37 results about "Customs declaration" patented technology

The invention relates to the field of intelligent information processing, in particular to a carbon border adjustment mechanism intelligent auxiliary customs declaration method and system based on natural language processing, and the method comprises the steps: carrying out the real-time translation and key information extraction of CBAM related rule files and unstructured documents; a dynamic CBAM knowledge graph is constructed based on related rule texts, rule updating is monitored in real time through a text classification and event extraction technology, and calculation rules and declaration logic are dynamically adjusted; performing standardization processing on supplier data in different formats, integrating an industry emission factor library, automatically matching a calculation model according to a product type, generating a carbon emission result meeting a CBAM requirement, and mapping the data to a corresponding position of a CBAM declaration form; based on historical declaration data and related rule texts, analysis and compliance risk prediction are carried out by using a natural language processing technology, so that the declaration data are ensured to accord with latest rules, and violation risks caused by rule changes are avoided.

The invention belongs to the technical field of artificial intelligence, and particularly relates to an export customs declaration commodity name intelligent matching system and method based on a large model. Through real-time acquisition and standardization of multi-source heterogeneous data, extraction and vectorization of multi-modal features of commodity information, generation of classification candidate items based on a hybrid expert big language model, and Pareto optimal decision based on multi-target optimization, intelligent and efficient matching of commodity names and customs codes is realized, and the matching efficiency of commodity names and customs codes is improved. And the compliance, the timeliness and the economic benefit of the customs declaration strategy are improved.

The application discloses an international trade intelligent customs declaration system and method, and relates to the technical field of international trade.The application comprises a data acquisition module for acquiring single certificate image data and associated form data of a batch to be declared; a multi-modal analysis and verification module for loading a trained multi-modal perception model; and the following steps: S1: acquiring single certificate image data and associated form data of a batch to be declared.The application has the advantages that single certificate information extraction and compliance logic verification are simultaneously completed in single semantic understanding, the recognition result directly carries a quantifiable and reliable verification conclusion, eliminating the information gap of the traditional separate architecture; at the same time, the maintenance work of creating fixed templates according to countries and single certificate types is eliminated, the application has self-adaptive capacity for format changes and unexpected abnormalities, and the model can be continuously optimized from the correction feedback of the customs officer, so that compliance conflicts can be effectively intercepted in the declaration preparation stage, and the single rejection rate and customs clearance time are reduced.

Embodiments of the present application disclose a customs declaration information processing method and device and electronic equipment. The method comprises: determining a customs declaration material file associated with a to-be-generated customs declaration form; identifying text information content of the customs declaration material file to determine at least one named entity included therein, the named entity comprising a continuous character fragment in the text information content; and during an information input operation for a target field in the customs declaration form, providing recommended information about to-be-input information in the target field according to the named entity identified from the customs declaration material file. Through the embodiments of the present application, the efficiency of generating a customs declaration form can be improved, and the probability of input errors and the like caused by a manual input process can be reduced.

The invention discloses a mail fusion governance device with an AI identification technology, and particularly relates to the technical field of mail governance, and the mail fusion governance device comprises a certification data receiving module, a multi-mode intelligent analysis engine, a mail account relation modeling module, a customs data collision engine and an Excel result output module. According to the method, intelligent structured conversion of multi-format attachments is realized by constructing a mail governance architecture fusing AI multi-modal identification and relation mining, and unstructured service data scattered in the attachments are automatically extracted and mapped into standard database fields by utilizing cooperative work of a large language model and a multi-modal model, so that the mail governance efficiency is improved. Establishing a dynamic mail entity relation graph, and generating an association network based on mail contact characteristics to strengthen the business traceability; a cross-source data intelligent collision engine is designed, structured mail data is compared with third-party systems such as customs declaration in real time, risk clues or business evidence closed loops are automatically output, and the time cost of manual checking is greatly reduced.

The invention discloses an intelligent customs declaration management system based on multi-model collaboration. The intelligent customs declaration management system comprises the steps of file format judgment, picture preprocessing, file uploading, information data extraction, storage and translation and the like. By means of the mode, the intelligent customs declaration management system based on multi-model cooperation can achieve automatic file sorting and direction correction, reduce manual intervention, improve the OCR recognition accuracy under complex format and multi-language scenes through layout analysis and AI large model understanding semantics, and improve the user experience. Therefore, the robustness and efficiency of key information extraction are improved.

The invention discloses a customs abnormal behavior recognition method based on a generative adversarial network, a storage medium and equipment, and the method comprises the steps: collecting customs behaviors: collecting luggage image data, corresponding customs declaration information and behavior tracks of corresponding personnel; multi-modal fusion features are obtained from the luggage image data, the corresponding customs declaration information and the behavior tracks of the corresponding personnel through a multi-head attention mechanism; sampling Gaussian distribution random noise, and splicing the multi-modal fusion feature and the random noise to obtain a condition vector; constructing a multi-modal generator, taking the condition vector as the input of the multi-modal generator, and guiding the cross-modal generator to generate a reconstructed multi-modal tensor; and constructing a multi-modal discriminator, taking the reconstructed multi-modal tensor as the input of the multi-modal discriminator, outputting the discrimination probability of the multi-modal tensor, and taking the customs behavior of which the discrimination probability exceeds an abnormal threshold value as the customs abnormal behavior, so that the recognition capability of the customs abnormal behavior is improved, and the dependence on manual recognition is reduced.

The invention discloses an import and export commodity classification verification method and system based on an AI large model, belongs to the technical field of data processing, and aims to solve the technical problem of how to improve the accuracy and automation level of import and export commodity classification verification. Comprising the steps of extracting data from an import and export commodity classification system, a general declaration element table and a GBase database, learning a commodity classification rule through an AI large model based on the extracted data, and constructing a standard classification library based on data related to commodity classification; comparing the commodity data in the customs declaration with the standard classification library through an AI large model, and labeling the commodity data to obtain labeled commodity data; carrying out manual correction on the marked commodity data to obtain corrected commodity data; and pushing the corrected commodity data to a declaration place customs and an enterprise terminal for processing.

The invention provides a customs declaration process teaching method and system based on virtual reality, and belongs to the technical field of teaching methods.The customs declaration process teaching method and system based on virtual reality comprises a virtual reality scene generation module used for constructing and outputting three-dimensional virtual scene data; the role distribution module is in communication connection with the virtual reality scene generation module; the document simulation module is used for storing and outputting the electronic form data to the student terminal; the process decision module is in communication connection with the document simulation module; the behavior acquisition module is used for acquiring operation track data generated by the student terminal in the virtual scene in real time; and the teaching management background is in communication connection with the behavior acquisition module, and solves the source denoising problems of high-frequency distortion of an operation track and inaccurate evaluation caused by vibration, rotation and misoperation in virtual reality-based customs declaration teaching.

The invention discloses a customs declaration method, system and device and a storage medium, and the method comprises the steps: responding to an order declaration request of an e-commerce platform, and obtaining the declaration configuration information of a corresponding target customs according to the order declaration request; calling a message type template and a value mapping template to construct the declaration configuration information into a declaration message; and encrypting the declaration message and sending the encrypted declaration message to a customs declaration system, so that the customs declaration system decrypts the declaration message and performs declaration verification. And the declaration message is constructed by using the message type template and the value mapping template, so that the requirements of different customs are flexibly met, and the accuracy and consistency of data are ensured. The encrypted declaration message protects sensitive information and prevents unauthorized access or tampering in the transmission process, and the accuracy and efficiency of customs declaration are improved.

The invention discloses an import and export prediction method and device based on the foreign trade industry and a medium. The method comprises the steps that macroeconomic data and customs declaration data are collected according to a preset period; performing preprocessing to generate standardized data; performing star modeling on the standardized data through a time-industry-commodity-nationality index rule, and constructing a multi-dimensional data warehouse; respectively adopting an SARIMA model and an LSTM network to carry out feature extraction and analysis on the data in the warehouse, and finally obtaining prediction data in a future preset time period through weighted fusion; constructing a prediction subject library according to the target foreign trade scene; and matching the received scene with the theme library, and visually displaying the related prediction data. According to the method, the import and export trend is accurately predicted through the hybrid model, the seasonal demand peak, the exchange rate sensitive window and the freight rate impact time point are effectively identified, the prediction precision and the policy response efficiency are remarkably improved, and the operation risk caused by fund occupation and price fluctuation is reduced.

This application provides a method for assessing the quality of customs declarations in cross-border e-commerce. Applied to the field of big data analytics, it extracts product attribute features and performs multi-condition searches to proactively generate a set of candidate declaration codes. Then, using the corresponding declaration supervision conditions and requirements for each candidate code, it differentiates and compliantly adjusts the user's original declaration data (marking missing documents and supplementing declaration elements). Based on the adjusted value information, it recalculates tariffs, forming multiple structured declaration schemes. Since each scheme is a feasible option that can pass customs review after supplementing the required materials, users can not only intuitively compare the tariff savings of each scheme with the list of additional materials required, but also make a quantitative trade-off between tariff costs and operational convenience. Under the premise of legality and compliance, it significantly improves the ability to optimize tax and fees in declarations and enhances the user's autonomy in decision-making.

The invention discloses a regional foreign trade enterprise development prediction and early warning method optimized through a random forest algorithm, and relates to the technical field of big data analysis. Comprising the steps of 1, establishing a foreign trade enterprise database, 2, collecting foreign trade enterprise data, preprocessing the collected data, associating customs declaration data of all foreign trade enterprises, foreign trade enterprise power data, export amount of the industry to which the foreign trade enterprises belong and trade environment data, performing standardization processing on the data, and storing the data in a database; step 2, converting indexes of different orders of magnitude into indexes of the same order of magnitude, and converting unstructured data into structured data, and step 3, performing preliminary analysis and calculation according to the collected foreign trade enterprise data; 4, establishing a regional foreign trade enterprise prediction and early warning model, predicting the condition according to each index condition, respectively giving different scores, and finally obtaining important foreign trade enterprise early warning levels; 5, introducing a random forest algorithm into the regional foreign trade enterprise prediction and early warning model, training historical early warning data, and calculating the early warning levels of the important foreign trade enterprises according to power trade settlement period characteristics. A double-cycle rolling window is adopted to capture short-term fluctuation, and meanwhile, a moon-level window is reserved to recognize tendency risks.

The invention relates to the technical field of image processing, in particular to an intelligent station inspection image and customs declaration data association method based on edge calculation, and aims to solve the problem of low inspection efficiency caused by insufficient image semantic segmentation precision in the prior art. And dynamically repairing and matching the preliminarily segmented semantic region, adaptively screening the optimal feature dimension, and finally associating the optimized target semantic region with customs declaration data. According to the method, the accuracy of image segmentation is effectively improved, and the query efficiency and reliability after the check image is associated with the customs declaration are improved.

The invention discloses an intelligent customs declaration information processing method and system based on an AI large model, and relates to the technical field of data processing.The method comprises the steps that through batch scanning and format analysis of full-type bill images, text information is extracted through the OCR technology, and an identification text information set is generated; traversing the set to construct an original tetrad and antagonistic tetrad set, and forming a structured information set; field conflict identification is carried out, conflict resolution and correction are carried out according to an identification result, and a verification structured information set is obtained; and converting the verified structured information set into a standardized customs declaration, and outputting a target customs declaration. The technical problems that in the prior art, customs declaration processing depends on manual operation, so that the document processing efficiency is low, and errors are high are solved, and the technical effects that the AI large model and the OCR technology are combined, customs declaration information is automatically processed, and the customs declaration efficiency and accuracy are improved are achieved.

The invention provides a declaration element code conversion method and device, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining customs declaration data of a target commodity; wherein the customs declaration data comprises commodity codes, original pairing information and original numerical value information; determining a declaration element demand field of the target commodity based on the commodity code; generating a cue word based on the declaration element demand field, the original pairing information and the original numerical value information; and based on the cue word and a preset declaration element rule, performing code conversion on the cue word to obtain a target code corresponding to the customs declaration data. According to the declaration element code conversion method provided by the invention, customs declaration data which is described by a natural language and possibly has errors or is not standard is automatically converted into normalized and standardized target codes, manual intervention is reduced, and the efficiency and accuracy of code conversion of declaration elements in customs receipts are improved.

The application provides a customs clearance risk detection method and system based on customs declaration document recognition, and relates to the technical field of customs declaration document risk management. The method comprises the following steps: obtaining a scanned copy of a basic customs declaration document, and determining whether additional customs declaration documents are required; if additional customs declaration documents are required, generating upload prompt information; determining a high customs declaration risk trigger result according to the recognition result of the scanned copy of the basic customs declaration document and the upload result of the scanned copy of the additional customs declaration document; determining a medium customs declaration risk trigger result according to the recognition results of the scanned copy of the basic customs declaration document and the scanned copy of the additional customs declaration document; determining a low customs declaration risk trigger result according to the recognition result of the scanned copy of the basic customs declaration document; and determining a customs clearance risk detection result according to the high customs declaration risk trigger result, the medium customs declaration risk trigger result and the low customs declaration risk trigger result. According to the application, accurate prompts can be given based on the risk level of the customs declaration documents, so as to improve the probability of smooth customs clearance.

The invention discloses an e-commerce customs clearance data security processing method based on cloud isolation, and is applied to the technical field of customs declaration. The method comprises the following steps: deploying a cloud isolation environment located in the same trusted domain in the e-commerce cloud to ensure that data is not out of the cloud; receiving and storing the original order data in the isolation environment through a unified order acquisition service module; analyzing and standardizing the data to generate customs clearance preprocessing data; performing irreversible desensitization processing based on a static or dynamic customs clearance declaration rule engine to generate desensitization declaration data; encrypting and transmitting the desensitized data through a security data channel based on TLS and bidirectional certificate authentication; and calling a unified customs declaration service module at a receiving end through an event triggering mechanism, generating a customs declaration message according with customs regulations based on the desensitization data, and submitting customs clearance. Through cooperation of cloud isolation, regularized desensitization and encrypted transmission, the security and compliance of customs clearance data are guaranteed while the requirement that the data cannot be out of the cloud is met, and the problem of data security integration in customs clearance of e-commerce is effectively solved.

This application provides a method, apparatus, storage medium, and electronic device for automated identification of customs declaration documents, relating to the field of automated information processing technology. The method includes: identifying the document type of the documents to be identified based on a general language model, determining the document type of each document among multiple documents to be identified; converting each document to be identified into a document image, and performing image preprocessing operations on each document image to obtain a target document image for each document to be identified; and using a visual language model corresponding to the document type to identify and extract key information from the target document image of each document to obtain the target information corresponding to each document to be identified. The automated identification method for customs declaration documents provided by this application can quickly extract the required information from the original customs declaration documents and convert it into structured data for subsequent processing and analysis, greatly reducing labor costs and improving customs declaration efficiency.

This device is installed in airports and allows users to go through immigration and customs procedures. It enables identity verification by comparing the facial image on the passport with the facial image captured by the camera, contactless fingerprint authentication using the camera, QR code reading for information required for immigration and customs procedures, and input of customs declaration forms using a touch panel.

The invention discloses an intelligent customs declaration compliance verification method and system based on multi-source data, and relates to the technical field of customs declaration compliance verification. According to the method, through multi-source data time sequence synchronization, credibility evaluation, multi-level rule verification, multi-protocol conflict judgment and AI semantic cross validation, the problem of verification contradiction caused by multi-source data time sequence deviation in the prior art is solved. And the system is in butt joint with a single window, an ERP system and a document file, calculates a data credibility weight, generates an initial risk score and a conflict judgment score, and outputs a grading risk report. According to the scheme, the compliance verification accuracy and efficiency are improved, the customs clearance delay risk is reduced, and the method is suitable for an intelligent declaration scene of enterprise customs declaration.

The invention relates to a CMS work order management system, and relates to the field of customs management technology, and the system comprises a document recognition system which is used for recognizing a document type, a business field, a certificate issuing attachment, order change data, and a certificate attachment; and the customs affair management system is in communication with the document identification system, the customs declaration system and the order management system, and is used for docking the work order, transmitting the customs declaration information, the order making information, the customs entry and exit list, the check and release list and the check and annotation list to the customs declaration system according to the work order configuration items, and returning customs inventory, the order making state and the order making result. According to the invention, the management efficiency of the customs management system can be improved.

This invention relates to the field of intelligent port analysis technology, and discloses a method and system for optimizing the entire process of intelligent port inspection appointments. The method includes: acquiring a customs declaration dataset and a container dataset from the China Railway Administration; preprocessing the data using a distributed data processing framework to construct a unified and associated dataset; logically matching the customs declaration dataset and the container dataset based on the container number field to generate a mapping relationship with container location information; obtaining real-time fused coordinates of customs officers through mobile GPS and BeiDou dual-mode positioning; constructing a deep learning navigation model considering travel time based on a deep reinforcement learning algorithm to generate navigation paths in real time; using an improved ResNet model to analyze container photos to determine inspection conditions, and automatically generating inspection task allocation instructions based on cargo type and customs officer qualification database; achieving real-time data exchange among customs, railway, and enterprises, and generating efficiency optimization suggestions, greatly improving customs clearance efficiency and enhancing customs clearance capabilities.

The invention discloses a customs declaration file generation method and system based on multi-port adaptation, and relates to the field of digital customs clearance, and the method comprises the steps: taking a customs declaration regulation text and a template as input to automatically analyze and generate a grammar model of each port, and achieving the structuralization and machine readable expression of a customs declaration rule of the port; a hierarchical constraint grammar model comprising a basic grammar layer and an extended grammar layer is constructed through unified identification of multi-port semantic equivalence fields, generality and personality are distinguished on the premise of unifying standard semantic fields, and centralized modeling and flexible extension of multi-port rules are achieved; and for a specific target port, automatically deriving a target port alignment grammar structure and a customs declaration field configuration result from the hierarchical grammar model, and automatically mapping and filling with multi-source data of an enterprise business system to generate an electronic customs declaration file meeting the requirements of the target port. Therefore, the automatic and refined processing capability of the multi-port customs declaration business is cooperatively improved from two key dimensions of rule management and data generation.

The application relates to the technical field of foreign trade services, in particular to an intelligent customs declaration form generation whole-process customs cooperation method and system for foreign trade services, which comprises the following steps: acquiring and cleaning multi-source data such as trade, bills and tax, and extracting key customs declaration elements; structuring and integrating the data and matching a process template to generate a customs declaration form to be examined; extracting full-link event nodes to construct a dynamic knowledge graph; training an examination intelligent agent based on historical data and supervision rules to perform compliance inspection and risk assessment on the customs declaration form and output an examination receipt containing modification suggestions; fusing the examination result of the intelligent agent and the reasoning conclusion of the knowledge graph to automatically generate an optimized final customs declaration form; and feeding back the actual customs clearance result to the knowledge graph and the intelligent agent for incremental learning and strategy updating to form a closed-loop optimization mechanism for continuous self-improvement. The technical scheme can significantly improve the declaration efficiency and customs clearance efficiency.

1. The name of the design product: graphical user interface of express delivery and customs declaration of electronic equipment. 2. The use of the design product: an electronic device. 3. The design points of the design product: in the graphical user interface. 4. The picture or photo that best shows the design points: front view. 5. The usual design, omit the rear view, left view, right view, top view, bottom view. 6. The use of the graphical user interface: to show the interface of the user in the operation of express delivery and customs declaration. 7. The human-computer interaction mode of the graphical user interface: the front view is the product homepage; click "send to Hong Kong and Macao" in the middle of the front view to enter the order page, get interface change state diagram 1; after filling in the address information of the sender and the recipient in the "address book" of interface change state diagram 1, get interface change state diagram 2, slide the interface change state diagram 2 interface upwards, the remaining content can be displayed, get interface change state diagram 3; click "customs declaration" in interface change state diagram 3 to get interface change state diagram 4; click "add delivery items" in interface change state diagram 4 to get interface change state diagram 5; after inputting the item name in interface change state diagram 5, the detailed classification interface of this type of item appears below, get interface change state diagram 6; click "confirm" below interface change state diagram 6 to get interface change state diagram 7, slide the interface change state diagram 7 upwards, the remaining content can be displayed, get interface change state diagram 8. The "X" in each design interface is a character area.

This invention provides an intelligent recommendation method for customs declaration timing that takes into account overseas holidays and customs clearance time differences. It collects time data from key nodes of customs clearance operations through multi-source heterogeneous interfaces, and generates standardized operation logs through time zone normalization, anomaly removal, and structured encapsulation. Further, it performs rhythmic phase alignment and density analysis on the logs to extract rhythmic fingerprint feature vectors reflecting the port operation rhythm, and establishes a rhythmic fingerprint database containing different port and holiday types. During real-time declaration, it can dynamically recommend the optimal declaration time window by combining historical high-efficiency periods and confidence analysis. The system can also adaptively calibrate rhythmic feature parameters based on the deviation of actual customs clearance time. This invention improves the accuracy of efficiency prediction for port customs clearance operations and the elasticity of the recommendation strategy, effectively alleviating problems such as holiday congestion and uneven resource allocation.

The application provides a granularity optimization integration method and system of customs trade data, relates to the technical field of big data, and obtains the coordination system code, commodity price data and associated commodity transaction records associated with the customs declaration form in cross-border trade and user data processing requirements through the application; according to the coordination system code, the customs trade data set with the granularity mark is obtained, and the customs trade data set includes fine granularity data and coarse granularity data; using the distributed storage optimization technology, a layered storage architecture with granularity as the core is constructed to obtain a layered storage data set; using the edge node data transmission technology, the layered storage data set is transmitted to the cloud platform to form the associated customs trade data; according to the user data processing requirement, the optimized customs trade data is obtained, the efficient storage and on-demand dynamic adaptation of cross-border trade data are realized, and the flexibility and analysis efficiency of the customs trade data processing are improved.

This invention provides a method and system for cross-border electronic customs declaration inspection and early warning based on dynamic risk learning. The method includes: acquiring historical and real-time declaration data, whereby historical declaration data includes structured and semi-structured fields, and real-time declaration data includes status markers, declaration timestamps, and company numbers; extracting static features from the structured and semi-structured fields, and extracting dynamic features from the status markers, declaration timestamps, and company numbers; constructing a dual-channel deep forest model, and inputting the static and dynamic features into the model to obtain static and dynamic risk probabilities; obtaining the risk probability based on the static and dynamic risk probabilities, and executing corresponding strategies based on the risk probabilities. This invention, by comprehensively extracting static and dynamic features and constructing a dual-channel deep forest model for risk assessment, enables comprehensive and dynamic analysis of customs declaration data.

The invention relates to a risk control model method based on cross-border trade cargo declaration, and belongs to the technical field of cross-border trade risk control. The method comprises the following steps: acquiring real-time customs declaration and enterprise historical declaration, logistics and credit multi-source data, and generating a data unit through differential privacy desensitization and dynamic data quality evaluation processing; multi-layer risk control is realized through static rule screening containing a rule conflict intelligent resolution mechanism, AI risk control model group research and judgment and dynamic policy knowledge base comparison; generating a risk score and a report by adopting multi-modal decision fusion and risk attribution; after grading processing, an AI model is trained and optimized through risk increment based on golden labels, newly-added risk cases are clustered, the policy execution effect is evaluated, and closed-loop optimization is formed. According to the method, the data privacy security is guaranteed, the risk control dimension is expanded, the research and judgment accuracy is improved, the model and policy adaptation dynamic optimization is realized, and the cross-border trade compliance risk control efficiency is effectively improved.