Real estate information intelligent management method and system

Abstract

The invention provides a real estate information intelligent management method, and relates to the technical field of real estate management. The method comprises the following steps: respectively acquiring geographical location information, usable area information and use cost information of a plurality of to-be-selected real estate; obtaining population information and traffic information of each to-be-selected real estate, and determining a traffic convenience coefficient; obtaining the number of residents and the use area information of the real estate to be selected, and determining a use convenience coefficient; and determining a screening coefficient of each real estate to be selected according to the traffic convenience coefficient, the use convenience coefficient and the use cost information, and generating a real estate screening management report. According to the method and the device, when the screening coefficient of the real estate is determined, multi-aspect evaluation can be carried out from the traffic convenience condition, the use convenience condition and the use cost condition, the screening coefficient of the real estate is determined, the screening management report is generated, the method and the device do not depend on manpower, the screening accuracy and comprehensiveness are improved, and the efficiency of real estate information management is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of real estate management, and particularly to an intelligent management method for real estate information. Background Art

[0002] CN119151733A discloses an intelligent real estate mobile settlement system and method, which relates to the technical field of real estate registration. It includes a data collection module for collecting user preference information; an intelligent recommendation module for recommending relevant real estate information according to the user preference information collected by the data collection module; an evaluation module for surveying real estate according to the information of the data collection module, and evaluating the value and potential risks of real estate. It can recommend real estate information in combination with the needs and characteristics of users. Personalized recommendation can improve user satisfaction and application stickiness, increase the possibility of real estate transactions, optimize the user experience, and reduce search time. It can also provide accurate real estate data on the mobile side to help users make more informed decisions and assist users in quickly understanding various types of information for logging in to real estate on the mobile side.

[0003] CN119205179A discloses an artificial intelligence-based real estate supervision method and system. The method includes: data collection, data preprocessing, real estate data balancing, constructing a real estate property right risk assessment model, and real estate supervision. This invention belongs to the technical field of real estate management, specifically referring to an artificial intelligence-based real estate supervision method and system. This solution screens out favorable neighbors to construct an adaptive neighborhood set according to the included angle between real estate data, introduces a similarity measure to calculate the quantity of synthetic data and synthesize data, detects the quality based on the classification confidence of the synthetic data, constructs a real estate data balance set according to the high-quality synthetic data; designs a dynamic frequency factor to calculate the frequency-adjusted cyclic learning rate, introduces a dynamic clipping threshold for gradient norm constraint, updates the parameters of the deep Q network, constructs a real estate property right risk assessment model, adapts to real-time requirements, and ensures that different types of real estate can be equally and effectively supervised.

[0004] CN119205286A relates to the field of lease management technology, specifically to a real estate lease management system. The system includes a contract and regulation verification module, a resource allocation and optimization module, a credit risk analysis module, and an event management and decision-making module. Based on the lease contract text information, it identifies the rent amount and payment cycle. This invention improves the inspection speed and accuracy of contract compliance by automatically reviewing the key financial terms in the contract and comparing them with regulatory standards. The process of automatic identification and comparison reduces the necessity of relying on manual operations, thereby reducing management errors and costs. Through optimized resource and time management, it effectively arranges and adjusts the key links of the lease cycle, thus significantly improving the operation efficiency. The analysis of tenant credit data and credit risk prediction makes risk management more precise, reducing the possibility of overdue and default. Automatically responding to key lease events and adjusting management decisions accordingly greatly enhances the flexibility and responsiveness of management.

[0005] Therefore, according to related technologies, the information of real estate can be managed informatization, but there is a lack of effective means for the intelligent screening of real estate, and it is impossible to accurately screen out real estate and provide a screening management report.

[0006] The information disclosed in the background art section of this application is only intended to deepen the understanding of the general background art of this application, and should not be regarded as an admission or any form of implication that this information constitutes the prior art known to those skilled in the art. Summary of the Invention

[0007] The present invention provides an intelligent management method for real estate information, which can solve the technical problem that it is difficult to accurately screen real estate in related technologies.

[0008] According to the first aspect of the present invention, an intelligent management method for real estate information is provided, including:

[0009] Respectively obtain the geographical location information, usable area information, and usage cost information of multiple candidate real estates;

[0010] According to the geographical location information, determine the population quantity information entering the preset range around each candidate real estate in multiple time periods on multiple historical dates;

[0011] Obtain the traffic information of each candidate real estate;

[0012] According to the traffic information, the population quantity information, and the geographical location information, determine the traffic convenience coefficient of each candidate real estate;

[0013] Determine the number of occupants;

[0014] According to the number of occupants and the usable area information of the candidate real estate, determine the usage convenience coefficient of each candidate real estate;

[0015] Determine the screening coefficients of each candidate real estate according to the traffic convenience coefficient, the usage convenience coefficient, and the usage cost information;

[0016] Generate a real estate screening management report according to the screening coefficients of each candidate real estate.

[0017] According to the second aspect of the present invention, there is provided an intelligent management system for real estate information, including:

[0018] A real estate information module that respectively obtains the geographical location information, the usable area information, and the usage cost information of multiple candidate real estates;

[0019] A population quantity information module that determines the population quantity information within a preset range around each candidate real estate during multiple time periods on multiple historical dates according to the geographical location information;

[0020] A traffic information module that obtains the traffic information of each candidate real estate;

[0021] A traffic convenience coefficient module that determines the traffic convenience coefficients of each candidate real estate according to the traffic information, the population quantity information, and the geographical location information;

[0022] An occupancy number module that determines the occupancy number;

[0023] A usage convenience coefficient module that determines the usage convenience coefficients of each candidate real estate according to the occupancy number and the usable area information of the candidate real estate;

[0024] A screening coefficient module that determines the screening coefficients of each candidate real estate according to the traffic convenience coefficient, the usage convenience coefficient, and the usage cost information;

[0025] A management report module that generates a real estate screening management report according to the screening coefficients of each candidate real estate.

[0026] By adopting the above technical solutions, the present invention can achieve the following technical effects:

[0027] According to the present invention, the geographical location information, usable area information, and usage cost information of multiple candidate real estates can be obtained respectively, so as to obtain the population quantity information and the traffic information of each candidate real estate, and then determine the traffic convenience coefficient. Obtain the number of occupants and determine the usage convenience coefficient. Determine the screening coefficient of each candidate real estate, and then generate a real estate screening management report. The real estate can be comprehensively evaluated from the aspects of traffic convenience, usage convenience, and usage cost of the candidate real estate to generate a screening management report, improving the accuracy and comprehensiveness of real estate screening, without relying on manual labor, and improving the efficiency of real estate information management. Further, the geographical location information, usable area information, and usage cost information of multiple candidate real estates can be obtained, and the population quantity information within a preset range around each candidate real estate in multiple time periods on multiple historical dates can be determined. When determining the population quantity information, the preset range can be determined according to the service range of the signal tower, and the population quantity information within the preset range can be determined according to the mobile phone signal positioning, improving the accuracy and convenience of determining the population quantity information and providing basic data for determining the screening coefficient of the candidate real estate. Based on the population quantity information, a population quantity sequence can be obtained, and then the average number of people entering during the peak period can be determined. According to the number of various public transportation stations, the transportation capacity of public transportation vehicles, the average width of roads, the number of parking spaces, and the number of charging piles, a weighted sum is obtained to determine the convenience degree of entering the candidate real estate and the convenience degree of staying at the candidate real estate, so as to determine the traffic convenience coefficient of each candidate real estate. The traffic convenience coefficient can accurately describe the traffic convenience degree of the candidate real estate, improving the accuracy, objectivity, and comprehensiveness of determining the traffic convenience degree of the candidate real estate. When determining the usage convenience coefficient, based on the number of occupants and the usable area information of the candidate real estate, the per capita usable area of each candidate real estate can be determined, and then the usage convenience coefficient of each candidate real estate can be determined. The usage convenience coefficient can accurately describe the usage convenience degree of the candidate real estate, improving the accuracy and objectivity of the usage convenience coefficient. When determining the screening coefficient, a virtual coordinate system can be established according to the traffic convenience coefficient, usage convenience coefficient, and usage cost information, and a virtual three-dimensional surface equation and the virtual position information of the candidate real estate can be determined. The screening range is determined according to the space enclosed by the first preset upper limit, the second preset upper limit, and the third preset lower limit in the virtual coordinate system. Based on the virtual position information of the candidate real estate, the total convenience of the candidate real estate is determined, so as to determine the cost performance of the candidate real estate. And according to the gradient at each position of the virtual three-dimensional surface equation, the change rate of the cost performance of each candidate real estate is determined, so as to determine the possibility of each candidate real estate being screened as the optimal candidate real estate, and then obtain the screening coefficient of the candidate real estate. The candidate real estate can be comprehensively screened through the possibility of being screened as the optimal candidate real estate and the cost performance, improving the accuracy and objectivity of determining the screening coefficient.

[0028] It should be understood that the above general description and the following detailed description are merely exemplary and explanatory, and do not limit the present invention. Other features and aspects of the present invention will become clearer based on the following detailed description of exemplary embodiments with reference to the accompanying drawings. Description of the Drawings

[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other embodiments can be obtained based on these drawings.

[0030] Figure 1 Exemplarily shown is a schematic flowchart of an intelligent management method for real estate information according to an embodiment of the present invention;

[0031] Figure 2 Exemplarily shown is a block diagram of an intelligent management system for real estate information according to an embodiment of the present invention. Detailed Embodiments

[0032] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0033] The following will detail the technical solutions of the present invention with specific embodiments. These several specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments.

[0034] Figure 1 Exemplarily shown is a schematic flowchart of an intelligent management method for real estate information according to an embodiment of the present invention, and the method includes:

[0035] Step S101, respectively obtain the geographical location information, usable area information, and usage cost information of multiple candidate real estates;

[0036] Step S102, according to the geographical location information, determine the population quantity information entering the preset range around each candidate real estate in multiple time periods among multiple historical dates;

[0037] Step S103, obtain the traffic information of each candidate real estate;

[0038] Step S104: Determine the transportation convenience coefficient of each candidate real estate according to the traffic information, the population quantity information, and the geographical location information.

[0039] Step S105: Determine the number of occupants.

[0040] Step S106: Determine the usage convenience coefficient of each candidate real estate according to the number of occupants and the usable area information of the candidate real estate.

[0041] Step S107: Determine the screening coefficient of each candidate real estate according to the transportation convenience coefficient, the usage convenience coefficient, and the usage cost information.

[0042] Step S108: Generate a real estate screening management report according to the screening coefficients of each candidate real estate.

[0043] An intelligent management method for real estate information according to an embodiment of the present invention can respectively obtain the geographical location information, the usable area information, and the usage cost information of multiple candidate real estates, thereby obtaining the population quantity information and the traffic information of each candidate real estate, and then determining the transportation convenience coefficient. Obtain the number of occupants and determine the usage convenience coefficient. Determine the screening coefficients of each candidate real estate, and then generate a real estate screening management report. It can evaluate the real estate in multiple aspects from the transportation convenience, usage convenience, and usage cost of the candidate real estate, generate a screening management report, improve the accuracy and comprehensiveness of real estate screening, and does not rely on manual work, improving the efficiency of real estate information management.

[0044] According to an embodiment of the present invention, in step S101, the geographical location information, the usable area information, and the usage cost information of multiple candidate real estates are respectively obtained. For example, when renting a house, multiple rentable houses can be screened and compared to select a suitable house. The geographical location information can be determined by using the GPS global positioning system. Since the number of people using the real estate and the area of the real estate need to be reasonably matched, for example, the per capita usable area is at least 5 square meters but does not exceed 20 square meters, the usable area information can be area information such as the total area of the candidate real estate, the total usable area, etc. The cost information can include cost expenses such as the rent, water and electricity bills, and property management fees of the candidate real estate.

[0045] According to an embodiment of the present invention, in step S102, according to the geographical location information, the population quantity information entering the preset range around each candidate real estate is determined for multiple time periods in multiple historical dates. The multiple historical periods can be determined as the previous month, and the duration of each time period can be determined as two hours. The present invention does not limit this. Since within a time period, the population within the preset range around the candidate real estate may leave the preset range, the population quantity information is the net population entry quantity within the preset range around the candidate real estate for a time period, which can be obtained by subtracting the population quantity within the preset range around the candidate real estate at the start time of a time period from the population quantity within the preset range around the candidate real estate at the end time of a time period. Since the preset range needs to include multiple public transportation stations and the preset range is larger than the range of the candidate real estate, it is difficult to count the population quantity by setting turnstiles. Therefore, the population quantity information within the preset range around the candidate real estate can be determined by the positioning of the mobile phone signals carried by people. For example, if a candidate real estate is served by a certain signal tower, the service range of this signal tower is the preset range, and the population quantity information can be determined according to the number of mobile phones located by the mobile phone signals using the same signal tower's service as the candidate real estate within a certain time period. The present invention does not limit this.

[0046] In this way, the geographical location information, usable area information, and usage cost information of multiple candidate real estates can be obtained, and the population quantity information entering the preset range around each candidate real estate can be determined for multiple time periods in multiple historical dates. When determining the population quantity information, the preset range can be determined by the service range of the signal tower, and the population quantity information within the preset range can be determined according to the mobile phone signal positioning, which improves the accuracy and convenience of determining the population quantity information and provides basic data for determining the screening coefficient of the candidate real estate.

[0047] According to an embodiment of the present invention, in step S103, the traffic information of each candidate real estate is obtained. The traffic information can be traffic information such as the number of public transportation stations, types of stations, means of transportation for population travel, and width of the passing roads.

[0048] According to an embodiment of the present invention, in step S104, according to the traffic information, the population quantity information, and the geographical location information, determining the traffic convenience coefficients of each candidate real estate includes: determining the number of various public transportation stations within a preset range around the candidate real estate according to the geographical location information; determining the average road width within a preset range around the candidate real estate according to the geographical location information; determining the number of parking spaces within a preset range around the candidate real estate according to the geographical location information; determining the number of charging piles within a preset range around the candidate real estate according to the geographical location information; sorting the population quantity information corresponding to multiple time periods in multiple historical dates to obtain a population quantity sequence; in the population quantity sequence, obtaining multiple population quantity information before the first preset quantity and determining the average number of people entering during the peak period; and determining the traffic convenience coefficients of each candidate real estate according to the average number of people entering during the peak period, the number of various public transportation stations, the average road width, the number of parking spaces, and the number of charging piles.

[0049] According to an embodiment of the present invention, based on the geographical location information, determine the total number of various public transportation stations such as subway stations, bus stations, and tram stations within a preset range around the candidate real estate. When determining the average road width, sampling points can be set at intervals on each road within the preset range around the candidate real estate, and the average value of the road widths at the positions of each sampling point is calculated as the average road width within the preset range around the candidate real estate. The convenience degree of entering the candidate real estate can be evaluated according to the number of various public transportation stations and the average road width within the preset range around the candidate real estate. Based on the geographical location information, determine the number of parking spaces and the number of charging piles within the preset range around the candidate real estate. Since the charging piles are located beside the parking spaces, there is a certain proportional relationship between the number of parking spaces and the number of charging piles, and the parking convenience degree after arriving at the candidate real estate can be evaluated. Sort the population quantity information corresponding to multiple time periods in multiple historical dates to obtain a population quantity sequence. For example, when sorting the population quantity information for each hour of the previous month, the population quantity information between 6:00 and 7:00 in the morning on a certain day is relatively small because it is not yet the working time, and the population quantity information between 8:00 and 9:00 is relatively large because it is the working time for most people. Therefore, the sorting of the population quantity information in the time period from 8:00 to 9:00 on that day will be before the sorting of the population quantity information in the time period from 6:00 to 7:00 on that day. Sort the population quantity information for each hour of the previous month to obtain the population quantity sequence. The present invention does not limit this. In the population quantity sequence, the time periods ranked before the first preset quantity have a relatively large number of people entering, and can be determined as the peak population entry periods. For example, if the first preset quantity is 10, then the time periods ranked before the 10th in the population quantity sequence are the peak population entry periods, and the present invention does not limit this. Average the population quantity information in the peak population entry periods to obtain the average number of people entering during the peak period. For example, if the population quantity information in the peak population entry periods for the previous three days is 1300, 1200, and 1100 respectively, then the average number of people entering during the peak period for these three days is 1200.

[0050] According to an embodiment of the present invention, based on the average number of people entering during the peak period, the number of various public transportation stations, the average road width, the number of parking spaces, and the number of charging piles, determine the traffic convenience coefficient of each candidate real estate, including: determining the traffic convenience coefficient T of the i-th candidate real estate according to formula (1) i ,

[0051]

[0052] where TN j is the number of inbound train trips of the j-th public transportation station within a preset time period, N tr,jis the unit transport capacity of the public transport vehicle corresponding to the j-th public transport stop, n i is the number of public transport stops within the preset range around the i-th candidate real estate, θ i is the preset road transport capacity coefficient around the i-th candidate real estate, W i is the average road width within the preset range around the i-th candidate real estate, N car is the preset average number of passengers per vehicle, n pa,i is the number of parking spaces within the preset range around the i-th candidate real estate, n pi,i is the number of charging piles within the preset range around the i-th candidate real estate, γ ep is the proportion of electric vehicles in the total number of vehicles, N p,ave,i is the average number of people entering during the peak period within the preset range around the i-th candidate real estate, w 1 and w 2 are preset weights.

[0053] According to an embodiment of the present invention, in formula (1), N tr,j TN j is the product of the number of incoming train trips at the j-th public transport stop within the preset time period and the unit transport capacity of the public transport vehicle corresponding to the j-th public transport stop, and can be used as the total transport capacity of the public transport vehicle corresponding to the j-th public transport stop within the preset time period. For example, the product of the number of incoming train trips at the j-th subway stop within the preset time period and the unit transport capacity of the subway is the total transport capacity of the subway at the j-th subway stop within the preset time period. Therefore, can represent the sum of the transport capacities of the public transport vehicles corresponding to each stop such as subways, trams, and buses within the preset time period, that is, the total transport capacity of the public transport vehicles within the preset range around the i-th candidate real estate within the preset time period. θ i W i N car is the product of the preset road transport capacity coefficient around the i-th candidate real estate, the average road width within the preset range around the i-th candidate real estate, and the preset average number of passengers per vehicle, and can be used as the total transport capacity of the roads within the preset range around the candidate real estate. θ i is the preset road transport capacity coefficient around the i-th candidate real estate, and the transport capacity coefficient can be an empirical coefficient related to the average speed of the vehicle flow on the roads around the candidate real estate. N car is the preset average number of passengers per vehicle. For example, after statistics, the preset average number of passengers per vehicle is 2. Therefore, can represent the weighted sum value of the total transport capacity of the public transport vehicles and the total transport capacity of the roads within the preset range around the i-th candidate real estate within the preset time period, and can be used as the convenience degree of entering the i-th candidate real estate.

[0054] According to an embodiment of the present invention, in formula (1), the proportion of electric vehicles in the total number of vehicles, for example, the proportion of the number of owned electric vehicles in the total number of owned vehicles, can be used as the ratio relationship between charging piles and parking spaces. Therefore, Dividing the number of charging piles within a preset range around the i-th candidate real estate by the proportion of electric vehicles in the total number of vehicles can be used as the matching degree between the number of charging piles and parking spaces for electric vehicles within a preset range around the i-th candidate real estate. n pa,i The number of parking spaces within a preset range around the i-th candidate real estate can be used as the convenience degree of vehicle parking within a preset range around the i-th candidate real estate. By weighted summing the matching degree between the number of charging piles and parking spaces for electric vehicles within a preset range around the i-th candidate real estate and the convenience degree of vehicle parking within a preset range around the i-th candidate real estate, the convenience degree of staying at the i-th candidate real estate can be obtained N p,ave,i The average number of people entering during the peak period within a preset range around the i-th candidate real estate. Since the more the average number of people entering during the peak period, the more congested the road and the less convenient the traffic, therefore, The ratio of the weighted sum value of the total transport capacity of public transportation tools and the total transport capacity of roads within a preset range around the i-th candidate real estate within a preset time period to the weighted sum value of the convenience degree of parking and charging electric vehicles within a preset range around the i-th candidate real estate and the convenience degree of vehicle parking within a preset range around the i-th candidate real estate, and the average number of people entering during the peak period within a preset range around the i-th candidate real estate can be used as the traffic convenience coefficient of the i-th candidate real estate. The higher the traffic convenience coefficient, the higher the traffic convenience degree of the i-th candidate real estate. Furthermore, the traffic convenience coefficients of each candidate real estate can be obtained.

[0055] In this way, based on the population quantity information, a population quantity sequence can be obtained, and then the average number of people entering during the peak period can be determined. According to the number of various public transportation stations, the transport capacity of public transportation tools, the average width of roads, the number of parking spaces, and the number of charging piles, a weighted sum is obtained to get the convenience degree of entering the candidate real estate and the convenience degree of staying at the candidate real estate, thereby determining the traffic convenience coefficients of each candidate real estate. The traffic convenience coefficient can accurately describe the traffic convenience degree of the candidate real estate, improving the accuracy, objectivity, and comprehensiveness of the determination of the traffic convenience degree of the candidate real estate.

[0056] According to an embodiment of the present invention, in step S105, determine the number of occupants. Determine the total number of people entering and staying at the candidate real estate.

[0057] According to an embodiment of the present invention, in step S106, according to the number of occupants and the usable area information of the candidate immovables, determining the usability convenience coefficient of each candidate immovable, including: determining the usability convenience coefficient Ui of the i-th candidate immovable according to formula (2) i ,

[0058]

[0059] wherein, A i is the usable area information of the i-th candidate immovable, and n se is the number of occupants.

[0060] According to an embodiment of the present invention can represent the ratio of the usable area information of the i-th candidate immovable to the number of occupants, that is, the per capita usable area of the i-th candidate immovable, and can be used as the usability convenience coefficient of the i-th candidate immovable. The larger the usability convenience coefficient, the larger the per capita usable area of the candidate immovable, and the more convenient the use of the immovable.

[0061] In this way, based on the number of occupants and the usable area information of the candidate immovables, the per capita usable area of each candidate immovable can be determined, and then the usability convenience coefficient of each candidate immovable can be determined. The usability convenience coefficient can accurately describe the usability convenience degree of the candidate immovables, improving the accuracy and objectivity of the usability convenience coefficient.

[0062] According to an embodiment of the present invention, in step S107, according to the traffic convenience coefficient, the usability convenience coefficient and the usage cost information, determining the screening coefficient of each candidate immovable, including: establishing a virtual coordinate system, wherein the X-axis of the virtual coordinate system represents the value of the traffic convenience coefficient, the Y-axis of the virtual coordinate system represents the value of the usability convenience coefficient, and the Z-axis of the virtual coordinate system represents the value of the usage cost information; determining the virtual position information of each candidate immovable in the virtual coordinate system according to the traffic convenience coefficient, the usability convenience coefficient and the usage cost information of each candidate immovable; performing fitting according to the virtual position information to obtain a virtual three-dimensional surface equation in the virtual coordinate system; setting a first preset lower limit of the traffic convenience coefficient, a second preset lower limit of the usability convenience coefficient and a third preset upper limit of the usage cost information; determining the screening coefficient of each candidate immovable according to the first preset lower limit, the second preset lower limit, the third preset upper limit and the virtual three-dimensional surface equation.

[0063] According to an embodiment of the present invention, a virtual three-dimensional coordinate system is established. The X-axis represents the value of the traffic convenience coefficient, the Y-axis represents the value of the usage convenience coefficient, and the Z-axis represents the value of the usage cost information. According to the traffic convenience coefficient, the usage convenience coefficient, and the value of the cost information of each candidate real estate, the coordinates of each candidate real estate in three dimensions are determined, which are the virtual position information of each candidate real estate in the virtual coordinate system. Since a surface can be obtained by fitting multiple scattered points in space, the above virtual position information can be fitted to obtain the virtual three-dimensional surface equation of all candidate real estates in the virtual coordinate system. Since when at least one of the traffic convenience coefficient and the usage convenience coefficient is too low, the overall convenience of the candidate real estate is too low and the candidate real estate is not suitable for use, a first preset lower limit of the traffic convenience coefficient and a second preset lower limit of the usage convenience coefficient can be set. When the usage cost information is too high, the usage cost of the candidate real estate is too high and it is not suitable for use. Therefore, a third preset upper limit of the usage cost information is set. Since in a three-dimensional coordinate system, the lower limit or upper limit of one dimension is a plane in the coordinate system, the three planes respectively corresponding to the first preset lower limit of the traffic convenience coefficient, the second preset lower limit of the usage convenience coefficient, and the third preset upper limit of the usage cost information can enclose a space in the above virtual coordinate system.

[0064] According to an embodiment of the present invention, according to the first preset lower limit, the second preset lower limit, the third preset upper limit, and the virtual three-dimensional surface equation, the screening coefficient of each candidate real estate is determined, including: determining the screening range in the virtual coordinate system according to the first preset lower limit, the second preset lower limit, and the third preset upper limit; determining the screening coefficient of the candidate real estate whose virtual position information is outside the screening range as 0; and determining the screening coefficient of the candidate real estate whose virtual position information is within the screening range according to the virtual three-dimensional surface equation. The space in the virtual coordinate system determined according to the first preset lower limit, the second preset lower limit, and the third preset upper limit is the screening range. For the candidate real estate whose virtual position information is outside the above space, at least one of the traffic convenience coefficient and the usage convenience coefficient is relatively low, or the usage cost information is relatively high, and it is not suitable for use, and the corresponding screening coefficient is 0.

[0065] According to an embodiment of the present invention, to determine the screening coefficient of the candidate real estate whose virtual position information is within the screening range according to the virtual three-dimensional surface equation, it includes: determining the screening coefficient Sk of the k-th candidate real estate whose virtual position information is within the screening range according to formula (3) k ,

[0066]

[0067] where, x kis the X-axis coordinate of the virtual position information of the k-th candidate real estate within the screening range, y k is the Y-axis coordinate of the virtual position information of the k-th candidate real estate within the screening range, z(x k ,y k ) is the Z-axis coordinate of the point with the planar position (x k ,y k ) in the virtual three-dimensional surface equation, is the direction vector in the X-axis direction of the virtual coordinate system, is the direction vector in the Y-axis direction of the virtual coordinate system, is the gradient of the virtual three-dimensional surface equation at the position (x k ,y k ), is 's modulus, and k is a positive integer.

[0068] According to an embodiment of the present invention, in formula (3), x k is the X-axis coordinate of the virtual position information of the k-th candidate real estate within the screening range, that is, the transportation convenience coefficient of the candidate real estate, y k is the Y-axis coordinate of the virtual position information of the k-th candidate real estate within the screening range, that is, the usage convenience coefficient of the candidate real estate. Therefore, can represent the total convenience of the k-th candidate real estate in the said space. z(x k ,y k ) is the Z-axis coordinate of the point with the planar position (x k ,y k ) in the virtual three-dimensional surface equation, that is, the usage cost information of the candidate real estate. Therefore, can represent the ratio of the total convenience of the k-th candidate real estate in the said space to the usage cost information, and can be used as the usage cost performance of the k-th candidate real estate. The higher the cost performance, the more suitable the candidate real estate is for use. In formula (3), is the gradient of the virtual three-dimensional surface equation at the position (x k ,y k ), and the gradient is the direction vector of the point with the largest rate of change in all directions of the surface of the virtual three-dimensional surface equation of the candidate real estate at the position (x k ,y k ). Therefore, the modulus of the above gradient can be used as the virtual three-dimensional surface equation at (x k ,y k)The rate of change at the position, that is, the rate of change of the cost performance of the k-th candidate real estate. The smaller the rate of change of the cost performance, the more stable the cost performance of the candidate real estate, the more suitable it is for use, the smaller the possibility of screening out candidate real estates with low cost performance, and the greater the possibility of being screened as the optimal candidate real estate. Therefore, It can be used as the possibility that the k-th candidate real estate is screened as the optimal candidate real estate.

[0069] In this way, a virtual coordinate system can be established based on the transportation convenience coefficient, the usage convenience coefficient, and the usage cost information, and the virtual three-dimensional surface equation and the virtual position information of the candidate real estate can be determined. The screening range is determined according to the space enclosed by the first preset upper limit, the second preset upper limit, and the third preset lower limit in the virtual coordinate system. Based on the virtual position information of the candidate real estate, the total convenience of the candidate real estate is determined, so as to determine the cost performance of the candidate real estate. And according to the gradient at each position of the virtual three-dimensional surface equation, the rate of change of the cost performance of each candidate real estate is determined, so as to determine the possibility that each candidate real estate is screened as the optimal candidate real estate, and then the screening coefficient of the candidate real estate is obtained. The candidate real estate can be comprehensively screened by the possibility of being screened as the optimal candidate real estate and the cost performance, which improves the accuracy and objectivity of the determination of the screening coefficient.

[0070] According to an embodiment of the present invention, in step S108, a real estate screening management report is generated according to the screening coefficients of each candidate real estate. The method further includes: determining the candidate real estate with the highest screening coefficient as the recommended real estate. The real estate screening management report may include information such as the screening coefficient, transportation convenience coefficient, usage convenience coefficient, and usage cost information of the real estate, and may also include multiple information such as the location and cost of the recommended real estate.

[0071] An intelligent management method for real estate information according to an embodiment of the present invention can respectively obtain the geographical location information, usable area information, and usage cost information of multiple candidate real estates, thereby obtaining the population quantity information and the traffic information of each candidate real estate, and then determining the traffic convenience coefficient. Obtain the number of occupants and determine the usage convenience coefficient. Determine the screening coefficients of each candidate real estate, and then generate a real estate screening management report. It is possible to evaluate the real estate in multiple aspects from the traffic convenience, usage convenience, and usage cost of the candidate real estate and generate a screening management report, improving the accuracy and comprehensiveness of real estate screening, and not relying on manual work, thereby improving the efficiency of real estate information management. Further, it is possible to obtain the geographical location information, usable area information, and usage cost information of multiple candidate real estates and determine the population quantity information within a preset range around each candidate real estate during multiple time periods on multiple historical dates. When determining the population quantity information, the preset range can be determined through the service range of the signal tower, and the population quantity information within the preset range can be determined according to mobile phone signal positioning, improving the accuracy and convenience of determining the population quantity information and providing basic data for determining the screening coefficients of candidate real estates. Based on the population quantity information, a population quantity sequence can be obtained, and then the average number of people entering during peak periods can be determined. According to the number of various public transportation stations, the transport capacity of public transportation vehicles, the average width of roads, the number of parking spaces, and the number of charging piles, a weighted sum is obtained to determine the convenience degree of entering the candidate real estate and the convenience degree of staying at the candidate real estate, thereby determining the traffic convenience coefficient of each candidate real estate. The traffic convenience coefficient can accurately describe the traffic convenience degree of the candidate real estate, improving the accuracy, objectivity, and comprehensiveness of determining the traffic convenience degree of the candidate real estate. When determining the usage convenience coefficient, based on the number of occupants and the usable area information of the candidate real estate, the per capita usable area of each candidate real estate can be determined, and then the usage convenience coefficient of each candidate real estate can be determined. The usage convenience coefficient can accurately describe the usage convenience degree of the candidate real estate, improving the accuracy and objectivity of the usage convenience coefficient. When determining the screening coefficient, a virtual coordinate system can be established according to the traffic convenience coefficient, usage convenience coefficient, and usage cost information, and a virtual three-dimensional surface equation and the virtual position information of the candidate real estate can be determined. The screening range is determined according to the space enclosed by the first preset upper limit, the second preset upper limit, and the third preset lower limit in the virtual coordinate system. Based on the virtual position information of the candidate real estate, the total convenience of the candidate real estate is determined, thereby determining the cost performance of the candidate real estate. And according to the gradient at each position of the virtual three-dimensional surface equation, the change rate of the cost performance of each candidate real estate is determined, thereby determining the possibility that each candidate real estate is screened as the optimal candidate real estate, and then obtaining the screening coefficient of the candidate real estate. The screening coefficient can be comprehensively screened through the possibility that the candidate real estate is screened as the optimal candidate real estate and the cost performance, improving the accuracy and objectivity of determining the screening coefficient.

[0072] Figure 2 The block diagram of a clinical detection system for diseased cells based on spectral optical coherence imaging according to an embodiment of the present invention is exemplarily shown. The system includes:

[0073] A real estate information module that respectively obtains the geographical location information, usable area information, and usage cost information of multiple candidate real estates;

[0074] A population quantity information module that determines the population quantity information entering the preset range around each candidate real estate during multiple time periods on multiple historical dates according to the geographical location information;

[0075] A traffic information module that obtains the traffic information of each candidate real estate;

[0076] A traffic convenience coefficient module that determines the traffic convenience coefficient of each candidate real estate according to the traffic information, the population quantity information, and the geographical location information;

[0077] An occupancy number module that determines the occupancy number;

[0078] A usage convenience coefficient module that determines the usage convenience coefficient of each candidate real estate according to the occupancy number and the usable area information of the candidate real estate;

[0079] A screening coefficient module that determines the screening coefficient of each candidate real estate according to the traffic convenience coefficient, the usage convenience coefficient, and the usage cost information;

[0080] A management report module that generates a real estate screening management report according to the screening coefficients of each candidate real estate.

[0081] Those skilled in the art should understand that the embodiments of the present invention described above and shown in the drawings are only examples and do not limit the present invention. The object of the present invention has been completely and effectively achieved. The functions and structural principles of the present invention have been demonstrated and explained in the embodiments. Without departing from the principle, the embodiments of the present invention can have any deformation or modification.

[0082] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for intelligent management of real estate information, characterized in that: include: Respectively obtain geographical location information, usable area information and use cost information of multiple real estates to be selected; According to the geographic location information, determining the number of people entering a preset range around each of the selected real estates during multiple time periods on multiple historical dates; Obtaining traffic information for each real estate to be selected; Determining the traffic convenience coefficient of each real estate to be selected according to the traffic information, the population information and the geographical location information; Determine the number of people who will be accommodated; Determine the use convenience coefficient of each real estate to be selected according to the number of residents and the use area information of the real estate to be selected; Determining the screening coefficient of each real estate to be selected according to the traffic convenience coefficient, the use convenience coefficient and the use cost information; Generate a real estate screening management report based on the screening coefficient of each real estate to be selected.

2. The method for intelligent management of real estate information according to claim 1, characterized in that: Determining the traffic convenience coefficient of each real estate to be selected according to the traffic information, the population information and the geographical location information includes: Determine the number of various public transportation stations within a preset range around the real estate to be selected based on the geographic location information; Determine the average width of roads within a preset range around the selected real estate according to the geographical location information; Determine the number of parking spaces within a preset range around the selected real estate according to the geographic location information; Determine the number of charging posts within a preset range around the selected real estate according to the geographic location information; Sort the population quantity information corresponding to multiple time periods in multiple historical dates to obtain a population quantity sequence; In the population quantity sequence, obtain multiple population quantity information before the first preset quantity, and determine the average number of people entering during the peak period; The traffic convenience coefficient of each real estate to be selected is determined based on the average number of people entering during the peak period, the number of the various public transportation stations, the average road width, the number of parking spaces and the number of charging piles.

3. The method for intelligent management of real estate information according to claim 2, characterized in that: The traffic convenience coefficient of each real estate to be selected is determined based on the average number of people entering during the peak period, the number of the various public transportation stations, the average road width, the number of parking spaces, and the number of charging piles, including: According to the formula Determine the transportation convenience coefficient T of the i-th real estate to be selected i , where TN j is the number of trains entering the jth public transportation station within the preset time period, N tr,j is the unit capacity of the public transport vehicle corresponding to the jth public transport station, n i is the number of public transportation stations within the preset range around the i-th selected real estate, θ i is the road capacity coefficient around the i-th selected real estate, W i is the average width of the roads within the preset range around the i-th real estate to be selected, N car is the average number of passengers per vehicle, n pa,i is the number of parking spaces within the preset range around the i-th real estate to be selected, n pi,i is the number of charging piles within the preset range around the i-th real estate to be selected, γ ep is the proportion of electric vehicles in the total number of vehicles, N p,ave,i is the average number of people entering during peak hours within the preset range around the i-th real estate to be selected, and w1 and w2 are the preset weights.

4. The method for intelligent management of real estate information according to claim 1, characterized in that: According to the number of residents and the usable area information of the real estate to be selected, the usability coefficient of each real estate to be selected is determined, including: According to the formula Determine the convenience coefficient U of the i-th real estate to be selected i , where A i is the usable area information of the i-th real estate to be selected, n se The number of people staying.

5. The method for intelligent management of real estate information according to claim 1, characterized in that: Determining the screening coefficient of each real estate to be selected according to the traffic convenience coefficient, the use convenience coefficient and the use cost information includes: Establishing a virtual coordinate system, wherein the X-axis of the virtual coordinate system represents the value of the traffic convenience coefficient, the Y-axis of the virtual coordinate system represents the value of the use convenience coefficient, and the Z-axis of the virtual coordinate system represents the value of the use cost information; Determine virtual position information of each real estate to be selected in the virtual coordinate system according to the traffic convenience coefficient, use convenience coefficient and use cost information of each real estate to be selected; Perform fitting according to the virtual position information to obtain a virtual three-dimensional surface equation in a virtual coordinate system; Setting a first preset lower limit of a traffic convenience coefficient, a second preset lower limit of a usage convenience coefficient, and a third preset upper limit of usage cost information; The screening coefficients of the respective real estates to be selected are determined according to the first preset lower limit, the second preset lower limit, the third preset upper limit and the virtual three-dimensional surface equation.

6. The method for intelligent management of real estate information according to claim 5, characterized in that: Determining the screening coefficient of each real estate to be selected according to the first preset lower limit, the second preset lower limit, the third preset upper limit and the virtual three-dimensional surface equation includes: Determine a screening range in a virtual coordinate system according to the first preset lower limit, the second preset lower limit, and the third preset upper limit; Determine the screening coefficient of the real estate to be selected whose virtual location information is outside the screening range as 0; According to the virtual three-dimensional surface equation, the screening coefficients of the selected real estates whose virtual location information is within the screening range are determined.

7. The method for intelligent management of real estate information according to claim 6, characterized in that: Determining the screening coefficient of the real estate to be selected whose virtual location information is within the screening range according to the virtual three-dimensional surface equation includes: According to the formula Determine the screening coefficient S of the kth real estate to be selected whose virtual location information is within the screening range k , where x k is the X-axis coordinate of the virtual location information of the kth real estate to be selected within the screening range, y k is the Y-axis coordinate of the virtual location information of the kth real estate to be selected within the screening range, z(x k ,y k ) is the plane position in the virtual coordinate system (x k ,y k ) in the Z-axis coordinate of the virtual three-dimensional surface equation, is the direction vector of the X-axis in the virtual coordinate system, is the direction vector of the Y axis in the virtual coordinate system, is the virtual three-dimensional surface equation at (x k ,y k ) position, for The modulus of , k is a positive integer.

8. The method for intelligent management of real estate information according to claim 1, characterized in that: The method also includes: determining the candidate real estate with the highest screening coefficient as the recommended real estate.

9. An intelligent real estate information management system, characterized in that: include: The real estate information module obtains the geographical location information, the use area information and the use cost information of multiple real estates to be selected; A population information module, based on the geographic location information, determines population information entering a preset range around each of the selected real estates during multiple time periods on multiple historical dates; Traffic information module, to obtain traffic information of each real estate to be selected; A traffic convenience coefficient module, which determines the traffic convenience coefficient of each real estate to be selected according to the traffic information, the population information and the geographical location information; The occupancy module determines the number of occupants; A convenience coefficient module for determining the convenience coefficient of each real estate to be selected according to the number of residents and the usable area information of the real estate to be selected; A screening coefficient module, which determines the screening coefficient of each real estate to be selected according to the traffic convenience coefficient, the use convenience coefficient and the use cost information; The management report module generates a real estate screening management report based on the screening coefficients of each real estate to be selected.

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