CN114881373A - Zonation pollution analysis method based on river biological activity - Google Patents

Zonation pollution analysis method based on river biological activity Download PDF

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CN114881373A
CN114881373A CN202210797601.4A CN202210797601A CN114881373A CN 114881373 A CN114881373 A CN 114881373A CN 202210797601 A CN202210797601 A CN 202210797601A CN 114881373 A CN114881373 A CN 114881373A
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邹美
姚东生
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Nantong Renyuan Energy Saving And Environmental Protection Technology Co ltd
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Abstract

The invention relates to the technical field of electric digital data processing, in particular to a river biological activity-based zonal pollution analysis method, which is a digital data processing method particularly suitable for specific functions, in particular to environmental pollution treatment data processing, wherein a computer is utilized for carrying out auxiliary design and processing, namely, according to the PH value, the dissolved oxygen content and the biological activity index of each set position of 2N zones in a first set time period in the past, the index fluctuation value of the 2N zones is determined, and further a first pollution index value, a second pollution index value and a third pollution index value corresponding to the 2N zones are determined, and finally whether the 2N zones are polluted or not is determined. The method can be suitable for internet data services such as big data resource services, databases and cloud database services, and can be configured into cloud computing software, cloud fusion application operation support platform software and the like related to environmental pollution control.

Description

Zonation pollution analysis method based on river biological activity
Technical Field
The invention relates to the technical field of data processing, in particular to a zonal pollution analysis method based on river biological activity.
Background
The current river pollution problem is a main problem in water conservancy, the current river mainly takes organic pollution as a main pollutant, the main pollutants are ammonia nitrogen, biochemical oxygen demand, permanganate index, volatile phenol and the like, and if the current river is not treated, the pollution is increasingly serious, so that the water quality is continuously deteriorated. However, at present, no reliable detection method for river pollution conditions exists.
Disclosure of Invention
The invention aims to provide a zonal pollution analysis method based on river biological activity, which is used for solving the problem that the river pollution condition cannot be reliably detected in the prior art.
In order to solve the technical problems, the invention provides a zonal pollution analysis method based on river biological activity, which comprises the following steps:
acquiring PH values, dissolved oxygen contents and biological activity indexes of preset positions of 2N subareas of a river to be analyzed in a first set time period and a second set time period in the past;
determining the index fluctuation values of the 2N wafer areas according to the PH value, the dissolved oxygen content and the biological activity index of each set position of the 2N wafer areas in the past first set time period;
determining a pH value predicted value, a dissolved oxygen content predicted value and a biological activity index predicted value of each set position in a past second set time period corresponding to N patch matching pairs and N patch matching pairs according to the pH value, the dissolved oxygen content and the biological activity index of each set position in the past first set time period of 2N patch and the index fluctuation value of 2N patch;
determining a first pollution index value, a second pollution index value and a third pollution index value corresponding to 2N patch areas according to the pH value, the dissolved oxygen content and the biological activity index of each set position in a second past set time period of two patch areas in the N patch area matching pairs and the pH value, the dissolved oxygen content and the biological activity index of each set position in the second past set time period corresponding to the N patch area matching pairs;
and respectively determining whether the 2N areas are polluted or not according to the first pollution index value, the second pollution index value and the third pollution index value corresponding to the 2N areas.
Further, the step of determining N patch matching pairs includes:
calculating overall approach index values between any two film areas according to the PH values, the dissolved oxygen contents and the biological activity indexes of the 2N film areas at each set position in the past first set time period and the index fluctuation values of the 2N film areas;
and pairing the 2N chip areas according to the overall approach index value between any two chip areas, thereby obtaining N chip area matching pairs.
Further, a calculation formula corresponding to the overall approach index value between any two slices is as follows:
Figure 100002_DEST_PATH_IMAGE002
wherein,
Figure 100002_DEST_PATH_IMAGE004
the overall proximity index value between slice a and slice B,
Figure 100002_DEST_PATH_IMAGE006
is a sequence of PH values of each set position of the parcel a in the first set period of time in the past,
Figure 100002_DEST_PATH_IMAGE008
is a sequence formed by PH values of each set position in the past first set time period of the parcel B,
Figure 100002_DEST_PATH_IMAGE010
is a sequence of dissolved oxygen contents at each set location in the past first set time period for patch a,
Figure 100002_DEST_PATH_IMAGE012
is a sequence of dissolved oxygen contents at each set position in the past first set time period of the patch B,
Figure 100002_DEST_PATH_IMAGE014
is a region AA sequence of biological activity indicators at each set position within a first set time period in the past,
Figure 100002_DEST_PATH_IMAGE016
is a sequence formed by biological activity indexes of all set positions of the film area B in the first set time period in the past,
Figure 100002_DEST_PATH_IMAGE018
is the index fluctuation value of the patch a,
Figure 100002_DEST_PATH_IMAGE020
is the index fluctuation value of the patch B,
Figure 100002_DEST_PATH_IMAGE022
in order to find the function of the degree of similarity,
Figure 100002_DEST_PATH_IMAGE024
in order to solve the function of the absolute value,
Figure 100002_DEST_PATH_IMAGE026
the length is calculated as pair.
Further, the step of determining the predicted PH value, the predicted dissolved oxygen content value and the predicted biological activity index value of each set position in the past second set time period corresponding to the matching of the N zones comprises:
filtering the biological activity indexes of the 2N film areas at each set position in the past first set time period to obtain the biological activity indexes of the 2N film areas at each set position in the past first set time period after filtering;
predicting the PH value, the dissolved oxygen content and the biological activity index of each set position of the 2N slices in a second set time period in the past by using a time sequence prediction neural network according to the PH value and the dissolved oxygen content of each set position of the 2N slices in the first set time period in the past and the biological activity index of each set position of the 2N slices in the first set time period in the past after filtering;
and determining a predicted value of the pH value, a predicted value of the dissolved oxygen content and a predicted value of the biological activity index of each set position in the past second set time period corresponding to the N patch matching pairs according to the predicted pH value, the dissolved oxygen content and the biological activity index of each set position in the second set time period of the two patches of the N patch matching pairs and the index fluctuation value of the two patches of the N patch matching pairs.
Further, the step of determining the predicted PH value, the predicted dissolved oxygen content value and the predicted biological activity index value of each set position in the past second set time period corresponding to the matching of the N zones comprises:
counting the reciprocal of the index fluctuation values of the two regions in the N region matching pairs, and then carrying out normalization processing to obtain the weight values of the two regions in the N region matching pairs;
and respectively carrying out weighted summation on the predicted PH value, the dissolved oxygen content and the biological activity index of each set position of the two districts in the N district matching pairs in a second set time period according to the weight values of the two districts in the N district matching pairs, thereby obtaining the predicted PH value, the predicted dissolved oxygen content and the predicted biological activity index of each set position of the N district matching pairs in the second set time period in the past.
Further, the calculation formula corresponding to the index fluctuation values of the 2N regions is determined as follows:
Figure 100002_DEST_PATH_IMAGE028
wherein,
Figure 100002_DEST_PATH_IMAGE030
the index fluctuation value of the nth slice is,
Figure 100002_DEST_PATH_IMAGE032
the average value of the biological activity indexes of the nth sheet area at each set position in the first set time period in the past,
Figure 100002_DEST_PATH_IMAGE034
is the average value of the PH value of each set position of the nth block in the first set time period,
Figure 100002_DEST_PATH_IMAGE036
is the mean value of the dissolved oxygen content of each set position in the first set time period in the past of the nth plate area,
Figure 100002_DEST_PATH_IMAGE038
to find the variance function.
Further, the step of determining a first contamination index value, a second contamination index value and a third contamination index value corresponding to the 2N patch areas comprises:
according to the PH value, the dissolved oxygen content and the biological activity index of two film areas in N film area matching pairs at each set position in the past second set time period and the PH value, the dissolved oxygen content and the biological activity index predicted value of the two film areas in the past second set time period corresponding to the N film area matching pairs at each set position in the past second set time period, calculating the module length of the PH value composition sequence, the module length of the dissolved oxygen content composition sequence, the module length of the biological activity index composition sequence of each film area in the N film area matching pairs at each set position in the past second set time period and the module length of the PH value composition sequence, the module length of the dissolved oxygen content composition sequence and the module length of the biological activity index predicted value composition sequence of each set position in the N film area matching pairs, and calculating the PH value composition sequence, the dissolved oxygen content index and the module length of the biological activity index predicted value composition sequence corresponding to each film area in the N film area matching pairs, The similarity between the dissolved oxygen content forming sequence and the biological activity index forming sequence, the dissolved oxygen content predicted value forming sequence and the biological activity index predicted value forming sequence are in one-to-one correspondence with the corresponding zone matching pair;
determining a first pollution index value corresponding to 2N fragment areas according to the modular length of a PH value composition sequence of each set position in a second past set time period of each fragment area in the N fragment area matching pairs, the modular length of a PH value predicted value composition sequence of each set position in the second past set time period corresponding to the N fragment area matching pairs, and the similarity between the PH value composition sequence corresponding to each fragment area in the N fragment area matching pairs and the PH value predicted value composition sequence corresponding to the corresponding fragment area matching pairs;
determining second pollution index values corresponding to 2N patch areas according to the modular length of a dissolved oxygen content composition sequence of each set position in a second past set time period of each patch area in the N patch area matching pairs, the modular length of a dissolved oxygen content predicted value composition sequence of each set position in the second past set time period corresponding to the N patch area matching pairs, and the similarity between the dissolved oxygen content composition sequence corresponding to each patch area in the N patch area matching pairs and the dissolved oxygen content predicted value composition sequence corresponding to the corresponding patch area matching pairs;
and determining a third pollution index value corresponding to 2N patch areas according to the module length of the bioactivity index forming sequence of each set position in the second past set time period of each patch area in the N patch area matching pairs, the module length of the bioactivity index predicted value forming sequence of each set position in the second past set time period corresponding to the N patch area matching pairs, and the similarity between the bioactivity index forming sequence corresponding to each patch area in the N patch area matching pairs and the bioactivity index predicted value forming sequence corresponding to the corresponding patch area matching pair.
Further, the step of determining whether the 2N chip regions are contaminated, respectively, includes:
comparing the first pollution index value, the second pollution index value and the third pollution index value corresponding to each section with a first pollution index value threshold, a second pollution index value threshold and a third pollution index value threshold respectively;
if the first pollution index value of a certain zone is not less than the first pollution index value threshold, the second pollution index value is not less than the second pollution index value threshold and the third pollution index value is not less than the third pollution index value threshold, judging that the zone is not polluted, otherwise, judging that the corresponding zone is polluted.
Further, the method also comprises the following steps:
if a certain zone is polluted, determining a first set number of target zones connected upstream and a second set number of target zones connected downstream;
acquiring the pH value, the dissolved oxygen content and the biological activity index of each uncontaminated target zone at each set position in a third set time period and the pH value, the dissolved oxygen content and the biological activity index of the other zone in the corresponding zone matching pair of the uncontaminated target zone at each set position in the third set time period, so as to determine a first diffusion index value, a second diffusion index value and a third diffusion index value of each uncontaminated target zone;
and determining whether the pollution diffusion occurs to each target area without pollution according to the first diffusion index value, the second diffusion index value and the third diffusion index value of each target area without pollution.
Further, the step of determining whether the target areas without the contamination are contaminated or not comprises:
respectively comparing the first diffusion index value, the second diffusion index value and the third diffusion index value of each target region without pollution with a first diffusion index value threshold, a second diffusion index value threshold and a third diffusion index value threshold;
if the first diffusion index value of the target area without pollution is not less than the first diffusion index value threshold, the second diffusion index value is not less than the second diffusion index value threshold and the third diffusion index value is not less than the third diffusion index value threshold, judging that the target area without pollution is not subjected to pollution diffusion, and otherwise, judging that the target area without pollution is subjected to pollution diffusion.
The invention has the following beneficial effects: the invention provides a river biological activity-based zonal pollution analysis method, which is a digital data processing method particularly suitable for specific functions, in particular to environmental pollution treatment data processing, and the method comprises the steps of obtaining the PH value, the dissolved oxygen content and the biological activity index of each set position of 2N zones in the past first set time period and second set time period, further determining the index fluctuation value of the 2N zones, and determining a first pollution index value, a second pollution index value and a third pollution index value corresponding to the 2N zones by combining the PH value, the dissolved oxygen content, the biological activity index and the index fluctuation value, thereby determining whether the 2N zones are polluted or not. The method can accurately determine the polluted river segment, is suitable for internet data services such as big data resource service, database and cloud database service, and can be configured into cloud computing software, cloud fusion application operation support platform software and the like related to environmental pollution control.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions and advantages of the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flow chart of a zonal contamination analysis method based on river bioactivities according to the present invention.
Detailed Description
To further explain the technical means and effects of the present invention adopted to achieve the predetermined objects, the following detailed description of the embodiments, structures, features and effects of the technical solutions according to the present invention will be given with reference to the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" refers to not necessarily the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The embodiment provides a zonal pollution analysis method based on river biological activity, which can reliably detect the pollution condition of a river, and a corresponding flow chart is shown in fig. 1, and comprises the following steps:
(1) acquiring PH values, dissolved oxygen contents and biological activity indexes of preset positions of 2N subareas of a river to be analyzed in a first set time period and a second set time period in the past.
Since the urban rivers are often connected with a plurality of urban water outlets, the pollution conditions at all places are not the same, and the urban rivers are different from the large rivers, the water flow of the urban rivers is slow, and therefore the probability of local pollution is increased. Therefore, the river needs to be divided into sections to achieve monitoring accuracy and scientificity. In this embodiment, along the direction of water flow, every 200 meters of river length is divided into 2N sub-areas, which are numbered 1 to 2N in sequence, where N is a positive integer.
The pH value of the unpolluted water has small fluctuation around a value and hardly changes greatly, and the pH value of the water can be changed only when the water is polluted. In order to measure the pH value of each zone, after dividing the urban river into 2N zones, three pH value detectors are uniformly arranged at the same set position of each zone, for example, for each zone, three pH value detectors are sequentially arranged at equal intervals along the flowing direction of the urban river, and each pH value detector is close to the center position of the river. These pH detectors measure pH simultaneously every half hour and can measure for a long time.
The content of dissolved oxygen is an index for measuring the self-purification capacity of water, and the dissolved oxygen has close relation with the partial pressure of oxygen in the air, the atmospheric pressure, the water temperature and the water quality. Some organic compounds require consumption of dissolved oxygen in water for degradation under aerobic bacteria action, and when the dissolved oxygen in water is very low, breathing of some fishes becomes difficult. When the water body is polluted by organic matters, the content of dissolved oxygen is reduced, and the water body is blackened and smelled. The content of dissolved oxygen is an index for researching the self-purification capability of water, and when the content of dissolved oxygen is lower than a normal value for a long time, the content means that the water body is seriously polluted and even loses the self-purification capability. In order to measure the dissolved oxygen content of each plate area, after dividing the urban river into 2N plate areas, three dissolved oxygen measuring instruments are also uniformly placed at the same set position of each plate area. These dissolved oxygen meters measure a dissolved oxygen content simultaneously every half hour and can measure for a long time.
As rivers in cities are slow in water speed and garbage filter screens are arranged in a plurality of places, most of organisms in water live in a certain range, and if water is polluted, fish schools feel abnormal and other water areas are found, so that the fish school activity of the water areas near the polluted places is reduced, and the fish school activity of other uncontaminated places is slightly increased. In order to measure the biological activity index of each zone, after 2N zones are divided in an urban river, five infrared distance meters are uniformly arranged at the same set position of each zone to detect the passing condition of underwater fishes and shrimps, the detection mode is that 1 is recorded and accumulated when the fishes and shrimps are detected to pass once, and the recorded value is used as the biological activity index. The infrared distance meters synchronously measure every hour to obtain a biological activity index, and can measure for a long time.
On the basis, when the pollution condition of the river needs to be analyzed, the pH value, the dissolved oxygen content and the biological activity index of each set position of the 2N slice zones in the last period of time in the past are obtained, the previous period of time in the last period of time in the past is used as a first set time period, the later period of time is used as a second set time period, and therefore the pH value, the dissolved oxygen content and the biological activity index of each set position of the 2N slice zones in the first set time period and the pH value, the dissolved oxygen content and the biological activity index of each set position in the second set time period are obtained. In the present embodiment, the last 32 days in the past are taken as the last period in the past, the first 30 days are taken as the first set period in the past, and the last 2 days are taken as the second set period in the past.
In this embodiment, for the nth partition, the PH values at the three setting positions in the first setting time period form three PH value sequences, which are recorded as
Figure DEST_PATH_IMAGE040
、
Figure DEST_PATH_IMAGE042
The dissolved oxygen contents of the three set positions form three dissolved oxygen content sequences which are recorded as
Figure DEST_PATH_IMAGE044
、
Figure DEST_PATH_IMAGE046
The biological activity indexes of the five set positions form five biological activity index sequences which are recorded as
Figure DEST_PATH_IMAGE048
、
Figure DEST_PATH_IMAGE050
、
Figure DEST_PATH_IMAGE052
、
Figure DEST_PATH_IMAGE054
}。
(2) And determining the index fluctuation values of the 2N film areas according to the PH value, the dissolved oxygen content and the biological activity index of each set position of the 2N film areas in the first set time period in the past.
Because each section of the river is divided according to the distance, when the number of water outlets of some sections is more, the discharged sewage is relatively more; in some areas, the drainage outlets are fewer, the discharged sewage is relatively less, so the pollution probability and degree of different areas are different, and each index of the areas discharging more easily fluctuates. Based on the above, the index fluctuation values of the 2N slice areas are calculated, and the corresponding calculation formula is as follows:
Figure DEST_PATH_IMAGE028A
wherein,
Figure 824352DEST_PATH_IMAGE030
the index fluctuation value of the nth slice is,
Figure 180641DEST_PATH_IMAGE032
the average value of the biological activity indexes of all the set positions of the nth sheet area in the first set time period in the past, namely the average value of the biological activity indexes of all the set positions at the same moment,
Figure 898061DEST_PATH_IMAGE034
the average value of the PH values of the setting positions of the nth block in the first setting time period in the past, namely the average value of the PH values of the setting positions at the same moment,
Figure 230953DEST_PATH_IMAGE036
the mean value of the dissolved oxygen content of each set position in the first set time period in the past of the nth plate area, namely the mean value of the dissolved oxygen content of each set position at the same moment,
Figure 983009DEST_PATH_IMAGE038
to find the variance function.
For the above calculation formula of the index fluctuation value, when the sewage is discharged more frequently in the parcel, the change conditions of the biological activity index, the pH value and the dissolved oxygen content are increased, and the fluctuation of the pH value, the dissolved oxygen content and the biological activity index is larger, the corresponding variance is larger, the denominator is larger, and the index fluctuation value Q of the parcel is smaller. The index fluctuation value Q has a value range of (0, 1), and the closer the index fluctuation value Q of the fragment area is to 1, the larger the sewage discharge amount of the fragment area is reflected, and the smaller the sewage discharge amount is, so that the discharge degree of each fragment area can be reflected according to the value of the index fluctuation value Q of the fragment area, and the fragment area with pollution can be conveniently detected subsequently.
(3) And determining a pH value predicted value, a dissolved oxygen content predicted value and a biological activity index predicted value of each set position in the past second set time period corresponding to the N patch matching pairs and the N patch matching pairs according to the pH value, the dissolved oxygen content and the biological activity index of each set position in the past first set time period of the 2N patches and the index fluctuation value of the 2N patches.
Since the flow rate of urban rivers is slow and the discharge amount of each plot is not the same, each plot needs to be discussed in a classified manner. In order to reduce the category of the classification discussion, the conditions of different parcel areas can be analyzed to find out the parcel pair with similar conditions, and the specific implementation process is as follows:
(3-1) calculating the overall approach index value between any two slices according to the pH value, the dissolved oxygen content and the biological activity index of each set position of the 2N slices in the first set time period in the past and the index fluctuation values of the 2N slices, wherein the corresponding calculation formula is as follows:
Figure DEST_PATH_IMAGE002A
wherein,
Figure 523580DEST_PATH_IMAGE004
the overall proximity index value between slice a and slice B,
Figure 14781DEST_PATH_IMAGE006
is a sequence of PH values of each set position of the parcel a in the first set period of time in the past,
Figure 151364DEST_PATH_IMAGE008
is a sequence formed by PH values of each set position in the past first set time period of the parcel B,
Figure 492346DEST_PATH_IMAGE010
is a sequence of dissolved oxygen contents at each set location in the past first set time period for patch a,
Figure 423393DEST_PATH_IMAGE012
is a sequence of dissolved oxygen contents at each set position in the past first set time period of the patch B,
Figure 613941DEST_PATH_IMAGE014
is a sequence formed by biological activity indexes of all set positions of the film area A in the first set time period in the past,
Figure 960740DEST_PATH_IMAGE016
is a sequence formed by biological activity indexes of all set positions of the film area B in the first set time period in the past,
Figure 421808DEST_PATH_IMAGE018
is the index fluctuation value of the patch a,
Figure 290800DEST_PATH_IMAGE020
is the index fluctuation value of the patch B,
Figure 470109DEST_PATH_IMAGE022
in order to find the function of the degree of similarity,
Figure 417336DEST_PATH_IMAGE024
in order to solve the function of the absolute value,
Figure 998491DEST_PATH_IMAGE026
the length is calculated as pair.
In the above calculation formula of the overall approach index value between any two patches, each sequence is a time sequence, and when calculating the similarity of the sequence formed by each index (PH value, dissolved oxygen content, or biological activity index) of the patch a and the patch B in a molecule, the cosine similarity between the sequence formed by the index (PH value, dissolved oxygen content, or biological activity index) of each set position in the area a and the sequence formed by the index (PH value, dissolved oxygen content, or biological activity index) of the corresponding set position in the area B is calculated first, the mean value of the cosine similarities corresponding to each set position is calculated, and the mean value of the cosine similarities is used as the final similarity of the sequence formed by each index of the patch a and the patch B. In addition, in calculating the modular length of the sequence formed by the indexes (PH value, dissolved oxygen content or biological activity index) of the slab region a or the slab region B in the denominator, the modular length of the sequence formed by the indexes (PH value, dissolved oxygen content or biological activity index) of each set position of the slab region a or the slab region B is calculated first, then the mean value of the respective modular lengths corresponding to each set position is calculated, and the mean value of the respective modular lengths is used as the final modular length of the sequence formed by the indexes of the slab region a or the slab region B.
From the above calculation formula of the overall approach index value between any two patches, the numerator is the similarity of the sequences formed by the indexes in the two patches, and the numerator is closer to 1 as the sequences formed by the indexes in the two patches are closer. The denominator comprises the difference of the modular length of the sequences formed by each index in the two segments, and the denominator is closer to 1 when the sequences formed by each index in the two segments are closer. Therefore, the value of the overall approach index value W is closer to 1 as the overall situation of two tiles is closer, and conversely closer to 0.
And (3-2) pairing the 2N areas according to the overall approach index value between any two areas, thereby obtaining N area matching pairs.
And (3) matching according to the conditions of the various districts on the basis of the step (3-1), wherein the biological activity indexes are different due to different positions of the districts, so that the districts are still slightly different, and in addition, the situation that the conditions of every two districts are most similar is paired by using a K-Means algorithm in consideration of the fact that the districts divided by rivers are not large, so that N matched pairs of the districts are obtained.
In addition, after obtaining N patch matching pairs, it is further required to determine a PH value predicted value, a dissolved oxygen content predicted value, and a biological activity index predicted value of each set position in a second past set time period corresponding to the N patch matching pairs, and the specific implementation steps include:
and (3-3) filtering the biological activity indexes of the 2N film areas at each set position in the first set time period in the past to obtain the biological activity indexes of the 2N film areas at each set position in the first set time period in the past after filtering.
Because the fish and the shrimp live underwater sometimes can be exposedThe influence of the boundary causes that the activity degree of a certain time period is particularly high or low, so that the biological activity indexes of each section at various set positions in the first set time period in the past need to be processed. In the embodiment, in order to eliminate partial fluctuation errors caused by external conditions, filtering processing is performed on a sequence formed by the biological activity indexes of the various setting positions of each parcel in the first setting time period in the past by using a median filtering method, so that the biological activity indexes of the various setting positions of each parcel in the first setting time period in the past after the filtering processing are obtained. For the nth slice area, the biological activity indexes of the five set positions after the filtering processing form five biological activity index sequences which are recorded as
Figure DEST_PATH_IMAGE056
、
Figure DEST_PATH_IMAGE058
、
Figure DEST_PATH_IMAGE060
、
Figure DEST_PATH_IMAGE062
}。
And (3-4) predicting the PH value, the dissolved oxygen content and the biological activity index of each set position of the 2N fragment areas in the second set time period in the past by using a time sequence prediction neural network according to the PH value and the dissolved oxygen content of each set position of the 2N fragment areas in the first set time period in the past and the biological activity index of each set position of the 2N fragment areas in the first set time period in the past after filtering.
Based on the above step (3-3), for the nth fragment, the sequence is formed by the PH value of each setting position of the fragment in the first setting time period in the past
Figure 553231DEST_PATH_IMAGE034
Sequence of dissolved oxygen content
Figure 219836DEST_PATH_IMAGE036
And a sequence formed by the biological activity indexes after filtering treatment
Figure DEST_PATH_IMAGE064
Respectively inputting the data into the corresponding time sequence prediction neural networks, and predicting the sequence of the future time by the corresponding time sequence prediction neural networks, thereby obtaining the predicted PH value, the dissolved oxygen content and the biological activity index of each set position of the parcel in the second set time period in the past.
The time-series prediction neural network is formed by an LSTM neural network, and the time-series prediction neural network is trained in advance, and the corresponding loss function is a mean square error loss function. When the time sequence prediction neural network is trained, sequences formed by PH values, dissolved oxygen contents and biological activity indexes are respectively used as the former parts of the characteristic sequences and input into the time sequence prediction neural network, and the latter parts of the characteristic sequences are used as labels, so that the time sequence prediction neural network can learn the next predicted value under the current sequence mode. Since the training process of the time-series prediction neural network belongs to the prior art, it is not described here in detail.
(3-5) according to the predicted PH value, dissolved oxygen content and biological activity index of two districts in the N district matching pairs at each set position in the second set time period and the index fluctuation value of the two districts in the N district matching pairs, determining the predicted PH value, dissolved oxygen content and biological activity index at each set position in the second set time period in the past corresponding to the N district matching pairs, and specifically realizing the steps of:
(3-5-1) calculating the reciprocal of the index fluctuation values of the two areas in the N area matching pairs, and then carrying out normalization processing to obtain the weight values of the two areas in the N area matching pairs.
According to the step (2), each patch corresponds to one index fluctuation value Q, and thus two patches in the N patch matching pairs correspond to one index fluctuation value Q. Since the index fluctuation value Q is closer to 1, it means that the corresponding slice region isThe greater the probability of contamination, the less reliable the three indicators of the slice corresponding to the indicator fluctuation value Q, and the smaller the weight value corresponding to the slice. Therefore, the index fluctuation values Q of the two areas A and B in the N area matching pairs are subjected to reciprocal calculation and then normalized to obtain
Figure DEST_PATH_IMAGE066
。
(3-5-2) according to the weight values of the two areas in the N area matching pairs, respectively carrying out weighted summation on the predicted PH values, the dissolved oxygen contents and the biological activity indexes of the two areas in the N area matching pairs at each set position in a second set time period, thereby obtaining the predicted PH values, the predicted dissolved oxygen contents and the predicted biological activity indexes of the N area matching pairs at each set position in the second set time period in the past.
On the basis of the step (3-5-1), for two slices A and B in the nth slice matching pair, recording the sequence formed by predicted PH value, dissolved oxygen content and biological activity index of each set position of the slice A in the second set time period as
Figure DEST_PATH_IMAGE068
、
Figure DEST_PATH_IMAGE070
、
Figure DEST_PATH_IMAGE072
Recording the sequence of predicted PH value, dissolved oxygen content and biological activity index of each set position of the section B in a second set time period as
Figure DEST_PATH_IMAGE074
、
Figure DEST_PATH_IMAGE076
、
Figure DEST_PATH_IMAGE078
Then now the nth slice matchesA sequence of predicted PH values of the corresponding set positions in the second set time period in the past
Figure DEST_PATH_IMAGE080
Sequence of predicted values of dissolved oxygen content
Figure DEST_PATH_IMAGE082
Sequence formed by biological activity index predicted value
Figure DEST_PATH_IMAGE084
。
(4) And determining a first pollution index value, a second pollution index value and a third pollution index value corresponding to 2N slice areas according to the pH value, the dissolved oxygen content and the biological activity index of each set position in the second set time period in the past of two slice areas in the N slice area matching pairs and the pH value, the dissolved oxygen content and the biological activity index of each set position in the second set time period in the past corresponding to the N slice area matching pairs.
Because the pollution of river sewage is gradually accumulated, the numerical value is also changed little by little, the index value corresponding to each index is determined by comparing the difference between the real sequence and the prediction sequence of each index, and the abnormality can be found before serious pollution based on the index value subsequently, the specific implementation steps comprise:
(4-1) calculating the model length of the pH value composition sequence, the model length of the dissolved oxygen content composition sequence, the model length of the biological activity index composition sequence and the model length of the pH value composition sequence, the model length of the dissolved oxygen content composition sequence and the model length of the biological activity index composition sequence of each set position in the past second set time period corresponding to the N slice region matching pairs, and the model length of the pH value composition sequence, the model length of the dissolved oxygen content composition sequence and the model length of the biological activity index composition sequence of each set position in the past second set time period corresponding to the N slice region matching pairs according to the pH value, the dissolved oxygen content and the biological activity index indexes of each set position in the past second set time period of two slice regions in the N slice region matching pairs and the pH value, the dissolved oxygen content index and the biological activity index predicted values of each set position in the past second set time period, and calculating the similarity between the pH value forming sequence, the dissolved oxygen content forming sequence and the biological activity index forming sequence corresponding to each of the N patch matching pairs, and the pH value predicted value forming sequence, the dissolved oxygen content predicted value forming sequence and the biological activity index predicted value forming sequence corresponding to the corresponding patch matching pairs in a one-to-one correspondence manner.
It should be noted that, the above step (3-1) may be referred to in the above specific process of calculating the similarity between two sequences formed by each index and the specific process of calculating the modular length of each sequence, and details are not repeated here.
(4-2) determining a first pollution index value corresponding to 2N fragment areas according to the modular length of the PH value composition sequence of each set position in the second past set time period of each fragment area in the N fragment area matching pairs, the modular length of the PH value prediction value composition sequence of each set position in the second past set time period corresponding to the N fragment area matching pairs, and the similarity between the PH value composition sequence corresponding to each fragment area in the N fragment area matching pairs and the PH value prediction value composition sequence corresponding to the corresponding fragment area matching pairs; and determining a second pollution index value corresponding to 2N patch areas according to the modular length of a dissolved oxygen content composition sequence of each set position in the second past set time period of each patch area in the N patch area matching pairs, the modular length of a dissolved oxygen content predicted value composition sequence of each set position in the second past set time period corresponding to the N patch area matching pairs, and the similarity between the dissolved oxygen content composition sequence corresponding to each patch area in the N patch area matching pairs and the dissolved oxygen content predicted value composition sequence corresponding to the corresponding patch area matching pairs. Determining a third pollution index value corresponding to 2N patch areas according to the module length of a biological activity index forming sequence of each set position in a second past set time period of each patch area in N patch area matching pairs, the module length of a biological activity index predicted value forming sequence of each set position in the second past set time period corresponding to N patch area matching pairs, and the similarity between the biological activity index forming sequence corresponding to each patch area in N patch area matching pairs and the biological activity index predicted value forming sequence corresponding to the corresponding patch area matching pairs, wherein the corresponding calculation formula is as follows:
Figure DEST_PATH_IMAGE086
Figure DEST_PATH_IMAGE088
Figure DEST_PATH_IMAGE090
wherein,
Figure DEST_PATH_IMAGE092
、
Figure DEST_PATH_IMAGE094
、
Figure DEST_PATH_IMAGE096
a first pollution index value, a second pollution index value and a third pollution index value corresponding to the nth chip region respectively,
Figure DEST_PATH_IMAGE098
a sequence of PH values for each set position in the second set period of time in the past for the nth tile,
Figure DEST_PATH_IMAGE100
matching the corresponding slice area of the nth slice area with the corresponding PH value predicted value of each set position in the second set time period in the past,
Figure DEST_PATH_IMAGE102
is a sequence formed by the dissolved oxygen content of each set position of the nth sheet area in the second set time period,
Figure DEST_PATH_IMAGE104
matching the corresponding past second chip region for the chip region corresponding to the nth chip regionTwo sequences formed by the predicted values of the dissolved oxygen content of each set position in a set time period,
Figure DEST_PATH_IMAGE106
a sequence formed by the biological activity indexes of the nth sheet area at each set position in the second set time period,
Figure DEST_PATH_IMAGE108
matching the corresponding slice area of the nth slice area with the corresponding sequence of the biological activity index predicted values of each set position in the second set time period in the past,
Figure 79793DEST_PATH_IMAGE022
in order to find the function of the degree of similarity,
Figure 515454DEST_PATH_IMAGE024
in order to solve the function of the absolute value,
Figure 460669DEST_PATH_IMAGE026
the length is calculated as pair.
A first contamination index value according to the nth region
Figure 348991DEST_PATH_IMAGE092
A second pollution index value
Figure 169179DEST_PATH_IMAGE094
And a third pollution index value
Figure 459346DEST_PATH_IMAGE096
The calculation formula shows that when the nth chip region is not contaminated, the first contamination index value is obtained
Figure 838113DEST_PATH_IMAGE092
A second pollution index value
Figure 885835DEST_PATH_IMAGE094
And a third pollution index value
Figure 244135DEST_PATH_IMAGE096
The closer to 1, the closer to 0 as the contamination becomes more severe.
(5) And respectively determining whether the 2N areas are polluted or not according to the first pollution index value, the second pollution index value and the third pollution index value corresponding to the 2N areas.
According to the relationship between the first, second and third pollution index values of a zone and the pollution condition of the corresponding zone, in this embodiment, a first pollution index value threshold is set
Figure DEST_PATH_IMAGE110
A second pollution index value threshold
Figure DEST_PATH_IMAGE112
And a third pollution index value threshold
Figure DEST_PATH_IMAGE114
. Respectively corresponding the first pollution index value, the second pollution index value and the third pollution index value corresponding to each region to the first pollution index value threshold value
Figure 703322DEST_PATH_IMAGE110
A second pollution index value threshold
Figure 252990DEST_PATH_IMAGE112
And a third pollution index value threshold
Figure 115904DEST_PATH_IMAGE114
A comparison is made. If the first pollution index value of a certain area is not less than the first pollution index value threshold
Figure 74633DEST_PATH_IMAGE110
The second pollution index value is not less than the second pollution index value threshold
Figure 73813DEST_PATH_IMAGE112
And the third pollution index value is not less than the third pollutionThreshold value of index value
Figure 520013DEST_PATH_IMAGE114
If not, judging that the corresponding wafer area is polluted.
After judging each polluted plot, because river pollution can be diffused gradually, when one plot is polluted, the upstream and downstream plots of the plot are likely to be polluted, in order to determine the pollution diffusion condition of each polluted plot, the method further comprises the following steps:
(5-1) if a certain zone is contaminated, determining a first set number of target zones connected upstream thereof and a second set number of target zones connected downstream thereof.
In this embodiment, if a certain parcel is contaminated, the 2 parcels connected upstream and the 2 parcels downstream thereof are taken as target parcels, that is, the first set number is 2, and the second set number is 5.
(5-2) acquiring the pH value, the dissolved oxygen content and the biological activity index of each target zone which is not polluted at each set position in a third set time period in each target zone and the pH value, the dissolved oxygen content and the biological activity index of the other zone in the matching pair of the target zones which are not polluted at each set position in the third set time period in the corresponding zone, so as to determine the first diffusion index value, the second diffusion index value and the third diffusion index value of each target zone which is not polluted.
After the target zone of each contaminated zone is determined through the step (5-1), a possible part of the target zones can already be determined to be contaminated definitely, so that target zones which are not contaminated are screened out from the target zones, and the pH value, the dissolved oxygen content and the biological activity index of each set position of each target zone which is not contaminated in the third set time period and the pH value, the dissolved oxygen content and the biological activity index of the other zone in the corresponding zone matching pair of the target zones which are not contaminated in the third set time period are obtained. In the present embodiment, the third set period of time is the same as the second set period of time, i.e., the last 2 days of the last 32 days in the past as the third set period of time.
Determining a first diffusion index value, a second diffusion index value and a third diffusion index value of each target area without pollution based on the acquired pH value, dissolved oxygen content and biological activity index of each set position in the third set time period, wherein the corresponding calculation formula is as follows:
Figure DEST_PATH_IMAGE116
Figure DEST_PATH_IMAGE118
Figure DEST_PATH_IMAGE120
wherein,
Figure DEST_PATH_IMAGE122
、
Figure DEST_PATH_IMAGE124
、
Figure DEST_PATH_IMAGE126
respectively a first diffusion index value, a second diffusion index value and a third diffusion index value of each target region without pollution,
Figure DEST_PATH_IMAGE128
a sequence formed by the pH value mean values of all the set positions in a third set time period for all the target areas without pollution,
Figure DEST_PATH_IMAGE130
a sequence formed by the pH value average values of the other one of the corresponding section matching pairs of each target section which is not polluted at each set position in a third set time period,
Figure DEST_PATH_IMAGE132
a sequence formed by the mean value of the dissolved oxygen content of each set position in a third set time period for each target area without pollution,
Figure DEST_PATH_IMAGE134
a sequence formed by the mean value of the dissolved oxygen content of each set position in a third set time period for the other one of the matching pairs of the corresponding target areas without pollution,
Figure DEST_PATH_IMAGE136
a sequence formed by the biological activity index mean values of all the set positions in a third set time period for all the target areas without pollution,
Figure DEST_PATH_IMAGE138
a sequence formed by the biological activity index mean values of the other one of the corresponding film zone matching pairs of each target film zone without pollution at each set position in a third set time period,
Figure DEST_PATH_IMAGE140
in order to find the covariance function of the two sequences,
Figure DEST_PATH_IMAGE142
、
Figure DEST_PATH_IMAGE144
、
Figure DEST_PATH_IMAGE146
、
Figure DEST_PATH_IMAGE148
、
Figure 60104DEST_PATH_IMAGE142
and
Figure DEST_PATH_IMAGE150
are respectively a sequence
Figure 464934DEST_PATH_IMAGE128
、
Figure 584199DEST_PATH_IMAGE130
、
Figure 383659DEST_PATH_IMAGE132
、
Figure 719700DEST_PATH_IMAGE134
、
Figure 223494DEST_PATH_IMAGE136
And
Figure 462846DEST_PATH_IMAGE138
the variance of each element in (a).
According to the above calculation formulas of the first diffusion index value, the second diffusion index value and the third diffusion index value of each target segment which is not contaminated, when the target segment which is not contaminated is more similar to the other segment in the corresponding segment matching pair, the target segment which is not contaminated is more unlikely to be contaminated, and the diffusion index value is larger at this time, whereas when the target segment which is not contaminated is more dissimilar to the other segment in the corresponding segment matching pair, the target segment which is not contaminated is more likely to be contaminated, and the diffusion index value is smaller at this time.
(5-3) determining whether the target areas without pollution are subjected to pollution diffusion according to the first diffusion index value, the second diffusion index value and the third diffusion index value of the target areas without pollution, wherein the specific implementation steps comprise:
according to the relationship between whether or not the pollution diffusion occurs in each target area without pollution and the diffusion index value, in the present embodiment, a first diffusion index value threshold, a second diffusion index value threshold, and a third diffusion index value threshold are set. And respectively comparing the first diffusion index value, the second diffusion index value and the third diffusion index value of each target region without pollution with the first diffusion index value threshold, the second diffusion index value threshold and the third diffusion index value threshold. If the first diffusion index value of the target area without pollution is not less than the first diffusion index value threshold, the second diffusion index value is not less than the second diffusion index value threshold and the third diffusion index value is not less than the third diffusion index value threshold, judging that the target area without pollution is not polluted and diffused, otherwise, judging that the target area without pollution is polluted and diffused, and needing to be timely treated, and then carrying out pollution diffusion early warning.
In addition, after each pollution-generating section is judged, in order to determine the pollution degree index value of each pollution-generating section, the section with the highest pollution degree in the whole river is found, namely the section corresponding to the smallest first pollution index value, second pollution index value and third pollution index value is found, the pollution degree index value of the section is set as 100, and then the conditions of other pollution-generating sections are compared with the section, so that the pollution degree index values of other pollution-generating sections are obtained.
In this embodiment, the sequence of the biological activity indicators of the other contaminated sections at the respective set positions in the past first set time period is compared with the sequence of the biological activity indicators of the sections at the respective set positions in the past first set time period, so as to obtain the contamination level index values of the other contaminated sections, and the corresponding calculation formula is as follows:
Figure DEST_PATH_IMAGE152
wherein,
Figure DEST_PATH_IMAGE154
the contamination level index values for the other nth piece of the contaminated material,
Figure 618494DEST_PATH_IMAGE032
for each contaminated area, the first set time is passedA sequence formed by biological activity indexes of each set position in the segment,
Figure DEST_PATH_IMAGE156
is a sequence formed by biological activity indexes of all set positions in a first set time period in the past in a sheet area with the highest pollution degree,
Figure 379515DEST_PATH_IMAGE022
in order to find the function of the degree of similarity,
Figure 686999DEST_PATH_IMAGE024
in order to solve the function of the absolute value,
Figure 249699DEST_PATH_IMAGE026
the length is calculated as pair.
In the above calculation formula of the contamination degree index value, the specific process of calculating the similarity between the two sequences and the specific process of calculating the modular length of the sequences may refer to step (4) above.
The method solves the problem that the urban river flow rate is slow and the polluted plot is difficult to determine based on the influence of the river pollution condition on river organisms, can determine the pollution diffusion condition of the polluted plot, and performs early warning and reminding at the moment when the plot pollution is not serious.
It should be noted that: the precedence order of the above embodiments of the present invention is only for description, and does not represent the merits of the embodiments. And specific embodiments thereof have been described above. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.

Claims (10)

1. A zonal pollution analysis method based on river biological activity is characterized by comprising the following steps:
acquiring PH values, dissolved oxygen contents and biological activity indexes of preset positions of 2N subareas of a river to be analyzed in a first set time period and a second set time period in the past;
determining the index fluctuation values of the 2N wafer areas according to the PH value, the dissolved oxygen content and the biological activity index of each set position of the 2N wafer areas in the past first set time period;
determining a pH value predicted value, a dissolved oxygen content predicted value and a biological activity index predicted value of each set position in a past second set time period corresponding to N patch matching pairs and N patch matching pairs according to the pH value, the dissolved oxygen content and the biological activity index of each set position in the past first set time period of 2N patch and the index fluctuation value of 2N patch;
determining a first pollution index value, a second pollution index value and a third pollution index value corresponding to 2N patch areas according to the pH value, the dissolved oxygen content and the biological activity index of each set position in a second past set time period of two patch areas in the N patch area matching pairs and the pH value, the dissolved oxygen content and the biological activity index of each set position in the second past set time period corresponding to the N patch area matching pairs;
and respectively determining whether the 2N areas are polluted or not according to the first pollution index value, the second pollution index value and the third pollution index value corresponding to the 2N areas.
2. The river bioactivity-based zonal contamination analysis method of claim 1, wherein the step of determining N zonal matching pairs comprises:
calculating overall approach index values between any two film areas according to the PH values, the dissolved oxygen contents and the biological activity indexes of the 2N film areas at each set position in the past first set time period and the index fluctuation values of the 2N film areas;
and pairing the 2N chip areas according to the overall approach index value between any two chip areas, thereby obtaining N chip area matching pairs.
3. The zonal pollution analysis method based on river bioactivities as claimed in claim 2, wherein the overall proximity index value between any two zones is corresponding to a calculation formula:
Figure DEST_PATH_IMAGE002
wherein,
Figure DEST_PATH_IMAGE004
the overall proximity index value between slice a and slice B,
Figure DEST_PATH_IMAGE006
is a sequence of PH values of each set position of the parcel a in the first set period of time in the past,
Figure DEST_PATH_IMAGE008
is a sequence formed by PH values of each set position in the past first set time period of the parcel B,
Figure DEST_PATH_IMAGE010
is a sequence of dissolved oxygen contents at each set location in the past first set time period for patch a,
Figure DEST_PATH_IMAGE012
is a sequence of dissolved oxygen contents at each set position in the past first set time period of the patch B,
Figure DEST_PATH_IMAGE014
is a sequence formed by biological activity indexes of all set positions of the film area A in the first set time period in the past,
Figure DEST_PATH_IMAGE016
is a sequence formed by biological activity indexes of all set positions of the film area B in the first set time period in the past,
Figure DEST_PATH_IMAGE018
is the index fluctuation value of the patch a,
Figure DEST_PATH_IMAGE020
is the index fluctuation value of the patch B,
Figure DEST_PATH_IMAGE022
in order to find the function of the degree of similarity,
Figure DEST_PATH_IMAGE024
in order to solve the function of the absolute value,
Figure DEST_PATH_IMAGE026
the length is calculated as pair.
4. The river bioactivity-based zonal pollution analysis method of claim 1, wherein the step of determining the PH, dissolved oxygen content, and bioactivity indicator predictions for each of the set locations over the second set time period in the past for the N zones matching comprises:
filtering the biological activity indexes of the 2N film areas at each set position in the past first set time period to obtain the biological activity indexes of the 2N film areas at each set position in the past first set time period after filtering;
predicting the PH value, the dissolved oxygen content and the biological activity index of each set position of the 2N slices in a second set time period in the past by using a time sequence prediction neural network according to the PH value and the dissolved oxygen content of each set position of the 2N slices in the first set time period in the past and the biological activity index of each set position of the 2N slices in the first set time period in the past after filtering;
and determining a predicted value of the pH value, a predicted value of the dissolved oxygen content and a predicted value of the biological activity index of each set position in the past second set time period corresponding to the N patch matching pairs according to the predicted pH value, the dissolved oxygen content and the biological activity index of each set position in the second set time period of the two patches of the N patch matching pairs and the index fluctuation value of the two patches of the N patch matching pairs.
5. The river bioactivity-based zonal pollution analysis method of claim 4, wherein the step of determining the PH, dissolved oxygen content, and bioactivity indicator predictions for each of the set locations over the second set time period in the past for the N zones comprises:
counting the reciprocal of the index fluctuation values of the two regions in the N region matching pairs, and then carrying out normalization processing to obtain the weight values of the two regions in the N region matching pairs;
and respectively carrying out weighted summation on the predicted PH value, the dissolved oxygen content and the biological activity index of the two districts in the N district matching pairs at each set position in a second set time period according to the weight values of the two districts in the N district matching pairs, thereby obtaining the predicted PH value, the predicted dissolved oxygen content and the predicted biological activity index of the N district matching pairs at each set position in the second set time period in the past.
6. The zonal pollution analysis method based on river bioactivities as claimed in claim 1, wherein the calculation formula for determining the index fluctuation value of 2N zones is:
Figure DEST_PATH_IMAGE028
wherein,
Figure DEST_PATH_IMAGE030
the index fluctuation value of the nth slice is,
Figure DEST_PATH_IMAGE032
the average value of the biological activity indexes of the nth sheet area at each set position in the first set time period in the past,
Figure DEST_PATH_IMAGE034
is the average value of the PH value of each set position of the nth block in the first set time period,
Figure DEST_PATH_IMAGE036
is the mean value of the dissolved oxygen content of each set position in the first set time period in the past of the nth plate area,
Figure DEST_PATH_IMAGE038
to find the variance function.
7. The river bioactivity-based zonal pollution analysis method of claim 1, wherein the step of determining a first pollution index value, a second pollution index value, and a third pollution index value for 2N zones comprises:
according to the PH value, the dissolved oxygen content and the biological activity index of two film areas in N film area matching pairs at each set position in the past second set time period and the PH value, the dissolved oxygen content and the biological activity index predicted value of the two film areas in the past second set time period corresponding to the N film area matching pairs at each set position in the past second set time period, calculating the module length of the PH value composition sequence, the module length of the dissolved oxygen content composition sequence, the module length of the biological activity index composition sequence of each film area in the N film area matching pairs at each set position in the past second set time period and the module length of the PH value composition sequence, the module length of the dissolved oxygen content composition sequence and the module length of the biological activity index predicted value composition sequence of each set position in the N film area matching pairs, and calculating the PH value composition sequence, the dissolved oxygen content index and the module length of the biological activity index predicted value composition sequence corresponding to each film area in the N film area matching pairs, The similarity between the dissolved oxygen content forming sequence and the biological activity index forming sequence, the dissolved oxygen content predicted value forming sequence and the biological activity index predicted value forming sequence are in one-to-one correspondence with the corresponding zone matching pair;
determining a first pollution index value corresponding to 2N fragment areas according to the modular length of a PH value composition sequence of each set position in a second past set time period of each fragment area in the N fragment area matching pairs, the modular length of a PH value predicted value composition sequence of each set position in the second past set time period corresponding to the N fragment area matching pairs, and the similarity between the PH value composition sequence corresponding to each fragment area in the N fragment area matching pairs and the PH value predicted value composition sequence corresponding to the corresponding fragment area matching pairs;
determining second pollution index values corresponding to 2N patch areas according to the modular length of a dissolved oxygen content composition sequence of each set position in a second past set time period of each patch area in the N patch area matching pairs, the modular length of a dissolved oxygen content predicted value composition sequence of each set position in the second past set time period corresponding to the N patch area matching pairs, and the similarity between the dissolved oxygen content composition sequence corresponding to each patch area in the N patch area matching pairs and the dissolved oxygen content predicted value composition sequence corresponding to the corresponding patch area matching pairs;
and determining a third pollution index value corresponding to 2N patch areas according to the module length of the bioactivity index forming sequence of each set position in the second past set time period of each patch area in the N patch area matching pairs, the module length of the bioactivity index predicted value forming sequence of each set position in the second past set time period corresponding to the N patch area matching pairs, and the similarity between the bioactivity index forming sequence corresponding to each patch area in the N patch area matching pairs and the bioactivity index predicted value forming sequence corresponding to the corresponding patch area matching pair.
8. The zonal contamination analysis method based on river bioactivities as claimed in claim 1, wherein the step of determining whether 2N zones are contaminated respectively comprises:
comparing the first pollution index value, the second pollution index value and the third pollution index value corresponding to each section with a first pollution index value threshold, a second pollution index value threshold and a third pollution index value threshold respectively;
if the first pollution index value of a certain zone is not less than the first pollution index value threshold, the second pollution index value is not less than the second pollution index value threshold and the third pollution index value is not less than the third pollution index value threshold, judging that the zone is not polluted, otherwise, judging that the corresponding zone is polluted.
9. The method for analyzing zonal pollution based on river bioactivities according to claim 1, further comprising:
if a certain zone is polluted, determining a first set number of target zones connected upstream and a second set number of target zones connected downstream;
acquiring the pH value, the dissolved oxygen content and the biological activity index of each uncontaminated target zone at each set position in a third set time period and the pH value, the dissolved oxygen content and the biological activity index of the other zone in the corresponding zone matching pair of the uncontaminated target zone at each set position in the third set time period, so as to determine a first diffusion index value, a second diffusion index value and a third diffusion index value of each uncontaminated target zone;
and determining whether the pollution diffusion occurs to each target area without pollution according to the first diffusion index value, the second diffusion index value and the third diffusion index value of each target area without pollution.
10. The river bioactivity-based zonal contamination analysis method of claim 9, wherein the step of determining whether contamination spread occurs for each target zone that is not contaminated comprises:
respectively comparing the first diffusion index value, the second diffusion index value and the third diffusion index value of each target area which is not polluted with a first diffusion index value threshold, a second diffusion index value threshold and a third diffusion index value threshold;
if the first diffusion index value of the target area without pollution is not less than the first diffusion index value threshold, the second diffusion index value is not less than the second diffusion index value threshold and the third diffusion index value is not less than the third diffusion index value threshold, judging that the target area without pollution is not subjected to pollution diffusion, and otherwise, judging that the target area without pollution is subjected to pollution diffusion.
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