Zoo intelligent scheduling system and method based on multi-source data fusion

Abstract

The invention discloses a zoo intelligent scheduling system and method based on multi-source data fusion, relates to the technical field of intelligent scheduling, and solves the technical problems of low resource allocation efficiency and insufficient tourist satisfaction and animal management scientificity caused by lack of a data-driven automatic matching and scheduling mechanism. Information is acquired in real time through the multi-source data acquisition module, a matching and scheduling scheme is automatically generated after processing and fusion, manual intervention is reduced, potential problems are recognized in advance through data cleaning and abnormal value processing, preventive adjustment is triggered, and the efficiency is improved. On the basis of overlapping analysis of animal active time periods (and high-flow time periods), a core display window is accurately identified, 'invalid display 'is avoided, a scheduling strategy is dynamically adjusted according to overlapping duration, flow is limited in a segmented mode, tourist batches and residence time are controlled, and scientization of display resource configuration, refinement of animal welfare guarantee and intelligentization of tourist experience improvement are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent scheduling, and in particular to a zoo intelligent scheduling system and method based on multi-source data fusion. Background Art

[0002] Existing zoo exhibition area planning and animal display scheduling rely primarily on manual experience, lacking the integrated analysis and scientific matching of multi-source data. For example, the allocation of exhibition areas does not systematically consider the dynamic relationship between animal environmental needs and visitor flow, resulting in some animals experiencing stress reactions due to environmental discomfort, or popular exhibition areas being affected by the concentration of tourists, which affects the viewing experience. At the same time, the scheduling of exhibition durations often adopts a fixed model, without dynamic adjustments based on the active habits of animals and peak visitor flow periods, making it difficult to balance animal welfare with visitor needs. Traditional solutions lack a data-driven automated matching and scheduling mechanism, resulting in inefficient resource allocation, insufficient visitor satisfaction, and insufficient scientific animal management. Summary of the Invention

[0003] In response to the shortcomings of the existing technology, the present invention provides a zoo intelligent scheduling system and method based on multi-source data fusion, which solves the problems of lack of data-driven automated matching and scheduling mechanism, resulting in inefficient resource allocation, insufficient visitor satisfaction and scientific animal management.

[0004] To achieve the above objectives, the present invention is implemented through the following technical solutions: a zoo intelligent scheduling system based on multi-source data fusion, comprising: The display area matching analysis module is used to analyze the fused multi-source data transmitted by the multi-source data processing and fusion module, match the regional environment of the display area with the environmental requirements of the display animals to obtain pre-selected display areas, and judge and screen their repeatability to obtain the area to be analyzed. The area and visitor density of the area to be analyzed are scored and assigned, and the corresponding regional fit is calculated according to the formula. The standard display area is screened based on the maximum regional fit, and the display area matching information is generated and transmitted to the display scheduling analysis module; The display scheduling analysis module is used to analyze the display area matching information, obtain the active time periods of the display animals in the standard display area and the corresponding number of visitors during the time periods, filter out overlapping time periods, and classify the overlapping time periods according to their time periods to obtain the first adjustment time period and the second adjustment time period. Different adjustments are made to the first and second adjustment time periods, the time period lengths are segmented, and the display animals are displayed to generate scheduling display information, which is then transmitted to the intelligent scheduling information display module.

[0005] As a further solution of the present invention, it also includes a multi-source data processing and fusion module and an intelligent scheduling information display module; The multi-source data processing and fusion module is used to clean and pre-process the multi-source data transmitted by the multi-source data acquisition module to obtain pre-processed data, and perform data fusion on the pre-processed data to obtain fused multi-source data; The intelligent scheduling information display module is used to display the acquired scheduling display information to the corresponding management personnel.

[0006] As a further solution of the present invention, the specific manner in which the display area matching analysis module analyzes the fused multi-source data transmitted by the multi-source data processing and fusion module is as follows: Obtain all display areas and label them as i, where i = 1, 2, ..., j, where j represents the number of display areas. Collect regional environmental information and visitor browsing information. Then obtain all displayed animals and label them as a, where a = 1, 2, ..., b, where b represents the type of displayed animal. Obtain the environmental requirements corresponding to displayed animal a and match them with the regional environmental information of display area i. If the two are matched successfully, they will be classified as pre-selected display areas If the two are not matched successfully, no processing will be done. Similarly, all display areas i are matched to obtain the corresponding pre-selected display areas. a ,and a =1, 2, ..., ,in Indicates the number of pre-selected display areas; Then, the pre-selected display area corresponding to all displayed animals a is a Make a repeat judgment, if it exists, the corresponding pre-selected display area a It is recorded as the area to be analyzed. Otherwise, if it does not exist, it will not be processed. At the same time, a secondary analysis will be performed on the pre-selected display areas where there is no sufficient situation.

[0007] As a further solution of the present invention, the specific manner in which the display area matching analysis module generates the display area matching information is as follows: Obtain the area and tourist density corresponding to the area to be analyzed, and score and assign values ​​to them respectively to obtain the corresponding area assignment and tourist density assignment. Then, calculate the corresponding regional fit according to the formula: regional fit = area assignment × first weight + tourist density assignment × second weight; The area with the greatest degree of fit is selected as the standard, which is used as the corresponding standard display area, and the display area matching information is generated and transmitted to the display scheduling analysis module.

[0008] As a further solution of the present invention, the specific manner in which the display area matching analysis module performs a secondary analysis on the pre-selected display areas that do not have sufficient conditions is as follows: For pre-selected display areas without duplication a , obtain the total number of tourists in the corresponding area, and at the same time obtain the number of views of the corresponding display animal a, and grade the total number of tourists in the area and the number of views of the display animal respectively to obtain the corresponding browsing level, then match the pre-selected display areas with the display animals at the same browsing level, and record the corresponding pre-selected display areas as standard display areas, and generate display area matching information at the same time.

[0009] As a further solution of the present invention, the specific manner in which the display scheduling analysis module analyzes the display area matching information is as follows: Obtain the display animals in the standard display area, their active periods, the number of visitors in different periods, and the browsing level. Match the high browsing level periods with the active periods, and mark the overlapping periods as overlapping periods. Compare the overlapping period duration with the threshold, and classify the period with a duration greater than the threshold as the first adjustment period, and the period with a duration ≤ the threshold as the second adjustment period, and process the two separately.

[0010] As a further solution of the present invention, the specific manner in which the display scheduling analysis module processes the two respectively is as follows: Adjusting the obtained first adjustment period to obtain the corresponding period duration, segmenting it according to the preset duration to obtain segment durations, and displaying the display animals according to the segment durations to generate scheduling display information; The obtained second adjustment period is adjusted, the corresponding period duration is evenly divided, and the display animals are displayed according to the evenly divided period duration, and the scheduling display information is generated and transmitted to the intelligent scheduling information display module.

[0011] As a further solution of the present invention, it also includes a multi-source data acquisition module for acquiring multi-source data of the zoo and transmitting it to the multi-source data processing and fusion module, and the multi-source data includes visitor data, animal data and environmental data.

[0012] A zoo intelligent scheduling method based on multi-source data fusion, the method specifically comprising the following steps: Step A1: Collect multi-source data, perform data cleaning and preprocessing to obtain preprocessed multi-source data, and fuse the data to obtain fused multi-source data; Step A2: matching the regional environment of the display area with the environmental requirements of the display animals to obtain a pre-selected display area, and judging and screening its repeatability to obtain an area to be analyzed; Step A3: Score and assign values ​​to the area and visitor density of the area to be analyzed, and calculate the corresponding regional fit according to the formula. Use the maximum regional fit as the criterion to select standard display areas, and generate display area matching information; Step A4: Obtain the active time periods of the exhibited animals in the standard exhibition area and the corresponding visitor numbers during these time periods, filter out overlapping time periods, and classify the overlapping time periods according to their duration to obtain a first adjustment time period and a second adjustment time period; Step A5: Make different adjustments to the first and second adjustment periods, divide the period lengths into segments, and display the animals to generate scheduling display information.

[0013] The present invention provides a zoo intelligent scheduling system and method based on multi-source data fusion. Compared with the existing technology, it has the following advantages: The present invention acquires information in real time through a multi-source data acquisition module, automatically generates matching and scheduling plans after processing and fusion, reduces manual intervention, and identifies potential problems in advance through data cleaning and outlier processing, triggering preventive adjustments. Based on the overlap analysis of animal active periods (and high-traffic periods), the core display window is accurately identified to avoid "ineffective display". The scheduling strategy is dynamically adjusted according to the overlap duration, and the flow of visitors is limited in sections to control the batches and length of stay of visitors. This realizes the scientific allocation of display resources, the refinement of animal welfare protection, and the intelligent improvement of visitor experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 This is a schematic diagram of the system of the present invention; Figure 2 It is a diagram of the steps of the present invention. DETAILED DESCRIPTION

[0015] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0016] Example 1 See also Figure 1 The present application provides a zoo intelligent scheduling system based on multi-source data fusion, including: multi-source data acquisition module, multi-source data processing and fusion module, display area matching analysis module, display scheduling analysis module and intelligent scheduling information display module, and combined with Figure 1 It can be known that the functional modules are electrically connected in a unidirectional manner.

[0017] Multi-source data acquisition module, which is used to obtain multi-source data of the zoo and transmit it to the multi-source data processing and fusion module. The multi-source data includes visitor data, animal data and environmental data.

[0018] Multi-source data processing and fusion module, this module is used to perform data cleaning and preprocessing on the acquired multi-source data to obtain preprocessed multi-source data, and the data cleaning and preprocessing mainly remove noise, duplicate values ​​and outliers in the data, fill in missing data, unify data formats and standards, and at the same time perform data fusion on the obtained preprocessed multi-source data to obtain fused multi-source data, and the data fusion methods include weighted averaging method, Kalman filtering method, neural network method, etc., and then transmit the fused multi-source data to the display area matching analysis module.

[0019] The display area matching analysis module is used to screen and match the display animals corresponding to different display areas based on the acquired fusion multi-source data. The specific screening and matching methods are as follows: Obtain all display areas and label them as i, where i = 1, 2, ..., j, where j represents the number of display areas. Also obtain the regional environmental information and visitor browsing information corresponding to display area i. Then obtain all displayed animals and label them as a, where a = 1, 2, ..., b, where b represents the species of the displayed animal. Also obtain the environmental requirements corresponding to displayed animal a and match them with the regional environmental information of display area i. If the two are matched successfully, it means that the display area i is suitable for displaying animal a, and the corresponding display area i is classified as a pre-selected display area. If the two are not matched successfully, it means that the display area is not suitable for displaying animal a, and no processing is done. Similarly, all display areas i are matched and processed to obtain the corresponding pre-selected display area. a ,and a =1, 2, ..., ,in Indicates the number of pre-selected display areas; Then, the pre-selected display area corresponding to all displayed animals a is a Repeatability judgment is performed, and the repeatability judgment here is to judge whether different display animals a have the same pre-selected display area. If so, the corresponding pre-selected display area is a Record it as the area to be analyzed. Otherwise, if it does not exist, it will not be processed. At the same time, the fit between the area to be analyzed and the area of ​​the display animal a is calculated respectively, and the specific calculation method is: Obtain the area and tourist density corresponding to the area to be analyzed. The tourist density is obtained by calculating the ratio of the total number of tourists to the area of ​​the tourist area, and scoring and assigning values ​​to the two respectively to obtain the corresponding area assignment and tourist density assignment. Then, according to the formula regional fit = area assignment × first weight + tourist density assignment × second weight, calculate the corresponding regional fit; The area with the greatest degree of fit is selected as the standard, which is used as the corresponding standard display area, and the display area matching information is generated and transmitted to the display scheduling analysis module; For pre-selected display areas without duplication a , obtain the total number of tourists in the corresponding area, and at the same time obtain the number of views of the corresponding display animal a, and grade the total number of tourists in the area and the number of views of the display animal respectively to obtain the corresponding browsing level, and the browsing level is specifically divided into three levels: high, medium and low, and each level corresponds to an interval value, then match the pre-selected display areas with the display animals at the same browsing level, and record the corresponding pre-selected display areas as standard display areas, and generate display area matching information at the same time.

[0020] Get all the exhibition areas in the zoo, numbered sequentially as i = 1, 2, ..., j, where j is the total number of areas. For each exhibition area, collect the following information: Environmental parameters: Area S i , temperature T i 、Humidity H i , light intensity L i , Noise level N i , water area ratio W i wait; Tourist data: real-time number of tourists C i 、Area A i (used to calculate tourist density D i =C i / A i ), historical average daily page views V i , Get all the animals on display, labeled a=1, 2, ..., b, where b is the number of animal species. For each animal, record: Basic information: Suitable temperature range [T a-min , T a-max ]、Humidity range [H a-min , H a-max ], minimum activity area requirement S a-min , Tolerable tourist density threshold D a-mar , average daily ideal display time E a ; For each display area i and animal a, perform environmental matching judgment: If the following conditions are met, then area i is marked as the pre-selected display area for animal a: T a-min ≤T i ≤T a-max And H a-min ≤H i ≤H a-max , S i ≥S a-min and D i ≤D a-max ; Identify areas where there is overlap in the pre-selected display areas of different animals and mark them as areas to be analyzed.

[0021] For each region k to be analyzed and the corresponding animal a, calculate the regional fit F k，a : Area score S score :According to S k / S a-min The ratio is mapped to 0-100 points through a piecewise function (for example, a ratio ≥ 1.5 is 100 points, 0.8-1.5 is scored linearly, and < 0.8 is 0 points) Visitor density score D score :According to D k / D a-mar The ratio is scored in reverse order (for example, a ratio ≤ 0.5 is scored as 100 points, 0.5-1 is scored linearly, and > 1 is scored as 0 points) Calculate the fit: F k，a =S score x +D score x Weight parameters: =0.6 (area importance), =0.4 (importance of tourist density), select F k，a The highest combination determines area k as the standard display area for animal a; For pre-selected display areas that do not have duplicates, follow these steps to match: The total number of regional tourists C i and animal views V a It is divided into three levels: high (Top 30%), medium (middle 40%), and low (Bottom 30%). Areas at the same browsing level are matched with animals first. If there are multiple candidate areas, the area closest to the animal's needs is selected as the standard display area.

[0022] For example, a zoo has 10 exhibition areas (j=10) and houses 8 species of animals (b=8). It now needs to allocate an exhibition area for the newly added "ring-tailed lemur" (a=9). Ring-tailed lemurs require: a temperature of 20-30°C, a minimum area of ​​100 m2, a visitor density of ≤3 people / m2, and are diurnal and social animals. The candidate area data (partial example) is shown in the following table: Preliminary matching Area 3: Meets temperature, area, and density requirements and is selected into the pre-selected area Area 5: Tourist density exceeds the limit, excluded Area 7: Insufficient area, excluded Repeat region analysis If area 3 is also the pre-selected area for "Squirrel Monkey", then calculate: Ring-tailed Lemur: S score =120 / 100x100=120 (full score is 100, take 100), D score =(3-2.5) / (3-0)x100=16.7, Squirrel Monkey: S score =100, D score =20 Ring-tailed lemur compatibility F 3，9=100x0.6+16.7x0.4=66.7； Squirrel Monkey Compatibility F 3，7=100x0.6+20x0.4=68； Because squirrel monkeys have a higher degree of fit, area 3 was allocated to squirrel monkeys, and ring-tailed lemurs continued to screen other areas; The intelligent scheduling information display module is used to display the acquired display area matching information to the corresponding management personnel.

[0023] Example 2 As the second embodiment of the present invention, it is implemented on the basis of the first embodiment, and differs from the first embodiment in the following aspects: The display area matching analysis module transmits the generated display area matching information to the display scheduling analysis module, and the display scheduling analysis module analyzes and processes the information.

[0024] The display scheduling analysis module is used to perform display duration scheduling analysis on the standard display area based on the acquired display area matching information. The specific scheduling analysis method is as follows: Obtain the display animals corresponding to the standard display area, and at the same time, obtain the corresponding active period based on the living habits of the display animals. The active period means that the animals are not resting during this period. The number of visitors corresponding to different time periods in the standard display area is obtained. Then, the browsing level corresponding to the number of visitors in different time periods is obtained. All time periods with high browsing levels are obtained and matched with the active period. If the two time periods overlap, it means the match is successful and the corresponding time period is marked as the overlapping time period. Otherwise, if the two time periods do not overlap, it means the match fails and no processing is performed. Then, all overlapping time periods are obtained, and their corresponding time period lengths are obtained. At the same time, secondary classification is performed based on the time period lengths. The time period lengths are compared with a threshold value, and the specific value of the threshold value is set by the operator. If the time period length is greater than the threshold value, it is secondary classified as the first adjustment time period. Conversely, if the time period length is less than the threshold value, it is secondary classified as the second adjustment time period, and adjustment processing is performed on both; The obtained first adjustment period is adjusted to obtain the corresponding period duration, and the period duration is divided into segments according to the preset duration to obtain segment durations. The specific value of the preset duration is set by the operator. At the same time, the display of the exhibited animals is processed according to the segment durations. For example, the giant panda is shortened from 2 hours to 1.5 hours, a group of tourists is released every 30 minutes (limited to 50 people / group), and the visiting time is limited to 10 minutes. The scheduling display information is generated; The obtained second adjustment period is adjusted, the corresponding period duration is evenly divided, and the display animals are displayed according to the evenly divided period duration, and the scheduling display information is generated and transmitted to the intelligent scheduling information display module.

[0025] Obtain a list of animals in the standard display area (such as giant pandas, golden monkeys, etc.) and determine their active periods based on the animal habit database.

[0026] For example: Giant pandas are active from 08:00 to 11:30 and 14:00 to 17:00 (non-resting periods), and lions are active from 10:00 to 12:00 and 16:00 to 18:00.

[0027] Statistics standardize visitor data for different time periods in the display area, categorizing it into three visitor levels: high (top 20%), medium, and low. For example, the peak visitor volume for a zoo's panda house is between 10:00 AM and 11:00 AM (500 visitors) and 2:30 PM and 3:30 PM (450 visitors), both of which are high visitor levels.

[0028] Compare the high browsing level period with the animal active period, if there is overlap, mark it as overlapping period, otherwise ignore it. Example: The pandas’ active period of 08:00-11:30 overlaps with the high tourist flow period of 10:00-11:00, generating an overlapping period of 10:00-11:00.

[0029] The lions' active period of 16:00-18:00 does not overlap with the high tourist flow period of 14:30-15:30, so the matching fails.

[0030] The operator presets a duration threshold (e.g., 1 hour) and classifies the overlapping periods according to their duration: First adjustment period: If the duration exceeds the threshold, segmented throttling is required. For example, if the overlapping period 10:00-11:00 (1 hour) is equal to the threshold and the threshold is set to 0.5 hours, it is classified as the first adjustment period.

[0031] Second adjustment period: Duration ≤ threshold, requiring even scheduling. Example: The overlapping period **14:00-14:40 (40 minutes)** is divided into the second adjustment period.

[0032] The time period is divided into preset segments (e.g. 30 minutes), and each segment is capped at a maximum number of visitors (e.g. 50 people / group), with a limited visiting time (e.g. 10 minutes). Example: The overlapping period of 10:00-11:00 is split into two sections: 10:00-10:30 and 10:30-11:00.

[0033] 50 people are allowed in each section, the visiting time is 10 minutes, and tourists can enter in the next time period after the area is cleared at 10:40.

[0034] Divide the time period into several sub-periods to maintain a fixed visiting rhythm. Example: The overlapping period 14:00-14:40 is divided into two sections: 14:00-14:20 and 14:20-14:40.

[0035] A group of tourists will be released every 20 minutes (limited to 30 people / group), and the visiting time is 15 minutes.

[0036] The intelligent scheduling information display module is used to display the obtained scheduling display information to the corresponding management personnel.

[0037] Example 3 As the third embodiment of the present invention, the focus is on combining the implementation processes of the first and second embodiments.

[0038] Example 4 See also Figure 2 The present application provides a zoo intelligent scheduling method based on multi-source data fusion, which specifically includes the following steps: Step A1: Collect multi-source data and perform data cleaning and preprocessing to obtain preprocessed multi-source data, and fuse them to obtain fused multi-source data. The specific processing method is the same as that of the multi-source data processing and fusion module in Example 1. Step A2: Match the regional environment of the display area with the environmental requirements of the display animals to obtain a pre-selected display area, and judge and screen its repeatability to obtain the area to be analyzed. The specific processing method is the same as the processing method of the display area matching analysis module in Example 1; Step A3: Score and assign values ​​to the area and visitor density of the area to be analyzed, and calculate the corresponding regional fit according to the formula. Use the maximum regional fit as the criterion to screen and obtain standard display areas, and generate display area matching information. The specific processing method is similar to that of the display area matching analysis module in Example 1. Step A4: Obtain the active periods of the animals displayed in the standard display area and the corresponding visitor volume during these periods, filter out overlapping periods, and classify the overlapping periods according to their duration to obtain a first adjustment period and a second adjustment period. The specific processing method is the same as that of the display scheduling analysis module in Example 2. Step A5: make different adjustments to the first and second adjustment periods, segment the period lengths, and generate scheduling display information for displaying the display animals. The specific processing method is the same as that of the display scheduling analysis module in Example 2.

[0039] Some of the data in the above formulas are calculated based on their numerical values ​​and are not substituted into parameter units for calculation. At the same time, the contents not described in detail in this specification belong to the existing technology known to those skilled in the art.

[0040] The above embodiments are only used to illustrate the technical method of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A zoo intelligent scheduling system based on multi-source data fusion, characterized in that: include: The display area matching analysis module is used to analyze the fused multi-source data transmitted by the multi-source data processing and fusion module, match the regional environment of the display area with the environmental requirements of the display animals to obtain pre-selected display areas, and judge and screen their repeatability to obtain the area to be analyzed. The area and visitor density of the area to be analyzed are scored and assigned, and the corresponding regional fit is calculated according to the formula. The standard display area is screened based on the maximum regional fit, and the display area matching information is generated and transmitted to the display scheduling analysis module; The display scheduling analysis module is used to analyze the display area matching information, obtain the active time periods of the display animals in the standard display area and the corresponding number of visitors during the time periods, filter out overlapping time periods, and classify the overlapping time periods according to their time periods to obtain the first adjustment time period and the second adjustment time period. Different adjustments are made to the first and second adjustment time periods, the time period lengths are segmented, and the display animals are displayed to generate scheduling display information, which is then transmitted to the intelligent scheduling information display module.

2. The zoo intelligent scheduling system based on multi-source data fusion according to claim 1 is characterized in that: It also includes a multi-source data processing and fusion module and an intelligent scheduling information display module; The multi-source data processing and fusion module is used to clean and pre-process the multi-source data transmitted by the multi-source data acquisition module to obtain pre-processed data, and perform data fusion on the pre-processed data to obtain fused multi-source data; The intelligent scheduling information display module is used to display the acquired scheduling display information to the corresponding management personnel.

3. The zoo intelligent scheduling system based on multi-source data fusion according to claim 1 is characterized in that: The specific method in which the display area matching analysis module analyzes the fused multi-source data transmitted by the multi-source data processing and fusion module is as follows: Obtain all display areas and label them as i, where i = 1, 2, ..., j, where j represents the number of display areas. Collect regional environmental information and visitor browsing information. Then obtain all displayed animals and label them as a, where a = 1, 2, ..., b, where b represents the type of displayed animal. Obtain the environmental requirements corresponding to displayed animal a and match them with the regional environmental information of display area i. If the two are matched successfully, they will be classified as pre-selected display areas If the two are not matched successfully, no processing will be done. Similarly, all display areas i are matched to obtain the corresponding pre-selected display areas. a ,and a =1, 2, ..., ,in Indicates the number of pre-selected display areas; Then, the pre-selected display area corresponding to all displayed animals a is a Make a repeat judgment, if it exists, the corresponding pre-selected display area a It is recorded as the area to be analyzed. Otherwise, if it does not exist, it will not be processed. At the same time, a secondary analysis will be performed on the pre-selected display areas where there is no sufficient situation.

4. The zoo intelligent scheduling system based on multi-source data fusion according to claim 1 is characterized in that: The specific method for the display area matching analysis module to generate the display area matching information is as follows: Obtain the area and tourist density corresponding to the area to be analyzed, and score and assign values ​​to them respectively to obtain the corresponding area assignment and tourist density assignment. Then, calculate the corresponding regional fit according to the formula: regional fit = area assignment × first weight + tourist density assignment × second weight; The area with the greatest degree of fit is selected as the standard, which is used as the corresponding standard display area, and the display area matching information is generated and transmitted to the display scheduling analysis module.

5. The zoo intelligent scheduling system based on multi-source data fusion according to claim 3 is characterized in that: The specific method in which the display area matching analysis module performs a secondary analysis on the pre-selected display areas that do not have sufficient conditions is as follows: For pre-selected display areas without duplication a , obtain the total number of tourists in the corresponding area, and at the same time obtain the number of views of the corresponding display animal a, and grade the total number of tourists in the area and the number of views of the display animal respectively to obtain the corresponding browsing level, then match the pre-selected display areas with the display animals at the same browsing level, and record the corresponding pre-selected display areas as standard display areas, and generate display area matching information at the same time.

6. The zoo intelligent scheduling system based on multi-source data fusion according to claim 1 is characterized in that: The specific method in which the display scheduling analysis module analyzes the display area matching information is as follows: Obtain the exhibited animals in the standard exhibition area, their active periods, the number of visitors in different periods, and their browsing levels. Match the high browsing level periods with the active periods, and mark the overlapping periods as overlapping periods. Compare the overlapping period length with the threshold, divide the overlapping period with a length greater than the threshold into the first adjustment period, and divide the overlapping period with a length less than or equal to the threshold into the second adjustment period, and process them separately.

7. The zoo intelligent scheduling system based on multi-source data fusion according to claim 6 is characterized in that: The specific way in which the display scheduling analysis module processes the two is as follows: Adjusting the obtained first adjustment period to obtain the corresponding period duration, segmenting it according to the preset duration to obtain segment durations, and displaying the display animals according to the segment durations to generate scheduling display information; The obtained second adjustment period is adjusted, the corresponding period duration is evenly divided, and the display animals are displayed according to the evenly divided period duration, and the scheduling display information is generated and transmitted to the intelligent scheduling information display module.

8. The zoo intelligent scheduling system based on multi-source data fusion according to claim 2 is characterized in that: It also includes a multi-source data acquisition module for acquiring multi-source data of the zoo and transmitting it to the multi-source data processing and fusion module, and the multi-source data includes visitor data, animal data and environmental data.

9. A zoo intelligent scheduling method based on multi-source data fusion, executed by the zoo intelligent scheduling system according to any one of claims 1 to 8, characterized in that: The method specifically comprises the following steps: Step A1: Collect multi-source data, perform data cleaning and preprocessing to obtain preprocessed multi-source data, and fuse the data to obtain fused multi-source data; Step A2: matching the regional environment of the display area with the environmental requirements of the display animals to obtain a pre-selected display area, and judging and screening its repeatability to obtain an area to be analyzed; Step A3: Score and assign values ​​to the area and visitor density of the area to be analyzed, and calculate the corresponding regional fit according to the formula. Use the maximum regional fit as the criterion to select standard display areas, and generate display area matching information; Step A4: Obtain the active time periods of the exhibited animals in the standard exhibition area and the corresponding visitor numbers during these time periods, filter out overlapping time periods, and classify the overlapping time periods according to their duration to obtain a first adjustment time period and a second adjustment time period; Step A5: Make different adjustments to the first and second adjustment periods, divide the period lengths into segments, and display the animals to generate scheduling display information.

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