2 results about "Nonlinear classifier" patented technology

The invention provides a method and a system TGrKCMI for predicting interaction between circRNA (Ribonucleic Acid) and miRNA (Micro Ribonucleic Acid). According to the method, a pre-training model is used for extracting sequence features of circRNA and miRNA, and redundant information is reduced through PCA dimension reduction; then, a multi-head attention module with a gating mechanism is introduced to encode sequence features, and the expression ability of key information is enhanced; on the basis, a circRNA-miRNA interaction diagram is constructed, and robust diagram feature learning is realized in combination with diagram attention convolution of random feature masks. And finally, a kernel-based adaptive nonlinear classifier is adopted to carry out modeling on the fusion features, and high-precision and high-robustness interaction prediction is realized.

This application relates to a method and system for risk early warning of geotechnical infrastructure based on a multi-scale damage model. The method includes: acquiring environmental monitoring data of a target geotechnical area based on a preset monitoring scale; transforming the environmental monitoring data into a multi-scale damage model through multi-scale coupling analysis modeling; extracting spatiotemporal features of damage from the multi-scale damage model using a pre-trained convolutional neural network, and determining risk patterns by matching with a preset risk pattern library; inputting the spatiotemporal features of damage and risk patterns into a pre-trained risk diffusion probability prediction model to obtain risk propagation prediction results; constructing a multi-dimensional risk decision boundary using a nonlinear classifier based on the risk patterns and risk propagation prediction results; and generating graded early warning instructions through preset dynamic risk decision rules. This method can achieve accurate and dynamic early warning of risks to geotechnical infrastructure, preventing safety accidents caused by multi-scale damage evolution.