CN116485034B - Urban drainage prediction method and system - Google Patents
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Abstract
The application relates to a city water discharge prediction method and a system, belonging to the technical field of water treatment, wherein the method comprises the steps of obtaining first data information and second data information, and preprocessing the first data information and the second data information to obtain a first data sample and a second data sample; constructing a city water drainage prediction model based on the first data sample and the second data sample; and inputting the third data information acquired in real time into the urban drainage prediction model to obtain a corresponding output result so as to be used for predicting urban drainage. The application can accurately predict the urban pipeline drainage by combining the drainage predicted value and the drainage pipeline related data, thereby predicting the urban waterlogging disasters in advance, and enabling the related personnel in the city to timely make measures for coping with the disasters.
Description
Technical Field
The application relates to the technical field of water treatment, in particular to a city water discharge prediction method and system.
Background
The existing waterlogging early warning system is obtained by deploying detection electronic equipment to collect information in an area where water accumulation is easy to form and comprehensively processing the information, but the early warning system can not collect the information until precipitation begins, however, in reality, strong precipitation often has burstiness, water accumulation is caused in a short time to form urban waterlogging, in addition, the current rainstorm waterlogging assessment model is mostly based on a hydrodynamic method, the operation time is too long, and because the structural data of a drainage pipeline are difficult to obtain, the pipeline accumulation condition is difficult to determine, the water drainage quantity of the urban pipeline cannot be estimated accurately in advance due to the uncertain conditions such as manual pumping and the like.
Therefore, there is a need to propose a method capable of predicting urban pipeline displacement in advance so that urban related personnel can cope with such disasters in advance in time.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a method and system for predicting urban drainage.
In one aspect, there is provided a city water displacement prediction method, the method comprising:
acquiring first data information and second data information, preprocessing the first data information and the second data information to obtain a first data sample and a second data sample, wherein the first data information comprises: a sewage amount, a precipitation amount, and a displacement amount in a plurality of target time periods, the second data information including: data obtained based on a topological model of the urban drainage system;
constructing a city water drainage prediction model based on the first data sample and the second data sample;
and inputting third data information acquired in real time into the urban drainage prediction model to obtain a corresponding output result for predicting urban drainage, wherein the third data information comprises change data in the urban drainage prediction model.
Optionally, preprocessing the first data information includes:
Performing data cleaning on the first data information, wherein the data cleaning comprises missing value processing, outlier processing and repeated value processing;
and carrying out data integration on the data information obtained after data cleaning to generate a data set with unified and standardized format, namely the first data sample.
Optionally, the building of the topology model of the urban drainage system includes:
the method comprises the steps of collecting relevant data information of the urban drainage pipeline, wherein the relevant data information of the urban drainage pipeline comprises the following steps: pipeline process information, pipeline management information and environment information where the pipeline is located;
extracting inflow points and outflow points of the urban drainage pipelines and crossing points among all pipelines in the urban drainage pipeline related data information;
calculating the drainage risk value of the pipeline between every two intersection points based on the related data information of the urban drainage pipeline;
and constructing the topology model of the urban drainage system in a three-dimensional simulation system according to the related data information of the urban drainage pipeline and the drainage risk value.
Optionally, the calculating the drainage risk value of the pipeline between every two intersections based on the related data information of the urban drainage pipeline includes:
defining the state set corresponding to the related data information of the urban drainage pipeline as The probability of activating the risk of draining per state is +.>The risk state occurrence frequency corresponding to the risk probability being larger than the preset threshold value is as followsAnd the sum of the probabilities is equal to 1, and the calculation formula of the drainage risk value of the pipeline between every two crossing points is as follows:
wherein ,represents a drainage risk value,/->Representing the number of risk status occurrences,/->A severity assignment indicating a risk status correspondence, +.>Represents the frequency of occurrence of the risk state->Representing constant coefficients, ++>Representing the probability of the target state triggering the drainage risk, +.>Fitting coefficients representing pipeline process information, < >>Representing the influence value of random disturbance factor,/-, for>Representing a correction function;
the calculation formula of the fitting coefficient of the pipeline process information comprises the following steps:
wherein ,、/>、/>respectively representing the circumference of the cross section of the pipe, the length of the pipe between two crossing points and the roughness coefficient of the pipe, n representing the age,/->Indicating the initial flow +.>Representing a loss function->A function representing a change in the state of the pipe,representing the fitting function value.
Optionally, preprocessing the second data information includes:
sequencing and marking the drainage risk values in sequence from large to small, and forming a one-to-one mapping relation between marking data and the drainage risk values;
Assigning values to the topological model of the urban drainage system based on the drainage risk values, and adjusting coordinate points of a plurality of target pipelines in the three-dimensional simulation system;
and extracting a plurality of target pipeline intermediate points, and connecting the plurality of target pipeline intermediate points in sequence based on the marking data to generate a second topological structure.
Optionally, the method further comprises: and obtaining the sum of the first slopes between the target pipeline and the adjacent pipeline in the topological model of the urban drainage system and the sum of the second slopes between the target pipeline and the adjacent pipeline in the second topological structure, and generating a corresponding data set, namely the second data sample.
Optionally, the constructing the urban drainage prediction model based on the first data sample and the second data sample includes:
dividing the first data sample and the second data sample into a training sample, a test sample and a verification sample according to a preset proportion;
training a pre-constructed urban drainage prediction model by using the training sample, and evaluating the prediction precision of the urban drainage prediction model obtained by training by using the test sample and the verification sample;
and stopping training when the prediction precision of the urban drainage prediction model reaches a preset standard, and obtaining a final urban drainage prediction model.
Optionally, the final urban drainage prediction model includes:
wherein ,indicating the predicted drainage flow value +.>Indicates the number of the water drainage pre-menstrual crossing points, +.>Indicating the total number of intersections of the urban drainage system, < >>Representing a compensation function->Indicating the assigned value of the target time period,/->Indicating predicted precipitation, < >>Indicating predicted sewage discharge amount>Representing a second slope, +.>Representing a first slope.
Optionally, inputting the third data information collected in real time to the final urban drainage prediction model to obtain a corresponding output result, so as to be used for predicting urban drainage, where the step of predicting urban drainage includes:
acquiring an absolute value of a difference between the predicted drainage flow value and the drainage in the target time period;
and sending early warning information to the user terminal when the absolute value of the difference is detected to be larger than a preset threshold value and the predicted drainage flow value is larger than the drainage in the target time period.
In another aspect, there is provided a municipal drainage prediction system, the system comprising:
the preprocessing module is used for acquiring first data information and second data information, preprocessing the first data information and the second data information to obtain a first data sample and a second data sample, and the first data information comprises: a sewage amount, a precipitation amount, and a displacement amount in a plurality of target time periods, the second data information including: data obtained based on a topological model of the urban drainage system;
The construction module is used for constructing an urban drainage prediction model based on the first data sample and the second data sample;
the prediction module is used for inputting third data information acquired in real time into the urban drainage prediction model to obtain a corresponding output result so as to be used for predicting urban drainage, and the third data information comprises change data in the urban drainage prediction model.
In yet another aspect, a computer device is provided comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the steps of:
acquiring first data information and second data information, preprocessing the first data information and the second data information to obtain a first data sample and a second data sample, wherein the first data information comprises: a sewage amount, a precipitation amount, and a displacement amount in a plurality of target time periods, the second data information including: data obtained based on a topological model of the urban drainage system;
constructing a city water drainage prediction model based on the first data sample and the second data sample;
and inputting third data information acquired in real time into the urban drainage prediction model to obtain a corresponding output result for predicting urban drainage, wherein the third data information comprises change data in the urban drainage prediction model.
In yet another aspect, a computer readable storage medium is provided, having stored thereon a computer program which when executed by a processor performs the steps of:
acquiring first data information and second data information, preprocessing the first data information and the second data information to obtain a first data sample and a second data sample, wherein the first data information comprises: a sewage amount, a precipitation amount, and a displacement amount in a plurality of target time periods, the second data information including: data obtained based on a topological model of the urban drainage system;
constructing a city water drainage prediction model based on the first data sample and the second data sample;
and inputting third data information acquired in real time into the urban drainage prediction model to obtain a corresponding output result for predicting urban drainage, wherein the third data information comprises change data in the urban drainage prediction model.
The urban drainage prediction method, system, computer equipment and storage medium, wherein the method comprises the following steps: acquiring first data information and second data information, preprocessing the first data information and the second data information to obtain a first data sample and a second data sample, wherein the first data information comprises: a sewage amount, a precipitation amount, and a displacement amount in a plurality of target time periods, the second data information including: data obtained based on a topological model of the urban drainage system; constructing a city water drainage prediction model based on the first data sample and the second data sample; the method and the system can accurately predict the urban pipeline drainage by combining the drainage prediction value and the drainage pipeline related data, so that the urban waterlogging disaster is predicted in advance, and related personnel in the city can timely make measures for coping with the disaster.
Drawings
FIG. 1 is a diagram of an application environment of a city water displacement prediction method in one embodiment;
FIG. 2 is a flow chart of a city water displacement prediction method in one embodiment;
FIG. 3 is a block diagram of a city water displacement prediction system in one embodiment;
fig. 4 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
It should be understood that in the description of the application, unless the context clearly requires otherwise, the words "comprise," "comprising," and the like throughout the description are to be construed in an inclusive sense rather than an exclusive or exhaustive sense; that is, it is the meaning of "including but not limited to".
It should also be appreciated that the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Furthermore, in the description of the present application, unless otherwise indicated, the meaning of "a plurality" is two or more.
It should be noted that the terms "S1", "S2", and the like are used for the purpose of describing the steps only, and are not intended to be construed to be specific as to the order or sequence of steps, nor are they intended to limit the present application, which is merely used to facilitate the description of the method of the present application, and are not to be construed as indicating the sequence of steps. In addition, the technical solutions of the embodiments may be combined with each other, but it is necessary to base that the technical solutions can be realized by those skilled in the art, and when the technical solutions are contradictory or cannot be realized, the combination of the technical solutions should be considered to be absent and not within the scope of protection claimed in the present application.
The urban drainage prediction method provided by the application can be applied to an application environment shown in figure 1. The terminal 102 communicates with a data processing platform disposed on the server 104 through a network, where the terminal 102 may be, but is not limited to, various personal computers, notebook computers, smartphones, tablet computers, and portable wearable devices, and the server 104 may be implemented by a stand-alone server or a server cluster composed of a plurality of servers.
Example 1: in one embodiment, as shown in fig. 2, there is provided a city water discharge prediction method, which is illustrated by taking a terminal in fig. 1 as an example, including the steps of:
s1: acquiring first data information and second data information, preprocessing the first data information and the second data information to obtain a first data sample and a second data sample, wherein the first data information comprises: a sewage amount, a precipitation amount, and a displacement amount in a plurality of target time periods, the second data information including: based on the data obtained by the topological model of the urban drainage system.
It should be noted that the first data information and the second data information refer to history data pre-stored in a database, and the target period may refer to a day, a month, or the like in one year.
Further, preprocessing the first data information includes:
performing data cleaning on the first data information, wherein the data cleaning comprises missing value processing, outlier processing and repeated value processing;
and carrying out data integration on the data information obtained after data cleaning to generate a data set with unified and standardized format, namely the first data sample.
Specifically, the data cleaning is to fill in missing values, smooth or delete outliers and repeated values, correct data inconsistency to achieve the purpose of cleaning, process data with problems in the data, combine a plurality of data source data after cleaning, and generate a data set with unified and standardized format.
Furthermore, the construction of the topological model of the urban drainage system comprises the following steps:
the method comprises the steps of collecting relevant data information of the urban drainage pipeline, wherein the relevant data information of the urban drainage pipeline comprises the following steps: pipeline process information, pipeline management information, pipeline environment information, and pipeline environment information, wherein the pipeline process information can comprise pipeline length, roughness and the like, the pipeline management information can comprise service life, maintenance times and the like, and the pipeline environment information comprises humidity, temperature, corrosion and the like;
extracting inflow points and outflow points of the urban drainage pipelines and crossing points among all pipelines in the urban drainage pipeline related data information;
calculating the drainage risk value of the pipeline between every two intersection points based on the related data information of the urban drainage pipeline;
and constructing the topology model of the urban drainage system in a three-dimensional simulation system according to the related data information of the urban drainage pipeline and the drainage risk value.
Specifically, based on the related data information of the urban drainage pipeline, calculating the drainage risk value of the pipeline between every two intersection points comprises:
defining the state set corresponding to the related data information of the urban drainage pipeline asThe probability of activating the risk of draining per state is +.>The risk state occurrence frequency corresponding to the risk probability being larger than the preset threshold value is as followsAnd the sum of the probabilities is equal to 1, and the calculation formula of the drainage risk value of the pipeline between every two crossing points is as follows:
wherein ,represents a drainage risk value,/->Representing the number of risk status occurrences,/->A severity assignment indicating a risk status correspondence, +.>Represents the frequency of occurrence of the risk state->Representing constant coefficients, ++>Representing the probability of the target state triggering the drainage risk, +.>Fitting coefficients representing pipeline process information, < >>Representing the influence value of random disturbance factor,/-, for>Representing a correction function;
the calculation formula of the fitting coefficient of the pipeline process information comprises the following steps:
wherein ,、/>、/>respectively representing the circumference of the cross section of the pipe, the length of the pipe between two crossing points and the roughness coefficient of the pipe, n representing the age,/->Indicating the initial flow +.>Representing a loss function->A function representing a change in the state of the pipe,representing the fitting function value.
Further, preprocessing the second data information includes:
sequencing and marking the drainage risk values in sequence from large to small, and forming a one-to-one mapping relation between marking data and the drainage risk values for subsequent data extraction;
assigning values to the topological model of the urban drainage system based on the drainage risk values, and adjusting coordinate points of a plurality of target pipelines in the three-dimensional simulation system, wherein the geographic coordinates of the target pipelines are taken as (x, y) coordinates in the three-dimensional simulation system, the drainage risk values corresponding to the target pipelines are taken as z coordinates, so that corresponding (x, y, z) coordinate points are generated, and each coordinate point is connected with the existing urban pipeline connection condition to generate a corresponding topological model of the urban drainage system;
and extracting a plurality of target pipeline intermediate points, connecting the plurality of target pipeline intermediate points in sequence based on the marking data to generate a second topological structure, and connecting the three pipelines according to the drainage risk value to generate the second topological structure if the drainage risk value of the first pipeline is 5, the drainage risk value of the second pipeline is 4 and the drainage risk value of the third pipeline is 3.
Obtaining a first slope sum of a target pipeline between adjacent pipelines in the urban drainage system topology model and a second slope sum between adjacent pipelines in the second topology structure, and generating a corresponding data set, namely the second data sample, wherein if two ends of the target pipeline are respectively connected with one pipeline, namely two pipelines are connected, the slope sum between the two pipelines and the target pipeline is calculated, and the slope calculation method comprises the following steps: and extracting z values in the two pipeline coordinate points, connecting the two pipeline coordinate points, calculating the slope of the connecting line, namely, a corresponding first slope or second slope, and combining the first slope and the second slope to generate a data set.
S2: and constructing a city water discharge prediction model based on the first data sample and the second data sample.
It should be noted that this step specifically includes:
dividing the first data sample and the second data sample into a training sample, a test sample and a verification sample according to a preset proportion, wherein the preset proportion is 8:1:1 in an exemplary manner;
training a pre-constructed urban drainage prediction model by using the training sample, and evaluating the prediction precision of the urban drainage prediction model obtained by training by using the test sample and the verification sample;
When the prediction accuracy of the urban drainage prediction model reaches a preset standard, the preset standard can be set according to actual requirements, training is stopped, and a final urban drainage prediction model is obtained.
Further, the final urban drainage prediction model includes:
wherein ,indicating the predicted drainage flow value +.>Indicates the number of the water drainage pre-menstrual crossing points, +.>Indicating the total number of intersections of the urban drainage system, < >>Representing a compensation function->Indicating the assigned value of the target time period,/->Indicating predicted precipitation, < >>Indicating predicted sewage discharge amount>Representing a second slope, +.>Representing a first slope.
S3: and inputting third data information acquired in real time into the urban drainage prediction model to obtain a corresponding output result for predicting urban drainage, wherein the third data information comprises change data in the urban drainage prediction model.
It should be noted that, the change data in the urban drainage prediction model may be predicted precipitation, predicted sewage discharge, etc., and the steps specifically include:
acquiring an absolute value of a difference between the predicted drainage flow value and the drainage in the target time period;
And in response to detecting that the absolute value of the difference is larger than a preset threshold value and the predicted drainage flow value is larger than the drainage amount in the target time period, sending early warning information to the user terminal so as to inform relevant personnel in the city of timely making measures for coping with the disasters.
In the urban drainage prediction method, the method comprises the following steps: acquiring first data information and second data information, preprocessing the first data information and the second data information to obtain a first data sample and a second data sample, wherein the first data information comprises: a sewage amount, a precipitation amount, and a displacement amount in a plurality of target time periods, the second data information including: data obtained based on a topological model of the urban drainage system; constructing a city water drainage prediction model based on the first data sample and the second data sample; the method and the system can accurately predict the urban pipeline drainage by combining the drainage prediction value and the drainage pipeline related data, so that the urban waterlogging disaster is predicted in advance, and related personnel in the city can timely make measures for coping with the disaster.
It should be understood that, although the steps in the flowchart of fig. 2 are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 2 may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of the sub-steps or stages of other steps or other steps.
Example 2: in one embodiment, as shown in fig. 3, there is provided a municipal drainage prediction system, comprising: the system comprises a preprocessing module, a construction module and a prediction module, wherein:
the preprocessing module is used for acquiring first data information and second data information, preprocessing the first data information and the second data information to obtain a first data sample and a second data sample, and the first data information comprises: a sewage amount, a precipitation amount, and a displacement amount in a plurality of target time periods, the second data information including: data obtained based on a topological model of the urban drainage system;
The construction module is used for constructing an urban drainage prediction model based on the first data sample and the second data sample;
the prediction module is used for inputting third data information acquired in real time into the urban drainage prediction model to obtain a corresponding output result so as to be used for predicting urban drainage, and the third data information comprises change data in the urban drainage prediction model.
As a preferred implementation manner, in the embodiment of the present invention, the preprocessing module is specifically configured to:
performing data cleaning on the first data information, wherein the data cleaning comprises missing value processing, outlier processing and repeated value processing;
and carrying out data integration on the data information obtained after data cleaning to generate a data set with unified and standardized format, namely the first data sample.
As a preferred implementation manner, in the embodiment of the present invention, the preprocessing module is specifically further configured to:
the method comprises the steps of collecting relevant data information of the urban drainage pipeline, wherein the relevant data information of the urban drainage pipeline comprises the following steps: pipeline process information, pipeline management information and environment information where the pipeline is located;
extracting inflow points and outflow points of the urban drainage pipelines and crossing points among all pipelines in the urban drainage pipeline related data information;
Calculating the drainage risk value of the pipeline between every two intersection points based on the related data information of the urban drainage pipeline;
and constructing the topology model of the urban drainage system in a three-dimensional simulation system according to the related data information of the urban drainage pipeline and the drainage risk value.
As a preferred implementation manner, in the embodiment of the present invention, the preprocessing module is specifically further configured to:
defining the state set corresponding to the related data information of the urban drainage pipeline asThe probability of activating the risk of draining per state is +.>The risk state occurrence frequency corresponding to the risk probability being larger than the preset threshold value is as followsAnd the sum of the probabilities is equal to 1, and the calculation formula of the drainage risk value of the pipeline between every two crossing points is as follows:
wherein ,represents a drainage risk value,/->Representing the number of risk status occurrences,/->A severity assignment indicating a risk status correspondence, +.>Represents the frequency of occurrence of the risk state->Representing constant coefficients, ++>Representing the probability of the target state triggering the drainage risk, +.>Fitting coefficients representing pipeline process information, < >>Representing the influence value of random disturbance factor,/-, for>Representing a correction function;
the calculation formula of the fitting coefficient of the pipeline process information comprises the following steps:
wherein ,、/>、/>respectively representing the circumference of the cross section of the pipe, the length of the pipe between two crossing points and the roughness coefficient of the pipe, n representing the age,/->Indicating the initial flow +.>Representing a loss function->A function representing a change in the state of the pipe,representing the fitting function value.
As a preferred implementation manner, in the embodiment of the present invention, the preprocessing module is specifically further configured to:
sequencing and marking the drainage risk values in sequence from large to small, and forming a one-to-one mapping relation between marking data and the drainage risk values;
assigning values to the topological model of the urban drainage system based on the drainage risk values, and adjusting coordinate points of a plurality of target pipelines in the three-dimensional simulation system;
and extracting a plurality of target pipeline intermediate points, and connecting the plurality of target pipeline intermediate points in sequence based on the marking data to generate a second topological structure.
As a preferred implementation manner, in the embodiment of the present invention, the preprocessing module is specifically further configured to:
and obtaining the sum of the first slopes between the target pipeline and the adjacent pipeline in the topological model of the urban drainage system and the sum of the second slopes between the target pipeline and the adjacent pipeline in the second topological structure, and generating a corresponding data set, namely the second data sample.
As a preferred implementation manner, in the embodiment of the present invention, the construction module is specifically configured to:
dividing the first data sample and the second data sample into a training sample, a test sample and a verification sample according to a preset proportion;
training a pre-constructed urban drainage prediction model by using the training sample, and evaluating the prediction precision of the urban drainage prediction model obtained by training by using the test sample and the verification sample;
stopping training when the prediction precision of the urban drainage prediction model reaches a preset standard to obtain a final urban drainage prediction model;
wherein the final urban drainage prediction model comprises:
wherein ,indicating the predicted drainage flow value +.>Indicates the number of the water drainage pre-menstrual crossing points, +.>Indicating the total number of intersections of the urban drainage system, < >>Representing a compensation function->Indicating the assigned value of the target time period,/->Indicating predicted precipitation, < >>Indicating predicted sewage discharge amount>Representing a second slope, +.>Representing a first slope.
As a preferred implementation manner, in the embodiment of the present invention, the prediction module is specifically configured to:
acquiring an absolute value of a difference between the predicted drainage flow value and the drainage in the target time period;
And sending early warning information to the user terminal when the absolute value of the difference is detected to be larger than a preset threshold value and the predicted drainage flow value is larger than the drainage in the target time period.
For specific limitations on the urban drainage prediction system, reference may be made to the above limitation on the urban drainage prediction method, and no further description is given here. The various modules in the urban drainage prediction system described above may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
Example 3: in one embodiment, a computer device is provided, which may be a terminal, and the internal structure of which may be as shown in fig. 4. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program when executed by a processor implements a city water displacement prediction method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by persons skilled in the art that the architecture shown in fig. 4 is merely a block diagram of some of the architecture relevant to the present inventive arrangements and is not limiting as to the computer device to which the present inventive arrangements are applicable, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the steps of when executing the computer program:
s1: acquiring first data information and second data information, preprocessing the first data information and the second data information to obtain a first data sample and a second data sample, wherein the first data information comprises: a sewage amount, a precipitation amount, and a displacement amount in a plurality of target time periods, the second data information including: data obtained based on a topological model of the urban drainage system;
s2: constructing a city water drainage prediction model based on the first data sample and the second data sample;
s3: and inputting third data information acquired in real time into the urban drainage prediction model to obtain a corresponding output result for predicting urban drainage, wherein the third data information comprises change data in the urban drainage prediction model.
In one embodiment, the processor when executing the computer program further performs the steps of:
performing data cleaning on the first data information, wherein the data cleaning comprises missing value processing, outlier processing and repeated value processing;
and carrying out data integration on the data information obtained after data cleaning to generate a data set with unified and standardized format, namely the first data sample.
In one embodiment, the processor when executing the computer program further performs the steps of:
the method comprises the steps of collecting relevant data information of the urban drainage pipeline, wherein the relevant data information of the urban drainage pipeline comprises the following steps: pipeline process information, pipeline management information and environment information where the pipeline is located;
extracting inflow points and outflow points of the urban drainage pipelines and crossing points among all pipelines in the urban drainage pipeline related data information;
calculating the drainage risk value of the pipeline between every two intersection points based on the related data information of the urban drainage pipeline;
and constructing the topology model of the urban drainage system in a three-dimensional simulation system according to the related data information of the urban drainage pipeline and the drainage risk value.
In one embodiment, the processor when executing the computer program further performs the steps of:
Defining the state set corresponding to the related data information of the urban drainage pipeline asThe probability of activating the risk of draining per state is +.>The risk state occurrence frequency corresponding to the risk probability being larger than the preset threshold value is as followsAnd the sum of the probabilities is equal to 1, and the calculation formula of the drainage risk value of the pipeline between every two crossing points is as follows:
wherein ,represents a drainage risk value,/->Representing the number of risk status occurrences,/->A severity assignment indicating a risk status correspondence, +.>Represents the frequency of occurrence of the risk state->Representing constant coefficients, ++>Representing the probability of the target state triggering the drainage risk, +.>Fitting coefficients representing pipeline process information, < >>Representing the influence value of random disturbance factor,/-, for>Representing a correction function;
the calculation formula of the fitting coefficient of the pipeline process information comprises the following steps:
/>
wherein ,、/>、/>respectively representing the circumference of the cross section of the pipe, the length of the pipe between two crossing points and the roughness coefficient of the pipe, n representing the age,/->Indicating the initial flow +.>Representing a loss function->A function representing a change in the state of the pipe,representing the fitting function value.
In one embodiment, the processor when executing the computer program further performs the steps of:
sequencing and marking the drainage risk values in sequence from large to small, and forming a one-to-one mapping relation between marking data and the drainage risk values;
Assigning values to the topological model of the urban drainage system based on the drainage risk values, and adjusting coordinate points of a plurality of target pipelines in the three-dimensional simulation system;
and extracting a plurality of target pipeline intermediate points, and connecting the plurality of target pipeline intermediate points in sequence based on the marking data to generate a second topological structure.
In one embodiment, the processor when executing the computer program further performs the steps of:
and obtaining the sum of the first slopes between the target pipeline and the adjacent pipeline in the topological model of the urban drainage system and the sum of the second slopes between the target pipeline and the adjacent pipeline in the second topological structure, and generating a corresponding data set, namely the second data sample.
In one embodiment, the processor when executing the computer program further performs the steps of:
dividing the first data sample and the second data sample into a training sample, a test sample and a verification sample according to a preset proportion;
training a pre-constructed urban drainage prediction model by using the training sample, and evaluating the prediction precision of the urban drainage prediction model obtained by training by using the test sample and the verification sample;
stopping training when the prediction precision of the urban drainage prediction model reaches a preset standard to obtain a final urban drainage prediction model;
Wherein the final urban drainage prediction model comprises:
wherein ,indicating predicted drainageFlow value,/->Indicates the number of the water drainage pre-menstrual crossing points, +.>Indicating the total number of intersections of the urban drainage system, < >>Representing a compensation function->Indicating the assigned value of the target time period,/->Indicating predicted precipitation, < >>Indicating predicted sewage discharge amount>Representing a second slope, +.>Representing a first slope.
In one embodiment, the processor when executing the computer program further performs the steps of:
acquiring an absolute value of a difference between the predicted drainage flow value and the drainage in the target time period;
and sending early warning information to the user terminal when the absolute value of the difference is detected to be larger than a preset threshold value and the predicted drainage flow value is larger than the drainage in the target time period.
Example 4: in one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
s1: acquiring first data information and second data information, preprocessing the first data information and the second data information to obtain a first data sample and a second data sample, wherein the first data information comprises: a sewage amount, a precipitation amount, and a displacement amount in a plurality of target time periods, the second data information including: data obtained based on a topological model of the urban drainage system;
S2: constructing a city water drainage prediction model based on the first data sample and the second data sample;
s3: and inputting third data information acquired in real time into the urban drainage prediction model to obtain a corresponding output result for predicting urban drainage, wherein the third data information comprises change data in the urban drainage prediction model.
In one embodiment, the computer program when executed by the processor further performs the steps of:
performing data cleaning on the first data information, wherein the data cleaning comprises missing value processing, outlier processing and repeated value processing;
and carrying out data integration on the data information obtained after data cleaning to generate a data set with unified and standardized format, namely the first data sample.
In one embodiment, the computer program when executed by the processor further performs the steps of:
the method comprises the steps of collecting relevant data information of the urban drainage pipeline, wherein the relevant data information of the urban drainage pipeline comprises the following steps: pipeline process information, pipeline management information and environment information where the pipeline is located;
extracting inflow points and outflow points of the urban drainage pipelines and crossing points among all pipelines in the urban drainage pipeline related data information;
Calculating the drainage risk value of the pipeline between every two intersection points based on the related data information of the urban drainage pipeline;
and constructing the topology model of the urban drainage system in a three-dimensional simulation system according to the related data information of the urban drainage pipeline and the drainage risk value.
In one embodiment, the computer program when executed by the processor further performs the steps of:
defining the state set corresponding to the related data information of the urban drainage pipeline asThe probability of activating the risk of draining per state is +.>The risk state occurrence frequency corresponding to the risk probability being larger than the preset threshold value is as followsAnd the sum of the probabilities is equal to 1, and the calculation formula of the drainage risk value of the pipeline between every two crossing points is as follows:
wherein ,represents a drainage risk value,/->Representing the number of risk status occurrences,/->A severity assignment indicating a risk status correspondence, +.>Represents the frequency of occurrence of the risk state->Representing constant coefficients, ++>Representing the probability of the target state triggering the drainage risk, +.>Fitting coefficients representing pipeline process information, < >>Representing the influence value of random disturbance factor,/-, for>Representing a correction function;
the calculation formula of the fitting coefficient of the pipeline process information comprises the following steps:
wherein ,、/>、/>respectively representing the circumference of the cross section of the pipe, the length of the pipe between two crossing points and the roughness coefficient of the pipe, n representing the age,/->Indicating the initial flow +.>Representing a loss function->A function representing a change in the state of the pipe,representing the fitting function value.
In one embodiment, the computer program when executed by the processor further performs the steps of:
sequencing and marking the drainage risk values in sequence from large to small, and forming a one-to-one mapping relation between marking data and the drainage risk values;
assigning values to the topological model of the urban drainage system based on the drainage risk values, and adjusting coordinate points of a plurality of target pipelines in the three-dimensional simulation system;
and extracting a plurality of target pipeline intermediate points, and connecting the plurality of target pipeline intermediate points in sequence based on the marking data to generate a second topological structure.
In one embodiment, the computer program when executed by the processor further performs the steps of:
and obtaining the sum of the first slopes between the target pipeline and the adjacent pipeline in the topological model of the urban drainage system and the sum of the second slopes between the target pipeline and the adjacent pipeline in the second topological structure, and generating a corresponding data set, namely the second data sample.
In one embodiment, the computer program when executed by the processor further performs the steps of:
dividing the first data sample and the second data sample into a training sample, a test sample and a verification sample according to a preset proportion;
training a pre-constructed urban drainage prediction model by using the training sample, and evaluating the prediction precision of the urban drainage prediction model obtained by training by using the test sample and the verification sample;
stopping training when the prediction precision of the urban drainage prediction model reaches a preset standard to obtain a final urban drainage prediction model;
wherein the final urban drainage prediction model comprises:
wherein ,indicating the predicted drainage flow value +.>Indicates the number of the water drainage pre-menstrual crossing points, +.>Representing the total number of intersections of urban drainage systems，/>Representing a compensation function->Indicating the assigned value of the target time period,/->Indicating predicted precipitation, < >>Indicating predicted sewage discharge amount>Representing a second slope, +.>Representing a first slope.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring an absolute value of a difference between the predicted drainage flow value and the drainage in the target time period;
And sending early warning information to the user terminal when the absolute value of the difference is detected to be larger than a preset threshold value and the predicted drainage flow value is larger than the drainage in the target time period.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application.
Claims (8)
1. A method for predicting urban drainage, the method comprising:
acquiring first data information and second data information, preprocessing the first data information and the second data information to obtain a first data sample and a second data sample, wherein the first data information comprises: a sewage amount, a precipitation amount, and a displacement amount in a plurality of target time periods, the second data information including: the method for generating the urban drainage system topology model comprises the following steps of: taking the geographic coordinates of the target pipeline as (x, y) coordinates in the three-dimensional simulation system, taking the drainage risk value corresponding to the target pipeline as z coordinates, generating corresponding (x, y, z) coordinate points, and connecting each coordinate point according to the existing urban pipeline connection condition to generate a corresponding urban drainage system topology model;
Constructing a city water drainage prediction model based on the first data sample and the second data sample;
inputting third data information acquired in real time into the urban drainage prediction model to obtain a corresponding output result for predicting urban drainage, wherein the third data information comprises change data in the urban drainage prediction model;
the constructing a city water displacement prediction model based on the first data sample and the second data sample comprises:
dividing the first data sample and the second data sample into a training sample, a test sample and a verification sample according to a preset proportion;
training a pre-constructed urban drainage prediction model by using the training sample, and evaluating the prediction precision of the urban drainage prediction model obtained by training by using the test sample and the verification sample;
stopping training when the prediction precision of the urban drainage prediction model reaches a preset standard to obtain a final urban drainage prediction model;
the final urban drainage prediction model includes:
wherein ,indicating the predicted drainage flow value +.>Indicates the number of the water drainage pre-menstrual crossing points, +.>Indicating the total number of intersections of the urban drainage system, < > >Representing a compensation function->Indicating the assigned value of the target time period,/->Indicating predicted precipitation, < >>Indicating predicted sewage discharge amount>Representing a second slope, +.>Representing a first slope;
the generation method of the first slope and the second slope comprises the following steps:
extracting a plurality of target pipeline intermediate points, and sequentially connecting the plurality of target pipeline intermediate points based on the marking data to generate a second topological structure;
extracting z values in coordinate points of a target pipeline and an adjacent pipeline in the urban drainage system topology model, connecting lines, and calculating the slope of the connecting lines to obtain corresponding first slopes;
and extracting z values in coordinate points of the target pipeline and the adjacent pipeline in the second topological structure, connecting the z values, and calculating the slope of the connecting line to obtain a corresponding second slope.
2. The urban drainage prediction method according to claim 1, wherein preprocessing the first data information comprises:
performing data cleaning on the first data information, wherein the data cleaning comprises missing value processing, outlier processing and repeated value processing;
and carrying out data integration on the data information obtained after data cleaning to generate a data set with unified and standardized format, namely the first data sample.
3. The urban drainage prediction method according to claim 2, wherein the construction of the urban drainage system topology model comprises:
the method comprises the steps of collecting relevant data information of the urban drainage pipeline, wherein the relevant data information of the urban drainage pipeline comprises the following steps: pipeline process information, pipeline management information and environment information where the pipeline is located;
extracting inflow points and outflow points of the urban drainage pipelines and crossing points among all pipelines in the urban drainage pipeline related data information;
calculating the drainage risk value of the pipeline between every two intersection points based on the related data information of the urban drainage pipeline;
and constructing the topology model of the urban drainage system in a three-dimensional simulation system according to the related data information of the urban drainage pipeline and the drainage risk value.
4. A city drainage prediction method according to claim 3, wherein said calculating a drainage risk value for a pipeline between each two intersections based on said city drainage pipeline related data information comprises:
defining the state set corresponding to the related data information of the urban drainage pipeline asThe probability of activating the risk of draining per state is +.>The risk state occurrence frequency corresponding to the risk probability being larger than the preset threshold value is as follows And the sum of the probabilities is equal to 1, and the calculation formula of the drainage risk value of the pipeline between every two crossing points is as follows:
wherein ,represents a drainage risk value,/->Representing the number of risk status occurrences,/->A severity assignment indicating a risk status correspondence, +.>Represents the frequency of occurrence of the risk state->Representing constant coefficients, ++>Representing the probability of the target state triggering the drainage risk, +.>Fitting coefficients representing pipeline process information, < >>Representing the influence value of random disturbance factor,/-, for>Representing a correction function;
the calculation formula of the fitting coefficient of the pipeline process information comprises the following steps:
wherein ,、/>、/>respectively representing the circumference of the cross section of the pipe, the length of the pipe between two crossing points and the roughness coefficient of the pipe, n representing the age,/->Indicating the initial flow +.>Representing a loss function->Function representing a change in the state of a pipeline, +.>Representing the fitting function value.
5. The urban drainage prediction method according to claim 4, wherein preprocessing the second data information comprises:
sequencing and marking the drainage risk values in sequence from large to small, and forming a one-to-one mapping relation between marking data and the drainage risk values;
assigning values to the topological model of the urban drainage system based on the drainage risk values, and adjusting coordinate points of a plurality of target pipelines in the three-dimensional simulation system;
And extracting a plurality of target pipeline intermediate points, and connecting the plurality of target pipeline intermediate points in sequence based on the marking data to generate a second topological structure.
6. The urban drainage prediction method according to claim 5, characterized in that it further comprises:
and obtaining the sum of the first slopes between the target pipeline and the adjacent pipeline in the topological model of the urban drainage system and the sum of the second slopes between the target pipeline and the adjacent pipeline in the second topological structure, and generating a corresponding data set, namely the second data sample.
7. The urban drainage prediction method according to claim 6, wherein inputting third data information acquired in real time to the final urban drainage prediction model, obtaining a corresponding output result for predicting urban drainage comprises:
acquiring an absolute value of a difference between the predicted drainage flow value and the drainage in the target time period;
and sending early warning information to the user terminal when the absolute value of the difference is detected to be larger than a preset threshold value and the predicted drainage flow value is larger than the drainage in the target time period.
8. A municipal drainage prediction system, the system comprising:
The preprocessing module is used for acquiring first data information and second data information, preprocessing the first data information and the second data information to obtain a first data sample and a second data sample, and the first data information comprises: a sewage amount, a precipitation amount, and a displacement amount in a plurality of target time periods, the second data information including: the method for generating the urban drainage system topology model comprises the following steps of: taking the geographic coordinates of the target pipeline as (x, y) coordinates in the three-dimensional simulation system, taking the drainage risk value corresponding to the target pipeline as z coordinates, generating corresponding (x, y, z) coordinate points, and connecting each coordinate point according to the existing urban pipeline connection condition to generate a corresponding urban drainage system topology model;
the construction module is used for constructing an urban drainage prediction model based on the first data sample and the second data sample;
the prediction module is used for inputting third data information acquired in real time into the urban drainage prediction model to obtain a corresponding output result so as to be used for predicting urban drainage, wherein the third data information comprises change data in the urban drainage prediction model;
The constructing a city water displacement prediction model based on the first data sample and the second data sample comprises:
dividing the first data sample and the second data sample into a training sample, a test sample and a verification sample according to a preset proportion;
training a pre-constructed urban drainage prediction model by using the training sample, and evaluating the prediction precision of the urban drainage prediction model obtained by training by using the test sample and the verification sample;
stopping training when the prediction precision of the urban drainage prediction model reaches a preset standard to obtain a final urban drainage prediction model;
the final urban drainage prediction model includes:
wherein ,indicating the predicted drainage flow value +.>Indicates the number of the water drainage pre-menstrual crossing points, +.>Indicating the total number of intersections of the urban drainage system, < >>Representing a compensation function->Indicating the assigned value of the target time period,/->Indicating predicted precipitation, < >>Indicating predicted sewage discharge amount>Representing a second slope, +.>Representing a first slope;
the generation method of the first slope and the second slope comprises the following steps:
extracting a plurality of target pipeline intermediate points, and sequentially connecting the plurality of target pipeline intermediate points based on the marking data to generate a second topological structure;
Extracting z values in coordinate points of a target pipeline and an adjacent pipeline in the urban drainage system topology model, connecting lines, and calculating the slope of the connecting lines to obtain corresponding first slopes;
and extracting z values in coordinate points of the target pipeline and the adjacent pipeline in the second topological structure, connecting the z values, and calculating the slope of the connecting line to obtain a corresponding second slope.
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