144 results about "Health score" patented technology

The invention discloses a server health state diagnosis method based on a GAT-LP algorithm, and relates to the technical field of server health diagnosis, and the method comprises the steps: collecting multi-dimensional operation state data of a server, transmitting the multi-dimensional operation state data to a data analysis platform, and carrying out the preprocessing, inputting the preprocessed historical operation state data of the server into a GAT-LP network for training to obtain a GAT-LP network model, evaluating health conditions of the server and the process and generating an overall health condition according to a health state diagnosis result of the server and health score features extracted based on the GAT-LP network model, converting an evaluation result into a visual health state, and displaying the visual health state in the GAT-LP network model. And triggering an alarm mechanism when the health state of the server is lower than a preset threshold value. By constructing a multi-dimensional health assessment index system, the running state of the server is visually displayed, potential risks are found in advance, and prevention measures are made.

The invention discloses an operating system health assessment method and system based on multi-dimensional index dynamic weighting, and the method comprises the steps: collecting the state of each hardware module, calculating the index, carrying out the weighted summation to obtain the score of the hardware module, adjusting the weight parameter of each hardware module through combining with the real-time load characteristic or business priority, and carrying out the real-time evaluation of the health of each hardware module. Performing weighted summation on the scores of the hardware modules to obtain a hardware health score; software state information in the operating system is collected, scores of all software modules are calculated, the software modules comprise key components, key services and key processes, and the scores of all the software modules are weighted and summed to obtain software health scores; and performing weighted summation on the hardware health score and the software health score to obtain a health score of the operating system so as to determine the health state of the operating system. The invention aims to solve the systematic defect in the existing health monitoring technology system, improve the comprehensive evaluation capability of the health evaluation of the operating system, and dynamically adapt to the change rule of the actual operating environment.

A method and a Large Language Model (LLM) evaluation system provides an end-to-end evaluation of LLM, which includes evaluating both input prompts and output prompt responses, wherein the evaluation includes assessing a plurality of input and output characteristics that encompasses both quality and quantity. Each of the plurality of input characteristics are assigned with a corresponding normalized score by employing one or more statistical techniques to derive a composite health score for the input prompts. Evaluation further comprises evaluating output prompt responses in both absence and presence of the ground truth. Upon evaluating both input prompts and output prompt responses, a final aggregated health score for the LLM is computed by a scorer module employing threshold based statistical techniques that considers input prompt health and output prompt response health, wherein the aggregated health score is generated based on the granular scores of each characteristic.

The invention belongs to the technical field of equipment management, discloses a health degree evaluation method, system and equipment for assembly line special equipment and a medium, and aims to solve the limitation of health state evaluation of the assembly line special equipment in the prior art. The method comprises the steps of obtaining evaluation indexes of equipment and comprehensive weight values corresponding to the indexes, and performing calculation based on the evaluation indexes to obtain a first health degree score; acquiring historical fault data and historical operation time data of the equipment, calculating a time interval between a fault occurrence moment and a maintenance occurrence moment of each fault based on the historical fault data and the historical operation time data, and constructing a time attenuation model to calculate a weighted risk score of each fault so as to calculate a second health score; and obtaining production scheduling data of the equipment, and performing calculation in combination with the health degree data to obtain a current production scheduling risk score, thereby completing health degree evaluation of the assembly line special machine equipment. According to the method, the comprehensiveness, the accuracy, the dynamism and the real-time performance of health degree evaluation of the assembly line special machine equipment are remarkably improved.

The invention discloses a health evaluation method, electronic equipment, a storage medium and a product, and relates to the technical field of computers, and the method comprises the steps: based on time sequence index data and log data in a to-be-evaluated system, respectively determining a monitoring index deviation degree corresponding to the time sequence index data and a log abnormal probability corresponding to the log data; based on the monitoring index deviation degree and the log abnormal probability, determining an index fusion weight corresponding to the monitoring index deviation degree and a log fusion weight corresponding to the log abnormal probability; and according to the monitoring index deviation degree, the log abnormal probability, the index fusion weight and the log fusion weight, in combination with a health degree scoring function, determining a health degree score of the to-be-evaluated system, so as to execute a recovery operation on the to-be-evaluated system according to the health degree score. The system fault can be detected and evaluated more accurately, the recovery strategy can be dynamically adjusted according to different fault severity degrees and actual conditions of the system, and the recovery efficiency and fault-tolerant capability of the system are remarkably improved.

The invention discloses a self-repairing method and system for multi-modal sensor fusion, electronic equipment and a medium, and relates to the technical field of automatic driving. The method comprises the following steps: generating a physical layer health score and a logic layer health score about a heterogeneous sensor based on original data; judging whether the heterogeneous sensor fails or not by combining the physical layer health score and the logic layer health score; inputting the effective original data into a generative adversarial network under the condition that the existence of the invalid heterogeneous sensor is determined, performing cross-modal generation, and outputting first virtual data of the invalid heterogeneous sensor; according to the comprehensive health score of the heterogeneous sensor, dynamically distributing a fusion weight coefficient of the heterogeneous sensor; and based on the fusion weight coefficient, fusing the effective original data and the first virtual data by using a data fusion algorithm, and outputting a fusion perception result. By adopting the method, the compensation precision can be improved, and a reliable sensing result is output.

A computer implemented preventative health care and health intervention application is described. The application includes a scoring system to score an overall health of the member, including breakdowns scoring the member's initial physical health, mental health, and an initial score for the lifestyle of the member. One or more health care providers are assigned to and / or selected by the user. The health care providers assess which health intervention programs are best suited to meet the goals of the member and to improve the score for the member's health. The score is re-evaluated when the member meets a minimum threshold of participation and attendance in the one or more selected health and health intervention programs. The score evaluation includes review of attendance, participation information, data collected from sensors and wearable devices, as well as based on predictive analytics integrated into the preventative health care and health intervention program.

The invention discloses a tunnel structure health dynamic monitoring system and method, and relates to the technical field of tunnel state monitoring. A tunnel structure health dynamic monitoring system comprises a data acquisition and processing module, a structure health evaluation module, a structure health prediction module, a score fusion and correction module and a monitoring scheme planning module. According to the method, weighted summation is performed on the recent structure health score and the predicted structure health score, and the comprehensive structure health score is obtained, so that the real-time state and the future development trend of the tunnel can be comprehensively considered, and the real health condition of the tunnel can be more comprehensively reflected; therefore, evaluation deviation caused by one-sided attention to a certain aspect at present or in the future is avoided, and insight of potential risks in advance is facilitated, so that resource allocation is optimized, risk areas are monitored emphatically, decision perspectiveness and planning rationality of monitoring work are improved, and the method is suitable for popularization and application. And the planning rationality of the tunnel structure health dynamic monitoring system and method on the monitoring scheme is improved.

The invention provides a bearing life prediction method, and belongs to the technical field of equipment life prediction, and the method comprises the steps: obtaining a bearing health state index, and comprehensively calculating a comprehensive health score CHS of a certain time step; based on the comprehensive health score CHS, constructing a prediction model of the bearing health state to the remaining use time; training the constructed prediction model by using a comprehensive health score (CHS); and the trained prediction model is used to identify the dynamic characteristics of the bearing health state to the remaining use time, and the bearing health state is predicted according to the trend of historical health state scoring so as to complete the prediction of the bearing life. According to the method, the problems of high model complexity, insufficient explanation, poor applicability and universality and large over-fitting risk in the prior art are solved, so that high precision, high robustness and high reliability of bearing life prediction are realized.

The invention relates to the technical field of computer input equipment, and discloses a keyboard design method and system fused with health monitoring, and the method comprises the steps: analyzing a keystroke behavior type corresponding to keyboard operation data, and generating a physiological signal feature of a target user; setting a baseline parameter threshold of health monitoring of the target user, calculating rhythm entropy change corresponding to the keyboard rhythm data, and analyzing a potential physiological risk type corresponding to the target user; analyzing a hand fatigue accumulation track and an instantaneous operation steady state curve in the historical operation data of the user, and evaluating a hand and brain coordination health score of the target user; dynamically adjusting the baseline parameter threshold to obtain a sensitivity threshold, analyzing the current scene demand corresponding to the keystroke behavior type in real time, and generating a multi-dimensional hierarchical early warning strategy of the target user; and executing health monitoring processing on the target user to obtain a health monitoring result. According to the invention, the accuracy of health detection when a user uses the keyboard can be improved.

Embodiments of the present disclosure provide a context based health visualization system and method for a computing environment that indicates context-based health information for the computing resources of a computing environment. According to one embodiment, an Information Handling System (IHS) includes computer-executable instructions to identify a maintenance task that needs to be performed on a computing resource, classify the maintenance task according to one of a plurality of health contexts, and generate, using information associated with the maintenance task, a health context score for the one health context. The maintenance task may be one that impacts an overall health score of the computing resource. The instructions may then cause the IHS to display the health context score for view by a user.

The invention provides a dynamic collaborative multi-path routing control method and device. The method comprises the following steps: determining a health score of each substream based on a performance index of the substream at the current moment; based on a first difference value between the health score of each substream and the health score mean value of all the substream, determining the weight adjustment amount of each substream at the current moment by adopting a PID control technology; and determining the weight of each substream at the next moment based on the weight adjustment amount of each substream at the current moment, and determining a multi-path routing control scheme at the next moment based on the weight of each substream at the next moment. According to the invention, rapid and stable switching of paths is realized through a dynamic cooperative routing control method.

A system and method for providing a true health-wellness status of a user, where such true health-wellness status is a holistic and / or a specific true health-wellness status. The method encompasses: receiving, by a transceiver unit [102] from a storage unit [108], a user data; analysing, by the processing unit [104], the received data, based at least on a first set of pre-set rules to generate a corresponding composite score for one or more health based dimensions of the user; automatically generating, by the processing unit [104], a health-wellness score of the user based on a weighting of the corresponding composite score based on a second set of pre-set rules; providing, by the processing unit [104], to at least one of the user and a healthcare provider, the true health-wellness status of the user based on the health-wellness score of the user.

The invention discloses a multi-dimensional student physical health monitoring method and system, and relates to the technical field of health monitoring, and the method comprises the steps: collecting data to construct a signal subset, carrying out time-frequency decomposition to construct a time-frequency graph matrix, carrying out autoregression modeling to extract an observation matrix and a design matrix, and constructing a frequency feature vector; according to the frequency characteristics of different frequency bands, calculating contribution factors and determining a dynamic health score, calculating a posterior probability of a health state based on a conditional probability of the health score, and calculating a frequency band offset to construct an abnormal frequency band set. According to the method, a health assessment model is constructed by using an observation matrix and a design matrix, so that signal values in each row are associated with lagging historical values, the time dependence of the signals can be captured, the dynamic characteristics of the health signals are reflected, and the mean value, variance, skewness and kurtosis are calculated based on PSD. And high-dimensional spectrum information is concentrated into a feature vector of a fixed dimension, so that the data complexity is reduced, and subsequent classification and health state analysis are facilitated.

The invention discloses a MySQL database management platform, which relates to the field of database management optimization, and comprises the following steps: acquiring an operation feature vector, constructing a waiting time prediction model in combination with transaction feature parameters, obtaining an optimal waiting threshold, and forming a consistency time window baseline and a consistency time window default rate; collecting cluster node operation state information, calculating a node comprehensive health score and a diagnosis health score, obtaining a cluster comprehensive health score, and determining a new main node; shadow read-write testing is carried out on the new main node, and a batch revenue function is constructed to obtain a preliminary low-load time window; further converging a low-load time window to determine a lowest-load window, putting online candidate indexes in the lowest-load window in stages, dynamically monitoring and adjusting a batch scale and an execution interval in an execution process, and calculating a comprehensive improvement score according to a consistent time window baseline, a comprehensive health score, the lowest-load window and online monitoring data; and updating the consistent time window baseline and the comprehensive health score.

The invention discloses a health degree score-based production capacity guarantee degree evaluation method and device and a medium, and the method comprises the steps: obtaining an offline equipment inspection parameter, and carrying out the health index evaluation of the offline equipment inspection parameter, so as to obtain an offline inspection equipment health degree score; obtaining equipment operation state inspection parameters, and performing time sequence health state analysis on the equipment operation state inspection parameters to obtain an operation inspection type equipment health degree score; determining a comprehensive health degree score through multi-level health degree index weight analysis based on the health degree of the offline inspection type equipment and the health degree of the operation inspection type equipment; according to the comprehensive health degree score, determining the current production capacity of the industrial system through production capacity evaluation; and performing system guarantee degree analysis on the current production capacity of the industrial system, and determining the comprehensive guarantee degree of the equipment. According to the method, the technical problem of mutual exclusion of health degree and guarantee degree analysis in an existing industrial system is solved.

The invention provides an intelligent health state assessment method for building electromechanical equipment, and relates to the technical field of equipment state assessment, and the method comprises the steps: building a temperature model through obtaining temperature curves of monitored equipment at different powers, obtaining a predicted temperature curve according to a next task, and carrying out the analysis to obtain a predicted temperature score; acquiring a previous vibration curve of the monitored equipment, analyzing the previous vibration curve, acquiring a current vibration score, acquiring a historical task similar to a next task, acquiring a historical temperature score and a historical vibration score, acquiring a health score in combination with an intermediate task, and analyzing the health degree; according to the method, the next task is associated with the actual physical state and the historical state of the equipment to generate the health score, so that the accuracy of equipment health state assessment is ensured.

The invention relates to a nursing home priority service response method, system and device based on digital twinning, and the method comprises the following steps: collecting health data of old people and state data of nursing personnel, and carrying out the preprocessing of the data; constructing an old people health state dynamic model, a nursing resource dynamic model and an environment path model; coupling the three models to form a digital twin model; calculating a service response priority based on the health score, the waiting time attenuation and the medical history characteristics of the elderly; according to the service response priority, scheduling the matched nursing personnel to carry out service response; and collecting a service execution result after the nursing personnel completes the task, updating the digital twinborn model based on the service execution result, and dynamically adjusting a scheduling strategy. According to the invention, real-time mapping and dynamic optimization of the health state of the elderly, the position of the nursing personnel and the environment path information in the nursing home are realized, and the service response efficiency, the resource scheduling accuracy and the nursing quality are remarkably improved.

The invention discloses a sub-health node switching method and device of a database cluster, equipment and a medium. Comprising the steps of collecting multi-dimensional resource indexes of all database nodes in a database cluster based on a preset period, and calculating a real-time health score of each database node by using a health assessment model; when the real-time health score is lower than a sub-health judgment threshold in a preset step length, marking the real-time health score as a sub-health master node; acquiring the real-time health score, the resource margin and the data synchronization delay of the standby node, and selecting a target standby node; switching the data service access from the sub-health master node to the target standby node, and changing the role identifier of the target standby node as the master node; and taking the sub-health main node as a standby node, completing state reconstruction of the database cluster, and putting into a next acquisition period. According to the embodiment of the invention, active identification and seamless switching of the sub-health nodes are realized, service interruption is effectively avoided, and high availability and service continuity of a distributed database cluster are improved.

The invention provides a storage pool fault risk prediction method and device and a product, and relates to the technical field of cloud computing. The method comprises the following steps: acquiring a health score of each storage unit according to hardware information of at least one storage unit included in a storage pool node; calculating a health score mean value of different types of storage units in the storage pool node according to the health score of each storage unit; and obtaining the health state score of the storage pool node according to the health score mean value of the plurality of different types of storage units and the weight value corresponding to the corresponding type of storage unit. According to the embodiment of the invention, the health score mean value of the storage unit of the corresponding type is calculated according to the health score obtained by the at least one storage unit included in the storage pool node by adopting the hardware information, and the health state score of the whole storage pool node is obtained by combining the weight value of the type; therefore, the overall hardware health state of the storage pool is scored in a unified manner, and the change of the hardware state is seen from the perspective of pooling.

The invention belongs to the technical field of offshore wind turbine monitoring, and particularly provides an offshore wind turbine generator health degree evaluation method based on multi-source data fusion, and the method comprises the following steps: 1, constructing a health scoring model; 2, performing health degree scoring on each module of the offshore wind turbine generator; the health degree scores, calculated in the second step, of all modules of the offshore wind turbine generator set are input into the health scoring model in the first step, a total score is obtained, and then health state grading is carried out. According to the method, multiple indexes of the fan are comprehensively considered, and the health state of the unit is evaluated in real time.

The invention discloses a question and answer type elderly health management method and device, and relates to the technical field of elderly health management. The method comprises the steps of constructing an old people group cognitive feature database, constructing a dynamic question and answer strategy library, collecting physiological, cognitive and sensory parameters in the daily activity peak period of the old people, calculating health degree coefficients corresponding to all dimensions, outputting comprehensive health scores by using a nerve attention mechanism technology, and determining the health degree of the old people according to the health degree coefficients. Dividing health levels and feeding back reports to update the strategy library; the device comprises a dynamic question and answer module, a rhythm perception scheduling module, a multi-modal data acquisition module, a health degree coefficient calculation module, a self-adaptive fusion calculation module, a health level judgment module and a closed-loop feedback optimization module. According to the invention, the accuracy of health assessment is improved, and the technical problems that traditional elderly health management lacks pertinence, multi-source data cannot be fully utilized and a management strategy cannot be dynamically adjusted are effectively solved.

The invention relates to the technical field of intelligent health monitoring, and provides a body fat scale data multi-dimensional health score calculation and generation method and system. The method comprises the steps of obtaining body data and basic information of a user; processing the body data and the basic information according to a preset multi-dimensional health scoring model; enabling each piece of body data to correspond to a scoring interval of the scoring dimension to which the body data belongs, obtaining a corresponding basic score, calculating a weighted score of each scoring dimension according to the weight coefficient of each scoring dimension, and summing the plurality of weighted scores to obtain an initial health score; and correcting the initial health score according to the basic information, and generating a final multi-dimensional health score. Aiming at the defects of singleness, no differentiation and non-dynamic health scoring of an existing intelligent body fat scale, a set of complete intelligent health assessment system is formed through multi-dimensional model construction, basic information correction and data driving optimization.

The invention discloses an occupational health analysis model construction method based on big data, and the method comprises the steps: obtaining occupational health data, carrying out the preprocessing of the occupational health data, carrying out the feature extraction, obtaining health features, labeling the health features with feature tags, and carrying out the feature extraction. Inputting the health features into the multi-modal machine learning model to obtain a health risk probability, obtaining interaction data, constructing a feature transformation matrix and a health coefficient according to the interaction data and the health features, fusing the feature transformation matrix and the health coefficient to obtain fused features, and obtaining a health risk probability; and constructing an occupational health analysis model based on big data according to the fusion features and the feature tags, and inputting occupational health data to be analyzed into the occupational health analysis model to obtain occupational health scores and health evaluations. The method not only can improve the precision and speed of occupational health analysis, but also has good interpretability, and can be directly applied to an occupational health analysis system.

Model selection is disclosed. Features used as inputs to models are scored in terms of importance and health. The importance and health scores are combined in order to generate a model score for each model. The model with a score above a threshold score is selected and deployed.

The invention discloses a gas drainer hidden danger checking method, device and equipment and a medium, and belongs to the technical field of metallurgy. The method comprises the following steps: acquiring an image and operation state data of the gas drainer, wherein the operation state data at least comprises one of temperature, pressure, liquid level and carbon monoxide concentration; determining a first health score of the gas drainer according to the image; determining a second health score of the gas drainer according to the operation state data; determining a comprehensive health score of the gas drainer according to the first health score and the second health score; and determining the hidden danger grade of the gas drainer according to the comprehensive health score. According to the method, the comprehensive health score of the gas drainer is objectively and accurately obtained by automatically and comprehensively analyzing the image and the operation state data of the gas drainer without manual participation, so that whether the gas drainer has a hidden danger or not can be checked according to the comprehensive health score.

This invention discloses a question-and-answer-based elderly health management method and apparatus, relating to the field of elderly health management technology. The method includes constructing a cognitive characteristic database of the elderly population, building a dynamic question-and-answer strategy library, collecting physiological, cognitive, and sensory parameters during peak daily activity periods of the elderly, calculating health coefficients corresponding to each dimension, outputting a comprehensive health score using neural attention mechanism technology, classifying health levels, and providing feedback reports to update the strategy library. The apparatus includes a dynamic question-and-answer module, a rhythm perception scheduling module, a multimodal data acquisition module, a health coefficient calculation module, an adaptive fusion calculation module, a health level determination module, and a closed-loop feedback optimization module. This invention improves the accuracy of health assessment and effectively solves the technical problems of traditional elderly health management lacking specificity, failing to fully utilize multi-source data, and being unable to dynamically adjust management strategies.

The invention relates to the technical field of IT resource health degree assessment, in particular to an IT resource health degree assessment method and system, and the method comprises the following steps: obtaining the number of requests of each business activity type; calculating the real-time proportion of each service activity type in the total amount of all service requests; when the real-time proportion deviates from the conventional service composition reference, identifying and quantifying a service composition abnormal event, and generating service composition abnormal event information; searching a matched adjustment strategy from a preset weight adjustment rule, wherein the adjustment strategy comprises a trigger condition, an affected index and a weight adjustment mode; calculating and applying a new weight of each business index in health degree evaluation; calculating an IT resource health score by using the new weight; and outputting the IT resource health score and the business composition abnormal event information. The accuracy and timeliness of evaluation are improved.

A system is provided.SOLUTION: A system comprising: a wearable device for acquiring health data of a user; a server means for receiving the health data from the wearable device and storing the health data in a database; an analysis means for analyzing the health data stored in the server means and calculating a health score of the user; a price calculation means for dynamically calculating an insurance premium based on the health score; a generation means for generating a suggestion for diet and exercise for improving the health score; and a notification means for notifying the user of the generated suggestion.SELECTED DRAWING: Figure 1

Embodiments of the invention provide a node election method and apparatus, a device and a storage medium. The method comprises the steps of obtaining a node index of a node; determining health degree scores of the nodes according to the node indexes; inputting the node indexes and the health degree scores into a pre-trained node fault prediction model to obtain node fault probabilities output by the node fault prediction model, and storing the node indexes, the health degree scores and the fault probabilities of the nodes in a resource lock; and if the health degree score of the master node in the resource lock is lower than a preset health degree threshold value, and / or the fault probability of the master node in the resource lock is higher than a preset safety threshold value, triggering the resource lock to execute a master selection decision. According to the embodiment of the invention, the real-time node indexes are introduced, so that the master selection decision is more fit with the actual running state of the node, and the real-time performance and reliability of the master selection decision are remarkably enhanced; according to the embodiment of the invention, the fault probability of the node is actively predicted by using the node fault prediction model, and the service interruption time caused by the fault is shortened.