59 results about "Urban design" patented technology

The invention belongs to the crossing field of computer vision and city design, and provides a multi-mode cooperative driving DiT city layout generation method, so as to solve the defects of an existing generation model in the aspects of spatial rationality and planning controllability. According to the method, a transformer-based diffusion generation model is innovatively constructed, and two additional control signals are integrated in a DiT model to realize controlled generation. On the aspect of model architecture design, a DiT framework with multi-modal condition fusion is constructed, and a road network sketch (image control) and planning semantics (text control) dual guide mechanism is integrated. In the text mode, a dynamic semantic fusion module based on a pre-training language model is designed, and text information is deeply embedded into the generation process. In the aspect of image control, a mixed attention regulation and control mechanism is put forward, multi-scale fusion of road network structural features is realized in combination with cross attention and AdaLN technologies, and the problem of spatial layout distortion is solved. Experiments show that the method can effectively integrate text and image information, and the generated city layout image is superior to that generated by an existing method.

The invention belongs to the crossing field of urban design and multidisciplinary, and particularly relates to a mountain historical block ownership perception evaluation method based on multi-modal data, public spaces of mountain historical blocks are divided into multiple types, an experimental path is selected from each public space, and multiple experimental parking points are selected from each experimental path; the evaluation index system comprises physiological data, psychological data and spatial data, and the spatial data comprises feature data and acoustic environment data; for each experiment path, obtaining feature data, recruiting a plurality of experimenters, collecting acoustic environment data and physiological data of each experimenter in real time, and collecting psychological data from the experimenters in real time in a questionnaire mode at an experiment stop point; independent variables are defined as spatial data, dependent variables are defined as psychological data and physiological data, based on experimental data, the relation between the independent variables and the dependent variables is learned through a random forest model, and bar charts of the influence degrees of the independent variables and the dependent variables are output; and the evaluation result is more accurate and persuasive.

The invention discloses an urban rainstorm waterlogging rapid simulation method based on a deep convolutional neural network, relates to the field of urban waterlogging management, and solves the problem that the judgment of the urban waterlogging prevention capability is inaccurate due to the fact that the current urban waterlogging prevention capability is generally obtained according to the urban water supply and drainage capability and the historical peak rainfall condition. The method comprises the steps that a catchment area corresponding to a target city is set according to a city design drawing, and catchment grids corresponding to the catchment area are divided based on the catchment area; a height-area curve corresponding to the catchment area is constructed according to the catchment grid, and an overflow model corresponding to the catchment area is constructed based on the height-area curve and improved; the result is simulated and recognized through the improved overflow model, then the result is compared with a historical actual value, and the precision condition of the improved overflow model is judged; real-time rainfall data is obtained and imported into the improved overflow model, the simulated submerging conditions of different catchment grids in the target city are obtained, and accurate simulation of urban rainstorm waterlogging is achieved.

The invention relates to the technical field of traffic planning, in particular to a road congestion shunting system suitable for urban design, which comprises a node congestion identification module, a signal time sequence adjustment module, a path interference screening module, a signal priority ordering module and a linkage time period correction module. According to the method, a multi-direction traffic pressure concentration area is formed through path overlapping structure identification, an association boundary of a path group and a node state is opened, a green light starting time sequence is adjusted in combination with a column head static continuous behavior, a vehicle response and period synchronization relation is reconstructed, and structural proximity judgment is introduced in path conflict screening. High-interference paragraphs are identified by utilizing the correlation degree of guidance, speed and lane parameters, a node sorting mechanism dynamically generates priorities through the consistency of a frequent path and a queuing trend, real-time refreshing of a signal response sequence is realized, linkage rhythm correction is bidirectionally verified according to release delay and an adjacent node blocking state, a starting segment is dynamically adjusted, and the linkage rhythm is corrected. Chained dislocation is avoided.

The present invention provides a sponge city design method and system, relating to the field of sponge city data processing technology. The method comprises obtaining information; simulating the waterlogging situation in the urban area using an agent-based model based on the information to obtain a waterlogging distribution map; constructing a graphical model based on the drainage system data; and constructing a drainage pipeline layout optimization model based on the graphical model and the waterlogging distribution map. The drainage pipeline layout optimization model includes an objective function and constraints, the objective function including minimizing the sum of the construction cost of the drainage pipeline and a penalty for insufficient drainage capacity. The constraints include flow balance constraints at the drainage points, capacity constraints of the drainage pipelines, drainage capacity constraints in the flood-prone areas, and drainage capacity constraints in the drainage bottleneck areas. The method then solves the drainage pipeline layout optimization model based on hypergeometric distribution sampling. The present invention takes into account the differences between different urban areas and significantly improves the design results of sponge cities.

The invention relates to the technical field of three-dimensional rendering, in particular to a digital city design city model visual display system which comprises a purpose calibration module, a component combination module, a path guide module, a view angle scheduling module and a rendering display module. According to the method, more accurate visual representation of urban model space purposes is realized by optimizing purpose calibration in the urban space and careful processing of geographic information, more reasonable space utilization distribution and visual display are realized by dynamically adjusting anchor points of the purpose space, more intelligent decision making in urban planning and building design is supported, and the method has the advantages of being high in practicability and easy to popularize. By extracting and combining building components with different functions, the functional semantic expression of the model is further enhanced, the information value and practicability of the model are enhanced, the interactivity and educational significance of the model are enhanced, and the model is more vivid visually and can reflect the appearance of a real city more accurately due to the improvement of rendering display. And the display quality and attraction of the model are improved.

The invention discloses a city design noise optimization method and system based on artificial intelligence, and the method comprises the steps: carrying out the preprocessing of building form and noise measurement data, and constructing a basic data set after noise simulation verification; a three-dimensional city model and a measuring point network are generated through a layered parameterization framework, the structural noise level is calculated, real-time verification is carried out in combination with planning constraints, and a structural design space, noise basic data and feasibility guarantee are provided; a two-stage multi-layer perceptron network is constructed, local building group acoustic influence and a global city noise mode are processed respectively, and high-precision noise prediction is achieved through training; and deploying a large language model as an optimization agent, and outputting an optimal scheme through multiple rounds of iterative optimization and evaluation. Compared with the prior art, the method has the advantages that the noise prediction precision is effectively improved, a structured design space is provided for parametric modeling, the feasibility is guaranteed through real-time verification, efficient iteration is achieved through large language model optimization, and compared with a traditional method, the efficiency is remarkably improved, and the labor cost is reduced.

The invention provides a building interface style migration and optimization method based on multi-machine learning model coupling. According to the method, a building interface style migration model is constructed based on various machine learning technologies, so that different building style characteristics and a mapping relation thereof are obtained. Based on a de-noising diffusion probability model and a cyclic generative adversarial network, high-quality style migration among different architectural styles is realized, the stability and detail quality of an architectural interface design scheme are optimized through a neural network, and a multi-objective optimization method is combined to generate an architectural interface layout scheme meeting urban design requirements. Compared with the prior art, the method has remarkable advantages in the aspects of building interface style migration precision, generation scheme adaptability and optimization design efficiency. Meanwhile, due to the reversibility of the design process, the generation result of the scheme can be returned to any step at any time to be optimized until the generated image meets the construction design requirement.

The application provides a kind of urban design scheme image generation method and device, with such characteristics, including step S1, according to existing city planning image construction training data set;Step S2, construct planning parameter prediction model and design generation model, and according to training data set respectively training, obtain trained planning parameter prediction model and trained design generation model;Step S3, input specified region image into trained planning parameter prediction model, obtain corresponding predicted planning parameter;Step S4, input predicted planning parameter and specified region image into trained design generation model, obtain design scheme image.In short, the method can generate effective and have specified features and style design scheme image according to specified image.

The present invention relates to a measurement method for high-density three-dimensional composite urban form characteristics, and a computing apparatus and a storage medium. The measurement method comprises: delineating a three-dimensional identification boundary, and acquiring raw map data; performing screening processing on the raw map data, and performing three-dimensional modeling within the identification boundary; calculating three-dimensional characteristic measurement indices; selecting three-dimensional base coverage rate and three-dimensional base plot ratio to construct a coordinate system, and classifying sample indices into hierarchies according to distribution characteristics; using a hierarchical clustering algorithm to constantly perform iteration until all data is combined into one category; and storing the data, building a three-dimensional urban database, and keeping the data updated. The present invention is aimed at the form characteristics of three-dimensional composite urban development during the renewal of high-density cities, and solves the problems in the prior art of it not being possible to precisely express three-dimensional urban forms and it also not being possible to perform effective quantitative analysis on the three-dimensional urban forms during urban design.

The invention discloses an urban carbon emission estimation method and device based on a VCA prediction spatial form and a medium. The method comprises the following steps: acquiring urban three-dimensional space driving factor data, and constructing a spatio-temporal data set; constructing a deep learning network, inputting the spatio-temporal data set into the deep learning network, and extracting spatio-temporal neighborhood features of the urban three-dimensional space driving factor data; according to the extracted space-time neighborhood features, predicting urban spatial form data by adopting a coupling model of an artificial neural network and a cellular automaton; and estimating urban carbon emission according to the urban spatial form data. According to the method, an innovative planning and design support tool is provided for low-carbon city planning and design, city arrangement carbon emission is controlled through related carbon emission reduction technical indexes, meanwhile, spatial distribution and time sequence distribution of the city carbon emission are output, a designer can conveniently optimize the city spatial form in the city design stage, and the design efficiency is improved. And the scientificity and the implementability of urban planning are obviously improved.

The application relates to a city design scheme generation method, device and equipment and a storage medium. The method comprises the following steps: obtaining multi-dimensional index data from a data source, performing a preprocessing operation to obtain a sample data set, constructing a data warehouse, obtaining related data of a city design scheme to be generated input by a user, dividing target plots according to the related data, calculating initial attribute indexes of each target plot, optimizing the initial attribute indexes by using predicted attribute indexes output by an index prediction model, obtaining target attribute indexes of each target plot, calculating building shape parameters of the city according to the target attribute indexes, generating an initial three-dimensional model of the city design scheme, and identifying the initial three-dimensional model by using different colors to obtain a target three-dimensional model of the city design scheme. The application can generate a city design scheme which is compliant, reasonable, has distinct city characteristics and designer will, and has high practicability.

The application relates to the technical field of grass-roots scheme generation, and discloses a parameterized rule-based urban design grass-roots scheme generation method and platform, which comprises the following steps: classifying and prototype extracting control regulation land blocks and corresponding building prototypes to obtain land blocks and building parameter rules of the same land property based on a control regulation land layout scheme; designing grass-roots scheme generation rules; the grass-roots scheme generation rules are used to form the grass-roots scheme in the order of control regulation land block-splitting land block-building block-concrete elements, and the land block-splitting rule, the building combination form rule, the building form prototype rule and the land block index accounting rule are met in the process of forming the grass-roots scheme; inputting the related parameters of the land block to be generated into the urban design grass-roots scheme, combining the grass-roots scheme generation rules to generate the corresponding urban design grass-roots scheme and performing index accounting on the generated urban design grass-roots scheme. The application further improves the efficiency and rationality of urban design scheme deduction.

The present invention relates to a method, computing device, and storage medium for measuring the morphological characteristics of high-density, three-dimensional, and composite cities. The method comprises: defining a three-dimensional identification boundary and obtaining original map data; screening and processing the original map data to perform three-dimensional modeling within the identification boundary; calculating three-dimensional characteristic measurement indicators; selecting a three-dimensional base surface coverage rate and a three-dimensional base surface volume ratio to construct a coordinate system, and dividing the sample indicators into hierarchical levels according to their distribution characteristics; employing a hierarchical clustering algorithm and continuously iterating until all data are merged into a single category; storing the data, establishing a three-dimensional city database, and maintaining data updates. The present invention addresses the morphological characteristics of three-dimensional composite urban development during high-density urban renewal, resolving the problems of prior art in accurately expressing three-dimensional urban morphology and effectively quantifying and analyzing three-dimensional urban morphology during urban design.

The invention provides an automatic modeling method for a high-density urban street canyon space. The automatic modeling method comprises the following steps: determining an acquisition range and acquiring basic data; effective street center lines are identified and screened out, an effective sampling range is obtained by measuring the maximum sampling distance, and effective building objects in the sampling range are identified; for each street, building a building projection reference surface according to a street center line, and measuring and identifying a projection surface of an effective building contour; for each street, according to a building projection reference surface constructed by a street center line, measuring and identifying a projection surface of a street space without building projection; and for each street, constructing a street canyon space model of all effective street objects through all projection surfaces and projection distances between each building or a street space without building projection and the projection surfaces, and carrying out association marking on the street canyon space model and a corresponding street number. The method aims at quantitatively analyzing the street canyon spatial form on a large scale, and a scientific and rational basis is provided for urban design and street public space planning.

The invention relates to the technical field of artificial intelligence and city design, in particular to a community national fitness space intelligent evaluation method and system based on an artificial intelligence algorithm, and the method comprises the following steps: obtaining three-dimensional space data, constructing a multivariate data set, and building a national fitness space three-dimensional model; identifying and disassembling national fitness space digital assets; recombining national fitness space assets, and training a national fitness space reference evaluation model; and constructing a national fitness space intelligent evaluation model. The invention provides a community nationwide fitness space intelligent evaluation method and system in the aspect of space quality evaluation by using an artificial intelligence algorithm. An innovative research framework is provided for scientific planning and optimized layout of community nationwide fitness space construction, the method can be suitable for nationwide fitness space quality evaluation in the design stage, space quality evaluation is preposed, design response can be conducted in a targeted mode according to the evaluation condition of the space quality, and the later space maintenance cost is reduced.

The application relates to the technical field of three-dimensional rendering, in particular to a digital city design city model visual display system, which comprises a use calibration module, a component combination module, a path guiding module, a visual angle scheduling module and a rendering display module. In the application, through optimization of use calibration in city space and detailed processing of geographic information, more accurate visual performance of the use of the city model space is realized, through dynamic adjustment of the anchor point of the use space, more reasonable space utilization distribution and visual display are realized, more intelligent decision making in city planning and building design is supported, through extraction and combination of building components with different functions, the functional semantic expression of the model is further strengthened, the information value and practicability of the model are enhanced, the interactivity and educational significance of the model are strengthened, and the improvement of the rendering display makes the model more realistic in vision and more capable of accurately reflecting the appearance of a real city, thereby improving the display quality and attraction of the model.

This invention provides a method for generating the spatial structure of historical sites that synergizes historical mechanisms with current urban functions. The method includes: mining the evolutionary mechanisms of the historical site's holographic pattern formation based on multi-evolutionary modal cellular automata, obtaining an evaluation of the historical space's evolutionary advantage, and deducing the historical space's directed structure based on a graph algorithm; mining the historical site's contraction evolutionary mechanisms and evaluating the compatibility strength of the historical attributes of open spaces based on a multi-type land use spatiotemporal evolution cellular automaton model; evaluating the public utilization potential of urban open spaces based on spatial configuration theory and multi-source spatial utilization data; and generating a fragmented urban historical site spatial structure using a weighted graph-inspired search algorithm, utilizing the historical space's directed structure, historical space evolutionary advantage evaluation, historical attribute compatibility strength evaluation, and public utilization potential evaluation, as a basic structure for site protection and revitalization development. This invention provides theoretical and methodological guidance for urban design innovation, as well as operational guidance.

The present invention discloses an automatic urban morphology measurement method based on a spatial entropy fourth-order matrix model, which relates to the field of urban design technology. The method performs fourth-order matrix modeling based on the relative morphological information of the target building and surrounding buildings, and then classifies the buildings according to the clustering algorithm of the fourth-order matrix. The city is partitioned according to the spatial entropy value measurement, thereby identifying problematic buildings and urban areas. The present invention can meet the work needs of large-scale urban renewal and automatically generate a morphological transformation plan specific to each building. It has the characteristics of large scale and high precision, thereby improving the work efficiency of urban renewal.

The present invention discloses an artificial intelligence (AI)-based urban design multi-plan generation method for a regulatory plot. The method includes operation steps performed by the following modules: (1) plot space calculation sand table module; (2) regulatory characteristic parameter input module; (3) characteristic case intelligent learning module; (4) plot road intelligent generation module; (5) plot landscape intelligent generation module; (6) plot architecture intelligent generation module; and (7) outputted plan auxiliary drawing module. By means of the AI-based urban design multi-plan generation method for a regulatory plot of the present invention, the planners realize real-time, accurate, and efficient feedback adjustment to a plurality of urban design plans under regulatory conditions, resolving a plurality of problems such as a long working period of a conventional design plan.

The invention relates to the technical field of scene simulation, in particular to a city design scene simulation system and method based on man-machine interaction, and the system comprises an interaction influence analysis module, a region priority analysis module, a simulation precision adjustment module, a thread task scheduling module and a scene simulation updating module. According to the method and the device, the interaction behavior data of the user is acquired and analyzed, the region priority is calculated according to the task density of the region, and the simulation precision is adjusted, so that the execution of the simulation task is more accurate and targeted, and the simulation task of the high interaction region is preferentially executed by dynamically optimizing thread scheduling; according to the method, computing resources and simulation precision can be ensured to be more intensively applied to an area which has greater influence on decision making, the operation efficiency and response speed of a simulation system are improved, details of a high-interaction area are more accurately presented through generation and task scheduling of a precision adjustment area list, and the user experience is improved. And excessive computing resource consumption of unimportant areas is avoided.

This invention provides a method and system for generating 3D digital maps of cities based on spatial entropy, relating to the field of artificial intelligence-based urban design. The method includes constructing a 3D spatial digital map based on land use function plots, measuring and displaying the spatial entropy of these plot units, collecting data on population activity and public sentiment, identifying and displaying plots requiring secondary updates and warnings, adjusting and reviewing the spatial entropy before updating, stitching together the adjusted 3D digital maps, and printing them out for reference by planning, design, and management personnel. It focuses on the production and display technology of large-scale 3D digital map images based on spatial entropy, achieving accurate expression of large-scale urban landscape features across a wide area, enabling real-time display of urban landscape features and rapid revelation of basic patterns, thus improving the efficiency and accuracy of determining urban landscape features.

The invention discloses a city design auxiliary optimization management system based on multi-modal data, and relates to the field of auxiliary optimization, and the system comprises a data collection module which is used for constructing a three-dimensional city image, obtaining a corresponding three-dimensional city function image layer according to the three-dimensional city image and structure function information, and obtaining function collection data; the data processing module carries out function evaluation on the collected function collection data and obtains function coverage data; the defect analysis module obtains corresponding functional defect data according to the functional coverage data; an optimization analysis module carries out vertical plane superposition and combination on the functional defect data at different positions in each three-dimensional urban functional map layer to obtain functional cooperation data at each position among different structure functional information; the design auxiliary module carries out scheduling matching on function defect data corresponding to different structure function information in sequence according to the obtained function collaboration data, and design auxiliary information is generated; according to the invention, the accuracy of the city design auxiliary optimization management process is improved.

An artificial intelligence-based urban design noise optimization method and system includes: preprocessing building form and noise measurement data, constructing a basic data set after noise simulation verification; generating a three-dimensional urban model and a network of measurement points through a hierarchical parameterized framework, calculating the structure-borne noise level, and verifying it in real time in conjunction with planning constraints, providing a structured design space, basic noise data, and feasibility assurance; constructing a two-stage multilayer perceptron network to process the acoustic impact of local building clusters and global urban noise patterns, respectively, and achieving high-precision noise prediction through training; deploying a large language model as an optimization agent, and outputting the optimal solution through multiple rounds of iterative optimization and evaluation. Compared with traditional technologies, this invention effectively improves noise prediction accuracy. Parametric modeling provides a structured design space, real-time verification ensures feasibility, and the use of a large language model for optimization enables efficient iteration, significantly improving efficiency and reducing labor costs compared to traditional methods.

The application discloses a city plot height self-adaptive generation and demonstration platform based on an artificial intelligence algorithm, and comprises the following steps: site data collection and calculation; case data collection and conversion; site space structure generation and structure potential value division; spatial structure holographic display and selection; plot height self-adaptive generation; human-computer interaction adjustment of plot height; scheme judgment and output; the city plot height self-adaptive generation and demonstration platform based on the artificial intelligence algorithm solves the problems of complicated traditional manual scheme design process, long working period, poor interactive design, high labor cost and the like, and further improves the efficiency of plot height generation; integrates the designer thinking and computer logic, realizes a top-down and bottom-up combined height form scheme generation method, and responds to city design height scheme generation in more scenes.

The invention relates to the technical field of urban planning, in particular to a street space livable measurement method under multi-source data fusion, which adopts an active sensing technology to carry out quantitative measurement research on street view data, space syntactic data and wind environment data in a space based on a human livable sensing view angle. On the basis of a human-based space livability evaluation index, an evaluation index weight and an index evaluation standard are further perfected, and a new scientific basis is provided for stock space update and development. For urban design practice requirements of urban micro-update under the human scale, the street space quality research needs continuous, large-scale and high-precision street space characteristic measurement instead of a few street section surfaces. Based on this, the research data of the method has good geographic position information attribute characteristics, rapid and accurate evaluation of the space livable quality is realized, and the research purpose of truly guiding human-scale street space quality micro-update practice is achieved.

The present invention discloses a method, device and storage medium for defining the isochronous three-dimensional influence domain of rail transit stations, which relates to the technical field of TOD urban design and influence scope definition of rail transit stations. The isochronous circle layer is defined and the vitality intensity is simulated based on the Urban Network Analysis (UNA) tool; based on the operation of service scope indicators, the isochronous circle layer is expanded at different speeds of various slow traffic connections, so as to enhance the awareness of traffic accessibility and weaken the value difference caused by far and near distances, thereby guiding the integration of scattered urban resources; from the perspective of comprehensive connection, multiple urban elements such as traffic, function and space are systematically integrated, and corresponding weight assignment and addition can be carried out to simulate the vitality intensity in UNA; based on the expansion of the isochronous circle layer and the integration of comprehensive connection elements, the research scope is extended to adjacent stations, forming a multi-station linkage mechanism guided by the isochronous circle layer and the integration of slow traffic vitality.

The invention discloses a crowd behavior pedigree modeling method based on multi-modal identification and high-precision positioning. The method comprises the following steps: step 1, collecting sample data; 2, performing high-precision behavior data fitting; step 3, extracting a multi-modal behavior factor; 4, constructing a behavior type pedigree; and step 5, database integration and visual display. According to the method, accurate alignment of behaviors and spatial information is realized by fusing video images and positioning data and combining target detection, posture recognition and spatial reconstruction. And then multiple types of behavior factors including speed, direction, attitude, facility interaction and group interaction are extracted, a behavior graph structure is constructed, a graph neural network is adopted to identify behavior types, and a structured pedigree model is formed. The method can cope with application scenes such as public space behavior recognition, city design optimization and smart city management, and fine analysis and presentation of a target space crowd behavior mode are realized.