600results about How to "Improve fairness" patented technology

The invention discloses a bid evaluation monitoring system and method based on a network platform, and aims to optimize a bid evaluation process through a plurality of advanced technologies. The system adopts a multi-factor identity verification and behavior biological recognition technology to ensure the identity safety of bid evaluation participants; simulating the performance of the bidding file in different situations by using a mixed reality situation simulator and a generative adversarial network technology; automatically auditing the bidding file through a natural language processing technology, and carrying out stylized analysis on design elements in combination with an art cognition algorithm; and dynamically optimizing an expert scoring process by using a fuzzy logic decision tree technology, identifying a scoring deviation and providing real-time feedback. The system also adopts an adaptive learning mechanism, continuously optimizes a scoring strategy, and improves the efficiency, transparency and compliance of the bid evaluation process.

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 relates to the field of carbon emission management, energy distribution and optimization regulation and control, in particular to an industrial enterprise carbon emission allocation method based on regional energy and carbon platform supervision data. The method comprises the following steps: step 1, data acquisition and preprocessing, including data acquisition, data preprocessing and data analysis; 2, initial carbon quota distribution, wherein a multi-level decision-making model is established, and the initial carbon quota of an enterprise is calculated; 3, a dynamic adjustment mechanism is provided, wherein the dynamic adjustment mechanism comprises the steps of obtaining power data feedback, calculating a quota adjustment coefficient and dynamically adjusting a quota; step 4, accumulation of double-control index data, including accumulation of the double-control index data and accumulation of carbon emission intensity data; and 5, continuously optimizing the model. According to the method, the flexibility of carbon quota distribution is improved, normal production of enterprises is ensured, meanwhile, the total carbon emission control target is not exceeded, and the overall efficiency of carbon emission management is improved by introducing a multi-level decision model and a feedback mechanism.

The invention discloses an intelligent recruitment system and method based on human-computer interaction and resume mining, and the method comprises the steps: giving a recruitment position demand by an HR, analyzing the position demand by a robot, and generating an HR demand label; the robot searches a resume on the network, analyzes the resume and extracts a corresponding resume label; resumes are screened in combination with HR demand labels, and the resumes are sorted; the entrusting robot and the job seeker of the resume chat online, verifying the authenticity of the label of the resume, and mining the temporary label of the job seeker; evaluating the importance of the temporary label, and constructing a job seeker evaluation model according to the HR demand label, the resume label and the temporary label; the robot recommends the job seekers meeting the HR requirements to the HR, and an evaluation report is generated based on a job seeker evaluation model; through resume screening, labeling processing, position knowledge graph construction and intelligent dialogue verification, the efficiency and accuracy of the recruitment process are improved.

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 discloses a multi-unmanned aerial vehicle track and power joint optimization method and device in an interference environment and a medium, and relates to the field of communication resource allocation, and the method comprises the steps: constructing a multi-unmanned aerial vehicle relay communication model in the interference environment; establishing a target function for balancing fairness and throughput by taking the hovering time of the unmanned aerial vehicle and the maximum distance of a path point as limitation, taking the path of the unmanned aerial vehicle, a ground user, a channel and power distribution as a joint optimization target and introducing a throughput ratio coefficient; and according to the objective function, adopting an optimization method combining a crown porcupine algorithm and a Kuhn-Munkres algorithm to obtain a joint optimization result of the track and the power of the unmanned aerial vehicle. According to the invention, the total communication throughput and the service fairness can be improved.

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 relates to the technical field of middle and long distance running evaluation, in particular to a middle and long distance running evaluation method and system based on human face body weight recognition, and the system comprises a data acquisition module, an algorithm host, a cloud server and a terminal module. A camera group and a pressure sensing pad in the data acquisition module respectively acquire images and pressure data; the algorithm host module processes data, identifies human face body features, tracks personnel, calculates scores and analyzes violation; the cloud server stores various data; and the terminal module is used for information input and result display. The evaluation method comprises the steps of data acquisition, identity recognition and tracking, score calculation, illegal behavior analysis, data integration and storage, exception handling and correction and the like. According to the invention, many problems of an existing RFID and AI face recognition evaluation mode are solved, for example, the RFID cannot perform biological feature recognition and violation judgment, and AI face recognition is interfered by the environment. Accurate identity recognition, whole-course tracking, accurate score calculation, comprehensive violation detection and efficient data management are realized.

The invention relates to the technical field of bidding document evaluation, and discloses an intelligent calibration method and device, computer equipment, a storage medium and a program product. The method comprises the steps of obtaining at least one to-be-calibrated bidding file and a preset bidding rule; screening the bidding files according to a preset bidding rule, and determining candidate bidding files; analyzing the candidate bidding file according to a preset review strategy to obtain a corresponding review result, the preset review strategy being predetermined based on the historical bidding data and the historical calibration data corresponding to the historical bidding data; and determining a calibrated target bidding file according to the review result. By implementing the technical scheme of the invention, automatic and accurate bidding document evaluation and calibration based on the preset rule and historical data can be realized.

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 technical field of operation training evaluation, in particular to a training quality evaluation method and system based on pilot attention distribution. The method comprises the following steps: collecting data required by pilot attention distribution training quality evaluation according to a specific flight mission scene; based on the collected data, calculating a standard attention distribution model of the pilot in a specific flight mission scene, and generating attention distribution and actual attention distribution of the standard attention distribution model; and comparing the attention distribution of the standard attention distribution model with the actual attention distribution, evaluating the training quality of the attention distribution of the pilot in the specific flight mission scene, and forming and displaying an evaluation result. According to the method, the attention distribution mode of the pilot is quantified, the eye movement tracking technology and task-related subjective and objective data are combined, the performance of the pilot in simulator training can be objectively and accurately evaluated, and the scientificity, fairness and safety of flight training are improved.

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 talent analysis and selection system based on AI auxiliary interview, relates to the technical field of talent analysis and selection, and solves the problems that in the prior art, evaluation on the honesty degree of an applicant is not considered, many applicants excessively describe the ability and personality of the applicant on a resume in order to embody the advantages of the applicant, even counterfeiting is caused, and the evaluation efficiency is poor. As a result, enterprises may find that candidates do not meet post requirements in the later period and have to perform recruitment procedures again, and loss of time and economic cost is caused. The method comprises the following steps: acquiring ability data on a resume of an applicant and interview data when the applicant interviews; processing the interview data to obtain interview text data; calculating cosine similarity between the interview text data and the capability data to obtain similarity data; calculating to obtain an integrity evaluation coefficient based on the similarity data; and judging whether the honesty degree of the applicant is qualified based on the honesty evaluation coefficient and a preset honesty threshold. The technical problem is solved.

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 discloses an online knowledge base platform for ensuring knowledge content quality and contributor rights and interests and a business model of the online knowledge base platform, and relates to the field of online knowledge bases. The platform integrates block chains, data encryption and artificial intelligence technologies, and aims to improve the quality of knowledge content and protect the rights and interests of contributors. The platform mainly comprises a block chain system, a data encryption system, an artificial intelligence system, a member management system, an auditor evaluation system, a knowledge content collection system, a knowledge content auditing system, an incentive management system, a template management system, a fund management system, a suggestion supervision system, a point transaction system, an advertisement management system and the like. Through a decentralized knowledge management mechanism, a contributor auditing and evaluating mechanism, a knowledge content providing and auditing mechanism and a contributor right protection mechanism, high quality of knowledge base content and fair reward of contributors are ensured, and sharing and communication of knowledge are promoted.

The invention provides an online examination cheating behavior detection method and system, and relates to the technical field of examination behavior detection, and the specific steps are as follows: collecting answer texts of examinees in real time, analyzing the answer texts of the examinees by using an NLP technology, and calculating the plagiarism probability of the answer texts by comparing the texts with data in a database; monitoring the network activity of the examinee, analyzing the network behavior mode of the examinee, and calculating the abnormal behavior mode index of the examinee; physiological data of examinees are collected, and psychological stress indexes of the examinees are calculated; calculating a comprehensive evaluation index by using weighted average, comparing the comprehensive evaluation index with an examination cheating threshold value, and judging that the behavior is cheating if the comprehensive evaluation index exceeds the threshold value; according to the invention, the behaviors of examinees are monitored in all directions, and a three-dimensional cheating detection system is provided; the artificial intelligence technology is applied, answer texts, network activities and psychological stress indexes are automatically analyzed, dependence on manual invigilation is reduced, and the monitoring efficiency and accuracy are improved; and cheating behaviors can be found in 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 relates to the technical field of virtual power plant differentiated contribution distribution and distributed carbon transaction under a multi-agent cooperation framework, and provides a differentiated multi-agent cooperative game-based virtual power plant low-carbon bargaining optimization method, and the method comprises the steps: constructing a multi-virtual power plant-load aggregator MVPP-LA cooperation alliance framework; a wind power system, a photovoltaic system, a combined heat and power generation system and an energy storage system are integrated, supply and demand interaction is enhanced, and a carbon emission quota distribution mechanism, a carbon transaction mechanism framework, a cooperative objective function and an energy system operation constraint condition based on energy interaction are constructed. Cooperative benefits are quantified through a Nash bargaining model, and a distributed adaptive iterative algorithm is adopted for solving, so that fair benefit distribution is realized, and carbon emission and transaction cost are reduced. The method plays a positive role in promoting the utilization of renewable energy sources, improving the utilization efficiency of energy sources and enhancing the flexibility and stability of the system.

The invention discloses a method for measuring the supply fairness of community old-age service facilities, and the method comprises the steps: obtaining the old-age service data of a community, carrying out the calculation and summation of the weights of four indexes, namely house type quality, activity space scale, environment greenness and service scale, and the normalized data, and obtaining an internal quality index; and evaluating the reachability score of the peripheral environment resource by adopting a Gaussian two-step mobile search method to obtain an old-age service supply index, and performing a superposition method on the internal quality index and the old-age service supply index to obtain a comprehensive score of the old-age service facility of each community. The Gini coefficient is used for calculating the comprehensive score accumulation proportion of the old people and the community old-age service facilities, the social environment space supply fairness is obtained, the community old-age service facility supply fairness is evaluated, the difference between communities is effectively reduced, and the community old-age service facilities are concerned and balanced.

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.

An intelligent standard sample examining and issuing device comprises a base station, and a face recognition module, a management system, a taking mechanism and a sample placing basket are arranged on the base station. The sample placing basket is used for placing a sample bottle, a two-dimensional code is pasted on the sample bottle, and the two-dimensional code comprises sample information of the sample. The face recognition module is used for recognizing identity information of the examined person. The taking mechanism is used for taking the sample bottle from the sample placing basket, and a sample identification module for identifying the two-dimensional code is arranged on the taking mechanism. And the management system is electrically connected with the face recognition module, the taking mechanism and the sample recognition module. Compared with the prior art, the utility model has the following beneficial effects: by integrating the face recognition technology, the mechanical arm operation and the advanced sample management information system, accurate distribution, effective tracking and intelligent management of examination samples are realized, and the efficiency and fairness of the sample examination process are obviously improved.

The invention discloses a face forgery detection method and system for reducing attribute prejudice. The method comprises the following steps: acquiring a video to be detected; preprocessing a to-be-detected video to obtain a to-be-detected image sequence; obtaining a pre-trained counterfeit detection model; inputting the to-be-detected image sequence into a pre-trained counterfeit detection model, extracting facial attribute features by using the attribute analysis model, and extracting facial texture features by using the texture analysis model; performing fusion processing on the facial attribute features and the facial texture features through a spatial-temporal feature aggregator to obtain a detection result; the detection result represents whether the face in the to-be-detected video is forged or not. Facial attribute features and facial texture features are extracted through an attribute analysis model and a texture analysis model, so that the method has higher resolution and robustness; facial attribute features and facial texture features are fused by using a spatial-temporal feature aggregator, so that prejudice is reduced while standard deviation between attributes is reduced, and accuracy, fairness and universality are improved.

The invention discloses an electronic digital signature system and method, particularly relates to the technical field of digital signatures, and comprises a digital signature extraction module, a signature verification module and a batch signature generation module. The method specifically comprises the following steps: S1, digital signature extraction; S2, signature verification; and S3, batch signature generation. According to the method, the review efficiency can be improved, the signature safety is ensured, the signature can be taken at any time, encryption and decryption integrated management is realized, the signature can be generated in batches, the accuracy is ensured, and meanwhile, the signature extraction accuracy is improved by adopting an advanced technology.