7results about How to "Rich connotation" patented technology

The invention belongs to the technical field of distributed energy storage control, and discloses an optimized operation method and system for a multi-network-constructed energy storage system, and the method comprises the steps: carrying out the equivalence of the multi-network-constructed energy storage system, and obtaining an equivalent energy storage system; wherein the equivalent energy storage system comprises an isomorphic network-following converter, an equivalent impedance R and an ideal voltage source which are sequentially connected in series; based on the equivalent energy storage system, obtaining a small signal stability boundary condition by adopting a Routh criterion; and taking the minimum operation cost as an objective function, solving the objective function under operation constraints including small signal stability boundary conditions, and obtaining J and D of each network construction type converter at different moments, so that each network construction type converter operates under the corresponding J and D. The method is suitable for optimized operation configuration of an energy storage system comprising a plurality of network following-constructing converters, and can effectively promote advantage complementation of renewable energy sources and energy storage, thereby improving system stability and operation economy.

The invention discloses a rumor detection method and system based on a multi-layer coding network, which belongs to the field of natural language processing, and comprises the following steps: obtaining all texts to be detected and preprocessing the texts; embedding word fragments with a marked vocabulary into the preprocessed texts, converting words in the texts into token marked words, and then performing vector encoding to obtain word vectors corresponding to each text; processing all word vectors to obtain input vectors; inputting the input vectors into a pre-trained multi-layer coding network to generate output vectors; processing the output vectors to obtain hidden state vectors; sending the hidden state vectors into a hidden layer and a classifier to obtain the probability that the text to be detected is detected as each rumor category, and the category with the highest probability is the detection result of the text; the problems of slow training speed and poor effect are effectively alleviated, the learning of word and sentence level information is realized, the relationship representation between different texts is extracted, and the accuracy of rumor detection is improved.

The invention discloses a digital human live broadcast strategy generation method and device, computer equipment and a storage medium. According to the specific implementation scheme, the method comprises the following steps: calculating the association degree of an associated live video and a current live video in a preset time interval based on a multi-modal association degree calculation mode, and obtaining an association degree calculation result; determining a dynamic digital human model corresponding to the associated live video according to a predetermined basic digital human model and the association degree calculation result; and determining a fusion live broadcast strategy according to the basic digital human model, the personalized digital human model and the dynamic digital human model. According to the method, the fusion live broadcast strategy is determined according to the digital human models corresponding to the multi-dimensional data, dynamic changes in a live broadcast scene can be well adapted, a comprehensive live broadcast decision is made in time, and differentiation of the digital human models is further considered through multi-modal correlation degree calculation, so that the live broadcast effect is improved.

The invention relates to a data processing method, a business system and a storage medium. The method comprises the steps that in response to an execution request sent by a target object for a target task, a first state machine cluster determines a first class matching state of the target object based on the target object and a plurality of first candidate objects; when the first type of matching state indicates that the object is successfully matched, the second state machine cluster determines a corresponding intention state based on the current operation information of the target object; and when the first type of matching state indicates that the object matching fails, the third state machine cluster determines a second type of matching state of the target object based on an object matching result of the auxiliary server, and when the second type of matching state indicates that the object matching succeeds, the third state machine cluster determines a second type of matching state of the target object. And determining a corresponding intention state based on the current operation information of the target object by using the second state machine cluster. According to the invention, the stability and disaster recovery capability of the service system are improved. The embodiment of the invention can be applied to various scenes such as cloud technology, artificial intelligence, intelligent transportation, intelligent entertainment and the like.

The invention discloses an embedded test software component library facing hardware interface and a design method thereof, comprising a file system, a database system and a component description file; the file system is used to store source files of test software components; wherein the source files of the test software components are developed according to the embedded test software component model facing hardware interface; the database system is used to store preset typical information of different types of test software components by using different data tables according to the types of test software components; the component description file is used for linking between the file system and the database system; specifically, the preset key information associated between the file system and the database system is described by XML description language; the invention adapts to the traditional software development mode, realizes the reuse of source code level, and can provide better support for the high-quality and high-reliability development of embedded software.

This invention relates to the field of data processing technology, and in particular to a method and system for matching questions and answers in innovation and entrepreneurship coaching. It includes constructing and analyzing dynamic user profiles based on user data, and combining current coaching questions with the dynamic user profiles to classify questions and deduce the user's true intentions. Compared to existing technologies that typically rely solely on direct user questions or simple interaction history to understand needs, failing to reflect the user's true capabilities and the root causes of problems, this invention systematically integrates multi-source information such as user-uploaded project documents and historical behavioral data. Through attribution analysis and capability assessment models, it dynamically constructs a structured profile containing capability maps, core challenges, and their root causes. This approach enables the system to go beyond surface-level issues, deeply understanding the user's true situation and inherent weaknesses, laying a solid cognitive foundation for providing highly personalized coaching.

The present invention is a method for topological optimization of automobile structure collision based on model order reduction. It is divided into a decomposition domain, an analysis domain, a transformation domain and a design domain. In the decomposition domain, the collision model is divided into a linear part and a nonlinear part, the nonlinear part is not processed, the linear model is reduced in model order, and the reduced-order stiffness matrix is ​​output; in the analysis domain, the nonlinear part and the reduced-order stiffness matrix are coupled to perform collision analysis to reduce the calculation cost of the structural collision analysis, and the collision response and model parameters are output at the same time; in the transformation domain, according to the collision model parameters and the collision response, the nonlinear dynamic model involved in the structural collision analysis is converted into a linear static model and output; in the topology optimization field, the static model is topologically optimized according to the preset optimization parameters, the optimal model is output, and the next cycle is entered; the entire optimization process is repeated until the optimization process meets the preset convergence conditions, then the optimization process is terminated and the optimization result is output.