60results about How to "Lower application threshold" patented technology

The invention discloses a seed information question-answering system and method. The invention provides a variety information question-answering system. The system comprises a computing resource; the big language model calls computing resources to perform seed information question answering, the big language model is configured to learn knowledge related to the seed from a seed field knowledge source, and the big language model comprises an input acquisition module configured to be used for acquiring text information related to seed information questions from user input; the semantic understanding module is coupled to the input acquisition module and is configured to be used for converting the text information into vector information; the information reasoning module is coupled to the semantic understanding module and is configured to be used for generating an answer information vector based on knowledge related to the seed industry in combination with the vector information and the context, and the answer information vector comprises breeding decision information; and the result output module is coupled to the information reasoning module and is configured to be used for converting the answer information vector into answer text information.

The invention relates to the technical field of document picture processing, in particular to an image correction method not constrained by document pictures, which comprises the following steps of: S1, constructing a correction model, and obtaining a trained correction model after batch data training of a data set; the correction model mainly comprises a feature extraction network, a distortion encoder, a correction decoder and a code stream header, S2, inputting a distorted document image to be corrected into the correction model, predicting the offset of each pixel value of the distorted document image, and recovering the pixel values of the document image through the offset, and the distorted document picture is corrected and repaired. The method is not limited by document images, distorted document images in various real scenes can be processed at low cost, and the effect is better than that of other traditional image correction methods.

The invention discloses a water quality evaluation WQI expert weight fusion method based on a weighted extremum fusion algorithm, and relates to the technical field of water quality evaluation WQI. The method comprises the following steps: designing a single-factor evaluation algorithm; the importance degree of the water quality index is described by using three dimensions, and three different weighting methods are provided for the three dimensions; an algorithm, namely a weighted extremum fusion algorithm, which can fuse three weighting methods and realize subjective and objective combination is provided; by comprehensively considering the uncertainty degree of the water quality data, the index contribution degree and the regional key degree, the more scientific water quality evaluation method is provided, the method not only can accurately reflect the water quality condition, but also can provide a large number of adjustable parameters so that a user can carry out optimization according to specific requirements, and the user experience is improved. Therefore, water quality evaluation requirements of different regions can be better met, and the overall evaluation effect and practical value are improved.

The invention discloses an atmosphere display method and system based on text data information analysis of video streaming, and the method comprises the following steps: emotional atmosphere configuration: configuring the display effects of emotions and corresponding atmosphere devices, and building a mapping relation between the emotions and the corresponding atmosphere expression effects through the configuration; acquiring and playing video stream data in real time; extracting and analyzing subtitles or bullet screen texts from the video stream data; preprocessing the extracted subtitles or bullet screen texts; performing emotional emotion analysis on the preprocessed subtitles or bullet screen texts, wherein an identified emotional emotion classification result comprises two numerical values, namely an emotional category and an emotional weight; emotion and atmosphere conversion is carried out, and an emotion analysis result is converted into expression data capable of being recognized by atmosphere display; and according to the emotion and atmosphere conversion result, obtaining emotion expression data corresponding to the emotion analysis result of the bullet screen content, and driving an atmosphere device to perform corresponding display.

The invention provides an urban green infrastructure comprehensive benefit applicability evaluation method based on subjective and objective weights. The urban green infrastructure comprehensive benefit applicability evaluation method comprises the steps of establishing a basic evaluation system, screening indexes, calculating index weights, calculating quantitative indexes, calculating qualitative indexes, performing grading evaluation, performing standardized score assignment and performing comprehensive evaluation. The basic evaluation system is of a three-layer structure and covers four criteria of runoff regulation and storage benefits, environmental benefits, economic benefits and social benefits and 19 indexes; a subjective weight is determined through an analytic hierarchy process, an objective weight is determined through an entropy weight method, and a comprehensive weight is obtained in combination with a D-S evidence theory fusion method; quantitative indexes are calculated through methods such as hydrological simulation, and qualitative indexes are rated by public; the indexes are unified into dimensionless scores through standardized score assignment, and finally an evaluation result is obtained through weighted summation. According to the method, the applicability quantitative evaluation of matching of the typical green infrastructure and the site condition construction target is realized, and a scientific and quantitative decision support tool is provided for sponge city planning.

The invention discloses an algorithm library management system supporting visual arrangement of an algorithm model construction process. The algorithm library management system comprises an algorithm component management module, an algorithm component configuration module, an algorithm process arrangement module, an algorithm process operation module and an algorithm process log management module. The algorithm component management module is used for constructing and managing a full-process model algorithm component; the algorithm component configuration module is used for responding to a request of a user for setting specific parameters for each algorithm component in an algorithm model construction process; the algorithm process arrangement module provides a visual arrangement interaction mode, responds to the operation that a user drags algorithm components into a canvas, and connects the algorithm components according to a logic sequence through connecting lines to achieve data communication and transmission between the algorithm components. The algorithm process operation module is used for automatically executing algorithm components and resource scheduling according to the arranged logic sequence and completing execution of the whole algorithm model construction process; according to the method, a developer can construct and manage the algorithm model more efficiently and flexibly.

The invention discloses a method, a system and equipment for troubleshooting a communication terminal of an all-moving simulator, and belongs to the technical field of aviation simulation equipment fault diagnosis. The method comprises the following steps: acquiring data of a communication terminal operation state, an input / output system state and a central control console environment state, synchronizing time, and constructing a time sequence feature vector through denoising normalization processing; inputting a Kalman filtering state space model to calculate an observation residual error, and distinguishing a fault source and interference characteristics; identifying a fault type by using an integrated decision tree classification model, positioning a target fault point in combination with a fault tree and a Bayesian network, and matching historical cases to generate a troubleshooting scheme; after troubleshooting is completed, the fault case library is updated, and the model is optimized. According to the scheme, intelligent and standardized troubleshooting of faults is achieved, the problems that a traditional method is low in efficiency and poor in accuracy, and fault sources are difficult to distinguish are solved, the troubleshooting efficiency and accuracy are greatly improved, the operation and maintenance cost is reduced, and stable operation of the full-motion simulator is guaranteed.

The invention discloses a total variation regularization depth expansion network method for hyperspectral image unmixing. The method comprises the following steps: inputting hyperspectral image data and an end member spectrum library; constructing a hyperspectral data unmixing model fusing a sparse constraint term and a total variation regularization term and an optimization objective function of the hyperspectral data unmixing model; converting the optimization objective function into an equivalent augmented Lagrangian form, and performing iterative solution on each variable; expanding an iteration process into a deep learnable network structure with a plurality of layers, and parameterizing hyper-parameters and a plurality of approximate operators in iteration into learnable network parameters; constructing a comprehensive loss function, and continuously optimizing network parameters by using back propagation and gradient descent methods; according to the method, total variation regularization prior is fused into a sparse unmixing model, the sparse unmixing model is expanded into a learnable end-to-end neural network through iterative solution, and the method has excellent unmixing precision and robustness for noise-containing data.

The present invention provides an intelligent generation system for urban rail track basic information models, which pre-builds a station roadbed model and an interval roadbed model that do not include drainage ditches; for the station roadbed model, a station roadbed deepening model is formed by widening and deepening the roadbed limit and processing the drainage details; for the interval roadbed model, a section roadbed deepening model is formed by processing the transverse drainage ditches and the longitudinal drainage ditches of the roadbed in detail; the present invention realizes BIM modeling of mainline tracks, especially covering interval and station track models, filling the gap in BIM application of urban rail tracks, greatly improving the accuracy and modeling efficiency of BIM models of urban rail tracks, and lowering the threshold for BIM application of urban rail tracks.

The invention provides a log analysis method and system based on a large language model, and belongs to the technical field of log analys.The method comprises the steps that anti-fact rewriting is conducted on a to-be-analyzed log, and multiple log variants are obtained; log parameters are extracted from the log variants through the large language model to serve as intermediate variables, and the confidence coefficient of each intermediate variable is determined; performing correctness scoring on each intermediate variable based on statistical information of a historical log corpus knowledge base; determining a comprehensive score of each intermediary variable according to the confidence coefficient of the intermediary variable and the correctness score of the intermediary variable; and screening the medium variable with the highest comprehensive score as a log parameter of the log to be analyzed, and generating a log template of the log to be analyzed according to the log parameter of the log to be analyzed. According to the log analysis method, the stable semantic structure of the log can be more emphasized in the log analysis process, and the accuracy and generalization ability of log analysis are improved.

The present application relates to the technical field of energy storage device design, transportation and safety detection, and discloses a method and device for determining the center of gravity of an energy storage container, which comprises the following steps: calculating the total weight of the internal devices of a target energy storage container according to the number and estimated weight of each type of device in the target energy storage container; dividing the target energy storage container into multiple partitions and calculating the total weight of the internal devices of each partition; calculating the center of gravity coordinates of each partition according to the center coordinates of each partition; and calculating the target center of gravity coordinates of the target energy storage container according to the net weight, factory center of gravity coordinates and total weight of the internal devices of the target energy storage container, and the total weight of the internal devices and center of gravity coordinates of each partition.

This invention discloses a method, apparatus, equipment, and storage medium for predicting the minimum miscibility pressure of crude oil. The method includes acquiring the target crude oil for which miscibility pressure prediction is to be performed and the target gas for injecting into the target crude oil for oil displacement. The target crude oil and target gas are subjected to component analysis to determine the necessary component parameters for predicting the minimum miscibility pressure. Based on a pre-fitted target miscibility pressure prediction model, the target minimum miscibility pressure for the miscibility of the target crude oil and target gas is determined according to the necessary component parameters. The target miscibility pressure prediction model is divided into a first miscibility pressure prediction model and a second miscibility pressure prediction model based on the gas type of the target gas. This invention is applicable to injection gas scenarios involving pure CO2 or flue gas containing different impurities. By separately calculating the miscibility pressure contributed by the oil phase itself and the miscibility pressure contributed by the injection gas, the accuracy and applicability of minimum miscibility pressure prediction can be significantly improved.

The invention discloses an output method based on 32-bit single-chip microcomputer firmware upgrade memory anti-overflow protection, and relates to the field of single-chip microcomputer memory anti-overflow protection, and the method specifically comprises the following operation steps: S1, environment variable configuration and management; s2, performing core execution of the Python automatic script; s3, performing anti-overflow protection on the memory; and S4, cleaning redundant files and environment variables. According to the output method based on the 32-bit single-chip microcomputer firmware upgrade memory anti-overflow protection, the file path is defined as the environment variable and stored in the independent configuration file in a centralized mode, complete separation of the path and script logic is achieved, the non-transplantable problem caused by a hard coding path is avoided, meanwhile, the adaptation cost in different environments is reduced, and the adaptation efficiency is improved. Operators do not need to modify script codes and only need to adjust configuration files to complete deployment.

This invention discloses a high-precision feedback measurement system and method for triaxial magnetic fields based on the SPGD algorithm, comprising: an atomic magnetometer, a triaxial Helmholtz coil group, a signal acquisition and processing module, an SPGD algorithm control module, a multi-channel precision current source, and a magnetic field calculation module, with each module forming a closed-loop feedback link. The signal acquisition and processing module extracts relevant physical quantities from the performance evaluation function in the output signal of the atomic magnetometer. The SPGD algorithm control module generates control commands through parallel perturbation, gradient estimation, and parameter updates. The multi-channel precision current source converts the commands into a stable current to drive the coils to generate a compensating magnetic field. The magnetic field calculation module calculates the environmental magnetic field components by combining calibration coefficients and the driving current. This invention can be directly adapted to commercial atomic magnetometers, automatically decouples the triaxial magnetic field coupling, and achieves rapid convergence and accurate measurement. It is suitable for high-precision vector magnetic field measurement in fields such as geomagnetic navigation, biomagnetic imaging, and space exploration.

This invention relates to the field of spectral analysis and identification of genuine and counterfeit Chinese medicinal materials, and discloses a method for identifying counterfeit Cordyceps sinensis based on multispectral fusion. This method first collects multispectral image data of samples under standard conditions; eliminates equipment and environmental noise through standardized preprocessing to establish a reliable data foundation; then, it fuses extracted spectral derivative features and spatial texture features to construct a lightweight neural network identification model. Its core innovation lies in introducing a physical interference stripping model, which can actively correct spectral distortion caused by moisture and mold, obtaining intrinsic spectra to improve model robustness; and through dynamic verification and incremental learning mechanisms, the model can continuously evolve, effectively identifying new counterfeiting methods. Finally, the entire model is integrated into a multispectral portable terminal, achieving rapid screening within seconds and outputting a complete report including authenticity determination, type inference, and confidence level. Ultimately, this solves the industry problems of low efficiency, reliance on experience, and inability to be applied on-site by traditional methods.

This invention discloses a non-inertial navigation mobile indoor volume measurement and 3D reconstruction method, equipment, and computer-readable medium, belonging to the interdisciplinary field of precision engineering measurement, computer vision, and digital twin technology. The method includes the following steps: S1, dynamic scanning data acquisition; S2, adaptive data augmentation and cleaning; S3, trajectory and depth calculation based on motion continuity constraints; S4, cross-sectional topology construction and closure constraints; S5, 3D solid modeling preserving volume characteristics; and S6, precise volume calculation based on the solid model. This invention employs the aforementioned non-inertial navigation mobile indoor volume measurement and 3D reconstruction method, equipment, and computer-readable medium, and through a single-line 2D LiDAR combined with innovative algorithms, achieves mobile high-precision volume measurement and high-fidelity 3D reconstruction of irregular indoor spaces under low-cost hardware conditions.

The application discloses an industrial control method and device based on model training, and belongs to the field of industrial control. The industrial control method based on model training comprises the following steps: using a target algorithm prediction model to perform operation processing on real-time industrial big data in a target industrial scene, so that a target control algorithm and a target independent variable for controlling a target controlled object in the target scene output by the target algorithm prediction model are obtained; and inputting the value of the target independent variable in the real-time industrial big data into a target controller in which the target control algorithm is deployed, so that the value of a target control variable is obtained, to control the target controlled object. The industrial control method based on model training has high precision and accuracy of the obtained target control algorithm, can significantly reduce the labor and time cost, improve the control efficiency and control effect, and has high universality.

The invention belongs to the technical field of fluid mechanical engineering, and particularly relates to a centrifugal pump and turbine dual-mode shaft power calculation method based on mechanical energy and internal energy analysis. Performing three-dimensional flow field calculation based on the pump mode system mass flow; calculating the specific mechanical energy difference between the outlet boundary and the inlet boundary of the pump mode system; calculating the specific internal energy difference between the outlet boundary and the inlet boundary; calculating pump mode shaft power of the centrifugal pump; determining a turbine mode system of the centrifugal pump; three-dimensional flow field calculation is executed based on the turbine mode system mass flow; calculating the specific mechanical energy difference between the inlet boundary and the outlet boundary of the turbine mode system; calculating the specific internal energy difference between the outlet boundary and the inlet boundary; calculating the turbine mode shaft power of the centrifugal pump; through collaborative analysis of mechanical energy and internal energy, the structure and operation characteristics of the pump and turbine dual mode of the centrifugal pump are adapted, and the technical blank of quantitative shaft power calculation under the pump and turbine dual mode of the centrifugal pump is made up from the perspective of system energy dissipation and conservation.

The invention discloses an InDel molecular marker closely linked to a wax gourd peel color change gene and its application, belonging to the technical field of plant molecular breeding. The InDel molecular marker is located on chromosome 5 of the wax gourd genome. Ms.pf3chr5g483 The promoter region of the gene; the InDel molecular marker is the nucleotide sequence shown in SEQ ID NO.3, and the 80th to 172nd bases of the nucleotide sequence are inserted or deleted. The InDel molecular marker provided by the present invention can quickly and high-throughput identify the peel color change phenotype of the offspring of the wax gourd hybrid combination at the seedling stage, and can be used for the identification of the peel color change genotype in large-scale wax gourd germplasm resources; the present invention can be applied to the molecular breeding and genetic improvement of the wax gourd peel color change trait, effectively improving the breeding efficiency, shortening the breeding cycle and saving resources.

The present application relates to the field of temperature measurement, in particular to a kind of metal organic framework crystal material and its preparation method and application.The present application provides a kind of metal organic framework crystal material, wherein the crystal material is connected body 2,6-di (2,4-dicarboxyphenyl) -4- (phenyl) pyridine and Zn (II) connected with the crystal material with periodic three-dimensional network structure.The metal organic framework crystal material provided by the present application still keeps the afterglow characteristic under the condition of smaller particle size, and the charging time is shorter;At the same time, the decay time of the metal organic framework crystal material of the present application is seconds, and the light source only needs ordinary ultraviolet semiconductor light source, and the camera can record the time / color of afterglow decay, as the basis for temperature judgment, which greatly reduces the temperature measurement cost and simplifies the measurement process;In addition, the metal organic framework crystal material of the present application can be synthesized below 120 DEG C, which reduces the production cost and danger.

The invention belongs to the field of early disease diagnosis, and particularly relates to a core-shell nanoparticle labeled portable dual-mode immunoassay platform based on dynamic driving, which comprises an antibody-gold nanoparticle biological coupling system, an amplification system, a color development system and a colorimetric-atomic emission spectrum detection system. The Au-coated Cu core-shell nano-particles are dynamically driven to realize signal amplification, colorimetric preliminary screening and atomic emission accurate quantification are combined, CEA (0.02 ng / mL), cTnI (0.35 fg / mL) and A beta (10.3 pg / mL) can be detected in an ultra-sensitive manner, and the Au-coated Cu core-shell nano-particles are suitable for bedside detection of early diseases.

The present invention discloses a landscape design tool based on parametric design, wherein the landscape design tool selects a plurality of batteries from Grasshopper software running on a Rhino software platform according to the needs of landscape design, builds a battery pack and packages it into a single new battery, and then classifies and integrates the packaged new batteries to form a toolbar including a plurality of columns; the battery is a basic unit of Grasshopper. The use of the present invention for garden design can lower the application threshold of parametric technology in landscape design, improve the scientific nature of design results, and greatly improve the work efficiency of enterprises. The present invention has the advantages of reducing the design difficulty of designers, making the design more targeted and the work efficiency higher.

The invention relates to model training, in particular to a community police information early warning model training system based on quantum safety protection, which comprises a multivariate data identification unit, a data processing unit, a data processing unit, a data processing unit, a data processing unit and a data processing unit, model training samples corresponding to the modal data are sent to the model training management unit; the model training management unit verifies the model training samples sent by the multivariate data identification unit, performs model training on models corresponding to various modal data, and optimizes the models according to model training quality and model operation efficiency scores provided by the model deployment unit; the model deployment unit is used for deploying the trained model in the operation environment and monitoring and evaluating the operation state and the operation efficiency of the model; according to the technical scheme provided by the invention, the defects of low accuracy and efficiency of community police information early warning caused by difficulty in effective model training can be effectively overcome.

This invention discloses a method and system for evaluating DNA storage sequencing depth based on channel simulation, addressing the problems of inaccurate predictions and limited guidance in existing uniform distribution models. The method includes: when sequencing data is available, fitting real data to obtain log-normal distribution parameters μ and σ; when sequencing data is unavailable, obtaining μ and σ through simulation modeling based on experimental parameters; and combining these parameters to calculate the decoding ratio of the coding strand in the noiseless channel and the sequencing depth boundary in the noisy channel. The system includes input, storage channel modeling, sequencing depth calculation, and output modules. The model of this invention closely reflects reality, provides accurate predictions, reduces DNA storage and retrieval costs, improves the success rate of single-sequencing decoding, and is easy to use, facilitating the practical application of the technology.

This invention discloses a rapid early warning and estimation method for the structural state of prestressed concrete continuous rigid frame bridges based on long-term deflection changes, belonging to the field of bridge structural health monitoring and assessment technology. This method involves setting up permanent observation points during the operation of the continuous rigid frame bridge to collect long-term deflection data and establish a deflection characteristic equation. Combined with the prestress-deflection and main beam stress-deflection regression relationships, it achieves dynamic calculation of the structure's prestress and stress state. Simultaneously, it sets early warning thresholds based on deflection development trends to provide rapid early warning of abnormal structural deformation and completes the serviceability limit state and ultimate limit state assessments according to current standards. This invention solves the problems of reliance on short-term data, delayed early warning, and inaccurate state estimation in traditional bridge assessments. It achieves long-term dynamic tracking and accurate prediction of structural state, providing a scientific basis for bridge maintenance decisions and is applicable to the health monitoring and performance assessment of continuous rigid frame bridges during the operation period.

The invention discloses a method for promoting growth of intercropping crops based on a soil micro food web and application of the method, and belongs to the technical field of crop planting. According to the invention, it is found for the first time that by adding a specific type of bacterial-feeding nematodes into soil, synergistic improvement of growth indexes such as plant height, stem diameter and biomass of two crops can be obviously and stably promoted; the application method is simple and easy to operate, the cost is controllable, and no additional farming equipment or steps are needed; the method is high in environmental compatibility, is particularly suitable for a farmland peanut-corn intercropping system in alkaline and calcareous soil, can effectively improve the crop growth performance, farmland productivity and agricultural product yield and quality, can optimize the soil ecological function, continuously increases the economic benefits of farmers, and has wide application prospects. A brand-new, low-cost and easy-to-popularize candidate scheme is provided for agricultural green sustainable development of the alkaline soil area in North China, and the application prospect is wide.

The invention is suitable for the technical field of automobile aerodynamics and thermal management, and provides an automatic opening and closing heat dissipation and resistance reduction hubcap structure and a control method thereof.The hubcap structure comprises a hubcap base and a hubcap cover, the hubcap base is provided with base ventilation openings, the hubcap cover is provided with cover cover ventilation openings, and the hubcap ventilation openings are communicated with the hubcap base. The blades are connected with the hubcap base through reset springs; the traction and locking unit comprises a sliding way, a traction sliding block is installed in the sliding way, the traction sliding block is connected with the blade through a traction rope, a locking magnet is arranged in the sliding way, a traction spring connected with the locking magnet is arranged in the sliding way, and a locking iron sheet used for attracting the locking magnet is arranged on the blade. The device completely depends on the physical principle to achieve self-adaptive opening and closing, does not need external energy, is simple and reliable in structure, low in cost and convenient to install, can balance the requirements for high-speed resistance reduction and low-speed heat dissipation, and effectively improves energy efficiency and driving safety.

The application provides a cable tunnel fire prediction method based on physical perception machine learning, relates to the field of fire prediction, and comprises the following steps: generating multiple groups of working condition combinations by using a Latin hypercube sampling method, and constructing a multi-working condition simulation training data set through simulation; constructing a composite loss function, using XGBoost to construct a nonlinear mapping model and performing physical perception modification, training the modified model by using the data set, and obtaining an enhanced XGBoost model; performing feature attribution analysis by using a SHAP method, and obtaining global importance weights and a key parameter contribution spectrum; taking the key parameter contribution spectrum as a search prior, guiding a symbolic regression algorithm PySR to perform evolutionary search, and obtaining an explicit analytical expression of cable ignition time; and substituting working condition parameter vectors of a cable tunnel to be evaluated into the explicit analytical expression, and obtaining a fire prediction result. The application can reduce systematic deviation caused by extrapolation while maintaining high prediction accuracy.

The invention discloses a large language model-driven cross-multi-source heterogeneous data platform collaborative abnormal behavior detection method and a large language model-driven cross-multi-source heterogeneous data platform collaborative abnormal behavior detection system. The method comprises the following steps: aiming at a target entity, respectively extracting local dynamic sub-graphs of the target entity in a plurality of heterogeneous data platforms, fusing specific structural relationships, attribute features and text contents of the platforms, and constructing a multi-source heterogeneous time sequence behavior snapshot sequence; a frozen graph encoder and a semantic model are adopted to independently encode each source sub-graph, and multi-channel snapshot embedding in a unified representation space is generated through cross-domain alignment projection under privacy protection constraint; designing a comparative learning strategy of federal perception, and in combination with a cross-platform behavior consistency regular item and a generative classification target, embedding and injecting the snapshots into a large language model in a multi-channel soft prompt form to perform parameter fine tuning; and performing end-to-end collaborative reasoning on the cross-platform behavior sequence by using the fine-tuned model, and outputting an abnormal risk level.

The invention belongs to the field of roads, and particularly relates to a road epoxy asphalt toughening additive and a preparation method thereof.The preparation method comprises the steps that calcium carbonate whiskers are prepared from calcium 2-methoxyethanol and ammonium bicarbonate and subjected to hydrophobic modification, and modified calcium carbonate is obtained; the preparation method comprises the following steps: carrying out surface coating on calcium sulfate, then mixing the coated calcium sulfate with modified calcium carbonate, putting the mixture into an ethanol dispersion liquid of ammonium carbonate, and fully dispersing to obtain the road epoxy asphalt toughening additive. The road epoxy asphalt toughening additive disclosed by the invention can be used for directionally filling pores of a road system and bridging and repairing cracks in a subsequent road use process, so that an internal structure is more compact, continuous toughening is realized, the durability of a road is improved, and the service life of the road is prolonged.