722 results about "Screening Result" patented technology

The invention discloses a marketing copywriting generation model optimization method and device and a storage medium, and the method comprises the steps: obtaining a to-be-optimized data model, and carrying out the incremental pre-training of a base model through marketing knowledge data, and obtaining the to-be-optimized data model; subjective indexes are screened through a preset evaluation index system, and screening results are integrated into objective indexes; constructing a sample data set based on the objective indexes, and training the data model by adopting the sample data set to obtain a target model; and generating a generation logic path of the target model by using a preset thinking chain decomposition model, and optimizing the target model through the generation logic path. According to the method, efficient injection and objective quantitative evaluation of marketing knowledge are realized by constructing a technical path combining a vertical field evaluation index system and incremental pre-training, and the technical effects of improving the brand integrating degree, the selling point accuracy and the commercial availability of the generated copywriting are realized in combination with an iterative optimization mechanism guided by a thinking chain.

The invention discloses a heterogeneous resource scheduling method and device of a cloud data center, a medium and a product, and relates to the technical field of cloud computing, and the method comprises the following steps: receiving a scheduling task of an application instance containing source architecture resource information; screening the processing nodes according to the computing power demand of the application instance and the specification reference values of the processing nodes, and determining candidate nodes according to the screening result; constructing an application performance portrait of the application instance according to the performance data of the application instance; according to the application performance portrait and the scheduling task, equivalent resource configuration corresponding to deployment of the application instance on the candidate node is determined, a score is determined based on the equivalent resource configuration and the specification reference value, and a target node is determined based on the score; and modifying the resource request of the application instance based on the equivalent resource configuration to obtain a modified resource request, and deploying the application instance to the target node, so that the target node performs resource configuration based on the modified resource request to complete heterogeneous resource scheduling. And equivalence quantization and intelligent scheduling of heterogeneous resources are realized.

The invention relates to the field of medical information processing and traditional Chinese medicine curative effect evaluation, in particular to a diabetic nephropathy traditional Chinese medicine curative effect evaluation method based on patient report outcome. The method comprises the following steps: searching related symptoms and clinical characterization data of diabetic nephropathy through a medical database, extracting target entries, performing language standardization processing, constructing an initial candidate entry set, calculating the occurrence frequency of each symptom entry, and screening entries meeting a set threshold value to form an entry set; carrying out dimension division on the entry set according to feature attributes to form a preliminary dimension structure set; forming a screening result set through preset logic screening conditions; and carrying out weighted regression fusion on the comprehensive curative effect score and clinical detection data, and outputting a patient curative effect index. In an item weight determination process, dynamic balance between subjective experience and objective statistical information is realized through a mixed weighting model, and the defects of strong subjectivity of expert scoring and large result fluctuation in a traditional method are overcome.

The disclosure describes a reading system and a reading method for fundus images, the reading system comprising: an input module for receiving fundus images; a screening module for outputting screening results based on the fundus images, the screening results at least including quality control judgment results and lesion judgment results; a first classification module for classifying the fundus images into screening qualified images and first images to be quality controlled based on the quality control judgment results, and taking at least one image from the first images to be quality controlled and the screening qualified images as an image to be quality controlled; and a quality control module for outputting quality control results based on the image to be quality controlled. According to the disclosure, the screening accuracy of the reading system can be improved.

The invention discloses a tracing method and system for atmospheric pollution in a chemical industry park, and relates to the technical field of tracing of atmospheric pollution. The method comprises the following steps: determining at least one first pollution source according to an enterprise-pollutant-raw material incidence matrix and at least one pollutant in the chemical industry park; and according to the real-time pollutant concentration data and a Gaussian diffusion model simulation result, screening out an enterprise with a relatively high fitting degree with the real-time pollutant concentration data, and according to a screening result, determining at least one second pollution source. And determining at least one third pollution source according to the position of the at least one pollution source. And determining at least one fourth pollution source in the high-concentration change area. And determining a pollution traceability result. According to the invention, multi-source data are fused to trace the air pollution, the comprehensiveness and timeliness of the data are ensured, and the accuracy of pollution traceability can be improved.

The invention relates to the technical field of automatic testing, in particular to an automatic software testing method and system based on multi-mode AI cooperation. According to the scheme, optical character recognition, voice recognition and natural language processing analysis tools are packaged into independent containers, and analysis results are input into a multi-mode semantic association model in real time; calculating the semantic similarity between the image description text and the corresponding voice transcription text; constructing a test demand complexity evaluation model; defining use case quality indexes, and establishing an error sample library to store manually labeled problem use cases and correction labels thereof; the intention demand is finally determined according to the screening result of the three-stage filter; and setting a test case template, optimizing a path according to the fusion quality, improving the case generation efficiency, and synchronously updating the optimized path to a knowledge base associated with the error sample library. According to the scheme, automatic software testing is achieved through multi-modal AI cooperation in combination with containerized deployment, model dynamic optimization and the like, and efficiency and recognition accuracy are improved.

The invention relates to the technical field of spine health, solves the problems that in the prior art, a spine posture abnormity screening mode is single, a screening process lacks grading progressive performance and a correction strategy lacks individuation, and provides a spine posture abnormity three-level screening and correction system and method. The system comprises a data acquisition module used for acquiring first original data, second original data and third original data; the primary screening module is used for obtaining a primary screening result; the secondary screening module is used for obtaining a secondary screening result according to the second original data; the third-stage screening module is used for obtaining a third-stage screening result according to the third original data; the comprehensive evaluation module is used for obtaining a comprehensive evaluation result; the correction management module is used for generating a personalized correction strategy; and the control module is used for managing the working process of each module. The invention provides a spine posture abnormity screening and correction system capable of generating a personalized spine correction strategy.

The invention discloses a storage system software defect analysis method and system based on a large model. The method comprises the following steps: firstly, collecting public and internal historical defect data and multi-source logs, training a lightweight log extraction model after cleaning, and coarsely screening original logs of newly added defects; and inputting a coarse screening result into a large language model, and further studying and judging to output a real key log. And fusing and vectorizing the key log and the Bug description, and writing the fused and vectorized key log and Bug description into Elasticsearch to construct a historical case knowledge base capable of semantic retrieval. When a new defect enters the system, quickly extracting a key log by utilizing the trained model, and executing dual-channel retrieval in the knowledge base to recall similar cases; and the big language model is combined with similar cases to automatically generate responsible person recommendation, root cause analysis and executable troubleshooting and avoiding suggestions. According to the method, the problem that historical cases are difficult to retrieve can be effectively solved, similar cases can be quickly and effectively found from massive historical data under the double-control of Bug description and key logs, and study and judgment assistance is provided.

The invention discloses a power station equipment abnormity rapid identification method based on cloud edge cooperation, and relates to the technical field of power station equipment data analysis. According to the method, firstly, edge time sequence data reflecting the real-time operation state of power station equipment is subjected to preprocessing and abnormal preliminary screening on the edge side so as to improve the timeliness of the process of uploading the data to the cloud, and then trend comparative analysis is performed based on a preliminary screening result so as to determine the fluctuation rule of the operation state. And performing multi-dimensional correlation analysis and data collaborative management at the same time to generate a visual fault risk assessment report, and finally identifying the equipment fault level according to the report and the edge-side real-time operation data, and synchronously dynamically optimizing the identification capability through cloud edge collaboration to form a complete anomaly identification process. The data transmission timeliness improvement, the clear equipment operation rule and the dynamic optimization of the identification capability under cloud-side cooperation are realized, and then the problem of compound fault missed judgment caused by non-fault fluctuation misjudgment is effectively solved.

The invention discloses a chronic obstructive pulmonary disease patient screening system for the respiratory medicine department, particularly relates to the field of computer-aided diagnosis, and is used for solving the technical problems that an existing screening method is low in screening efficiency, low in patient adaptability and difficult to popularize on a large scale in a basic level. According to the system, a standardized patient medical event sequence is constructed by obtaining a target population medical record containing medicine distribution and disease diagnosis codes; identifying a characteristic medication and diagnosis mode before definite diagnosis of the chronic obstructive pulmonary disease based on a sequence pattern mining technology; constructing a medical knowledge graph by using the modes, obtaining a feature embedding vector representing a chronic obstructive pulmonary disease medical trajectory through graph neural network learning, and establishing a high-risk digital portrait; inputting the medical sequence of the person to be screened into a feature extraction model based on same map training, and generating an individualized risk probability prediction value by calculating the matching degree of the medical sequence and the digital portrait; and a screening result report is automatically generated, so that efficient and noninvasive early risk screening is realized.

The invention relates to the technical field of GIS partial discharge high-precision three-dimensional positioning, and discloses a multi-stage iteration GIS partial discharge high-precision three-dimensional positioning method, and the technical scheme is characterized in that S1, an electromagnetic simulation model is constructed based on a GIS equipment structure, and the installation position of an ultrahigh frequency sensor is optimized through electromagnetic simulation; s2, performing wide-band adaptive sub-band reconstruction and multi-resolution feature enhancement processing on the acquired signals; s3, calculating three-dimensional focusing energy distribution by adopting a multi-band time inversion method, and extracting candidate discharge positions; s4, screening candidate positions; s5, performing multi-stage hybrid optimization on the screening result to obtain refined three-dimensional positioning coordinates; and S6, outputting a three-dimensional positioning result, and performing performance evaluation based on a confidence index. According to the method, a time delay consistency screening mechanism is introduced, false candidate points which do not conform to an actual signal propagation rule are effectively eliminated, and the accuracy and reliability of a positioning result are remarkably improved.

The invention provides an automatic training data screening method and device, electronic equipment and a storage medium. The method comprises the following steps: sequentially inputting each training sample in an original training data set into a target reference model to obtain a prediction label and a confidence value corresponding to the training sample, and generating a prediction result set; performing consistency comparison on prediction labels in the prediction result set and labeling labels of the original training data set to obtain a sample set with prediction results inconsistent with original labels; matching a preset confidence interval according to the confidence value of the training sample, calling a corresponding weight, and calculating a comprehensive score by using the confidence value and the weight; and comparing the comprehensive score according to a preset first threshold value and a preset second threshold value, grading a sample set of which the prediction result is inconsistent with the original mark, and generating a screening result containing different levels of problem samples. According to the method, the screening efficiency and accuracy can be improved, labeled error samples are quickly eliminated, and the training data quality is optimized.

The invention provides an entanglement coding quantum direct communication method and system. The method comprises the following steps: an entanglement source sends a first photon in an entanglement photon pair to a first measurement terminal machine and sends a second photon in the entanglement photon pair to a second measurement terminal machine; the first measurement terminal machine encodes the first information to obtain a first information encoding bit sequence, and selects a corresponding demodulation quantum state according to the first information encoding bit sequence to demodulate and detect the received first photon; the second measurement terminal machine carries out demodulation detection on the received second photon; the first measurement terminal machine and the second measurement terminal machine carry out basis screening and quantum channel security analysis based on a demodulation detection result, and when a quantum channel security analysis result is that a security requirement is met, post-processing is carried out according to a basis screening result to obtain a first information decoding bit sequence, and the first information decoding bit sequence is sent to the second measurement terminal machine; the second measurement terminal machine decodes the first information decoding bit sequence to obtain first information; quantum direct communication based on entanglement coding can be realized.

The invention discloses a laying hen genetic disease molecular marker screening system based on data fusion and AI prediction, the system comprises six modules, a multi-omics data acquisition module obtains laying hen genome and transcriptome data, and a FineDataLink data fusion module carries out feature alignment and association mapping to generate a fusion feature matrix; the dynamic time sequence diagram neural network processing module constructs a time sequence association diagram and outputs a time sequence feature vector, and the attention enhancement deep forest analysis module evaluates feature importance and outputs a screening result; the federal variation auto-encoder modeling module constructs a federal training framework to generate a molecular marker probability distribution model, and finally the molecular marker screening output module extracts key molecular markers. The system realizes deep fusion of multi-omics data and efficient application of an AI algorithm through multi-module cooperation, improves the molecular marker screening efficiency and accuracy, and provides technical support for disease-resistant breeding of laying hens.

The invention discloses a self-adaptive multi-dimensional evaluation high-quality scientific and technological information screening method and system, and relates to the technical field of information screening, and the method comprises the following steps: collecting data from a database by using an API interface and a web crawler technology, and establishing a multi-source data set; establishing a preprocessing data set; performing feature extraction on the preprocessed data set, and establishing a multi-dimensional feature set after standardization processing; carrying out dimension evaluation under a six-dimensional evaluation channel on the multi-dimensional feature set, and establishing a dimension score; and after the dynamic weight mapped by the dimension score is adaptively configured, weighted calculation is executed, and a scientific and technological information screening result is generated. The technical problems that in the prior art, due to the fact that the scientific and technological information screening dimension is single, the evaluation weight is fixed and different scenes are difficult to adapt, the screening result is insufficient in accuracy and comprehensiveness are solved, and the purposes of achieving self-adaptive multi-dimensional evaluation and high-quality screening of the scientific and technological information and improving the screening efficiency are achieved. And the accuracy and comprehensiveness of scientific and technological information screening are improved.

An early screening system for chronic obstructive pulmonary disease based on blood routine test data. It belongs to the technical field of digital medical treatment, and specifically relates to the technical field of intelligent early screening of chronic obstructive pulmonary disease. It solves the technical problem that the generalization ability of a COPD prediction model is limited due to differences between different research data sets. The system comprises a data collection module that collects blood routine test data of a plurality of chronic obstructive pulmonary disease patients and blood routine test data of a plurality of normal personnel; a data preprocessing module that performs standardization processing on the blood routine test data to obtain a standardized data set; a screening model training module that trains N classification models using the standardized data set and calculates the prediction accuracy of each classification model; and a screening model application module that obtains the fusion weight of each model by using a normalization processing method based on the prediction accuracy of each classification model, fuses the risk scores predicted by the multiple models, and obtains a final screening result.

The invention discloses a knowledge component retrieval method, and relates to the technical field of computers, and the specific implementation scheme is as follows: obtaining an industry query request of a user; analyzing the industry query request to obtain an analysis content including a query intention type and a key industry entity; based on the key industrial entity, performing metadata preliminary screening on knowledge components in a preset knowledge component library to obtain a first preliminary screening result; based on the key industry entity, performing semantic vector matching on the first preliminary screening result to obtain a first matching result; and based on the query intention type and the industry query request, performing service scene screening on the first matching result to obtain a target industry knowledge component set.

The invention discloses an information display frequency control method based on user behavior characteristics, relates to the technical field of information display control, is used for solving the problem of excessive pushing of display contents, and obtains similar potential groups by setting a group division mechanism for initial users. Selecting target information according to the information display duration of each group, extracting word frequency, screening representative vocabularies, screening a target group according to the representative vocabularies, displaying the information of the target group on a user interface, setting a display frequency, monitoring the browsing duration and the browsing amount of a user in real time, performing statistics, and screening out the target group according to a result. Generating an update ratio according to the screening quantity to enter a frequency adjustment mechanism, adjusting a display frequency by using the update ratio to obtain a precise frequency, monitoring a screening result in real time to judge whether to quit the frequency adjustment mechanism, and collecting user click search and active refresh times during quit to determine whether to quit the group division mechanism; user fatigue caused by information redundancy is avoided, and information utilization efficiency and resource allocation rationality are improved.

The invention relates to the technical field of supply chain management, in particular to a CBAM-based product full-life-cycle dynamic supply chain optimization method and management system, and the method comprises the steps: obtaining materials and numbers required by an outlet, building the association between raw materials and transportation links, collecting production carbon release details, and screening compliance paths to form an operation list. And judging the position overlap ratio to generate a resource path atlas, and outputting a supply chain scheduling scheme according to time consumption and span sorting. The method comprises the following steps: quantifying a geographic distance and a transportation mode in a raw material path, establishing mapping between transportation and a carbon source, identifying a carbon release path by combining an equipment operation section sequence, rejecting non-compliant paths according to target market limitation, associating a screening result with a carrying node space position, and constructing a connection combination according to a position overlap ratio. The path is optimized through time consumption and span sorting, and collaborative optimization of path screening and job scheduling is achieved.

The invention discloses an accounting risk identification and auxiliary decision-making method and system, and relates to the technical field of accounting information processing, and the method comprises the steps: carrying out the cleaning and standardization of an accounting related data flow, and generating an accounting event flow; pre-screening the accounting event flow in real time, and determining the accounting event to be verified and a pre-screening result; evidence is called according to an association rule to form a structured evidence packet, cross-modal consistency verification is executed, and contradictory evidence features are extracted; updating the entity relation graph based on the accounting event flow and the contradictory evidence feature increment, constructing a local sub-graph, and reasoning to obtain a graph risk score and a risk association path; and fusing the multi-source results to determine a risk type and a risk level, and outputting an auxiliary decision result. According to the method, the real-time performance and the accuracy are both considered, the hidden association and network type fraud recognition capability is improved, false alarm and missing alarm are remarkably reduced, manual retrieval and comparison are reduced, the time delay of evidence calling and rechecking is shortened, and the conclusion interpretability and the audit traceability are enhanced through evidence positioning and association paths.

The invention discloses a generative adversarial network optimization method for small molecule drug virtual screening, and belongs to the field of computer-aided drug design. The method comprises the following steps: constructing a small molecule drug data set; building a GAN basic model comprising a generator and a discriminator; performing multi-objective optimization training (optimizing chemical effectiveness, combining affinity and structural diversity) on the model through a joint loss function; generating candidate molecules by using the optimized model, and screening through a threshold value; and carrying out molecular docking verification on the screening result and outputting a final result. The quality of generated molecules is improved through multi-objective optimization, the drug research and development cycle is shortened, and the method is suitable for efficiently screening potential drug molecules.

The invention provides a sweet substance screening method and application, and relates to the field of sweet substance development and application, and the sweet substance screening method is characterized by comprising the following steps: providing a sweet substance, analyzing the sweet substance by adopting an electronic tongue technology and a molecular docking technology to obtain first information and second information of the sweet substance, and constructing a bimodal model at the same time, obtaining a screening result; according to the technical scheme provided by the invention, taste features of various common sweet substances are analyzed in a mode of combining an electronic tongue technology and a molecular docking technology, so that taste feature differences of the sweet substances and sucrose can be effectively compared; a machine learning prediction model based on taste attribute values of nine electronic tongue sweet substances and four molecular docking characteristic values is established, and sensory evaluation is used for verification; sweet substances similar to cane sugar in taste are rapidly screened, and the screening accuracy is improved. Based on the method, a thought is provided for excavation and development of novel sweet substances.

The invention relates to the technical field of steel pipe concrete structure detection, in particular to a method for detecting fatigue damage of a steel pipe concrete correction structure for waste incineration power generation. The ultrasonic detection signals under different primary frequencies are subjected to comparative analysis of signal intervals with different amplitude changes, and the ultrasonic detection signals under different frequencies are subjected to targeted filtering optimization processing based on analysis results, so that the accuracy of damage information judgment under different frequencies is comprehensively evaluated. Accurately screening ultrasonic detection signals in the detection process of the correction structure according to an evaluation result, and obtaining a fatigue damage detection result of the correction structure based on a screening result; the accuracy of fatigue damage information judgment of the correction structure is improved, and the detection performance of the concrete filled steel tube correction structure at different positions is improved.

The invention relates to the technical field of information retrieval, in particular to an intelligent screening method based on multi-source data, which comprises the following steps: acquiring high-frequency time sequence data of a first data source, and dividing the high-frequency time sequence data into a state change interval and a state stable interval; extracting dynamic features from the state change interval, extracting statistical features from the state stable interval, and generating a pattern feature cluster sequence; acquiring low-frequency data of a second data source, acquiring a timestamp as an anchor point, acquiring a precursor node and a subsequent node of a mode feature cluster in combination with the mode feature cluster sequence, and generating an anchor point association map; executing bidirectional prediction verification based on the anchor point association graph, calculating a bidirectional consistency score, and generating an alignment confidence label; and monitoring incremental updating of high-frequency time sequence data, performing reverse prediction verification again, updating and aligning confidence labels, screening anchor point association records with high confidence, performing fusion processing on low-frequency data features and mode feature clusters, and outputting a screening result.

The invention provides a power battery echelon utilization evaluation method, device and equipment and a storage medium, and the method comprises the steps: carrying out the first qualified battery screening of a to-be-evaluated battery based on historical traceability information, and carrying out the second qualified battery screening of the to-be-evaluated battery based on real-time monitoring data, determining the non-destructive grade of the cascade utilization of the to-be-evaluated battery according to the two screening results; performing performance test on the to-be-evaluated battery based on the electrical test data, the electrochemical test data and the electrical property test data to obtain a test grade of echelon utilization of the to-be-evaluated battery; and performing consistency evaluation on the to-be-evaluated batteries under the condition that both the nondestructive grade and the test grade meet preset conditions, and sorting the to-be-evaluated batteries based on a consistency evaluation result. According to the method, the nondestructive grade is determined through two times of screening, and the performance test is further performed, so that the accuracy of power battery echelon utilization evaluation is improved.

The invention discloses a topological structure simplification system, method and device of a power system and a medium. The system comprises an input module and a simplification module. The input module is used for a user to input data file information of the power system; the simplification module comprises the following steps: constructing a topological structure model according to the data file information and determining an initial reserved node set; determining a to-be-screened node set according to the node features of each node in the topological structure model, removing the to-be-screened node set and the corresponding associated edges from the topological structure model to obtain a plurality of first augmented sub-graphs, and performing hierarchical screening on each first augmented sub-graph based on the first node number to obtain a screening result, determining an elimination node set and a boundary node set based on the screening result and the initial reserved node set; and generating a node admittance matrix based on the elimination node set and the electrical relationship, simplifying the node admittance matrix, and outputting a simplified target topological structure model. According to the invention, the complexity of the power grid topology model can be reduced.

The invention relates to the technical field of knowledge maps, in particular to an intelligent decision support method fusing service knowledge maps, which comprises a data access module used for collecting structured or semi-structured service data from a service system, and a knowledge map construction module used for constructing a knowledge map based on the standardized service data. The business knowledge graph is used for constructing an attribute graph model, the path optimization module is used for screening the causal chain path set, and the result output module is used for displaying the sorted candidate scheme set to a user through a visual component and receiving user feedback information; and the feedback optimization module is used for, according to the user feedback information, the intelligent decision support system fusing the business knowledge graph provided by the invention aims to overcome the technical bottlenecks of static lagging of the knowledge graph, subjective reasoning evaluation, opaque process and lack of self-optimization ability in the prior art.

This application relates to the field of data processing technology, and discloses a method, system, and storage medium for screening marketing locations. The method includes: collecting multi-dimensional data through a monitoring system and calculating quality assessment indicators; extracting user characteristics to build profiles and calculating matching degrees; predicting effects by combining operational data; screening locations based on predictions and assessments; monitoring and analyzing the screening results, and dynamically adjusting to obtain an optimized solution. This application achieves multi-dimensional assessment of shopping mall quality, accurate matching of user profiles, and dynamic optimization of screening results, thereby improving the scientific nature and success rate of merchants' site selection decisions.

The invention relates to the technical field of tumor marker detection, in particular to a breast cancer lung metastasis related biomarker screening system which comprises a differential genetic factor mining module, a function association module, a verification screening module, an interference elimination module and an optimization integration module. According to the method, the candidate genetic factors highly associated with lung metastasis are extracted, and the expression fluctuation characteristics are combined to carry out difference analysis, so that the preliminary screening accuracy is improved, pathological information and pathway annotation are integrated to construct an action network, pathway weights are analyzed, and functional expressions of the candidate factors are quantitatively evaluated; an independent sample is called to verify transcription consistency and clinical relevance, interference factors with poor repeatability are eliminated, non-tumor tissue high-expression interference items are rejected in combination with background transcription characteristics, the specificity and adaptability of screening results are improved, and finally a marker set with metastasis mechanism indicating significance and prognosis prediction value is formed through comprehensive evaluation. And clinical transformation support is provided for identification of lung metastasis of breast cancer.

The invention discloses a low-abundance organism screening and abundance gradient model construction method and device. The screening method comprises the following steps: preprocessing a biological sample; collecting optical image data of the biological sample, collecting a spectral range of the biological sample, and performing cross-modal alignment according to the optical image data and the spectral range; performing edge sharpening compensation processing on optical image data of a biological sample, monitoring an SNR value of a weak peak region of a Raman signal baseline, and triggering dynamic threshold compensation processing of laser power when the SNR value is smaller than a set threshold so as to obtain low-abundance related data; inputting a two-channel abundance gradient model, calculating an environmental factor contribution degree based on a node splitting gain of a regression tree, and dynamically allocating a bimodal feature weight by using an attention mechanism to obtain an importance score of a bimodal feature; and drawing an SHAP value three-dimensional thermodynamic diagram, and outputting a biomarker screening result. According to the scheme, the performance index of biological abundance analysis can be remarkably improved.