35 results about "City area" patented technology

The invention discloses an autonomous decision-making system of a multi-level intelligent agent in an urban area and an operation method thereof. Each end-side decision-making unit broadcasts an equipment state variable to a side-side decision-making unit; the side decision-making unit determines a global reference state and generates a control instruction of each end decision-making unit; after the equipment executes the control instruction, each end-side decision-making unit updates an equipment state variable according to the real-time operation data of the equipment, and when an abnormal event is judged to occur, a side decision-making unit predicts a decision-making variable of each piece of equipment based on a collaborative optimization model of an equipment target and an urban area target; the cloud regulation and control platform predicts a global consistency variable based on the collaborative optimization model of all the side decision units; predicting a regulation and control instruction of each side decision-making unit according to a global dynamic optimization target under a system operation constraint; and the side decision-making unit decomposes the regulation and control instruction into the control instruction of each end decision-making unit, so that the problems that the global cooperative capability of the urban regional integrated energy system is weak and cooperative scheduling is not timely under extreme events are solved.

The invention discloses a path planning method based on a city engine and an unreal engine. The method comprises the following steps: completing basic data preparation, rule definition, model generation and visual presentation and analysis, and establishing a city model; secondly, constructing a vehicle motion model in an unreal engine, and simulating weather; the three-dimensional static model and a dynamic model in an unreal engine are fused to generate an urban environment; carrying out geographical gridding on the urban area; introducing a trafficability map and physical restrictions of the vehicle, and setting the trafficability map of the vehicle; an improved A * algorithm based on geographic gridding is introduced, path planning is conducted, the improved A * algorithm is used, and path optimization is achieved through a heuristic function and a penalty function; and outputting the generated path plan.

The application discloses a kind of city area photovoltaic cluster dynamic grid division methods based on space-time coupling tensor, comprising: synchronously collecting the active power time series and geographic coordinates of all photovoltaic nodes in city area;Build the heterogeneous space adjacency matrix considering electrical topology constraint, calculate the static space correlation degree between any two photovoltaic nodes;Build the time-shift cross-correlation matrix that captures the moving characteristics of weather system, quantify the dynamic time correlation degree between nodes;Perform space-time feature tensor fusion, obtain global space-time affinity matrix;Photovoltaic nodes are divided using improved spectral clustering algorithm, and the optimal grid number is adaptively determined by contour coefficient, finally generate photovoltaic cluster grid division scheme at this moment;According to grid drift threshold, trigger grid reconstruction.The application can effectively consider physical topology constraint and meteorological time delay characteristics, realize the accurate aggregation of photovoltaic cluster, significantly improve the accommodation capacity and regulation flexibility of distribution network to distributed energy.

The invention relates to the technical field of data processing, and discloses a ditch ecological restoration benefit evaluation method and system. The method comprises the following steps: inputting a ditch pollution source tracking data set into a ditch pollution transmission simulation algorithm, and calculating a ditch purification capability coefficient through ditch hydraulic retention time and a pollutant degradation rate to obtain a ditch self-purification efficiency matrix; a ditch bearing capacity comparison model before and after restoration is established according to the ditch self-purification efficiency matrix, the restoration gain proportion is calculated and determined through the ditch containing threshold value difference, and a ditch capacity improvement vector is obtained; and carrying out space coupling operation on the channel capacity improvement vector and a village-in-city building density distribution factor to generate a regional channel restoration contribution index, and obtaining a channel restoration efficiency quantification result. According to the method, the problem that environmental feature pertinence and quantitative analysis means are lacked in village-in-city ditch restoration benefit evaluation is solved, and the accuracy of restoration benefit evaluation is improved.

The invention discloses an adaptive adjustment method and system for urban lighting under digital twinning, and relates to the technical field of urban intelligent lighting, and the method comprises the steps: carrying out the twinning reconstruction of a lighting equipment network in an urban region, and determining a lighting twinning body; through urban distributed sensing, state initialization is carried out on a lighting twinborn body, lamp control constraint elements are introduced, each lighting device is used as a light environment intelligent agent, local game decision is executed, a lighting strategy is determined, and the lamp control constraint elements at least comprise comfort income, energy-saving income and glare punishment; and performing multi-thread instruction generation according to the lighting strategy, and performing lighting management and control on the lighting equipment network. According to the invention, the technical problems that the traditional urban illumination regulation and control are difficult to accurately match the actual demand and cannot balance the multi-aspect targets are solved, and the technical effects of adaptively adjusting the urban illumination, balancing the multi-aspect targets and improving the accuracy and effectiveness of illumination management and control are achieved.

The application discloses a three-dimensional map aided GNSS positioning method based on density clustering improvement, comprising the following steps: constructing a three-dimensional building model, generating a sky mask, pre-generating a sky mask database, judging satellite visibility, scoring the satellite visibility based on a shadow matching algorithm, optimizing candidate point screening rules, introducing an OPTICS clustering algorithm to sort, clean and select candidate points, and screening high-score points; taking the score of the high-score points as a weight, optimizing the calculation formula into a weighted average formula considering cluster weight, and calculating a final position. The positioning method can solve the problem of multiple adjacent peak candidate points in three-dimensional building model aided GNSS pseudorange single point positioning under similar geometric observation conditions in the vicinity of a city area in a complex urban environment, the OPTICS clustering algorithm is adopted to sort data points according to density, small clusters are removed, and effective cleaning and selection of candidate points are realized, so that the positioning precision is effectively improved.

The application discloses a city area train operation scheme optimization method for co-line operation with national railway trains, comprising the following steps: S1: determining a car bottom operation scheme based on known car bottom quantity, vehicle maintenance conditions and large-small loop operation quantity; S2: setting a train stop scheme based on the section and station co-line of the national railway and the city area train and the limited demand of the city area train operation number; S3: determining a national railway train and city area train flow distribution scheme of the co-line station in unit time; S4: determining a city area train timetable based on the train stop scheme, large-small loop scheme and car bottom operation scheme of the city area train; and S5: considering the difference between daily lines and weekend lines, drawing a track use scheme and fine-tuning the train timetable based on the city area train timetable. According to the application, different transport demands can be integrated, the overall network efficiency in the hub can be improved, and on the basis of guaranteeing the national railway train transport capacity, the comprehensive benefits of the city area train can be maximized.

The invention discloses an urban area traffic road network subarea outer boundary drawing method, which comprises the following steps of: based on intersection position information and road section information which are preset on a map, slicing and refining the whole road network according to a topological relation by utilizing a slicing principle, and taking two adjacent intersections with the topological relation as minimum topological units; taking a boundary external expansion range as a limiting condition for drawing a region boundary, and obtaining a region external boundary of a minimum topological unit by using an envelope principle and a Convex Hull convex hull algorithm; and performing de-duplication and union on the plurality of minimum topological units according to the road network topological relation, and finally forming a crawler-type boundary set of the traffic road network of the whole urban area. According to the method, the situation that different region boundaries are overlapped due to the fact that the region boundaries are caught in concave packet traps during region boundary drawing can be avoided, and high adaptability and flexibility are achieved; and meanwhile, different scene requirements are met by setting different boundary limit thresholds.

The invention discloses a city-level parking resource optimization method and system, and relates to the technical field of intelligent transportation. The method comprises the following steps: acquiring real-time operation data and a geographic position of a parking lot in a target city area; constructing an urban parking topological graph which takes each parking lot as a node and takes a connecting road as a side; obtaining the real-time weight of each edge based on the real-time traffic data; calculating a real-time parking pressure value; nodes with the real-time parking pressure values larger than or equal to a first preset pressure value are high-pressure nodes, and nodes with the real-time parking pressure values smaller than the first preset pressure value are judged as potential nodes; performing pressure conduction simulation to obtain a simulated parking pressure value; the potential nodes and the high-pressure nodes with the simulated parking pressure values larger than the second preset pressure value and smaller than the first preset pressure value are determined as potential congestion clusters; and for each potential congestion cluster, calculating a price adjustment coefficient based on the simulated parking pressure value, obtaining a real-time parking rate, and generating a drainage instruction. According to the invention, the configuration accuracy of city-level parking resources can be improved.

The invention provides a cross-department false information processing method based on urban social governance, and belongs to the technical field of false information processing, and the method comprises the steps: obtaining to-be-recognized first information; the first information is information obtained by standardizing the multi-source data; extracting risk features of the first information based on a predetermined standard feature library; the risk features comprise content features, main body features, propagation features, time features and regional features; inputting the risk feature into a pre-trained long-short-term memory network to obtain a risk level of the first information; and in response to the fact that the risk level is greater than a predetermined risk level, generating a cross-department disposal work order, and sending the cross-department disposal work order to a corresponding government affair department based on the department responsibility graph to realize cross-department false information processing. According to the invention, the processing efficiency of cross-department false information can be improved.

The application provides a city identification design performance evaluation method, relates to the technical field of performance evaluation, and introduces a solid angle quantitative index to describe the performance of identification design, so as to make up for the problem that quantitative indexes are lacked in the evaluation of the emergency response capability of a city area, has important theoretical value and practical significance for improving the safety resilience of a smart city, and the application also considers various city elements and the behavior capability of people when calculating, so that dynamic perception, group statistics and complex scene correction are realized. The application not only provides quantitative indexes for the evaluation of the emergency response capability of a city, but also can be used for guiding the design of an identification system by a chief engineer.

The invention discloses a wireless information transmission system and a wireless information transmission method in a mixed communication mode. The system comprises a national railway CTC; city area CTC; the urban rail train is provided with an LTE wireless communication module, and the national railway train is provided with a GSM-R wireless communication module; based on the line where the national railway train is located, the national railway train is selectively in wireless communication connection with the city CTC or the national railway CTC through the GSM-R wireless communication module of the national railway train. The city GSM-R system is used for realizing data transmission between the GSM-R wireless communication module and the city CTC; the LTE system is used for realizing data transmission between the LTE wireless communication module and the city CTC; and the city area communication front-end processor is configured with a GSM-R communication thread and an LTE communication thread which are respectively used for realizing data transmission between the city area CTC and the city area GSM-R system and between the city area CTC and the LTE system. The method has the advantage that the requirement for mixed running of trains of different communication systems on urban rail transit lines can be met.

The application discloses a kind of quick cross path scheduling methods of inter-city area customized public transport system, the shortest distance method between regions is used to build start point area end point set and end point area start point set, to generate start point area travel sequence Yo by insertion method, to generate end point area travel sequence Yd by insertion method, then the Yo and Yd are optimized by quick exchange method, finally the minimum value of start point × Yo × Yd is solved, which is the final inter-city area customized public transport system target path, with the shortest bus travel distance as the target;The method does not use probability distribution, effectively avoids the fluctuation of the final path result, according to the characteristics that the distance between nodes in different regions is much larger than the distance between nodes in the same region, the inter-regional traffic node set is established, and it is used as the end point of the start point region and the start point of the end point region, respectively, to maximize the range of optimal solution, effectively reducing the overall calculation scale.

The invention discloses an urban area change detection method fusing multi-modal data and a knowledge graph, and relates to the technical field of area change detection, and the method comprises the steps: obtaining multi-source geographic data, such as a remote sensing image, a streetscape image, an interest point and the like, and carrying out the preprocessing; inputting data such as streetscape image texts obtained through preprocessing into a knowledge graph ontology structure, and constructing a multi-mode dual-temporal city knowledge graph; constructing a multi-modal knowledge representation framework by using a bidirectional cross attention mechanism to obtain knowledge graph vector features; and constructing a regularized cosine similarity index by using the vector features of the knowledge graph, and analyzing a city region change detection result. According to the method, the multi-mode double-time-phase city knowledge graph is constructed, and the change condition of the city region is accurately sensed; a multi-modal knowledge representation learning framework based on a bidirectional cross attention mechanism is designed, and deep fusion of features between image information and text information is promoted.

The invention discloses an urban inland inundation prediction method based on multi-source sensor fusion, and the method comprises the steps: collecting multi-source original time sequence observation data in a target urban region, and carrying out the preprocessing of the observation data, and obtaining a preprocessing time sequence data set; calculating the reliability weight of each sensor in combination with historical observation data, and performing weighted correction on the observation value of each sensor based on the reliability weight; splicing the corrected observation values of the sensors according to a unified time axis vector, constructing a multi-source joint observation vector, and inputting the multi-source joint observation vector into a pre-training neural network time sequence prediction model; in the model training process, an innovative loss function is adopted, the sensor reliability weight is introduced into loss calculation, and weighted optimization of key sensor data is achieved. According to the method, multi-source sensor information can be fully utilized, the influence of abnormal data of a single sensor is weakened, high-precision and real-time prediction and early warning of urban inland inundation are realized, and scientificity and reliability of urban disaster prevention decision making are improved.

The invention belongs to the technical field of intelligent traffic systems, urban calculation and geographic information systems, and provides an electric vehicle charging pile utilization rate prediction method and device, equipment and a medium, and the method comprises the steps: carrying out the preprocessing of original data of a target urban region; according to the obtained static features and dynamic features, determining a geographic adjacency map and a travel tide flow diagram, then performing feature weighted fusion by adopting a time feature embedding mode, and according to obtained node fusion features, performing double-layer map attention aggregation on the geographic adjacency map and the travel tide flow diagram to obtain spatial feature embedding; learning the evolution of the charging load of the grid along with time by adopting a gating circulation unit; according to the method, the prediction error of the effective grid is adopted as a loss function, the data set is adopted for training, the grid charging load prediction model is obtained, follow-up prediction is carried out, and the environment adaptability and prediction precision of the model in different time periods can be effectively improved.

The invention discloses an urban digital twinning online channel modeling method, and relates to the technical field of cross fusion application of a digital twinning technology and wireless channel modeling. Comprising the following steps: 1) acquiring geographic information system data of a target city area, establishing a city three-dimensional static model through Unity software, and performing equal-proportion reconstruction and reflector parameter addition, so that electromagnetic characteristics of the model are matched with a real physical world; 2) acquiring satellite remote sensing images, constructing a data set of various urban scenes, and training the data set by adopting Swin Transform to realize identification and segmentation of urban communication scenes; 3) based on a scene identification and segmentation result, completing electromagnetic parameter matching of a communication scene in combination with a 6G universal channel model, and performing static electromagnetic reconstruction by using a ray tracing technology of Wireless Insite software; and 4) integrating the scene segmentation module, the channel characteristic prediction module and the three-dimensional city model to a Unity Platform.According to the method, the channel characteristic change in a complex city scene can be accurately captured.

The invention relates to the technical field of urban greening management, and discloses an urban three-dimensional greening partition optimization method and system based on multi-target guidance, and the method comprises the following steps: S1, obtaining multi-source data of a target urban region, and generating an urban spatial database; s2, constructing a three-dimensional greening potential evaluation index system, and forming a three-dimensional greening potential initial evaluation graph; s3, constructing a four-dimensional target vector, carrying out multi-target optimization, and solving a multi-target weighted demand index; s4, a constraint clustering algorithm is adopted, and greening optimization partitions are automatically generated; and S5, establishing a three-dimensional greening strategy knowledge graph, calculating the strategy-partition adaptation degree of each greening optimization partition, and selecting an optimal strategy combination as a recommendation scheme through Monte Carlo simulation. According to the method, multi-source data can be deeply fused, spatial heterogeneity can be scientifically identified, differential strategy configuration is realized, and the precision, individuation and high efficiency of greening work can be promoted.

The invention discloses an urban inland inundation decision-making method based on agent simulation and evolution deduction, and the method comprises the steps: constructing an urban inland inundation digital base model, dividing an urban region into a plurality of space grid units, and setting a static attribute and a dynamic state variable for each unit; establishing a drainage facility agent model; constructing an intelligent agent decision-making model, generating a drainage control action by taking the dynamic state of the space grid unit as input, and acting on the drainage facility agent model to adjust the operation state; a training data set is generated based on historical rainfall and ponding data, and the intelligent agent is trained by comprehensively considering the ponding depth, the threshold exceeding condition and the drainage facility operation cost through a reward function; the drainage facility is intelligently regulated and controlled by simulating the evolution process of urban inland inundation. According to the method, urban waterlogging evolution can be dynamically simulated, a drainage facility control strategy is optimized, economic losses of different land utilization types are considered, and urban global waterlogging intelligent prevention and control and decision optimization are achieved.

The invention discloses an urban power system decarburization path evaluation method and system considering renewable resource constraints. The method comprises the following steps: carrying out full-quantity simulation on annual hour-level power demands of large-scale single buildings in a target urban area; aggregating by using a multi-dimensional space clustering algorithm to obtain a plurality of planning nodes; verifying the roof photovoltaic development potential upper limit, the distributed wind power site selection feasibility constraint and the physical limitation of the power grid interface transmission capacity of each planning node; a coupling optimization model is constructed and solved, an optimal technology investment portfolio and operation scheme is obtained, and a system cost-emission frontier curve, capacity configuration evolution paths of all technology types and an energy balance atlas of all nodes are obtained. According to the method, a physically-driven refined load simulation and multi-node capacity planning coupling framework is constructed to explicitly quantify the nonlinear influence of urban microscopic space resource constraints on the decarburization cost and the technical path and accurately reveal a key technical turning point and marginal cost sudden increase mechanism under a deep decarburization scene.

The embodiment of the invention discloses an urban area radar rainfall correction method and product fusing raindrop dynamic process simulation and machine learning, and relates to the technical field of meteorological radar data processing.In the scheme provided by the invention, on one hand, three-dimensional atmospheric field data and dual-polarization radar data are utilized for an urban complex underlying surface and an atmospheric environment; radar-rain gauge rainfall deviation caused by raindrop drifting is corrected by simulating the drifting process of raindrops in the atmosphere and combining a high-resolution three-dimensional atmosphere field and raindrop size distribution (DSD) data; and on the other hand, a machine learning random forest (RF) method is introduced, radar observation data, a rain gauge measurement value and related atmospheric influence factors are used as input, a nonlinear mapping model is constructed to excavate a complex function relationship between the radar observation data and the rain gauge measurement value, and the deviation of the radar-rain gauge pair in the urban environment is directly calculated and reduced. And finally, the results of the physical correction method and the random forest method are subjected to weighted fusion, so that the rainfall difference between the radar and the rain gauge is effectively reduced.

The invention relates to the field of rail transit transportation, in particular to a dynamic evaluation method for the adaptability of urban fast rail cross-line transportation organizations. Comprising the following steps: S1, constructing a city area fast rail transportation organization benefit evaluation index system from four categories of passenger benefits, transportation capability, enterprise benefits and social benefits; the first type comprises per capita travel time, per capita transfer frequency and riding convenience; the second class comprises a trafficability utilization rate and trafficability loss; the third type comprises the maximum section load factor of the train in the peak period, the use cost of the train bottom and the newly-added passenger flow volume; the fourth class comprises land value, district connection degree, travel business development and travel mode structure development; and S2, constructing a D-S evidence fusion model, thereby integrating qualitative, quantitative, subjective and objective information, outputting a multi-level credibility result, performing scheme screening and sorting, and selecting a proper operation mode according to the scheme.

The invention relates to a city charging prediction method and device based on a multi-semantic topological graph and a medium, and the method comprises the steps: dividing a target city region into a plurality of space nodes, obtaining the space information and semantic information of each space node, and constructing a geographic adjacency matrix and a plurality of single semantic similarity matrixes; constructing a long-range connection candidate set based on the single semantic similarity matrix; obtaining a scene demand, and performing sparsification on the long-range connection candidate set based on the scene demand to obtain a long-range shortcut matrix; constructing a multi-semantic topological graph of the target area based on the geographic adjacency matrix and the long-range shortcut matrix; historical city charging data is acquired, and the future city charging demand is predicted by using the space-time diagram neural network based on the multi-semantic topological graph and the historical city charging data. Compared with the prior art, the method has the advantages that a traditional topological graph is optimized by fusing multiple spatial semantics such as geographical adjacency, functional similarity, travel modes and behavior modes, and therefore more accurate charging prediction is achieved.

The invention discloses an A-BiLSTM-based method for predicting vibration of buildings along a city fast rail. The method comprises the following steps: firstly, collecting building vibration related data of a city area fast rail line section; secondly, establishing a vehicle rail-soil body-building finite element model based on actually measured data, designing test working conditions after main characteristic variables are selected, obtaining ground vibration acceleration time-history data right above a rail and building indoor vibration acceleration time-history data under each working condition, and constructing a data set; constructing a vibration prediction model by using a bidirectional long-short-term memory network, an attention mechanism and a full-connection network, performing model training by using divided training set data, optimizing the model by using a grid search method, and finally determining an A-BiLSTM vibration prediction model; and urban area fast rail vibration data are used as input, and building indoor vibration acceleration is output, so that data support is provided for building vibration evaluation along the urban area fast rail. According to the invention, vibration control and operation management along the urban fast rail can be effectively assisted.

The embodiment of the invention provides an urban ecological space layout optimization method and device, and the method comprises the steps: obtaining a multi-source spatial data set of a target urban region, evaluating different types of ecological functions in parallel, and generating a group of distribution diagrams representing different ecological functions; based on the generated group of distribution diagrams and basic geographic data, carrying out ecological space structure diagnosis, identifying an ecological source land, an ecological resistance surface, an ecological corridor and an ecological vulnerable node, and generating an ecological space diagnosis diagram set; the ecological fragile nodes comprise ecological pinch points and obstacle points; generating an ecological network strengthening graph based on the ecological space diagnosis graph set and urban space planning data; and generating a blue-green space optimization graph based on the generated group of distribution graphs and the ecological network enhancement graph, thereby realizing benefit optimization of comprehensive ecology and urban ecological space layout in a limited urban space.

The application discloses a kind of building height extraction methods based on spaceborne laser radar and high-resolution remote sensing image, comprising the following steps: obtaining the spaceborne laser radar ATLAS / ICESat-2L2A global positioning photon product data of city area;The data obtained is preprocessed, and high-quality spaceborne laser radar photon in region is obtained, and further higher quality ICESat-2 photon data is extracted;Obtain high-resolution remote sensing image data of city area, and the high-resolution remote sensing image is cropped and data is marked;Building roof extraction deep learning model and building side elevation extraction deep learning model are constructed and trained;Model predicts building roof extraction result and building side elevation extraction result;Based on building side elevation, building roof is corrected, and building base extraction result is obtained;Building base extraction result is vectorized and intersected with ICESat-2 photon, and based on spatial analysis method, building point is identified, and building height precision evaluation is carried out.The application can extract building height, and provide scientific basis for city planning and ecological environment research.

The invention discloses an urban unmanned logistics transportation method and system by means of an urban public transportation network. The method comprises the following steps: creating an urban unmanned logistics transportation mode by means of the urban public transportation network; according to the urban unmanned logistics transportation mode, constructing an urban unmanned logistics transportation feature data set by means of an urban public transit network; according to the collected urban unmanned logistics transportation feature data set, determining a transportation scheme of cargo cross-regional unmanned consignment by means of an urban public transit network; according to the collected urban area unmanned logistics transportation feature data set, distribution stations distributed to all bus downlink stop stations are determined, the number of buses needed for goods distribution in all distribution sections is calculated, and a transportation scheme of goods cross-area unmanned distribution by means of an urban public transportation network is determined. According to the method, efficient transportation of urban logistics is realized by means of the urban public transportation network, so that the public transportation use efficiency is improved, and the logistics transportation cost is reduced.

The invention provides a city area line and subway line interconnection and intercommunication ticket dynamic threshold value clearing system, which comprises an input data module for creating a transmission file path class and storing feature data of each path in an object form; the judgment and optimization module is provided with a threshold range and a corresponding candidate path rule, screens candidate paths meeting conditions, and calculates the matching probability of the actual travel time and the reference time consumption of each candidate path when a plurality of candidate paths exist in a screening result; and the sorting scheme output module is used for generating and outputting a final path sorting scheme according to the judgment result. The invention also provides a city area line and subway line interconnection ticket dynamic threshold value clearing method, which comprises the following steps: creating a transmission file path class, and setting a threshold value range and a corresponding candidate path rule; and determining the actual travel path of the passenger based on the actual travel time of the passenger in combination with the threshold range and the corresponding candidate path rule, and generating and outputting a final path clearing scheme.

The invention provides a city steward service method and system based on the Internet of Things, and relates to the technical field of city steward. Comprising the following steps: dividing a management unit according to urban area features, defining a facility sensing template based on functions of the management unit, and classifying sensing equipment according to monitoring types to obtain equipment sensing data; based on a federated learning algorithm, fusing the multi-source sensing data to construct a city state evaluation model, inputting equipment sensing data and historical operation and maintenance records, and generating a city operation state evaluation result; according to a city operation state evaluation result, the city management demand is disassembled into a plurality of service tasks, and equipment perception data is associated to construct a service response matrix; and calculating a priority coefficient of each service task in the service response matrix, and dynamically scheduling resources to generate an optimal service scheme. According to the method, the city state evaluation model is constructed by fusing multi-source sensing data through the federated learning algorithm, the dynamic change of the city is continuously adapted, and the city management is promoted to be more intelligent.

According to the slurry circulating device for cast-in-situ bored pile construction, a large-size hollow box girder of a decommissioned bridge is converted into a prefabricated settling pond or a prefabricated slurry circulating pond, and due to the fact that the hollow box girder is directly used for replacing a newly-built pond body, new excavation and investment of a large number of new materials are avoided, and the engineering cost and carbon emission are remarkably reduced; crack control and strength verification are carried out on old components, so that the safety and reliability of the recycling process of the hollow box girder are ensured; by means of the large-volume characteristic of the box girder, the basic requirement of cast-in-situ bored pile construction for the slurry storage capacity is met. Therefore, the device effectively solves the technical problem that a traditional mud pit cannot be excavated and arranged in an urban area, meanwhile, a structured and high-added-value recycling way is provided for a large number of abandoned bridge components, and economic benefits and ecological benefits are achieved.