8 results about "Community structure" patented technology

The application discloses a stable anti-reversibility microbial community structure and a construction method and application thereof, and relates to the technical field of microbial community construction, and in particular to a stable anti-reversibility microbial community structure and a construction method and application thereof.

The application belongs to the technical field of comprehensive energy optimization operation, and provides a comprehensive energy optimization control method and system based on community game, comprising: obtaining a directed weighted graph of comprehensive energy; taking all nodes in the obtained directed weighted graph as game participants, and constructing a detection model based on community game; hierarchically solving the constructed detection model based on community game to obtain single-layer community structure; merging the obtained single-layer community structure to form comprehensive energy community structure; performing cooperative game benefit distribution in the formed comprehensive energy community structure, processing multi-objective optimization priority through a hierarchical sequence method to obtain optimal weight coefficients and income distribution of all nodes, and completing optimization control of comprehensive energy based on community game.

This invention discloses a federated graph synthesis method and system based on a differential privacy model, belonging to the field of federated learning technology. It is applied to a federated graph synthesis system comprising one server and multiple clients. The method includes a community detection stage, an information extraction stage, and a graph reconstruction stage. This method achieves global graph synthesis that satisfies edge differential privacy without centralized original sensitive edge data or cross-client interaction of original data, thus ensuring data privacy from an architectural perspective. It designs a noise-resistant edge statistics mechanism between supernodes, converting the weighted supernode graph into an unweighted undirected graph to reduce the impact of high noise on community detection in federated scenarios. It also designs a local community optimization mechanism to improve the accuracy of community structure detection. Furthermore, it proposes a fine-grained edge construction strategy, adaptively stopping client contribution value collection based on the connection strength of supernode pairs. Finally, it designs a heterogeneity-aware information extraction mechanism, allocating differentiated privacy budgets based on edge participation patterns.

This invention provides an offline community detection method for software ecosystems based on co-evolutionary optimization. Software ecosystem networks are often dynamic, forming dynamic networks. Based on the network formation mechanism, dynamic networks can be divided into offline and online networks. The goal of dynamic network community detection in software ecosystems is to efficiently reveal the community structure and evolutionary patterns of the system, contributing to understanding individual interaction behavior and promoting the healthy and sustainable development of software ecosystems. This invention segments the dynamic network into several continuous multi-layer networks based on the similarity of the network at different time periods. It considers both the saliency of the intra-layer network community structure and the similarity of the inter-layer network community division. Nine offline software ecosystem networks with different characteristics are constructed using data crawled from GitHub. Comparative experimental results show that the proposed offline community detection method for software ecosystems is superior.

The invention discloses a phytoplankton community stability evaluation method based on cascade reservoir influence. The method comprises the following steps: step 1, river reach division and sample collection; step 2, community structure and diversity analysis; step 3, analyzing a community construction mechanism; step 4, co-occurrence network construction and stability evaluation; step 5, environment driving factor modeling; and step 6, performing multi-group comparative analysis. According to the method, multi-dimensional analysis of a community structure, a construction mechanism, network stability and environment driving factors is integrated, and a complete evaluation chain is formed; a neutral community model and a co-occurrence network analysis method are introduced, and the influence mechanism of the cascade reservoir is revealed from the angles of the ecological process and interaction; the method is suitable for river and reservoir systems of different scales and different types, and is especially suitable for ecological assessment of areas without data or with less data; the method has important theoretical and practical values for scientifically guiding ecological scheduling and biodiversity protection of the drainage basin.

The application discloses a kind of community structure water source driving cause-effect relationship analytical method, device, equipment and medium.It includes: obtaining soil water sample, plant water sample, precipitation water sample and groundwater water sample in target sample plot;The layered treatment of soil water sample obtains multilayer soil water sample and soil moisture content;The target sample plot is divided to obtain groundwater depth zoning data;The species number, species proportion and simpson diversity of annual plant and perennial plant are calculated as community structure characterization index;Test to obtain the isotopic characteristic data of each water sample, and input bayesian mixture model to calculate utilization ratio;Key water source factor is identified by redundancy analysis;The cause-effect relationship influence path is analyzed using partial least squares path model, and the complete cause-effect chain of community structure variation and ecological risk early warning basis are output.The present application realizes shallow groundwater grassland plant water source utilization quantification and water source driving cause-effect relationship analysis, and provides technical support for ecological early warning and water resources development.

The application discloses a network reconstruction and overlapping community detection joint method, device, equipment and medium, the method comprises the following steps: obtaining binary time series data and community quantity of community network; initializing community membership matrix and community interaction matrix; using expectation maximization algorithm to iterate community membership matrix and community interaction matrix to obtain target community membership matrix; determining the community structure of the community network and the overlapping community in the community network based on the target community membership matrix. The application explicitly introduces the community membership variable in the parameter space, so that the network inference and community detection, which are regarded as independent problems, form a unified optimization architecture. The responsibility variable is used to track the specific contribution of each edge to the observed dynamics, ensuring the deep coupling and mutual promotion of network inference and community detection. The application not only realizes the detection of the underlying overlapping community structure of the complex network and the accurate reconstruction of the hidden network topology structure, but also ensures the reconstruction accuracy of the complex network.

This application belongs to the field of computer-aided medical technology and discloses an adaptive hierarchical medical knowledge graph community construction method, device, and medium. The method first calculates the normalized evidence support of the medical knowledge graph triples; then, it constructs a collaborative initial edge weight matrix by combining the graph topology, entity semantic similarity, and evidence support; next, it adaptively calculates the initial resolution based on the graph size and density, and performs coarse partitioning to obtain a set of entity topic communities; for large communities, it removes outliers to obtain robust semantic centers, and performs secondary partitioning correction based on consistency to update edge weights; it calculates the maximum similarity between small communities and the centers of large communities and performs adsorption or containment processing; finally, it employs a strategy of increasing resolution with hierarchy to perform top-down recursive partitioning. This invention effectively suppresses the interference of clinical literature extraction noise and weak evidence on the community, ultimately generating a high-quality hierarchical community structure that can be used for medical consultation, clinical decision-making, and medical retrieval.