6 results about "Gravitational search algorithm" patented technology

This application discloses a transformer condition monitoring method, device, and electronic equipment, relating to the field of power equipment. It involves sequentially performing data normalization, outlier detection, and missing value processing on the acquired raw transformer data. The correlation between various features in the preprocessed data is analyzed, and the preprocessed data is divided according to the analysis results to obtain feature data characterizing transformer condition changes. A prediction model is invoked to extract and predict features from the feature data, obtaining feature prediction data for a preset future time period. Key feature data is extracted from the feature prediction data using a feature selection algorithm, and a fault identification model is invoked to perform fault identification processing on the key feature data. The fault identification model is obtained by optimizing an artificial neural network model or support vector machine based on a gravity search algorithm. By performing multiple data processing and filtering processes from data preprocessing to model prediction, the reliability and accuracy of subsequent model predictions are ensured.

The invention discloses a dam break omen method based on gravitational search and a double-branch converter, and relates to the technical field of dam break, and the method comprises the steps: carrying out the preprocessing of a pre-obtained multi-source remote sensing image data set; constructing an initial feature set, and performing feature subspace optimization on the initial feature set by adopting a gravitational search algorithm; constructing a double-branch converter model, inputting the optimal feature subset into the double-branch converter model, and embedding the optimal feature subset into a gravitation coefficient matrix; mapping the fragment-level abnormal heat map into dam body pixel-level, section-level and reservoir-level space grids; cutting the double-branch converter model, distributing an edge lightweight subnet model to an edge node, receiving a hierarchical confidence map, and uploading the hierarchical confidence map to a cloud node; reasoning is carried out at the cloud node, and dam break early warning is carried out. According to the method, cross-modal correlation modeling under time dynamic is realized, texture details of a local area and the displacement trend of the dam body can be distinguished more finely, and the detection capability of progressive micro-deformation of the dam body is improved.

The application discloses a kind of complex product function structure configuration equilibrium solving method considering parameter misalignment, comprising: the direct influence interval matrix between the construction product function structure attribute;Design consensus reaching process measures the judgment of expert group and establishes updating mechanism;Affine arithmetic is used instead of interval analysis to avoid interval dependency problem;The reliable weight of product function structure attribute is calculated by improving DEMATEL method;The product function structure configuration equilibrium multi-objective optimization model considering parameter misalignment disturbance is constructed;Three kinds of intelligent optimization algorithms, improved gravity search algorithm based on adaptive mechanism, improved hybrid gravity search and differential evolution algorithm and projection gradient descent algorithm, are designed to solve the model and obtain the optimal configuration solution of product function structure.The application can effectively handle the parameter misalignment problem caused by cognitive uncertainty, and improve the reliability and balance of product function structure configuration.

This invention proposes a cooperative search method for underwater unmanned underwater vehicles (UUVs) based on an improved gravity search algorithm, relating to the field of UUV search. The method includes: deploying multiple virtual particles within the search area to form a gravitational field; dynamically updating the mass and orientation preference states of each particle during the search process; calculating the basic gravitational force acting on each UUV and performing orientation-sensitive corrections to obtain the total attractive force; calculating the repulsive force between the UUVs and modulating the repulsive force to obtain the total repulsive force; synthesizing the total attractive and repulsive forces to obtain the total resultant force, resulting in a new course and velocity; updating the position of the UUVs based on the new course and velocity, detecting and avoiding search area boundaries and obstacles, and updating the state of the detected particles. This invention achieves efficient adaptive cooperative search of an underwater UUV swarm by constructing a gravitational field using virtual particles.

The application discloses a power task allocation and optimization method and system, and belongs to the technical field of power Internet of Things. The method comprises the following steps: obtaining a calculation task generated by a business terminal; extracting a feature vector T of the calculation task through an edge access point or an edge node controller; periodically broadcasting a resource state vector S of each edge node, and quickly matching the feature vector T of the task with the resource state vector S of a peripheral available edge node based on a fuzzy logic edge node resource state; modeling the feature vector T of the task and the resource state vector S of the peripheral available edge node as a dynamic system, and performing dynamic collaborative task allocation based on an improved gravity search algorithm; and unloading the task to a target edge node for execution according to the allocation result. The application has the effects of real-time response to network and load changes, accurate satisfaction of multi-dimensional quality requirements of power business, and realization of task allocation and optimization with the globally optimal efficiency of edge clusters.

The present application relates to the technical field of electric data processing, more particularly, the present application relates to a conference content context-aware question and answer retrieval method and system for continuous conferences, comprising: acquiring multi-session conference text data of continuous conferences and user input retrieval requirements; performing vectorization processing on the conference text data and the retrieval requirements to obtain conference content vectors and retrieval vectors; and calculating semantic similarity of each session conference and the retrieval requirements.The present application constructs theme consistency drift index and time-effect correlation saturation, accurately quantifies evolution and turning point of conference theme and actual value of historical information, and on this basis, uses context correction coefficient to improve the gravitational search algorithm, so that the search process can dynamically adjust the gravity according to the context correlation strength, thereby effectively excluding obsolete information and achieving accurate and time-effective knowledge retrieval in long-span and complex logic continuous projects.