6results about How to "Ease complexity" patented technology

The invention discloses a sequential causal-driven meteorological disaster prediction method, and belongs to the field of causal relationship discovery and meteorological disaster prediction. According to the specific scheme, the method comprises the following steps: preprocessing time series data of meteorological disasters to obtain an optimal lag window and an optimal data length; dividing the meteorological data into a plurality of meteorological data segments with the same length according to the optimal lagging window and the optimal data length; respectively applying a time sequence causal relationship discovery method to the divided meteorological data segments to obtain window causal structure diagrams; and fusing the causal structure diagrams in the plurality of data fragments in an ensemble learning mode to obtain a globally consistent time sequence causal structure diagram. In meteorological disaster prediction, the time sequence causal relationship between disaster risk levels and key meteorological factors in meteorological data can be mined, the accuracy of meteorological disaster prediction by a meteorological institution is improved, and effective prevention of meteorological disasters is realized.

The present invention relates to a lightweight encrypted traffic analysis method and system based on a distillation representation model, comprising: obtaining an original data set of encrypted network traffic, performing unified processing on the data in the original data set and then dividing it according to a set ratio to generate various sample data sets; inputting pre-trained samples into a BERT model based on representation learning for pre-training to obtain a pre-trained model, inputting fine-tuning samples into the pre-training model for detailed task training to obtain a traffic classification teacher model; using a knowledge distillation method of multi-layer jump fusion learning to extract teacher information of the traffic classification teacher model, and inputting fine-tuning samples into a lightweight traffic analysis model for training; inputting test samples into the lightweight traffic analysis model to realize end-to-end target network encrypted traffic classification tasks; while ensuring classification accuracy, reducing analysis resource requirements, and facilitating the realization of online low-consumption encrypted traffic classification functions in delay-sensitive resource-constrained network scenario nodes.

The present invention discloses a complex signal field recovery system based on native optical carrier, including a transmitting end digital signal processing module, a digital-to-analog converter, an electro-optical modulator, an optical fiber link, an optical coupler, a dispersion element, a photodetector, an analog-to-digital converter and a receiving end digital signal processing module; the transmitting end digital signal processing module performs nonlinear pre-compensation and DC bias correction of the electro-optical modulator; the electro-optical modulator converts the electrical signal from the digital-to-analog converter into an optical signal carrying target information, and generates a native optical carrier at the same time; the dispersion element performs dispersion on the optical signal passing through; and the receiving end digital signal processing module performs signal recovery operations. The present invention also discloses a complex signal field recovery method, including the following steps: electro-optically modulating an optical carrier signal using an electro-optical modulator with a finite extinction ratio; receiving an optical signal using a phase recovery receiver; and performing signal field recovery based on an improved Gerchberg‑Saxton algorithm in the receiving end digital signal processing module.

The present invention belongs to the field of image classification technology, and specifically relates to a class-level relationship constraint and structured graph enhancement method, system, medium and terminal. Clustering is used to construct the visual representation distribution of the data set image, and a hierarchical structured relationship is constructed based on the distribution information; the typical batch construction process is extended under the guidance of the relationship, and the associated knowledge is hierarchically aggregated through graph smoothing operations to enhance the representation learning ability of the model in a guided knowledge manner; a sampling strategy based on visual distribution is designed to construct intra-class and inter-class constraints, and at the same time, the course construction and class-level distribution regularization operations are combined to further explicitly enhance the visual representation. Finally, the enhanced visual representation is used for classification tasks, thereby improving the visual classification effect. This innovative method provides an effective solution to the visual classification problem by deeply mining and utilizing the distribution information of the visual representation.

This invention discloses a forward-transmission distributed optical fiber vibration sensor based on time-division multiplexing, belonging to the field of distributed optical fiber vibration sensor technology. It includes: a laser, a first optical coupler, an optical modulator, a first circulator, a second optical coupler, a time-division multiplexing structure, and a photodetector. The output of the laser is connected to the input of the first optical coupler. The output of the first optical coupler is connected to the inputs of both the optical modulator and the second optical coupler. The output of the optical modulator is connected to one end of the optical fiber under test via the first circulator. The other end of the optical fiber under test is connected to the time-division multiplexing structure. One end of the optical fiber under test is also connected to the input of the second optical coupler via the first circulator. The output of the second optical coupler is connected to the photodetector. This invention alleviates the technical problems of high system complexity and high implementation cost in existing technologies.

The application discloses an elevator power-off emergency rescue device, method and elevator. The device comprises a control module, a storage battery, a voltage boosting module, an auxiliary source module and a relay module. The auxiliary source module is connected with commercial power and connected with the control module through the relay module. The control module is used for adjusting the state of the relay in the relay module according to the state of the commercial power, and determining whether to connect the commercial power to the elevator control cabinet or connect the storage battery and the voltage boosting module to the elevator control cabinet. The storage battery is connected with a frequency converter of the elevator control cabinet through the relay module. The storage battery is connected with the voltage boosting module. The voltage boosting module is connected with an integrated power source of the elevator control cabinet through the relay module. The application is beneficial to reducing the complexity of the emergency rescue equipment and improving the working reliability. The application can be widely applied in the elevator control technical field.