192results about How to "Improve fairness" patented technology

The invention provides a method and system for virtual power plant resource allocation optimization and computing equipment, and is applied to the technical field of new energy prediction. The method comprises the following steps: collecting data of a distributed energy production and elimination main body through a centralized control center; establishing prediction data by using the prediction model; forming an internal scheduling plan by using a master-slave game model so as to determine the output and income of each distributed energy production and elimination main body; the operation state of the distributed energy production and elimination main body is monitored in real time through a sensor, intelligent metering equipment and a communication network, and the internal scheduling plan is dynamically adjusted according to the operation state, so that the stability and economy of the system are ensured. By using the method and the system of the invention, flexibility and economy of internal and external resource allocation of the virtual power plant can be improved.

The invention relates to the technical field of data fusion, in particular to a multi-source data fusion law enforcement record generation system and method, and the system comprises a data collection module which normalizes and eliminates repeated data, an anomaly detection module which carries out the data verification and cleaning, and an information source evaluation module which carries out the quantitative scoring of a data source. And the weight adjustment module dynamically adjusts the weight based on the score, and the data fusion module executes weight fusion and field verification and outputs a collaborative law enforcement record. According to the method, the data quality is further ensured through the verification of the data value range and the calculation of the deviation value, and the reliability of the data set is enhanced by removing the abnormal data. And through quantitative scoring and dynamic weight adjustment, the quality evaluation of the data source and the fairness of input are ensured, so that the law enforcement record is more comprehensive and authoritative. The refined data processing not only improves the accuracy of law enforcement records, but also enhances the security and integrity of information, thereby significantly improving the response speed and decision quality of a law enforcement agency.

The invention discloses a task processing method and system applying robot process automation, and relates to the technical field of robot process automation, and the method comprises the steps: S1, carrying out the priority evaluation of tasks in a task queue based on a preset rule, S2, sorting the evaluation results to generate a priority task queue, s3, allocating execution resources to the tasks according to the priority task queues; S4, monitoring task execution states and dynamically adjusting the priorities of the task queues; according to the task processing method and system applying robot process automation, task scheduling requirements in complex and changeable business scenes are met, efficient operation of the system in a dynamic environment is ensured, key tasks are ensured to be completed on time, continuity and stability of a business process are improved, business risks are reduced, and the task processing efficiency is improved. The problem that how to regulate and control the priority of the task queue to solve the service influence caused by the fact that key tasks are preempted by low-priority tasks is solved.

The invention relates to the technical field of medicine information management, in particular to a traceability method and system based on a medicine consumable traceability code. The method comprises the following steps: acquiring medicine purchasing information data; generating a unique code for the number of medicine purchasing information so as to generate a medicine warehousing traceability code; performing drug information association on the drug purchase information data according to the drug warehousing traceability code to generate a drug warehousing associated traceability code; storing the medicine warehousing associated traceability code in an information base to generate a medicine warehousing traceability code information base; performing scanning access mode division on the medicine warehousing traceability code, and generating a medicine dispensing scanning request mode and a medicine returning scanning request mode; and performing drug splitting tracing on the drug warehousing tracing code in a drug dispensing scanning request mode to generate drug splitting tracing data. According to the invention, through full-process closed-loop management, data association enhancement, intelligent scheduling optimization and drug return tracing improvement, the efficiency and precision of the drug consumable traceability code tracing method are improved.

The invention discloses an intelligent bid evaluation method and system based on a large model, and a related product, relates to the technical field of purchase bid evaluation systems, and solves the problems that an existing intelligent bid evaluation system is difficult to understand a complex logical relationship and semantic connotation and cannot provide a comprehensive and accurate scoring result. According to the technical scheme, the method comprises the steps that S1, bidding and tendering files are obtained; s2, performing disassembly processing based on the bidding and tendering file to obtain a plurality of bidding and tendering data pairs; s3, performing instruction construction on the bidding and tendering data pair based on a historical bidding and tendering database to obtain a prompt instruction of the bidding and tendering data pair; s4, processing the prompt instruction of the bidding and tendering data pair based on the large model after training and fine tuning to obtain the score of the bidding and tendering data pair, and accumulating the scores to obtain the score of the bidding file; through the method based on the large model, the scoring effect is effectively improved in the intelligent bid evaluation work, the efficiency is improved, manpower and material resources are saved, and meanwhile interference caused by human factors is avoided.

The invention discloses a multi-mechanism attribute-based encryption algorithm based on creditworthiness consensus and zero-knowledge proof, and relates to the field of blockchains. On the basis of traditional attribute-based encryption, creditworthiness evaluation is introduced, a decentralized trust model is established for evaluating and selecting trusted nodes, and the reliability of the algorithm is improved. According to the method and the system, the data can be shared and accessed in a credible environment, zero-knowledge proof is used for verifying the correctness and integrity of the data, specific data values or other sensitive information are not leaked, and the reliability of the data is improved by combining credibility consensus and the zero-knowledge proof technology. And an innovative and efficient solution is provided for data security sharing in a multi-mechanism environment.

The invention discloses an equipment scheduling method and system based on dynamic priority and multi-objective optimization, and the method takes the minimization of a waiting time mean square error, the minimization of total waiting time and the minimization of maximum completion time as optimization objectives. A task dependency relationship, an equipment maintenance time window, a time window constraint, a student learning progress priority and a delay compensation mechanism constraint condition are comprehensively considered, a dynamic priority calculation mechanism is introduced, the priority is dynamically adjusted in real time according to task waiting time, deadline and urgency, and a high-quality initial population is generated through CMA-ES; a non-dominated sorting framework optimized by NSGA-II is combined, crossover variation of a traditional genetic algorithm is replaced by PSO updating, and an optimal solution is searched by using an elitism mechanism. The method can effectively improve the utilization rate of equipment resources, reduce the task completion time and optimize the fairness of task allocation, is suitable for equipment sharing and dynamic scheduling scenes, and has high practicability and popularization value.

The invention relates to the technical field of data management methods, in particular to a bid inviting data management method and system based on a block chain. According to the technical scheme, the system comprises a data storage module, a network communication module, an intelligent contract module, a user interface module and a data backup and recovery module. Through a block chain distributed account book technology and an asymmetric encryption algorithm, data integrity, authenticity, confidentiality and security are improved, and data are prevented from being stolen or tampered; the bid invitation data management system based on the block chain enables the bid invitation data to be traced by authorized parties, and the transparency and fairness of the bid invitation process are improved; meanwhile, automatic execution of a bid invitation process is realized through an intelligent contract, efficiency and fairness are improved, transaction cost and risk are reduced, transparency and credibility of the bid invitation process are enhanced, and availability and integrity of bid invitation data and stable operation of a block chain network are ensured and Byzantine node risk is resisted based on a P2P network architecture and a PBFT algorithm.

The invention belongs to the technical field of digital bid evaluation, and provides an intelligent bid evaluation method and system based on a knowledge enhancement large language model.The method comprises the steps that firstly, a to-be-evaluated file library of project bid inviting and tendering files is established; then, files in the to-be-reviewed file library are analyzed, file slices are generated, and a reviewed file knowledge base is formed; then, text slices in the file knowledge base are retrieved and reviewed through key fields, and input cue words of the knowledge enhancement large language model are generated in combination with the key fields and the file slices; then, interacting the input cue word with a pre-trained knowledge enhancement large language model to obtain all key field information; then, scoring the bidding file according to a preset bid evaluation algorithm for all the obtained key field information; and finally, sorting the scores of all the bidding files in a descending order to generate an intelligent bid evaluation report. According to the method, the application of the knowledge-enhanced large language model in the aspects of bidding and tendering key information extraction and intelligent bid evaluation is realized, the flexibility and adaptability are relatively high, the influence of human factors on bid evaluation work is reduced, and the fairness and justice of the bid evaluation process and result are actively promoted.

The invention relates to the field of industrial automation and intelligent logistics, and discloses a vision-based operation management system, which comprises a visual perception module, a traffic modeling module, a path optimization module, a scheduling optimization module and a feedback adjustment module, the visual perception module obtains image or video data in the operation area and extracts the dynamic state of the target equipment; the traffic modeling module constructs a dynamic weighted graph model based on the equipment state data; the path optimization module generates an optimal path of the equipment by solving a dynamic Hamiltonian path problem; the scheduling optimization module optimizes the passing sequence and speed of the equipment based on a game theory model; and the feedback adjustment module monitors the running state of the equipment in real time, detects abnormal conditions and dynamically adjusts modeling and optimization results. The method can effectively solve the problems of path conflict and traffic jam in multi-device collaborative operation, improves the operation efficiency and the resource utilization rate, has high real-time performance and adaptability, and is suitable for various scenes such as logistics storage, industrial production and intelligent transportation.

The invention discloses a tumor postoperative treatment staged planning method based on artificial intelligence. The method comprises the following steps: S1, constructing a multi-modal medical data set; s2, performing standardization processing on the acquired multi-modal medical data set to form a standardized data set which can be used for feature extraction; s3, generating a unified patient feature vector; s4, according to the characteristics of tumor postoperative treatment, dividing the whole treatment process into a postoperative immediate recovery stage, a postoperative recovery middle stage and a long-term follow-up visit stage, and defining a corresponding optimization target for each stage; s5, based on the patient feature vector and the optimization target of each stage, generating an initial treatment plan by using a deep ant colony algorithm; and S6, outputting a staged treatment scheme. According to the method, the professional and technical thresholds required by traditional modeling are reduced, and the universality and convenience of three-dimensional modeling are improved.

The present application discloses a graph database load balancing method and device based on request type, which relates to the field of graph database query technology, and solves the problem in the prior art that several complex queries with long time consumption and heavy load may all fall on the same query service, causing the query service to be under great pressure and slow response, because only focusing on the resource utilization of the server and ignoring the characteristics of the query request itself. The method includes: constructing a mapping table, and according to the complexity of the query request, independently polling and routing the requests for complex queries according to the type, and independently polling and routing the requests for non-complex queries. Since the complex queries are routed to different query services, the effective dispersion of complex query requests of the same type is achieved, and the pressure on each query service to process data is balanced and small, thereby effectively improving the overall query efficiency and reducing the query time.

The invention belongs to the technical field of cosmetics, and particularly relates to a skin-color-uniformizing whitening composition derived from plant extracts and application of the skin-color-uniformizing whitening composition. The whitening composition provided by the invention is prepared from the following components in parts by weight: 10 to 15 parts of saussurea involucrata extract, 1 to 8 parts of dendrobium officinale extract, 1 to 5 parts of wood apple extract and 0.5 to 5 parts of banana fruit extract. The four plant extracts are synergistically compounded, transdermal absorption of active ingredients can be promoted, the tyrosinase inhibition rate is effectively increased, and the skin glossiness and whiteness are improved, so that the effects of whitening, brightening and uniformizing the skin color are achieved, the whitening composition is mild and non-irritant, the preparation method is simple and convenient to operate, and the whitening composition has large-scale production capacity and industrial feasibility. When the whitening composition is applied to skin care products such as face cream, the whitening and brightening effects of the face cream can be effectively improved, and the whitening composition has wide market application value.

The invention provides a cross-micro-grid power transaction method based on cross-chain of a block chain, and comprises a cross-micro-grid power transaction method based on a cross-chain technology of the block chain. Comprising the steps of transaction demand and quotation submission, cross-chain information synchronization and summarization, expected transaction set generation, transaction matching calculation, transaction result verification, smart contract transaction execution, reputation index adjustment and unmatched transaction processing. The micro-grids share power supply or demand and quotation information through the cross-chain technology, and the relay chain technology broadcasts information to ensure information synchronization. The micro-grids form an expected transaction set, and transaction matching is calculated and synchronized through a cross-chain technology. And after verification succeeds, the smart contract automatically executes a transaction and records a result, the reputation index is updated, and unmatched transactions can be transacted with the public power grid. According to the invention, the transaction efficiency and reliability can be improved, the reputation index is dynamically adjusted, a multi-dimensional evaluation system is adopted, and the fairness and environmental friendliness of the transaction are enhanced.

The invention belongs to the technical field of server cluster load balancing, and discloses a server cluster load balancing method based on edge computing, which comprises the following steps: acquiring task data, transmission data between nodes and load data of server nodes; constructing a load topological graph based on the load data and the transmission data, and performing multi-dimensional aggregation on the load data based on the load topological graph to obtain node state description; performing priority evaluation on the task data by adopting an analysis algorithm to obtain a task score; performing task optimal matching on node state description based on task scores to obtain an optimal allocation scheme, predicting the optimal allocation scheme based on the constructed load prediction model to obtain overload allocation, and performing local task migration on the overload allocation to obtain a local optimization scheme; and the overall processing capability of the server cluster is greatly improved.

The invention provides a charging pile interface distribution method, device and system and computing equipment. The method comprises the steps that charging pile information and a reservation request are acquired, and the reservation request comprises vehicle identification information, charging position information, charging time period information and user bidding information; and based on the charging pile information and the predetermined request, obtaining a distribution result of the charging pile interface by adopting a Veckrii-Clark-Groffs auction algorithm. According to the method, the VCG auction algorithm is applied to the distribution process of the charging pile interfaces, so that the owner of the new energy automobile is promoted to really bid, the possibility that the owner of the new energy automobile carries out strategic manipulation or bid is too high is reduced, and the efficiency and fairness of the charging pile reservation process are improved; moreover, the social welfare is improved to the greatest extent, and the motivation of the charging pile owner participating in the shared charging plan is increased.

The invention discloses a shadowboxing action coordination evaluation method and device based on gravity center height detection, equipment and a medium, and the method comprises the following steps: obtaining a shadowboxing action video, and recognizing the three-dimensional coordinates of human joints; based on the three-dimensional coordinates, identifying the motion style of the shadowboxing; calculating gravity center data corresponding to each action style based on the three-dimensional coordinates; the gravity center data comprises a human body gravity center point and a human body gravity center height difference; and performing coordination scoring according to the constructed standard data and the gravity center data of the shadowboxing action video. According to the method, subjective errors in manual scoring are effectively reduced, the scientificity and fairness of action scoring are improved, meanwhile, a practicer is helped to find and improve unstable points in actions, and the practice effect is improved.

The invention relates to the technical field of talent assessment, and discloses a multi-dimensional talent assessment method and system based on an artificial intelligence technology, and the method comprises the following steps: S101, collecting resume text data and interview video data of a to-be-tested person; step S102, preprocessing the resume text data and the interview video data to respectively obtain a first feature sequence and a second feature sequence; s103, a scoring model is constructed according to the first feature sequence and the second feature sequence, the input of the scoring model is the first feature sequence and the second feature sequence, and the output of the scoring model is the score of the person to be tested; and step S104, training and optimizing the scoring model. According to the method, the multi-modal data is fused, the resume text data and the interview video data are combined, the multi-dimensional features of the to-be-tested person are extracted, and the scoring model is constructed to output the score of the to-be-tested person, so that the subjectivity in the evaluation process is reduced, and objective and standardized scores are provided.

The invention discloses a garbage classification recycling excitation method and system. The weight, classification accuracy, classification participation frequency and variety diversity of garbage are comprehensively considered. The weight of the garbage is the most direct influence factor, the classification accuracy of the garbage reflects the accuracy degree of garbage classification of the user, the classification participation frequency of the garbage reflects the enthusiasm and continuity of the user participating in garbage classification, and the variety diversity of the garbage reflects the recognition and treatment capacity of the user on different types of garbage. The four factors jointly influence an integral calculation value in garbage classification and recovery excitation, so that the accuracy and the fairness of integral calculation are improved, garbage classification behaviors of the user can be comprehensively evaluated, and the user is excited to more actively participate in garbage classification and recovery activities.

The invention relates to the technical field of AI large models, in particular to a large model resume screening system and method for the human industry, and the system consists of a working post analysis module, a candidate resume analysis module, a matching degree analysis module and a personal information module. The working post analysis module is used for deeply analyzing and extracting key requirements of working posts; the candidate resume analysis module is used for comprehensively analyzing the uploaded candidate resumes and extracting key information; the matching degree analysis module is used for carrying out accurate matching degree analysis in combination with working post requirements and candidate information and giving a comprehensive ranking; the personal information module is used for the user to manage personal information and account setting; the large model resume screening system and method for the human industry have the beneficial effects that efficient screening and processing of a large number of resumes are achieved through an automation technology, so that the working pressure of a human resource department is remarkably reduced, and the screening efficiency is greatly improved.

The invention discloses an enterprise operation management system based on big data analysis, which belongs to the technical field of operation management systems and comprises a plurality of merchant systems, a plurality of user systems and an enterprise operation management system. The enterprise operation management system is in communication connection with the user system and the merchant system; each merchant system corresponds to one merchant, and each user system corresponds to one user; the merchant system runs on the enterprise operation management system and is used for providing online commodity ordering service for users and performing data statistics and viewing by merchants; and the user system is used for filling in user information and enabling a user to access the merchant system on the enterprise operation management system to place an order of a commodity. Through the mode, the propaganda and sales profit distribution for the commercial tenants is regulated and controlled based on the contribution condition of the commercial tenants to the platform.

The invention discloses a data analysis decision-making system based on artificial intelligence, and relates to the technical field of administrative management. In data preprocessing, a resampling technology is used for processing dominant prejudice, so that data of different groups are more balanced in sample quantity, a model is prevented from excessively inclining a specific group, a multi-objective optimization algorithm is introduced, and the data analysis decision-making efficiency is improved. An accuracy loss function of the model is combined with a plurality of fairness loss functions, the weight is dynamically adjusted through a gradient descent method, fairness and accuracy can be optimized at the same time in the training process, an automatic responsibility asking mechanism is introduced, a responsibility allocation matrix is defined, responsibility boundaries of data providers, developers and operators are clearly divided, and the training efficiency is improved. And a log and a tracking system are established to record each decision path, responsibility can be automatically backtracked when an error occurs, and responsibility investigation is carried out according to the responsibility proportion of participants.

The invention is suitable for the technical field of data identification, and provides an automatic evaluation method and system for enterprise bidding and tendering data, and the method comprises the steps: extracting text data in the enterprise bidding and tendering data; obtaining a keyword corresponding to each evaluation item, and matching a text position corresponding to the keyword in the text data; determining whether the text position is a text region corresponding to the evaluation item or not according to a context relationship of keywords in the text position; if it is determined that the text position is the text area corresponding to the evaluation item, item information located behind the keyword is extracted; and according to a preset scoring strategy corresponding to the evaluation item, scoring the item information to obtain a total score corresponding to the enterprise bidding and tendering data. According to the scheme, the accuracy and the reliability of the bid evaluation result are improved, and the efficiency and the fairness of bid evaluation work are also remarkably improved.

The invention relates to a three-camera linkage and intelligent evaluation eight-brocade intelligent scoring system based on machine learning and a sum-product method. In an eight-section brocade scoring scene, a traditional subjective scoring mode has many defects. In order to solve the problems, an intelligent scoring system is constructed. The system comprises a video data acquisition module, a posture recognition module, an intelligent scoring module, a score integration module and the like. The video data acquisition module acquires multi-angle videos through three high-definition cameras; the posture recognition module accurately recognizes actions by using an advanced algorithm and a deep neural network technology; the intelligent scoring module designs a multi-dimensional index, and scores based on a sum-product algorithm; and the score integration module gathers scores from different perspectives to obtain a comprehensive score. According to the method, various measures are adopted to overcome the limitation of the existing AI technology in sports detection, including environment optimization and action detail identification, construction of a diversity and balance data set, research of cross-group adaptability, establishment of a man-machine cooperation trust relationship and the like. The system improves objectivity, accuracy and fairness of eight-segment brocade scoring, and is of great significance to eight-segment brocade teaching and competition. Meanwhile, a new technical means is provided for the fields of physical education and detection, the application range of the artificial intelligence technology in the field of physical education is expanded, and fusion innovation of the AI technology and the traditional field is promoted.

The invention relates to the technical field of reinforcement learning, in particular to a deep reinforcement learning method and system based on multiple agents. The method comprises the following steps of performing operation log extraction on multiple agents and constructing a multi-agent interaction graph to obtain the multi-agent interaction graph; carrying out resource release limited interval calculation among different load nodes on the multi-agent interaction map to obtain a node resource release limited interval; according to the node resource release limited interval, making a multi-agent resource competition strategy and carrying out multi-agent hierarchical convergence behavior coupling to obtain hierarchical convergence behavior coupling data; and constructing a multi-agent resource competition balance model according to the layered convergence behavior coupling data to obtain the multi-agent resource competition balance model, and sending the multi-agent resource competition balance model to a cloud platform to execute multi-agent deep reinforcement learning. According to the method, multi-agent collaboration is more perfect through optimization processing of multi-agent reinforcement learning.

The invention discloses an urban waterlogging resident emergency evacuation path guiding method for a smart community, and relates to the technical field of smart cities and emergency management. The method comprises the following steps: firstly, constructing a community digital twinborn base fusing geographic information, building information, Internet of Things sensing data and a hydrodynamic model; dynamic inversion and prediction of the waterlogging situation are realized by assimilating a multi-source observation data driving model; calculating the space-time dynamic risk of the evacuation road network based on the prediction result, and generating a risk map; calculating a space-time evacuation scheme including optimal departure time and a specific path sequence for residents or families by combining resident personalized constraints and adopting a double-layer optimization model combining macroscopic flow distribution and microscopic path planning; finally, instructions are issued through multiple channels such as an intelligent terminal and broadcast, and dynamic adjustment is performed based on real-time monitoring, so that accurate perception, prospective prediction, personalized planning and collaborative guidance of waterlogging evacuation are realized, and the overall efficiency of community emergency evacuation is effectively improved.

The invention discloses a bidding and tendering file generation method and system, and the method specifically comprises the following steps: S1, bidding file analysis: carrying out the structural analysis of a bidding file, and extracting key information; s2, a template selection and calling step: selecting a proper bidding file template according to the type of the bidding file and the item category; the invention relates to the technical field of data processing. According to the bidding and tendering file generation method and system, the bidding file is subjected to structured analysis in an automatic mode, and the tendering file meeting the requirement is quickly generated. Therefore, the time and the labor cost for manually compiling the bidding document are greatly reduced, an enterprise can respond to the bidding demand more quickly, the possibility of human errors is reduced due to automatic generation, and the accuracy and the consistency of the document are improved.

The invention relates to an object resource allocation information determination method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring a resource allocation range, resource allocation time and information of each resource allocation object corresponding to a resource allocation task; determining a resource allocation index parameter corresponding to the resource allocation task according to the resource allocation range, the resource allocation time and the information of each resource allocation object; constructing a resource allocation processing model corresponding to the resource allocation task according to the resource allocation index parameter and the resource allocation task; and inputting the resource allocation basic information corresponding to each piece of resource allocation object information into a resource allocation processing model to obtain object resource allocation information corresponding to each piece of resource allocation object information. By adopting the method, the resource allocation accuracy can be improved.

The invention relates to a cost accounting system based on SKU asset management, which is applied to the technical field of asset management, and comprises the steps of: by constructing an SKU-based asset price management system, realizing classified management of assets, SKU attribute definition, asset price calculation and dynamic updating, supporting a multi-dimensional pricing strategy, and being capable of adapting to a scene of dynamic change of resources; meanwhile, in the cost accounting process, different apportionment modes can be adopted for apportionment according to user requirements instead of a simple average apportionment mode, and the accounting fairness and flexibility are improved; the unit price of the fixed assets is automatically calculated through the product module and is applied to the accounting process in real time, and the real-time performance and precision of the accounting result are improved.

The invention relates to the technical field of power system carbon emission analysis, and discloses a carbon flow closed-loop traceability and allocation method, system, equipment and medium considering network loss, which comprises the following steps: analyzing network loss components contributed by each load, and establishing quantitative correlation between load power consumption behaviors and network loss power; and then, constructing an equivalent lossless network, reasonably allocating the carbon emission corresponding to the network loss to a load side, and introducing a renewable energy carbon reduction load mechanism to quantify the carbon emission reduction benefit of the renewable energy. The method aims to improve the accuracy and rationality of carbon flow allocation in the whole link, and provides reliable support for low-carbon scheduling and carbon market mechanism design of a power system.