4 results about "Degree matrix" patented technology

The application discloses a TBM tunneling parameter abnormal data identification method and system, and belongs to the technical field of data processing. The application constructs a polynomial chaos expansion regression model through polynomial chaos expansion, identifies abnormal data in TBM tunneling parameter data by using data clustering and polynomial chaos expansion regression error, depicts the correlation between TBM tunneling parameters through polynomial chaos expansion, compares the difference between data by using the correlation between TBM tunneling parameters, constructs a clustering objective function based on polynomial chaos expansion regression error, optimizes and solves the clustering objective function by using a Lagrange multiplier method, and obtains a TBM tunneling parameter membership degree matrix. Whether the data is abnormal is determined by using the TBM tunneling parameter membership degree matrix, and accurate identification of abnormal data of TBM tunneling parameters is realized.

This invention discloses an array ACFM detection method and system for detecting wide weld seams. The method includes: S1, establishing an AC electromagnetic field by attaching the array detection probe to the surface of the wide weld seam to be tested, and scanning along the weld seam direction; S2, synchronously acquiring multi-channel magnetic field disturbance signals using a magnetic field sensor array; S3, preprocessing and demodulating the multi-channel magnetic field disturbance signals to extract in-phase and quadrature components; S4, calculating the amplitude and phase to construct a joint feature vector; S5, constructing a similarity matrix and a degree matrix to obtain a Laplace matrix, and using an unsupervised clustering algorithm for defect classification; S6, calculating the confidence index of the classification result and comparing it with a preset threshold to determine whether crack defects exist. This invention achieves accurate determination of crack defects in wide weld seams by extracting the joint feature vector and spatial correlation features of multi-channel magnetic field signals and performing unsupervised clustering using the Laplace matrix, and then calculating the confidence index based on the classification results.

This invention discloses an intelligent notebook storage method and system based on multimodal semantic topology. The system includes: a multimodal acquisition module, a feature extraction engine, a dynamic topology construction module, an adaptive optimization module, a 3D mapper, an index manager, and a retrieval interface. By setting up a multimodal semantic topology engine, when storing multimodal note content, it ensures the accuracy of semantic association between different modal data by constructing a dynamic semantic network topology structure and generating a cross-modal association degree matrix based on a graph neural network. At the same time, it establishes cross-modal semantic association topology in real time by topologically associating the feature vectors of text, handwriting, image, and voice data, solving the problem of fragmented storage of key information, ensuring the integrity of cross-modal data association, and reducing the semantic retrieval error rate.

This invention provides a method and system for evaluating green mines, belonging to the field of mining development technology. The method includes: constructing a green mine evaluation index system and determining grading standards; constructing an index relationship network graph based on the index system, generating an adjacency matrix, calculating index degree centrality using graph theory, calculating index proximity centrality using a breadth-first search algorithm, and determining index weights based on a game theory combination of the two centralities; acquiring measured index data, calculating the cloud correlation degree of the indicators relative to each level using a cloud model, and constructing a cloud correlation degree matrix; calculating the membership degree of the mine relative to each level based on the weights and the cloud correlation degree matrix, and determining the green construction level of the mine based on the principle of maximum membership degree. This invention effectively solves the problems of excessive subjectivity, insufficient quantification, and low accuracy of evaluation results in existing technologies, and can be widely applied to the evaluation of the green construction level of various types of mines.