15 results about "Network density" patented technology

The invention discloses a preparation method and application of a swelling-inhibiting dual-network membrane, and the method comprises the following steps: (1) putting chloromethylated polysulfone and tetramethylethylenediamine into a NaOH solution for pre-crosslinking to obtain a crosslinked chloromethylated polysulfone solution; (2) mixing the cross-linked chloromethylated polysulfone solution with the sulfonated polyetheretherketone solution, stirring at 60-80 DEG C for 2-4 hours, then cooling to 40-50 DEG C at a rate of 5-10 DEG C / h, and stirring at a constant temperature for 8-12 hours to obtain a membrane casting solution; and (3) drying the membrane casting solution to prepare the swelling-inhibiting dual-network membrane. According to the invention, through precise regulation and control of covalent cross-linked network density and directional optimization of a blended microphase structure, synergistic improvement of swelling inhibition, efficient ion conduction, excellent mechanical properties and zinc dendrite resistance is synchronously realized in a strong alkaline environment.

The embodiment of the invention provides a social network feature-based team communication complexity analysis method and system, and the method comprises the steps: constructing a command and control social network model, carrying out the fuzzy evaluation of a task unit, determining the overall fuzziness of a task, carrying out the multi-dimensional evaluation of a communication medium, determining a comprehensive value of the richness of the medium, and carrying out the analysis of the richness of the medium. Constructing a task fuzziness-communication medium matching matrix, coupling the task overall fuzziness with a medium richness comprehensive value, determining a medium communication efficiency parameter, and performing complexity analysis on a command and control social network model according to the medium communication efficiency parameter to obtain a command and control social network model; the average path length complexity feature, the network diameter complexity feature and the network density complexity feature of the network are obtained, weighted optimization is carried out on the network edge according to the network complexity feature, an optimized command and control social network model is obtained, and the efficiency of team communication and task execution can be improved.

This invention discloses a method for optimizing well layout parameters in a three-dimensional well network for fracturing in thick shale oil reservoirs. The optimization method includes: Step S1: Inputting the logging curve interpretation results of the pilot test well, and calculating the physical and geomechanical parameters of the target reservoir rock; Step S2: Calculating the reservoir quality, completion quality, and overall quality based on the physical and geomechanical parameters, and initially selecting the vertical landing sites for horizontal wells; Step S3: Establishing a reservoir fracturing geological model based on the physical and geomechanical parameters, building an unconventional oil and gas fracturing fracture propagation model, and simulating the vertical fracture height propagation of the initially selected vertical landing sites for horizontal wells; Step S4: Determining the optimal lateral well network density for each sub-layer based on single-well productivity; Step S5: Outputting the three-dimensional well network layout results. This method maximizes reservoir stimulation volume by drilling the fewest horizontal wells, meeting the needs of cost reduction and efficiency improvement.

The invention relates to the technical field of network communication security, in particular to a hierarchical broadcast key management method and system applied to the Internet of Things, an intelligent sensor network and a distributed system. Comprising a root node, an intermediate node and a leaf node, the system collects network state parameters such as network density and node average energy, calculates a tree balance factor and dynamically adjusts a key tree structure, the network is divided into a plurality of security domains, each domain has an independent key system and comprises a broadcast key, a forward key and a communication key, a domain key is decomposed into a plurality of key components, and the key components are distributed in the security domains. According to the method, a subtree key is generated in a sectional type combined key derivation mode, a node state is monitored in cooperation with a self-repairing mechanism, key fragment reconstruction is triggered when a failure or key leakage occurs, the expandability of the system is remarkably improved, the network capacity is increased in an exponential level, and the network communication safety performance is effectively improved.

The application discloses a deep coal seam gas fracture network density prediction method and relates to the technical field of reservoir development. The application extracts an average fracture network spacing from microseismic event point data as a fracture network density representation label; a multi-source data fusion framework with a fracturing section as a sample unit is established, and geological and engineering parameters are spliced into feature vectors; a machine learning algorithm is used to construct an intelligent prediction model, and a complex nonlinear mapping relationship between multi-source features and labels is automatically learned. The application realizes intelligent prediction of the fracture network density and can provide reliable support for fracturing effect evaluation and construction parameter optimization.

The application discloses a high-density gravity-magnetic force composite acquisition processing method, which comprises the following steps: establishing a first measuring network and a second measuring network in a measuring area, wherein the first measuring network and the second measuring network are gravity-magnetic force general point measuring networks, the measuring network density of the first measuring network is different from that of the second measuring network, and the second measuring network comprises two measuring line orthogonal measuring networks; collecting gravity-magnetic force data in the first measuring network and the second measuring network respectively, and performing preliminary processing on the gravity-magnetic force data, wherein the preliminary processing comprises preliminary merging and interference value correction; and performing secondary merging on the data of the first measuring network and the second measuring network after the preliminary processing to generate a composite data body. The method realizes high-density gravity-magnetic force data acquisition processing, and has important practical and popularization and application values in complex oil and gas target gravity-magnetic force exploration. The application further discloses a high-density gravity-magnetic force composite acquisition processing device.

This invention discloses a decentralized MESH multi-hop random access method. The method includes: dividing the communication frequency band into a common control channel and several service data channels; acquiring inter-node interaction signals on the common control channel to maintain a neighbor state table; responding to transmission requirements, relay nodes perform differentiated backoff forwarding based on multi-factor quality characteristics composed of target proximity, signal quality, load, and hop count; target nodes adaptively establish backup routing paths and evaluate and determine the primary transmission path based on local network density; and after completing the handshake on the common control channel, switching to the corresponding service channel to perform data transmission. This invention eliminates the risk of central node failure, improves path search efficiency and transmission reliability in complex building obstruction environments, and achieves high-performance self-healing and multi-channel concurrent communication in the network.

The invention relates to the technical field of database structures, in particular to a dynamic optimization system and method based on label nebula density analysis for a large-scale business system and a storage medium. The optimization system comprises a data connection and acquisition module; a label star map construction and calculation module; a density analysis module; an optimization suggestion generation module; according to the method, an abstract tag quality problem is converted into a concrete graph network density problem, and quantitative and visual diagnosis of the health degree of a tag system is realized. The method not only solves the problem of'overfitting ', but also solves the problem of'missing', and meanwhile, can reversely promote the improvement of the content of a service system.

The invention belongs to the technical field of film-forming lacquer modification, and particularly relates to a crosslinking-enhanced lacquer modification method which comprises the following steps: mixing raw lacquer and a crosslinking agent, coating a base material, curing to form a primary crosslinking network, preparing an initiator system, immersing a cured lacquer film into an initiator, performing secondary crosslinking enhancement and the like. The three-dimensional network density of a paint film is greatly enhanced from the molecular design level through the synergistic effect of the cross-linking agent and the initiator, compared with an original lacquer material, the cross-linking enhanced lacquer modified through the method has the advantages that the adhesion effect on glass and ceramic is remarkably improved, and the stripping degree on the surfaces of the glass and the ceramic is remarkably reduced.

Computer systems and computer-implemented methods are configured to assign limited resources such as cloud or other computing resources to objects such as networks of computers having demands for the resources. Efficiencies are optimized by assigning the objects based upon an intra-network score and an inter-network score, both of which may include an associated network density and / or an associated metric, and may be based on information received from electronic records. The metric may be a parameter relating to a factor or other characteristic that is desired to be optimized by the assignments. For example, the metric may be related to costs of communications between the computers of a network.

The application provides a kind of distributed scalable intelligent routing method based on key node, belongs to network resource scheduling optimization field.The method according to network topology scale, network density and the centrality of various nodes calculates network average aggregation coefficient, key node proportion and node key degree, determines the position of agent deployment by comprehensively considering key node proportion and node key degree;Agent generates routing strategy according to service flow demand and network state, network feedback utility function after executing strategy, and agent adjusts parameters through feedback to optimize strategy;After the training of agent is completed, routing strategy is continuously adjusted with the change of network state, and the network performance is continuously optimized.The application realizes complex network control through a small number of agent nodes, effectively improves network throughput, reduces average service delay and deployment cost on the basis of not greatly changing existing network environment, has good scalability, can be flexibly deployed under different network scales, and is suitable for engineering implementation.

The present application belongs to the field of process safety management and industrial internet technology, and particularly relates to a kind of dynamic evaluation method and system for LNG receiving station operation discipline. The method comprises: real-time acquisition of DCS operation log, alarm record and informal communication data, extraction of three dynamic indexes of interruption recovery time R(t), response diversity D(t) and informal communication network density C(t); a five-state nonlinear system dynamics model is constructed, and state variables include R(t), D(t), C(t), trust level T(t) and work load W(t); Monte Carlo simulation is used to sample the key uncertainty parameters, and the statistical distribution of system safety margin S(t) is obtained by running simulation; when S(t) is lower than the preset threshold, a risk warning signal is output. The present application provides a specific method: by real-time acquisition of the deviation value of operation sequence and standard discipline template, the adjustment coefficient of intelligent adjustment effect degree to deviation change is calculated, and then the safety margin prediction value of the system under the current working condition is output, to fill the above technical gap, and to provide effective technical support for process safety management of high-risk enterprises such as LNG receiving station under the background of industrial 4.0.

The invention relates to the technical field of biological materials, and discloses a silk fibroin degradation rate and mechanical property coordinated regulation method. Comprising the following steps: S1) grading degumming; s2) performing temperature-controlled dissolution; s3) dynamic crosslinking; s4) performing gradient dialysis; s5) performing reverse dialysis concentration; s6) stopping concentration when the mass difference is less than or equal to 3%; s7) performing microporous filtration to remove impurities; the core of the method is as follows: a double-track regulation mechanism: degumming / reverse dialysis controls beta-folding crystallinity dominant mechanical strength, and dynamic crosslinking adjusts covalent network density to control degradation rate; correlation of cross-process parameters: reversely deducing a process threshold through target parameters such as degradation time Mt, crosslinking density rho and tensile strength sigma; according to industrialization adaptability, quantitative criteria are set in all steps, and automatic production is supported; according to the invention, the contradiction that the fibroin material is difficult to decline if being strong and is rapid to collapse if being weak is solved, and the method is suitable for tissue engineering scaffolds and implanted instruments with customizable degradation periods.

The application provides a network public opinion evolution simulation and social risk prediction method based on a DQTN, which comprises the following steps: accessing a data stream of a target social media, mapping user data of the target social media into a quantum spin state in a Hilbert space, and constructing a whole network state of the target social media; performing two-dimensional projection entangled pair state processing on the whole network state, reconstructing complex social connections in the whole network state into a tensor network, and performing dimension reduction through singular value decomposition to obtain a reconstructed and reduced whole network state; constructing a public opinion Hamiltonian describing emotional interaction and external driving force, simulating a dynamic evolution process by using a time evolution block extraction algorithm, and calculating a whole network density matrix; calculating a public opinion magnetization based on the whole network density matrix, determining and positioning a phase transition critical point of a public opinion outbreak based on a power law divergence characteristic of a first-order derivative of the public opinion magnetization with respect to time and a preset phase transition critical threshold, and thus realizing accurate prediction of a social risk.

The application relates to the technical field of data processing, in particular to a method and system for digital grassroots governance, the method comprising the following steps: collecting multi-dimensional risk signals of a shop in real time, and dynamically generating a risk value corresponding to the shop based on the multi-dimensional risk signals; taking the shop with the maximum risk value as a source shop, calculating resonance strength between other shops and the source shop through industry correlation, and constructing a resonance strength network based on the resonance strength; obtaining resonance network density based on the resonance strength network; calculating intervention urgency based on the network density and the maximum risk value; and triggering an intervention signal when the intervention urgency is greater than a threshold value. The application has the characteristics of improving the timeliness of data governance to curb the risk transmission tide.