CN117407828B - Data analysis method applied to sponge city rainwater collection system - Google Patents
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Abstract
The invention relates to the technical field of data processing, in particular to a data analysis method applied to a sponge urban rainwater collection system, which comprises the following steps: acquiring rainwater monitoring data; acquiring neighborhood data of each rainwater monitoring data according to the distance between the rainwater monitoring data; acquiring the initial abnormality degree of each rainwater monitoring data according to the distance between each rainwater monitoring data and the neighborhood data of each rainwater monitoring data; obtaining the abnormality degree of each item of data of each rainwater monitoring data, and further obtaining a plurality of suspected abnormal data of each rainwater monitoring data; acquiring an abnormality factor of each piece of rainwater monitoring data according to each piece of suspected abnormality data in each piece of rainwater monitoring data; acquiring the actual abnormality degree of each piece of rainwater monitoring data according to the abnormality factor and the initial abnormality degree of each piece of rainwater monitoring data, and further acquiring the abnormality data in the rainwater monitoring data; the present invention aims to identify accurate anomaly data.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a data analysis method applied to a sponge urban rainwater collection system.
Background
Along with the increasing serious of water resources and environmental problems, a sponge city concept is developed, the purpose is to improve the hydrologic environment of a city through green infrastructure and sustainable water resource management, a rainwater collection system is taken as an important component of the city, the method has important significance for effectively utilizing the rainwater resources, relieving urban waterlogging, improving water quality and the like, and the rainwater monitoring data in the rainwater collection system are subjected to abnormal analysis, so that the rainwater collection system can be helped to optimize the rainwater treatment and utilization mode, and the effective utilization of the rainwater resources is ensured.
When the anomaly detection is carried out on the rainwater monitoring data through the LOF algorithm, the anomaly data judgment is carried out according to the density between the rainwater monitoring data and the adjacent rainwater monitoring data, and the anomaly of each item of the rainwater monitoring data can cause the anomaly of the rainwater monitoring data when the anomaly occurs, so that the anomaly of each item of data in the rainwater monitoring data also affects the anomaly data of the rainwater monitoring data, and the obtained anomaly data is inaccurate according to the density between the rainwater monitoring data and the adjacent rainwater monitoring data, and can cause false detection.
Disclosure of Invention
In order to solve the problems, the invention provides a data analysis method applied to a sponge urban rainwater collection system.
The invention relates to a data analysis method applied to a sponge urban rainwater collection system, which adopts the following technical scheme:
an embodiment of the invention provides a data analysis method applied to a sponge urban rainwater collection system, which comprises the following steps:
acquiring rainwater monitoring data;
acquiring neighborhood data of each rainwater monitoring data according to the distance between the rainwater monitoring data; acquiring the initial abnormality degree of each rainwater monitoring data according to the distance between each rainwater monitoring data and the neighborhood data of each rainwater monitoring data;
acquiring the abnormality degree of each item of data of each piece of rainwater monitoring data according to the value of each item of data of the rainwater monitoring data; acquiring a plurality of suspected abnormal data of each rainwater monitoring data according to the abnormal degree of each data of each rainwater monitoring data; acquiring an abnormality factor of each piece of rainwater monitoring data according to the abnormality degree of each piece of suspected abnormality data in each piece of rainwater monitoring data; acquiring the actual abnormality degree of each piece of rainwater monitoring data according to the abnormality factors and the initial abnormality degree of each piece of rainwater monitoring data;
and acquiring abnormal data in the rainwater monitoring data according to the actual abnormal degree of each rainwater monitoring data.
Preferably, the step of obtaining the neighborhood data of each rainwater monitoring data according to the distance between the rainwater monitoring data includes the following specific steps:
presetting neighborhood data quantityMapping each item of rainwater monitoring data into a multi-dimensional coordinate system, and acquiring and +.>The rainwater monitoring data are nearest +.>Rainwater monitoring data, designated->Neighborhood data of individual stormwater monitoring data.
Preferably, the step of obtaining the initial abnormality degree of each rainwater monitoring data according to the distance between each rainwater monitoring data and the neighborhood data of each rainwater monitoring data includes the following specific steps:
in a multidimensional coordinate system, obtain the firstRainwater monitoring data and->The distance between each neighborhood data of each rainwater monitoring data is set as the maximum distance +.>The initial degree of anomaly of the individual stormwater monitoring data.
Preferably, the obtaining the abnormality degree of each item of the rainwater monitoring data according to the value of each item of the rainwater monitoring data includes the following specific steps:
in the method, in the process of the invention,represents->No. of individual stormwater monitoring data>Degree of abnormality of item data; />Indicate->The number of neighborhood data of the individual rain monitoring data; />Represents->No. of individual stormwater monitoring data>A value of item data; />Represents->No. of individual stormwater monitoring data>Personal area data->A value of item data; />Represents->All neighborhood data of individual stormwater monitoring data +.>Standard deviation of values of item data; />Representing absolute value symbols.
Preferably, the obtaining a plurality of suspected abnormal data of each rainwater monitoring data according to the abnormality degree of each data of each rainwater monitoring data comprises the following specific steps:
presetting an abnormality degree thresholdIf->No. of individual stormwater monitoring data>The degree of abnormality of the item data is greater than or equal to the threshold degree of abnormality +.>Will->No. of individual stormwater monitoring data>Item data is marked as->Obtaining a suspected abnormal data of the rainwater monitoring data to obtain +.>Several items of suspected anomaly data for the individual stormwater monitoring data.
Preferably, the obtaining the abnormality factor of each piece of rainwater monitoring data according to the abnormality degree of each piece of suspected abnormality data in each piece of rainwater monitoring data includes the following specific steps:
obtaining the abnormality degree of each suspected abnormal data in each rainwater monitoring data according to the abnormality degree of each data of each rainwater monitoring data;
in the method, in the process of the invention,represents->Abnormal factors of the rainwater monitoring data; />Represents->The number of items of suspected abnormal data of the rainwater monitoring data; />Represents->No. of individual stormwater monitoring data>The term is suspected of the degree of abnormality of the abnormal data.
Preferably, the obtaining the abnormality degree of each piece of suspected abnormal data in each piece of rainwater monitoring data includes the following specific steps:
and taking the abnormality degree of the data corresponding to each piece of suspected abnormal data in each piece of rainwater monitoring data as the abnormality degree of each piece of suspected abnormal data in each piece of rainwater monitoring data.
Preferably, the obtaining the actual abnormality degree of each rainwater monitoring data according to the abnormality factor and the initial abnormality degree of each rainwater monitoring data includes the following specific steps:
in the method, in the process of the invention,indicate->Actual anomaly degree of each rainwater monitoring data; />Represents->Abnormal factors of the rainwater monitoring data; />Represents->The initial degree of anomaly of the individual stormwater monitoring data.
Preferably, the acquiring a plurality of abnormal data in the rainwater monitoring data according to the actual abnormal degree of each rainwater monitoring data includes the following specific steps:
presetting an actual abnormality degree thresholdIf->The actual abnormality degree of the individual rainwater monitoring data is greater than or equal to the actual abnormality degree threshold +.>Then->The rainwater monitoring data are abnormal data in the rainwater monitoring data, and the abnormal data in the rainwater monitoring data are obtained.
Preferably, the step of acquiring the rainwater monitoring data includes the following specific steps:
acquiring a plurality of rainwater monitoring data in a period of time in a rainwater collecting system, wherein each rainwater monitoring data comprises a plurality of items of data: the rainwater collection amount, the rainwater PH value, the rainwater turbidity, the rainwater heavy metal content and the rainwater organic matter content.
The technical scheme of the invention has the beneficial effects that: firstly, acquiring neighborhood data of rainwater monitoring data; according to the distance between the rainwater monitoring data and the neighborhood data thereof, the initial abnormality degree of the rainwater monitoring data is obtained in a quantification mode, and the abnormality of the rainwater monitoring data is reflected; according to the difference of the values of each item of data of the rainwater monitoring data and each item of data of the neighborhood data of the rainwater monitoring data, the abnormal degree of each item of data of each rainwater monitoring data is obtained, a plurality of suspected abnormal data of each item of rainwater monitoring data are obtained, then according to the abnormal degree of a plurality of suspected abnormal data of the rainwater monitoring data, the abnormal factor of the rainwater monitoring data is obtained, and the abnormal of the whole rainwater monitoring data is analyzed by analyzing the abnormal of each item of data of the rainwater monitoring data, so that the abnormal analysis of the rainwater monitoring data is more accurate; finally, according to the initial abnormality degree combined with the abnormality factors of each piece of rainwater monitoring data, the actual abnormality degree of each piece of rainwater monitoring data is obtained, so that the abnormality data in the rainwater monitoring data are obtained, the abnormality of each piece of data in the rainwater monitoring data is considered, the abnormality of the rainwater monitoring data is considered, the actual abnormality degree of the obtained rainwater monitoring data is more accurate, the obtained abnormality data is more accurate, and the false detection phenomenon is avoided.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of the steps of a method for analyzing data applied to a sponge city rainwater collection system.
Detailed Description
In order to further describe the technical means and effects adopted by the invention to achieve the preset aim, the following is a detailed description of a specific implementation, structure, characteristics and effects thereof of the data analysis method for the sponge urban rainwater collection system according to the invention, which is provided by the invention, with reference to the accompanying drawings and the preferred embodiment. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The invention provides a specific scheme for a data analysis method applied to a sponge urban rainwater collection system, which is specifically described below with reference to the accompanying drawings.
Referring to fig. 1, a flowchart of steps of a method for analyzing data of a sponge city rainwater collection system according to an embodiment of the present invention is shown, the method includes the following steps:
s001, collecting rainwater monitoring data.
It should be noted that the purpose of the invention is to analyze abnormal data of the rainwater monitoring data, so as to be convenient for finding potential environmental problems in time, and be helpful for the rainwater collecting system to optimize the rainwater treatment and utilization mode and ensure the utilization of resources, therefore, the rainwater monitoring data mainly comprises the data of rainwater collection amount, rainwater pH value, rainwater turbidity, rainwater heavy metal content, rainwater organic matter content and the like.
In the embodiment of the invention, a plurality of rainwater monitoring data in a period of time are acquired in a rainwater collecting system, wherein each rainwater monitoring data comprises a plurality of items of data: the rainwater collection amount, the rainwater PH value, the rainwater turbidity, the rainwater heavy metal content and the rainwater organic matter content; the rainwater collecting system collects rainwater monitoring data 1 time/day, and collects rainwater monitoring data when it rains, and does not collect rainwater monitoring data when it does not rains.
Thus, rainwater monitoring data is obtained.
S002, acquiring neighborhood data of each rainwater monitoring data according to the rainwater monitoring data; and acquiring the initial abnormality degree of each rainwater monitoring data according to the distance between each rainwater monitoring data and the neighborhood data thereof.
It should be noted that, the LOF algorithm obtains the degree of abnormality of the data according to the distance between each data and the neighborhood data of each data, and can detect the data with abnormal local relative density from all the data, so that in the invention, the neighborhood data of each rainwater monitoring data is obtained first, and then the initial degree of abnormality of each rainwater monitoring data is obtained according to the distance between each rainwater monitoring data and the neighborhood data.
In the embodiment of the invention, neighborhood data of each rainwater monitoring data are acquired: presetting neighborhood data quantityMapping each item of data of each rainwater monitoring data into a multi-dimensional coordinate system, wherein each rainwater monitoring data corresponds to one coordinate point in the multi-dimensional coordinate system, each item of data is one dimension in the multi-dimensional coordinate system, and the data is acquired from the first coordinate system in the multi-dimensional coordinate systemThe rainwater monitoring data are nearest +.>Rainwater monitoring data, i.e. and +.>Coordinate point corresponding to rainwater monitoring data is nearest to +.>Rainwater monitoring data corresponding to the coordinate points are marked as +.>Neighborhood data of each rainwater monitoring data are obtained in a similar way, and in the embodiment of the invention, the number of the neighborhood data is preset +.>In other embodiments, the practitioner can set +.>Is a value of (2).
Acquiring the initial abnormality degree of each rainwater monitoring data: in a multidimensional coordinate system, obtain the firstRainwater monitoring data and->The distance between each neighborhood data of each rainwater monitoring data is taken as the maximum distance +.>The initial anomaly degree of the rainwater monitoring data is to be explained, wherein the Euclidean distance is used for measuring the distance between the rainwater monitoring data.
So far, according to the rainwater monitoring data, neighborhood data of each rainwater monitoring data are obtained; and acquiring the initial abnormality degree of each rainwater monitoring data according to the distance between each rainwater monitoring data and the neighborhood data thereof.
S003, obtaining the abnormality degree of each item of data of each piece of rainwater monitoring data, obtaining a plurality of suspected abnormality data of each piece of rainwater monitoring data according to the abnormality degree of each item of data of each piece of rainwater monitoring data, obtaining an abnormality factor of each piece of rainwater monitoring data according to the abnormality degree of a plurality of suspected abnormality data of each piece of rainwater monitoring data, and obtaining the actual abnormality degree of each piece of rainwater monitoring data according to the abnormality factor of each piece of rainwater monitoring data and the initial abnormality degree of each piece of rainwater monitoring data.
It should be noted that, when the difference between the value of any item of data in the rainwater monitoring data and the value of the item of data in the neighborhood data is large, the rainwater monitoring data may be considered to be abnormal, so that the abnormal degree of any item of data in the rainwater monitoring data is obtained by analyzing the difference between the value of any item of data in the rainwater monitoring data and the value of the item of data in the neighborhood data, so that the abnormal factor of the rainwater monitoring data is obtained conveniently according to the abnormal degree of each item of data in the rainwater monitoring data.
In the embodiment of the invention, the first is acquiredNo. of individual stormwater monitoring data>Degree of abnormality of item data:
in the method, in the process of the invention,represents->No. of individual stormwater monitoring data>Degree of abnormality of item data; />Indicate->Neighborhood data of individual stormwater monitoring dataNumber of pieces; />Represents->No. of individual stormwater monitoring data>A value of item data; />Represents->No. of individual stormwater monitoring data>Personal area data->A value of item data; />Represents->All neighborhood data of individual stormwater monitoring data +.>Standard deviation of values of item data; />Representing absolute value symbols; />Represents->No. of individual stormwater monitoring data>The value of item data and->No. of individual stormwater monitoring data>Personal area data->The absolute value of the difference of the values of the item data;represents->No. of individual stormwater monitoring data>Value of item data and +.>Average difference of values of item data, if the average difference is equal to +.>All neighborhood data of individual stormwater monitoring data +.>The greater the ratio of standard deviations of the values of the item data, the description +.>No. of individual stormwater monitoring data>All +.>The greater the degree of outlier, the +.>No. of individual stormwater monitoring data>The greater the degree of abnormality of the item data, the same way, the degree of abnormality of each item of data of each rainwater monitoring data is obtained.
When the degree of abnormality of any one item of data of any one of the rainwater monitoring data is greater than 1, it is explained that the average difference between the value of the item of data of the rainwater monitoring data and the value of the item of data of all the neighborhood data thereof is far greater than the standard deviation of the value of the item of data of all the neighborhood data of the rainwater monitoring data (the degree of fluctuation of the item of data of all the neighborhood data), at which time the item of data of the rainwater monitoring data is more likely to be abnormal data.
In the embodiment of the invention, an abnormality degree threshold is presetWhen->No. of individual stormwater monitoring data>The degree of abnormality of the item data is greater than or equal to the threshold degree of abnormality +.>At the time->No. of individual stormwater monitoring data>The item data is suspected abnormal data, the +.>No. of individual stormwater monitoring data>Item data is marked as->Obtaining a suspected abnormal data of the rainwater monitoring data to obtain +.>A plurality of suspected abnormal data of the rainwater monitoring data; similarly, a plurality of suspected abnormal data of each rainwater monitoring data are obtained, and in the embodiment of the invention, an abnormal degree threshold value is preset>In other embodiments, the practitioner can set +.>Is a value of (2).
It should be noted that, regarding the degree of abnormality of each piece of rain monitoring data, the degree of abnormality of each piece of suspected abnormality data of each piece of rain monitoring data needs to be considered, and the value of the degree of abnormality of each piece of suspected abnormality data is known to be greater than 1, so that when the difference between the degree of abnormality of all pieces of suspected abnormality data in each piece of rain monitoring data and 1 is greater, the more abnormal the rain monitoring data is described, and therefore in the present invention, the abnormality factor of each piece of rain monitoring data is obtained from the degree of abnormality of each piece of suspected abnormality data in each piece of rain monitoring data.
In the embodiment of the invention, the first is acquiredAbnormality factor of individual stormwater monitoring data:
the abnormality degree of the data corresponding to each piece of suspected abnormal data in each piece of rainwater monitoring data is used as the abnormality degree of each piece of suspected abnormal data in each piece of rainwater monitoring data;
in the method, in the process of the invention,represents->Abnormality of individual rain monitoring dataA factor; />Represents->The number of items of suspected abnormal data of the rainwater monitoring data; />Represents->No. of individual stormwater monitoring data>And similarly, obtaining the abnormality degree of each piece of rain monitoring data, wherein the value of the abnormality factor of the rain monitoring data without the suspected abnormality data is 0.
It should be noted that, the initial anomaly degree of each piece of rainwater monitoring data is obtained according to the distance between the pieces of rainwater monitoring data, the overall anomaly of the rainwater monitoring data is reflected, and the anomaly factor of each piece of rainwater monitoring data judges the anomaly degree of each piece of data in the rainwater monitoring data, so that the actual anomaly degree of each piece of rainwater monitoring data is required to be obtained according to the initial anomaly degree of each piece of rainwater monitoring data and the anomaly factor of each piece of rainwater monitoring data.
In the embodiment of the invention, the actual abnormality degree of each rainwater monitoring data is acquired:
wherein,indicate->Actual anomaly degree of each rainwater monitoring data; />Represents->Abnormal factors of the rainwater monitoring data; />Represents->Initial anomaly degree of each rainwater monitoring data; when->Initial degree of abnormality of individual rain monitoring data +.>The greater the abnormality factor of the individual rain monitoring data is +.>The greater the actual degree of anomaly of the individual stormwater monitoring data.
The method comprises the steps of obtaining the abnormality degree of each item of data of each piece of rainwater monitoring data, obtaining a plurality of suspected abnormality data of each piece of rainwater monitoring data according to the abnormality degree of each item of data of each piece of rainwater monitoring data, obtaining an abnormality factor of each piece of rainwater monitoring data according to the abnormality degree of a plurality of suspected abnormality data of each piece of rainwater monitoring data, and obtaining the actual abnormality degree of each piece of rainwater monitoring data according to the abnormality factor of each piece of rainwater monitoring data and the initial abnormality degree of each piece of rainwater monitoring data.
S004, acquiring abnormal data in the rainwater monitoring data according to the actual abnormal degree of each rainwater monitoring data.
When the actual degree of abnormality of any one of the rainwater monitoring data is larger, the rainwater monitoring data is more abnormal, and thus, the abnormal data in the rainwater monitoring data is acquired according to the actual degree of abnormality of each of the rainwater monitoring data.
In the embodiment of the inventionIn the method, an actual abnormality degree threshold value is presetIf->The actual abnormality degree of the individual rainwater monitoring data is greater than or equal to the actual abnormality degree threshold +.>Then->The rainwater monitoring data are one abnormal data in the rainwater monitoring data, and a plurality of abnormal data in the rainwater monitoring data are obtained, and in the embodiment of the invention, an actual abnormal degree threshold value is presetIn other embodiments, the practitioner can set +.>Is a value of (2).
When abnormal data exists in the rainwater monitoring data, the reasons for generating the abnormal data are analyzed, potential environmental problems can be found in time, the rainwater collecting system is facilitated to optimize the rainwater treatment and utilization mode, effective utilization of rainwater resources is ensured, and health and stability of urban water environment are ensured.
So far, according to the actual abnormality degree of each rainwater monitoring data, obtaining the abnormality data in the rainwater monitoring data.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the invention, but any modifications, equivalent substitutions, improvements, etc. within the principles of the present invention should be included in the scope of the present invention.
Claims (6)
1. The data analysis method applied to the sponge urban rainwater collection system is characterized by comprising the following steps of:
acquiring rainwater monitoring data;
acquiring neighborhood data of each rainwater monitoring data according to the distance between the rainwater monitoring data; acquiring the initial abnormality degree of each rainwater monitoring data according to the distance between each rainwater monitoring data and the neighborhood data of each rainwater monitoring data;
according to the value of each item of rainwater monitoring data, the abnormal degree of each item of data of each rainwater monitoring data is obtained, and according to the value of each item of data of the rainwater monitoring data, the abnormal degree of each item of data of each rainwater monitoring data is obtained, and the method comprises the following specific steps:
in the method, in the process of the invention,represents->No. of individual stormwater monitoring data>Degree of abnormality of item data; />Indicate->The number of neighborhood data of the individual rain monitoring data; />Represents->No. of individual stormwater monitoring data>A value of item data; />Represents->No. of individual stormwater monitoring data>Personal area data->A value of item data; />Represents->All neighborhood data of individual stormwater monitoring data +.>Standard deviation of values of item data; />Representing absolute value symbols;
acquiring a plurality of suspected abnormal data of each rainwater monitoring data according to the abnormal degree of each data of each rainwater monitoring data; obtaining an abnormality factor of each piece of rainwater monitoring data according to the abnormality degree of each piece of suspected abnormality data in each piece of rainwater monitoring data, wherein the abnormality factor of each piece of rainwater monitoring data is obtained according to the abnormality degree of each piece of suspected abnormality data in each piece of rainwater monitoring data, and the method comprises the following specific steps:
the abnormality degree of the data corresponding to each piece of suspected abnormal data in each piece of rainwater monitoring data is used as the abnormality degree of each piece of suspected abnormal data in each piece of rainwater monitoring data;
in the method, in the process of the invention,represents->Abnormal factors of the rainwater monitoring data; />Represents->The number of items of suspected abnormal data of the rainwater monitoring data; />Represents->No. of individual stormwater monitoring data>The degree of abnormality of the item of suspected abnormal data;
according to the abnormality factor and the initial abnormality degree of each rainwater monitoring data, acquiring the actual abnormality degree of each rainwater monitoring data, wherein the actual abnormality degree of each rainwater monitoring data is acquired according to the abnormality factor and the initial abnormality degree of each rainwater monitoring data, and the specific steps are as follows:
in the method, in the process of the invention,indicate->Actual anomaly degree of each rainwater monitoring data; />Represents->Initial anomaly degree of each rainwater monitoring data;
and acquiring abnormal data in the rainwater monitoring data according to the actual abnormal degree of each rainwater monitoring data.
2. The method for analyzing data of a sponge city rainwater collection system according to claim 1, wherein the step of obtaining neighborhood data of each rainwater monitoring data according to a distance between rainwater monitoring data comprises the following specific steps:
presetting neighborhood data quantityMapping each item of rainwater monitoring data into a multi-dimensional coordinate system, and acquiring and +.>The rainwater monitoring data are nearest +.>Rainwater monitoring data, designated->Neighborhood data of individual stormwater monitoring data.
3. The method for analyzing data of a sponge city rainwater collection system according to claim 2, wherein the step of obtaining the initial anomaly degree of each rainwater monitoring data according to the distance between each rainwater monitoring data and the neighborhood data of each rainwater monitoring data comprises the following specific steps:
in a multidimensional coordinate system, obtain the firstRainwater monitoring data and->The distance between each neighborhood data of each rainwater monitoring data is set as the maximum distance +.>The initial degree of anomaly of the individual stormwater monitoring data.
4. The method for analyzing data of a sponge city rainwater collection system according to claim 1, wherein the step of obtaining a plurality of suspected abnormal data of each rainwater monitoring data according to the degree of abnormality of each data of each rainwater monitoring data comprises the following specific steps:
presetting an abnormality degree thresholdIf->No. of individual stormwater monitoring data>The degree of abnormality of the item data is greater than or equal to the threshold degree of abnormality +.>Will->No. of individual stormwater monitoring data>Item data is marked as->Obtaining a suspected abnormal data of the rainwater monitoring data to obtain +.>Several items of suspected anomaly data for the individual stormwater monitoring data.
5. The method for analyzing data of a sponge city rainwater collection system according to claim 1, wherein the step of acquiring a plurality of abnormal data in the rainwater monitoring data according to the actual degree of abnormality of each rainwater monitoring data comprises the following specific steps:
presetting an actual abnormality degree thresholdIf->The actual abnormality degree of the individual rainwater monitoring data is greater than or equal to the actual abnormality degree threshold +.>Then->The rainwater monitoring data are abnormal data in the rainwater monitoring data, and the abnormal data in the rainwater monitoring data are obtained.
6. The method for analyzing data of a sponge city rainwater collecting system according to claim 1, wherein the step of acquiring rainwater monitoring data comprises the following specific steps:
acquiring a plurality of rainwater monitoring data in a period of time in a rainwater collecting system, wherein each rainwater monitoring data comprises a plurality of items of data: the rainwater collection amount, the rainwater PH value, the rainwater turbidity, the rainwater heavy metal content and the rainwater organic matter content.
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