203 results about "Scoring system" patented technology

A computing system for adaptive electronic message classification employs a multi-agent architecture comprising a media feature analysis system, a user context refinement system, and a response synthesis system. The media feature analysis system generates pillar scores including message type, intent, and link risk scores with associated confidence values using trained classification models. When pillar scores and confidence values do not satisfy predetermined threshold conditions, the user context refinement system dynamically constructs contextual prompts using the pillar scores and confidence values as input parameters. User responses generate score modification data that refines the pillar scores and contextual response data for recommendation generation. The response synthesis system generates refined classifications and personalized recommendations using the refined pillar scores and contextual response data. An orchestration system coordinates agent interactions using learned uncertainty points and implements asymmetric influence algorithms with variable weighting based on content and URL analysis concordance.

In some embodiments, a configured artificial intelligence system includes a plurality of intelligence models; a scoring system configured to generate know-your-model scores that quantify suitability for specific tasks of each model; a model execution system configured to provide standardized execution environment for the plurality of intelligence models; a training and reinforcement system configured to monitor outcomes relating to decisions or predictions made by the plurality of intelligence models and use outcome data as feedback to reinforce model performance; and a governance and analysis system configured to ensure model operations comply with governance standards. The intelligence controller may be configured to receive task requests, analyze task complexity, decompose tasks into manageable subtasks, and dynamically select appropriate models from the plurality of intelligence models to execute each subtask based on model suitability and performance characteristics.

The invention relates to an intelligent interview scoring system capable of explaining decisions based on a large language model, and the system comprises a multi-mode resume analysis and feature coding unit, a resume feature adaptive matching unit, an interactive scoring and knowledge enhancement unit, and an answer quality evaluation unit. Text, image and audio features are extracted through a cross-modal attention mechanism of a multi-modal large language model, resume features are encoded into dynamic word vectors, and entity-level feature vectors are extracted; the post description text is encoded into a demand feature vector by a resume feature adaptive matching unit; calculating semantic similarity between the resume entity feature vector and the demand feature vector; the interactive scoring and knowledge enhancement unit dynamically retrieves knowledge fragments to generate a preliminary evaluation report containing a scoring basis; and the answer quality evaluation unit fuses the information density, the fluency and the integrating degree to generate a final score. And the whole-process intelligence from demand analysis to final decision making is realized.

The invention relates to the technical field of voice processing, can be applied to business scenes such as financial science and technology and medical health, and discloses a multi-speaker dialogue voice analysis method, device and equipment and a medium, and the method comprises the steps: obtaining a to-be-analyzed multi-speaker dialogue voice, determining a naturalness score based on an acoustic feature, and obtaining a multi-speaker dialogue voice analysis result; determining a semantic consistency score based on voice embedding and semantic embedding corresponding to a preset text, determining a speaker consistency score based on embedding of a plurality of speakers of the same speaker, determining an interaction rationality score based on voice alternate overlapping duration, determining a diversity score based on a variance of voice features, and fusing the scores, the comprehensive mass fraction is obtained. According to the invention, through quantitative evaluation of five dimensions of naturalness, semantic consistency, speaker consistency, interaction rationality and diversity, a comprehensive quality scoring system is established, so that the evaluation result simultaneously reflects voice fluency, content matching degree, identity stability, interaction rhythm rationality and feature richness.

The invention relates to the technical field of financial risk control, and discloses a telecommunication fraud risk identification method based on a bank card transfer scene. The method comprises the following steps: a basic feature construction stage: acquiring multi-source data of historical victim users, extracting multi-dimensional features, and processing the multi-source data into standardized time sequence data through feature coding and a DTW algorithm; in the multi-modal fusion and adversarial learning stage, a core layer containing a multi-modal analysis engine, a risk reasoning model and an adversarial generation model is constructed, and multi-modal feature fusion, risk probability output under an RLHF framework and simulated fraud feature generation driven by WGAN-GP are achieved; in the strategy output stage, risk scores are mapped through a double-layer scoring system, and three-level interception is triggered; in the model management stage, model iteration is achieved by means of a monitoring instrument panel and a rolling time window, the online effect is guaranteed by combining gray release and A / B testing, the telecommunication fraud in the transfer scene can be accurately recognized, and the risk control efficiency is improved.

The invention provides a contaminated site remediation technology scoring system which comprises a multi-dimensional evaluation index system construction module, a situational weight dynamic adjustment module, a remediation technology applicability scoring module, an uncertainty analysis and sensitivity test module, a scoring result visualization module, a technical scheme sorting and screening unit and the like. Through four innovations of a dynamic weight adaptation mechanism, a multi-model fusion scoring algorithm, a technology combination scheme evaluation module and uncertainty robust analysis, the problems of single dimension, weight solidification, difficulty in quantification of a synergistic effect and the like in pollution remediation technology evaluation are systematically solved; and an objective, efficient and transparent intelligent decision-making tool is provided for repairing a complex polluted site.

The invention discloses a multi-source heterogeneous data flow real-time fusion and weight adaptive correction system and method, and relates to the technical field of multi-source data fusion. Comprising a path monitoring data extraction module, an initial fusion weight determination module, an abnormal transportation event analysis module, an initial correction strategy table generation module, a response updating module and a real-time weight adjustment fusion module. According to the method, a multi-dimensional data quality scoring system is established, so that strong association between weight distribution and data quality is ensured, and fusion precision loss caused by'fixed weight 'is avoided. For an abnormal monitoring point, through indexes such as a data missing rate, a deviation change rate, an auxiliary positioning deviation rate and the like, an abnormal data source type is accurately identified, a weight adjustment scheme of'target data source decreasing amplitude + increasing amplitude data source equal proportion complementation 'is formulated until abnormity is eliminated, and closed-loop correction of'abnormity positioning-weight adjustment-error elimination' is realized.

The invention relates to the technical field of image processing, and discloses a paper ruler regulation drawing operation image batch processing and cloud collaborative scoring system, which comprises the following steps: acquiring operation images of a paper ruler regulation drawing through a multi-source image, carrying out resolution adaptation and intelligent edge detection, carrying out perspective correction and standardization processing, and carrying out cloud collaborative scoring on the operation images of the paper ruler regulation drawing; reconstructing a brightness component of the operation image and carrying out vectorization processing; constructing a geometric constraint network of the job image to perform complex topological relation automatic constraint verification, after verification is finished, constructing a symbol data set, detecting and classifying symbol data, and performing multi-scale detection on symbol feature values obtained through calculation; constructing a directed acyclic graph, accelerating a key operator by using CUDA, constructing a mapping specification knowledge graph, dynamically adjusting a scoring weight, establishing a dynamic scoring mechanism, and calculating to obtain a processing score; and establishing a distributed storage architecture, analyzing and calculating a final score, and generating personalized improvement suggestions and teaching resource recommendations through error pattern mining.

The invention discloses a performance scoring system and method for emergency response of a chemical park, and relates to the field of scoring of emergency response of chemical parks. Comprising an intelligent perception and risk early warning module, an intelligent decision and command scheduling module, an emergency execution and on-site disposal module, a resource management and logistics guarantee module, an evaluation optimization and continuous improvement module and an innovative technology application module. According to the performance scoring system and method for the emergency response of the chemical park, a mutually coordinated organic whole is formed from perception early warning, decision scheduling, field disposal, resource guarantee and continuous optimization to technical enabling, the assessment optimization and continuous improvement module continuously improves the emergency response capability through closed-loop management, and the performance scoring efficiency is improved. And continuous iteration from experience to capability is realized. The post-event analysis sub-module automatically collects data such as early warning response time, resource allocation efficiency and evacuation completion time after the emergency ends, and identifies weak links through data mining.

A Large Language Model (LLM) and scoring system to generate responses or queries in the context of consulting or advisory services (AI advisory system). The system includes a user trust wallet 1,2 for

The invention provides a truss structure autonomous design system and method based on multiple agents. A layered multi-agent architecture is adopted, a general control agent is taken as a core, and a high-level design intention is analyzed and a plurality of downstream special agents are arranged for cooperative work; the whole design process realizes automatic closed loop through a graph-based workflow engine; the core innovation of the method is a hybrid intelligent optimization algorithm of LLM heuristic exploration and genetic algorithm accurate fine tuning, and the algorithm is driven by an original and quantifiable design quality scoring system to efficiently carry out analysis-diagnosis-optimization iteration so as to cooperatively improve the safety and economy of the design. The design time can be shortened from several hours to several minutes, about 7.0% of material consumption is saved on average, it is ensured that the scheme completely conforms to industry specifications, the design efficiency, economy and reliability are greatly improved, and meanwhile the use threshold of professional design software is remarkably reduced through natural language interaction.

The present application describes an electronic scoring system, especially designed for combat sports. The system allows a judge to automatically and consistently record the scoring parameters throughout a combat and its various rounds. In order for this to be possible, the judge evaluation is captured periodically, during the combat, using a scoring device and is sent to, central control unit, which is in charge of all the processing underlying the determination of the final winner of the combat.

The invention discloses a multi-sensor fusion target scoring system high-precision positioning method, and relates to the technical field of target scoring positioning, and the method comprises the following steps: building a transient interference recognition channel based on the electromagnetic response of a shock wave sensor, obtaining the electromagnetic disturbance of the bullet hit front edge, and generating an interference time sequence; performing delay triggering on the image sensor according to the interference time sequence, and avoiding an interference peak value to form a safe exposure time period; performing charge pre-release on the image acquisition chain before safe exposure; carrying out synchronous compensation on the shock wave signal based on energy distribution of charge pre-release, so that the shock wave signal and image energy response are symmetrical and mutually stable in a time domain; and dynamic shielding control is carried out on a space coupling path between the two types of sensors by utilizing an energy balance region formed in the mutual stable state. Through energy symmetric compensation and dynamic shielding control of shock waves and image signals, time-space separation and synchronous mutual stability of the signals are achieved, and high precision and stability of target scoring positioning under high-energy shooting are ensured.

The invention discloses a bus shift extraction optimization method based on multi-dimensional score driving, and relates to the field of urban public traffic scheduling management, and the method comprises the following steps: initializing shift extraction parameters, determining a shift extraction target, defining time period features, and setting a score weight and a penalty coefficient; constructing a shift extraction optimization mathematical model, including defining decision variables and establishing an objective function and constraint conditions thereof; respectively constructing a multi-dimensional scoring system and a constraint verification strategy by utilizing the objective function and the constraint conditions thereof; generating candidate shift drawing schemes, calculating a comprehensive score and selecting an optimal shift drawing scheme; performing iteration processing on the optimal shift extraction scheme in combination with loop control and a scheme rollback strategy to obtain a final shift extraction scheme; and verifying and counting the final shift drawing scheme, and generating a corresponding shift drawing report. On the premise that operation balance and service integrity are ensured, global optimal selection of the shift drawing scheme is achieved, and the intelligent level and operation efficiency of bus dispatching are remarkably improved.

The invention relates to the technical field of computers, discloses a data sharing method and system for patients suffering from metabolic acidosis, and aims to solve the problem of out-of-control safety caused by extensive authority, bare transmission and traceless behaviors in cross-institution medical data circulation. A dynamic authority strategy based on roles and scenes is constructed by extracting and standardizing patient diagnosis and treatment data from a hospital system; end-to-end encrypted transmission is realized through bidirectional authentication and a temporary session key; establishing a three-layer block chain type audit log tracking access, a secret key and a data flow direction; dynamic desensitization, quality verification, cache acceleration and intelligent contract extension mechanisms are integrated, and a visual authority topology monitoring and credit scoring system is supplemented. According to the technical scheme, data field-level accurate authorization, encryption and anti-theft in the whole transmission process, traceability in the whole operation period and use compliance self-feedback are achieved, and the scientific research value of clinical data is released to the maximum extent while the privacy safety of a patient is effectively guaranteed.

A scoring system for pickleball and other games. The scoring system generally includes a scoreboard configured to track and display the score and / or the serving player throughout a game. The scoreboard is configured to receive inputs to change the score, the serving player, and / or the serving team. In one example, the scoreboard includes a speaker configured to audibly announce the score of each team and the serving player before each serve. The scoring system includes remote controls, such as fobs, that allow players to control the scoreboard remotely. Further, the scoring system is expandable to include multiple displays and / or multiple scoreboards. The system includes a data management system that communicates with multiple scoreboards, such as for tracking performance and arranging matchups. The scoreboard is configured to connect to an external display, such as through a wireless connection.

The invention relates to a medical quality control dynamic scoring system, device and equipment based on multi-modal perception and federal evolution, and the method comprises the steps: obtaining original scene information through multi-modal input based on a medical equipment recognition model, carrying out the scene analysis and semantic fusion, generating structured medical scene data, and carrying out the dynamic scoring of the medical quality control according to the structured medical scene data. Multi-source evidence verification is carried out through a medical scoring rule base, a quality evaluation result is generated through weight dynamic adjustment, difference analysis is carried out through comparison with a manual correction result according to the quality evaluation result, and model parameters and scoring rule updating are generated. Multi-modal input is fused based on a medical special perception layer, anti-interference scene analysis and equipment semantic binding are achieved, multi-source evidences are verified in real time through a dynamic scoring engine, deduction weights are dynamically adjusted, subjective item scoring floating is compressed, an identification model is updated through federation, and a rule base is thermally loaded in real time, so that the anti-interference scene analysis and equipment semantic binding is achieved. And automatic closed-loop processing of problem items is realized.

The invention discloses a multi-agent collaborative examination question automatic correction optimization suggestion recommendation method and system, and particularly relates to the technical field of artificial intelligence auxiliary education, and the method comprises the following steps: generating agent consistency scores through periodic preliminary evaluation, judging score collaborative deviation conditions, if deviation exceeds a threshold value, entering correction detection, and if the deviation exceeds the threshold value, entering the next step; key data features are extracted to construct a score divergence aggregation degree index and an offset logic attribution index, a score behavior model is input to generate a behavior adjustment coefficient, a score structure reconstruction operation is executed based on the coefficient, a feedback suggestion generation mode is adjusted in a linkage mode, and collaborative optimization and dynamic evolution of scores and suggestions are achieved; according to the method, score collaborative deviation is identified in time through agent consistency scoring, a score deviation source is accurately positioned based on a score bifurcation polymerization degree index and an offset logic attribution index, and score structure reconstruction and feedback suggestion linkage adjustment are executed according to a behavior adjustment coefficient; and the stability, adaptive optimization and closed-loop feedback capability of the scoring system are realized.

Systems and methods of conducting a fantasy sport contest are disclosed. According to some embodiments, the fantasy sport contest is provided for participants to join. The fantasy sport contest includes one or more fantasy teams where each fantasy team includes a multiplicity of real-life players. A player adjustment value (PAV) is determined for each of the real-life players. Accumulated statistics of the real-life player during real-life games are converted into a baseline fantasy score according to a baseline scoring system. The baseline fantasy score is adjusted according to the real-life player's PAV to produce an adjusted fantasy score of the real-life player.

The embodiment of the invention provides a multi-layer Agent and expert cooperation test question scoring system and method. The system comprises an answer receiving module, an answer content analysis module, an objective question scoring module, a multi-agent cooperation scoring module, an expert verification module and a data analysis module. Wherein the multi-agent collaborative scoring module performs multi-dimensional scoring through a multi-level Agent and generates a result through weighted consensus; the expert verification module supports an expert to check and determine a result; and the data analysis module generates an optimization suggestion based on the verification result and feeds back the optimization suggestion to the multi-level Agent. According to the system, a three-level cooperation mechanism of answer detail analysis-AI driven scoring-professional field personnel verification is constructed, a multi-Agent scoring and expert auditing feedback mode is innovatively adopted, Agents are promoted to carry out self iterative evolution, intelligent and precise scoring of various test questions is achieved, and meanwhile continuous optimization of the system is supported to adapt to teaching requirements.

The invention relates to a biomarker applied to early diagnosis of sepsis. The biomarker is a fibrous protein degradation product FDP / D-dimer ratio. Compared with a single index (such as PCT, D-dimer), the biomarker has the advantages that the influence of individual difference and detection error can be reduced, and the stability of a result is improved; in combination with clinical information (such as infection evidence), the ratio can be used as an independent or joint index to assist an existing scoring system (such as SOFA) in improving diagnosis accuracy.

The invention discloses a batch composition scoring system, method and device based on multi-dimensional quantization and a storage medium. The system comprises an input processing module, a scoring module and a scoring module, wherein the input processing module extracts basic information of each composition from a batch composition picture based on multiple threads; the large model module extracts composition text feature information from the corresponding composition pictures according to the basic information of each composition based on the message queue, analyzes the composition text feature information according to a preset special constraint rule, a penalty factor rule and a basic score rule, and outputs a multi-dimensional score of each composition picture; and the multi-dimensional scoring engine performs multi-dimensional quantitative scoring on each composition picture through a multi-dimensional quantitative scoring formula according to the multi-dimensional scores. According to the method, the multi-dimensional quantification rule is fused to the large model, the objectivity of traditional rule quantification is reserved, a dimension self-defining mechanism is introduced, a user is allowed to expand the scoring dimension and adjust the quantification standard or the weight proportion according to the requirement, and fair and accurate automatic batch scoring is achieved.

The invention discloses a quantitative evaluation method and system for the autonomous controllability of a power grid dispatching automation master station system, and the method comprises the steps: building a hierarchical structure model of autonomous controllable evaluation through determining a quantitative index of the autonomous controllable evaluation of a hardware part, and enabling the model to comprise a target layer, a criterion layer and an index layer; then determining weights of the criterion layer and the index layer, and performing consistency check on the weights of the criterion layer and the index layer; and establishing a three-level scoring system, calculating a component autonomous controllability score corresponding to the index layer, calculating a complete machine equipment autonomous controllability score corresponding to the criterion layer, and calculating a system hardware equipment autonomous controllability score corresponding to the target layer. Compared with the prior art, the method has the advantages that the hardware autonomous controllability level is scored from small to large and from local to overall from three levels of parts, a whole machine and a system, a set of hardware autonomous controllability quantitative evaluation model is constructed, and quantitative indexes are provided for system hardware selection.

The invention belongs to the technical field of intelligent control and electronic circuits, and particularly relates to an intelligent peripheral control method based on an Android box, which comprises the following steps: acquiring sensor data and peripheral operation data of the Android box; performing feature data extraction through a time-frequency joint feature algorithm; a fault precursor prediction model is utilized to identify potential risks, a synchronous state is fed back to a user through voice, an equipment abnormal trend and a current operation condition are grasped, a federal learning cooperative training model is utilized to perform dynamic monitoring based on the potential risks, and a predictive pre-control instruction and an emergency instruction are generated; the method is executed after verification of the block chain, a standby power supply is started in an extreme scene, a user is informed of a real-time state through LED light flickering, a reinforcement learning iteration strategy is utilized, a maintenance scoring system is constructed, and point details are displayed to the user through an APP according to maintenance point redeemable services. Therefore, the problems of insufficient data processing and risk prediction capabilities, lack of user maintenance incentive mechanisms and the like in the prior art are solved.

The invention relates to the technical field of medicine safety monitoring, in particular to an individual case safety report automatic scoring system based on a large model. The system comprises a report receiving module, a deep semantic understanding module, a dynamic graph structure construction module, a graph neural network scoring module and an interpretability output module. Deep semantic analysis is carried out through a large language model pre-trained in the medical field, a multi-dimensional semantic graph with time sequence characteristics is constructed, a graph neural network based on an attention mechanism is utilized to carry out multi-round iterative reasoning to generate scores, and reasoning process interpretation based on a critical path is provided. According to the method, medical report semantics can be deeply understood, the dynamic relation between entities is accurately captured, the scoring accuracy and interpretability are improved, and reliable technical support is provided for drug safety monitoring.

The invention discloses an intelligent detection method for a reservoir piping phenomenon, and the method comprises the following specific steps: firstly, collecting piping phenomenon pictures for different reservoir scenes, constructing a training data set, and training the training data set to obtain a piping recognition model; secondly, performing candidate area detection on a video to be detected by adopting a piping recognition algorithm to obtain a candidate area containing a potential water flow target; then, in each candidate area, a water flow velocity detection algorithm is used for obtaining a horizontal velocity characteristic value between continuous frames; extracting a texture contrast characteristic value based on a texture analysis technology; and finally, constructing a comprehensive scoring system through weighted fusion of the horizontal speed characteristic value and the texture contrast characteristic value of the water flow, and determining an effective piping detection result only when a fusion score exceeds a preset threshold value. According to the method, deep learning and image analysis technologies are fused, the limitation of single feature detection is effectively solved, and the reservoir piping phenomenon is accurately recognized.

This invention belongs to the field of acute lymphoblastic leukemia (ALL) technology and discloses an ALL scoring system. The system divides the entire treatment cycle into three major phases: induction remission, consolidation therapy, and maintenance therapy. Each phase is further subdivided into sub-phases, forming a two-tiered data acquisition architecture. During data collection, baseline data such as age and fusion genes are included, along with dynamic data such as the rate of MRD decline and drug exposure concentration. Simultaneously, anchor triggering mechanisms are set at different sub-phases, making the risk score more closely aligned with the patient's real-time condition and providing a more accurate reference for clinical treatment strategy selection. The feature adaptation module matches subtype-specific biomarkers and analyzes the interaction between rare subtypes and comorbidities. The matching module calls upon a three-dimensional protocol library to select standardized protocols for common subtypes, targeted protocols for rare subtypes, and dose adjustment or drug substitution protocols for patients with comorbidities, matching more suitable protocols for different patients.

The invention belongs to the technical field of virtual power plant operation evaluation, and particularly relates to a virtual power plant operation comprehensive evaluation method and system.The method comprises the steps that a three-level multi-dimensional operation risk evaluation index system is constructed, and three types of weight vectors are obtained through an analytic hierarchy process, an entropy weight method and an inter-index correlation and conflict objective weighting method; carrying out collaborative correction through a non-cooperative game model to obtain an optimal comprehensive weight vector; a standard cloud model of each risk level is constructed based on an extension cloud model, an actual evaluation cloud model is constructed in combination with the score of a professional scoring system and an optimal weight, the score weight of the professional scoring system is determined through a grey correlation degree, an evaluation value is corrected, the actual cloud model is updated, and finally the digital characteristics of the actual and standard cloud models are compared. And quantitatively judging the operation risk level of the virtual power plant. According to the method, the comprehensiveness, reliability and scientificity of evaluation are improved, and support is provided for risk prevention and control of the virtual power plant.

The invention relates to an English dictation intelligent scoring system based on a multi-modal large model. The system comprises a multi-modal dictation input processing module, a dictation content analysis module, a fine-grained error detection module, a multi-dimensional scoring module and a personalized feedback generation module. The system realizes full coverage of three dictation forms of text, handwritten form and voice, and adapts to different teaching scenes. According to the method, multi-dimensional errors such as spelling, form, writing specification, voice and the like can be accurately recognized, the single dimension of'correct rate 'is broken through, comprehensive scoring is performed from the four aspects of'accuracy, normalization, fluency and context adaptability', and the real dictation quality of students is reflected.

The invention relates to the field of intelligent card punching and scoring, and discloses a high-altitude exploration card punching and scoring system based on NFC radio frequency and somatosensory interaction, and the system comprises a path and node configuration module which is used for setting NFC card punching nodes in a high-altitude exploration path and setting path parameters; the user identification and clock-in trigger module identifies the bracelet through NFC, records clock-in time and triggers a clock-in signal; the somatosensory action recognition module collects somatosensory data at the clock-in node and calculates an action score according to the path parameters; the clock-in event generation and authentication module generates a unique clock-in token; the integral calculation and path tracking module calculates single node scores and summarizes total scores; and the communication and data uploading module uploads the total score and the clock-in token to a server. According to the invention, the card punching nodes and the NFC radio frequency inductor are integrally arranged, and a body feeling triggering time sequence and standard action template comparison mechanism is combined, so that the technical effects that the card punching behavior is credible and verifiable and the action performance is automatically scored are achieved.