Dynamic city model system based on scenario planning

Abstract

The invention relates to the technical field of city planning, and provides a dynamic city model system based on scenario planning, a city data acquisition and integration module collects multi-dimensional data and provides a basis for land project evaluation, and a land project evaluation module covers sub-modules of location, matching, cost and financial index measurement and calculation and the like, comprehensively analyzes projects, and improves the evaluation efficiency. The real-time dynamic adjustment module can timely cope with planning change and adjust cost, the scenario planning module considers various scenario simulation project development, and the decision support and strategy making module comprehensively assesses a decision, so that a real estate company can fully consider uncertainty factors, comprehensively assess project investment value and risk, make a scientific decision, and improve the project quality. The method provides a comprehensive, scientific and dynamic tool for real estate companies, and is used for evaluating the investment potential and feasibility of a land project in different scenes, assisting in deciding whether to obtain a land or not and making a subsequent development strategy, ensuring that the project meets the requirements of urban planning and land utilization planning, and maximizing economic benefits.

Description

Technical Field

[0001] The present invention relates to the technical field of urban planning, and in particular to a dynamic urban model system based on scenario planning. Background Art

[0002] The real estate industry faces a complex market environment and decision-making needs. On the one hand, cities are developing rapidly, and geographic information, planning policies, economic population and other data are constantly changing; on the other hand, land project investment decisions need to comprehensively consider multiple factors to ensure a balance between benefits and risks.

[0003] At the technical level, geographic information system (GIS) technology provides support for the accurate acquisition and analysis of geographic spatial data, including topography, transportation networks, and water distribution, and is the basis for the location and supporting analysis of land projects. At the same time, database technology is used to integrate various types of data, such as urban planning documents, economic and demographic data, etc., so that each module can call it. Data analysis technology is widely used in land project evaluation modules, such as multi-factor weighted scoring method and gravity model for location analysis, and cost measurement needs to be combined with financial analysis technology, including earned value calculation, cost deviation and performance index analysis. These technologies together constitute a systematic technical background for comprehensive evaluation of land project investment value and risk.

[0004] In order to help real estate companies solve the problem of lack of comprehensive, scientific and dynamic tools for evaluating the investment potential and feasibility of land projects under different scenarios, assisting in decision-making on whether to acquire land and formulating subsequent development strategies, ensuring that projects comply with urban planning and land use planning requirements, and maximizing economic benefits, the present invention proposes a dynamic urban model system based on scenario planning to solve the above problems. Summary of the invention

[0005] Technical issues solved

[0006] In view of the lack of comprehensive, scientific and dynamic tools in the existing technology to help real estate companies solve the problem of lack of relevant tools for evaluating the investment potential and feasibility of land projects under different scenarios, assisting in decision-making on whether to acquire land and formulating subsequent development strategies, ensuring that the projects comply with urban planning and land use planning requirements, and maximizing economic benefits, the present invention provides a dynamic urban model system based on scenario planning.

[0007] Technical Solution

[0008] To achieve the above-mentioned solution, the present invention provides the following technical solutions: a dynamic city model system based on scenario planning, including a city data collection and integration module, a land project evaluation module, a scenario planning module and a decision support and strategy formulation module;

[0009] The urban data collection and integration module is used to obtain the city's geospatial data, collect various planning documents prepared by the urban planning department, and collect macroeconomic data of the city and region;

[0010] The land project evaluation module includes location analysis submodule, supporting analysis submodule, market and customer research submodule, scheme design submodule, cost estimation submodule, cost analysis and monitoring, financial indicator estimation submodule and real-time dynamic adjustment module;

[0011] The real-time dynamic adjustment module establishes a data sharing interface with the urban planning department to obtain the official urban planning adjustment information in real time, establishes an information monitoring channel, extracts key planning change event information, divides planning change events into facility addition, facility change, and facility removal, and constructs a cost adjustment coefficient model. The basic cost in the absence of planning changes is C0. For facility addition events, the cost adjustment coefficient is set to α, and the calculation formula is:

[0012] α=f1(S,D,I),

[0013] Among them, S represents the scale index of the new facilities, D represents the distance between the new facilities and the land project, I represents the overall development level or influence index of the region, and f1 is a functional relationship determined based on historical data and expert experience, which is fitted by multiple linear regression analysis and neural network methods.

[0014] For facility change events, let the cost adjustment coefficient be β, and its calculation formula is:

[0015] β=f2(ΔS,ΔF,R),

[0016] Among them, ΔS represents the difference between the scale of the facility after the change and the original scale, ΔF represents the quantitative index of the change of the facility function, R represents the elasticity coefficient of the regional real estate market, and f2 is the functional relationship determined according to the characteristics of the facility change and market data.

[0017] For facility demolition events, let the cost adjustment coefficient be γ, and its calculation formula is:

[0018] γ=f3(T,U,P),

[0019] Among them, T represents the type of demolition facilities, U represents the original service scope and influence index of the demolition facilities, P represents the adjustment direction of land use planning in the area where the land project is located, and f3 is a functional relationship determined according to the characteristics of the demolition facilities and the regional planning situation.

[0020] According to the cost adjustment coefficient model, the adjustment range of land project cost after planning changes is calculated. For new facility events, the calculation formula for the adjusted cost C1 is:

[0021] C1=C0×(1+α),

[0022] For facility change events, the adjusted cost C2 is calculated as follows:

[0023] C2=C0×(1+β),

[0024] For facility removal events, the adjusted cost C3 is calculated as follows:

[0025] C3=C0×(1-γ);

[0026] The scenario planning module is used to set scenarios with different variable combinations and compare and analyze the simulation results;

[0027] The decision support and strategy formulation module is used to enable real estate company staff to adjust relevant data or scenario parameters in the system in a timely manner based on the results of scenario simulation and analysis, re-simulate and analyze the scenario, and quickly generate new decision suggestions and strategy adjustment plans.

[0028] Preferably, the urban data collection and integration module includes a geographic information system data access function for acquiring geospatial data from professional geographic information databases or relevant surveying and mapping departments; an urban planning data import function for collecting various planning documents formulated by urban planning departments; and an economic, population and industry data collection function for collecting macroeconomic data, population data and industry data for cities and regions.

[0029] Preferably, the location analysis submodule determines the evaluation factors and weights by collecting basic geographic information, traffic-related data, surrounding supporting facilities data, regional economic data and population data of the land project, and uses gravity model analysis to evaluate and grade the location of the land project.

[0030] Preferably, the supporting analysis submodule evaluates the completeness of public supporting facilities around the land project based on urban planning data and field survey data through data collection and organization, buffer zone analysis and accessibility analysis, and predicts the impact of future changes in supporting facilities on the land project.

[0031] Preferably, the cost estimation submodule calculates the land acquisition cost, development and construction cost, and operation and management cost based on the basic information of the land project, market data, and real-time dynamic adjustment module information through project pre-preparation, data collection and recording, earned value calculation, cost analysis and monitoring, and cost forecasting and adjustment, and adjusts the cost estimate in time when there are new plans around the land.

[0032] Preferably, the financial indicator calculation submodule calculates profitability indicators, debt-paying ability indicators, operating ability indicators and development ability indicators according to specific financial data and analysis purposes to evaluate project profitability and investment value.

[0033] Preferably, the real-time dynamic adjustment module monitors the land surrounding planning change information in real time, constructs an event classification system, determines direct cost influencing factors, establishes a cost adjustment model, and feeds back the adjusted cost data to the cost estimation submodule.

[0034] Preferably, the scenario planning module sets multiple scenarios according to the macro-environment of urban development, policy trends, and market trend uncertainty factors, combines the results of the land project evaluation module with the scenario setting parameters, performs scenario simulation and analysis, and outputs project evaluation reports under different scenarios.

[0035] Preferably, the decision support and strategy formulation module determines the decision objectives, sets evaluation criteria and weights based on scenario simulation results and internal company data, uses multi-criteria decision analysis methods to conduct decision evaluation, generates a decision recommendation report, and formulates corresponding strategy adjustment plans.

[0036] Preferably, there is data interaction between the modules in the system. The urban data collection and integration module stores the collected data in the system database for other modules to call. The land project evaluation module obtains data from the database for analysis. The real-time dynamic adjustment module feeds back the adjusted data to the cost estimation submodule. The scenario planning module uses the results of the land project evaluation module for simulation analysis. The decision support and strategy formulation module performs decision evaluation and strategy formulation based on the scenario simulation results.

[0037] Beneficial Effects

[0038] Compared with the prior art, the present invention provides a dynamic city model system based on scenario planning, which has the following beneficial effects:

[0039] 1. This dynamic urban model system based on scenario planning provides real estate companies with a comprehensive, scientific and dynamic tool to evaluate the investment potential and feasibility of land projects under different scenarios, assist in making decisions on whether to acquire land and formulate subsequent development strategies, ensure that the project complies with urban planning and land use planning requirements, and maximize economic benefits.

[0040] 2. The dynamic urban model system based on scenario planning collects multi-dimensional data through the urban data collection and integration module to provide a basis for land project evaluation. The land project evaluation module covers sub-modules such as location, supporting facilities, cost and financial indicator measurement, and comprehensively analyzes the project. The real-time dynamic adjustment module can adjust the cost in time to respond to planning changes. The scenario planning module considers multiple scenarios to simulate project development, and the decision support and strategy formulation module comprehensively evaluates the decision. This enables real estate companies to fully consider uncertainty factors, comprehensively evaluate the investment value and risks of the project, and make scientific decisions.

[0041] 3. The dynamic urban model system based on scenario planning has a complete process from data collection to decision-making, which enables real estate companies to fully consider various factors in the process of land investment decision-making, and formulate reasonable investment strategies by comprehensively evaluating the investment value and risks of projects, thus avoiding blind investment. At the same time, during the project development process, strategies can be adjusted in time according to changes in the market environment and other factors to effectively deal with risks. The system's strategy library function can also store and draw on past successful cases, continuously enriching the company's strategic resources, thereby enhancing the company's competitiveness and risk resistance in the real estate market. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a schematic diagram of the system module framework of the present invention;

[0043] Figure 2 It is a schematic diagram of the framework of the land project assessment module of the present invention. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0045] See also Figure 1-2 The present invention proposes a dynamic city model system based on scenario planning, which includes the following contents:

[0046] 1. System module design

[0047] 1. Urban data collection and integration module

[0048] 1. Geographic Information System (GIS) Data Access

[0049] Function: Obtain the city's geospatial data from professional geographic information databases or relevant surveying and mapping departments, including topography, land use status, transportation network (roads, railways, bus routes, etc.), water distribution, etc. These data are stored in the form of vector graphics or raster images, providing basic geographic information support for subsequent location analysis and supporting analysis.

[0050] Data sources: such as topographic maps provided by the local surveying and mapping bureau, satellite image data, traffic route data from the transportation department, etc.

[0051] Data update frequency: This depends on the update cycle of the data source. For example, satellite image data may be updated quarterly or annually, and traffic route data is updated in a timely manner when new routes are opened or adjusted.

[0052] 2. Import urban planning data

[0053] Function: Collect various planning documents prepared by urban planning departments, such as master plans, control detailed plans, special plans (such as transportation plans, green space system plans, etc.). Import information such as land use zoning, building density restrictions, plot ratio requirements, and public facilities supporting planning into the system, so as to follow relevant planning requirements in land project evaluation and scenario planning, and analyze the impact of planning adjustments on land projects.

[0054] Data sources: official documents of urban planning management departments, planning publicity information, etc.

[0055] Data update frequency: Update in a timely manner when urban planning is revised or adjusted to ensure that the system uses the latest planning data.

[0056] 3. Economic, demographic and industrial data collection

[0057] Function: Collect macroeconomic data of cities and regions, such as GDP growth trend, industrial structure distribution, resident income level, consumption level, etc.; collect population data, including total population, population growth rate, age structure, employment population distribution, etc.; understand the types of industries in the area where the land project is located, such as manufacturing, service industry, science and technology industry, etc., collect information such as the scale, output value, and number of employees of the industry, and study the development trend, policy support, and technological innovation of the industry, such as how many enterprises are around the plot, and what type of industry is the main type of enterprise. The more enterprises there are, the more industries that can attract high-end talents, the more employed people there are, the higher the quality of the people in the plate, and the higher the value of the corresponding plot. These data are used to analyze the economic development potential and population demand characteristics of the area where the land project is located, and provide a basis for financial indicator calculation and market positioning.

[0058] Data sources: Statistical yearbooks, economic census data, population census data released by statistical departments, and analysis reports from relevant economic research institutions.

[0059] Data updating frequency: Economic data are usually updated annually, while population data are updated according to the census cycle and regular releases by relevant statistical departments.

[0060] (II) Land Project Assessment Module

[0061] 1. Location analysis submodule

[0062] By collecting relevant data and information, the scores obtained by the multi-factor weighted scoring method and the gravity values ​​calculated by the gravity model are comprehensively analyzed, and the location of the land project is evaluated and graded according to the comprehensive score.

[0063] 1) Data collection and organization

[0064] Collect basic geographic information of land projects, including latitude and longitude coordinates, land area, shape and other data. These data can be obtained from the geographic information system (GIS) database or related surveying and mapping data.

[0065] Collect traffic-related data, such as urban road network information (road grade, length, width, etc.), public transportation station locations (bus stops, subway stations, etc.) and line information, traffic flow data, etc. Traffic flow data can be obtained through traffic monitoring equipment or data provided by relevant transportation departments, and road network and station information can be integrated from the data of urban transportation planning departments.

[0066] Collect data on surrounding supporting facilities, including the location, scale, and grade of schools, hospitals, shopping malls, parks, and entertainment venues. School data can be obtained from the school directory and related introductions of the education department, hospital information can be obtained from the health department, shopping malls and other commercial facilities can be collated through commercial survey agencies or field research, and public facilities such as parks can be obtained from urban construction management departments.

[0067] Collect regional economic data, including GDP data, industrial distribution, number and type of employment positions in the area where the land project is located and surrounding areas. These data are usually provided by statistical departments or economic research institutions.

[0068] Collect population data, such as population size, population density, age structure, household income distribution and other information, based on census data or related demographic information.

[0069] 2) Determine the evaluation factors and weight table as follows:

[0070]

[0071]

[0072] 3) Gravity model analysis

[0073] Determine the parameters and indicators in the gravity model

[0074] Select "attraction points" with significant influence in the region, such as major commercial centers, employment centers (large corporate parks, office building concentration areas), transportation hubs (airports, railway stations, large bus stations, etc.) as location j in the gravity model.

[0075] For each attraction point j, determine its attraction index P j For example, indicators such as annual turnover, commercial area or brand influence index can be used for commercial centers; indicators such as the number of jobs and total enterprise size can be used for employment centers; indicators such as passenger flow and freight volume can be used for transportation hubs. These indicator data can be obtained through commercial statistics, enterprise surveys, transportation department data, etc.

[0076] Determine the location of the land project as location i and calculate the distance d between the land project and each attraction point j ij The distance can be calculated by the GIS system based on the latitude and longitude coordinates to obtain the straight-line distance or the actual traffic path distance (taking into account the road network conditions).

[0077] The empirical constant K and the distance attenuation coefficient λ in the gravity model are determined based on experience and actual data fitting. For example, K = 1 and λ = 2 can be set in the preliminary analysis, and then adjusted and optimized based on the subsequent analysis results.

[0078] Calculate gravity value

[0079] According to the gravity model formula Calculate the gravitational force I between the land item and each attraction point ij The larger the gravity value, the stronger the attraction of the attraction point to the land project, and the more obvious the location advantage of the land project in this direction.

[0080] 2. Supporting analysis submodule

[0081] Based on urban planning data and field survey data, the completeness of public supporting facilities around the land project is evaluated. The number, scale, quality and distance of surrounding schools, hospitals, shopping malls, supermarkets, parks, cultural and entertainment facilities, etc. are analyzed to calculate the comprehensive score of supporting facilities. At the same time, the planning and construction of supporting facilities are considered to predict the impact of future changes in supporting facilities on the land project.

[0082] 1) Data collection and organization

[0083] Educational facilities: Collect information on the number, type (kindergarten, primary school, middle school, university, etc.), distance, and teaching quality (which can be measured by indicators such as school ranking and admission rate) of schools around the project.

[0084] Medical support: Statistics on the number, grade, department settings, medical equipment and distance from the project of surrounding hospitals and clinics.

[0085] Commercial facilities: Investigate the scale, business types, brand level, customer flow, and walking distance or driving time from the project of nearby shopping malls, supermarkets, commercial streets, farmers' markets and other commercial facilities.

[0086] Leisure and entertainment facilities: Understand the distribution, scale and completeness of facilities of surrounding parks, squares, gyms, cinemas, KTVs and other leisure and entertainment venues.

[0087] Public service facilities: including information such as the location and service scope of government offices, post offices, banks, community service centers, etc.

[0088] 2) Buffer analysis

[0089] Based on geographic information system (GIS) technology, different buffer radii are set with the project site as the center, and the distribution and quantity of various supporting facilities in each buffer zone are analyzed.

[0090] Different buffer zone radius standards are set according to different types of supporting facilities:

[0091] Educational facilities: For kindergartens, 300-meter and 500-meter buffer zones are set up; for primary schools, 500-meter and 1,000-meter buffer zones are set up; for secondary schools, 1,000-meter and 2,000-meter buffer zones are set up, which are used to analyze the distribution density and coverage of educational resources within different distance ranges.

[0092] Medical support: A 500-meter buffer zone is set up in community clinics, and a 1,000-meter and 2,000-meter buffer zone is set up in general hospitals to assess the convenience and accessibility of medical services around the project.

[0093] Commercial facilities: Small supermarkets and convenience stores will have a 200-meter buffer zone, medium-sized shopping malls will have a 500-meter or 1,000-meter buffer zone, and large commercial complexes will have a 1,000-meter or 2,000-meter buffer zone, which is used to measure the richness and service scope of commercial facilities around the project.

[0094] Leisure and entertainment facilities: Parks will set up 500-meter and 1,000-meter buffer zones; gyms, cinemas, etc. will set up 300-meter and 500-meter buffer zones to analyze the distribution of leisure and entertainment resources and their correlation with the projects.

[0095] Using the spatial analysis function of GIS, the number, type, area and other attribute information of various supporting facilities in the set buffer zone are counted, and the results are output in the form of visual charts (such as bar charts, pie charts) and data reports to intuitively display the distribution pattern of different supporting facilities around the land project within different buffer zones. For example, it is clear at a glance how many kindergartens and convenience stores there are in a 500-meter buffer zone, and how many primary schools and medium-sized shopping malls there are in a 1,000-meter buffer zone.

[0096] 3) Accessibility analysis

[0097] By calculating the travel time or distance from the project site to various supporting facilities, the convenience of residents in accessing supporting services can be assessed.

[0098] Integrate traffic data: collect road network data (including road grade, number of lanes, location of traffic lights, etc.) in the area where the land project is located, public transportation line data (bus stop location, bus route direction, operating hours, departure intervals, etc.) and real-time traffic flow data (which can be obtained through the transportation department's intelligent transportation system or in cooperation with third-party traffic data providers).

[0099] Determine the mode of transportation and its weight: Set multiple modes of transportation, such as walking, cycling, driving, public transportation, etc., and assign corresponding weights to each mode of transportation according to the travel habits and traffic conditions of local residents. For example, in the central area of ​​the city, the weight of public transportation may be higher; while in some suburbs or areas with inconvenient transportation, the weight of driving may be relatively large. The weight can be determined through resident travel surveys or traffic big data analysis.

[0100] Calculate the reachability index:

[0101] Walkability: Using the network analysis function of GIS, calculate the shortest walking distance from the land project to the surrounding supporting facilities, and combine the road conditions (such as whether there are overpasses, underground passages, sidewalk width, etc.) and real-time pedestrian density (which can be estimated through surveillance camera data or mobile phone signaling data) to comprehensively evaluate the convenience and time required to walk to supporting facilities. For example, if a walking path is short but needs to cross a congested commercial street or a narrow sidewalk, its walkability score will be reduced accordingly.

[0102] Public transportation accessibility: Based on the location of bus stops and bus routes, calculate the number of bus transfers, waiting time, and travel time from the project to supporting facilities. Consider the real-time operation of buses (such as whether they are late, changes in operating speed due to road congestion, etc.), and make corrections through the data of the bus intelligent dispatching system or real-time traffic information. For example, if a bus line is often late during peak hours, then the corresponding time cost needs to be added when calculating the accessibility of the line.

[0103] Driving accessibility: Combine the road network and real-time traffic flow data, and use traffic flow models to calculate the shortest driving route and driving time from the project to the supporting facilities. Consider factors such as speed limits of different road grades, intersection capacity, parking lot location and capacity. For example, if the surrounding supporting facilities are located in a busy commercial area, although the driving distance is short, parking is difficult, and its driving accessibility will also be affected.

[0104] Comprehensive accessibility evaluation: The accessibility indicators under different modes of transportation are weighted and summed to obtain the comprehensive accessibility score of the land project to various supporting facilities. For example, assuming that the walking weight is 0.3, the bus weight is 0.4, and the driving weight is 0.3, if the walking accessibility score of a school is 6 points, the bus accessibility score is 7 points, and the driving accessibility score is 5 points, then the comprehensive accessibility score of the school is 6×0.3+7×0.4+5×0.3=6.1 points. Sort and grade the surrounding supporting facilities according to the comprehensive accessibility score to intuitively understand the degree of connection and convenience between different supporting facilities and projects.

[0105] 3. Market and customer research submodule

[0106] This module aims to gain an in-depth understanding of market demand and customer preferences, and provide a basis for the positioning and planning of land projects. The specific contents are as follows:

[0107] Market research: Collect macroeconomic data, industry development trends, policies and regulations, and analyze the overall market situation. For example, study the supply and demand relationship, price trends, and competition situation in the real estate market.

[0108] Customer demand analysis: Through questionnaire surveys and interviews, we can understand the customer's demand characteristics, purchasing intentions, spending power, etc. For example, the customer's preferences for apartment type, area, decoration style, supporting facilities, and expectations for the community's positioning.

[0109] Target customer group positioning: Determine the target customer group of the land project based on the results of market research and customer demand analysis. For example, formulate corresponding marketing strategies for different groups such as young office workers, family users, and high-end customers.

[0110] 4. Solution design submodule

[0111] Based on the results of the market and customer research module, the land project scheme is designed. The specific contents are as follows:

[0112] Apartment design: Design different types of apartment types according to the needs and preferences of the target customer groups, including apartment size, layout, functions, etc. For example, for young families, design compact and practical small apartments; for high-end customers, design luxurious and spacious large apartments.

[0113] Community positioning: Combine market positioning and customer needs to determine the overall positioning of the community, such as high-end, mid-to-high-end, ordinary residential, etc. For example, create a high-end community with high-quality living facilities and beautiful green environment, or an economical and affordable community that meets the needs of the general public.

[0114] Supporting facilities planning: According to the community positioning and customer needs, planning supporting facilities, including architectural design, landscape design and interior decoration design.

[0115] 5. Cost calculation submodule

[0116] According to the basic information of the land project (such as land area, land nature, volume ratio, etc.), market data and information provided by the real-time dynamic adjustment module, calculate the land acquisition cost, development and construction cost (including construction project cost, infrastructure supporting cost, preliminary project cost, etc.), operation and management cost and other costs. When there are new plans around the land (such as new schools, hospitals, subway stations, etc.) that cause the land value to rise or fall, adjust the land cost estimate in time. The cost of the land project includes preliminary engineering costs (survey and design fees, three connections and one leveling engineering costs, administrative and operating charges, etc.), supporting facilities fees (civil air defense supporting facilities, equipment rooms, bicycle garages, community management service rooms, etc.), infrastructure fees (water, electricity, gas, roads in the community, weak electricity), construction engineering costs (materials and construction costs of the main structure of the building), environmental landscape engineering costs (greening, landscaping, sketches, lighting, etc.), engineering related fees (supervision fees, consulting fees, special testing fees, etc.), and subsequent engineering costs (maintenance and rectification fees).

[0117] 1) Project preparation

[0118] Determine the work breakdown structure (WBS): Decompose the project in detail according to deliverables and work tasks to form a clearly structured WBS. Each work package should have a clear scope of work, responsible person, time node and budget cost.

[0119] Develop a project schedule: Based on the WBS, determine the sequence and duration of each work task, draw a Gantt chart or other schedule chart, and identify the critical path and milestone nodes of the project.

[0120] Allocate budget costs: Allocate budget costs to each work package to ensure that the budget covers all work content of the project and that the budget allocation is reasonable and accurate. At the same time, establish a budget cost tracking and monitoring mechanism to keep track of budget usage in real time.

[0121] 2) Data collection and recording

[0122] Actual cost data collection: During the project execution, the finance department or cost management personnel are responsible for collecting the actual cost data of various work tasks, including labor costs, material costs, equipment rental costs, outsourcing costs, etc. These data should be recorded in the cost management system in a timely and accurate manner.

[0123] Data collection on work completion: Project team members regularly (such as weekly or monthly) report on the completion of their respective work tasks, including the amount of work completed, the quality of the work, whether milestones have been reached, etc. This can be quantified using methods such as the percentage of work completed and the actual amount of work completed.

[0124] 3) Earned value calculation

[0125] Determine the earned value calculation method: Choose the appropriate earned value calculation method based on the characteristics of the project and the nature of the work. Common methods include the 0 / 100 method (earned value is 0 before the work starts, and the earned value is the budget cost when the work is completed), the 50 / 50 method (earned value is 50% of the budget cost when the work starts, and the earned value is the budget cost when the work is completed), and the percentage of completion method (earned value is calculated based on the proportion of the actual completed work to the total work).

[0126] Calculate earned value: Calculate the earned value of each work package based on the selected earned value calculation method and work completion data. For example, if the budget cost of a work package is 10,000 yuan, and the actual completion rate is 60% using the percentage of completion method, the earned value of the work package is 10,000 × 60% = 6,000 yuan.

[0127] 4) Cost analysis and monitoring

[0128] Calculate cost variance (CV) and schedule variance (SV):

[0129] Cost variance (CV): CV = earned value - actual cost. CV>0 indicates cost savings, and CV<0 indicates cost overruns.

[0130] Schedule Variance (SV): SV = Earned Value - Planned Cost. SV>0 indicates that the schedule is ahead of schedule, and SV<0 indicates that the schedule is behind schedule.

[0131] Calculate the Cost Performance Index (CPI) and Schedule Performance Index (SPI):

[0132] Cost Performance Index (CPI): CPI = Earned Value / Actual Cost. CPI>1 indicates good cost performance and cost is lower than budget; CPI<1 indicates poor cost performance and cost overrun.

[0133] Schedule Performance Index (SPI): SPI = Earned Value / Planned Cost. SPI>1 indicates good schedule performance and ahead of schedule; SPI<1 indicates poor schedule performance and behind schedule.

[0134] Draw cost and schedule performance curves: With time as the horizontal axis and CV, SV, CPI, and SPI as the vertical axes, draw cost and schedule performance curves to intuitively display the changing trends of project cost and schedule.

[0135] 5) Cost forecasting and adjustment

[0136] Forecasting project completion costs (EAC): Based on the current cost performance, choose an appropriate method to predict the cost at project completion.

[0137] Forecast based on current performance: EAC = actual cost + (total budgeted cost - earned value) / CPI.

[0138] Consider the forecast of remaining work performance: Assuming that the remaining work will be performed according to the current performance level, EAC = actual cost + (total budget cost - earned value) × (total budget cost / earned value).

[0139] Cost adjustment measures: Take corresponding cost adjustment measures based on cost analysis and forecast results. If cost overruns are found, measures such as optimizing work processes, reducing unnecessary expenses, and adjusting resource allocation can be taken; if progress lags and affects costs, methods such as increasing resource input and adjusting work order can be considered to speed up progress and thus control costs.

[0140] 6. Financial indicator calculation submodule

[0141] Based on specific financial data and analysis purposes, these methods and models are flexibly used to measure financial indicators, and combined with industry standards and corporate historical data for comprehensive analysis to comprehensively evaluate the company's financial status and operating results. Through these financial indicators, the profitability and investment value of the project are evaluated, providing a quantitative basis for decision-making.

[0142] 1) Profitability indicator calculation

[0143] Gross profit margin = (operating income - operating costs) / operating income × 100%

[0144] Note: This indicator reflects the profit margin left after deducting direct costs, and reflects the basic profitability of the enterprise without considering other expenses. It can help enterprises understand the profitability of their core businesses. The higher the gross profit margin, the greater the advantage the enterprise has in cost control and product pricing.

[0145] Net profit margin = net profit / operating income × 100%

[0146] Note: Net profit margin is a comprehensive indicator to measure the profitability of an enterprise, which takes into account all cost and expense factors, including operating costs, sales expenses, administrative expenses, financial expenses, etc. The higher the net profit margin, the stronger the ability of the enterprise to obtain net profit in its operating activities.

[0147] Return on equity (ROE) = Net profit / average net assets × 100%

[0148] Note: ROE reflects the level of return on shareholders' equity and is used to measure the efficiency of a company's use of its own capital. It is one of the important indicators for measuring a company's profitability and reflects the company's ability to create value for shareholders. Generally speaking, the higher the ROE, the stronger the company's profitability and the more attractive it is to investors.

[0149] Internal Rate of Return IRR:

[0150] Assume that the net cash flow of the project is CF t (t=0,1,2,…,n), IRR satisfies the following equation:

[0151]

[0152] IRR is usually solved through iteration or by using professional financial software or spreadsheet software.

[0153] Note: Internal rate of return (IRR) refers to the discount rate when the cumulative present value of the net cash flow of the project in each year during the entire calculation period is equal to zero. It reflects the intrinsic return level of the project investment and is one of the important indicators for project investment decision-making. When the IRR is greater than the minimum required rate of return of the project (such as market interest rate, industry average rate of return, etc.), the project has investment feasibility; otherwise, the project may not have investment value. The higher the IRR of different projects, the higher the investment return of the project. By comparing the IRR of different projects, more attractive projects can be selected. Determine the project risk. The higher the IRR, the lower the risk of the project. In project decision-making, IRR can help assess the risk level of the project.

[0154] 2) Debt-paying capacity indicator calculation

[0155] Current Ratio = Current Assets / Current Liabilities

[0156] Note: Current ratio is a common indicator to measure a company's short-term debt repayment ability. It shows how much current assets a company has to repay each dollar of current liabilities. It is generally believed that the current ratio should be kept at around 2, but the standards in different industries may vary.

[0157] Quick ratio = quick assets / current liabilities, where quick assets = current assets - inventory

[0158] Note: The quick ratio can better reflect the ability of an enterprise to quickly convert assets into cash to repay short-term debts. Since the speed of converting inventory into cash is relatively slow, the quick ratio is more conservative and strict in measuring the short-term debt repayment ability of an enterprise. It is generally believed that the quick ratio should be kept at around 1, which is more reasonable.

[0159] Debt-to-asset ratio = total liabilities / total assets × 100%

[0160] Note: The debt-to-asset ratio reflects how much of a company's total assets are raised through debt, and it is an important indicator for measuring a company's long-term debt repayment ability. The higher the debt-to-asset ratio, the higher the company's debt level and the greater the long-term debt repayment risk. However, the reasonable range of debt-to-asset ratios varies from industry to industry. Generally, the debt-to-asset ratio of manufacturing companies may be relatively high, while that of service companies is relatively low.

[0161] 3) Calculation of operating capacity indicators

[0162] Accounts receivable turnover rate = operating income / average accounts receivable balance

[0163] Note: This indicator reflects the turnover rate of the company's accounts receivable, that is, the efficiency of the company in collecting accounts receivable. The higher the accounts receivable turnover rate, the faster the company's accounts receivable are collected and the stronger the liquidity of funds. It also shows that the company's credit management policy is relatively effective and reduces the risk of bad debt losses.

[0164] Inventory turnover rate = operating cost / average inventory balance

[0165] Note: Inventory turnover rate measures the turnover speed of an enterprise's inventory and reflects the level of an enterprise's inventory management. The higher the inventory turnover rate, the faster the enterprise's inventory turnover speed, the less funds occupied by inventory, and the higher the efficiency of fund use.

[0166] Total asset turnover rate = operating income / average total assets

[0167] Note: The total asset turnover rate reflects the operating quality and utilization efficiency of all assets of an enterprise. It reflects the sales revenue achieved by the assets of an enterprise in a certain period of time. The higher the total asset turnover rate, the higher the operating efficiency of the enterprise's assets and the more fully the assets are utilized.

[0168] NPI (Net Property Income)

[0169] NPI refers to the net rental income of a property after deducting operating expenses. The calculation formula is: NPI = total rental income of a property - operating expenses. Among them, operating expenses include property management fees, maintenance fees, taxes (excluding income tax) and other expenses directly related to property operations.

[0170] Note: NPI is mainly used to measure the profitability of the property operation stage in real estate investment projects, focusing on reflecting the operating benefits of the property itself. NPI is a key indicator when evaluating the development of land projects into commercial or rental properties (such as office buildings, apartments, shops, etc.). For example, for a commercial complex project, the profitability of its leasing business can be evaluated by calculating NPI, helping investors understand the level of net income that the property can generate after deducting operating costs. A higher NPI means that the property has better profitability and operating efficiency.

[0171] Yield-Cost

[0172] The Yield-Cost ratio refers to the ratio between the income and cost of a property, which is used to measure the level of return on investment relative to the cost. The calculation formula is: Yield-Cost = (annual net operating income / total cost) × 100%. Among them, the annual net operating income is similar to NPI, and the total cost includes all project-related costs such as land acquisition cost, development cost, financing cost, etc.

[0173] Description: This indicator can intuitively reflect the relationship between the project's revenue and input costs, helping investors quickly evaluate whether the project can obtain reasonable returns based on costs. In land project evaluation, whether it is a development and sale project or a long-term holding project, the Yield-Cost ratio can be used to compare the pros and cons of different project plans or different investment opportunities. For example, when comparing two land development projects in different locations, a higher Yield-Cost ratio means that higher returns can be obtained with the same cost input, or lower costs can be achieved with the same returns.

[0174] ROI (Return on Investment)

[0175] ROI refers to the value that should be returned through investment, that is, the economic return that an enterprise gets from an investment activity. The calculation formula is: ROI = (net profit / total investment) × 100%. For land projects, net profit refers to the balance after deducting total costs and taxes from the total income during the project operation period. The total investment includes all investment amounts such as land acquisition costs, development and construction costs, and operating capital investment.

[0176] Note: ROI is a comprehensive indicator to measure investment returns. It takes into account the entire process of project returns from investment to operation, and can fully reflect the profitability of the project. In the real estate field, investors can use ROI to evaluate the investment value of land projects and compare the effects of different investment projects or different investment strategies. For example, when deciding whether to invest in a large residential development project, by predicting the project's net profit and calculating ROI, you can intuitively understand the level of return that the project can bring to investors, thereby assisting in deciding whether it is worth investing.

[0177] NPV (Net Present Value)

[0178] NPV refers to the difference between the sum of the present values ​​of a project's cash flows in future periods and the present value of the initial investment. The calculation formula is: where CF t is the cash flow of period t (including cash inflows and outflows), r is the discount rate, n is the number of calculation periods for the project, and I0 is the initial investment.

[0179] Note: NPV takes into account the time value of money and is used to evaluate the profitability of a project throughout its life cycle. In land project evaluation, NPV can help investors determine whether a project is worth investing in. If NPV is greater than zero, it means that the project still has room for profit after considering the time value of money and is a feasible investment project; if NPV is less than zero, the project may not achieve the expected return on investment. For example, for a large-scale land project that is developed in phases, the overall value of the project is evaluated by calculating NPV by predicting the cash flow of each phase (such as sales revenue, rental income, development cost expenditure, etc. after land development) and selecting an appropriate discount rate (usually referring to the market interest rate or the rate of return required by investors).

[0180] 4) Calculation of development capability indicators

[0181] Operating income growth rate = (current period operating income - previous period operating income) / previous period operating income × 100% Description: This indicator reflects the growth rate of the company's operating income and is one of the important indicators for measuring the company's development capabilities. The higher the operating income growth rate, the stronger the company's market expansion capabilities and the better the business growth momentum.

[0182] Net profit growth rate = (net profit of this period - net profit of the previous period) / net profit of the previous period × 100%

[0183] Note: Net profit growth rate reflects the growth trend of the company's net profit and the growth rate of the company's profitability. A high net profit growth rate indicates that the company has strong development potential and growth momentum in terms of profitability.

[0184] Total assets growth rate = (total assets of this period - total assets of the previous period) / total assets of the previous period × 100%

[0185] Note: The total asset growth rate measures the growth rate of the company's asset scale and reflects the expansion of the company's assets over a certain period of time. A high total asset growth rate indicates that the company is proactive in capital investment and has strong development strength and potential.

[0186] 7. Real-time dynamic adjustment module

[0187] Real-time monitoring of planning changes around the land, such as new planning projects announced by the government (addition or removal of schools, hospitals, subway stations, etc.). When there are planning adjustments, timely analysis of their impact on land costs, and feedback of adjusted cost data to the cost calculation submodule.

[0188] 1) Establish information monitoring channels: Establish data sharing interfaces with urban planning departments to obtain official urban planning adjustment information in real time, including land use changes, public facility construction plans (such as new construction, expansion, relocation or demolition plans of schools, hospitals, subway stations, etc.) and regional infrastructure renovation plans (such as road widening, bridge construction, etc.). Use web crawler technology to collect information related to the planning around land projects from multiple channels such as official government websites, news media websites, and social media platforms, and use natural language processing technology to screen and classify information and extract key planning change event information.

[0189] 2) Construction of event classification system

[0190] Planning change events are divided into three categories: new facilities, facility changes, and facility removals. New facilities include new schools, hospitals, subway stations and other public service facilities or infrastructure; facility changes cover the expansion or reduction of the scale of facilities, functional adjustments (such as upgrading a school from an ordinary school to a key school), etc.; facility removal refers to the removal or relocation of existing schools, hospitals, subway stations and other facilities.

[0191] 3) Identify direct cost influencing factors

[0192] For new facility events, analyze the type, scale, and distance from the land project of the new facility to enhance the land value. For example, when building a large hospital, its scale index can be determined based on the number of beds and medical service level of the hospital, and its straight-line distance or actual traffic distance from the land project can be measured through the Geographic Information System (GIS). Generally speaking, the larger the scale of the facility and the closer the distance, the more significant the effect on enhancing the land value.

[0193] In the case of facility changes, the focus is on the differences between the changed facilities and the original facilities in terms of scale, function, etc., as well as the direction and degree of impact of these differences on land value. For example, if a school is upgraded to a key school, the increase in the value of the surrounding land can be quantified based on the differences between key schools and ordinary schools in terms of teaching staff, investment in teaching facilities, and academic performance.

[0194] For facility demolition events, the negative impact of factors such as the type of demolished facility, the original service scope and influence, and the planned use of the land after demolition on the land value should be considered. For example, the demolition of a subway station may lead to a significant decline in the traffic convenience of the surrounding land, thereby reducing the land value. The extent of the decline can be estimated based on factors such as the passenger flow of the subway station and the degree of dependence of the surrounding land on subway traffic.

[0195] 4) Construction of cost adjustment model

[0196] Building a basic cost model

[0197] First, determine the basic cost structure of the land project, including land acquisition costs, development and construction costs (such as construction costs, infrastructure costs, pre-project costs, etc.) and operation and management costs. These costs can be estimated using traditional cost measurement methods (such as the methods in the cost measurement submodule described above) to obtain the basic cost C0 of the land project without planning changes.

[0198] Constructing a cost adjustment factor model

[0199] According to different types of planning change events and their corresponding cost influencing factors, a cost adjustment coefficient model is constructed. For new facility events, the cost adjustment coefficient is set to α, and its calculation formula is:

[0200] α=f1(S,D,I)

[0201] Among them, S represents the scale index of the newly added facilities (such as the number of hospital beds, the number of school classes, etc.), D represents the distance between the newly added facilities and the land project, I represents the overall development level or influence index of the region (such as regional GDP, population density, etc.), and f1 is a functional relationship determined based on historical data and expert experience, which can be fitted through multiple linear regression analysis, neural network and other methods. For example, for the impact of new subway stations on land costs, the scale of subway stations (such as the number of lines, station passenger flow, etc.), the distance from the land project, the relationship between the regional development level and the land cost adjustment coefficient can be determined by analyzing the land cost change cases around multiple existing subway stations, and the corresponding function model can be constructed.

[0202] For facility change events, let the cost adjustment coefficient be β, and its calculation formula is:

[0203] β=f2(ΔS,ΔF,R)

[0204] Among them, ΔS represents the difference between the scale of the facility after the change and the original scale, ΔF represents the quantitative indicator of the change in the function of the facility (such as the improvement level of school teaching quality, the number of new medical service items in the hospital, etc.), R represents the elasticity coefficient of the regional real estate market (reflecting the market's sensitivity to facility changes, which can be obtained through regression analysis of historical market data), and f2 is the functional relationship determined based on the characteristics of the facility change and market data.

[0205] For facility demolition events, let the cost adjustment coefficient be γ, and its calculation formula is:

[0206] γ=f3(T,U,P)

[0207] Among them, T represents the type of demolished facilities (such as schools, hospitals, subway stations, etc.), U represents the original service scope and influence indicators of the demolished facilities (such as the enrollment scope of schools, the number of service populations of hospitals, the passenger flow of subway stations, etc.), P represents the land use planning adjustment direction of the area where the land project is located (such as adjustment from commercial land to residential land, etc.), and f3 is a functional relationship determined according to the characteristics of the demolished facilities and the regional planning situation.

[0208] Calculate adjusted cost

[0209] According to the cost adjustment coefficient model, calculate the adjustment range of land project cost after planning changes. For new facility events, the adjusted cost C1 calculation formula is:

[0210] C1=C0×(1+α)For facility change events, the adjusted cost C2 is calculated as follows:

[0211] C2=C0×(1+β)

[0212] For facility removal events, the adjusted cost C3 is calculated as follows:

[0213] C3=C0×(1-γ)

[0214] Scenario Planning Module

[0215] 1. Scenario Setting

[0216] Real estate investment experts or system administrators set up multiple scenarios in the system based on uncertain factors such as the macro environment of urban development, policy trends, and market trends. For example:

[0217] Optimistic scenario: Assuming that the city's economy maintains rapid growth in the next few years (such as an annual GDP growth rate of more than 8%), there is a large influx of population (such as an increase of more than 100,000 permanent residents each year), the area where the land is located is listed as a key development area of ​​the city, there is a large amount of infrastructure investment and industrial projects, and the real estate market has strong demand. House prices are expected to rise by more than 10% each year, and rental levels will also rise simultaneously.

[0218] Neutral scenario: The city's economy develops steadily (annual GDP growth rate is between 3% and 5%), the population grows moderately (30,000 to 50,000 new permanent residents are added each year), the region proceeds with construction as normal according to the existing plan, the supply and demand in the real estate market is basically balanced, and house prices and rents remain relatively stable, with an annual increase of about 3% to 5%.

[0219] Pessimistic scenario: Urban economic growth slows down (annual GDP growth rate is less than 3%), or even turns negative, with population outflow (permanent population decreases by 10,000 to 30,000 people each year), and regional development is restricted, such as lagging infrastructure construction and stagnant industrial projects. There is oversupply in the real estate market, and house prices are expected to fall by 5% to 10% each year, and rental levels will also decline accordingly.

[0220] Under each scenario, different combinations of variables are further refined, such as the specific value of the economic growth rate, the scale and structure of population inflows and outflows, the intensity and timing of policy control measures (such as purchase restrictions, loan interest rate adjustments, etc.), changes in land supply plans, etc., in order to construct a richer scenario model that is closer to actual possible situations.

[0221] 2. Scenario simulation and analysis

[0222] The system starts the scenario simulation function by combining various data obtained during the land project evaluation phase (such as location score, supporting score, cost data, financial indicator data, etc.) with the parameters in the scenario setting.

[0223] The simulation process follows the chronological order of project development, starting from land acquisition, and gradually simulating the cost expenditure and project progress during the development and construction process, to the income inflow during the sales or rental operation phase after the project is completed, and calculating the financial status and key indicator changes of the project at each time node. For example, in an optimistic scenario, due to rising housing prices and faster sales, the project's sales revenue will be realized in advance and the amount will increase, thus affecting the rapid improvement of indicators such as profit and return on investment; while in a pessimistic scenario, sales difficulties and slow capital recovery may occur, resulting in increased cost pressure and deterioration of financial indicators.

[0224] The system compares and analyzes the simulation results under different scenarios, plots the curves of key indicators (such as cost, income, profit, ROI, IRR, NPV, etc.) changing over time, and intuitively displays the development trends and differences of projects under different scenarios. Through sensitivity analysis, the factors and sensitive variables that have the greatest impact on the project are found. For example, in some scenarios, housing price fluctuations have the most significant impact on project profits, while in other scenarios, changes in land costs may become a key factor.

[0225] 4. Decision Support and Strategy Formulation Module

[0226] 1. Decision evaluation

[0227] According to the results of scenario simulation and analysis, the system uses multi-criteria decision analysis methods (such as the analytic hierarchy process AHP) to conduct decision evaluation. First, determine the decision-making goals, such as maximizing investment returns, minimizing risks, and complying with the company's strategic development direction. Then, factors such as the project's financial indicators, risk levels (such as market volatility risks, policy risks, etc.) and compatibility with the company's strategy (such as whether it complies with the company's layout plan in a specific region or product type) under different scenarios are used as evaluation criteria.

[0228] Set weights for each evaluation criterion, and the weights can be adjusted according to the company's strategic focus and risk appetite. For example, for companies pursuing steady investment, a higher risk level weight may be given; while for companies focusing on rapid expansion and high returns, more emphasis may be placed on the weight of investment return indicators. The system calculates a comprehensive evaluation score based on the performance of the project on each evaluation criterion in each scenario and the weights.

[0229] Generate a decision recommendation report for the project based on the comprehensive evaluation score. If the comprehensive evaluation score of the project is high in a certain scenario and meets the company's minimum investment requirements (such as minimum return on investment, acceptable risk level, etc.), the system recommends acquiring the land and gives corresponding investment strategy recommendations, such as whether the project is positioned as high-end residential or ordinary residential or commercial complex, development scale recommendations (such as building area, floor height, etc.), sales strategy (such as pricing strategy, promotion timing, etc.), operation and management strategy (such as property management service standards, business operation model, etc.). If the comprehensive evaluation score of the project is low in all scenarios, or there are unacceptable risk factors, the system recommends abandoning the land project.

[0230] 2. Strategy Adjustment

[0231] During the project development process, if the market environment, policies and regulations or the project itself changes (such as land costs increasing due to policy adjustments, new competing projects emerging in the surrounding area, sudden changes in the macroeconomic situation, etc.), real estate company staff can promptly adjust relevant data or scenario parameters in the system.

[0232] The system re-simulates and analyzes scenarios based on new data and parameters, and quickly generates new decision-making suggestions and strategy adjustment plans. For example, if land costs increase, the system will re-evaluate the financial feasibility of the project under different scenarios, and may suggest adjusting the project positioning to a higher-end product to increase the selling price, or optimizing the design to reduce development and construction costs; if new competing projects appear in the surrounding area, the system may suggest adjusting sales strategies, such as opening the market earlier, increasing promotion efforts, or highlighting project features for differentiated competition.

[0233] The system also provides a strategy library function to store successful strategy cases of similar projects in the past. When formulating new strategies, you can search for matching cases in the strategy library for reference and learning according to the characteristics of the project. At the same time, you can also include the strategy plan of the current project into the strategy library, continuously enriching and improving the company's strategy resource library, and providing experience reference for subsequent projects.

[0234] Through the above system operation process, real estate companies can fully consider various uncertainties in the process of land investment decision-making, comprehensively evaluate the investment value and risks of the project, formulate scientific and reasonable investment strategies, and adjust strategies in time according to market changes, thereby improving the accuracy and flexibility of land investment decisions and enhancing the company's competitiveness and risk resistance in the real estate market.

[0235] 2. System Process and Data Interaction

[0236] The system first starts the urban data collection and integration module to collect and integrate geographic information system (GIS) data, urban planning data, and economic and population data, and stores these data in the system database for use by other modules.

[0237] The land project evaluation module obtains relevant data from the database and conducts location analysis, supporting analysis, cost estimation and financial indicator estimation for the land project. Among them, the real-time dynamic adjustment module monitors the planning change information in real time, and if there is any change, it will adjust the cost data in time and feedback it to the cost estimation submodule.

[0238] The scenario planning module sets up a variety of scenario plans based on economic and demographic data trends, policy research and other information, and then uses the results of the land project evaluation module to perform scenario simulation and analysis, and output project evaluation reports under different scenarios.

[0239] The decision support and strategy formulation module evaluates the investment decision of the land project based on the scenario simulation results and the company's internal data, and formulates corresponding strategy adjustment plans. During the project development process, the above process is continuously circulated, and data is updated and strategies are adjusted according to actual conditions to ensure the scientific nature and dynamic adaptability of project decisions.

[0240] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A dynamic city model system based on scenario planning, characterized by: It includes urban data collection and integration module, land project assessment module, scenario planning module and decision support and strategy formulation module; The urban data collection and integration module is used to obtain the city's geospatial data, collect various planning documents prepared by the urban planning department, and collect macroeconomic data of the city and region; The land project evaluation module includes location analysis submodule, supporting analysis submodule, market and customer research submodule, scheme design submodule, cost estimation submodule, cost analysis and monitoring, financial indicator estimation submodule and real-time dynamic adjustment module; The real-time dynamic adjustment module establishes a data sharing interface with the urban planning department to obtain the official urban planning adjustment information in real time, establishes an information monitoring channel, extracts key planning change event information, divides planning change events into facility addition, facility change, and facility removal, and constructs a cost adjustment coefficient model. The basic cost in the absence of planning changes is C0. For facility addition events, the cost adjustment coefficient is set to α, and the calculation formula is: α=f1(S,D,I) Among them, S represents the scale index of the new facilities, D represents the distance between the new facilities and the land project, I represents the overall development level or influence index of the region, and f1 is a functional relationship determined based on historical data and expert experience, which is fitted by multiple linear regression analysis and neural network methods. For facility change events, let the cost adjustment coefficient be β, and its calculation formula is: β=f2(ΔS,ΔF,R) Among them, ΔS represents the difference between the scale of the facility after the change and the original scale, ΔF represents the quantitative index of the change of the facility function, R represents the elasticity coefficient of the regional real estate market, and f2 is the functional relationship determined according to the characteristics of the facility change and market data. For facility demolition events, let the cost adjustment coefficient be γ, and its calculation formula is: γ=f3(T,U,P) Among them, T represents the type of demolition facilities, U represents the original service scope and influence index of the demolition facilities, P represents the adjustment direction of land use planning in the area where the land project is located, and f3 is a functional relationship determined according to the characteristics of the demolition facilities and the regional planning situation. According to the cost adjustment coefficient model, the adjustment range of land project cost after planning changes is calculated. For new facility events, the calculation formula for the adjusted cost C1 is: C1=C0×(1+α) For facility change events, the adjusted cost C2 is calculated as follows: C2=C0×(1+β) For facility removal events, the adjusted cost C3 is calculated as follows: C3=C0×(1-γ); The scenario planning module is used to set scenarios with different variable combinations and compare and analyze the simulation results; The decision support and strategy formulation module is used to enable real estate company staff to adjust relevant data or scenario parameters in the system in a timely manner based on the results of scenario simulation and analysis, re-simulate and analyze the scenario, and quickly generate new decision suggestions and strategy adjustment plans.

2. A dynamic city model system based on scenario planning according to claim 1, characterized in that: The urban data collection and integration module includes a geographic information system data access function for obtaining geospatial data from professional geographic information databases or relevant surveying and mapping departments; Urban planning data import function, used to collect various planning documents prepared by urban planning departments; The economic, population and industrial data collection function is used to collect macroeconomic data, population data and industrial data for cities and regions.

3. The dynamic city model system based on scenario planning according to claim 1, characterized in that: The location analysis submodule determines the evaluation factors and weights by collecting basic geographic information, traffic-related data, surrounding supporting facilities data, regional economic data and population data of the land project, and uses gravity model analysis to evaluate and grade the location of the land project.

4. The dynamic city model system based on scenario planning according to claim 1, characterized in that: The supporting analysis submodule evaluates the completeness of public supporting facilities around land projects based on urban planning data and field survey data through data collection and organization, buffer zone analysis and accessibility analysis, and predicts the impact of future changes in supporting facilities on land projects.

5. The dynamic city model system based on scenario planning according to claim 1, characterized in that: The cost estimation submodule calculates the land acquisition cost, development and construction cost, and operation and management cost based on the basic information of the land project, market data, and real-time dynamic adjustment module information through project pre-preparation, data collection and recording, earned value calculation, cost analysis and monitoring, and cost forecasting and adjustment, and adjusts the cost estimate in a timely manner when there are new plans around the land.

6. The dynamic city model system based on scenario planning according to claim 1, characterized in that: The financial indicator calculation submodule calculates profitability indicators, debt repayment indicators, operating capacity indicators and development capacity indicators according to specific financial data and analysis purposes to evaluate project profitability and investment value.

7. The dynamic city model system based on scenario planning according to claim 1, characterized in that: The real-time dynamic adjustment module monitors the land surrounding planning change information in real time, builds an event classification system, determines direct cost influencing factors, establishes a cost adjustment model, and feeds back the adjusted cost data to the cost calculation submodule.

8. The dynamic city model system based on scenario planning according to claim 1, characterized in that: The scenario planning module sets multiple scenarios based on the macro-environment of urban development, policy trends, and market trend uncertainty factors, combines the results of the land project evaluation module with the scenario setting parameters, conducts scenario simulation and analysis, and outputs project evaluation reports under different scenarios.

9. The dynamic city model system based on scenario planning according to claim 1, characterized in that: The decision support and strategy formulation module determines the decision objectives, sets evaluation criteria and weights based on scenario simulation results and internal company data, uses multi-criteria decision analysis methods to conduct decision evaluation, generates decision recommendation reports, and formulates corresponding strategy adjustment plans.

10. The dynamic city model system based on scenario planning according to claim 1, characterized in that: There is data interaction between the modules in the system. The urban data collection and integration module stores the collected data in the system database for other modules to call. The land project evaluation module obtains data from the database for analysis. The real-time dynamic adjustment module feeds back the adjusted data to the cost estimation submodule. The scenario planning module uses the results of the land project evaluation module for simulation analysis. The decision support and strategy formulation module performs decision evaluation and strategy formulation based on the scenario simulation results.

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