12results about How to "Reliable output" patented technology

The invention provides an AI-based aerial work engineering entity quality defect identification method and system, and the method comprises the steps: constructing a quality defect sample library, and building a standard database; associating information in the standard database with the standard image data, extracting target features from the standard database, and merging the target features with the standard image data; using supervised learning to train an image recognition model according to the data label; data are collected from the standard database and the real-time image data and provided for the image recognition model for prediction and inference; and carrying out cross validation on an output result of the image recognition model and information in a standard database, wherein the output result contains corresponding database information. The system comprises a data processing module, a model construction module and a result output module. According to the method, the quality defect of the aerial work engineering entity can be efficiently identified, the working efficiency and quality are improved, and important decision support is provided for quality control.

Provided is a module output electrode structure. The structure includes: an output electrode base (1), and an output electrode inserter (2) fixedly connected to the output electrode base (1). A base busbar (100) is provided on the output electrode base (1). An inserter busbar (200) in an electrical connection with the base busbar (100) is provided in the output electrode inserter (2). One end of the base busbar (100) is formed as an adapter end (50) protruding from the output electrode base (1). One end of the inserter busbar (200) extends out of the output electrode inserter (2). The adapter end (50) and the output electrode inserter (2) are offset at two sides of the output electrode base (1), respectively. The module output electrode structure not only has good electrical connection performance and use safety level, but also reduces a size of an output electrode and improves safety in the event of high-voltage crush.

The invention relates to the field of network public opinion data change analysis, in particular to a time sequence analysis-based network public opinion data change analysis method, which comprises the following steps of: acquiring network public opinion data characteristics by utilizing real-time network public opinion data; according to the real-time network public opinion data and the network public opinion data characteristics, establishing a network public opinion time sequence data chain based on time sequence analysis; and obtaining a network public opinion data change analysis result according to the network public opinion time sequence data chain, introducing time sequence analysis into change process processing, establishing an analysis basis by extracting multiple features of the network public opinion data and various hardware addresses associated with the features, and subsequently performing multi-moment multi-feature cross judgment and screening, so that the network public opinion data change analysis result is obtained. The change condition of the network public opinion data is obtained through step-by-step analysis, the change part is selected in a targeted mode, the public opinion data change screening efficiency is improved, and it is ensured that the final output result is stable and reliable.

This invention provides a method and system for dynamic project budget management based on multi-source data fusion in the field of project management and artificial intelligence. The method includes: Step S1, acquiring a large amount of historical project budget management data to construct a dataset for training a project budget management model; Step S2, collecting real-time project budget management data and inputting it into the project budget management model to obtain a real-time project budget management report, encrypting the real-time project budget management report into an encrypted report for storage, and sending a budget adjustment notification to the management terminal; Step S3, after receiving the budget adjustment notification, the management terminal performs an authentication operation with the budget management server to access the budget management server, decrypts the encrypted report through the budget management server to obtain the real-time project budget management report, and performs dynamic project budget management based on the real-time project budget management report. The advantages of this invention are: it greatly improves the timeliness, accuracy, reliability, and security of project budget management.

The invention provides a loan repayment capability prediction method and a related device, and relates to the technical field of data analysis. K neighbors of personal loan information are determined by using a distance value of a feature space matrix based on a loan application condition and a loan repayment condition, and the k neighbors are screened based on a Jaccard similarity coefficient; the method comprises the following steps: screening a loan application, constructing a priori knowledge matrix based on a screening result, training an initial prediction model by adopting the priori knowledge matrix to obtain a target prediction model, and predicting the newly obtained loan application by adopting the target model, so that an output result of the target prediction model is more reliable and higher in accuracy.

The invention discloses a tin-based flame-retardant polymer composite material based on artificial intelligence and a design method thereof. The method comprises the following steps: S1, constructing a flame-retardant property data set of the flame-retardant polymer composite material; s2, constructing a random forest regression model; s3, screening a flame-retardant polymer composite material; and S4, verifying the performance of the candidate flame-retardant polymer composite material. The tin-based flame-retardant polymer composite material with excellent flame retardant property is designed by adopting an artificial intelligence design strategy, the flame-retardant polymer composite material with specific LOI and TS properties at the same time can be obtained, and the flame-retardant polymer composite material with multiple synchronous and excellent properties can be rapidly, efficiently and accurately designed; and the requirements of industrialization development of the tin-based flame-retardant polymer composite material are met.

The invention discloses an egg yolk oil release rapid detection method based on photoelectric acquisition and multi-index fusion. According to the method, various characteristic indexes of the yolk in the pickling process are collected through spectral absorption signals and electromagnetic relaxation characteristics, a multi-dimensional characteristic system of an oxidative damage index, a structural collapse index and a water migration index is constructed, a three-layer structured prediction model is provided, and quantitative correlation is established between photoelectric characteristics and yolk oil release behaviors; and rapid prediction of egg yolk oil release is realized. Meanwhile, by combining a multi-index fusion strategy and model interpretability analysis, the stability and reliability of a prediction result are improved. The method can be used for quality control and product grading in the salted egg yolk production process, and has remarkable industrial application value. The method is suitable for online monitoring and product quality grading in the salted egg yolk processing process, and has remarkable industrial application value.

This invention provides a quantum computing method based on fuzzy processing, relating to the field of quantum computing technology. The method includes: inputting the fuzzy quantum state into a quantum circuit containing at least one quantum logic gate operation to obtain an output quantum state; performing continuous weak measurements on the qubits during the operation of the quantum circuit to obtain imprecise error information; processing the imprecise error information based on fuzzy mathematics to obtain error estimation parameters; generating and applying feedback operations to the qubits based on the error estimation parameters to suppress errors; measuring the output quantum state and determining the output result according to a preset probability threshold interval, where the probability threshold interval is used to distinguish different output categories. This invention can also be further combined with quantum error correction to achieve long-depth quantum computing using error correction methods, realizing effective quantum state stability control.

The application discloses a kind of early warning methods for monitoring the degree of brain edema of epilepsy children based on disturbance coefficient, to solve the problems that existing monitoring means is difficult to continuously track disease evolution, is easily disturbed by body movement and lacks individualized determination standard.The application identifies and excludes body movement artifact points by combining motion vector data, after exponential weighting smoothing to effective data, individualized reference disturbance coefficient is established in initial stable period;At the same time, according to the age interval of the children and the sleep / wake state, the corresponding threshold group is dynamically called, the deviation rate, the change rate and the change acceleration of the disturbance coefficient are calculated, and the early warning level is output according to the hierarchical determination rule of continuous sampling points.The application integrates artifact control, individualized foundation, state adaptive threshold and multi-dimensional trend determination, realizes stable, continuous and sensitive early warning of the degree of brain edema of epilepsy children.

The invention provides a traditional Chinese medicine genuine identification method, system and device based on an artificial intelligence fusion multi-omics technology, a medium and a program product, and relates to the field of medicinal material identification. The method comprises the following steps: acquiring metallomics data and metabonomics data of a medicinal material to be detected; calculating CPS response values of key feature elements in the metal omics data; processing the metabonomics data to obtain mass spectrum data of peak information of key chemical components in the data; and inputting the CPS response values of the key characteristic elements and the key chemical component peak information into a genuine production area identification model to obtain a classification result of whether the key characteristic elements belong to genuine production areas or not. The invention also discloses a key characteristic element of Ca contained in metallomics data and key peak information of a peak 17307 contained in metabonomics data. According to the method, through combination with machine learning, rapid capturing of complex system features is realized, a high-precision classification model is established, and traceability of traditional Chinese medicine genuine features is realized.

The invention discloses a blood glucose control system and control method based on a closed-loop technology, the blood glucose control system comprises a dynamic blood glucose monitoring system, an insulin pump and a central algorithm control system, the central algorithm control system comprises a storage recording module, a database access module and an algorithm module, the database access module outputs an insulin injection unit A1 or a carbon water intake amount B1, and the database access module outputs the insulin injection unit A1 or the carbon water intake amount B1; the algorithm module outputs an insulin injection unit A2 or a carbon water intake amount B2, and the database access module and the algorithm module output are combined to carry out optimization calculation on the algorithm module to obtain a final insulin injection unit A3 or a final carbon water intake amount B3. According to the blood glucose control system and control method based on the closed-loop technology, through optimization processing of the insulin injection unit A1 or the carbon water intake amount B1 output by the database access module and the insulin injection unit A2 or the carbon water intake amount B2 output by the algorithm module, the output result is more accurate and reliable, so that the blood glucose of a user is efficiently adjusted, and the user experience is improved. And user life quality is ensured.

The invention discloses a self-adaptive retrieval surveying and mapping quality inspection method based on knowledge graph enhancement, and the method comprises the following steps: S1, constructing a lightweight quality inspection knowledge graph, extracting a clause number, an inspection element and a threshold value, and binding a document anchor point; s2, performing entity identification and standardization processing on the user input, generating a standardization query and identifying a query intention; s3, retrieving the evidence in parallel in the text channel and the knowledge graph channel and obtaining an evidence score; s4, generating an initial candidate answer, calculating a support degree, and executing controlled knowledge graph migration to supplement evidence when the support is insufficient; s5, forming an evidence packet and generating candidate answers; s6, an evidence guardrail is applied, and consistency checking is executed; s7, outputting a traceable result of the number and the page number of the embedded terms; according to the method, through dual-channel retrieval, error perception evidence mending and evidence guardrail mechanisms, clause retrieval integrity and reasoning stability are improved, illusion and wrong reference risks are reduced, and it is ensured that a final result can be accurately traced according to clause sources.