1901 results about "Information model" patented technology

The invention provides an intelligent building energy conservation and emission reduction digital twin management system and method, and relates to the field of building automation and energy conservation control. The intelligent building energy conservation and emission reduction digital twinborn management system comprises a digital twinborn model construction module, an energy consumption prediction and regulation module, a multi-device cooperative control module, a real-time feedback and self-learning module and an edge-cloud cooperative architecture. By integrating a building information model, real-time sensor data, meteorological data and the like, a three-dimensional visual dynamic twinborn model is constructed, historical data playback and thermodynamic diagram analysis are supported, omnibearing virtual mapping of a physical building is realized, a physical system and virtual model data are synchronized in real time through an Internet of Things sensor network, and the real-time real-time dynamic twinborn model is established. The consistency of a virtual model and an actual system is ensured, the precision and reliability of the model are remarkably improved, artificial illumination is dynamically compensated according to natural illumination, lamps are automatically turned off in an unmanned area through infrared induction, and equipment-level energy saving is achieved in combination with air conditioning system optimization.

The invention provides a BIM-based building energy consumption simulation analysis optimization method and system, and relates to the technical field of building energy consumption, and the method comprises the steps: building a building energy consumption digital twinborn model through integrating a building information model (BIM) and real-time operation data, such as indoor and outdoor temperature, equipment operation, electrical load and personnel density, collected by an Internet of Things sensor. An LSTM and GNN mixed deep learning algorithm is used to predict building energy consumption, and clustering analysis is used to identify an energy consumption abnormal mode and a peak period. And finally, based on a reinforcement learning algorithm, constructing an energy consumption optimization model taking total energy consumption minimization as a target and taking indoor thermal comfort and air quality as constraints, outputting equipment optimization operation parameters such as air conditioner temperature, fresh air volume, illumination brightness and the like, and realizing intelligent optimization control of building energy consumption, so that the building energy consumption is reduced, and the building operation efficiency is improved.

The invention provides a BIM-based fabricated building component management method and system, and the method comprises the steps: firstly obtaining a building information model data set of a target fabricated building project, a component attribute parameter set covering a prefabricated component unit, and a component geometric feature set, and then carrying out the multi-level component feature analysis of the building information model data set, obtaining a standardized geometric feature sequence and a dynamic construction state feature set containing a transportation positioning offset, a hoisting stress distribution gradient and an installation collision risk coefficient, and then performing cross-stage collaborative analysis on the features based on a preset construction stage matching strategy to generate a component matching strategy set; and the component dynamic optimization module is used for indicating component installation sequence adjustment and connection node precision compensation, finally generating a component dynamic optimization instruction set according to the component matching strategy set, and synchronizing the component dynamic optimization instruction set to the building information model data set to update component attributes, so that efficient management of the fabricated building components is realized.

The invention provides an information system engineering supervision project risk adaptive assessment method and system. According to the project management scheme, a dynamic knowledge graph is formed by constructing a data model fusing a building information model and a geographic information system. The three-dimensional coordinate track of the construction machinery is captured in real time by using an ultra wide band positioning device array, and the space occupied hot area distribution is generated by using a multipath interference suppression technology. An operation simulation environment is established based on a digital twinning technology, and a space-time risk topology network is established to early warn path conflicts and safety spacing problems. And according to network node density characteristics, dynamically adjusting a risk assessment parameter weight, and assessing an equipment collision probability and a construction process conflict index. Finally, the stress threshold value and the signal sampling frequency are adjusted according to the composite risk level result feedback, and construction management and safety guarantee are optimized. According to the technical scheme provided by the invention, the efficiency and safety of information system engineering supervision project risk adaptive assessment can be improved.

The invention relates to the technical field of building information models, augmented reality, synchronous localization and map construction, and provides a deep learning-based SLAM-BIM augmented reality cooperative localization method and system, and the method comprises the steps: introducing a Transform time sequence feature extractor and a geometric relation graph, evaluating a dynamic distribution weight through combining with the confidence, achieving the cross-modal closed-loop detection, and obtaining an SLAM-BIM augmented reality cooperative localization result. A lightweight semantic segmentation network and a feature fusion module are utilized, a dense map with consistent geometric semantics is constructed, a space-time error propagation equation is constructed, online calibration is realized by means of BIM scale prior, an incremental fusion algorithm is designed, a global pose is optimized in combination with AR interaction, and the system fuses SLAM visual trajectory features and BIM semantic geometric features through a deep learning technology. According to the method, the problems that traditional SLAM accumulative errors are large and the BIM fusion precision is low are solved, robust positioning and map construction in a complex scene are achieved, the cooperation precision and real-time performance of SLAM and BIM are improved, and the method is suitable for AR scenes such as building construction and operation and maintenance.

The invention relates to a building design scheme multi-objective optimization comparison and selection method and device, equipment and a medium. The method comprises the steps of generating a multi-dimensional design parameter set by obtaining building information model data and parameterized design data; performing multi-dimensional target analysis and evaluation by using a multi-field joint simulation platform to generate a multi-dimensional evaluation index; a dynamic multi-objective optimization model is constructed through a dynamic weight adaptive algorithm in combination with project stage demands and user interaction data; carrying out iterative optimization by adopting an improved non-dominated sorting genetic algorithm to obtain an optimized design scheme gene sequence result, and introducing a spatial topology connectivity constraint to generate a Pareto optimal solution set; and according to the Pareto optimal solution set, generating an optimization scheme through user weight adjustment and scheme screening. According to the method, the optimal design scheme set meeting the project requirements can be quickly and efficiently generated and screened out, the project stage requirements and user preferences are met, and the design efficiency and the scheme quality are improved.

The invention provides a BIM intelligent management platform oriented to a whole life cycle of project construction. A building information model, Internet of Things sensing data and a block chain evidence storage mechanism are integrated through a multi-source data fusion technology, and a whole-process data chain of association planning, design, construction, operation and maintenance is associated. The platform adopts space optimization Huffman coding to realize model lightweight, combines a constraint genetic algorithm to optimize a construction path, and applies a bidirectional long-short-term memory network to analyze an equipment state. A three-chain block chain system is reconstructed on the architecture, intelligent association of engineering quantity and payment nodes is realized through cooperation of a main chain, a calculation quantity side chain and an auditing side chain, and mobile terminal offline interaction is supported based on a digital-analog separation technology. The platform covers an intelligent design management unit, a block chain investment management unit, a dynamic correction management unit, a quality safety responsibility tracing unit, an NLP risk management unit and a digital twin operation and maintenance unit. The units achieve cross-system cooperation through a unified data bus, and a closed-loop management architecture covering the whole life cycle of project construction is formed.

Techniques for using a model to generate a response to a user input, where the response is associated with a personality determined to be relevant to the user input, are described. The system receives a user input and context data associated with the user input. Using the user input data and / or the context data, the system determines a personality (e.g., including a personality type and / or personality characteristics) relevant to the user input. The system generates a prompt instructing a model to generate a response to the user input that corresponds to the personality. The model processes the prompt to generate a response to the user input that corresponds to the personality. In some embodiments, the model generates a request for another component of the system to generate information responsive to the user input. The model may transform the responsive information into the personality-associated response.

The invention discloses an intelligent building energy-saving management method and system based on a digital twinning technology, and relates to the field of digital twinning technologies, and the method comprises the steps: building a three-dimensional building model based on a building information model and three-dimensional laser scanning point cloud data, and generating a twinning database through multi-source equipment data fusion; performing energy consumption simulation modeling according to the lamp dimming parameters, the air conditioner performance curve and the elevator operation log in the twin database to generate an energy consumption reference report; acquiring personnel density and environment parameters, and generating a building environment state matrix mapped with the twin database after space-time calibration; and establishing a hierarchical threshold value control strategy library based on the building energy consumption reference report and the building environment state matrix, and generating an optimization control strategy set through the equipment linkage relation matrix. According to the method, by embedding a Pareto optimal solution screening mechanism and equipment mutual exclusion rule verification, the daily average energy consumption is reduced on the premise that the comfort reaching rate of the optimal control parameter packet is ensured.

The invention relates to the technical field of engineering collaborative management, and discloses a BIM (Building Information Modeling)-based engineering full-life-cycle collaborative management method. The method comprises the following steps: acquiring building information model data and associated progress monitoring data of a full life cycle of a project, and providing a data basis for collaborative management. Based on a stage decomposition strategy, a single-stage dependency graph is constructed according to building information model data, and association logic of elements such as tasks and resources in each stage is clearly presented. Through a cross-stage dependency integration method, the single-stage dependency graph is integrated into a full-life-cycle dependency graph, and a cross-stage task connection and influence relationship is defined. In combination with data consistency verification and resource constraint review, conflict detection is performed according to a full life cycle dependency graph, and potential data conflicts and resource conflicts are identified in advance. And based on a progress fluctuation analysis mechanism, correcting the dynamic parameters according to a conflict detection result, and finally generating a full-life-cycle collaborative management report.

The invention provides a geographic information visualization intelligent analysis system based on unmanned aerial vehicle surveying and mapping, and belongs to the field of surveying and mapping, and the system comprises an unmanned aerial vehicle aerial survey module which carries out regional aerial survey based on a multi-source sensor carried by an unmanned aerial vehicle, obtains multi-modal geographic data, and carries out the preprocessing of the multi-modal geographic data; the data processing module is used for forming an initial geographic data set under a standard coordinate system; the three-dimensional modeling module is used for obtaining the fused geographic feature data, constructing a three-dimensional geographic information model, optimizing the three-dimensional geographic information model and embedding time dimension information to form a four-dimensional spatio-temporal data set; the analysis and decision module is used for generating an analysis report comprising a terrain evolution trend and disaster risk assessment; and the visual platform module is used for visualizing the analysis report through a preset visual interaction interface and adjusting the rendering precision of the optimized three-dimensional geographic information model in real time according to the change of the visual angle of the user. The system provides an efficient and intelligent solution for geographic surveying and mapping and disaster early warning.

The invention discloses a building carbon emission analysis method based on an STIRPAT algorithm and a building information model technology, and the method comprises the steps: collecting the whole life cycle information of a building through the BIM technology in a data collection and integration stage, covering the data of all links of design, construction and operation, widely collecting the external environment data of a project location, such as social economy, energy technology, etc. Multi-source data such as geographic space and weather are introduced and fused, and real-time monitoring is performed by means of an intelligent sensing technology. Secondly, an extended STIRPAT model is constructed, core independent variables such as population, economy and technology and control variables such as building scale are comprehensively considered, and the influence of factors is accurately quantified through dynamic parameter adjustment and scene simulation prediction; according to the method, carbon emission attributes are given to components and equipment based on a BIM model, full-life-cycle carbon emission is simulated and calculated, integrated optimization is carried out with solar photovoltaic, intelligent control, waste management and other technologies, finally, results are comprehensively analyzed, carbon emission distribution and trend are displayed by utilizing a BIM visualization function, and a building low-carbon decision is provided.

The invention provides a distribution network line routing inspection path planning method based on a gas-electric hybrid unmanned aerial vehicle, which combines geographic information system data and power equipment information to construct a three-dimensional geographic information model, and determines a routing inspection sequence through a scientific and reasonable region division and scoring mechanism. Meanwhile, detailed path evaluation is carried out on the key inspection points and reachable inspection sub-paths of each sub-region, an optimal inspection sub-path is selected by adopting a comprehensive scoring model, and finally an optimal inspection total path passing through all the key inspection points is generated, so that the overall inspection time is greatly shortened, and the inspection efficiency is improved. According to the method, position coordinates and residual energy consumption information of the unmanned aerial vehicle are monitored in real time, so that continuity and safety of inspection work are ensured.

The invention relates to the technical field of building information management, in particular to a BIM (Building Information Modeling)-based prefabricated part design quality management method, which comprises the following steps of S1, establishing a prefabricated part three-dimensional information model with multi-dimensional parameters by using BIM software; S2, collecting real-time production data by using a sensor in a prefabricated part production process; s3, comparing the production data with initial design parameters in the BIM model to identify deviations exceeding a set tolerance range; s4, feeding back the identified deviation information to a production link, and adjusting operation parameters of production equipment according to the deviation condition; s5, after production is completed, whether the indexes meet the requirements or not is determined; and S6, adjusting the design and process standard of subsequent production. According to the invention, through real-time data acquisition, deviation analysis and feedback, optimization suggestion generation and closed-loop management, continuous improvement of precision and quality of a prefabricated part production process is ensured, and effective combination of design and production is realized.

The invention discloses an object searching method and system based on combination of a door lock and geographical relationship feedback, and the method comprises the steps: generating a local position information table containing a device ID and a position weight according to the RSSI signal strength of a Bluetooth label broadcast frame periodically received by the door lock; obtaining adjacent door lock IDs based on a topological relation pre-stored in the building information model, and obtaining a position information topological table synchronized in the whole network; according to the position information topology table, the voting weight value of each door lock is calculated by adopting a grading voting algorithm of a main vote right, a secondary vote right and a weak vote right, and a door lock voting result table is generated through vote accumulation; and in response to a Bluetooth equipment ID query request input by a loser, screening door locks with weights higher than a preset threshold value according to the voting result table, sorting the door locks according to the total number of votes, forwarding object searching instructions to a predetermined number of door locks with the highest number of votes, and triggering voice and screen display guide prompts. According to the embodiment of the invention, high-efficiency and low-delay object searching feedback can be realized, and the positioning precision and reliability are improved.

The invention discloses a two-arm robot cooperative motion planning method and system for multi-machine cooperative co-fusion, and the method comprises the steps: constructing a machine-machine-environment co-fusion collision information estimation model: carrying out the discretization of the whole reachable space of a two-arm robot, and obtaining the environment information through a depth camera; a gap estimation neural network model is adopted to obtain interaction information of the double-arm robot and the environment, meanwhile, interaction information of left and right mechanical arms is obtained, and synchronous collision detection between the robots and between the robot and the environment is achieved; on the basis of the machine-machine-environment co-fusion collision information estimation model, performing two-arm robot collaborative path planning to obtain an estimated feasible path; and based on the geometric collision checker, carrying out double-arm robot motion path safety check and path repair, and ensuring absolute safety of a planned path. The problems that an existing two-arm robot motion planning method is low in efficiency, and multi-robot collaborative operation is difficult to effectively achieve are solved.

The invention belongs to the technical field of distributed resource control of a power distribution network, and particularly relates to a distributed resource cooperative control method based on layering and partitioning autonomy of the power distribution network. The method comprises the following steps: S100, proposing an active power grid layering and zoning control strategy oriented to feeder autonomy; s200, establishing a power distribution network area power regulation and control information model of hierarchical and distributed control; and S300, realizing distributed resource cooperative control based on layering and partitioning autonomy of the power distribution network. According to the distributed resource cooperative control method provided by the invention, the distributed photovoltaic, user load and distributed energy storage coordinated control in the transformer area is realized by combining a feeder-autonomous-oriented active power distribution network layered and partitioned control strategy and utilizing the edge computing capability of the transformer area intelligent fusion terminal, the distributed photovoltaic absorption capability is improved, and the distributed resource utilization rate is improved. Energy supply and demand imbalance caused by distributed photovoltaic randomness is stabilized, and the economic operation level of a power distribution area is improved.

The invention relates to the technical field of geotechnical engineering digitization, in particular to a BIM (Building Information Modeling)-based three-dimensional geotechnical engineering investigation information model construction method. The construction method comprises the following steps: acquiring multidimensional geotechnical engineering investigation data, acquiring geotechnical engineering investigation data from multiple sources in real time, including geological drilling position coordinates, soil sample attributes, underground water level dynamic values and geological structure maps, and executing data synchronization operation in the acquisition process to ensure timestamp consistency. According to the method, the technical bottleneck of static physical process in traditional modeling is fundamentally broken through the synergistic effect of a multi-physics field coupled rock and soil information generation mechanism and the dynamic response architecture of the BIM framework.

The invention provides a water conservancy construction progress intelligent management method and system. Wherein hydraulic engineering project plans are collected, dynamic changes in a life cycle are obtained through an integrated building information model technology, and a hydraulic engineering construction progress management framework is generated; extracting multi-source heterogeneous data, performing cross-modal information integration by applying a multi-modal fusion network algorithm, evaluating specific influence of external environment factors by adopting a causal forest technology, and generating a water conservancy construction progress and risk early warning report; establishing a kinetic equation by applying a graph neural differential equation algorithm, performing dynamic system simulation, and constructing a virtual water conservancy construction environment by adopting an enhanced digital twinborn simulation technology to capture construction efficiency and resource utilization conditions and generate a water conservancy construction resource allocation optimization report; and a lean six-sigma methodology is introduced to set a lean improvement plan, project feedback is collected, and a water conservancy construction progress intelligent management scheme is generated. According to the technical scheme provided by the invention, the intelligent level of water conservancy construction progress management is remarkably improved.

The invention discloses a communication pipeline laying system for an underground intelligent pipe gallery, and relates to the technical field of underground intelligent pipe gallery construction, and the system comprises the steps: collecting point cloud data and underground environment parameters through a laser radar and a sensor, and carrying out the synchronous processing; fusing the synchronously processed point cloud data and the underground environment parameters, and constructing a three-dimensional geographic information model; analyzing and planning the three-dimensional geographic model by using artificial intelligence, and optimizing a laying path to obtain an optimal laying path; according to the optimal laying path, automatic pipeline laying is conducted through automatic construction equipment; according to the method, the three-dimensional geographic model is analyzed and planned through artificial intelligence, the laying path is optimized, the optimal laying path is obtained, the risk area under the complex geological condition is effectively avoided, the construction cost is reduced, and the reliability of communication pipeline laying path planning is improved.

The invention provides a BIM (Building Information Modeling)-based rail transit construction geological exploration profile generation method, which belongs to the technical field of exploration measurement and comprises the step of comprehensively improving the accuracy of rail transit construction geological exploration through an advanced data acquisition and intelligent analysis method. In a construction site, multi-dimensional data of geological drilling, geological radar, geophysical prospecting testing and the like are acquired through various precise instruments, and a three-dimensional coordinate system is firstly established; and deep feature extraction is performed on complex data by using a deep learning algorithm, and key information such as geological stratification, rock and soil parameters and underground water level is accurately obtained. Intelligent fusion of multi-source data is realized by constructing a geological stratification model, a rock and soil parameter model and an underground water level model, and a comprehensive geological information model is generated. And importing the extracted geological profile data into a BIM platform, and carrying out strict precision verification and optimization by adopting a professional geological information collaborative equation set to finally form a highly accurate and reliable rail transit construction geological exploration profile.

In a technique for directing network traffic to distribute client service requests among a set of service clusters of a service network, capacity and performance information is regularly obtained for the service clusters and provided to a trained reinforcement-learning (RL) model that integrates learned request-distribution and reward information for the service network. The RL model is operated to regularly update recommendation values for directing the client service requests to the service clusters, and updated recommendation values are regularly provided to a traffic director which directs network traffic at least partly based on the regularly provided updated recommendation values. The traffic director may be realized by a Domain Name System (DNS) server, having an ability to select among candidate service clusters based on weight values reported by the RL model.

The invention discloses a building engineering progress automatic identification early warning system based on computer vision, which relates to the field of building engineering informatization and comprises a synchronous calibration module, a joint calibration module, a pose generation module, a mapping construction module, a resampling module, a mapping registration module and a comparison early warning module. Clock synchronization and rolling readout calibration are carried out on a camera and an inertial measurement unit, a continuous time pose is established in a frame, sampling is carried out according to rows, and an equivalent global shutter frame is generated in combination with plane and pixel-level geometric mapping; outputting a camera pose track and a local measurement map by adopting back-end optimization containing a rolling mechanism, and registering with the building information model; component detection, instance segmentation and state discrimination are completed on an equivalent global shutter frame, pixel domain measurement is unified into engineering quantity under pose and registration constraints, the engineering quantity is mapped to a work decomposition structure and a progress plan, deviation is calculated, and graded early warning is output according to a multi-threshold rule. Long-term stable and reliable operation and evidence traceability of the system are guaranteed through whole-course quality monitoring and threshold grading.

The invention relates to the technical field of decoration construction management, and discloses a BIM-based decoration construction scene resource consumption simulation analysis method. The method comprises the following steps: firstly, creating a multi-dimensional BIM resource model, and integrating building information model data, real-time construction data flow and historical resource consumption records; identifying resource consumption characteristics through the model, and generating an initial resource allocation strategy set comprising material allocation, equipment scheduling and process priority schemes; receiving a user interaction instruction, and dynamically adjusting the initial strategy set; and finally, executing the adjusted strategy, and updating the multi-dimensional BIM resource model based on a result. Wherein the resource consumption feature comprises construction stage division, resource node dynamic weight calculation and space correlation correction operation. According to the method, by integrating multi-dimensional data and dynamically analyzing a resource consumption rule, real-time optimization of a resource allocation strategy is realized, and the accuracy and flexibility of decoration construction resource management can be improved.

The invention relates to the technical field of scene rendering, in particular to a building information model scene rendering method and system based on parallel computing, and the method comprises the following steps: based on scene data stored in a building information model, analyzing space coordinates of geometric structure nodes of a building, and associating the geometric structure nodes with material attributes; and analyzing a data partition relationship according to the illumination distribution, and generating a geometric material illumination analysis result. According to the method, deep integration of geometry, materials and illumination is realized by analyzing spatial coordinates of geometric nodes and material attributes and combining illumination partition analysis, the data organization efficiency of a complex scene and the analysis precision of an illumination path are improved, light energy in a noise area is optimized by analyzing light propagation and energy distribution in a segmented manner, refraction and reflection paths are corrected, and the accuracy of the light path analysis is improved. And through texture boundary and scene geometry conjoint analysis, texture fracture is repaired, detail expression is enhanced, efficient analysis and optimization of complex building scene data are realized, and the high-precision rendering requirement is met.

The invention relates to the technical field of air conditioner energy-saving optimization, and discloses an air conditioner energy-saving optimization control system and method based on multi-parameter regulation and control, and the method comprises the following steps: obtaining environment data; the environment data comprises building information model data, indoor environment data, electricity price data and meteorological prediction data; based on the environment data, a three-dimensional game model used for air conditioner energy-saving optimization control is constructed; and solving the three-dimensional game model through a multi-target equalization algorithm, and generating and executing a control instruction of the air conditioning system. Multi-parameter regulation and control of the air conditioning system are achieved, energy can be remarkably saved, the comfort degree of the human body is guaranteed, and meanwhile the electricity utilization cost is reasonably controlled.

The invention provides a wind power mixed tower damage prediction method and system based on digital twinning. The method comprises the steps of obtaining multi-source data of a wind power mixed tower; wherein the multi-source data comprises structure response data, environment load data and historical operation and maintenance data; based on a building information model and finite element model fusion technology, constructing a digital twinborn model of the wind power mixing tower; inputting the multi-source data into a digital twinborn model to realize real-time mapping of the wind power mixed tower and the digital twinborn model, and obtaining real-time structure state data of the wind power mixed tower through the digital twinborn model; inputting the multi-source data and the real-time structure state data into a pre-trained LSTM-GRU hybrid neural network model, and predicting a damage evolution trend of the wind power hybrid tower in combination with an attention mechanism; and on the basis of the damage evolution trend, a maintenance scheme of the wind power mixed tower is generated by using a multi-target particle swarm algorithm, so that balanced optimization of maintenance cost, power generation loss and risk level is realized, and the operation and maintenance efficiency and safety of the wind power mixed tower are integrally improved.

The invention discloses a building robot multi-machine collaborative operation optimizing and monitoring method and system based on digital twinning, and belongs to the technical field of building construction intellectualization. The method comprises the following steps: constructing a digital twinborn body comprising an environment perception model and a kinematics / dynamics model based on a building information model and robot physical parameters; performing multi-machine task allocation and path planning containing static / dynamic obstacle avoidance in the virtual environment; synchronizing physical environment data in real time through a multi-mode sensor; dynamically optimizing operation parameters by adopting a genetic algorithm or a particle swarm algorithm and realizing closed-loop control; and generating a safety early warning and emergency scheme based on machine learning. According to the method, Markov decision path planning of reinforcement learning and multi-agent game task allocation are creatively fused, laser radar-vision-inertial navigation multi-source data fusion is adopted, the technical problems that in a traditional method, digital twinning precision is insufficient, and dynamic cooperation efficiency is low are solved, and the method is suitable for large-scale popularization and application. And the construction efficiency, the safety and the man-machine interaction experience are remarkably improved.

The invention discloses a smart city planning design method, and relates to the field of city planning, and the method comprises the steps: collecting monitoring data; determining two targets of land utilization rate maximization and traffic jam minimization according to the preprocessed monitoring data; an epsilon-constraint method is adopted to convert two targets of land utilization rate maximization and traffic jam minimization into a single-target optimization problem; solving a single-target optimization problem by adopting a swarm intelligence algorithm MOEAD to obtain a Pareto non-inferior solution set; performing clustering analysis on the Pareto non-inferior solution set by adopting a K-means clustering algorithm, and dividing the Pareto non-inferior solution set into K clusters according to a clustering result; and according to the preprocessed monitoring data, constructing a three-dimensional city information model by using a smart city CIM technology, mapping each solution in the representative solution set to a corresponding planning parameter in the three-dimensional city information model, and generating a corresponding city planning design scheme. The contradiction between the land utilization rate and the traffic efficiency in urban planning is balanced.

The invention provides an instrument panel type building engineering construction progress display method, system and device and a medium, and relates to the field of building construction management.The method comprises the steps that geographic information system map data and building information model data of an area where a building project is located are obtained and fused, and then a multi-dimensional display platform of the building engineering progress is constructed and formed; actual progress data, historical construction data and environment data of a construction site are collected, risk factors of construction tasks are analyzed, the dependency relationship between the construction tasks is analyzed through topological sorting, and a construction risk task tree is constructed; a construction risk task tree is adopted to identify potential risks of a construction task, weighted calculation is carried out on risk factors according to weight coefficients, a comprehensive risk assessment score of the construction task is generated, a construction progress sequence is optimized, and integration is carried out through an instrument panel to form a unified visual display interface. Dynamic prediction, real-time display and automatic adjustment can be realized, and the accuracy of construction progress monitoring is improved.