A water environment quality assessment method, system, equipment and program

Abstract

The present invention discloses a water environment quality assessment method, system, device, and program. The method comprises: obtaining observations of water area data to be tested; calculating the unfitness index of organisms within the water area based on the observations; calculating the influence transfer coefficient between any two sampling points within the water area based on the observations; and inputting the unfitness index of organisms within the water area and the influence transfer coefficient into a decision tree model, which outputs a health rating for the water area. The disclosed processing scheme enables timely and accurate tiered alerts upon changes in the water environment, enabling timely implementation of corresponding measures and preventing the spread of pollutants and property loss.

Description

Technical Field

[0001] The present invention relates to the technical field of water environment monitoring, and in particular to a water environment quality assessment method, system, equipment and program. Background Art

[0002] Existing technologies for water environment assessment overly rely on water quality sensors, which monitor a single dimension, focusing on a few common parameters such as DO, pH, and NH3-N. These sensors are unable to cover the diverse pollutants in complex water bodies and present significant limitations. This can lead to the omission of numerous potential pollutants, such as sudden heavy metal leaks and emerging organic pollutants, which can easily lead to missed detections and prevent pollution risks from being detected in a timely manner.

[0003] Furthermore, this technology simply equates parameter excursions with pollution incidents, ignoring the influence of natural factors. For example, storm runoff from heavy rain can temporarily alter water pH, and tidal fluctuations can cause dissolved oxygen to fluctuate. These normal, natural fluctuations are often misinterpreted as pollution, triggering unnecessary emergency responses. This wastes resources, undermines the credibility of the monitoring system, and negatively impacts the accuracy of water environment management.

[0004] Therefore, it can be seen that the above existing water environment assessment methods still have inconveniences and defects in use and are in urgent need of further improvement. How to create a new water environment quality assessment method has become a goal that the industry urgently needs to improve. Summary of the Invention

[0005] In view of this, an embodiment of the present disclosure provides a water environment quality assessment method, which at least partially solves the problems existing in the prior art.

[0006] In a first aspect, an embodiment of the present disclosure provides a method for assessing water environment quality, the method comprising the following steps:

[0007] Obtain the observation value of the water area data to be detected;

[0008] Calculating the discomfort index of organisms in the water area based on the observed values ​​of the water area data;

[0009] Calculating the influence transfer coefficient between any two sampling points in the water area through the observation values ​​of the water area data;

[0010] The discomfort index of the organisms in the water area and the influence transfer coefficient are input into a decision tree model, and the decision tree model outputs a health rating of the water area.

[0011] According to a specific implementation of the embodiment of the present disclosure, the data of the water area to be detected includes:

[0012] Water pH, dissolved oxygen content, nitrogen compound content, phosphorus compound content, water turbidity, types and number of plankton, types and number of benthic animals, activity of microbial biofilms and fish swimming trajectories.

[0013] According to a specific implementation of the embodiment of the present disclosure, the calculation of the discomfort index of organisms in the water area based on the observed values ​​of the water area data includes the following steps:

[0014] Defining a baseline of the health status of organisms in the water area through historical data; wherein the baseline of the health status is an indicator range for organisms in the water area to maintain a healthy state in the water area;

[0015] Calculating indicators of organisms in the water area based on the observed values ​​of the water area data; wherein the indicators of organisms in the water area include the Shannon-Wiener diversity index of algae, the biomass ratio of oligochaetes to chironomid larvae, the ATP content on microbial biofilms, and the vertical migration frequency of fish;

[0016] The discomfort index of the organisms in the water area is calculated based on the baseline of the health status of the organisms in the water area and the indicators of the organisms in the water area.

[0017] According to a specific implementation of the embodiment of the present disclosure, the calculation of the discomfort index of the organisms in the water body based on the baseline of the health status of the organisms in the water body and the indicators of the organisms in the water body respectively includes:

[0018] The relative offset of the water area data observation values ​​is calculated based on the following formula:

[0019] ;

[0020] in, is the relative offset; For groups Observations in waters, taxa Include , For plankton, For benthic organisms, For microbial biofilm, For fish; is the minimum value under the baseline of healthy condition; It is the maximum value under the baseline of healthy condition;

[0021] The relative offset is calculated based on the following formula: Truncated to the interval [0,1]:

[0022] ;

[0023] in, is the relative offset after truncation;

[0024] Calculate correction amount by ecological weight :

[0025] ;

[0026] in, is the correction amount; is the ecological weight;

[0027] When the observed value of the water area data is a positive indicator:

[0028] ;

[0029] When the observed value of the water area data is a negative indicator:

[0030] ;

[0031] in, The discomfort index.

[0032] According to a specific implementation of the embodiment of the present disclosure, calculating the influence transfer coefficient between any two sampling points in the water area through the observation value of the water area data includes:

[0033] The influence transfer coefficient between any two sampling points in the water area is calculated based on the following formula:

[0034] ;

[0035] in, is the influence transfer coefficient; For sampling points and sampling points The Euclidean distance between For sampling points and sampling points Projection distance between is a constant; is the standard deviation of pollutant spatial diffusion; is the river weight coefficient; is the river connectivity factor.

[0036] According to a specific implementation of the embodiment of the present disclosure, inputting the discomfort index of the organisms in the water area and the influence transfer coefficient into a decision tree model includes:

[0037] The decision tree model constructs a fusion feature based on the discomfort index of the organisms in the water area and the influence transfer coefficient; the fusion feature includes a spatiotemporal pressure index, a biological response difference, and a key indicator abnormality mark;

[0038] Determining whether the space-time pressure index is greater than a first threshold; when the space-time pressure index is greater than the first threshold, entering a high-pollution risk branch;

[0039] determining whether the benthic organism discomfort index is greater than a second threshold; triggering an acute pollution alarm when the benthic organism discomfort index is greater than the second threshold;

[0040] Determine whether the fluctuation of the fish swimming sequence is greater than a third threshold; when the fluctuation of the fish swimming sequence is greater than the third threshold, confirm that the fish swimming is abnormal.

[0041] According to a specific implementation of the embodiment of the present disclosure, the decision tree model outputs the health rating of the water area, including:

[0042] When the acute pollution alarm is triggered and fish swimming is abnormal, the output health level is severe pollution;

[0043] When the acute pollution alarm is triggered and the dissolved oxygen level is normal, the output health level is moderate pollution;

[0044] When the space-time pressure index is greater than the first threshold, the discomfort index of benthic organisms is less than the second threshold, and the fluctuation of fish swimming sequence is less than the third threshold, the output health level is slightly polluted.

[0045] In a second aspect, an embodiment of the present disclosure provides a water environment quality assessment system, the system comprising:

[0046] A data acquisition module is configured to obtain observation values ​​of water area data to be detected;

[0047] a calculation module configured to calculate an unsuitable index of organisms in the water area based on the observed values ​​of the water area data; and calculate an influence transfer coefficient between any two sampling points in the water area based on the observed values ​​of the water area data;

[0048] The health rating module is configured to input the discomfort index of the organisms in the water area and the influence transfer coefficient into a decision tree model, and the decision tree model outputs the health rating of the water area.

[0049] In a third aspect, an embodiment of the present disclosure further provides an electronic device, the electronic device comprising:

[0050] at least one processor; and,

[0051] a memory communicatively connected to the at least one processor; wherein,

[0052] The memory stores instructions that can be executed by the at least one processor. When the instructions are executed by the at least one processor, the at least one processor implements the water environment quality assessment method described in any one of the first aspect or any one of the implementations of the first aspect.

[0053] In a fourth aspect, an embodiment of the present disclosure further provides a non-transitory computer-readable storage medium, which stores computer instructions, and when the computer instructions are executed by at least one processor, the at least one processor executes the water environment quality assessment method in the aforementioned first aspect or any implementation of the first aspect.

[0054] In the fifth aspect, an embodiment of the present disclosure also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer executes the water environment quality assessment method in the aforementioned first aspect or any implementation of the first aspect.

[0055] The water environment quality assessment method in the disclosed embodiment quantifies the sub-health status through the BDI index; captures the sudden change of swimming speed through DTW behavior analysis, and accurately calculates the pollution diffusion path by combining the time influence transfer coefficient and the spatial influence transfer coefficient; and rates the health of the water area based on a decision tree. When the water environment changes, it can issue timely and accurate graded alarms and take corresponding measures in a timely manner to avoid the spread of pollutants and property loss. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 A schematic flow chart of a water environment quality assessment method provided in an embodiment of the present disclosure;

[0057] Figure 2 A decision tree flow diagram provided in an embodiment of the present disclosure;

[0058] Figure 3 A schematic diagram of the structure of a water environment quality assessment system provided in an embodiment of the present disclosure;

[0059] Figure 4 A schematic diagram of an electronic device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0060] The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0061] The following describes the embodiments of the present disclosure through specific examples, and those skilled in the art can easily understand other advantages and effects of the present disclosure from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all of the embodiments. The present disclosure can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present disclosure. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present disclosure.

[0062] It should be noted that the aspects described herein may be embodied in a wide variety of forms, and any specific structure and / or functionality described herein is illustrative only. Based on this disclosure, those skilled in the art will appreciate that one aspect described herein may be implemented independently of any other aspect, and that two or more of these aspects may be combined in various ways. In addition, other structures and / or functionality other than one or more of the aspects described herein may be used to implement this apparatus and / or practice this method.

[0063] Additionally, in the following description, specific details are provided to provide a thorough understanding of the examples. However, one skilled in the art will appreciate that the aspects described can be practiced without these specific details.

[0064] An embodiment of the present invention provides a method for assessing water environment quality. By simultaneously observing the behavior and state changes of multiple organisms of different levels, and combining the spatial mutual influence of these organisms and the changes brought about by the passage of time, a decision tree is used to comprehensively, dynamically, and earlier diagnose the true health status of the water environment.

[0065] Figure 1 A schematic diagram of the water environment quality assessment method process provided in an embodiment of the present disclosure.

[0066] like Figure 1 As shown, in step S110, the observation value of the water area data to be detected is obtained.

[0067] In an embodiment of the present invention, the data of the water area to be tested include: water pH, dissolved oxygen content, nitrogen compound content, phosphorus compound content, water turbidity, type and number of plankton, type and number of benthic animals, activity of microbial biofilm and fish swimming trajectory.

[0068] More specifically, first, the water area complexity level is assessed.

[0069] Secondly, the water area is divided into grids according to the complexity level of the water area. For example, when the water area is relatively simple, the water area is divided into 3×3 grids, and one sampling point is set at the center of each grid; when the water area is more complex, the shorter the side length of the grid is, and the greater the number of sampling points.

[0070] Furthermore, additional sampling points are added near the pollution sources.

[0071] Secondly, collection devices were installed at the sampling points to obtain comprehensive data of the water ecosystem to be tested. The specific collection methods are shown in Table 1.

[0072] Table 1 Collection of multi-source data

[0073]

[0074] More specifically, the process proceeds to step S120.

[0075] In step S120, the discomfort index of organisms in the water area is calculated based on the observed values ​​of the water area data.

[0076] In an embodiment of the present invention, the calculation of the discomfort index of organisms in the water area through the observation values ​​of the water area data includes the following steps: defining a baseline of the health status of organisms in the water area through historical data; wherein the baseline of the health status is an index range for the organisms in the water area to maintain a healthy state in the water area; calculating the indicators of the organisms in the water area respectively through the observation values ​​of the water area data; wherein the indicators of the organisms in the water area include the Shannon-Wiener diversity index of algae, the biomass ratio of Oligochaeta to Chironomid larvae, the ATP content on the microbial biofilm and the vertical migration frequency of fish; and calculating the discomfort index of the organisms in the water area based on the baseline of the health status of the organisms in the water area and the indicators of the organisms in the water area.

[0077] In an embodiment of the present invention, the calculation of the discomfort index of the organisms in the water area based on the baseline of the health status of the organisms in the water area and the indicators of the organisms in the water area includes:

[0078] The relative offset of the water area data observation values ​​is calculated based on the following formula:

[0079] ;

[0080] in, is the relative offset; For groups Observations in waters, taxa Include , For plankton, For benthic organisms, For microbial biofilm, For fish, among which, 、 is a positive indicator, 、 It is a negative indicator; is the minimum value under the baseline of healthy condition; It is the maximum value under the baseline of healthy condition;

[0081] The relative offset is calculated based on the following formula: Truncated to the interval [0,1]:

[0082] ;

[0083] in, is the relative offset after truncation;

[0084] Calculate correction amount by ecological weight :

[0085] ;

[0086] in, is the correction amount; is the ecological weight;

[0087] When the observed value of the water area data is a positive indicator:

[0088] ;

[0089] When the observed value of the water area data is a negative indicator:

[0090] ;

[0091] in, The discomfort index.

[0092] More specifically, different biological groups have different sensitivities to pollution or pressure and their importance in the ecosystem. Therefore, the present invention uses an expert scoring method (Analytic Hierarchy Process, AHP) to determine the importance of each group. Weight Based on their experience and research, experts compared and scored the indicative significance and functional importance of different biological groups. For example, benthic organisms were given a higher weight because they directly interact with the sediment and are more likely to reflect sediment contamination and its long-term cumulative effects. Fish, as top consumers, provide a comprehensive reflection of the cumulative toxicity of the entire food chain.

[0093] Construct a judgment matrix and perform consistency test.

[0094] Finally, each cluster is calculated Weight (satisfy ).

[0095] Next, go to step S130.

[0096] In step S130, the influence transfer coefficient between any two sampling points in the water area is calculated based on the observation values ​​of the water area data.

[0097] In an embodiment of the present invention, calculating the influence transfer coefficient between any two sampling points in the water area through the observation value of the water area data includes:

[0098] The influence transfer coefficient between any two sampling points in the water area is calculated based on the following formula:

[0099] ;

[0100] in, is the influence transfer coefficient; For sampling points and sampling points The Euclidean distance between For sampling points and sampling points Projection distance between is a constant; is the standard deviation of pollutant spatial diffusion; is the river weight coefficient; is the river connectivity factor.

[0101] Furthermore, the time influence transfer coefficient between any two sampling points in the water area is calculated based on the following formula:

[0102] Step 1: Identify the core pollutants.

[0103] By locating key pollutants through abnormal BDI index, for example, in a chemical leakage incident, benthic organisms (severely damaged), plankton (severely impaired), the pollutants to which benthic organisms react most strongly are selected as indicators (i.e., core pollutants).

[0104] Step 2: Determine the half-life of the pollutant through degradation experiments, historical records, or literature references.

[0105] Step 3: Calculate the time interval between the starting time of the pollution event and the current assessment time.

[0106] Step 4: Correct the decay rate based on the law of radioactive decay.

[0107]

[0108] in, is the actual degradation rate constant; is the half-life of the pollutant.

[0109] In the embodiment of the present invention, the environmental correction coefficient may be determined as shown in Table 2.

[0110] Table 2 Environmental correction factors

[0111]

[0112] Time decay factor:

[0113]

[0114] in, is the time decay factor; is a constant; is the actual degradation rate constant; It is the time interval between the starting time of the pollution event and the current assessment time.

[0115] Next, go to step S140.

[0116] In step S140 , the discomfort index of the organisms in the water area and the influence transfer coefficient are input into a decision tree model, and the decision tree model outputs a health rating of the water area.

[0117] In an embodiment of the present invention, the inputting of the discomfort index of the organisms in the water area and the influence transfer coefficient into the decision tree model includes: the decision tree model constructing a fusion feature based on the discomfort index of the organisms in the water area and the influence transfer coefficient; the fusion feature includes a spatiotemporal pressure index, a biological response difference and an abnormal sign of a key indicator; judging whether the spatiotemporal pressure index is greater than a first threshold; when the spatiotemporal pressure index is greater than the first threshold, entering a high-risk pollution branch; judging whether the discomfort index of benthic organisms is greater than a second threshold; when the discomfort index of benthic organisms is greater than the second threshold, triggering an acute pollution alarm; judging whether the fluctuation of the fish swimming sequence is greater than a third threshold; when the fluctuation of the fish swimming sequence is greater than the third threshold, confirming that the fish swimming is abnormal (DTW, Dynamic Time Warping).

[0118] More specifically, if Figure 2 As shown in the figure, the discomfort index and influence transfer coefficient of organisms in the water area are input into the decision tree model, and the model automatically constructs three key fusion features:

[0119] 1. Create a spatiotemporal pressure index to quantify the spatiotemporal losses during pollutant transfer.

[0120]

[0121] in, is the influence transfer coefficient; It is the discomfort index of the most sensitive organisms; is the time decay factor.

[0122] 2. Biological response difference: the larger the difference, the more acute the pollution.

[0123]

[0124] in, is the discomfort index for the least sensitive organism; It is the discomfort index for the most sensitive organisms.

[0125] 3. Abnormal signs of key indicators.

[0126] When benthic organisms When the dissolved oxygen DO is >0.9, the "benthic alarm" is automatically triggered, and when the dissolved oxygen DO is <3mg / L, the "hypoxia alarm" is triggered.

[0127] In an embodiment of the present invention, the decision tree model outputs a health rating of the water area, including: when an acute pollution alarm is triggered and fish swimming is abnormal, the health level is output as severe pollution; when an acute pollution alarm is triggered and the dissolved oxygen content is normal, the health level is output as moderate pollution; when the space-time pressure index is greater than a first threshold, and the discomfort index of benthic organisms is less than a second threshold, and the fluctuation of the fish swimming sequence is less than a third threshold, the health level is output as light pollution.

[0128] More specifically, the decision tree model performs hierarchical judgment by priority.

[0129] The first level of judgment: space-time pressure index, excluding background fluctuations without spatial transmission risk.

[0130] Whether the space-time pressure index is greater than 0.2. If the space-time pressure index is greater than 0.2, enter the high-risk pollution branch.

[0131] The second level of judgment: benthic organisms.

[0132] Benthic organisms are in direct contact with sediments and are most sensitive to pollutants.

[0133] Identify benthic organisms Is it greater than 0.9? If it is greater than 0.9, an acute pollution alarm will be triggered.

[0134] The third level of judgment: biological behavioral verification.

[0135] Call DTW (Dynamic Time Warping) dynamic time warping analysis to analyze fish behavior.

[0136] The current fish swimming sequence and the healthy template sequence are input and the behavioral pattern difference (i.e., DTW distance) is calculated. When the DTW distance is greater than 2.0, abnormal behavior is confirmed.

[0137] Based on the above judgment, the health rating of the water area is given according to Table 3.

[0138] Table 3 Water health rating

[0139]

[0140] The water environment quality assessment method proposed in this paper advances water environment assessment from "single-point physical and chemical analysis" to "dynamic ecosystem diagnosis." It quantifies sub-health status through the BDI index; uses DTW behavioral analysis to capture sudden changes in swimming speed, combining temporal and spatial influence transfer coefficients to accurately calculate pollution diffusion paths; and uses a decision tree to rate the health of water bodies. This allows for timely and accurate graded alerts when water environment changes occur, enabling timely response measures to prevent the spread of pollutants and property damage.

[0141] Figure 3 The water environment quality assessment system 300 provided by the present invention is shown, including a data acquisition module 310 , a calculation module 320 and a health rating module 330 .

[0142] The data acquisition module 310 is used to obtain the observation value of the water area data to be detected;

[0143] The calculation module 320 is used to calculate the discomfort index of organisms in the water area based on the observed values ​​of the water area data; and

[0144] Calculating the influence transfer coefficient between any two sampling points in the water area through the observation values ​​of the water area data;

[0145] The health rating module 330 is used to input the discomfort index of the organisms in the water area and the influence transfer coefficient into a decision tree model, and the decision tree model outputs the health rating of the water area.

[0146] See also Figure 4 The present disclosure further provides an electronic device 40, which includes:

[0147] at least one processor; and,

[0148] a memory communicatively connected to the at least one processor; wherein,

[0149] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the water environment quality assessment method in the aforementioned method embodiment.

[0150] An embodiment of the present disclosure further provides a non-transitory computer-readable storage medium, which stores computer instructions for causing the computer to execute the water environment quality assessment method in the aforementioned method embodiment.

[0151] An embodiment of the present disclosure also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions, which, when executed by a computer, enable the computer to execute the water environment quality assessment method in the aforementioned method embodiment.

[0152] Reference below Figure 4 , which shows a schematic structural diagram of an electronic device 40 suitable for implementing an embodiment of the present disclosure. The electronic devices in the embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 4 The electronic device shown is only an example and should not limit the functions and scope of use of the embodiments of the present disclosure.

[0153] like Figure 4 As shown, electronic device 40 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 401, which can perform various appropriate actions and processes according to programs stored in a read-only memory (ROM) 402 or programs loaded from a storage device 408 into a random access memory (RAM) 403. RAM 403 also stores various programs and data required for the operation of electronic device 40. Processing device 401, ROM 402, and RAM 403 are interconnected via a bus 404. An input / output (I / O) interface 405 is also connected to bus 404.

[0154] Typically, the following devices may be connected to the I / O interface 405: an input device 406 including, for example, a touch screen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; an output device 407 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; a storage device 408 including, for example, a magnetic tape, hard disk, etc.; and a communication device 409. The communication device 409 may allow the electronic device 40 to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows the electronic device 40 with various devices, it should be understood that not all of the devices shown are required to be implemented or present. More or fewer devices may alternatively be implemented or present.

[0155] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network via the communication device 409, or installed from the storage device 408, or installed from the ROM 402. When the computer program is executed by the processing device 401, the above-mentioned functions defined in the method of the embodiment of the present disclosure are performed.

[0156] It should be noted that the computer-readable medium described above in the present disclosure may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. Computer-readable storage media may include, for example, but not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or components, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such a propagated data signal may take a variety of forms, including, but not limited to, electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wire, optical cable, RF (radio frequency), or any suitable combination thereof.

[0157] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0158] The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device: obtains at least two Internet Protocol addresses; sends a node evaluation request including the at least two Internet Protocol addresses to a node evaluation device, wherein the node evaluation device selects an Internet Protocol address from the at least two Internet Protocol addresses and returns it; receives the Internet Protocol address returned by the node evaluation device; wherein the obtained Internet Protocol address indicates an edge node in a content distribution network.

[0159] Alternatively, the computer-readable medium carries one or more programs, which, when executed by the electronic device, causes the electronic device to: receive a node evaluation request including at least two Internet Protocol addresses; select an Internet Protocol address from the at least two Internet Protocol addresses; and return the selected Internet Protocol address; wherein the received Internet Protocol address indicates an edge node in a content distribution network.

[0160] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0161] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the module, program segment, or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0162] The units involved in the embodiments described in this disclosure may be implemented in software or hardware. In some cases, the name of a unit does not limit the unit itself. For example, the first acquisition unit may also be described as a "unit for acquiring at least two Internet Protocol addresses."

[0163] It should be understood that various parts of the present disclosure can be implemented in hardware, software, firmware, or a combination thereof.

[0164] The above description is only a specific embodiment of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with this technical field within the technical scope disclosed in this disclosure should be covered by the protection scope of the present disclosure.

Claims

1. A water environment quality assessment method, characterized in that: The method comprises the following steps: Obtain the observation value of the water area data to be detected; Calculating the discomfort index of organisms in the water area based on the observed values ​​of the water area data; Calculating the influence transfer coefficient between any two sampling points in the water area through the observation values ​​of the water area data; Inputting the discomfort index of organisms in the water area and the influence transfer coefficient into a decision tree model, and the decision tree model outputs a health rating of the water area; The data of the water area to be tested include: water pH, dissolved oxygen content, nitrogen compound content, phosphorus compound content, water turbidity, species and number of plankton, species and number of benthic animals, activity of microbial biofilms, and fish swimming tracks; The calculating of the discomfort index of organisms in the water area by using the observed values ​​of the water area data comprises: The relative offset of the water area data observation values ​​is calculated based on the following formula: Among them, RD k is the relative offset; X k is the observed value of group k in the water area, group k includes k1,k 2, k3, k4, k1 is plankton, k2 is benthic organisms, k3 is microbial biofilm, k4 is fish; X min,k is the minimum value under the baseline of health status; X max,k It is the maximum value under the baseline of healthy condition; The relative offset RD is calculated based on the following formula: k Truncated to the interval [0,1]: Among them, RD k ' is the relative offset after truncation; Calculate the correction amount P by ecological weight k : Among them, P k is the correction amount; ω k is the ecological weight; When the observed value of the water area data is a positive indicator: BDI k =1-P k , When the observed value of the water area data is a negative indicator: BDI k =P k , Among them, BDI k is the discomfort index; Calculating the influence transfer coefficient between any two sampling points in the water area through the observation values ​​of the water area data includes: The influence transfer coefficient between any two sampling points in the water area is calculated based on the following formula: Among them, Γ ij is the influence transfer coefficient; d ij is the Euclidean distance between sampling point i and sampling point j; r is the projected distance between sampling point i and sampling point j; e is a constant; σ is the standard deviation of pollutant spatial diffusion; λ is the river weight coefficient; δ river is the river connectivity factor.

2. The water environment quality assessment method according to claim 1, characterized in that: The method of calculating the discomfort index of organisms in the water area by using the observed values ​​of the water area data comprises the following steps: Defining a baseline of the health status of organisms in the water area through historical data; wherein the baseline of the health status is an indicator range for organisms in the water area to maintain a healthy state in the water area; Calculating indicators of organisms in the water area based on the observed values ​​of the water area data; wherein the indicators of organisms in the water area include the Shannon-Wiener diversity index of algae, the biomass ratio of oligochaetes to chironomid larvae, the ATP content on microbial biofilms, and the vertical migration frequency of fish; The discomfort index of the organisms in the water area is calculated based on the baseline of the health status of the organisms in the water area and the indicators of the organisms in the water area.

3. The water environment quality assessment method according to claim 1, characterized in that: The step of inputting the discomfort index of the organisms in the water area and the influence transfer coefficient into a decision tree model comprises: The decision tree model constructs a fusion feature based on the discomfort index of the organisms in the water area and the influence transfer coefficient; the fusion feature includes a spatiotemporal pressure index, a biological response difference, and a key indicator abnormality mark; Determining whether the space-time pressure index is greater than a first threshold; when the space-time pressure index is greater than the first threshold, entering a high-pollution risk branch; determining whether the benthic organism discomfort index is greater than a second threshold; triggering an acute pollution alarm when the benthic organism discomfort index is greater than the second threshold; Determine whether the fluctuation of the fish swimming sequence is greater than a third threshold; when the fluctuation of the fish swimming sequence is greater than the third threshold, confirm that the fish swimming is abnormal.

4. The water environment quality assessment method according to claim 3, characterized in that: The decision tree model outputs a health rating of the watershed, including: When the acute pollution alarm is triggered and fish swimming is abnormal, the output health level is severe pollution; When the acute pollution alarm is triggered and the dissolved oxygen level is normal, the output health level is moderate pollution; When the space-time pressure index is greater than the first threshold, the discomfort index of benthic organisms is less than the second threshold, and the fluctuation of fish swimming sequence is less than the third threshold, the output health level is slightly polluted.

5. A water environment quality assessment system, characterized in that: The system comprises: a data acquisition module configured to acquire observation values ​​of data of the water area to be inspected, wherein the data of the water area to be inspected includes: pH value of the water, dissolved oxygen content, nitrogen compound content, phosphorus compound content, water turbidity, species and number of plankton, species and number of benthic animals, activity of microbial biofilm, and swimming tracks of fish; a calculation module configured to calculate an unsuitable index of organisms in the water area based on the observed values ​​of the water area data; and calculate an influence transfer coefficient between any two sampling points in the water area based on the observed values ​​of the water area data; The discomfort index of the organisms in the water area is calculated based on the baseline of the health status of the organisms in the water area and the indicators of the organisms in the water area, including: The relative offset of the water area data observation values ​​is calculated based on the following formula: Among them, RD k is the relative offset; X k is the observed value of group k in the water area, group k includes j1,j 2, j3, j4, j1 are plankton, k2 are benthic organisms, k3 are microbial biofilms, and k4 are fish; X min,k is the minimum value under the baseline of health status; X max,k It is the maximum value under the baseline of healthy condition; The relative offset RD is calculated based on the following formula: k Truncated to the interval [0,1]: Among them, RD k ' is the relative offset after truncation; Calculate the correction amount P by ecological weight k : Among them, P k is the correction amount; ω k is the ecological weight; When the observed value of the water area data is a positive indicator: BDI k =1-P k , When the observed value of the water area data is a negative indicator: BDI k =P k , Among them, BDI k is the discomfort index; Calculating the influence transfer coefficient between any two sampling points in the water area through the observation values ​​of the water area data includes: The influence transfer coefficient between any two sampling points in the water area is calculated based on the following formula: Among them, Γ ij is the influence transfer coefficient; d ij is the Euclidean distance between sampling point i and sampling point j; r is the projected distance between sampling point i and sampling point j; e is a constant; σ is the standard deviation of pollutant spatial diffusion; λ is the river weight coefficient; δ river is the river connectivity factor; The health rating module is configured to input the discomfort index of the organisms in the water area and the influence transfer coefficient into a decision tree model, and the decision tree model outputs the health rating of the water area.

6. An electronic device, characterized in that: The electronic device includes: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor. When the instructions are executed by the at least one processor, the at least one processor is caused to execute the water environment quality assessment method according to any one of claims 1 to 4.

7. A computer program product, characterized in that The computer program product includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer is caused to execute the water environment quality assessment method according to any one of claims 1 to 4.

Images