] The present invention proposes a drainage and noise reduction asphalt pavement construction planning scheme based on multi-source data. The feedback value is calculated through a feedback training model according to the pavement performance and cost obtained from the real-time asphalt pavement construction, and compared with the data in the parameter training data. The parameter training data is updated according to the comparison result, and then the pavement construction parameters corresponding to the pavement performance and cost under a more optimized state are updated and calculated according to the updated parameter training data, and a more optimized pavement construction planning strategy is output. By gradually updating the calculation during the pavement construction process, the optimal pavement construction parameters that are most suitable for the current road section environment can be obtained according to the actual pavement construction state. The pavement construction is carried out using this pavement construction parameter, which can effectively ensure that the pavement construction conforms to the real-time environment of the road section area, ensure the stability of the asphalt pavement construction, and improve the performance of the drainage and noise reduction asphalt pavement. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 This is a flow chart of the drainage and noise reduction asphalt pavement construction planning method based on multi-source data proposed by the present invention;

[0052] Figure 2 A flow chart of a method for screening parameter training data in the present invention;

[0053] Figure 3 A flow chart of a method for selecting N pieces of parameter data from preliminary screening parameter data based on a feedback training model as initial parameter training data in the present invention;

[0054] Figure 4 A flow chart of a method for updating parameter training data of a drainage and noise reduction asphalt pavement in the present invention;

[0055] Figure 5 A flow chart of a method for calculating and obtaining construction process parameters of drainage and noise reduction asphalt pavement by using parameter training data in the present invention;

[0056] Figure 6 This is a schematic diagram of the structure of the drainage and noise reduction asphalt pavement construction planning system based on multi-source data proposed by the present invention;

[0057] Figure 7 It is a schematic diagram of the structure of the electronic device in the present invention;

[0058] Figure 8 It is a schematic diagram of the structure of the computer-readable storage medium in the present invention. DETAILED DESCRIPTION

[0059] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0060] Reference Figure 1 As shown, a drainage and noise reduction asphalt pavement construction planning method based on multi-source data includes:

[0061] Acquire a parameter training database, the parameter training database including pavement performance parameters and cost parameters under different pavement construction processes;

[0062] Obtain the current construction requirements of drainage and noise reduction asphalt pavement, and select initial parameter training data from the parameter training database according to the current construction requirements of drainage and noise reduction asphalt pavement;

[0063] Calculate and obtain drainage and noise reduction asphalt pavement construction process parameters based on parameter training data;

[0064] The drainage and noise reduction asphalt pavement is constructed according to the construction process parameters of the drainage and noise reduction asphalt pavement;

[0065] Obtain the real-time construction process parameter data of the current drainage and noise reduction asphalt pavement construction, and update the parameter training data of the drainage and noise reduction asphalt pavement;

[0066] Calculate and obtain updated drainage and noise reduction asphalt pavement construction process parameters based on updated parameter training data;

[0067] When constructing drainage and noise reduction asphalt pavement on new road sections, updated drainage and noise reduction asphalt pavement construction process parameters are used.

[0068] This solution calculates the feedback value through the feedback training model based on the pavement performance and cost obtained from real-time asphalt pavement construction, and compares it with the data in the parameter training data. The parameter training data is updated according to the comparison results, and then the pavement construction parameters corresponding to the pavement performance and cost under a more optimized state are updated and calculated based on the updated parameter training data, and a more optimized pavement construction planning strategy is output. By gradually updating the calculation during the pavement construction process, the optimal pavement construction parameters that are most suitable for the current road section environment can be obtained according to the actual pavement construction status.

[0069] Reference Figure 2 As shown, the current construction requirements of drainage and noise reduction asphalt pavement are obtained, and parameter training data are screened from the parameter training database according to the current construction requirements of drainage and noise reduction asphalt pavement, specifically including:

[0070] Based on the current construction requirements of drainage and noise reduction asphalt pavement, determine the performance requirements and cost requirements of drainage and noise reduction asphalt pavement. The performance requirements include drainage performance, noise reduction performance and pavement strength performance, and the cost requirements include construction cost and construction efficiency.

[0071] Set a training sample number, denoted as N;

[0072] Filter out several parameter data that meet the current construction requirements of drainage and noise reduction asphalt pavement from the parameter training database as the initial screening parameter data;

[0073] Based on the feedback training model, N parameter data are screened out from the initial screening parameter data as initial parameter training data.

[0074] Reference Figure 3 As shown, based on the feedback training model, N parameter data are screened out from the initial screening parameter data, and the initial parameter training data specifically includes:

[0075] Based on the parameter feedback calculation formula, calculate the feedback value of each initial screening parameter data;

[0076] Filter out N pieces of initial screening parameter data with the largest feedback values ​​as initial parameter training data;

[0077] Among them, the parameter feedback calculation formula is specifically:

[0078]

[0079] Among them, Z fb is the feedback value of the initial screening parameter data, α i is the emphasis weight of the i-th construction data, x i0 is the demand value of the i-th construction data, x i is the parameter value of the i-th construction data in the initial screening parameter data, and n is the total number of types of construction data.

[0080] It is understandable that in the actual application process of road construction, different road construction requirements have different emphasis. Therefore, in this solution, emphasis weights are introduced for the calculation of feedback values, and corresponding feedback values ​​are calculated according to the different emphasis requirements in actual situations.

[0081] Specifically, for example, in the stage of reducing costs and increasing efficiency, greater weight needs to be added to construction costs and construction efficiency. In areas with dense large vehicles, greater weight needs to be added to pavement strength performance. In areas with heavy precipitation, greater weight needs to be added to drainage performance. In areas close to residential areas, greater weight needs to be added to noise reduction performance.

[0082] In the initial planning stage of drainage and noise reduction asphalt pavement construction, this scheme constructs a parameter training database for pavement construction, imports all historical processing data of asphalt pavements, selects several parameter data that meet the construction requirements of drainage and noise reduction asphalt pavements from the parameter training database as preliminary screening parameter data, and based on the preliminary screening parameter data, selects N preliminary screening parameter data that are closer to the overall construction data and the pavement construction requirements through the parameter feedback calculation formula as initial parameter training data. The initial parameter training data is used to train and calculate the construction process parameters of drainage and noise reduction asphalt pavement, which can effectively ensure that the parameter planning in the initial construction stage is compatible with the pavement construction requirements.

[0083] Reference Figure 4 As shown, obtaining the real-time construction process parameter data of the current drainage and noise reduction asphalt pavement construction and updating the parameter training data of the drainage and noise reduction asphalt pavement specifically includes:

[0084] The pavement performance and construction cost parameters corresponding to the real-time construction process parameter data under the current drainage and noise reduction asphalt pavement construction are input into the parameter feedback calculation formula to obtain the real-time feedback value under the real-time construction process parameter data;

[0085] Compare the real-time feedback value with the feedback value in the parameter training data to determine whether there is data with a feedback value smaller than the real-time feedback value in the current parameter training data;

[0086] If so, determine whether the number of data in the current parameter training data is less than N. If so, directly add the real-time construction process parameter data corresponding to the real-time feedback value to the parameter training data. If not, delete the data with the smallest feedback value in the parameter training data, and add the real-time construction process parameter data corresponding to the real-time feedback value to the parameter training data.

[0087] If not, the data with the smallest feedback value in the parameter training data is deleted, and the remaining data is retained as the parameter training data.

[0088] Reference Figure 5 As shown in the figure, the construction process parameters of drainage and noise reduction asphalt pavement are calculated based on the parameter training data, including:

[0089] Obtain the feedback values ​​of all data in the parameter training data, and calculate the training weight of each data based on the feedback values ​​of all data;

[0090] Based on the training weight of each piece of data and the construction process parameters corresponding to each piece of data, the construction process parameters of the drainage and noise reduction asphalt pavement are calculated based on the process parameter calculation formula;

[0091] The specific process parameter calculation formula is:

[0092]

[0093] Where Y is the calculated drainage and noise reduction asphalt pavement construction process parameter, β j is the training weight of the jth data in the parameter training data, y j is the drainage and noise reduction asphalt pavement construction process parameter corresponding to the j-th data in the parameter training data, and M is the total number of data in the parameter training data.

[0094] The training weight of each piece of data is calculated based on the feedback value of all data, including:

[0095] Get the feedback values ​​of all data and summarize them into a feedback value set E, E = {e1…e j …e M}, where is the feedback value of the jth data in the parameter training data;

[0096] The specific training weights are:

[0097]

[0098] It can be understood that the feedback value represents the adaptability of the data in the parameter training data to the current needs. The larger the feedback value, the higher the adaptability. Parameters with higher adaptability should be given higher emphasis when calculating the construction parameters of drainage and noise reduction asphalt pavement. Based on this, this scheme uses feedback value to calculate the training weight. The larger the feedback value, the higher the emphasis of the corresponding parameter training data when calculating the construction parameters of drainage and noise reduction asphalt pavement.

[0099] After screening and iteration, the data existing in the parameter training data is the optimized drainage and noise reduction asphalt pavement construction parameter set under the current training progress. The average value of the enhanced parameters in the parameter training data is taken as the drainage and noise reduction asphalt pavement construction parameter output, which can effectively ensure that the output drainage and noise reduction asphalt pavement construction parameters are the optimized parameters under the current training state, and effectively ensure the asphalt pavement construction quality.

[0100] Further, see Figure 6 As shown, based on the same inventive concept as the above-mentioned drainage and noise reduction asphalt pavement construction planning method based on multi-source data, this solution proposes a drainage and noise reduction asphalt pavement construction planning system based on multi-source data, including:

[0101] A storage module, which is used to store a parameter training database;

[0102] A sample data acquisition and update module, the sample data acquisition and update module is electrically connected to the storage module, and the sample data acquisition and update module is used to obtain the current construction requirements of the drainage and noise reduction asphalt pavement, filter out the initial parameter training data from the parameter training database according to the current construction requirements of the drainage and noise reduction asphalt pavement, obtain the real-time construction process parameter data under the current drainage and noise reduction asphalt pavement construction, and update the parameter training data of the drainage and noise reduction asphalt pavement;

[0103] The construction process planning module is electrically connected to the sample data acquisition and update module. The construction process planning module is used to calculate and obtain the drainage and noise reduction asphalt pavement construction process parameters according to the parameter training data.

[0104] The sample data acquisition and update module includes:

[0105] The primary screening unit is used to screen out a number of parameter data that meet the current construction requirements of drainage and noise reduction asphalt pavement from the parameter training database as primary screening parameter data;

[0106] A feedback analysis unit, the feedback analysis unit is used to calculate the feedback value;

[0107] An initial parameter determination unit, which is used to screen out N pieces of initial screening parameter data with the largest feedback values ​​as initial parameter training data;

[0108] The updating unit is used to obtain the real-time construction process parameter data of the current drainage and noise reduction asphalt pavement construction, and to update the parameter training data of the drainage and noise reduction asphalt pavement.

[0109] The process of using the above system is as follows:

[0110] Step 1: The primary screening unit retrieves the parameter training database from the storage module, and selects a number of parameter data that meet the current construction requirements of the drainage and noise reduction asphalt pavement from the parameter training database as the primary screening parameter data;

[0111] Step 2: The initial parameter determination unit is used to screen out N pieces of initial screening parameter data with the largest feedback values ​​as initial parameter training data;

[0112] Step 3: The construction process planning module calculates and obtains the initial construction process parameters of the drainage and noise reduction asphalt pavement according to the initial parameter training data;

[0113] Step 4: Perform pavement construction according to the initial construction process parameters of the drainage and noise reduction asphalt pavement. The update unit obtains the real-time construction process parameter data under the current drainage and noise reduction asphalt pavement construction, and updates the parameter training data of the drainage and noise reduction asphalt pavement. The update steps are as follows:

[0114] The pavement performance and construction cost parameters corresponding to the real-time construction process parameter data under the current drainage and noise reduction asphalt pavement construction are input into the parameter feedback calculation formula to obtain the real-time feedback value under the real-time construction process parameter data;

[0115] Compare the real-time feedback value with the feedback value in the parameter training data to determine whether there is data with a feedback value smaller than the real-time feedback value in the current parameter training data;

[0116] If so, determine whether the number of data in the current parameter training data is less than N. If so, directly add the real-time construction process parameter data corresponding to the real-time feedback value to the parameter training data. If not, delete the data with the smallest feedback value in the parameter training data, and add the real-time construction process parameter data corresponding to the real-time feedback value to the parameter training data.

[0117] If not, the data with the smallest feedback value in the parameter training data is deleted, and the remaining data is retained as the parameter training data.

[0118] Furthermore, the method according to the embodiment of the present application can also be performed by Figure 7 The electronic device architecture shown in FIG. Figure 7 As shown, the electronic device 500 may include a bus 501, one or more CPUs 502, a read-only memory (ROM) 503, a random access memory (RAM) 504, a communication port 505 connected to a network, an input / output component 506, a hard disk 507, etc. The storage device in the electronic device 500, such as the ROM 503 or the hard disk 507, may store a drainage and noise reduction asphalt pavement construction planning method based on multi-source data provided in the present application. The electronic device 500 may also include a user interface 508. Of course, Figure 7 The architecture shown is only exemplary and can be omitted according to actual needs when implementing different devices. Figure 7 One or more components of an electronic device are shown.

[0119] Figure 8 Schematic diagram of a computer-readable storage medium structure provided by an embodiment of the present application. Figure 8 As shown, a computer-readable storage medium 600 according to an embodiment of the present application is shown. Computer-readable instructions are stored on the computer-readable storage medium 600. When the computer-readable instructions are executed by the processor, a drainage and noise reduction asphalt pavement construction planning method based on multi-source data according to an embodiment of the present application described with reference to the above figures can be executed. The storage medium 600 includes, but is not limited to, for example, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and cache memory (cache), etc. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0120] In summary, the advantages of the present invention are: the use of dynamic planning and updating for asphalt pavement construction effectively ensures that the pavement construction conforms to the real-time environment of the road section area, ensures the stability of asphalt pavement construction, and improves the performance of drainage and noise reduction asphalt pavement.

[0121] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A drainage and noise reduction asphalt pavement construction planning method based on multi-source data, characterized in that: include: Acquire a parameter training database, wherein the parameter training database includes pavement performance parameters and cost parameters under different pavement construction processes; Obtain the current construction requirements of drainage and noise reduction asphalt pavement, and select initial parameter training data from the parameter training database according to the current construction requirements of drainage and noise reduction asphalt pavement; Calculate and obtain drainage and noise reduction asphalt pavement construction process parameters based on parameter training data; The drainage and noise reduction asphalt pavement is constructed according to the construction process parameters of the drainage and noise reduction asphalt pavement; Obtain the real-time construction process parameter data of the current drainage and noise reduction asphalt pavement construction, and update the parameter training data of the drainage and noise reduction asphalt pavement; Calculate and obtain updated drainage and noise reduction asphalt pavement construction process parameters based on updated parameter training data; When constructing drainage and noise reduction asphalt pavement on new road sections, updated drainage and noise reduction asphalt pavement construction process parameters are used.

2. The method for planning construction of drainage and noise reduction asphalt pavement based on multi-source data according to claim 1 is characterized in that: The obtaining of the current construction requirements of the drainage and noise reduction asphalt pavement and the screening of parameter training data from the parameter training database according to the current construction requirements of the drainage and noise reduction asphalt pavement specifically include: Based on the current construction requirements of drainage and noise reduction asphalt pavement, determine the performance requirements and cost requirements of drainage and noise reduction asphalt pavement, the performance requirements include drainage performance, noise reduction performance and pavement strength performance, and the cost requirements include construction cost and construction efficiency; Set a training sample number, denoted as N; Filter out several parameter data that meet the current construction requirements of drainage and noise reduction asphalt pavement from the parameter training database as the initial screening parameter data; Based on the feedback training model, N parameter data are screened out from the initial screening parameter data as initial parameter training data.

3. The method for planning construction of drainage and noise reduction asphalt pavement based on multi-source data according to claim 2 is characterized in that: The feedback training model is used to screen out N pieces of parameter data from the initial screening parameter data, which specifically include: Based on the parameter feedback calculation formula, calculate the feedback value of each initial screening parameter data; Filter out N pieces of initial screening parameter data with the largest feedback values ​​as initial parameter training data; The parameter feedback calculation formula is specifically: Among them, Z fb is the feedback value of the initial screening parameter data, α i is the emphasis weight of the i-th construction data, x i0 is the demand value of the i-th construction data, x i is the parameter value of the i-th construction data in the initial screening parameter data, and n is the total number of types of construction data.

4. The method for planning construction of drainage and noise reduction asphalt pavement based on multi-source data according to claim 3 is characterized in that: The obtaining of real-time construction process parameter data of the current drainage and noise reduction asphalt pavement construction and updating of parameter training data of the drainage and noise reduction asphalt pavement specifically includes: The pavement performance and construction cost parameters corresponding to the real-time construction process parameter data under the current drainage and noise reduction asphalt pavement construction are input into the parameter feedback calculation formula to obtain the real-time feedback value under the real-time construction process parameter data; Compare the real-time feedback value with the feedback value in the parameter training data to determine whether there is data with a feedback value smaller than the real-time feedback value in the current parameter training data; If so, determine whether the number of data in the current parameter training data is less than N. If so, directly add the real-time construction process parameter data corresponding to the real-time feedback value to the parameter training data. If not, delete the data with the smallest feedback value in the parameter training data, and add the real-time construction process parameter data corresponding to the real-time feedback value to the parameter training data. If not, the data with the smallest feedback value in the parameter training data is deleted, and the remaining data is retained as the parameter training data.

5. The method for planning construction of drainage and noise reduction asphalt pavement based on multi-source data according to claim 4 is characterized in that: The method of calculating and obtaining the drainage and noise reduction asphalt pavement construction process parameters according to the parameter training data specifically includes: Obtain the feedback values ​​of all data in the parameter training data, and calculate the training weight of each data based on the feedback values ​​of all data; Based on the training weight of each piece of data and the construction process parameters corresponding to each piece of data, the construction process parameters of the drainage and noise reduction asphalt pavement are calculated based on the process parameter calculation formula; The process parameter calculation formula is specifically: Where Y is the calculated drainage and noise reduction asphalt pavement construction process parameter, β j is the training weight of the jth data in the parameter training data, y j is the drainage and noise reduction asphalt pavement construction process parameter corresponding to the j-th data in the parameter training data, and M is the total number of data in the parameter training data.

6. The method for planning construction of drainage and noise reduction asphalt pavement based on multi-source data according to claim 5 is characterized in that: The calculation of the training weight of each piece of data based on the feedback value of all data specifically includes: Get the feedback values ​​of all data and summarize them into a feedback value set E, E = {e1…e j …e M }, where is the feedback value of the j-th data in the parameter training data; The specific training weights are:

7. A drainage and noise reduction asphalt pavement construction planning system based on multi-source data, characterized in that: The method for planning construction of drainage and noise reduction asphalt pavement based on multi-source data as claimed in any one of claims 1 to 6 comprises: A storage module, wherein the storage module is used to store a parameter training database; A sample data acquisition and update module, the sample data acquisition and update module is electrically connected to the storage module, and the sample data acquisition and update module is used to obtain the current construction requirements of the drainage and noise reduction asphalt pavement, filter out initial parameter training data from the parameter training database according to the current construction requirements of the drainage and noise reduction asphalt pavement, obtain real-time construction process parameter data under the current drainage and noise reduction asphalt pavement construction, and update the parameter training data of the drainage and noise reduction asphalt pavement; A construction process planning module, wherein the construction process planning module is electrically connected to the sample data acquisition and update module, and the construction process planning module is used to calculate and obtain drainage and noise reduction asphalt pavement construction process parameters according to parameter training data.

8. The drainage and noise reduction asphalt pavement construction planning system based on multi-source data according to claim 7 is characterized in that: The sample data acquisition and update module includes: A primary screening unit, which is used to screen out a number of parameter data that meet the current construction requirements of drainage and noise reduction asphalt pavement from the parameter training database as primary screening parameter data; A feedback analysis unit, wherein the feedback analysis unit is used to calculate a feedback value; An initial parameter determination unit, the initial parameter determination unit is used to screen out N pieces of initial screening parameter data with the largest feedback values ​​as initial parameter training data; The updating unit is used to obtain the real-time construction process parameter data of the current drainage and noise reduction asphalt pavement construction, and to update the parameter training data of the drainage and noise reduction asphalt pavement.

9. An electronic device, characterized in that: include: 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 so that the at least one processor can execute the drainage and noise reduction asphalt pavement construction planning method based on multi-source data as described in any one of claims 1-6.

10. A computer-readable storage medium storing a computer-readable program, characterized in that: When the computer-readable program is executed by a processor, the drainage and noise reduction asphalt pavement construction planning method based on multi-source data described in any one of claims 1-6 is implemented.

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