CN114168670B

CN114168670B - Industrial ecological big data integration method and system and cloud platform

Info

Publication number: CN114168670B
Application number: CN202111464529.5A
Authority: CN
Inventors: 张海萍; 刘虎; 单骏
Original assignee: Suzhou Doctor Innovation Technology Transfer Co ltd
Current assignee: Suzhou Doctor Innovation Technology Transfer Co ltd
Priority date: 2021-12-03
Filing date: 2021-12-03
Publication date: 2022-12-27
Anticipated expiration: 2041-12-03
Also published as: CN114168670A

Abstract

The application provides an industrial ecological big data integration method, a system and a cloud platform, which remove a target boundary range with characteristic relevance meeting preset relevance parameters from the target boundary range to be selected, determine the difference degree of the industrial ecological monitoring data state of the first target boundary range to be selected, and eliminating a target boundary range to be selected with the difference degree of the industrial ecological monitoring data state larger than the preset state difference parameter from the first target boundary range to be selected to obtain a second target boundary range to be selected, and determining a target integration target boundary range according to the second target boundary range to be selected. Therefore, the target integration scheme has high integrity on the ecological monitoring data of the new industry, improves the precision of target integration, enables the boundary range of the target to be selected to be determined, and eliminates the difference parameters in the boundary range of the first target to be selected and the boundary range of the second target to be selected, and is beneficial to improving the accuracy of the boundary range of the target integration target.

Description

Industrial ecological big data integration method and system and cloud platform

Technical Field

The application relates to the technical field of data integration, in particular to an industrial ecological big data integration method, system and cloud platform.

Background

Data integration (Data association) is a way of collecting, sorting, cleaning and converting Data in different Data sources and then loading the Data into a new Data source, and provides a uniform Data integration mode for industrial ecological Data.

With the continuous progress of big data technology, the big data technology enables the relevant data integration technology to be continuously optimized, and improves the efficiency of relevant data integration.

However, there are some drawbacks in the related art integration technology.

Disclosure of Invention

In view of this, the present application provides an industrial ecological big data integration method, system and cloud platform.

In a first aspect, an industrial ecological big data integration method is provided, including:

carrying out industrial ecology monitoring data association on sample industrial ecology monitoring data of a target industrial ecology monitoring data strategy to be processed and industrial ecology monitoring data to be processed based on at least three industrial ecology monitoring data association modes, and determining a target boundary range to be selected of the target industrial ecology monitoring data strategy in the industrial ecology monitoring data to be processed, wherein the category of the target industrial ecology monitoring data strategy is at least one;

according to each target industry ecological monitoring data strategy, respectively extracting the characteristics of the corresponding sample industry ecological monitoring data and the boundary range of the target to be selected to obtain the characteristics of the sample industry ecological monitoring data and the characteristics of the industry ecological monitoring data corresponding to the boundary range of the target to be selected;

acquiring the characteristic relevance between sample industrial ecological monitoring data characteristics corresponding to the same target industrial ecological monitoring data strategy and industrial ecological monitoring data characteristics corresponding to a target boundary range to be selected, and removing the target boundary range to be selected, of which the characteristic relevance meets preset relevance parameters, from the target boundary range to be selected of the target industrial ecological monitoring data strategy to obtain a first target boundary range to be selected of each target industrial ecological monitoring data strategy;

determining the difference degree of the corresponding sample industrial ecological monitoring data and the industrial ecological monitoring data within the boundary range of the first target to be selected according to each target industrial ecological monitoring data strategy;

removing a to-be-selected target boundary range of each target industrial ecological monitoring data strategy, wherein the difference degree of the industrial ecological monitoring data strategy in the state is larger than that of a preset state difference parameter, from the first to-be-selected target boundary range of each target industrial ecological monitoring data strategy, so as to obtain a second to-be-selected target boundary range of each target industrial ecological monitoring data strategy;

and determining a target integration target boundary range of each target industry ecological monitoring data strategy according to the second candidate target boundary range of each target industry ecological monitoring data strategy.

Optionally, the sample industrial ecology monitoring data of the target industrial ecology monitoring data policy to be processed and the industrial ecology monitoring data to be processed are associated with each other based on at least three industrial ecology monitoring data association modes, so as to determine a target boundary range to be selected of the target industrial ecology monitoring data policy in the industrial ecology monitoring data to be processed, including:

carrying out industrial ecological environment association on sample industrial ecological monitoring data of a target industrial ecological monitoring data strategy to be processed and the industrial ecological monitoring data to be processed, determining industrial ecological monitoring data target boundary ranges meeting requirements of industrial ecological environment association of each target industrial ecological monitoring data strategy in the industrial ecological monitoring data to be processed, and using the industrial ecological monitoring data target boundary ranges as target boundary ranges to be selected of each target industrial ecological monitoring data strategy;

sample industrial ecological monitoring data of the target industrial ecological monitoring data strategy to be processed are subjected to sample association with the industrial ecological monitoring data to be processed, and an industrial ecological monitoring data target boundary range which meets the requirement of the sample association of each target industrial ecological monitoring data strategy in the industrial ecological monitoring data to be processed is determined and is used as a target boundary range to be selected of each target industrial ecological monitoring data strategy;

and performing characteristic point association on the sample industrial ecological monitoring data of the target industrial ecological monitoring data strategy to be processed and the industrial ecological monitoring data to be processed, and determining an industrial ecological monitoring data target boundary range which meets the requirement of the characteristic point association of each target industrial ecological monitoring data strategy in the industrial ecological monitoring data to be processed as a target boundary range to be selected of each target industrial ecological monitoring data strategy.

Optionally, the method for determining the industrial ecological monitoring data target boundary range, where the industrial ecological environment association of each target industrial ecological monitoring data policy in the to-be-processed industrial ecological monitoring data meets the requirement, before being used as the to-be-selected target boundary range of each target industrial ecological monitoring data policy, further includes:

acquiring an industrial ecology monitoring data content expression label of sample industrial ecology monitoring data aiming at the sample industrial ecology monitoring data of a target industrial ecology monitoring data strategy to be processed;

and if the industrial ecological monitoring data content expression label is a preset non-industrial ecological environment content label, aiming at the sample industrial ecological monitoring data of the target industrial ecological monitoring data strategy, not executing the sample industrial ecological monitoring data of the target industrial ecological monitoring data strategy to be processed, and carrying out industrial ecological environment association with the industrial ecological monitoring data to be processed.

Optionally, the performing sample association on the sample industrial ecological monitoring data of the target industrial ecological monitoring data policy to be processed and the industrial ecological monitoring data to be processed, determining an industrial ecological monitoring data target boundary range in which the sample association of each target industrial ecological monitoring data policy in the industrial ecological monitoring data to be processed meets requirements, and using the industrial ecological monitoring data target boundary range as a candidate target boundary range of each target industrial ecological monitoring data policy, includes:

carrying out industrial ecology monitoring data type division on the sample industrial ecology monitoring data of the target industrial ecology monitoring data strategy to be processed and the industrial ecology monitoring data to be processed respectively;

and carrying out sample association on the divided sample industry ecological monitoring data and the divided to-be-processed industry ecological monitoring data, and determining the boundary range of the to-be-selected target of each target industry ecological monitoring data strategy in the to-be-processed industry ecological monitoring data according to the association result.

Optionally, the extracting, for each target industry ecological monitoring data strategy, the industrial ecological monitoring data features of the corresponding sample industry ecological monitoring data and the target boundary range to be selected, to obtain the sample industry ecological monitoring data features and the industrial ecological monitoring data features corresponding to the target boundary range to be selected, includes:

aiming at each target industry ecological monitoring data strategy, identifying and processing corresponding sample industry ecological monitoring data to obtain identification characteristics of the sample industry ecological monitoring data as sample industry ecological monitoring data characteristics;

and aiming at each target industrial ecology monitoring data strategy, identifying the boundary range of the target to be selected corresponding to the strategy to obtain the identification characteristic of the boundary range of the target to be selected as the industrial ecology monitoring data characteristic corresponding to the boundary range of the target to be selected.

Optionally, the determining, for each target industry ecology monitoring data policy, a difference degree between the corresponding sample industry ecology monitoring data and the industry ecology monitoring data state of the first target boundary range to be selected includes:

determining a first industrial ecological index average probability of corresponding sample industrial ecological monitoring data and a second industrial ecological index average probability of the corresponding industrial ecological monitoring data in a first target boundary range to be selected aiming at each target industrial ecological monitoring data strategy;

and calculating the difference value between the average probability of the first industrial ecological index and the average probability of the second industrial ecological index to obtain the difference degree of the sample industrial ecological monitoring data of the target industrial ecological monitoring data strategy and the industrial ecological monitoring data state of the first target boundary range to be selected.

Optionally, the determining, for each target industry ecology monitoring data policy, a first industry ecology index average probability of corresponding sample industry ecology monitoring data and a second industry ecology index average probability of corresponding industry ecology monitoring data in a target boundary range to be selected includes:

if the sample industry ecological monitoring data of the target industry ecological monitoring data strategy or the area range of the corresponding first target boundary range to be selected is smaller than the preset area range, dividing the sample industry ecological monitoring data and the first target boundary range to be selected into industry ecological monitoring data chains with the same category according to a similar dividing mode, and obtaining sample sub-industry ecological monitoring data of the sample industry ecological monitoring data and the first target sub-target boundary range of the first target boundary range to be selected;

calculating the average probability of a first industrial ecological index of each sample sub-industry ecological monitoring data and the average probability of a second industrial ecological index of each first sub-industry ecological monitoring data to be selected within the boundary range;

the calculating a difference between the average probability of the first industrial ecological index and the average probability of the second industrial ecological index to obtain a difference degree of the sample industrial ecological monitoring data of the target industrial ecological monitoring data strategy and the industrial ecological monitoring data of the boundary range of the first target to be selected under the condition of the boundary range of the target industrial ecological monitoring data comprises the following steps: calculating the difference value of the average probabilities of the sample industry ecological monitoring data, the sample sub-industry ecological monitoring data at the corresponding position in the boundary range of the object to be selected and the industry ecological indexes of the boundary range of the first sub-object to be selected based on the average probability of the first industry ecological indexes and the average probability of the second industry ecological indexes;

the method for eliminating the target boundary range to be selected of each target industrial ecological monitoring data strategy, in which the difference degree of the industrial ecological monitoring data strategy in the state is greater than the target boundary range to be selected of the preset state difference parameters, from the first target boundary range to be selected of each target industrial ecological monitoring data strategy to obtain the second target boundary range to be selected of each target industrial ecological monitoring data strategy, includes: and removing the boundary range of the target to be selected, in which at least one industrial ecological index average probability difference value is larger than a preset difference value parameter, from the boundary range of the first target to be selected of each target industrial ecological monitoring data strategy to obtain the boundary range of the second target to be selected of each target industrial ecological monitoring data strategy.

Optionally, the determining a target integration target boundary range of each target industry ecology monitoring data policy according to a second candidate target boundary range of each target industry ecology monitoring data policy includes:

if the second candidate target boundary range does not coincide with other second candidate target boundary ranges, determining the second candidate target boundary range as a target integration target boundary range of a corresponding target industrial ecological monitoring data strategy;

if the boundary range of a second target to be selected is overlapped with the boundary ranges of other second targets to be selected, determining a minimum unit target boundary range containing the overlapped second target to be selected from the industrial ecological monitoring data to be processed, and determining sample industrial ecological monitoring data of a target industrial ecological monitoring data strategy corresponding to the minimum unit target boundary range;

correlating the minimum unit target boundary range with sample industrial ecological monitoring data of a target industrial ecological monitoring data strategy corresponding to the minimum unit target boundary range;

and determining a target industrial ecological monitoring data strategy finally corresponding to the minimum unit target boundary range and a target integration target boundary range of the target industrial ecological monitoring data strategy in the minimum unit target boundary range according to the correlation result.

In a second aspect, an industrial ecological big data integration system is provided, which includes a processor and a memory, which are communicated with each other, and the processor is configured to read a computer program from the memory and execute the computer program, so as to implement the above method.

In a third aspect, a cloud platform, comprising:

a memory for storing a computer program;

a processor coupled to the memory for executing the computer program stored by the memory to implement the above-described method.

The industrial ecological big data integration method, system and cloud platform provided by the embodiment of the application can associate the sample industrial ecological monitoring data of the target industrial ecological monitoring data strategy to be processed with the industrial ecological monitoring data to be processed based on at least three industrial ecological monitoring data association modes to determine the target boundary range to be selected of the target industrial ecological monitoring data strategy in the industrial ecological monitoring data to be processed, wherein the category of the target industrial ecological monitoring data strategy is at least one, and for each target industrial ecological monitoring data strategy, the industrial ecological monitoring data characteristic extraction is respectively carried out on the corresponding sample industrial ecological monitoring data and the target boundary range to be selected to obtain the sample industrial ecological monitoring data characteristic and the industrial ecological monitoring data characteristic corresponding to the target boundary range to be selected, acquiring the characteristic relevance between the sample industry ecological monitoring data characteristics corresponding to the same target industry ecological monitoring data strategy and the industry ecological monitoring data characteristics corresponding to a target boundary range to be selected, removing the target boundary range to be selected, the characteristic relevance of which meets preset relevance parameters, from the target boundary range to be selected of the target industry ecological monitoring data strategy to obtain a first target boundary range to be selected of each target industry ecological monitoring data strategy, determining the difference degree of the corresponding sample industry ecological monitoring data and the industry ecological monitoring data state of the first target boundary range to be selected aiming at each target industry ecological monitoring data strategy, removing the target boundary range to be selected, the difference degree of which is greater than the preset state difference parameter, from the first target boundary range to be selected of each target industry ecological monitoring data strategy, and obtaining a second candidate target boundary range of each target industrial ecological monitoring data strategy, and determining a target integration target boundary range of the target industrial ecological monitoring data strategy according to the second candidate target boundary range of each target industrial ecological monitoring data strategy. Therefore, a large amount of samples are not needed to be used for training, resources can be saved, the integrity of the new production ecological monitoring data is high through the target integration scheme, the target integration precision is improved, the difference parameters are eliminated from the boundary range of the target to be selected, the boundary range of the first target to be selected and the boundary range of the second target to be selected, and the accuracy of the boundary range of the target integration target is improved.

Drawings

To more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.

Fig. 1 is a flowchart of an industrial ecological big data integration method according to an embodiment of the present disclosure.

Fig. 2 is a block diagram of an industrial ecological big data integration apparatus according to an embodiment of the present disclosure.

Fig. 3 is an architecture diagram of an industrial ecological big data integration system according to an embodiment of the present application.

Detailed Description

In order to better understand the technical solutions, the technical solutions of the present application are described in detail below with reference to the drawings and specific embodiments, and it should be understood that the specific features in the embodiments and examples of the present application are detailed descriptions of the technical solutions of the present application, and are not limitations of the technical solutions of the present application, and the technical features in the embodiments and examples of the present application may be combined with each other without conflict.

Referring to fig. 1, an industrial ecological big data integration method is shown, which may include the technical solutions described in the following steps 100-600.

Step 100, performing industrial ecological monitoring data association on sample industrial ecological monitoring data of a target industrial ecological monitoring data strategy to be processed and industrial ecological monitoring data to be processed based on at least three industrial ecological monitoring data association modes, and determining a target boundary range to be selected of the target industrial ecological monitoring data strategy in the industrial ecological monitoring data to be processed.

Illustratively, the target industrial ecology monitoring data strategy represents the content of monitoring related industrial ecology data, for example, in the construction process of an industrial ecosystem, the obsolete equipment, industrial departments with high material consumption, high energy consumption and serious pollution, products with serious environmental negative effects and the like are inevitably eliminated.

Further, the boundary range of the target to be selected represents at least one category of the target industry ecology monitoring data strategy.

And 200, respectively extracting industrial ecological monitoring data characteristics of the corresponding sample industrial ecological monitoring data and the boundary range of the target to be selected according to each target industrial ecological monitoring data strategy to obtain the sample industrial ecological monitoring data characteristics and the industrial ecological monitoring data characteristics corresponding to the boundary range of the target to be selected.

Illustratively, the industrial ecology monitoring data characteristics represent key characteristics in the target industrial ecology monitoring data strategy.

Step 300, obtaining a feature correlation between sample industry ecological monitoring data features corresponding to the same target industry ecological monitoring data strategy and industry ecological monitoring data features corresponding to a target boundary range to be selected, and removing the target boundary range to be selected, of which the feature correlation meets preset correlation parameters, from the target boundary range to be selected of the target industry ecological monitoring data strategy to obtain a first target boundary range to be selected of each target industry ecological monitoring data strategy.

Illustratively, the first target boundary range to be selected represents information in the target industry ecology monitoring data strategy meeting the condition of preset relevance parameters.

Step 400, determining the difference degree between the corresponding sample industrial ecological monitoring data and the industrial ecological monitoring data state of the first target boundary range to be selected according to each target industrial ecological monitoring data strategy.

Step 500, eliminating the target boundary range to be selected, in which the difference degree of the industrial ecological monitoring data in the state is greater than the preset state difference parameter, from the first target boundary range to be selected of each target industrial ecological monitoring data strategy, and obtaining the second target boundary range to be selected of each target industrial ecological monitoring data strategy.

Illustratively, the second candidate target boundary range represents a boundary range of the candidate target boundary range in which the difference degree in the industry ecological monitoring data elimination state in the first candidate target boundary range is greater than the preset state difference parameter.

Step 600, determining a target integration target boundary range of each target industrial ecological monitoring data strategy according to a second candidate target boundary range of the target industrial ecological monitoring data strategy.

Illustratively, the target integrated target boundary scope represents an integrated scope of the target industry ecology monitoring data strategy.

It can be understood that, when the technical solutions described in the above steps 100 to 600 are executed, the sample industrial ecological monitoring data of the target industrial ecological monitoring data policy to be processed and the industrial ecological monitoring data to be processed are associated with the industrial ecological monitoring data based on at least three industrial ecological monitoring data association modes, so as to determine the boundary range of the target to be selected of the target industrial ecological monitoring data policy in the industrial ecological monitoring data to be processed, wherein the category of the target industrial ecological monitoring data policy is at least one, and for each target industrial ecological monitoring data policy, the industrial ecological monitoring data feature extraction is respectively performed on the corresponding sample industrial ecological monitoring data and the boundary range of the target to be selected, so as to obtain the sample industrial ecological monitoring data feature and the industrial ecological monitoring data feature corresponding to the boundary range of the target to be selected, acquiring the characteristic relevance between the sample industry ecological monitoring data characteristics corresponding to the same target industry ecological monitoring data strategy and the industry ecological monitoring data characteristics corresponding to a target boundary range to be selected, removing the target boundary range to be selected, the characteristic relevance of which meets preset relevance parameters, from the target boundary range to be selected of the target industry ecological monitoring data strategy to obtain a first target boundary range to be selected of each target industry ecological monitoring data strategy, determining the difference degree of the corresponding sample industry ecological monitoring data and the industry ecological monitoring data state of the first target boundary range to be selected aiming at each target industry ecological monitoring data strategy, removing the target boundary range to be selected, the difference degree of which is greater than the preset state difference parameter, from the first target boundary range to be selected of each target industry ecological monitoring data strategy, and obtaining a second candidate target boundary range of each target industrial ecological monitoring data strategy, and determining a target integration target boundary range of the target industrial ecological monitoring data strategy according to the second candidate target boundary range of each target industrial ecological monitoring data strategy. Therefore, a large amount of samples are not needed to be adopted for training, resources can be saved, the target integration scheme is high in integrity of new production ecological monitoring data, the target integration precision is improved, the difference parameters are eliminated from the boundary range of the target to be selected, the boundary range of the first target to be selected and the boundary range of the second target to be selected, and the accuracy of the boundary range of the target integration target is improved.

In an alternative embodiment, the inventor finds that, in order to improve the above technical problem, the sample industrial ecology monitoring data of the target industrial ecology monitoring data policy to be processed is associated with the industrial ecology monitoring data to be processed based on at least three industrial ecology monitoring data association manners, so that the industrial ecology monitoring data to be processed is associated with the industrial ecology monitoring data to be processed in an inaccurate industrial ecology environment, and thus it is difficult to accurately determine the target boundary range to be selected of the target industrial ecology monitoring data policy in the industrial ecology monitoring data to be processed, and the step of associating the sample industrial ecology monitoring data of the target industrial ecology monitoring data policy to be processed with the industrial ecology monitoring data to be processed based on at least three industrial ecology monitoring data association manners to determine the target boundary range to be selected of the target industrial ecology monitoring data policy in the industrial ecology monitoring data to be processed may specifically include the technical solutions described in the following steps q1 to q 3.

And q1, carrying out industrial ecological environment association on sample industrial ecological monitoring data of a target industrial ecological monitoring data strategy to be processed and the industrial ecological monitoring data to be processed, and determining an industrial ecological monitoring data target boundary range which meets requirements and is associated with the industrial ecological environment of each target industrial ecological monitoring data strategy in the industrial ecological monitoring data to be processed as a target boundary range to be selected of each target industrial ecological monitoring data strategy.

And q2, carrying out sample association on the sample industrial ecological monitoring data of the target industrial ecological monitoring data strategy to be processed and the industrial ecological monitoring data to be processed, and determining an industrial ecological monitoring data target boundary range which meets the requirement of the sample association of each target industrial ecological monitoring data strategy in the industrial ecological monitoring data to be processed as a target boundary range to be selected of each target industrial ecological monitoring data strategy.

And q3, performing characteristic point association on the sample industrial ecological monitoring data of the target industrial ecological monitoring data strategy to be processed and the industrial ecological monitoring data to be processed, and determining an industrial ecological monitoring data target boundary range which meets requirements and is associated with the characteristic points of each target industrial ecological monitoring data strategy in the industrial ecological monitoring data to be processed as a target boundary range to be selected of each target industrial ecological monitoring data strategy.

It can be understood that, when the technical solution described in the above step q1 to step q3 is executed, the sample industrial ecological monitoring data of the target industrial ecological monitoring data policy to be processed and the industrial ecological monitoring data to be processed are associated with each other based on at least three industrial ecological monitoring data association manners, so as to avoid the problem that the industrial ecological environment association performed on the industrial ecological monitoring data to be processed is not accurate, and thus the target boundary range to be selected of the target industrial ecological monitoring data policy in the industrial ecological monitoring data to be processed can be accurately determined.

Based on the above basis, before determining the industrial ecological monitoring data target boundary range of each target industrial ecological monitoring data policy in the to-be-processed industrial ecological monitoring data, where the industrial ecological environment association of each target industrial ecological monitoring data policy meets the requirement, as the to-be-selected target boundary range of each target industrial ecological monitoring data policy, the method may further include the following technical solutions described in steps w1 and w 2.

And w1, acquiring an industrial ecological monitoring data content expression label of the sample industrial ecological monitoring data aiming at the sample industrial ecological monitoring data of the target industrial ecological monitoring data strategy to be processed.

And w2, if the industrial ecological monitoring data content expression label is a preset non-industrial ecological environment content label, aiming at the sample industrial ecological monitoring data of the target industrial ecological monitoring data strategy, not executing the sample industrial ecological monitoring data of the target industrial ecological monitoring data strategy to be processed, and performing industrial ecological environment association with the industrial ecological monitoring data to be processed.

It can be understood that, when the technical solutions described in the above steps w1 and w2 are executed, the industrial ecological monitoring data content expression tag of the sample industrial ecological monitoring data is accurately obtained, so as to improve the accuracy of industrial ecological environment association of the to-be-processed industrial ecological monitoring data.

In an alternative embodiment, the inventor finds that, for sample association between the sample industrial ecological monitoring data of the target industrial ecological monitoring data policy to be processed and the industrial ecological monitoring data to be processed, there is a problem that classification of the types of the industrial ecological monitoring data is inaccurate, so that it is difficult to accurately determine an industrial ecological monitoring data target boundary range satisfying requirements for sample association of each target industrial ecological monitoring data policy in the industrial ecological monitoring data to be processed as a candidate target boundary range of each target industrial ecological monitoring data policy, and in order to improve the above technical problem, the step of performing sample association between the sample industrial ecological monitoring data of the target industrial ecological monitoring data policy to be processed, which is described in step q2, and the industrial ecological monitoring data to be processed, and determining an industrial ecological monitoring data target boundary range satisfying requirements for sample association of each target industrial ecological monitoring data policy in the industrial ecological monitoring data to be processed as a candidate target boundary range of each target industrial ecological monitoring data policy may specifically include the technical solutions described in the following steps q2a1 and q2a 2.

And q2a1, carrying out industrial ecology monitoring data type division on the sample industrial ecology monitoring data of the target industrial ecology monitoring data strategy to be processed and the industrial ecology monitoring data to be processed respectively.

And q2a2, carrying out sample association on the divided sample industrial ecological monitoring data and the divided industrial ecological monitoring data to be processed, and determining the boundary range of the target to be selected of each target industrial ecological monitoring data strategy in the industrial ecological monitoring data to be processed according to the association result.

It can be understood that, when the technical solutions described in the above step q2a1 and step q2a2 are executed, sample association is performed on the sample industrial ecological monitoring data of the target industrial ecological monitoring data policy to be processed and the industrial ecological monitoring data to be processed, so as to avoid the problem of inaccurate classification of the industrial ecological monitoring data, and thus, an industrial ecological monitoring data target boundary range, in which sample association of each target industrial ecological monitoring data policy in the industrial ecological monitoring data to be processed meets requirements, can be accurately determined as a target boundary range to be selected of each target industrial ecological monitoring data policy.

In an alternative embodiment, the inventor finds that, when performing industrial ecological monitoring data feature extraction on corresponding sample industrial ecological monitoring data and a target boundary range to be selected respectively according to each target industrial ecological monitoring data policy, there is a problem that the characteristics of the sample industrial ecological monitoring data are inaccurate, so that it is difficult to accurately obtain the characteristics of the sample industrial ecological monitoring data and the characteristics of the industrial ecological monitoring data corresponding to the target boundary range to be selected, and in order to improve the above technical problem, the step of performing industrial ecological monitoring data feature extraction on corresponding sample industrial ecological monitoring data and a target boundary range to be selected respectively according to each target industrial ecological monitoring data policy described in step 200 to obtain the characteristics of the sample industrial ecological monitoring data and the characteristics of the industrial ecological monitoring data corresponding to the target boundary range to be selected may specifically include the technical problems described in the following step e1 and step e 2.

And e1, aiming at each target industry ecological monitoring data strategy, identifying corresponding sample industry ecological monitoring data to obtain the identification characteristics of the sample industry ecological monitoring data as the sample industry ecological monitoring data characteristics.

And e2, aiming at each target industrial ecological monitoring data strategy, identifying the boundary range of the target to be selected corresponding to the target to be selected, and obtaining the identification characteristic of the boundary range of the target to be selected as the industrial ecological monitoring data characteristic corresponding to the boundary range of the target to be selected.

It can be understood that, when the technical problems described in the above step e1 and step e2 are performed, and for each target industrial ecological monitoring data strategy, when industrial ecological monitoring data features are extracted from the corresponding sample industrial ecological monitoring data and the target boundary range to be selected, the problem of inaccurate sample industrial ecological monitoring data features is avoided, so that the sample industrial ecological monitoring data features and the industrial ecological monitoring data features corresponding to the target boundary range to be selected can be accurately obtained.

In an alternative embodiment, the inventor finds that, for each target industry ecology monitoring data policy, there is a problem that the average probability of the first industry ecology index is not accurate, so that it is difficult to accurately determine the degree of difference between the corresponding sample industry ecology monitoring data and the industry ecology monitoring data state of the first target boundary range to be selected, and in order to improve the above technical problem, the step of determining the degree of difference between the corresponding sample industry ecology monitoring data and the industry ecology monitoring data state of the first target boundary range to be selected, which is described in step 400, for each target industry ecology monitoring data policy may specifically include the technical solutions described in step r1 and step r2 below.

And r1, aiming at each target industry ecological monitoring data strategy, determining a first industry ecological index average probability of corresponding sample industry ecological monitoring data and a second industry ecological index average probability of corresponding industry ecological monitoring data in a first target boundary range to be selected.

And r2, calculating a difference value between the average probability of the first industrial ecological index and the average probability of the second industrial ecological index to obtain the difference degree of the sample industrial ecological monitoring data of the target industrial ecological monitoring data strategy and the industrial ecological monitoring data of the first target boundary range to be selected in the state.

It can be understood that, when the technical solutions described in the above steps r1 and r2 are executed, the problem that the average probability of the first industrial ecological index is not accurate is avoided for each target industrial ecological monitoring data policy, so that the difference degree between the corresponding sample industrial ecological monitoring data and the industrial ecological monitoring data state of the first target boundary range to be selected can be accurately determined.

In an alternative embodiment, the inventor finds that, when aiming at each target industrial ecological monitoring data policy, there is a problem that the difference between the average probabilities of the industrial ecological indexes is inaccurate, so that it is difficult to accurately determine the average probability of the first industrial ecological index of the corresponding sample industrial ecological monitoring data and the average probability of the second industrial ecological index of the industrial ecological monitoring data in the corresponding target boundary range to be selected, and in order to improve the above technical problem, the step of determining the average probability of the first industrial ecological index of the corresponding sample industrial ecological monitoring data and the average probability of the second industrial ecological index of the industrial ecological monitoring data in the corresponding target boundary range to be selected, which is described in step r1, for each target industrial ecological monitoring data policy, may specifically include the technical solutions described in the following steps r1a 1-r 1a 4.

Step r1a1, if the sample industry ecological monitoring data of the target industry ecological monitoring data strategy or the area range of the corresponding first target boundary range to be selected is smaller than the preset area range, dividing the sample industry ecological monitoring data and the first target boundary range to be selected into industry ecological monitoring data chains with the same category according to a similar dividing mode, and obtaining the sample sub-industry ecological monitoring data of the sample industry ecological monitoring data and the first target sub-target boundary range of the first target boundary range to be selected.

And r1a2, calculating the average probability of a first industrial ecological index of each sample sub-industry ecological monitoring data and the average probability of a second industrial ecological index of each first sub-target boundary range to be selected.

Step r1a3, calculating a difference between the average probability of the first industrial ecological index and the average probability of the second industrial ecological index to obtain a difference degree of the sample industrial ecological monitoring data of the target industrial ecological monitoring data strategy and the industrial ecological monitoring data of the first target-to-be-selected boundary range under the condition of the boundary range, including: and calculating the difference value of the average probabilities of the sample industry ecological monitoring data and the sample sub-industry ecological monitoring data at the corresponding position in the boundary range of the target to be selected and the industry ecological index of the boundary range of the first sub-target to be selected based on the average probability of the first industry ecological index and the average probability of the second industry ecological index.

Step r1a4, the step of eliminating the boundary range of the target to be selected in which the difference degree of the industrial ecological monitoring data in the state is greater than the preset state difference parameter from the boundary range of the first target to be selected of each target industrial ecological monitoring data strategy to obtain the boundary range of the second target to be selected of each target industrial ecological monitoring data strategy comprises the following steps: and removing at least one target boundary range to be selected with an industrial ecological index average probability difference value larger than a preset difference value parameter from the first target boundary range to be selected of each target industrial ecological monitoring data strategy to obtain a second target boundary range to be selected of each target industrial ecological monitoring data strategy.

It can be understood that, when the technical solutions described in the above steps r1a1 to r1a4 are executed, and the problem of inaccurate difference of the average probabilities of the industrial ecological indexes is avoided for each target industrial ecological monitoring data policy, so that the average probability of the first industrial ecological index of the corresponding sample industrial ecological monitoring data and the average probability of the second industrial ecological index of the industrial ecological monitoring data in the corresponding target boundary range to be selected can be accurately determined.

In an alternative embodiment, the inventors found that, when the second candidate target boundary range of each target industry ecology monitoring data policy is used, there is a problem that the minimum unit target boundary range is inaccurate, so that it is difficult to accurately determine the target integration target boundary range of the target industry ecology monitoring data policy, and in order to improve the above technical problem, the step of determining the target integration target boundary range of the target industry ecology monitoring data policy according to the second candidate target boundary range of each target industry ecology monitoring data policy described in step 600 may specifically include the technical solutions described in the following steps i1 to i 4.

Step i1, if the second candidate target boundary range does not coincide with other second candidate target boundary ranges, determining the second candidate target boundary range as a target integration target boundary range of a corresponding target industry ecological monitoring data strategy.

And i2, if the boundary range of a second candidate target is overlapped with the boundary ranges of other second candidate targets, determining a minimum unit target boundary range containing the overlapped boundary range of the second candidate target from the industrial ecological monitoring data to be processed, and determining sample industrial ecological monitoring data of a target industrial ecological monitoring data strategy corresponding to the minimum unit target boundary range.

And i3, associating the minimum unit target boundary range with sample industry ecological monitoring data of a target industry ecological monitoring data strategy corresponding to the minimum unit target boundary range.

And i4, determining a target industry ecological monitoring data strategy finally corresponding to the minimum unit target boundary range and a target integration target boundary range of the target industry ecological monitoring data strategy in the minimum unit target boundary range according to the correlation result.

It can be understood that, when the technical solutions described in the above steps i1 to i4 are executed, and according to the second candidate target boundary range of each target industry ecology monitoring data policy, the problem that the minimum unit target boundary range is inaccurate is avoided, so that the target integration target boundary range of the target industry ecology monitoring data policy can be accurately determined.

In a possible embodiment, the inventor finds that there are many possible problems when associating the minimum unit target boundary range with the sample industrial ecological monitoring data of the target industrial ecological monitoring data policy corresponding to the minimum unit target boundary range, so that it is difficult to accurately associate the minimum unit target boundary range with the sample industrial ecological monitoring data of the target industrial ecological monitoring data policy corresponding to the minimum unit target boundary range, and in order to improve the above technical problems, the step of associating the minimum unit target boundary range with the sample industrial ecological monitoring data of the target industrial ecological monitoring data policy corresponding to the minimum unit target boundary range described in step i3 may specifically include the technical solutions described in the following step i3a1 and step i3a 2.

Step i3a1, if the number of the categories of the target industry ecological monitoring data policies corresponding to the minimum unit target boundary range is at least two, respectively performing sample association on the minimum unit target boundary range and the sample industry ecological monitoring data of each corresponding target industry ecological monitoring data policy to obtain a sample association target boundary range associated with each sample industry ecological monitoring data in the minimum unit target boundary range and a first sample association evaluation of the sample industry ecological monitoring data and the sample association target boundary range.

Illustratively, the first sample association evaluation is used for characterizing the association degree of the sample industry ecology monitoring data and the sample association target boundary range.

Step i3a2, determining a final corresponding target industry ecological monitoring data strategy of the minimum unit target boundary range and a target integration target boundary range of the target industry ecological monitoring data strategy in the minimum unit target boundary range according to the association result, including: and determining sample industry ecological monitoring data with the highest correlation degree and a sample correlation target boundary range according to the first sample correlation evaluation, and respectively using the sample industry ecological monitoring data with the highest correlation degree and the sample correlation target boundary range as a target industry ecological monitoring data strategy finally corresponding to the minimum unit target boundary range and a target integration target boundary range of the target industry ecological monitoring data strategy in the minimum unit target boundary range.

It can be understood that, when the technical solutions described in the above steps i3a1 and i3a2 are executed, the minimum unit target boundary range and the sample industry ecology monitoring data of the target industry ecology monitoring data strategy corresponding to the minimum unit target boundary range are associated, and analysis is performed for each situation, so that the association can be performed accurately.

Based on the above basis, before determining the target integration target boundary range of each target industrial ecology monitoring data policy according to the second candidate target boundary range of each target industrial ecology monitoring data policy, the following technical solutions described in step s1 and step s2 may also be included.

Step s1, aiming at each target industry ecological monitoring data strategy, carrying out sample association on corresponding sample industry ecological monitoring data and a second candidate target boundary range, and determining second sample association evaluation of each second candidate target boundary range.

Illustratively, the second sample association evaluation is used for characterizing the association degree between the sample industry ecology monitoring data and the second candidate target boundary range.

And step s2, eliminating the boundary range of the target to be selected, in which the second sample association evaluation meets the preset sample association score parameter, from the boundary range of the second target to be selected, so as to obtain the updated boundary range of the second target to be selected.

It can be understood that, when the technical solutions described in the above steps s1 and s2 are executed, the second candidate target boundary range after updating can be accurately obtained by evaluating each target industry ecology monitoring data policy.

On the basis, please refer to fig. 2 in combination, which provides an industrial ecological big data integration apparatus 200 applied to a cloud platform, the apparatus includes:

the range determining module 210 is configured to perform industrial ecology monitoring data association on sample industrial ecology monitoring data of a target industrial ecology monitoring data policy to be processed and the industrial ecology monitoring data to be processed based on at least three industrial ecology monitoring data association modes, and determine a target boundary range to be selected of the target industrial ecology monitoring data policy in the industrial ecology monitoring data to be processed, where the category of the target industrial ecology monitoring data policy is at least one;

the characteristic obtaining module 220 is configured to, for each target industry ecological monitoring data strategy, perform industry ecological monitoring data characteristic extraction on the corresponding sample industry ecological monitoring data and the boundary range of the target to be selected, respectively, to obtain sample industry ecological monitoring data characteristics and industry ecological monitoring data characteristics corresponding to the boundary range of the target to be selected;

a first range obtaining module 230, configured to obtain a feature association between sample industry ecological monitoring data features corresponding to a same target industry ecological monitoring data policy and industry ecological monitoring data features corresponding to a target boundary range to be selected, and remove, from the target boundary range to be selected of the target industry ecological monitoring data policy, a target boundary range to be selected where the feature association meets a preset association parameter, so as to obtain a first target boundary range to be selected of each target industry ecological monitoring data policy;

a difference determining module 240, configured to determine, for each target industrial ecology monitoring data policy, a difference degree between the corresponding sample industrial ecology monitoring data and the industrial ecology monitoring data state of the first target-to-be-selected boundary range;

a second range obtaining module 250, configured to remove, from a first target-to-be-selected boundary range of each target industrial ecological monitoring data policy, a target-to-be-selected boundary range in which a difference degree in the industrial ecological monitoring data state is greater than a preset state difference parameter, and obtain a second target-to-be-selected boundary range of each target industrial ecological monitoring data policy;

and a target range determining module 260, configured to determine a target integration target boundary range of each target industrial ecological monitoring data policy according to a second candidate target boundary range of the target industrial ecological monitoring data policy.

On the basis of the above, please refer to fig. 3, which shows an industrial ecological big data integration system 300, which includes a processor 310 and a memory 320 that are in communication with each other, wherein the processor 310 is configured to read a computer program from the memory 320 and execute the computer program to implement the above method.

On the basis of the above, there is also provided a computer-readable storage medium on which a computer program is stored, which when executed implements the above-described method.

In summary, based on the above solution, the sample industrial ecological monitoring data of the target industrial ecological monitoring data policy to be processed and the industrial ecological monitoring data to be processed are associated with each other based on at least three industrial ecological monitoring data association manners, so as to determine the target boundary range to be selected of the target industrial ecological monitoring data policy in the industrial ecological monitoring data to be processed, wherein the category of the target industrial ecological monitoring data policy is at least one, for each target industrial ecological monitoring data policy, the industrial ecological monitoring data feature extraction is respectively performed on the corresponding sample industrial ecological monitoring data and the target boundary range to be selected, so as to obtain the sample industrial ecological monitoring data feature and the industrial ecological monitoring data feature corresponding to the target boundary range to be selected, and obtain the feature association between the sample industrial ecological monitoring data feature corresponding to the same target industrial ecological monitoring data policy and the industrial ecological monitoring data feature corresponding to the target boundary range to be selected, removing a candidate target boundary range with characteristic relevance meeting preset relevance parameters from the candidate target boundary range of the target industrial ecological monitoring data strategy to obtain a first candidate target boundary range of each target industrial ecological monitoring data strategy, determining the difference degree of corresponding sample industrial ecological monitoring data and the industrial ecological monitoring data state of the first candidate target boundary range aiming at each target industrial ecological monitoring data strategy, removing the candidate target boundary range with the difference degree of the industrial ecological monitoring data state larger than the preset state difference parameters from the first candidate target boundary range of each target industrial ecological monitoring data strategy to obtain a second candidate target boundary range of each target industrial ecological monitoring data strategy, and determining a target integration target boundary range of the target industrial ecological monitoring data strategy according to the second candidate target boundary range of each target industrial ecological monitoring data strategy. Therefore, a large amount of samples are not needed to be adopted for training, resources can be saved, the target integration scheme is high in integrity of new production ecological monitoring data, the target integration precision is improved, the difference parameters are eliminated from the boundary range of the target to be selected, the boundary range of the first target to be selected and the boundary range of the second target to be selected, and the accuracy of the boundary range of the target integration target is improved.

It should be appreciated that the system and its modules shown above may be implemented in a variety of ways. For example, in some embodiments, the system and its modules may be implemented in hardware, software, or a combination of software and hardware. Wherein the hardware portion may be implemented using dedicated logic; the software portions may be stored in a memory for execution by a suitable instruction execution system, such as a microprocessor or specially designed hardware. Those skilled in the art will appreciate that the methods and systems described above may be implemented using computer executable instructions and/or embodied in processor control code, such code being provided, for example, on a carrier medium such as a diskette, CD-or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The system and its modules of the present application may be implemented not only by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but also by software executed by various types of processors, for example, or by a combination of the above hardware circuits and software (e.g., firmware).

It is to be noted that different embodiments may produce different advantages, and in different embodiments, any one or combination of the above advantages may be produced, or any other advantages may be obtained.

Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing detailed disclosure is to be considered merely illustrative and not restrictive of the broad application. Various modifications, improvements and adaptations to the present application may occur to those skilled in the art, though not expressly described herein. Such modifications, improvements and adaptations are proposed in the present application and thus fall within the spirit and scope of the exemplary embodiments of the present application.

Also, this application uses specific language to describe embodiments of the application. Reference to "one embodiment," "an embodiment," and/or "some embodiments" means a feature, structure, or characteristic described in connection with at least one embodiment of the application. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, some features, structures, or characteristics of one or more embodiments of the present application may be combined as appropriate.

Moreover, those skilled in the art will appreciate that aspects of the present application may be illustrated and described in terms of several patentable species or situations, including any new and useful combination of processes, machines, manufacture, or materials, or any new and useful improvement thereon. Accordingly, aspects of the present application may be embodied entirely in hardware, entirely in software (including firmware, resident software, micro-code, etc.) or in a combination of hardware and software. The above hardware or software may be referred to as "data block," module, "" engine, "" unit, "" component, "or" system. Furthermore, aspects of the present application may be represented as a computer product, including computer readable program code, embodied in one or more computer readable media.

The computer storage medium may comprise a propagated data signal with the computer program code embodied therewith, for example, on baseband or as part of a carrier wave. The propagated signal may have any of a variety of representations, including electromagnetic, optical, etc., or any suitable combination thereof. A computer storage medium may be any computer-readable medium that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code on a computer storage medium may be propagated over any suitable medium, including radio, cable, fiber optic cable, RF, or the like, or any combination of the preceding.

Computer program code required for various portions of the processes of the present application may be written in any one or more programming languages, including an object oriented programming language such as Java, scala, smalltalk, eiffel, JADE, emerald, C + +, C #, VB.NET, python, and the like, a conventional programming language such as C, visual Basic, fortran 2003, perl, COBOL 2002, PHP, ABAP, a dynamic programming language such as Python, ruby, and Groovy, or other programming languages, and the like. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any network expression, such as a Local Area Network (LAN) or a Wide Area Network (WAN), or to an external computer (e.g., through the Internet), or in a cloud computing environment, or as a service using, for example, software as a service (SaaS).

Additionally, unless explicitly recited in the claims, the order of processing elements and sequences, use of numbers and letters, or use of other designations in this application is not intended to limit the order of the processes and methods in this application. While various presently contemplated embodiments of the invention have been discussed in the foregoing disclosure by way of example, it is to be understood that such detail is solely for that purpose and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements that are within the spirit and scope of the embodiments herein. For example, although the system components described above may be implemented by hardware devices, they may also be implemented by software-only solutions, such as installing the described system on an existing server or mobile device.

Similarly, it should be noted that in the foregoing description of embodiments of the application, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the embodiments. This method of disclosure, however, is not intended to imply that more features are required than are expressly recited in the claims. Indeed, the embodiments may be characterized as having less than all of the features of a single embodiment disclosed above.

Some embodiments use numbers to describe the components, property classes, it being understood that such numbers used in the description of the embodiments are modified in some instances by the modifier "about", "approximately" or "substantially". Unless otherwise indicated, "about", "approximately" or "substantially" indicates that the numbers allow for variation in flexibility. Accordingly, in some embodiments, the numerical parameters set forth in the specification and claims are approximations that may vary depending upon the desired properties sought to be obtained by a particular embodiment. In some embodiments, the numerical parameter should take into account the specified significant digits and employ a general digit-preserving approach. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the range are approximations, in the specific examples, such numerical values are set forth as precisely as possible within the scope of the application.

Each patent, patent application publication, and other material, such as articles, books, specifications, publications, documents, and the like, cited in this application is hereby incorporated by reference in its entirety. Except where the application history document is inconsistent or conflicting with the present application as to the extent of the present claims, which are now or later appended to this application. It is to be understood that the descriptions, definitions and/or uses of terms in the attached materials of this application shall control if they are inconsistent or inconsistent with the statements and/or uses of this application.

Finally, it should be understood that the embodiments described herein are merely illustrative of the principles of the embodiments of the present application. Other variations are also possible within the scope of the present application. Thus, by way of example, and not limitation, alternative configurations of the embodiments of the present application may be viewed as being consistent with the teachings of the present application. Accordingly, the embodiments of the present application are not limited to only those explicitly described and illustrated herein.

The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement or the like made within the spirit and principle of the present application shall be included in the scope of the claims of the present application.

Claims

1. An industrial ecological big data integration method is characterized by comprising the following steps:

according to each target industrial ecological monitoring data strategy, respectively extracting industrial ecological monitoring data characteristics of corresponding sample industrial ecological monitoring data and a target boundary range to be selected to obtain sample industrial ecological monitoring data characteristics and industrial ecological monitoring data characteristics corresponding to the target boundary range to be selected;

2. The industrial ecological big data integration method according to claim 1, wherein the sample industrial ecological monitoring data of the target industrial ecological monitoring data policy to be processed and the industrial ecological monitoring data to be processed are associated with the industrial ecological monitoring data based on at least three industrial ecological monitoring data association modes, and the target boundary range to be selected of the target industrial ecological monitoring data policy in the industrial ecological monitoring data to be processed is determined, and the method comprises the following steps:

carrying out industrial ecological environment association on sample industrial ecological monitoring data of a target industrial ecological monitoring data strategy to be processed and the industrial ecological monitoring data to be processed, and determining an industrial ecological monitoring data target boundary range which meets requirements and is associated with the industrial ecological environment of each target industrial ecological monitoring data strategy in the industrial ecological monitoring data to be processed as a target boundary range to be selected of each target industrial ecological monitoring data strategy;

carrying out sample association on the sample industrial ecological monitoring data of the target industrial ecological monitoring data strategy to be processed and the industrial ecological monitoring data to be processed, and determining an industrial ecological monitoring data target boundary range which meets the requirement of the sample association of each target industrial ecological monitoring data strategy in the industrial ecological monitoring data to be processed as a target boundary range to be selected of each target industrial ecological monitoring data strategy;

and performing characteristic point association on the sample industrial ecology monitoring data of the target industrial ecology monitoring data strategy to be processed and the industrial ecology monitoring data to be processed, and determining an industrial ecology monitoring data target boundary range which satisfies the requirement of the characteristic point association of each target industrial ecology monitoring data strategy in the industrial ecology monitoring data to be processed as a target boundary range to be selected of each target industrial ecology monitoring data strategy.

3. The industrial ecological big data integration method according to claim 2, wherein the sample industrial ecological monitoring data of the target industrial ecological monitoring data policy to be processed is associated with the industrial ecological monitoring data to be processed in an industrial ecological environment, and before determining that the industrial ecological environment association of each target industrial ecological monitoring data policy in the industrial ecological monitoring data to be processed meets the required industrial ecological monitoring data target boundary range, the method further comprises:

and if the industrial ecological monitoring data content expression label is a preset non-industrial ecological environment content label, aiming at the sample industrial ecological monitoring data of the target industrial ecological monitoring data strategy, not executing the sample industrial ecological monitoring data of the target industrial ecological monitoring data strategy to be processed, and carrying out industrial ecological environment association on the sample industrial ecological monitoring data of the target industrial ecological monitoring data strategy to be processed and the industrial ecological environment association on the sample industrial ecological monitoring data of the target industrial ecological monitoring data strategy to be processed.

4. The industrial ecological big data integration method according to claim 2, wherein the step of performing sample association on the sample industrial ecological monitoring data of the target industrial ecological monitoring data policy to be processed and the industrial ecological monitoring data to be processed to determine an industrial ecological monitoring data target boundary range in which the sample association of each target industrial ecological monitoring data policy in the industrial ecological monitoring data to be processed meets requirements, as a target boundary range to be selected of each target industrial ecological monitoring data policy, comprises:

5. The industrial ecological big data integration method according to claim 1, wherein the extracting of the industrial ecological monitoring data characteristics of the corresponding sample industrial ecological monitoring data and the boundary range of the target to be selected is performed respectively for each target industrial ecological monitoring data strategy to obtain the sample industrial ecological monitoring data characteristics and the industrial ecological monitoring data characteristics corresponding to the boundary range of the target to be selected, and the extracting includes:

6. The industrial ecological big data integration method according to claim 1, wherein the determining, for each target industrial ecological monitoring data strategy, the degree of difference between the corresponding sample industrial ecological monitoring data and the industrial ecological monitoring data state of the first target boundary range to be selected comprises:

7. The industrial ecological big data integration method according to claim 6, wherein the determining, for each target industrial ecological monitoring data policy, a first industrial ecological index average probability of corresponding sample industrial ecological monitoring data and a second industrial ecological index average probability of corresponding industrial ecological monitoring data in a boundary range of a candidate target comprises:

the calculating a difference value between the average probability of the first industrial ecological index and the average probability of the second industrial ecological index to obtain a difference degree of the state of the sample industrial ecological monitoring data of the target industrial ecological monitoring data strategy and the state of the industrial ecological monitoring data of the first target boundary range to be selected comprises the following steps: calculating the difference value of the average probabilities of the sample industry ecological monitoring data, the sample sub-industry ecological monitoring data at the corresponding position in the boundary range of the object to be selected and the industry ecological indexes of the boundary range of the first sub-object to be selected based on the average probability of the first industry ecological indexes and the average probability of the second industry ecological indexes;

the method for eliminating the target boundary range to be selected of each target industrial ecological monitoring data strategy, in which the difference degree of the industrial ecological monitoring data strategy in the state is greater than the target boundary range to be selected of the preset state difference parameters, from the first target boundary range to be selected of each target industrial ecological monitoring data strategy to obtain the second target boundary range to be selected of each target industrial ecological monitoring data strategy, includes: and removing at least one target boundary range to be selected with an industrial ecological index average probability difference value larger than a preset difference value parameter from the first target boundary range to be selected of each target industrial ecological monitoring data strategy to obtain a second target boundary range to be selected of each target industrial ecological monitoring data strategy.

8. The industrial ecological big data integration method according to any one of claims 1 to 7, wherein the determining a target integration target boundary range of each target industrial ecological monitoring data policy according to a second candidate target boundary range of the target industrial ecological monitoring data policy comprises:

correlating the minimum unit target boundary range with sample industry ecology monitoring data of a target industry ecology monitoring data strategy corresponding to the minimum unit target boundary range;

9. An industrial ecological big data integration system, characterized in that it comprises a processor and a memory which are communicated with each other, the processor is used for reading computer programs from the memory and executing the computer programs so as to realize the method of any claim 1-8.

10. A cloud platform, comprising:

a memory for storing a computer program;

a processor coupled to the memory for executing the computer program stored by the memory to implement the method of any of claims 1-8.