102 results about "Rurality" patented technology

The invention discloses an educational resource recommendation method and system based on artificial intelligence. The method comprises the following steps: acquiring audio data, interaction data and task data acquired by a user terminal; performing feature extraction on the audio data, the interaction data and the task data to obtain an emotion feature vector, a learning rhythm vector and a content feature vector; inputting the emotion feature vector and the learning rhythm vector into a pre-constructed emotion recognition model to obtain a psychological state vector; the cognitive load is calculated based on the learning rhythm vector and the content feature vector, and then the cognitive load is corrected through the psychological state vector; matching a state interval of the corrected cognitive load according to a preset threshold interval; and according to the state interval, adjusting a difficulty coefficient of the recommended course, rearranging a course content sequence and an auxiliary learning prompt, generating structured data, and outputting the structured data as an intelligent auxiliary learning recommendation result. According to the invention, online learning interactivity and teaching quality in rural and remote areas are effectively improved.

The invention discloses a multi-objective optimization method, medium and equipment for passenger and goods mail fusion in rural areas, and the method comprises the steps: S1, building a multi-objective optimization model of urban and rural passenger vehicle operation based on the constraint conditions of urban and rural passenger vehicle operation; s2, acquiring operation parameters of urban and rural passenger vehicles and inputting the operation parameters to the multi-objective optimization model; s3, determining and coding values of decision variables involved in the operation optimization process; s4, searching an optimal solution set by using a multi-target genetic algorithm; and S5, adjusting an urban and rural passenger vehicle operation scheme based on the optimal solution set, and departing the vehicle. The urban and rural passenger transport vehicle operation multi-objective optimization model under the passenger-goods-mail fusion is constructed, the optimal decision of the vehicle operation problem of the subject benefits of all parties is met, and the problem that the transport capacity and the transport volume of the passenger-goods-mail in the rural area are not matched and unbalanced is effectively solved.

The invention belongs to the technical field of residential area ecological evaluation, and particularly relates to a GIS-based hydropower engineering residential area ecological suitability evaluation method. The method comprises the following steps: aiming at the terrain, climate characteristics and social attributes of the residential area of the hydropower project, extracting evaluation factors of ecological suitability of the residential area from multiple aspects of the terrain, the environment, the society, the traffic and the space; adopting an analytic hierarchy process and a Delphi method to analyze the obtained evaluation factors, and constructing a residential area ecological suitability index system; and superposing the spatial data of each evaluation factor by using ArcGIS to obtain a residential area ecological suitability evaluation model, and analyzing the overall ecological suitability of the residential area. According to the method, by obtaining the residential area ecological suitability evaluation model, the relation between hydropower engineering construction and rural residential area development and ecological environment protection can be better evaluated, sustainable development of the regional ecological environment is achieved, and the peaceful industry of reservoir area immigrants is guaranteed.

The invention belongs to the technical field of building group flood influence analysis, and provides a rural building group flood disaster loss assessment method and system for solving the problem that the accuracy of an assessment result is low due to the fact that an existing building flood loss function does not fully consider uncertainty factors in the loss assessment process. The method comprises the following steps: simulating a dynamic evolution process of a flood disaster by adopting a hydrodynamic model to obtain an inundation depth map and a maximum inundation depth map; comparing the submerging water depth map with the SAR image water body extraction data and the social media data to obtain a flood simulation result; combining the building classification information with the maximum submerging depth map to obtain the submerging depth of each building; calculating component information of the building; according to the component information and the submerging depth, building flood vulnerability analysis is carried out, and the total loss of all buildings is determined; and evaluating the effect of the current disaster prevention measure according to the total loss under different disaster prevention measures. The method can provide a scientific basis for building flood loss assessment and disaster prevention decision.

The invention provides a rural non-point source water quality prediction method and system based on machine learning, and relates to the technical field of machine learning, and the method comprises the steps: obtaining basic data; constructing a pollutant migration path according to the basic data to obtain a dynamic migration network; performing space-time state evolution according to the dynamic migration network to obtain a dynamic graph structure; performing multi-modal feature fusion according to the dynamic graph structure, and quantifying the combined influence of factors such as farmland plots, soil attributes and crop types on the water quality change of the monitoring points by analyzing the dependency relationship of pollutant flux in the graph structure on the space-time dimension to obtain pollution contribution degree features; constructing a prediction function according to the pollution contribution degree characteristics to obtain a water quality prediction function; generating a water quality value based on the water quality prediction function, inputting the real-time environment data into the water quality prediction function, and calculating to obtain a water quality prediction result. According to the method, the accuracy and reliability of water quality prediction in a rural non-point source pollution complex scene are remarkably improved.

The invention discloses a rural area new energy consumption-oriented user side time-of-use electricity price optimization method, which comprises the steps of determining an original daily net load curve according to user side load data and new energy output data of a rural area; clustering the original daily net load curve by using an improved K-means + + algorithm to obtain a typical daily net load curve; carrying out peak-valley period refined division based on the typical daily net load curve to obtain a peak-valley period division result; taking the minimum peak-valley difference rate of the power system in the rural area as a target, constructing a target function with the minimum peak-valley difference rate, and constructing a time-of-use electricity price optimization model in combination with the peak-valley time period division result; and solving the time-of-use electricity price optimization model by using an RODDPSO algorithm to obtain an optimal time-of-use electricity price scheme. Based on this, the method can effectively stimulate the user-side adjustable load to participate in demand response, guides the time-space transfer of the load, and smooths the rural power grid net load curve while improving the new energy consumption.

The invention discloses a rural land planning and construction method fusing multi-source data, and the method comprises the steps: obtaining rural land planning data and a building distribution diagram, and obtaining a cultivated land region and a population gathering region; calculating the distance between the cultivated land area and the population gathering area, distributing a nearest cultivated land area for each population gathering area according to the distance, and outputting the nearest cultivated land area as a cultivated land area to be planned; obtaining remote sensing image data of a to-be-planned cultivated land area, extracting farmland and ridges based on the remote sensing image data, and constructing a shortest path from a population gathering area to each farmland through the ridges; physical parameters and micro-ecological parameters of the ridge are obtained, a labor-saving index of the shortest path is calculated based on the physical parameters, and a planting assistance index of the ridge on the farmland side is calculated based on the micro-ecological parameters; based on the labor-saving index and the planting assistance index, combining with the peasant household body function data of the population gathering area, dynamically distributing the farmland; adaptive farmlands can be recommended for planting according to different body functions of farmers, and reasonable resource allocation is realized.

The application relates to the technical field of remote sensing monitoring, and discloses a rural house building remote sensing dynamic monitoring method, a rural house building remote sensing dynamic monitoring system and computer equipment, wherein the method comprises the following steps: collecting homestead basic information investigation data, house and land integrated right confirmation registration and certificate issuing data, stock land occupation for house building graph spot data and national land space planning data to obtain rural house building basic data; performing change detection on remote sensing images of a target monitoring area to obtain new house building change detection results; comparing the new house building change detection results with approval information in the rural house building basic data to determine suspected illegal house building graph spots; issuing a mobile terminal application to patrol personnel for on-site verification to obtain illegal house building verification confirmation results; and performing visual display on the rural house building basic data, the suspected illegal house building graph spots and the illegal house building verification confirmation results in a preset cloud management platform, so that the accuracy of rural house building change detection is improved, and full-process digital management is realized.

We provide the system. [Solution] An online platform for matching businesses in rural areas with specialized engineers concentrated in urban areas, A means of receiving and storing registration information of businesses and technical experts in a database, A means including a generative AI model that receives input of consultation content from businesses and analyzes said consultation content, A matching means that automatically selects the most suitable expert based on the analysis results of the generated AI model, A means to support the selected expert technician in providing advice to the client, A means of collecting feedback from clients and using it to improve the system, A system that includes this.

According to the method, the complexity of a remote rural distribution environment is considered, the high dispersion characteristic of order space-time distribution is considered, the differentiation characteristic of multi-vehicle-type transport capacity resources is also considered, and the order combination distribution method based on space-time clustering in a rural common distribution mode is provided. In the first stage, customer geographic positions and order time window constraints are comprehensively considered, reachability-guaranteed clustering is formed to realize order combination, and an initial path feasible solution is constructed based on a space-time clustering result; in the second stage, a simulated annealing framework is designed to be fused into adaptive large neighborhood search, a clustering result is dynamically adjusted according to multi-vehicle-type differential time-space characteristics, and an initial solution is improved; on-demand combination of orders, accurate path planning and multi-vehicle collaborative distribution are realized, and logistics enterprises are helped to cope with distribution challenges of scattered orders, fuzzy time windows and complex road networks in remote rural areas with lower cost on the premise of ensuring distribution timeliness and service quality.

The application discloses a population migration dynamic attribution assessment method and system for air pollution health risk, and belongs to the technical field of environmental health risk assessment and spatio-temporal big data analysis. The method firstly fuses multi-source spatio-temporal data and carries out standardization preprocessing; secondly, based on night light and built-up area statistical data, a provincial adaptive threshold algorithm is used to dynamically identify three types of spatial units, i.e. urban core area, expansion area and rural area; then, a "no migration" counterfactual population distribution scenario is constructed based on the population pattern in the base year; finally, the health risk in the real and counterfactual scenarios is calculated in parallel, and the net health risk caused by population migration is quantified by difference. The application effectively solves the exposure misclassification and attribution capability loss problems caused by the use of static population and fixed boundaries in the traditional assessment method, improves the spatio-temporal accuracy of the assessment and the calculability of the attribution result, and provides a standardized analysis tool for environmental health risk management.

This invention relates to the field of rural economic data analysis technology, specifically an artificial intelligence-based method for rural economic data analysis. The method includes: delineating an economic data perception domain in a geographic information system based on the administrative division vector data of the target administrative village; collecting multi-source heterogeneous economic data through a protocol parser of an agricultural IoT terminal and converting it into standardized economic behavior data; extracting entities using natural language processing technology to generate a structured rural economic behavior fact table; inputting the fact table into a pre-trained economic activity association model and constructing a rural industry relationship graph using a graph embedding algorithm; and calculating the centrality index of economic entities based on the graph topology to identify core operating entities. This method enables accurate processing and association analysis of rural economic data, clearly presenting industry relationships and providing effective technical support for rural economic analysis.

The application discloses a rural housing structure safety multi-dimensional characterization index and an evaluation system construction method, and belongs to the technical field of the cross of building engineering safety appraisal, disaster prevention and mitigation and artificial intelligence. The method comprises the following steps: constructing a rural house structure safety quantitative characterization index system comprising macroscopic elements, microscopic elements and microscopic elements, collecting image data and geographical position information of a target rural house, performing collaborative analysis on the image data through an improved Mask R-CNN network and a panoramic segmentation network based on a recursive layer aggregation structure, extracting quantitative parameter values strictly corresponding to the index system, inputting the extracted quantitative parameter values into a rule engine with built-in judgment rules, automatically executing multi-level safety evaluation by the rule engine, and outputting a final safety level and an evaluation report. The application realizes efficient, objective and standardized rural house safety evaluation through an AI model and a rule engine, and significantly improves the evaluation efficiency and reliability.

The invention relates to the technical field of geographic space information, and discloses a rural cadastre dynamic updating and property management method and system based on remote sensing and a GIS (Geographic Information System). A multi-source data acquisition module, a data arrangement module, a dynamic updating module, a property management module, a data analysis module, a three-dimensional visualization module, a quality inspection scale module, a public participation module, a dispute mediation module, a resource sharing module and an operation and maintenance security module are deployed, and initialization configuration and linkage testing of each module are completed. The multi-source data acquisition module is used for integrating multi-source data, the dynamic updating module is used for detecting land type changes through a CNN model, the data analysis module is used for quantifying conflict risks and cultivated land / development trends, and all the modules cooperatively support application, so that the system has the advantages of real-time monitoring, intelligent early warning, accurate metering and dynamic optimization. The problems that in traditional rural cadastral management, land utilization change perception is lagged, ownership disputes are passively handled, cultivated land protection quantification is absent, and development intensity regulation and control are not accurate are solved.

The invention discloses a rural finance propaganda and display device, and relates to the field of propaganda and display, the rural finance propaganda and display device comprises a supporting plate and a first driving mechanism, one side of the supporting plate is provided with two symmetrically arranged first display mechanisms, each first display mechanism comprises a first display plate, one side of each first display plate is rotatably connected with an A supporting column, and the A supporting column is rotatably connected with a B supporting column; the bottom of the supporting column A is slidably connected with the supporting plate, the first driving mechanism is used for driving the supporting column A to move in the length direction of the supporting plate, and a supporting column B is fixedly installed on the other side of the first display plate; according to the rural financial propaganda and display device, the two first display boards can be adjusted at multiple angles so as to adapt to arrangement of the device in places such as forks in rural areas, people can watch the device conveniently, the two first display boards can be close to each other during moving and transporting, the occupied size of the device is reduced, moving and transporting are facilitated, and the device is convenient to use. The display area is effectively enlarged, and the practicability is higher.

The invention relates to the technical field of federated learning and financial risk control, and discloses a cross-institution rural financial modeling method based on federated learning, and the method comprises the steps: a central server broadcasts a synchronous beacon containing a feature attention list according to an agricultural event calendar; and after each participant terminal receives the synchronization beacon, executing local model training according to the synchronization beacon, and performing information entropy analysis on the obtained initial gradient to screen out a high-value gradient subset and only uploading the high-value gradient subset to the central server. And the information value is taken as a transmission basis, and continuous data interaction in a weak network environment is avoided, so that the effectiveness of the risk control model is ensured, and the operation reliability and deployment feasibility of the whole collaborative modeling system in an actual rural scene are improved.

The invention discloses a remote sensing residential area extraction method and system based on multi-source data fusion semantic segmentation, and particularly relates to the field of remote sensing image processing and land utilization mapping. A multi-source fusion automatic labeling strategy is adopted, and a rural residential area pixel-level training label is automatically generated by using an impervious surface product, an open source map interest point and a night light learning area-brightness threshold value; the method comprises the following steps: constructing an SELPFormer lightweight Transform segmentation model, introducing Lite-PPM, SCSE and ELA feature enhancement modules and a lightweight decoder on the basis of SegFormer, and outputting a rural residential spot pixel level extraction result for regional scale rural residential spot mapping.

The invention belongs to the field of territorial space improvement and resource optimization, and particularly discloses a decision-oriented rural abandoned residential area arrangement potential evaluation and grading method, which comprises the following steps: acquiring a multi-source sample and constructing a multi-dimensional feature factor set to generate a standardized data set; training set sample distribution is optimized by applying multiple sampling methods, training and hyper-parameter optimization are performed in combination with multiple machine learning technologies, and an optimal sampling method corresponding to each technology is screened out to obtain a model set; discarding state prediction is carried out based on the model set, a majority voting mechanism is adopted to integrate discrimination results, and variable importance analysis is carried out on each model to comprehensively identify core driving factors; key evaluation indexes are screened according to core driving factors, forward and normalization processing is carried out, weights are distributed according to variable importance results, potential indexes are sorted through weighted comprehensive evaluation calculation, and priority levels are divided according to the potential indexes. According to the invention, effective connection from discarding state identification to decision arrangement support can be effectively realized.

The invention discloses a hierarchical reinforcement learning regulation and control method and system for rural distributed resources, belongs to the technical field of power system engineering control, and aims to solve the problems of difficult control and insufficient economical efficiency and safety caused by strong randomness and weak communication of traditional rural distributed resource regulation and control. The method comprises the following steps: extracting aggregation regulation and control characteristics of distributed resources such as rural energy storage equipment and temperature control loads; constructing a mass heterogeneous resource equivalent model to realize dimension reduction; building a scheduling model containing power balance, equipment constraint and economic targets; layered reinforcement learning is adopted, an upper-layer agent controls polymer power, a lower-layer agent regulates and controls a single resource, and an actor-commentator algorithm is combined to optimize a strategy. The invention further discloses a regulation and control system which realizes the flow of the regulation and control method through a modular program. The method is suitable for rural scenes, can meet millisecond-level decisions, and has the advantages of improving the operation efficiency, reliability and economical efficiency of the rural distribution network.

This invention relates to the field of water demand prediction technology, specifically to an intelligent water demand prediction system and method for rural areas. By quantifying the crop growth process into continuous growth state parameters and constructing a dynamic crop coefficient model based on a sine function, it solves the problems of discontinuous water demand calculation and physiological distortion caused by traditional step-type models during growth stage transitions. It corrects root depth and combines measured soil moisture content with preset field capacity to dynamically constrain effective precipitation, overcoming the shortcomings of existing technologies that ignore basic soil moisture conditions and overestimate the contribution of natural precipitation. By constructing a priority score based on water depletion time and growth sensitivity, it achieves rational scheduling in scenarios with limited water resources across multiple plots, ensuring the continuity of crop physiological water demand and improving the precision of irrigation decisions and water resource utilization efficiency.

The invention relates to the technical field of road network construction, in particular to a rural area road network construction method and device based on a generative adversarial network and a medium, which can effectively capture different density trajectory characteristics and process sparse agricultural machinery trajectories and complex rural roads. The invention provides a road extraction model T2R-GAN based on the CGAN, the T2R-GAN adopts a conditional generative adversarial network (CGAN) architecture, a generator and a discriminator are continuously optimized through adversarial training, the model can effectively capture fuzzy road features in an agricultural machinery track by means of the adversarial training mode, an image highly similar to a real road is generated, and the road extraction efficiency is improved. The road is effectively extracted from sparse and complex agricultural machinery trajectory data, and the precision and applicability of road extraction in the rural area are remarkably improved.

The invention relates to the technical field of infrastructure and IT support, in particular to a rural area broadband site selection method, device and equipment, a medium and a product, and the method comprises the steps: obtaining house contour data and house codes of all houses in a target rural area, and obtaining obstacle contour data of obstacles; determining a covered house by identifying whether the house code is associated with the asset management house number identifier; converting the community model data, the fiber distribution box model data, the rubber-insulated wire rod model data, the obstacle contour data and the house contour data into layer data, and projecting the layer data into a projection coordinate system of a satellite map to obtain a rendered map; and based on the rendered map, acquiring site selection information of the target house applying for accessing the broadband. The target rural area is rendered through the high-definition satellite map, houses and obstacles can be accurately displayed, the rural area where the user is located can be searched according to the rendered map, the house of the user can be accurately positioned, and the problem that site selection of the rural user is difficult is solved.

The application discloses a linear drainage ditch for rural areas and a permeation testing method thereof, relates to the technical field of sewage collection, and solves the problems of high use cost and easy damage of the existing concrete drainage ditch for rural areas, reduces the material consumption, and reduces the construction difficulty, and the specific scheme is as follows: the drainage ditch main body is provided with a grid on the groove, the drainage ditch main body is made of a mixed material, the main agent of the mixed material is epoxy resin, the curing agent is modified amine T31 synthesized by phenol, formaldehyde and fatty amine, the diluent is acetone, the toughening agent is dibutyl phthalate, the filler is fly ash, and the aggregate is fine aggregate produced by using construction waste.

The invention discloses a rural ecological environment distributed monitoring and public participation method and system based on a mobile internet, and relates to the technical field of ecological environment monitoring. According to the invention, through a multi-source data fusion verification mechanism, spatial-temporal correlation analysis is carried out on monitoring data of different nodes, abnormal data is eliminated, and the accuracy and consistency of the data are ensured; local preprocessing and feature extraction are carried out by utilizing an edge computing unit to form a simplified core data set, and through lossless compression processing, a data transmission path is optimized, the transmission quantity is reduced, the transmission efficiency and the stability are improved, and a multi-party cooperation mechanism based on real-time pushing is constructed, so that the real-time pushing is realized. According to the method, priority ranking is carried out in combination with the geographic positions and severity of the abnormal events, a collaborative response task list is generated, the response speed is increased, the emergency response capability and treatment efficiency of the rural ecological environment monitoring system are improved, and powerful support is provided for rural ecological environment protection.

The invention discloses a rural housing structure safety multi-dimensional characterization index and evaluation system construction method, and belongs to the technical field of building engineering safety appraisal, disaster prevention and reduction and artificial intelligence crossing. Comprising the steps of constructing a rural house structure safety quantitative characterization index system containing three levels of macroscopic elements, mesoscopic elements and microscopic elements and corresponding judgment rules, collecting image data and geographic position information of a target rural house, carrying out collaborative analysis on the image data through an improved Mask R-CNN network and a panoramic segmentation network based on a recursive layer aggregation structure, and carrying out quantitative characterization on the rural house structure safety. And extracting a quantization parameter value strictly corresponding to the index system, inputting the extracted quantization parameter value into a rule engine with a built-in judgment rule, automatically executing multi-level safety evaluation by the rule engine, and outputting a final safety level and an evaluation report. Efficient, objective and standardized rural house safety assessment is realized through the AI model and the rule engine, and the assessment efficiency and reliability are remarkably improved.

The utility model belongs to the technical field of water treatment, and discloses a rural multi-water-source collection and comprehensive pretreatment wetland device in an arid region, a water treatment tank and a water storage regulating tank are arranged on the inner side of a concrete tank, and the water treatment tank is positioned on the upstream of the water storage regulating tank; a soil layer, a harmless solid waste mixture layer and a gravel layer are sequentially arranged in the water treatment pond from top to bottom, and salt-tolerant aquatic plants are planted on the upper side of the soil layer; the upper end of the water storage adjusting pool is communicated with an external force pump through a first water taking pipe, the lower end of the outer side of the water storage adjusting pool is communicated with a water level siphon pump, and the water outlet end of the water level siphon pump is communicated with an irrigation pipeline and a second water taking pipe. Collected multiple water sources are treated by the water treatment tank, water overflows into the water storage adjusting tank for water storage after being filled with water, the stored water can be pumped and used by the external force pump and the water level siphon pump which are communicated with the water storage adjusting tank, and the taken water can be used for farmland irrigation and landscape water after being subjected to further deep treatment.

The invention discloses a student subsidy intelligent management system and method based on artificial intelligence, and the system comprises a basic layer, a data processing layer, a knowledge base and an application layer. The intelligent management system integrates the structured and unstructured data of multiple departments such as education, civil administration, agriculture and rural areas, builds a unified data warehouse, and improves the management efficiency. And performing instruction fine tuning by using a large language model, and establishing a policy knowledge base and a case knowledge base. The management system adopts a random forest, LSTM, BERT and other machine learning algorithms, develops three core algorithms of poor student identification, subsidy demand prediction and risk early warning, and realizes accurate identification, dynamic monitoring and intelligent matching of subsidy objects. According to the invention, the method achieves the conversion from a mode of making a policy by people to a mode of making a person by a policy, supports a mode of exclusive use and sharing, remarkably improves the precision and efficiency of subsidy work, protects the privacy of students, and reduces the workload of a basic level.

The system according to this embodiment aims to provide people who wish to relocate to rural areas with a unified service that includes local information, vacant house renovation, and post-relocation support. [Solution] The system according to the embodiment comprises an information provision unit, a renovation support unit, a lifestyle support unit, and a marketing support unit. The information provision unit provides local information. The renovation support unit provides support for vacant house renovations based on the information provided by the information provision unit. The lifestyle support unit provides support for life after relocation based on the information supported by the renovation support unit. The marketing support unit provides marketing support based on the information provided by the lifestyle support unit.

The invention discloses a pavement performance prediction method for a rural simple pavement, and the method comprises the steps: data standardization: constructing an original matrix based on a disease evaluation value, and carrying out the standardization; carrying out formalized quantitative analysis, collecting disease, climate and traffic data, calculating weights and road surface damage condition indexes through a dynamic weight function, and carrying out multi-level summarization; constructing a rural highway use performance evaluation system, and performing PQI evaluation based on sampling data; feature selection, systematic analysis of disease types, and screening of main diseases through optimal subset regression, LASSO regression and random forest; index entropy and weight are calculated, disease entropy is quantified and standardized, and entropy weight is calculated based on information utility value. According to the method, the problems that in the prior art, rural simple paving materials lack systematic research, maintenance intervention influences are ignored, disease weight distribution is not scientific, and classification depends on artificial experience, so that model generalization is poor are solved, and the scientificity and accuracy of rural road maintenance are improved.