70 results about "Rating system" patented technology

Aspects of the subject disclosure may include, for example, generating network configuration data for a network device according to device information of a vendor; providing the network configuration data to an Artificial Intelligence (AI) analysis platform that applies an AI model to the network configuration data based at least in part on topology data resulting in a configuration analysis, wherein the configuration analysis evaluates the network configuration data and generates at least one of rating information, adjustment information or a combination thereof. The rating information can include a security rating, a risk rating and / or an efficiency rating. The adjustment information can include a recommendation for changing at least a portion of the network configuration data for the network device.

An AI-powered rating system includes a central artificial intelligence (AI) agent framework configured to orchestrate a rating process and automatically utilize available tools for data gathering and extraction; a data processing pipeline configured to simultaneously handle multiple streams of information from diverse sources, including structured data and unstructured data; a machine learning infrastructure comprising multiple specialized artificial intelligence models, each configured to evaluate a specific type of entity; a generative AI integration layer configured to provide a natural language explanation of a rating result for the rating process and enable conversational interaction with the system, where the generative AI integration layer is further configured to transform the unstructured data into quantifiable risk signals that are integrated with a structured data processing stream; and an output generation and reporting engine configured to deliver the rating result through one or more channels and formats.

The invention discloses an intelligent fire-fighting equipment fault prediction method, and belongs to the technical field of intelligent maintenance of fire-fighting equipment. According to the method, pressure, electrical waveform and environmental data are dynamically acquired through a multi-source sensor, spatial-temporal features are extracted in parallel by adopting a bidirectional LSTM and a multi-scale convolutional network, and feature fusion is realized by utilizing a cross-modal attention mechanism; outputting a fault probability based on a gradient boosting decision tree model, and predicting the remaining service life in combination with Bayesian regression; the firmware upgrading authority is controlled through a health degree dynamic scoring system, and the upgrading safety is guaranteed through AES-256-CBC encryption and SM3 signature verification; and generating an optimal maintenance path based on an improved genetic algorithm, and scheduling an engine to respond to a sudden fault in real time. Tests show that the fault early warning accuracy rate reaches 93.1%, the maintenance cost is reduced by 45%, the upgrade failure blocking rate is 100%, and the intelligent level and reliability of operation and maintenance of the fire-fighting equipment are remarkably improved.

The invention discloses a credit rating system based on multi-source data fusion and an enterprise knowledge graph. The credit rating system comprises the following modules: a data acquisition module, a data preprocessing module, a data fusion module, a knowledge graph construction module and a credit rating module. The data collection module is configured to collect enterprise-related data from a plurality of heterogeneous data sources. By integrating multi-source data fusion and an enterprise knowledge graph technology, comprehensive and dynamic evaluation of enterprise credit is realized, the system can acquire data from multiple channels and construct a unified enterprise data view through preprocessing and fusion, and the enterprise knowledge graph constructed on the basis not only contains attributes of enterprises, but also can construct a unified enterprise data view. Various relationships between enterprises are also disclosed, enabling credit rating to take into account associated risks.

A system includes a processor and a memory accessible to the processor. The memory stores instructions that, when executed by the processor, cause the processor to determine a privacy policy score for one of an application and a website and provide the privacy policy score to a device.

The invention relates to an electric power resource adjustability resource multi-dimensional analysis and visualization method, which comprises the following steps of: selecting four dimensions of response time, service time, adjustable capacity and credibility in electric power resource adjustability characteristic indexes as a rating system, and drawing an electric power adjustability resource adjustability characteristic radar map; and constructing a power adjustable resource characteristic cube by taking the power adjustable resource adjustment characteristic radar map as a bottom surface and taking the corresponding scale capacity as a high surface to represent the adjustable characteristic characteristics of the source network load power resources. Compared with the prior art, the multi-dimensional visualization of the adjustment performance of the power adjustable resource is realized by constructing the characteristic cube, the adjustable characteristic characteristics of the source network load power resource can be comprehensively and accurately represented, and a large number of, multiple and dispersed flexible resources can be aggregated to participate in system adjustment.

This invention discloses a hydrophobicity rating system for superhydrophobic surfaces of energy equipment, relating to the field of hydrophobicity rating technology. The system includes a data acquisition module, an optimal parameter combination module, a sample preparation module, a hydrophobicity quantification and evaluation module, a test closed-loop calibration module, and a hydrophobicity rating classification and output module. These modules are interconnected, and through their collaborative operation, the system quantifies, performs closed-loop calibration, and classifies the hydrophobicity index of superhydrophobic samples of energy equipment with different microstructures. The closed-loop calibration process fully considers both anti-icing and weather resistance, significantly improving the accuracy and generalization ability of the hydrophobicity rating results. This solves the problems of inaccurate evaluation results and inability to adapt to extreme field conditions caused by traditional evaluation systems relying solely on conventional laboratory environments, single physical tests, and empirical thresholds for rating. This enhances the intelligence level of hydrophobicity rating evaluation for superhydrophobic surfaces of energy equipment.

A system includes a processor and a memory accessible to the processor. The memory stores instructions that, when executed by the processor, cause the processor to determine a privacy policy score for one of an application and a website and provide the privacy policy score to a device.

A high volume scoring system for bread dough is provided with a conveyor table that includes a first scoring apparatus and a second scoring apparatus that is located downstream from the first scoring apparatus to permit longitudinal and angled scoring of dough pieces. Trays containing unbaked dough pieces are loaded onto the conveyor and shuttled downstream along the conveyor to selectively align the trays beneath the first or second scoring apparatus depending on whether diagonal or longitudinal score lines are desired on the dough pieces. The first scoring apparatus is configured to make a series of diagonal score lines on the dough pieces positioned beneath the first scoring apparatus using a first series of blades. The system can also convey the trays containing the unbaked dough pieces downstream along the conveyor to align the trays beneath the second scoring apparatus. The second scoring apparatus is configured to make longitudinal score lines on the dough pieces positioned beneath the second scoring apparatus using a second series of blades. Once the dough pieces have been scored, they are conveyed by the system into an oven for baking.

Disclosed herein are systems and methods for generating an Al work score for tasks assisted by artificial intelligence. The score is determined by collecting and processing user data using scoring algorithms that consider at least one of the following: Al integration, task complexity, baseline metrics, and time calibration. The system and methods also generate composite scores across users, tasks, groups or industries and classifications across various metrics, enabling correlation reports. These scores can assist in evaluating Al integration, optimizing task assignments and improving Al usage in supervised environments.

The present invention relates to a system (1) for evaluating and scoring the compliance of a driver with traffic rules while driving by analyzing data collected from the vehicle.

The invention discloses an enterprise credit automatic rating method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring to-be-rated enterprise data; inputting the to-be-rated enterprise data into a credit rating model for credit score calculation to obtain a calculation result; determining an industry to which the enterprise belongs according to the to-be-rated enterprise data; determining a mapping relation according to the industry to which the enterprise belongs; determining the credit rating of the enterprise according to the calculation result and the mapping relation; and outputting the credit rating of the enterprise. By implementing the method provided by the invention, a more comprehensive and accurate credit rating system can be realized, and the problems of difficulty in data acquisition, unstable data quality, poor model interpretability and complexity and accuracy of a processing process in the prior art are solved.

The invention relates to the technical field of financial supervision, in particular to an e-commerce loan financing online return clearing supervision system and method. According to the invention, through refined classification of the transaction data and accurate identification of the type of the returned money, independent processing of different types of returned money is ensured, the risk of fund confusion is reduced, and the transparency of fund flow direction is improved. The accurate matching of the return fund and the financing order enables each fund to be quickly cleared according to a preset rule, and improves the efficiency of fund collection and repayment. Based on the real-time evaluation of the shop refunding condition, a plurality of dimensions such as sales fluctuation, refunding proportion and refunding arrival time are comprehensively considered, a stability index is established, the business state of a merchant can be accurately judged, and misjudgment caused by short-term abnormal fluctuation is avoided. In combination with the fund return stability index and the merchant credit score, the credit rating system is optimized, so that the dynamic adjustment of the credit score better conforms to the real business condition of the merchant.

According to the multi-level wind turbine generator cooperative reliability rating system, method and device and the storage medium, the system comprises a domain self-adaptive processing sub-module, a digital twin working condition label calibrates a local gradient through an MMD algorithm, a domain self-adaptive calibration algorithm of federal transfer learning is adopted, and the local gradient of the digital twin working condition label is calibrated; a virtual fault sample generated by digital twinning is combined with real monitoring data, a mixed data set covering all working conditions is constructed, a model can still learn corresponding fault features under the condition that no real extreme fault data exists, a safety aggregation module carries out cross-domain adaptation processing on local gradients through a domain self-adaptation gradient processing formula, and the safety aggregation module carries out cross-domain adaptation processing on the local gradients through the domain self-adaptation gradient processing formula. The method comprises the following steps of: calculating an aggregation weight according to a block chain-federated security aggregation formula, generating block chain evidence hash according to the aggregation weight, fusing real-time real data and digital twin virtual data, reducing interference of a single data source, and greatly improving reliability rating accuracy.

Rating system (10) that determines a network connectivity performance road map (12), wherein the rating system (10) comprises: one or more back-end servers (20) in wireless communication with multiple vehicles (24) located in a geographical area (26) through a wireless communication network (28), wherein the multiple vehicles (24) collect multiple overall performance metrics of the wireless communication network (28); and one or more street map databases (54) in electronic communication with the one or more back-end servers (20), wherein the one or more street map databases (54) store a map data street graph of the geographic area (26) containing multiple nodes (60) connected by multiple edges (62), and one or more statistical measures corresponding to the multiple overall performance metrics of the wireless communication network (28) for each of the multiple nodes (60), and where one or more back-end servers (20) execute instructions to: Calculating one or more statistical measures corresponding to the multiple overall performance metrics of the wireless communications network (28) for each of the multiple edges (62) of the map data street graph of the geographic area (26); and Determining the network connectivity performance road map (12) of the geographical area (26) based on one or more statistical measures corresponding to the multiple overall performance metrics for each of the multiple nodes (60) and for each of the multiple edges (62), Receiving a route request containing a starting point and a final destination from one of the vehicles (24); Calculating distance costs for each of the multiple edges (62) that are part of the network connectivity performance road map (12) in response to receiving the route request; Calculating time costs for each of the multiple edges (62) that are part of the network connectivity performance road map (12), Combining the distance costs and the time costs together on the basis of a weight value assigned to the distance costs and a weight value assigned to the time costs to determine basic edge costs assigned to each of the edges (62) that are part of the network connectivity performance road map (12); and Determining one or more basic route plans by minimizing the basic edge costs assigned to each of the edges (62) located between the starting point and the final destination of the route requirement, characterized by the fact that the one or more back-end servers (20) further execute instructions to: Calculating relief costs for each of the multiple edges (62) that are part of the network connectivity performance road map (12) in response to receiving the route request; and Calculating network live latency costs for each of the multiple edges (62) that are part of the network connectivity performance road map (12).

Systems and methods are provided that comprise an app with access to a website comprising critiques and ratings of food and beverages by critics for use by potential consumers. The critics are enabled and compensated for their critiques and ratings that increases the critics' efficiency, organization, usefulness, quality, and rewards using cryptocurrencies. The systems and methods comprise a plurality of computer devices operating the app and interfaced with the critiquing and rating website hosted on one or more computer servers on the Internet and supporting critiques by authorized critics using said computer devices. The app comprises a comprehensive rating system that includes ratings for take-out, delivery, and in-store dining. The app supports displaying on the website reviews and ratings of food and alcoholic beverages, pictures of dishes, menus from restaurants and pictures of each dish, rankings of dishes, delineating rankings by ethnicity, and other information.

1000 MORE is a digital political marketplace that centralizes all civic engagement for constituents, advocacy organizations and elected officials. It generates information about bills coming up for a vote, elected officials, and advocacy efforts, then provides action options including calls, emails, connecting via social media and crowdfunding. 1000 MORE provides constituent users with information about how their elected officials and candidates align with their interests based on their usage of the platform. With that information in hand, constituents can engage with candidates through phone, email, social media or donations. Furthermore, 1000 MORE uses that information to build a hyper personalized voter guide for constituents. It also gamifies civic engagement with a scoring system and options to connect with other users. Advocacy organizations have an interface where they can connect with constituents and crowdfund. Elected officials have an interface where they can track the preferences of and communicate with their constituency.

Aggregation and scoring system for collecting and analyzing public and survey data of public entities, private entities, elected officials, candidates for public office, and other individuals or entities who hold a position of public or private prominence, or public or private influence, to generate a five-tiered score predicated on predetermined metrics of evaluation.

The invention discloses a leg posture analysis and rating system for a football player in a ball kicking process, and the system comprises a data collection unit which collects four-stage kinematics parameters of kicking, kicking and stretching, backward swinging, forward swinging and ball touching through a three-dimensional motion capture system and a high-speed camera; the data processing unit is used for processing parameters and extracting characteristic parameters of each stage; the expert evaluation interface is used for receiving evaluation data of multiple experts on different ball kicking technology types on the multi-score influence factors; the weight calculation unit is used for calculating an influence factor attribute weight by using a Bayesian method based on expert data; the rating decision matrix construction unit is used for constructing a comprehensive matrix in combination with a weight rough projection method; the multi-angle analysis unit is used for performing multi-angle risk rating by fusing a rough set theory and an approximate ideal solution sorting method; and the result output unit is used for outputting the posture quality grade and the training suggestion. According to the method, the actual requirements of football training on precision, standardization and comprehensiveness of posture analysis can be met.

A method for displaying digital media objects and dynamically calculating their rating values. A first digital media object is displayed on a first computing device. A first user provides one of predefined inputs corresponding either to a positive or a negative response to the first digital media object. The rating value of the first digital media object is increased if the response is positive and decreased if the response is negative. The numerical change of the rating value is calculated based on a coefficient value associated with the first user. The rating value of the first digital media object and the coefficient value of the first user are dynamically recalculated based on subsequent responses of the first digital media object from other users. The updated coefficient value is used to calculate subsequent numerical changes in the ratings of other digital media objects based on the first user's subsequent responses.

The invention discloses a rating method, a rating system, electronic equipment and a storage medium. The rating method comprises the following steps: presetting priority levels of various performance requirements of a to-be-rated object according to requirements; formulating an executable rating standard based on each performance requirement with the preset priority level; and based on the actual performance of the to-be-rated object, performing performance rating on the to-be-rated object according to the executable rating standard, and outputting a formal rating report. Due to the adoption of the rating method, the classification rule of the rating object such as a crystal bar in multiple dimensions can be easily realized, so that different rating standards are easy to maintain; and specific classification is realized by setting the priority level, so that the requirement of product customization can be met, and the customer satisfaction is improved.

The invention provides a network visitor reputation rating system based on public intelligence clues, relates to the field of network security, and adopts a data processing technology based on artificial intelligence to carry out data cleaning and structured mapping on obtained public intelligence data of a target network visitor so as to obtain a plurality of public intelligence data features. Then performing IP address activity record semantic dynamic transmission on the time sequence of the IP address activity record semantic embedded coding feature to obtain an IP address activity time sequence mode feature; and finally, automatically obtaining a reputation rating tag of the target network visitor based on the joint representation between the IP address activity time sequence mode characteristics and other public intelligence data characteristics. In this way, the real risk level of the visitor can be evaluated more accurately, and then the accurate prevention and control requirement can be met.

The invention relates to the technical field of credit scoring, in particular to a credit scoring system for quantitative model service capability based on artificial intelligence, which aims at the pain points of current credit data output and traditional technical architecture, constructs a unified data table, breaks the independence of data distribution and storage, and improves the credit scoring efficiency. Real-time integration and linkage of multi-source heterogeneous data are achieved, characterization, tagging and business based on data are provided, original information and fields scattered in different data sources are collected in a unified mode, indexes are processed and integrated in a unified mode, a unified tag library with enterprises as the granularity is formed, and support is provided for decision-making type model development and business decision making. And in the aspect of the model, a machine learning algorithm is introduced, and the automatic learning capability and the dynamic adjustment characteristic of the machine learning algorithm are utilized, so that rapid iteration and accurate prediction of the risk control model are realized, the high requirements of banks on real-time data processing and dynamic risk strategies are met, and credit investigation companies are comprehensively assisted to promote general financial services.

As disclosed herein, a method for billing for usage of software applications is provided. The method may include receiving usage data associated with a software application and stored in a first plurality of user fields. The method may include aggregating the usage data using a unique identifier. The aggregated usage data may include values stored in a second plurality of user fields. The method may include receiving a mapping between the second plurality of user fields and a plurality of predefined fields. The method may include applying the mapping to the aggregated usage data to store the aggregated usage data in a usage database. The method may include applying a usage rate to the stored usage data to determine a total usage charge. The method may include generating a usage invoice based on the total usage charge. A system and a non-transitory computer-readable storage medium are also disclosed.

A system and related methods for analyzing and generating a score for web sites containing content, and providing recommendations and guidance for content modifications and additions. The system provides and receives content survey results from users or viewers of a site, aggregates the content survey results, integrates metrics for multiple content types and domains, and generates a content score for each content type and domain. A summary or aggregate score based upon the scores for each content type and domain also is calculated. The scores can be presented or displayed in a dashboard, graphic interface, report, or other means.

The invention provides a building decoration material environmental protection property detection and rating system. Relates to the technical field of building and decoration material detection, and comprises a multi-source detection unit which forms a composite detection channel through an electrochemical sensing coupling detection technology, and the composite detection channel detects key environmental protection indexes of building decoration materials to generate key environmental protection index data. According to the environment-friendly property detection and rating system for the building decoration material, the environment-friendly property of the building decoration material is comprehensively detected through a multi-source electrochemical detection technology in combination with methods such as infrared spectrum sensing, differential pulse voltammetry and electrochemical impedance spectroscopy. The innovative detection can evaluate the key environmental protection indexes of the material in multiple dimensions, such as formaldehyde emission, volatile organic compound concentration, heavy metal element content and radioactivity, so that the accuracy and comprehensiveness of the detection result are ensured, and the scientificity of environmental protection material evaluation is effectively improved.

The application belongs to the technical field of scientific education, and discloses a popular science quantitative intelligent scoring system; the system comprises a data collection module, which is used for acquiring popular science activity data; an intelligent recommendation module, which is used for recommending different popular science contents to participants according to the popular science activity data; a popular science effect evaluation module, which is used for evaluating whether the participants achieve positive influence after participating in different popular science contents; and a popular science quantitative scoring module, which is used for scoring the positive influence achieved by the participants after participating in different popular science contents, so as to provide an effective basis for the examination of popular science work, help improve the quality and efficiency of the popular science work, and help improve the effect of the popular science activities and the satisfaction of the participants.

The invention discloses a film scoring system and method based on big data. The film scoring system comprises a data acquisition layer, a data storage and processing layer, a model construction layer, a service layer and a user interface layer, wherein the data acquisition layer is used for performing data acquisition; the data storage and processing layer is used for carrying out data cleaning and preprocessing on the collected data and extracting features from the preprocessed data; the model construction layer is responsible for processing and analyzing big data, generating movie scores, analyzing user behavior data by using naive Bayes, quantifying positive / negative emotions, reducing weights of easy-to-classify samples by using focus loss when emotional tendency distribution of a specific group is imbalanced, and constructing a classification model based on movie features, multi-dimensional features and time features; according to the method, multiple XGBoost models are trained through multi-task learning, scores of different dimensions are predicted respectively, input of emotional tendency is provided for different dimensions through naive Bayesian analysis results, and meanwhile personalized scores are provided for different groups in combination with group characteristics.

The invention, which relates to the technical field of data processing and intelligent matching, discloses a digital intelligence platform comprising a multi-modal data acquisition module, a multi-modal sentiment analysis module, a data basic module, an intelligent negotiation auxiliary module and a false information identification and correction module. The multi-modal data acquisition module is used for acquiring text, audio and video multi-modal data of enterprises and job seekers; the multi-modal sentiment analysis module extracts sentiment features from the multi-modal data, fuses the sentiment features and outputs sentiment matching scores of the two parties; the data basic module collects market data of industries and regions in real time and records user behavior data; the intelligent negotiation auxiliary module provides a negotiation strategy in salary, man-hour and welfare dimensions based on the data; according to the system and the method, a real, efficient and humanized intelligent matching and negotiation environment can be constructed, and the long-term integrating degree of people and posts is improved.

An information acquisition unit (S410 to S420) captures an API access log, which represents the usage status of an API according to a request from an application installed in a vehicle. A sales-related index generation unit (S480 to S490) generates a sales-related index according to a log aggregation value. This index is the result of aggregating the API access log for each vehicle classification, obtained by classifying the vehicle based on vehicle sales data, and for each API type. The sales-related index is an API index that indicates the degree of influence of the API on the application and a vehicle user. An output unit (S510) outputs the sales-related index.