266results about How to "Improve personalization" patented technology

The invention relates to the technical field of multimedia interaction, in particular to an intelligent interaction control method and system for digital exhibition hall multimedia equipment, and the method comprises the following steps: S1, carrying out the arrangement of a sensor, and carrying out the intelligent sensing and data collection; s2, generating an intelligent interaction strategy; s3, equipment cooperative control and execution; and S4, performing real-time feedback and system optimization. According to the method, user behaviors and environment data are collected in real time through the multi-modal sensor, user requirements are accurately speculated in combination with a deep learning algorithm, the optimal interaction strategy and task priority are generated, individuation and interaction efficiency of user experience are remarkably improved, multi-device cooperation is optimized through distributed task scheduling, and user experience is improved. According to the method, display content and environment parameters are dynamically adjusted, self-optimization of the system is realized by utilizing user feedback, real-time performance, smoothness and reliability of interactive experience of the exhibition hall are ensured, rapid fault response and accurate maintenance demand prediction are realized through anomaly detection and equipment log analysis, and the stability and sustainability of operation of the exhibition hall system are greatly improved.

The invention discloses a text-driven automatic image generation method and system, and belongs to the technical field of image generation, and the generation method comprises the following specific steps: I, receiving and analyzing text data input by a user, carrying out explicit modeling on entities and relationships in a text, and extracting implicit languages in the text data; according to the method, the multi-modal alignment of the text and the visual features is improved, the visual deviation problem caused by semantic information errors is avoided, the detail richness and semantic information expansion capability of the generated image are improved, the global layout reasonability of the generated image is improved, and the individuation and stylization capabilities of the generated image are enhanced; according to the method, a rigid effect caused by a fixed template is avoided, the performance of the generated image on scene complexity and detail richness is improved, the accuracy of relation modeling between objects in a complex scene is remarkably improved, the intelligent level of image generation is improved, and the generation process is more adaptive.

The invention discloses a driving skill training method constructed based on a diversified virtual examination room, and relates to the technical field of data processing, and the method comprises the steps: constructing a system based on the diversified virtual examination room, constructing a virtual examination room scene to carry out the driving training of a training user, outputting a driving behavior data set in real time, and carrying out the scoring, and analyzing the data according to the driving score, generating a personalized training path in combination with historical data when the driving score does not reach the standard, and training the user to carry out training step by step according to the training path until a preset skill scoring target is achieved. The technical problems that in the prior art, a traditional driving training method cannot dynamically adjust a training path to meet the actual skill requirements of trainees, consequently, training content lacks pertinence and is low in efficiency are solved, the individuation and pertinence of driving skill training are improved, it is ensured that the training content is highly matched with the actual skill requirements of the trainees, and the driving skill training efficiency is improved. And the training efficiency and effect are improved.

The invention discloses a chronic disease follow-up visit and management platform driven by a large model, and relates to the technical field of medical information technology platforms. The system is applied to managing and tracking the follow-up visit process of chronic disease patients and providing health consultation and answers, and comprises a user interface module, a logic control module, a database module, a large model module and an auxiliary function module, and the user interface module is used for providing an interactive interface between a patient and a doctor. An intelligent and efficient system platform is constructed by integrating a large model technology, a voice recognition technology and a digital human technology, the system platform adopts a privatized large model, data security and privacy protection are ensured, medical institutions are allowed to autonomously optimize and control the application of the model, and on the whole, through an advanced technical means, the intelligent and efficient system platform has the advantages of being high in practicability and easy to popularize. Refining, individuation and high efficiency of chronic disease management are remarkably improved, and the purpose is to improve the health outcome and life quality of patients.

The invention discloses an advertisement budget distribution method and system based on machine learning and user behaviors, and the method comprises the following steps: collecting the historical behavior data of a user, and extracting the feature data of the historical behavior data through feature engineering; constructing a user probability prediction model, and training the model by using the feature data; in an advertisement putting process, collecting real-time behavior data of a user, inputting the real-time behavior data into the trained model, and predicting an advertisement clicking probability of the user and an advertisement commodity purchasing probability of the user; a fusion model is constructed, the fusion model calculates the conversion rate of the user according to the advertisement clicking probability of the user and the advertisement commodity purchasing probability of the user, and calculates the channel conversion rate according to the putting channel; distributing a preliminary advertisement budget according to the historical data of the putting channel; and dynamically adjusting the preliminary advertisement budget of the putting channel based on the channel conversion rate. According to the invention, precise distribution of the advertisement budget can be realized, and the overall conversion effect of the advertisement is improved.

The invention discloses an intelligent rehabilitation treatment management system and method based on big data, and relates to the technical field of intelligent management. During operation of the system, rehabilitation-related data of an orthopedic patient is collected, real-time data is obtained through intelligent wearable equipment and a sensor, the pain and fatigue state of the patient is monitored, preprocessing is carried out, and the patient is subjected to rehabilitation treatment; the method comprises the following steps: analyzing collected data, monitoring the rehabilitation progress of a patient in real time, calculating to obtain a comprehensive rehabilitation progress evaluation index Etotal, comparing the comprehensive rehabilitation progress evaluation index Etotal with a preset state threshold value M and a second preset state threshold value N to generate a personalized rehabilitation scheme, and remotely monitoring rehabilitation data of the patient by a doctor so as to obtain a personalized rehabilitation scheme. According to the method, the rehabilitation plan and the training progress of a patient can be checked through a mobile phone APP, the rehabilitation plan, the training progress and real-time feedback are fed back, intelligent reminding is obtained, and through rehabilitation video or voice guidance, the patient can share experience, exchange rehabilitation experience and obtain psychological support and encouragement.

The invention relates to the technical field of medical information, in particular to a hospital pharmacy dispensing information intelligent processing method and system, and the method comprises the following steps: S1, obtaining the basic data of a medicine in real time; s2, acquiring medical record information, current medication conditions and physiological parameters of the patient from a hospital information system; s3, analyzing an existing drug combination, and detecting potential drug incompatibility; s4, a medication scheme of the patient is automatically generated; s5, pushing the medication scheme and the taboo information generated in the step S4 to work terminals of doctors and pharmacists, and providing medication suggestions at the same time; and S6, continuously monitoring the reaction of the patient, and when abnormity is monitored, performing drug adjustment through an adjustment algorithm. According to the system and the method, the medicine data is updated in real time, the patient information is integrated, and incompatibility identification and medication adjustment are carried out by utilizing an intelligent algorithm, so that the safety and the efficiency of hospital pharmaceutical dispensing are remarkably improved, and meanwhile, the individuation and the scientificity of a treatment scheme are optimized.

The invention relates to the technical field of energy efficiency optimization, and discloses a lamp energy efficiency optimization method based on artificial intelligence, and the method comprises the steps: data collection: carrying out the all-around and multi-dimensional data collection of an environment where a lamp is located through a plurality of sensors. According to the lamp energy efficiency optimization method based on artificial intelligence, in order to make energy utilization efficient, the multi-dimensional environment and lamp operation data are obtained through the data acquisition step, optimization is carried out in combination with the adaptive learning algorithm, lamp energy efficiency control parameters can be adjusted in real time according to different environments, places, time periods and other situations, and the energy efficiency optimization efficiency is improved. The lamp can be kept in the optimal energy efficiency state in various complex and changeable environments, the energy utilization efficiency of the lamp is effectively improved, energy waste is reduced, in the scene-based energy efficiency optimization link, for different application scenes, differentiation strategies are implemented according to respective typical lighting requirements and energy-saving potentials, parameters such as lamp brightness are accurately adjusted, and the energy efficiency of the lamp is improved. And the energy utilization efficiency of the lamp in various scenes is improved.

The invention relates to the technical field of television image communication, in particular to a user information input method and system in an intelligent television all-in-one machine. The method comprises the following steps: collecting a user image, carrying out white balance correction and focusing processing, generating a moving object focusing image, carrying out identification and attention tendency analysis on a character in the focusing image, obtaining character tendency data, analyzing a historical interaction image, identifying an interaction mode and constructing a user intention prediction model, and obtaining a user intention prediction result. And when the tendency data shows that the user preferences the television content, intention drilling and auxiliary adjustment are performed on the current image based on the prediction model, predicted user input information is generated, logic conflicts in the predicted information are detected, feedback optimization is performed, and final user input information is output. According to the invention, a more accurate and more flexible user information input method is realized.

The invention discloses an official document generation system and method based on a large model, belongs to the technical field of artificial intelligence, and aims to solve the technical problems of low official document format and content accuracy, poor material failure and poor content innovation in official document generation. Comprising a model training module used for performing model training on an official document generation model based on official document samples in an official document sample library; the model fine tuning module is used for performing layered fine tuning on the trained official document generation model; the cue word optimization module is used for carrying out cue word matching on user input based on a built-in cue word set; the outline generation module is used for calling a final official document generation model to generate an official document outline based on the cue word combination and user input; and the official document generation module is used for calling the final official document generation model to generate and output an official document body based on the user input and the final official document outline, and calling the privacy data shielding module to shield the privacy data in the official document body.

The invention discloses a patient rehabilitation monitoring method and system based on nursing data, and particularly relates to the technical field of rehabilitation monitoring. Core rehabilitation indexes are extracted by acquiring and classifying nursing data of a patient; analyzing the nursing data, identifying the current rehabilitation stage of the patient and evaluating the matching degree of the rehabilitation target and the core rehabilitation index; performing trend analysis on the time sequence of the nursing data, identifying abnormal data and evaluating the interference degree on the rehabilitation process; judging whether the rehabilitation progress of the patient meets the expectation or not according to the evaluation results of the matching degree and the interference degree; when the rehabilitation progress does not conform to the expectation, analyzing the demand change of the patient and evaluating the help effect of the nursing scheme; by comprehensively analyzing the matching degree, the interference degree and the nursing effect, the rehabilitation effect of the patient is evaluated, whether the nursing scheme needs to be adjusted or not is judged, individuation, accuracy and effectiveness of the nursing scheme are improved, the rehabilitation process of the patient can be accelerated, and the nursing quality is improved.

The invention discloses an intelligent hospital guide and tracking return visit recording integrated system for medical examination, which relates to the technical field of intelligent medical treatment, and comprises the following steps: based on a comprehensive data set, using an A-star algorithm to identify a hospital guide path; in the process that the patient waits for the hospital according to the hospital guide path, the system collects behavior data of the patient in real time; based on historical data, training a waiting time difference prediction model, inputting the patient behavior data into the waiting time difference prediction model, and predicting a waiting time deviation value; dynamically adjusting a hospital guide path according to the waiting time deviation value; and after the patient finishes visiting according to the adjusted hospital guide path, the system automatically provides health propaganda and education contents, collects patient feedback data and stores the patient feedback data in the tracking return visit system. Through the A-star algorithm and the waiting time prediction model, the system can perceive waiting delay in advance and adjust a path in time, the waiting time of a patient is remarkably shortened, and the doctor-seeing experience is improved.

The invention relates to a method and a system for realizing personalized recommendation based on multi-feature fusion face recognition, and aims to provide real-time, efficient and accurate recommendation service, the method comprises the following steps: collecting a face image of a target audience in real time through a camera device, and preprocessing the image to extract a face region; running a face recognition algorithm in the edge computing device, and extracting multi-modal features including age, gender, appearance and style features; a comprehensive feature vector is generated by using a Transform model through a feature fusion module, and style classification and appearance classification are realized; according to the method, user feature vectors and a content database are matched on the basis of cosine similarity, personalized recommendation content is generated, the weight of a classification model is dynamically optimized in combination with user feedback, and dynamic behaviors and appearance features of a user are accurately captured through a time sequence analysis module, a dynamic style analysis module and a deep appearance analysis module; and comprehensively generating user feature description by combining vision, voice and character multi-mode information.

The invention discloses a transcutaneous electrical stimulation device based on a large language model, and relates to the technical field of wearable devices. The transcutaneous electrical stimulation equipment based on the large language model comprises a data acquisition and preprocessing module, a feature extraction and fusion module, a model training and prediction module and a real-time information processing and response module, real-time data processing and intervention capabilities are integrated, human body data can be analyzed in real time, electrical stimulation parameters can be automatically adjusted, an instant treatment or adjustment scheme is provided for the problems of arrhythmia, chronic pain and the like, and the timeliness and effectiveness of treatment are greatly improved. And secondly, by fusing the physiological signal features and the symptom text features, the equipment can more comprehensively understand the health condition of the user, so that a more accurate treatment scheme is provided. Besides, the equipment also has the functions of anomaly detection and trend analysis, can predict potential health risks, and triggers an alarm in time when a serious anomaly is detected, thereby effectively guaranteeing the life safety of the user.

The invention relates to the technical field of federated learning, and discloses a discriminator knowledge distillation personalized federated learning method based on a conditional generative adversarial network. The problems of appearance of massive participants and influence of non-independent identical distribution of data on federal learning data cost and personalized learning efficiency are solved; a discriminator knowledge distillation model fused with the conditional generative adversarial network is put forward to be embedded into a personalized federated learning framework; the differentiated feature representation of the client model is enhanced through the discriminator knowledge distillation model, so that the personalized model effectively recognizes and captures specific modes and features of individuals, the representation capability and the personalized effect of the model are enhanced, the higher model compression rate is achieved, and meanwhile, the user experience is improved. The conditional generative adversarial network fused with the discriminator generates synthetic data specific to each client, and the synthetic data improves the generalization ability of personalized federal learning and the adaptability of the model on the premise of fully ensuring the data privacy.

The invention belongs to the technical field of medicine supply, and particularly relates to a personalized federal learning-based medicine purchase quantity prediction method, which realizes model data sharing on the basis of protecting the problem of user privacy disclosure. The drug purchase quantity prediction method comprises the following steps: S1, determining hospitals and drugstores participating in a region, and collecting and preprocessing data; s2, selecting and constructing a federal learning model, wherein the constructed model is a DCNN-LSTM hybrid model; s3, performing training, parameter cutting and transmission, aggregation and optimization on the model constructed in the step S2, wherein the data is not out of the local; s4, performing prediction and application on the optimization model obtained in the step S3; and S5, supply chain adjustment. According to the method, doctor-patient information leakage is prevented, information communication overhead is reduced, development of a medical intelligent system is promoted, and key support is provided for promoting sustainable development of the intelligent medical system and further development of the artificial intelligence industry by utilizing the federated learning technology and accurately predicting the drug demand quantity.

The invention provides an AI-driven multi-dimensional short video matrix analysis and management system, and relates to the technical field of information prediction.The AI-driven multi-dimensional short video matrix analysis and management system is characterized in that audience modal information when a short video is played is obtained by performing audience verification on a traffic feature set, and click attribute information when a short video user clicks the short video is determined according to the audience modal information; determining audience acceptability of the short video content according to the access like data, and determining a delivery matching coefficient during short video delivery according to the audience acceptability and the click attribute information; according to the behavior characteristic information, determining a perception monster degree when the short video user watches the playing of the short video; and performing trend analysis on the dynamic interest tag of the short video user according to the delivery matching coefficient and the user behavior sequence subjected to the correction constraint, so as to perform short video recommendation on the short video user. According to the method, the user experience and the platform activity degree can be improved under the influence that dynamic interests and complex preferences of the user are difficult to accurately capture from the recommended content.

The invention discloses a medical text data synthesis method based on role driving, and relates to the technical field of text data synthesis and artificial intelligence, and the method comprises the following steps: S100, generating an original problem; s200, screening original problems; and S300, synthesizing the medical text data. According to role description and interest content generation, the adaptability to different medical role requirements is enhanced, semantic duplicate removal and correlation evaluation are realized by utilizing a text coding model and a vector database, semantic duplicate content is removed, correlation is accurately evaluated by utilizing a large language model, the data quality and diversity are improved, and the method is suitable for popularization and application. Through generation of variant questions and answers, diversity and practicability of medical text data are enriched. According to the method, the personalization and pertinence of the medical text data are improved, the quality and duplicate removal efficiency of the medical text data are enhanced, the problem types are enriched, the generated content is optimized, and various information requirements of the medical text data are comprehensively covered.

The invention relates to a joint control lamp effect adaptation method and device, equipment and a medium. The method comprises the following steps: acquiring a target image of a planar lamp in a lamp effect joint control system according to the applied lamp effect; extracting a feature color set based on the target image, and determining a lamp effect color matching scheme applied by a non-planar lamp in a lamp effect joint control system according to the feature color set; based on a content description text generated according to the target image, determining a lamp effect motion mode applied by the non-planar lamp; and sending the lamp effect movement mode and the lamp effect color matching scheme to the non-planar lamp, so that the non-planar lamp plays the corresponding lamp effect by applying the lamp effect movement mode and the lamp effect color matching scheme. The lamp effect color matching scheme and the lamp effect movement mode of the non-planar lamp are determined based on the planar lamp according to the target image of the applied lamp effect, it is ensured that the lamp effects of different types of lamps in the lamp effect joint control system can be coordinated and consistent, and therefore the coordination and aesthetic feeling of the overall lighting effect are improved.

The invention discloses a policy information intelligent pushing system and method based on big data analysis, and relates to the technical field of policy information intelligent pushing. Comprising a data acquisition and preprocessing module, a dynamic keyword and semantic analysis module, a cross-domain information analysis and classification module, a user portrait and push strategy adjustment module and an intelligent push and feedback optimization module. According to the method, through multi-source data collection and NLP preprocessing, the data quality and availability are ensured; a keyword library and a semantic model are dynamically generated through deep learning, and accurate matching is achieved; policy information is intelligently analyzed and classified through a cross-domain information fusion technology, so that the correlation of pushed contents is ensured; the pushing strategy is dynamically adjusted in combination with the user portrait and real-time feedback, so that the system adapts to the interest change of the user, the pushing model is continuously optimized, the personalization and the accuracy of policy information pushing are remarkably improved, and the information obtaining efficiency and the decision-making ability of the user are improved.

The invention provides an automatic correction scoring method and system based on data driving, and relates to the field of electric digital data processing, and the method comprises the steps: obtaining to-be-corrected homework data and a corresponding question type; matching correction modes according to the question types, wherein the correction modes comprise a direct correction mode and a retrieval correction mode; if the mode is the direct correction mode, inputting the homework data into the trained direct correction model to obtain a correction result; if the mode is the retrieval correction mode, a preset number of student answers with the highest similarity and corresponding scores are retrieved from a database according to the homework data; and inputting the homework data, the student answer and the corresponding score into a scoring model to obtain a correction result. By implementing the method, the most suitable correction mode can be automatically matched according to the complexity of the question, the ability of evaluating the diversity and depth of answers is improved, and then the accuracy and efficiency of automatic correction are improved.

The invention relates to the technical field of man-machine interaction data, in particular to man-machine interaction equipment and a control method thereof. The method comprises the following steps: acquiring equipment screen operation data, performing time window segmentation, generating a discrete touch event sequence and a dynamic touch feature sequence, clustering and processing the features by utilizing interaction features, forming user operation behavior grouped data, and combining equipment historical interaction data to form a user operation behavior group. Frequent item set mining is carried out to identify a high-frequency operation mode, a user operation preference model is constructed, user operation habits are identified, redundant actions are eliminated, main interaction action data are extracted, interaction intention prediction is carried out on main interaction actions based on historical data of equipment, and dynamic response is carried out on the man-machine interaction equipment according to a prediction result. And effective control is realized. According to the invention, a more personalized and smoother man-machine interaction equipment control method is realized.

The invention provides a voice interaction method and device, electronic equipment and a computer storage medium, and the method comprises the steps: obtaining voice instruction information sent by a user; determining user feature information of the user according to the voice instruction information; determining intention information corresponding to the voice instruction information according to the voice instruction information; and determining feedback content corresponding to the voice instruction information based on the user feature information and the intention information. According to the embodiment provided by the scheme, the personalization and accuracy of voice interaction can be improved.

The invention relates to a digital human personalized emotion interaction method, which belongs to the technical field of emotion calculation, and comprises the following steps: S1, carrying out emotion quantification on interaction input of a user to obtain a pleasure-wake-dominate PAD emotion value in a continuous dimension space; s2, performing emotion state evaluation on the user interaction input emotion to obtain an interaction input emotion evaluation function; s3, calculating a digital human emotion transition probability matrix by using a Bayesian network; s4, calculating an emotional response calculation value of the digital human character corrected by the big five-factor model in the current emotional state; s5, the corrected emotion response passes through an emotion influence factor matrix, and a response with complex emotion features is output; and S6, performing PAD emotional space coordinate calibration on the emotional intensity of the digital person on the six basic emotions to obtain an emotional response of the digital person.

The invention discloses an online fire-fighting training simulation training system and a training method thereof. The system comprises a sensing module, a virtual environment module, an interaction and feedback module and a learning recording and suggestion module. According to the invention, multiple sensory experiences such as smell, temperature, wind feeling and the like are comprehensively introduced into fire-fighting simulation training, the limitation that a traditional VR / AR system purely depends on vision and hearing is broken, the sense of reality and immersion of training are greatly improved, and the coping ability of students in a real fire scene is effectively improved; the state of a trainee is analyzed in real time through an AI algorithm, a self-adaptive threshold intervention mechanism is combined, a virtual AI coach can provide dynamic and personalized guidance in different training scenes, and intelligent intervention based on real-time data greatly improves the fire-fighting training effect; the system not only pays attention to the short-term training effect of the student, but also makes a personalized continuous learning plan through the learning recording and suggestion module, and promotes the long-term progress of the student.

The invention discloses a coal mine production management knowledge question-answering method based on natural language processing, and the method comprises the following steps: S1, collecting environment data and user behavior data, and constructing a data set; s2, performing real-time processing on the data set; s3, constructing a user portrait by using a density-based spatial clustering algorithm; s4, constructing a knowledge graph, constructing a cognitive model by adopting a graph convolutional network and an improved Transform, and performing reasoning in combination with logistic regression and an XGBoost algorithm; s5, constructing an environment simulation model through historical data analysis; s6, generating a personalized natural language answer according to the user portrait, the knowledge graph and the environment state prediction; s7, collecting user feedback data, and adjusting model parameters and an optimization strategy by using an adaptive learning algorithm; and S8, storing the plan template by using a relational database, and continuously optimizing the plan template through historical data analysis. Natural language processing and deep learning are utilized, coal mine production management intelligent question answering is achieved, and the method has the advantages of being efficient and high in individuation.

The invention relates to the technical field of hollow microneedles, in particular to a preparation method of a hollow microneedle and a mold of the hollow microneedle. The female die and the limiting plate are clamped through the positioning device, the relative positions of the female die and the limiting plate are finely adjusted, then a guide wire is used for penetrating, the hollow microneedle manufacturing die is obtained, and the die can be used for casting hollow microneedles in one step. The mold can be repeatedly used, all procedures and materials are low in price and easy to obtain, and the manufacturing cost of the hollow microneedle is greatly reduced; by changing the shape of the recess in the female die, the hollow microneedles with different shapes and different sizes can be manufactured, and the preparation of the hollow microneedles with large length-diameter ratio can be realized; the hollow microneedles with different holes can be prepared by changing the size and the shape of the guide wire; by adding different microneedle preparation solutions, the platform can be suitable for producing hollow microneedles made of different materials; in conclusion, the preparation method of the hollow microneedle has the characteristics of low cost, universality and high individuation.

The invention provides a personalized medical-seeking path planning method and platform fused with data analysis, and relates to the technical field of medical-seeking path planning, and the method comprises the steps: collecting and obtaining a multi-platform medical data flow; obtaining a medical attribute index set, and carrying out attribute classification identification on the available multi-platform medical data flow; performing data fusion analysis according to the multi-platform data attribute information set; constructing a medical summary knowledge base, and performing feature clustering analysis on the medical summary knowledge base to obtain a general medical knowledge base and a personalized medical knowledge base; and performing medical treatment path planning analysis on the target medical treatment fusion feature to obtain target medical treatment path information, and performing personalized medical treatment management on the target user. According to the method and the device, the technical problem of poor medical path planning accuracy caused by non-uniform platform data and difficulty in information intercommunication in the prior art can be solved, and the medical path planning accuracy and personalization are improved by integrating the data of a plurality of medical platforms.

The invention discloses a brake disc manufacturing process, and relates to the technical field of brake disc manufacturing. The brake disc manufacturing process specifically comprises the following steps that S1, a casting is purchased, and machining operation is conducted on the casting, so that an initial disc is obtained; s2, carrying out first cladding operation on the disc surface of the initial disc; according to the manufacturing process of the brake disc, while color individuation of the brake disc is guaranteed, the color of a disc body of the brake disc is guaranteed by applying a laser cladding technology, and one or more special metal or nonmetal wear-resistant layers are formed on the surface of the brake disc, so that the wear resistance and the rust resistance of the brake disc are improved, the attractiveness is improved, and the attractiveness and individuation of the brake disc are improved; the automobile brake disc is subjected to surface treatment through laser coating, the metal coating is formed, coloring agent materials such as metal or metal compounds or ceramic are added while laser coating is conducted, color changing of multiple colors can be conducted on the brake disc, and the effect that the brake disc is not discolored after long-term operation can be kept.

The invention relates to the technical field of electronic signatures, in particular to an aviation equipment purchasing electronic seal generation method and system based on a block chain, and the method comprises the following steps: based on aviation equipment purchasing demand data, through a block chain network, matching the identity of merchant information in the data, including the recognition information of a purchaser and a salesperson, and generating a verification identity identifier; according to the method, the seal data is protected by applying asymmetric encryption, so that the personalization and specificity of the seal are enhanced, the security of the data in the transmission and storage process is ensured through encryption, the electronic seal data are published into the block chain network, a unique identifier is generated by utilizing a hash function, and the publishing state is tracked in real time; according to the method, the tampering resistance of data is guaranteed, the comprehensive auditing tracking capability is provided, technical support is provided for law and compliance review, the efficiency and transparency of a purchasing process are remarkably improved, fraudulent behaviors in a supply chain are reduced, meanwhile, the purchasing process is accelerated, and additional trust and value are provided for users and enterprises.