19 results about "Social perception" patented technology

The invention discloses a land value evaluation method and system based on multi-source heterogeneous data fusion, and relates to the technical field of land economic evaluation. The invention discloses a land value evaluation method and system based on multi-source heterogeneous data fusion. The method comprises four steps of multi-source data acquisition and preprocessing, standardized evaluation index quantification, index weighted fusion and value calculation, and value distribution diagram generation and output. Firstly, four types of data of background status, planning, market feedback and social perception are acquired and preprocessed; secondly, constructing a hierarchical index system to quantify indexes; determining a weight through an analytic hierarchy process and calculating a land value index according to a preset formula; and finally generating a value distribution diagram in a thermodynamic diagram form. The method realizes standardization, high efficiency and visualization of land value evaluation, can be applied to the fields of city updating, land market monitoring, government planning decision making and the like, and provides scientific support for related decision making.

The invention discloses a public service supply and demand matching intelligent regulation and control system based on social perception data, which relates to the technical field of public service supply and demand matching and comprises a data construction module, a service mapping module, a disturbance identification module, an anomaly judgment module, a strategy execution module and a regulation and control feedback module. The disturbance identification module is used for performing time sequence clustering analysis on the data record set, identifying a data segment influenced by an external non-service event, and calibrating the data segment as a disturbed social perception data segment; and the anomaly judgment module is used for obtaining the associated behavior feature information of each disturbed social perception data segment, evaluating the data anomaly degree of each disturbed social perception data segment by constructing an anomaly degree generation model after obtaining, and carrying out classification according to an evaluation result. According to the method, the problem of resource misadjustment caused by service external event interference in social perception data is solved, and accurate identification and dynamic grading adjustment of public service regulation response are realized.

The present application discloses a method, device, equipment and storage medium for detecting selfish nodes in a social perception network, and relates to the field of data processing technology. The present application discloses a method for detecting selfish nodes in a social perception network, including: obtaining each node in the social perception network, judging whether the node is a selfish node according to the residual energy and the rate of rejecting received messages of each node, and obtaining a first judgment result; when the first judgment result is that the node is not the selfish node, judging whether the node is a selfish node by calculating the social trust of the node, and obtaining a second judgment result; when the second judgment result is that the node is not the selfish node, checking whether the node forwards the message after receiving the message and checking whether the node discards the message to judge whether the node is a selfish node. The present application can detect selfish nodes in a social perception network and improve data transmission performance.

The invention provides a post-disaster scenic spot recovery evaluation method and device fusing ecological monitoring and social perception, and relates to the technical field of data processing, and the method comprises the steps: obtaining first remote sensing image data and first social media data of each scenic spot in a target scenic spot before a disaster occurs, the second remote sensing image data and the second social media data are obtained after the disaster occurs; determining an ecological evaluation index based on the first remote sensing image data and the second remote sensing image data; determining an emotion feedback index based on the first social media data and the second social media data; and based on the ecological evaluation indexes, the emotion feedback indexes and preset thresholds corresponding to the ecological evaluation indexes, obtaining a recovery evaluation result of each scenic spot in the target scenic area after the disaster occurs. According to the post-disaster scenic spot recovery evaluation method fusing ecological monitoring and social perception, accurate, comprehensive and fine recovery evaluation can be carried out on the target scenic spot.

The present invention provides a health care information push method and system based on social perception technology, the method comprising: obtaining health care comment filter words, and creating an information retriever to crawl comment data according to the health care comment filter words to obtain corresponding health care comment information; performing text processing on the health care comment information to obtain a number of first comment information; performing sentiment analysis on the first comment information to obtain second comment information; obtaining a preset number of the second comment information, combining with a preset reputation value calculation model, to obtain the reputation value of the health care location; generating health care location recommendation information according to the reputation value of the health care location, and pushing the health care location recommendation information to the target user. Therefore, by applying the method described in the present invention, it is possible to effectively promote each health care location to improve its own health care services and assist users in selecting suitable health care locations, and efficiently handle complex health care comments.

The invention discloses a social perception maximization method based on differentiatable graph optimization, and relates to the technical field of data mining and network analysis, and the method comprises the steps: obtaining social network cascade data, and constructing a weighted bigraph of a user perception event; constructing a social perception forward propagation model according to the weighted bigraph, defining an activation state variable for each user, defining a total activation amount for each event, and introducing a function to evaluate the perception quality of each event; the activation state variables of all the users form an activation vector, the process of searching the optimal activation vector is constructed into a differentiable optimization task, and the optimization target is to maximize the perceived quality sum of all the events; and according to the optimal activation vector, generating a final seed user set as an optimal solution for maximizing social perception. According to the method, the problems of local optimization and model simplification in the prior art are solved, global optimization is realized, and the user influence can be accurately modeled.

The invention discloses a smart traffic adaptive regulation and control system and method based on social perception, and belongs to the technical field of traffic Internet of Things. Comprising a multi-modal social perception layer module, an edge intelligent preprocessing node module, a dynamic social flow modeling engine module, a space-time social prediction engine module, an adaptive signal lamp optimization module, an Internet of Vehicles collaborative pushing module and a traffic closed-loop feedback module. A social event factor is dynamically injected through an LSTM-Transform hybrid model, and self-adaptive adjustment of space-time prediction is achieved; the accuracy and robustness of traffic prediction are remarkably improved, and the congestion risk can be accurately recognized in advance in the social event high-incidence period; and prediction misjudgment caused by neglecting social behaviors is avoided, so that the system can dynamically respond to traffic flow changes, the congestion pressure is effectively relieved, and the road traffic efficiency and the overall traffic smoothness are improved.

This invention relates to a method and apparatus for predictive control of a robot device using a social perception model. The invention relates to a computer-implemented method for determining the control trajectory of a robot device (1), comprising the following steps: - performing (S1-S8) information theory model predictive control, thereby applying prior control trajectory samples at each time step ( u * ) to obtain a given time range ( t f The control trajectory depends on a data-driven trajectory prediction model to determine (S21) the control trajectory sample prior. u * The trajectory prediction model is trained to output control trajectory samples based on the actual state of the robot device (1) as the prior of the control trajectory samples. u * ).

The application discloses a social perception recommendation method under multi-category sensitive link relationship protection and relates to the technical field of big data analysis. The application generates vector representations of users and items by using a heterogeneous graph neural network, introduces a mask protection mechanism of multi-type edges, solves the privacy leakage problem of multiple types of sensitive links, and thus prevents reasoning attacks of attackers based on background knowledge. A heterogeneous social perception model based on a session is constructed based on a session and multi-type nodes, recommendation performance is improved, the problem that multi-type node information cannot effectively act on a recommendation model is solved, and the problem of limited data use in a real scene is solved.

The invention belongs to the technical field of wireless communication, and discloses a wireless network edge caching method based on device-to-device (D2D), a block chain and social perception, which realizes content caching on user equipment (UE) and allows the UE to cache the content from the UE, obtain the content from other UE through a D2D link or obtain the required content from a content server. The intimacy between users is evaluated through social perception cooperation, and a real D2D communication link is reconstructed, so that a caching strategy is optimized. Considering the problem that terminals from different operation institutions cannot mutually trust to share contents, the block chain technology is combined to supervise cache transactions, UE transaction records are continuously updated, and a safe and credible transaction platform is constructed. In a D2D edge cache system, the invention aims to optimize content deployment and access strategies so as to reduce D2D communication delay and energy consumption. In order to cope with the dynamic change of the environment, the invention provides a deep reinforcement learning (DRL) framework to solve the problem.

The application discloses a public service supply and demand matching intelligent regulation and control system based on social perception data, relates to the technical field of public service supply and demand matching, and comprises a data construction module, a service mapping module, a disturbance identification module, an abnormality judgment module, a strategy execution module and a regulation and control feedback module; the disturbance identification module performs time series clustering analysis on a data record set, identifies a data section affected by external non-service events, and labels the data section as a disturbed social perception data section; the abnormality judgment module acquires associated behavior characteristic information of each disturbed social perception data section, evaluates the data abnormality degree of each disturbed social perception data section by constructing an abnormality degree generation model after acquisition, and classifies according to the evaluation result. The application solves the problem of resource misadjustment caused by external service event interference in social perception data, and realizes accurate identification and dynamic hierarchical adjustment of public service regulation and control response.

The present invention discloses an intelligent cooperative caching strategy based on asynchronous federated learning and social perception in the Internet of Vehicles (IoV). The strategy includes: a user vehicle sends a cache request to a local RSU; a local RSU, nearby user vehicles, neighboring RSUs, and macro base stations with requested content are selected according to priority to respond to the user vehicle's cache request, and inter-vehicle communication uses a social network; after the user vehicle receives the request content, it uses the vehicle's local local model to update the local cache content, and updates the local local model based on the vehicle's local experience pool data; the selected vehicle uploads the updated local model to the local RSU; when the local RSU receives the local model, it updates the global model based on vehicle weights; and the local RSU uses the global model to update the local cache content based on the requested content of vehicles in its service area. The present invention uses DQN training under asynchronous FL to collaboratively update the cache, which can reduce the transmission delay of the request content and improve the cache hit rate.

The invention relates to the technical field of image processing, and discloses an old cell identification method combining transfer learning and a graph neural network, and the method comprises the steps: obtaining multi-source remote sensing data, social perception data and building footprint data of a sample region; performing space unit division on the sample region to obtain basic evaluation units of the block; constructing feature indexes of the blocks; a plot in the sample region is used as a node, a Delaunay triangulation algorithm is used to construct a spatial adjacency graph network, and a spatial graph network is constructed; the graph attention network is utilized, weights among nodes of the space graph network are calculated through neighborhood sampling and a feature aggregation mechanism, and an old cell recognition result is output; a source domain model is obtained based on graph attention network training, and a transfer learning model is constructed by using a domain adaptation strategy. According to the method, efficient, accurate and extensible old community identification is realized, and technical support is provided for city update decision and space governance practice.

The invention relates to the technical field of virtual reality, in particular to a virtual reality transmission method and system, electronic equipment, a storage medium and a product, and the method comprises the steps: obtaining the current positions of a target user and other users around the target user in a virtual environment; constructing a target potential field according to the current positions of the target user and other users, and determining the restricted areas of other users according to the target potential field and the target transmission position of the target user; and evaluating and adjusting the target transmission position based on the restricted area, enabling the actual transmission target point to avoid the restricted area during adjustment, and executing spatial movement from the current position of the target user to the actual transmission target point. Therefore, the problems of discomfort, social anxiety and the like caused by the fact that the user abruptly intrudes into the personal space of other people due to the fact that a virtual reality transmission method in the related technology lacks social perception in a multi-person environment are solved.

The invention discloses a social perception robot navigation method, device and equipment, a medium and a product. The method comprises the following steps: acquiring grid map data, robot position data and target object voice data; converting the grid map data into an image information vector by using a first preprocessing network, converting the robot position data into a relative position information vector, and converting the target object voice data into a condition code vector by using a second preprocessing network; connecting to obtain an aggregation state; and inputting the aggregation state into a pre-trained HSAC-LLM model to obtain a target action, and generating voice prompt information according to the target action, so that the target object receives the voice prompt information. According to the embodiment of the invention, bidirectional natural language interaction is realized in the navigation process between the robot and the pedestrian, real-time communication is promoted, navigation safety is enhanced in a dynamic environment, intelligent obstacle avoidance is realized, and interaction experience is provided at the same time.

The invention relates to the field of urban governance, and discloses an urban physical examination method based on social perception big data fusion, and the method comprises the steps: S10, collecting and processing heterogeneous social perception big data from a plurality of channels; s20, preprocessing the heterogeneous social perception big data; s30, based on a preset urban physical examination framework and the preprocessed heterogeneous social perception big data, an evaluation system covering multiple criterion layers is constructed, and each index defines a data source and a housing, community or urban area scale to which the data source belongs; s40, an analytic hierarchy process is adopted, a judgment matrix is constructed for each criterion layer through expert scoring, the weight of each index is calculated, consistency check is carried out, and the comprehensive weight of each index is determined; and S50, based on the comprehensive weight of each index, taking a regular grid as a minimum space evaluation unit, uniformly aggregating the point, line, surface and heterogeneous social perception big data to a grid unit by using a space analysis tool, and calculating the governance development degree score of each grid.

The application provides a speaking head generation method, device, equipment, medium and product. The speaking head generation method comprises the following steps: a step of extracting speech features and facial motion features of a speaker and a listener from a multi-round dialogue scene comprising the speaker and the listener, processing the speech features and the facial motion features by using a motion coding network to obtain interaction representation; a step of injecting social perception features into the interaction representation to obtain Gaussian displacement correction and joint representation; a step of generating facial network animation according to the joint representation; a step of correcting the facial network animation according to the Gaussian displacement correction to obtain a dynamic three-dimensional Gaussian primitive set; and a final generation step of bidirectionally generating a speaking head according to the dynamic three-dimensional Gaussian primitive set. Thus, the problems of the contradiction between realism and interactivity, the bottleneck of computational efficiency and practicality, and the lack of social context factors in the prior art are solved.

The invention relates to a population distribution prediction sample generation method fusing multi-source remote sensing and social perception data, particularly relates to the field of computers, and remarkably improves the precision and reliability of a population distribution prediction sample through multi-source data fusion and cooperative processing. According to the method, the problems of spatial-temporal inconsistency, noise interference, insufficient regional generalization ability and the like of multi-source data are effectively solved, the generated sample can accurately reflect the spatial-temporal distribution characteristics of the population and has good adaptability, and the technology provides a high-quality data basis for applications such as earthquake risk assessment and supports long-term disaster prevention planning and resource optimization configuration.

This invention provides a public space evaluation method that integrates social perception data. Through multi-source perception data collection, behavior log construction, group behavior feature extraction, spatial function modeling, behavior-function matching degree assessment, and attribution analysis, it achieves quantitative diagnosis of the adaptability of community public spaces among different groups. By integrating visual tracking and questionnaire annotation, a multi-dimensional log with behavioral semantics is formed. Spatiotemporal clustering and topic modeling are used to extract group behavior fingerprints, and a spatial ontology library is used to quantify the service attributes of each functional unit. Based on an intent mapping mechanism, the matching degree between behavior and space is determined. Combined with counterfactual simulation and causal analysis, spatial mismatch and its causes are located. This invention can automatically identify service blind spots and output space optimization suggestions for different groups, improving the refinement and fairness of community public space governance.