11results about How to "Consider comprehensively" patented technology

The invention discloses an on-orbit failure probability estimation method for a single-particle hard error of a wide bandgap semiconductor device, and aims to support on-orbit prediction of the single-particle hard error failure probability of the wide bandgap semiconductor device. Wide bandgap semiconductor devices such as silicon carbide (SiC), gallium nitride (GaN) and the like are easy to generate hard errors such as single-particle burnout and single-particle gate-through under the radiation of high-energy particles, and the risk of the hard errors in aerospace application needs to be comprehensively predicted and evaluated. Therefore, the invention provides a method for estimating the in-orbit failure probability of the single-particle hard error of the wide bandgap semiconductor device, which considers the influence of a failure section angle and particle distribution characteristics in different orbit environments, and provides data support for model selection.

This invention discloses a three-impulse control method and system applicable to chemical waste heat boilers, belonging to the technical field of boiler automatic regulation. It includes the following steps: acquiring the operating parameters of the chemical waste heat boiler; collecting and storing the boiler drum water level, steam flow rate, and feedwater flow rate; calculating the steam flow rate change rate; determining the current operating state; setting the boiler drum set water level; calculating the target feedwater flow rate using the set water level, current boiler drum water level, steam flow rate, steam enthalpy, and energy conversion coefficient; selecting a comprehensive state coefficient based on the current operation; calculating the feedwater regulation amount using the selected comprehensive state coefficient combined with the target feedwater flow rate; generating a feedwater regulation command based on the feedwater regulation amount and transmitting it to the chemical waste heat boiler. This invention has the effect of automatically and timely controlling the water level of the chemical waste heat boiler with good control stability.

This design is a multi-task automatic EEG detection and prediction system for epilepsy. The system first receives the EEG signals from epilepsy patients to be identified or the collected patient EEG signals used for training the module through a preprocessing module. The preprocessing module performs noise reduction, filtering, segmentation, and normalization on the signals, and outputs the processed patient EEG signals to the training module. In the training module, the collected patient EEG signals are used for training and testing. First, feature extraction is performed using a multi-scale convolutional network. Then, the detection and prediction branches incorporating a dual attention mechanism are trained, and the trained model parameters are saved for use in the detection and prediction module. Finally, the detection and prediction module provides detection and prediction results for the EEG signals from epilepsy patients to be identified. This invention employs a modular design, achieving real-time detection and prediction of noisy, unbalanced EEG signals, providing a reliable system for practical applications.

The application discloses a power battery monomer abnormality early warning method and device, electronic equipment and storage medium. Including: acquiring full working condition state parameters of a power battery pack; respectively storing and accumulating voltage state data of monomer batteries in the power battery pack during charging and discharging; establishing a monomer battery abnormality detection model; inputting the voltage state data into the monomer battery abnormality detection model, combining the full working condition state parameters of the power battery pack, and determining monomer batteries in an abnormal state. The early warning information can be sent before the power battery cannot be repaired, the efficiency of inspection and repair is improved, the monomer battery abnormality alarm lag is avoided, and the advance and accuracy of the new energy automobile power battery safety early warning are improved.

The invention belongs to the technical field of natural gas exploration and development, and discloses a fault control type karst residual hill weathering crust gas reservoir favorable area optimization method and related device.The method comprises the steps that well seismic data in a target area are obtained, marker beds are selected according to the well seismic data for layer position calibration, and the stratum thickness of each layer is counted; according to the horizon calibration and the stratum thickness, an impression method and a trend surface removing method are adopted to recover ancient landform and micro-ancient landform forms, and a target area weathering crust interface top surface structure and a fracture distribution diagram are compiled; and calculating an ancient landform evaluation index, a structure evaluation index and a fault evaluation index at the deployment well point according to the ancient landform, the micro-ancient landform, the weathering crust interface top surface structure and the fracture distribution diagram, solving a comprehensive evaluation index of a favorable region, and screening a favorable target region. According to the method, the relevance and interaction of different control factors are explored, a multi-factor fusion method is provided to solve the favorable area, and the method has better evaluation means and accuracy.

This invention belongs to the field of pedestrian trajectory prediction technology, and particularly relates to a method for predicting pedestrian trajectories at unsignalized right-turn intersections based on game theory. The method includes the following steps: S1, acquiring historical data on pedestrians and vehicles at unsignalized right-turn intersections; S2, analyzing the human-vehicle game factors at unsignalized right-turn intersections and constructing a corresponding human-vehicle game model; S3, inserting the human-vehicle game model into a pre-set S-GAN model to obtain an SDG-GAN model for predicting pedestrian trajectories; S4, training the SDG-GAN model using the historical data acquired in S1; S5, using the trained SDG-GAN model to predict pedestrian trajectories at unsignalized right-turn intersections in real time. This invention ensures the accuracy of pedestrian trajectory prediction at unsignalized right-turn intersections and the effectiveness of assisted driving decisions at such intersections, thus balancing the efficiency and safety of vehicles passing through unsignalized right-turn intersections.

The invention relates to a prognosis prediction model construction method and device, electronic equipment and a storage medium. The prognosis prediction model construction method comprises the following steps: determining key distinguishing features capable of distinguishing a normal region from a focus region based on a brain medical image; determining a hidden damaged tissue boundary around the focus area according to the key distinguishing features; wherein the brain tissue between the focus area and the damaged tissue boundary is a hidden abnormal blood flow tissue area which is difficult to directly detect based on a brain medical image; and constructing the prognosis prediction model based on the brain tissue characteristics in the damaged boundary. The embodiment of the invention can improve the prediction level.

The invention discloses a drug resistance gene detection system and program for beta-lactam drugs for RA, and relates to the technical field of gene detection. The drug resistance gene detection system comprises: a gene library containing drug resistance markers of beta-lactam drugs for RA; the gene sequencing equipment is used for performing gene detection on whether the to-be-detected sample contains the drug resistance marker or not and the serum type of the to-be-detected sample; and the data processing module is used for giving a drug resistance analysis report based on a detection result of the gene sequencing equipment. According to the invention, drug resistance markers and serum detection are combined, the prediction accuracy of drug resistance is high, and the method has good reference value for predicting pathological changes and prognosis after infection; the method can be applied to the fields of virus detection, risk assessment, drug research and development and the like.

This invention discloses a coupling method for aerodynamics and vehicle dynamics applicable to high-speed trains, relating to the interdisciplinary field of aerodynamics and vehicle dynamics. The method includes: establishing separate aerodynamic and vehicle dynamic models for the high-speed train; exchanging data between the two models using a dual-time-step time-progression method, improving computational time accuracy, step size, and stability. While comprehensively considering the interaction between the high-speed train and its surrounding flow field, the influence of track irregularities, and tunnel effects, a multi-region mesh generation method is adopted, improving the quality and efficiency of mesh generation. Furthermore, the overlapping mesh method avoids mesh reconstruction problems. Simultaneously, the use of six-degree-of-freedom motion velocity to reflect the attitude changes of the high-speed train simplifies the coupling steps. The entire process saves time on mesh generation, calculating the displacement of mesh nodes around the train, mesh reconstruction, and computational iterations, enabling the coupling method to be implemented quickly and on a large scale.

A kind of anti-cancer cell sensitivity prediction method, system, equipment and medium of fusion gene network relationship, method includes: the vector of the expression amount of each gene of cell line is as the original gene expression feature of cell line, compressed low-dimensional hidden vector is used as the gene expression feature of cell line by using self-encoder, graph self-encoding is carried out to gene interaction network to obtain gene interaction feature, gene network feature is calculated according to gene expression feature and gene interaction feature, the feature of each atom in drug compound molecule is obtained by establishing drug compound molecular graph, and the predicted anti-cancer cell sensitivity is obtained according to EIGA model;System, equipment and medium are used to realize a kind of anti-cancer cell sensitivity prediction method of fusion gene network relationship;The present application fully considers the interaction relationship between genes and the topological structure in compound molecule by designing new algorithm, realizes the anti-cancer cell sensitivity prediction on cell line and single cell level.

The application discloses a kind of multi-objective optimization method and system for nuclear power system sensor layout, comprising: based on directed graph theory, by analyzing fault propagation path and the correlation matrix of sensor and fault is established by the correlation of fault and sensor, and correlation matrix is improved based on actual industrial process;Establish the reliability model of sensor arrangement number and position;Based on the correlation matrix of sensor and fault, form the multi-objective optimization model of sensor optimal arrangement;Improved NSGA-II algorithm is constructed, and multi-objective optimization model is solved based on NSGA-II algorithm;Realize sensor selection and arrangement multi-objective optimization;The formed sensor selection and arrangement multi-objective optimization method is verified in nuclear power system deaerating system simulation model.The application establishes the quantitative relationship between fault diagnosis efficiency and sensor arrangement number and position, improves the fault diagnosis capability to the operating state of nuclear power equipment, and guarantees the safe operation of nuclear power station.