167 results about "Network layout" patented technology

The invention provides an intelligent water affair scheduling method based on LSTM and multi-objective optimization, and belongs to the technical field of intelligent water affair management and urban water supply system optimization. Comprising the following steps: based on water consumption data, performing analysis through a long short term memory neural network to obtain water consumption demand prediction; based on the water consumption demand prediction, combining pipeline information and pipe network layout data, performing pipe network pressure partition optimization, and obtaining a pipe network layout optimization result; and based on the pipe network layout optimization result, combining the historical operation data of the equipment and the water demand prediction, carrying out efficiency analysis on the pump station equipment to obtain an operation combination scheme of the equipment.

The invention discloses a collaborative planning method for a regional integrated energy system, and the method comprises the steps: firstly collecting regional historical energy consumption data and various external factor data, and predicting an energy demand through employing a gray prediction and multiple linear regression combined algorithm; exploring existing energy supply facilities in the region and evaluating renewable energy potential; determining a candidate type of the integrated energy system component according to the result, establishing an optimal configuration model, and solving through a particle swarm optimization algorithm; constructing an energy network layout planning model, and determining an optimal topological structure and parameters of the network; establishing a dynamic operation model, and formulating a collaborative operation strategy by using a model prediction control algorithm; and finally, comprehensively evaluating the planning scheme, and analyzing and adjusting the scheme by utilizing sensitivity according to an evaluation result. According to the method, multiple factors are comprehensively considered, and the problems that in existing regional integrated energy system planning, demand prediction is not accurate, resource evaluation is not comprehensive, component configuration and network layout lack optimization collaboration, and the operation strategy is single are effectively solved.

The invention discloses a water supply control method and system based on fluid flow self-adaptive adjustment. The efficiency and reliability of a water supply system are improved. The method comprises the steps that pipe network layout information of a target water supply area is acquired, a water supply network topological structure is constructed, and the layout position of a water supply monitoring sensor is determined; constructing a water supply monitoring simulation model based on a topological structure and sensor layout, monitoring a water supply condition in real time, and identifying water demand characteristics; constructing an adaptive flow regulation model according to the water demand characteristics, analyzing demands, determining water supply control parameters, and generating a water supply control strategy; the water supply control is realized through the strategy, the satisfaction degree of the water demand is evaluated in real time, and the water supply control strategy is optimized. The water supply system can intelligently adapt to water demand changes, and the operation efficiency and service quality of the water supply system are improved.

The invention provides a storage network planning method and a logistics simulation system for energy enterprise materials, and relates to the field of energy enterprise material planning, user data is received through an interactive interface, and the user data is pre-processed and stored in a database; after a user triggers a solving instruction, a back end calls a solver to construct a mixed integer programming model, a warehouse network layout scheme is iteratively optimized based on a constraint satisfaction algorithm, and a result is stored back to a database; the support visualization module generates a multi-dimensional chart to display data before and after optimization, provides a data export function to output a portable document according to a preset format, integrates business rules, algorithm solution and visual interaction, supports dynamic optimization and rapid verification of an energy storage network, realizes dynamic collaborative optimization of storage site selection, inventory decision and transportation planning, and improves the efficiency of the energy storage network. And through introduction of multi-scene and multi-dimensional simulation analysis capability, an integrated optimization and simulation platform and a human-computer interaction friendly visual decision-making interface are constructed.

The present invention discloses a method for modeling ultra-large-scale MIMO geometric random and beam-domain wireless channels, and the specific steps include: 1) setting simulation parameters, network layout, etc., generating initial large-scale parameters, and generating initial clusters based on model initialization parameters; 2) updating large-scale and small-scale parameters; 3) generating geometric random channel model channel coefficients, steering matrices, and beam-domain channel matrices; 4) analyzing channel characteristics, and verifying the accuracy of the model by comparing with measured data. The wireless channel modeling method established by the present invention supports spherical waves and spatial non-stationary characteristics, and can realize the conversion from geometric random to beam-domain channel models under near-field conditions. The model accuracy is verified by the consistency of simulation and measurement results of space-time-frequency correlation functions and channel capacity. The present invention has guiding significance for the design and performance evaluation of ultra-large-scale MIMO communication systems.

The invention relates to the technical field of agricultural internet of things and intelligent regulation and control, in particular to a tobacco planting greenhouse microclimate real-time monitoring and regulation and control method based on a cloud platform, which adopts a'cloud-side-end 'three-level architecture, deploys a multi-source sensor network layout in a tobacco planting greenhouse, is connected with terminal equipment and is used for monitoring and controlling the microclimate of the tobacco planting greenhouse. The multi-source sensor network is a three-level sensor network, the data acquisition and processing module adopts LoRaWAN and 4G / 5G dual-mode redundancy transmission, deploys an LSTM prediction model at an edge computing node, inputs time sequence sensor data, adopts a micro-service architecture, adopts a gRPC protocol for inter-service communication, and constructs a virtual tobacco planting greenhouse model through a Unity 3D engine; according to the method, environmental parameters are collected in real time through a multi-source sensor network, a regulation and control strategy is dynamically optimized through a machine learning algorithm, and precise control over the tobacco growth environment is achieved.

The invention relates to the technical field of municipal planning, in particular to a BIM + GIS-based municipal underground pipe network intelligent planning and conflict avoidance system and method, and the system comprises a BIM-GIS data fusion module which is used for integrating a BIM model and GIS topographic data; the construction process association module is used for analyzing the construction plan to generate a dynamic construction progress table, and constructing a directed graph based on the spatial position relationship of each construction unit in the BIM model; the conflict prediction and avoidance module is used for calculating the space conflict probability of the temporary pipe network and the permanent pipe network in real time in combination with the directed graph and GIS topographic data; the land-saving optimization module is used for carrying out iterative optimization on the temporary pipe network layout through a genetic algorithm based on GIS topographic data and construction area boundary constraints so as to minimize the total length and the occupied area of the temporary pipe network; and the dynamic visualization interaction module is used for providing a three-dimensional BIM-GIS fusion view. According to the method, management and control from static design to dynamic construction are achieved, and the scientificity of underground pipe network planning and the land resource utilization efficiency are improved.

The invention discloses a multi-mode soil moisture content sensor layout method, and relates to the technical field of sensor network layout and optimization. The problem that soil moisture content monitoring quality and low operation cost cannot be considered at the same time in a traditional laying method is solved. According to the method, a soil moisture status state estimation vector and an error covariance estimation vector are obtained and corrected by using a constructed measurement and calculation model and a constructed measurement model, and an objective function is constructed by using the corrected error covariance estimation vector and the soil moisture status state estimation vector to minimize estimation error, state estimation deviation and sensor operation cost. And according to a set constraint condition, enabling the target function to be minimum for constraint, and carrying out optimization solution on the target function by utilizing an optimization algorithm to obtain an optimal layout position of each sensor. The method is mainly used for carrying out optimized layout design on the sensors in the farmland.

The invention discloses a rainfall station network layout method, and relates to the technical field of hydrometric station network layout, and the method comprises the steps: obtaining the rainfall data of a historical rainfall station network in a target region, the historical rainfall station network comprising a plurality of rainfall stations; extracting spatio-temporal characteristics of the rainfall data, and obtaining a rainfall prediction value of each spatial unit based on the spatio-temporal characteristics; obtaining prediction precision and a mutual information mean value based on the rainfall prediction value, constructing a fitness function based on the prediction precision and the mutual information mean value, and obtaining an optimal solution based on the fitness function; and obtaining a target rainfall station network layout result based on the optimal solution. The method solves the problems that an existing rainfall station network layout method is insufficient in spatial-temporal feature capture capability, is easy to fall into a local optimal solution due to dependence on a certain heuristic algorithm, and is low in optimization efficiency and cannot effectively balance and collaboratively optimize multiple targets.

The invention discloses a drainage basin monitoring network layout optimization method based on mutual information active learning. The method comprises the following steps: data processing; constructing an integrated learning prediction model composed of a plurality of LSTMs, initializing each LSTM model parameter by setting different random number seeds, and iteratively updating the model parameters; constructing a covariance matrix of prediction results of the potential monitoring points by using the trained integrated learning prediction model; on the basis of an active learning algorithm of mutual information maximization, mutual information gains of all candidate sites added into the current monitoring network are calculated, candidate points enabling the mutual information gains to be maximum are selected, and information value sorting is carried out on potential monitoring points according to the sizes of the mutual information gains; and outputting a monitoring station optimization suggestion list. According to the method, uncertainty is scientifically quantified by adopting an ensemble learning method, and global information value is evaluated by adopting a mutual information maximization strategy, so that point selection decision does not depend on subjective experience any more, but strict calculation based on data and information theory, and the scientificity of decision is remarkably improved.

The invention discloses a multi-source rainfall monitoring station network design method and device based on a complex network theory, and relates to the field of rainfall monitoring station network design, and the method comprises the steps: obtaining multi-source rainfall data of a research region; grid division is carried out in the research area according to preset precision, candidate sites are determined according to divided grids, connection edges between the candidate sites are determined according to correlation between the multi-source rainfall data of the candidate sites, and a rainfall network of the research area is constructed; calculating a weighting degree betweenness of each candidate station in the precipitation network according to a weighting degree betweenness index calculation method; determining the minimum rainfall monitoring station number in the research area; and sorting the weighting degree betweenness of each candidate station, and at least selecting a minimum number of candidate stations from a sorting result as rainfall monitoring stations. According to the invention, multi-source precipitation data is adopted, optimization design is carried out on precipitation monitoring station network layout points based on a complex network theory, and the accuracy of precipitation monitoring station network layout is improved.

Aspects of the present disclosure include system, methods, and software for buffer insertions. In one example, a method includes receiving a clock signal network layout, wherein the clock signal layout comprises a clock source electrically coupled to a plurality of clock sinks via a plurality of net segments, and creating a plurality of buffering solutions, wherein each buffering solution of the plurality of buffering solutions comprises a plurality of buffers inserted on one or more net segments of plurality of net segments. The method further includes assigning each buffering solution a timing delay value and an area value, and selecting a buffering solution of the plurality of buffering solutions based on the timing delay value and the area value. The method additionally includes committing the selected buffering solution into an integrated circuit design comprising the clock signal network.

The invention provides a communication deployment method for monitoring an intelligent power distribution network, and belongs to the technical field of telecommunication, and the method comprises the steps: 1, analyzing a topological structure of the power distribution network, and determining a topological graph of the power distribution network; 2, analyzing the topological graph of the power distribution network, and further determining a data transmission demand coefficient of each node in the power distribution network; step 3, determining a communication mode of each area in the power distribution network based on the data transmission demand coefficient of each node in the power distribution network, and further generating a preliminary communication network layout in combination with the topological graph of the power distribution network; step 4, carrying out performance simulation on the communication network based on the preliminary communication network layout so as to obtain a network performance analysis report; and step 5, based on the network performance analysis report, optimizing and adjusting the communication network layout, and further determining a final communication network deployment scheme.

The invention discloses a public space social behavior and environment influence identification method based on a sensing equipment network. The method comprises the following steps of public space area selection, measuring point layout and sensing equipment distribution, public space physical environment monitoring, public space social behavior identification, behavior environment index influence analysis and influence rating and output. Based on the network layout of the sensing equipment, the physical environment of the public space is monitored through the environment sensing equipment, the social behaviors of the public space are identified through the behavior sensing equipment, the influence relation between the environment indexes and the behavior indexes is comprehensively analyzed, and the influence degrees are sequenced and output. The method can be used for identifying the behavior environment influence relationship in the urban intelligent sensing field, and is beneficial to building a more efficient and comfortable urban public space.

The invention relates to the field of ecological monitoring, in particular to an unmanned aerial vehicle monitoring network layout method based on geographic space information, and the method comprises the steps: constructing an ecological source service supply region and an ecological resistance surface of the ecological source service supply region, and recognizing an ecological corridor region and an ecological strategy point; according to an ecological source service supply area, an ecological corridor area and an ecological strategy point, an unmanned aerial vehicle monitoring network is constructed to form a unified and independent unmanned aerial vehicle ecological system monitoring system, so that reasonable layout of unmanned aerial vehicle networking is realized, high-frequency, real-time and dynamic monitoring requirements are met, and the monitoring efficiency is improved. Accurate matching of monitoring area coverage and monitoring requirements of the unmanned aerial vehicle is realized.

The invention discloses a centralized heat supply network pipe pressure monitoring method and system based on artificial intelligence, and relates to the technical field of heat supply system monitoring, and the method comprises the steps: firstly laying optical fibers and point pressure sensors on a network pipe, and collecting acoustic strain and pressure data; constructing a digital twin grid through same-frequency alignment and Delaunay triangulation, and reconstructing a continuous pressure field; calculating the residual error between the reconstruction pressure and the measured value at the monitoring node; extracting multi-scale residual features to form a feature matrix based on a wavelet operator of a pipe network topological structure map; inputting the features into a pre-trained spectrogram wavelet neural network, and outputting a normalized abnormal score; and finally positioning a fault pipe section according to the score and performing graded warning. Physical modeling and deep learning are fused in the whole process, closed-loop monitoring from data collection to fault diagnosis is achieved, and the precision and timeliness of pipe network anomaly detection are remarkably improved. Manual detection is not needed, and the monitoring process is more flexible.

The invention relates to the technical field of double-loop network links, and particularly discloses a redundancy system of a double-loop network link, which comprises a main rack and a plurality of extension racks, and is characterized in that the main rack comprises a first controller, a second controller, a first CPU module base, a second CPU module base, a plurality of first I / O modules and a plurality of first I / O module bases, the first CPU module base is positioned at the head end of the main frame; according to the invention, by optimizing the network layout and reducing the transmission hop count of the data packet in the double-loop network, the network delay is reduced, the redundancy is ensured, the complexity of a redundant path is reduced as much as possible, the introduction of excessive extra delay is avoided, and a switch with high forwarding rate and low delay is selected, so that the overall performance of the network is improved, and the network performance is improved. High-quality optical fibers and cables are adopted, signal attenuation and transmission delay are reduced, and the length and complexity of a transmission path are correspondingly reduced, so that the phenomenon that network response time is increased is avoided, and use by people is facilitated.

Apparatuses, systems, and methods for providing enhanced visualization of lifecycle information and management for a network, such as an industrial network, enable the creation / design of a virtualized network. The virtualized network eases the physical deployment / installation of a real network by using augmented reality (AR) to enable configuration / monitoring of the network using the virtualized network and real-time and / or historical information. Performance issues may be identified and visually conveyed to a user using AR overlay. The virtualized network may be created by a user via a network layout creation tool that combines both physical and logical mappings of devices and elements. One or more AR tools may be used to add, edit, remove, and / or manipulate elements of the network model using gestures. The virtualized network may be implemented as a digital twin of the location and used to assist in the physical deployment, maintenance, and monitoring of a network at the location.

The present invention discloses a method and system for evaluating the adaptability of a highway network layout structure. The present invention comprises the following steps: constructing a network model: constructing a traffic flow database and a highway network structure model; tracing the traffic flow OD: analyzing and tracing the traffic flow OD of highways; evaluating the network structure: calculating and analyzing the accessibility of the highway network, the matching degree between the network structure center and the travel demand center based on the traffic flow database and the highway network structure model, and measuring the adaptability of the network structure layout through the matching degree index; optimizing the structure strategy: proposing ideas and strategies for optimizing the highway network structure based on the adaptability calculation results. The present invention is of great significance to the evaluation, optimization and planning of highway networks.

The invention discloses a fire-fighting pipe network inspection management system based on BIM (Building Information Modeling) and CIM (Common Information Modeling), and aims to solve the technical problems that a current fire-fighting pipe network inspection management system cannot realize three-dimensional visualization of a fire-fighting pipe network and is low in management efficiency and fault positioning accuracy, and the fire-fighting pipe network inspection management system comprises a multi-dimensional model data integration unit which is used for building a BIM platform model and expanding a CIM platform; the real-time monitoring and dynamic updating unit is used for acquiring operation data in real time and transmitting the operation data to the BIM / CIM platform, and realizing synchronous updating of a physical pipe network state and a digital model and model parameter adjustment; the intelligent analysis and decision support unit is used for fire-fighting pipe network fault diagnosis and prediction; and the visualization and collaborative management unit is used for displaying the full view of the pipe network and supporting 360-degree view angle switching, attribute query and simulation drilling. Through integration of BIM and CIM technologies, the system realizes three-dimensional visualization of the fire-fighting pipe network, so that information such as pipe network layout and equipment installation positions is clear at a glance, and the management efficiency and the fault positioning accuracy are greatly improved.

The invention discloses a port logistics carbon emission monitoring system based on the Internet of Things and a computer, and the system comprises a multi-modal data collection and transmission module which carries out the full-amount collection of the multi-dimensional data of equipment, sensors and environment in a port area through a hierarchical heterogeneous communication network; the edge intelligent processing and resource scheduling module is deployed at the local of a port, performs priority dynamic allocation and real-time processing on the acquired data, and uploads aggregated data; the anomaly detection and carbon flow modeling module is used for carrying out anomaly detection based on a space-time diagram neural network and constructing an operation chain carbon flow model integrated with a port production operation system; the digital twinning driven monitoring network optimization module is used for constructing and operating a communication-environment digital twinning model and dynamically optimizing the layout of the monitoring network; the accounting decision and intelligent optimization module is used for performing carbon footprint tracing based on a task-level accounting unit and generating a low-carbon optimization strategy; and the visualization and user interaction module is used for providing a visualization display and decision support interface of the carbon emission data.

The invention provides a damage monitoring auxiliary system based on self-sensing concrete, which relates to the technical field of concrete damage monitoring and comprises a self-sensing concrete hardware module, a data acquisition and processing module, an environment compensation and correction module, a data decoupling module and a data analysis and prediction module. According to the invention, the layout of the sensing network is optimized, a high-density microelectrode grid is pre-embedded in self-sensing concrete, the microelectrodes can not only increase signal acquisition points, but also effectively reduce the problem of signal attenuation, and at the same time, the electromagnetic suppression sub-module is matched, so that the resistance to local electromagnetic interference is enhanced, and the self-sensing performance of the sensor is improved. Even in a complex construction environment, good signal stability can still be kept, so that high-precision and high-robustness damage monitoring is realized by optimizing the layout of the sensing network, enhancing the anti-electromagnetic interference capability, establishing a temperature and humidity compensation model and combining an intelligent signal processing algorithm; therefore, the monitoring efficiency and the engineering applicability of the self-sensing concrete in a complex environment are improved.

The invention provides an electrical automation system fault prediction method based on big data analysis. The method comprises the steps of sensor network layout planning, data acquisition, data transmission, data preprocessing, feature extraction, fault prediction model construction, real-time prediction and fault early warning. According to the method, the problems that an equipment fault diagnosis method in an existing electrical automation system cannot realize omnibearing real-time monitoring through manual inspection, potential faults are difficult to perceive based on threshold judgment, troubleshooting and positioning consume long time and the like can be solved, early warning of the equipment fault is realized through a method based on big data analysis, and the fault diagnosis efficiency is improved. Stable and reliable operation of an electrical automation system is guaranteed, and the strict requirement of modern industry for intelligent management of equipment is met.

The invention discloses a site selection method and device of a financial institution website and a storage medium. Relates to the field of artificial intelligence, and the method comprises the steps: obtaining a pre-site selection position set, the pre-site selection position set comprises X pre-site selection positions, and X is a positive integer greater than 1; determining a service point set according to the pre-site selection position set and the existing financial institution network points; according to the pre-addressing location set and the service point set, determining a shortest route set between each pre-addressing location in the pre-addressing location set and each service point in the service point set based on a path planning algorithm; and according to the shortest route set, determining a target site selection position from the pre-site selection position set based on a P-median algorithm. According to the invention, the problem that the accuracy of website site selection is low and the rationality of website layout is influenced in the prior art is solved.

The present invention is applicable to the technical field of airport transfer hub capacity assessment and provides a multi-scale airport network flight transfer comprehensive index calculation method, which includes the following steps: data preparation, including airport network layout, airport layout, flight schedule, and transfer flight demand; calculation of the transfer flight proportion, feasible transfer number, average transfer waiting time, and transfer success rate of each airport; calculation of the average transfer flight proportion, average feasible transfer number, average transfer waiting time, and average transfer success rate of all airports and regions; calculation of the industry level of transfer flight proportion, feasible transfer number, average transfer waiting time, and transfer success rate of each airport and region; and calculation of the flight transfer index of each airport and region. The present invention can be used to dynamically evaluate the spatial distribution of flight time resource transfer supply and demand and its rationality, thereby providing data support for the rational planning and adjustment of flight time resources.

The invention discloses a logistics network layout method for electric power emergency material dispatching, and the method can optimize the layout of emergency materials through constructing a network layout model, can make a timely response more quickly when a sudden fault occurs in an electric power system, and guarantees the recovery of the electric power system as soon as possible. Moreover, the time and cost of material distribution are comprehensively considered, so that the cost can be reduced as much as possible while the emergency materials of the power system meet the requirements. According to the method disclosed by the invention, a data-driven emergency logistics network basic model is constructed by combining the current situation of emergency management of a power system and taking the maximization of the emergency service level as a target. According to the method, social benefits are created in the field of electric power emergency, an existing electric power system emergency management method is improved, influences and losses are reduced to the maximum extent, the efficiency and flexibility of emergency material dispatching in an electric power system are further improved, and the emergency response cost is effectively controlled.

The present disclosure relates to a computer-implemented method for determining a network layout of an electrical network with two or more network ports, wherein a network layout indicates a spatial distribution of conductive material electrically connecting network ports of the electrical network, the method comprising: (a) generating a plurality of candidate network layouts, wherein each candidate network layout is divided into a plurality of modules; (b) computing, for each candidate network layout, a performance metric based on module-specific scattering information of each module of the candidate network layout; and (c) determining the network layout based on the performance metric of each candidate network.

The invention discloses a dual-hub airline network optimization method and system, and belongs to the technical field of civil aviation flight, and the method comprises the steps: building a dual-hub airline efficiency evaluation index system through obtaining an input index, an output index and an environment variable for evaluating the efficiency of a to-be-optimized dual-hub airline, and carrying out the efficiency evaluation of the dual-hub airline. The technical efficiency value of each route of the to-be-optimized dual hub is obtained to analyze the operation characteristics of the dual hub airport, and the principles of reduction of the coincidence rate, efficient operation of the route network, convenience of passengers and minimum route adjustment amplitude are put forward. And establishing a dual-hub airline network optimization model by taking the minimum airline overlap ratio, the minimum airline efficiency mismatching degree, the minimum passenger departure airport selection cost and the minimum airline flight adjustment amount as targets, performing solving, and optimizing the network layout of the dual-hub airline to obtain an optimization result. According to the method, the efficiency is evaluated before optimization, the double-hub overall route efficiency is improved, and differentiation and high efficiency of a double-hub route network can be achieved.

The invention discloses a salinized frozen soil roadbed multi-parameter coupling monitoring method, and relates to the field of salinized frozen soil area roadbed monitoring, and the method comprises the steps: executing field investigation and demand analysis, outputting a field investigation and monitoring demand analysis report, executing a sensor network intelligent dynamic topology design, and outputting an intelligent dynamic sensor network layout detailed drawing. According to an intelligent dynamic sensor network layout detailed drawing, sensor preparation, verification and drilling channel construction are executed, and drilling holes and channels are output; cooperative arrangement, installation and fixation of a multi-parameter sensor are executed, an on-site sensing network is output, cables are led out and connected to an integrated data acquisition box in a tandem mode, cable tandem is executed, system integration and acquisition box installation and debugging are carried out, and an integrated on-site monitoring station is output. According to the method, the ultimate targets of comprehensive, synchronous and accurate monitoring and intelligent early warning of the roadbed water-salt-thermal coupling migration process are achieved, and the fundamental problems of data splitting and analysis lagging of a traditional method are effectively solved.

This invention discloses a method for extracting the equivalent permeability of multi-stage seepage paths in a pore network, comprising the following steps: S1, binarizing the images captured by the experimental testing equipment, executing the pore numbering module L to obtain pore regions with different numbers; S2, executing the directed graph generation module B to generate a directed connectivity matrix C. B S3. Execute the path search module W, using continuous repeatability as a constraint during path search. S4. Execute the penetration rate equivalence module P to determine the experimental calibration coefficient C. E By confirming the magnitude of seepage resistance and the range of equivalent permeability for each path, this invention can quickly solve key issues such as the applicable range of permeability and multi-layer fluid distribution for fluid transport (such as geologically sealed CO2 and displacement fluids for reservoir development) in heterogeneous geological bodies. It provides important guidance and support for the formulation of schemes such as well location / well network layout, layer combination, and quantification of recovery / storage volume for reservoir development or CO2 geological storage.