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35 results about "Social perception" patented technology
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Social perception (or person perception) is the study of how people form impressions of and make inferences about other people as sovereign personalities. Social perception refers to identifying and utilizing social cues to make judgments about social roles, rules, relationships, context, or the characteristics (e.g., trustworthiness) of others. This domain also includes social knowledge, which refers to one’s knowledge of social roles, norms, and schemas surrounding social situations and interactions. People learn about others' feelings and emotions by picking up information they gather from physical appearance, verbal, and nonverbal communication. Facial expressions, tone of voice, hand gestures, and body position or movement are a few examples of ways people communicate without words. A real-world example of social perception is understanding that others disagree with what one said when one sees them roll their eyes. There are four main components of social perception: observation, attribution, integration, and confirmation.
User discovery and resource allocation method based on social perception in D2D communication
ActiveCN105960024AOptimize quantityImprove performanceWireless communicationCarrier signalThroughput
The invention discloses a user discovery and resource allocation method based on social perception in D2D communication and belongs to the mobile communication field. The method specifically comprises the following steps of firstly, establishing a D2D communication scene which meets the limitation of the social relationship and the physical location; secondly, carrying out pairing and optimization on D2D communication users in the scene according to a discovery and pairing algorithm of the D2D communication users; thirdly, further computing the entire system throughput CTotal of a base station; fourthly, taking the system throughput CTotal as a target function, combining a limiting condition and adopting a quantum-behaved particle swarm optimization algorithm to solve to obtain an optimal particle position to carry out system subcarrier and power allocation; and lastly, carrying out simulation verification on user discovery and resource allocation based on the social perception in the D2D communication. The method has the advantages that an adaptive abdication under the conflict condition of the residual energy and the request of user nodes is considered; the subcarrier allocation and the power allocation are combined, a resource co-allocation method is provided, and a simulation result shows that the D2D discovery and pairing algorithm based on social perception has better performance.
Owner:BEIJING UNIV OF POSTS & TELECOMM
Routing method of social perception and probability prediction for mobile opportunity social network
ActiveCN107071852AImprove delivery rateLow overhead rateHigh level techniquesWireless communicationLivenessTransfer procedure
The invention discloses a routing method of social perception and probability prediction for a mobile opportunity social network. According to the method, two kinds of related centrality are provided in an initialization phase by researching the liveness, interest and mobility of nodes and the relationship between the nodes so as to simplify a network model; and in a routing phase, message transmission is carried out on the basis of comprehensive consideration of social perception and probability prediction depending on the simplified network model. In addition, a message transcript control strategy is adopted in the message transmission process to effectively control the number of transcripts of a message in the network and reduce the consumption of network resources. The simulation experiment results show that compared with the other three classical routing methods, the method disclosed in the invention has the advantages of effectively improving the delivery rate of the message and reducing the overhead rate of the network.
Owner:SHAANXI NORMAL UNIV
Urban agglomeration height space information and contour line extraction method
The invention relates to an urban agglomeration height space information and contour line extraction method. the method is characterized in that , for extraction of urban buildings, remote sensing data and social perception data are fused, a high / low density building area of a plot scale is established, and the extraction of the urban buildings is realized by combining a multi-view difference feature map; for extraction of urban building heights, dense point clouds are generated by matching every two of forward-looking, backward-looking and front images of a resource No.3, a digital surface model is solved by adopting a TIN linear interpolation method, the thought of point cloud classification is introduced, accurate ground points are obtained, and a digital elevation model is established.According to the invention, the forward-looking, backward-looking and front images of the resource No.3 are fully utilized, and a system framework for extracting urban building information and building height information is innovatively constructed, models of an urban contour line, an urban undulation degree and an urban growth height are obtained on the basis of the system framework, and an evolution pattern of urban transverse area expansion and longitudinal height increase is revealed.
Owner:INST OF GEOGRAPHICAL SCI & NATURAL RESOURCE RES CAS
Green space extracting method and medium of urban agglomeration
ActiveCN109299673AAchieve statisticsRealize researchCharacter and pattern recognitionSensing dataLand cover land use
The invention provides a method and a medium for extracting green degree space of an urban agglomeration. The method comprises the following steps: acquiring high-score remote sensing data of urban agglomeration and extracting land cover data of urban agglomeration; Obtaining the social perception data of urban agglomeration, and extracting the social function attribute data of urban agglomerationland; According to the cover data and social function attribute data, the land of urban agglomeration is classified, and the information about the land and greenness of urban agglomeration is obtained. According to the classification information, the greenness of urban agglomeration is extracted. The present invention solves the problem that only a single remote sensing data can obtain the land cover information in the related art, and the social function attribute of the urban green space cannot be obtained, and realizes the statistics and research of the urban agglomeration green space containing the social function attribute.
Owner:INST OF GEOGRAPHICAL SCI & NATURAL RESOURCE RES CAS
Space keyword query method based on social perception in distributed environment
ActiveCN108932347AFulfil requirementsSupport inquiriesSpecial data processing applicationsData setDistributed index
The invention discloses a space keyword query method based on social perception in distributed environment. The method comprises: through analyzing a Top-k query problem, providing an index for solving the problem and a query framework, an index structure introducing social information, using a retrieval characteristic of keywords, providing a Top-k query algorithm based on social perception on the basis of a SDPR distributed index structure, through inputting a query parameter, a result being first k objects with highest rankings in a data set, the objects satisfying a specific ranking function. Through space keyword query with weight, the method makes query more accurate, and a more accurate result can be obtained.
Owner:NORTHEASTERN UNIV
Social perception D2D collaborative caching method based on deep Q learning
PendingCN114205791AReduce redundant trafficReduce the burden onNetwork traffic/resource managementNeural architecturesContent distributionOptimal decision
The invention discloses a social perception D2D collaborative caching method based on deep Q learning, and aims to solve the problem of link congestion caused by redundant content transmission in a network. The method comprises the following steps: step 1, initializing a communication scene; 2, performing multi-attribute modeling on the social relation strength of the equipment owner; step 3, modeling a D2D cooperative caching process based on a reinforcement learning process; step 4, designing a network structure of a Behavior network for training and a Target network for calculation in the deep Q network; and step 5, based on a set system model, utilizing a deep reinforcement learning algorithm to enable the intelligent agent and the environment to interact to carry out iterative learning to output an optimal strategy, namely, an optimal decision of equipment cache resource allocation and D2D content distribution. According to the technology, normal communication of cellular users can be ensured, the average time delay of the system can be minimized on the premise of meeting personal willingness of the users, and the satisfaction degree of the users is improved to the maximum extent.
Owner:XIDIAN UNIV
Systems and methods for determining social perception scores
A system for evaluating communicative acts to determine a social perception network based on communicative acts between a plurality of communicative pairs. Each communicative pair includes two communicating entities. The system includes a patterns database, a scoring processor, and a communications network aggregation processor. The patterns database stores behavior recognition patterns defining particular behaviors and a score associated with each of the particular behaviors. The scoring processor is configured to determine a pairwise social perception score for the communicative pair based on the particular behaviors identified in the communicative acts. The scoring processor is configured to determine a different pairwise social perception score for each one of the plurality of communicative pairs. The communications network aggregation processor is configured to combine the pairwise social perception scores for each of the plurality of communicative pairs into a social perception network. Other embodiments including other systems, methods, and products are also disclosed.
Owner:SMART INFORMATION FLOW TECH
Personalized dynamic vehicle sharing method and system based on price income and social perception
ActiveCN109447356AImproving rideshare service experienceMeet individual travel needsForecastingPersonalizationSimulation
The invention particularly relates to a personalized dynamic vehicle sharing method and system based on price benefit and social perception, the invention provides the personalized dynamic vehicle sharing method based on price benefit and social perception, the social relationship concerned by users and the pricing mechanism are simultaneously applied to the vehicle ride-sharing matching service.In the matching process, under the premise of guaranteeing the basic travel constraint of passengers, not only the price income brought by new passengers to drivers is considered, but also the priority of passengers with certain social relations to be arranged on a vehicle is considered, and the comfort degree of passengers and the price income of drivers are taken into account under the conditionof meeting the basic travel needs of passengers. The invention can provide a whole set of optimization mechanism of matching process for users. By utilizing upper limit of price benefit and social relation, branch boundary algorithm and index mechanism to cut search space, the invention improves matching speed of passengers and vehicles, enhances system operation efficiency and improves riding experience.
Owner:ZHENGZHOU UNIV
Channel allocation method for D2D multicast video transmission in social perception network
InactiveCN109951828AIncrease access rateIncrease profitPower managementAssess restrictionFrequency spectrumVideo transmission
The invention relates to a channel allocation method for D2D multicast video transmission in a social perception network. The channel allocation method comprises the step of D2D multicast cluster, access control, optimal transmitting power allocation, and optimal channel allocation. The beneficial effects of the invention are as follows: the paint has good effects. According to the channel allocation strategy for D2D multicast video transmission in the social perception network, D2D multicast communication of two stages is added into video transmission of a traditional cellular network. Therefore, D2D multicast communication in the first stage is realized. A video can be transmitted to cellular users in a cell in a multicast manner through a base station. A full-load transmission process is realized; if yes, D2D multicast communication in the second stage is carried out, firstly, cellular users capable of serving as cluster heads of the D2D multicast groups are selected, and after theD2D multicast clusters are formed, the cluster head users forward video data received by the cluster head users to the D2D users in the multicast groups in a mode of multiplexing uplink channel spectrum resources of other cellular users.
Owner:XIDIAN UNIV
PM2.5 deep learning inversion method combining remote sensing data and social perception data
InactiveCN110287455AFully consider natureFully consider the economyParticle suspension analysisComplex mathematical operationsInformation processingData set
The invention discloses a PM2.5 deep learning inversion method combining the remote sensing data and the social perception data. The PM2.5 deep learning inversion method comprises the steps of preprocessing the PM2.5 data of a ground station point, the remote sensing data, the social perception data and the auxiliary data; performing feature variable extraction and calculation on the multi-source data by using a geoscience space statistics and analysis method and a remote sensing information processing means; carrying out space-time matching on the multi-source data in a gridding mode, taking a grid with a ground station point true value as a training sample, and generating a multi-source data set with uniform space and time; normalizing the grid data set with the site PM2.5 true value, then inputting the grid data set into a deep learning model for training, and inverting the unknown grid PM2.5 concentration through the model after the grid data set passes the verification; and carrying out fine PM2.5 space-time distribution mapping on an inversion result. According to the method, the multi-source information can be effectively mined by using a deep learning technology, the defect of a traditional statistical model in a nonlinear problem is overcome, and the higher inversion precision and the finer space-time PM2.5 distribution are obtained.
Owner:WUHAN UNIV
Multisource heterogeneous data-based real estate information visualization system
InactiveCN108921734AImprove interactivityShow fullData processing applicationsSocial mediaMultiple linear regression analysis
The invention discloses a multisource heterogeneous data-based real estate information visualization system. The system is characterized by comprising a real estate information module, a regional function module, a traffic analysis module, a social perception module and a comprehensive evaluation module, wherein the real estate information module is used for displaying real estate information; theregional function module is used for carrying out statistical analysis on quantities and distances of infrastructure around real estates; the traffic analysis module is used for carrying out statistical analysis on traffic conditions and peak hours around the real estates; the social perception module is used for mining texts of social media data and displaying social perception conditions aroundthe real estates through word frequency word clouds, keyword extraction and topic models; and the comprehensive evaluation module is used for establishing a multiple linear regression model by applying statistical methods such as multiple linear regression analysis and the like, determining real estate evaluation indexes and methods, and obtaining pointed real estate cost performance-based transaction suggestions so as to support more reasonable house purchasing decisions.
Owner:BEIHANG UNIV
Method for sensing network sudden hotspots based on perception maximization
ActiveCN108153914AAchieving real-time perceptionWeb data indexingCharacter and pattern recognitionUnexpected eventsPattern perception
The invention provides a method for sensing network sudden hotspots based on perception maximization. The method comprises the following steps: collecting historical sudden events in a network and corresponding post messages at first, defining reference time and difference between time of post messages of participates and the reference time, defining evaluation indexes for sensing the post messages according to perception maximization, and training a perceptron set; aggregating the post messages acquired in real time in the perceptron set into different clusters on the basis of a text similarity detecting method, wherein each cluster is regarded as a potential hotspot; and detecting every potential hotspot, and when the observation amount of the post messages corresponding to a certain potential hotspot at a certain time is not smaller than a threshold value, regarding that the potential hotspots burst out. All user nodes in a social network are regarded as the perceptron according tocommunication characteristics of information in the social network, all information which circulates in the social network is regarded as perceptual information, and the information which circulates in the social network, namely social perception, is sensed through the perceptron which monitors the social network.
Owner:北京东方科诺科技发展有限公司
Urban agglomeration living space construction time identification method
PendingCN112818923ASolving the \"Semantic Gap\"Resolution timeCharacter and pattern recognitionSensing dataEnvironmental resource management
The invention relates to an urban agglomeration living space construction time identification method, which comprises the steps of collecting Landsat5 / 7 / 8 data through a google earth engine platform, and calculating time sequence data of three indexes, namely, NDVI, MNDWI and SWIR; obtaining urban residential land boundary vector data through map data and crawler analysis, and carrying out data analysis and space connection in Arcgis; classifying and identifying the residential land before and after a specific time point through a random forest classification method; and identifying the construction time of the residential land in a specific time period year through a time sequence segmentation method to complete the identification of the construction time of the whole residential land. According to the method, the construction time of the urban residential land is identified by fusing the spectrum and texture information of the remote sensing data and the social perception data, so that the problems of a semantic gap and a time gap existing in the two data are solved, and scientific and technical means support is provided for researching horizontal and vertical expansion and space-time evolution of the urban residential land.
Owner:INST OF GEOGRAPHICAL SCI & NATURAL RESOURCE RES CAS
Health-care climate evaluation method combining climate data and social perception data
The invention discloses a health-care climate evaluation method combining climate data and social perception data. The method comprises the following steps: S1, collecting historical climate information and latitude and longitude information of different positions in an evaluation area; s2, calculating a temperature and humidity index IH, a wind-cold index IWC and a holiday index IHC of all positions in the set area in each day within a set year number; s3, constructing a health-care climate model; s4, constructing a health-care climate social perception model; s5, according to the health-care climate model and the health-care climate social perception model, a final health-care climate evaluation model is constructed; s6, performing classification and grading evaluation on the result by using a natural breakpoint method through reclassification; and finally, a result D is obtained, D is a geographic space distribution map layer, the file is raster data and is composed of pixels organized according to rows and columns, and each pixel comprises latitude and longitude information of the point and a D value. According to the method, historical data information, social perception data and multi-source data fusion evaluation are combined, and the evaluation model of the health and maintenance climate can be accurately obtained.
Owner:四川省气候中心(西南区域气候中心)
Metering device clock error trend prediction method based on social perception
PendingCN111476392ATroubleshooting Clock ErrorsForecastingNeural architecturesAlgorithmGenerative adversarial network
The invention discloses a metering device clock error trend prediction method based on social perception, and relates to the field of electric power operation and maintenance. Existing work can only solve the clock error problem of a specific scene and is not universal enough. According to the method, a time sequence evolution gene model is adopted, an ammeter clock error is divided into a plurality of sub-sequences on a certain window, the model can analyze the error change characteristics of the window sub-sequences, and the sub-sequences with similar distribution are divided into one blockthrough a classifier of the model; genes for generating the subsequence distribution characteristics are mined through a generative adversarial network; the genes of the sub-sequences in history are combined, the evolution process of the sub-sequences is analyzed through a recurrent neural network, the evolution mode of the sub-sequences is analyzed and the future clock error trend of the sub-sequences is predicted. The technical scheme is not limited to specific devices and reasons causing errors, and can adapt to different scenes, so that a more universal scheme is provided, and the generalized clock error problem of the electric energy device is solved.
Owner:WENZHOU ELECTRIC POWER BUREAU +4
An urban land use function recognition method based on remote sensing images and point of interest data
ActiveCN113111691BAvoid inefficiencyAdaptableCharacter and pattern recognitionNeural architecturesGeographic featureFunctional identification
The invention proposes an urban land use function recognition method based on remote sensing pictures and interest point data. The previous identification methods of urban functional areas only aimed at a single remote sensing image data or social perception data, ignoring the overall functional attribute information of urban areas to a certain extent. To solve this problem, a multimodal urban land use function identification framework is proposed. The methods include: constructing a deep multi-channel residual neural network for urban remote sensing image recognition, and exploring spatial and geographical features in remote sensing images. Second, the frequency-functional density of the distribution of interest points in different functional areas of the city is studied, and the functional distribution features of urban areas are extracted based on metric learning. Finally, two features of different dimensions are fused in the heterogeneous feature fusion module to further improve the performance of urban land use function recognition. Experiments prove that this method has good practicability and can be widely used in the identification of urban functional areas.
Owner:SICHUAN UNIV
Urban land function recognition method based on remote sensing picture and interest point data
ActiveCN113111691AAvoid featuresAvoid inefficiencyCharacter and pattern recognitionNeural architecturesGeographic featureResidual neural network
The invention provides an urban land function recognition method based on remote sensing pictures and interest point data. A conventional urban functional area recognition method only aims at single remote sensing image data or social perception data, and neglects overall functional attribute information of an urban area to a certain extent. In order to solve the problem, a multi-mode urban land function recognition framework is provided. The method comprises the following steps: constructing a deep multi-channel residual neural network for urban remote sensing image recognition, and exploring spatial geographic features in a remote sensing image; secondly, frequency function density of interest point distribution of different functional areas of the city is researched, and function distribution characteristics of the city area are extracted based on metric learning; and finally, fusing two features of different dimensions in the heterogeneous feature fusion module, thereby further improving the urban land function recognition performance. Experiments prove that the method has good practicability and can be widely applied to recognition of urban functional areas.
Owner:SICHUAN UNIV
A D2D communication mode selection method based on social perception
ActiveCN108718444BIncrease data transfer rateSolve the problem of selectivityOrthogonal multiplexNetwork planningEngineeringData mining
The invention discloses a D2D communication mode selecting method based on social sensing. The method comprises the steps that step one, the social connecting strength between a content providing userand a content demanding user is firstly calculated; step two, the theoretical transmission rate between the content providing user and the content demanding user is calculated; step three, a user utility matrix is calculated according to the social connecting strength and the theoretical transmission rate; step four, user matching is conducted taking user total utility maximization as the goal according to the user utility matrix obtained in step three, and if the content demanding user is matched with a base station, contents are obtained from the base station by the content demanding user through a cellular mode; if the content demanding user is matched with the content providing user, the content demanding user uses a D2D mode to obtain the contents from the content providing user. Themethod has the advantage that problems of user matching and mode selecting between multiple content providing users and content demanding users can be effectively solved.
Owner:NANJING UNIV OF POSTS & TELECOMM
Environment adaptive routing method and system based on Bayesian classification and medium
ActiveCN113301627AImprove real-time awarenessImprove distribution efficiencyCharacter and pattern recognitionHigh level techniquesClassification methodsEngineering
The invention relates to an environment adaptive routing method and system based on Bayesian classification and a medium, and the method comprises the steps: constructing a dynamic network environment learning model, and carrying out the dynamic perception of each node, and obtaining a dynamic perception information set of each node; selecting any encountering node pair, and obtaining a cooperation type vector between the two encountering nodes and cooperation degree information sets corresponding to the two encountering nodes one by one according to the dynamic sensing information sets of the two encountering nodes based on a Bayesian classification method; according to a preset adaptive data distribution strategy, completing data distribution of the two encountering nodes according to the dynamic sensing information set, the cooperation degree information set and the cooperation type vector of the two encountering nodes; and traversing each encountering node pair to complete data distribution of the social perception network. According to the method, the self-perception of a dynamic change network environment is effectively improved, the self-adaptability of a data distribution strategy and the self-adjustability of a cooperation degree incentive mechanism are enhanced, and the data distribution efficiency is remarkably improved.
Owner:SHANDONG WOMENS UNIV
A method and system for optimizing computing task network parameters combined with social perception
ActiveCN113015144BReduce energy consumptionData processing applicationsHigh level techniquesTask networkAlgorithm
The present invention discloses a computing task network parameter optimization method and system combined with social perception, and relates to the field of MEC-D2D network application technology, including determining the MEC-D2D network architecture, data transmission model, and consumption model combined with social networks corresponding to the research area and social trust matrix; according to the social trust matrix and the data in the consumption model, execute the consumption calculation function and the data transmission consumption calculation function to determine the maximum long-term system network utility function and constraint conditions corresponding to the research area, and use the Lyapunov optimization algorithm to maximize The system network utility function is decoupled to obtain three deterministic optimization objective functions; according to the total amount of computing task data and optimization algorithm corresponding to the research area, the above three deterministic optimization objective functions are solved to obtain the optimal network parameters. The application of the above network parameters in the present invention can reduce the energy consumption of the device execution process and the device transmission process in the MEC-D2D network for a long time.
Owner:NORTH CHINA ELECTRIC POWER UNIV (BAODING)
A user discovery and resource allocation method based on social perception in d2d communication
ActiveCN105960024BOptimize quantityImprove performanceWireless communicationCarrier signalThroughput
Owner:BEIJING UNIV OF POSTS & TELECOMM
The extraction method and medium of urban agglomeration green space
The invention provides a method and medium for extracting urban agglomeration green space. Among them, the method includes: obtaining high-resolution remote sensing data of urban agglomerations, and extracting land cover data of urban agglomerations; obtaining social perception data of urban agglomerations, and extracting social function attribute data of urban agglomeration land; Functional attribute data, classify the land of the urban agglomeration, and obtain the classification information related to the greenness of the urban agglomeration land; according to the classification information, extract the greenness of the urban agglomeration. The present invention solves the problem in the related art that only relying on a single remote sensing data can only obtain land cover information, but cannot obtain the social function attributes of urban green space, and realizes the statistics of green space of urban agglomerations including social function attributes and research.
Owner:INST OF GEOGRAPHICAL SCI & NATURAL RESOURCE RES CAS
A Congestion Control Method Based on Social Awareness in Delay Tolerant Networks
ActiveCN103532865BReduce the impact of routing efficiencyReduce the probability of packet lossData switching networksTime delaysNetwork connection
Owner:王堃
RIS-based social perception V2X network joint resource optimization method
PendingCN113747396AGuaranteed reliabilityImprove performancePower managementParticular environment based servicesMultiplexingResource assignment
The invention discloses an RIS-based social perception V2X network joint resource optimization method. A problem is decomposed into three sub-problems which can be effectively solved: RIS reflection coefficient design, power distribution of each pair of vehicles and spectrum multiplexing mode optimization. On the basis, a novel three-stage joint resource allocation and RIS optimization (JRARO) algorithm is provided. Simulation results show that the proposed algorithm significantly improves the V2I total capacity, the RIS can compensate channel gain loss caused by high maneuverability of the vehicle to a great extent, and the superiority of RIS assisted vehicle-mounted communication is verified.
Owner:NANTONG UNIVERSITY
Method and system for personalized dynamic vehicle sharing based on price benefit and social perception
ActiveCN109447356BImproving rideshare service experienceMeet individual travel needsForecastingPersonalizationArtificial intelligence
The present invention specifically relates to a method and system for personalized dynamic carpooling based on price income and social perception. The present invention is based on the personalized dynamic carpooling method based on price income and social perception. The social relationship that users care about and the price mechanism act simultaneously In the vehicle-sharing matching service, when matching, under the premise of ensuring the basic itinerary constraints of passengers, not only consider the price benefits brought by new passengers to drivers, but also consider prioritizing passengers with certain social relationships in a car , in the case of meeting the basic itinerary needs of passengers, taking into account the comfort of passengers and the price benefits of drivers. The present invention can provide users with a complete set of optimization mechanism for the matching process. By using the upper limit of price income and social relationship, branch and limit algorithm and index mechanism to cut the search space, the speed of matching passengers and vehicles is improved, and the system operation is improved. Efficiency improves the shared ride experience.
Owner:ZHENGZHOU UNIV
Infection transmission prediction method and system based on Internet of Things perception
ActiveCN114068036AHigh speedImprove accuracyEpidemiological alert systemsNeural architecturesInfection transmissionMedicine
The invention provides an infection transmission prediction method and system based on Internet of Things perception. The method comprises the steps of: obtaining first close contact population information of a first region according to a first information collection module; obtaining first positioning sensing information; obtaining first social perception information; constructing an Internet of Things perception model which comprises a first preprocessing function; obtaining a first action track which is the action track of an infected person; carrying out anti-aggregation analysis on the first close contact population to obtain a plurality of infection aggregation points; carrying out infection aggregation point analysis and infection time point analysis, and determining a first aggregation distribution characteristic and a first time distribution characteristic; and performing prediction according to an ARIMA model to obtain first prediction information and first propagation information. With the method and system adopted, the technical problem that perception speed and perception accuracy are low in the prior art due to complexity of an application environment and imperfection of a perception technology is solved.
Owner:JIANGSU VOCATIONAL COLLEGE OF BUSINESS
Residential area extraction and type recognition method based on remote sensing and social perception data
PendingCN111832527AReal-time extractionEfficiently provideCharacter and pattern recognitionGeographical information databasesUrban researchData source
The invention relates to a residential area extraction and type recognition method based on remote sensing and social perception data. The method comprises the steps of remote sensing image preprocessing, angle difference feature calculation, residential area Point of Interest recognition, residential area boundary extraction and residential area type recognition. Aiming at the blank of extractionand type recognition of urban residential quarters at present, remote sensing and social perception data are fused, a technical scheme for quickly and effectively carrying out the extraction and typerecognition method of the urban residential quarters is provided, and an accurate data source is provided for urban planning departments and urban researchers; the effect of extracting residential areas in real time can be achieved; in addition, due to the fact that text similarity analysis is combined, residential area surface vector files can be quickly and effectively provided for urban researchers and urban planning departments.
Owner:AEROSPACE INFORMATION RES INST CAS
Modeling analysis method and system based on social perception data
The invention discloses a modeling analysis method and system based on social perception data, and the system comprises a perception data obtaining module, an impact factor modeling module, and an explanatory analysis output module. The perception data obtaining module is used for collecting and obtaining related multipath original data for a traffic road section, and carrying out the primary preprocessing; the influence factor modeling module is used for establishing a relation model of called environmental influence factors and pedestrian road section traffic accident data, the explanatory analysis output module is used for explaining and analyzing predictive variables and influence factors in the relation model, and the perception data acquisition module is electrically connected with the influence factor modeling module. The influence factor modeling module is electrically connected with the explanatory analysis output module, the incidence relation between influence factors and pedestrian traffic accidents is established through social perception data, variable prediction and explanatory analysis output of the influence factors are carried out, and the method has the advantage that environment and pedestrian traffic accident analysis is carried out through the perception data.
Owner:南通市大数据发展集团有限公司
Calculation task network parameter optimization method and system combined with social perception
ActiveCN113015144AReduce energy consumptionData processing applicationsHigh level techniquesTask networkLyapunov optimization
The method comprises the following steps: determining a social network-combined MEC-D2D network architecture corresponding to a research area, a data transmission model, a consumption model and a social trust matrix; according to the social trust matrix and a data execution consumption calculation function and a data transmission consumption calculation function in the consumption model, determining a maximum long-term system network utility function and constraint conditions corresponding to the research area; a Lyapunov optimization algorithm is utilized to decouple the maximized system network utility function, and three deterministic optimization objective functions are obtained; and finally, according to the total amount of calculation task data corresponding to the research area and an optimization algorithm, solving the three deterministic optimization objective functions to obtain optimal network parameters. By applying the network parameters, the energy consumption of the equipment execution process and the equipment transmission process in the MEC-D2D network can be reduced for a long time.
Owner:NORTH CHINA ELECTRIC POWER UNIV (BAODING)
Mobile ad hoc cloud terminal cluster construction and service method based on social perception
ActiveCN112637900ANarrow searchEffectively achieve matchingNetwork traffic/resource managementNetwork topologiesTerminal equipmentEngineering
The invention discloses a social perception-based mobile ad hoc cloud terminal cluster construction and service method, which comprises the following steps that: 1) user terminals are randomly distributed in a cell served by a base station, and periodically report terminal resource states of the user terminals to a base station controller by taking a fixed time slot as a unit; 2) the base station controller establishes and maintains a user encountering information graph and a terminal equipment resource table; and 3) after receiving the terminal resource state, the base station controller autonomously constructs an ad-hoc cloud terminal cluster by adopting an ad-hoc cloud terminal cluster construction algorithm based on non-uniform granularity according to the number requirement of the terminal clusters. According to the method, the terminals are classified according to the performance of the resources, the terminal clusters are formed by the nodes with similar performance, the tasks are cooperatively completed through near-distance D2D communication, and the matching of the tasks and the resources is effectively realized, so that the task scheduling speed is increased, and the terminal resource utilization rate of the network is increased.
Owner:NANJING VOCATIONAL UNIV OF IND TECH
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