15 results about "Customs declaration" patented technology

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 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 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 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.

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.

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 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.

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 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.

The present application relates to a container weight abnormality detection device and method, and a computer program product, the device comprising: a weight abnormality detection module for determining whether or not there is an abnormality in a weight filled in customs declaration data input into the container weight abnormality detection device by invoking a historical library, and for determining whether or not there is an abnormality in the weight filled in customs declaration data input into the container weight abnormality detection device; the normal interval is obtained by inputting historical commodity data into a probability generation model; the declaration element detection module is used for performing named entity recognition on declaration elements in the customs declaration data to extract declaration element weight information, and comparing the declaration element weight information with the weight filled in the customs declaration so as to judge whether the weight in the declaration elements is abnormal or not; and the comprehensive output module is used for calculating and outputting a comprehensive result according to a detection result of the weight anomaly detection module and a detection result of the declaration factor detection module. According to the container weight anomaly detection device, weight anomaly detection can be conveniently and reliably carried out based on the information of the customs declaration.

The application relates to a pre-warning method for customs clearance compliance management based on big data analysis, which comprises a knowledge acquisition step, a feature matching step and a pre-warning analysis step; a knowledge graph is constructed through acquisition of regulation information and case information to generate key pre-warning items of customs for customs declaration, and when a certain declaration abnormal item corresponding to each pre-warning item appears, the relationship between the pre-warning item and the abnormal item is calculated to analyze the risk of each pre-warning item, so that the customs declaration personnel can be reminded to perform self-checking, verification or take remedial measures in advance.

The embodiment of the invention provides a customs declaration information auditing method, device and equipment and a storage medium, and the method comprises the steps: obtaining customs declaration information of goods, and generating prompt information according to the customs declaration information; retrieving the customs declaration information in a knowledge base to obtain retrieval information; integrating the prompt information and the retrieval information to obtain enhanced information; and generating an auditing result according to the enhanced information and the large model. According to the embodiment of the invention, the retrieval is performed in the knowledge base according to the customs declaration information, and the obtained retrieval information and the prompt information are integrated, so that the quality and accuracy of the input large model information can be improved, the data management capability and understanding capability of the large model are improved, and the user experience is improved. Therefore, the quality and the accuracy of the generated auditing result are higher.