Marine ecological environment assessment method and system based on artificial intelligence

Abstract

The invention discloses a marine ecological environment assessment method and system based on artificial intelligence, and relates to the technical field of artificial intelligence, and the system comprises a control center which is connected with an intelligent collection module, an ecological processing module, an environment analysis module and a comprehensive examination module. Extracting and analyzing the marine environment data, and constructing a standard environment curve graph for form reconstruction to obtain a preprocessed environment sequence; setting a cyclic capture coefficient to capture the preprocessed environment sequence to obtain a balanced allocation coefficient segment, and performing cyclic decomposition extraction and sequence updating on the preprocessed environment sequence according to the balanced allocation coefficient segment to obtain an environment identity coding sequence; performing grade assignment on the quality standard data to obtain a quality grade coding set, and performing comprehensive evaluation on the environment identity coding sequence according to the quality grade coding set to obtain an environment judgment integral; a large amount of data is automatically processed, the evaluation period is shortened, and evaluation efficiency and evaluation result accuracy are improved.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to an artificial intelligence-based marine ecological environment assessment method and system. Background Art

[0002] Artificial intelligence refers to systems created by humans that learn and improve their performance by analyzing large amounts of data.

[0003] Marine ecological environment assessment is of great significance for the rational development and protection of marine resources, including helping to understand and monitor changes in marine diversity, so as to take appropriate measures to protect endangered species and ecosystems for sustainable survival; it can monitor marine pollution and help formulate strategies to reduce pollution and repair damaged ecosystems; it helps to ensure that marine resources are rationally managed and sustainably used; while traditional assessment methods rely on manual sampling and data analysis, which are inefficient and have limited data accuracy. The development of artificial intelligence technology has provided a new means for marine ecological environment assessment. To this end, a marine ecological environment assessment method and system based on artificial intelligence is provided to efficiently process large amounts of data and improve the accuracy and efficiency of the assessment. Summary of the invention

[0004] The purpose of the present invention is to provide a marine ecological environment assessment method and system based on artificial intelligence.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] An artificial intelligence-based marine ecological environment assessment system includes a control center, wherein the control center is connected to an intelligent acquisition module, an ecological processing module, an environmental analysis module, and a comprehensive review module;

[0007] The process of collecting marine environment data and quality standard data by the intelligent collection module includes:

[0008] Divide the ocean area for collection and obtain ocean capture blocks;

[0009] Set up a collection plan, conduct field collection of the ocean capture block according to the collection plan, obtain ocean environmental data, perform identity marking on the obtained ocean environmental data, and obtain time marking points;

[0010] Set up a standard collection terminal, collect programs through the standard collection terminal, and obtain quality standard data.

[0011] The process of obtaining a preprocessing environment sequence includes:

[0012] Perform quality extraction on the obtained marine environmental data to obtain water quality relationship data and nutrient data, perform hazard analysis on the obtained marine environmental data to obtain pollutant content data, perform species extraction on the obtained marine environmental data to obtain biodiversity data;

[0013] Mark the obtained water quality relationship data, nutrient data, pollutant content data and biodiversity data as standard environmental data;

[0014] Constructing a two-dimensional rectangular coordinate system of time-dependent standard environment data, generating an environment data change line according to the obtained standard environment data, uploading the obtained environment data change line to the two-dimensional rectangular coordinate system, and obtaining a standard environment curve diagram;

[0015] The obtained standard environment curve graph is formally reconstructed to obtain a preprocessing environment sequence.

[0016] The process of setting the cyclic capture coefficient of the environment analysis module to capture the preprocessing environment sequence includes:

[0017] Sequence marking is performed on the pre-processed environment sequence to obtain response sample points;

[0018] Set the loop capture coefficient, and divide the loop capture coefficient according to the response sample points to obtain the loop level;

[0019] The shape of the loop capture coefficient is adjusted to obtain the adjustment parameters, and the loop capture coefficient is captured and divided according to the obtained adjustment parameters to obtain the balanced adjustment coefficient segments.

[0020] The process of obtaining the environment identity encoding sequence includes:

[0021] Based on the cycle level, the preprocessed environment sequence is subjected to cyclic decomposition and extraction according to the obtained balanced allocation coefficient segments to obtain the environment identity sequence segments;

[0022] Performing sequence encoding on the obtained environment identity sequence segment to obtain an environment identity encoding segment;

[0023] The marine environment data are sorted based on time marking points to obtain an environment data time series, and the environment identity coding segments are sequentially updated according to the environment data time series to obtain an environment identity coding sequence.

[0024] The process of assigning grades to quality standard data by the comprehensive review module includes:

[0025] The obtained quality standard data is graded to obtain quality judgment grades, and the quality judgment grades are assigned values ​​to obtain quality grade points;

[0026] The obtained quality standard data is serially encoded based on the quality judgment level to obtain the quality standard code, a quality level code set is constructed according to the quality standard code, and the quality standard code is uploaded to the quality level code set.

[0027] The process of moving and comparing the environmental identity code sequence according to the quality level code set and obtaining the comparison matching code includes:

[0028] Upload the quality standard code to the environment identity code sequence based on the quality level code set;

[0029] Comparing the environmental identity coding sequence bit by bit through the quality standard coding to obtain a comparison result, wherein the comparison result includes a matching comparison and a difference comparison;

[0030] When the comparison result is a matching control, the quality standard code corresponding to the comparison result is recorded as the control matching code, and the bit-by-bit comparison is terminated;

[0031] When the comparison result is a difference comparison, the quality standard code is moved to the next bit in the environmental identity code sequence for bit-by-bit comparison. If the comparison result is a match comparison, the bit-by-bit comparison ends. If the comparison result is a difference comparison, the quality standard code continues to be moved to the next bit until it moves to the last bit of the environmental identity code sequence. If a comparison result is a match comparison, a comparison matching code is obtained. If the comparison results are all difference comparisons, the next quality standard code in the quality level code set is uploaded to the environmental identity code sequence. The process of obtaining the comparison result is repeated until all quality standard codes in the quality code set are uploaded to the environmental identity code sequence and compared bit by bit with the environmental identity code sequence. The quality standard code corresponding to the comparison result obtained as a match comparison is recorded as a comparison matching code.

[0032] The process of assessing and determining ocean catch blocks by comparing and matching codes includes:

[0033] Construct a matching code set according to the comparison matching code, and upload the comparison matching code to the matching code set;

[0034] Based on the quality grade score, the quality of the ocean capture block is judged according to the obtained matching code set to obtain the environmental judgment score.

[0035] Based on the above-mentioned marine ecological environment assessment system based on artificial intelligence, the present invention also provides a marine ecological environment assessment method based on artificial intelligence, comprising the following steps:

[0036] Step 1: Collect marine environmental data and quality standard data;

[0037] Step 2: Extract and analyze the marine environment data to obtain standard environment data, construct a standard environment curve chart based on the standard environment data, reconstruct the standard environment curve chart in form, and obtain a preprocessed environment sequence;

[0038] Step 3: Set the cyclic capture coefficient to capture the pre-processed environment sequence to obtain the balanced adjustment coefficient segment, perform cyclic decomposition and extraction on the pre-processed environment sequence to obtain the environment identity sequence segment, perform sequence encoding and sequence update on the environment identity sequence segment to obtain the environment identity encoding sequence;

[0039] Step 4: Assign grades to the quality standard data to obtain a quality grade code set, perform mobile comparison on the environmental identity code sequence based on the quality grade code set to obtain a comparison matching code, evaluate and determine the marine capture block through the comparison matching code, and obtain an environmental determination score.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] The collected marine environmental data is processed and converted into a form to obtain a pre-processed environmental sequence. By capturing, decomposing and extracting features from the pre-processed environmental sequence, the feature segment corresponding to the identity information is obtained, which is the environmental identity coding sequence. Large amounts of data can be processed automatically, greatly shortening the evaluation cycle. By collecting data in real time, real-time evaluation can be performed to achieve dynamic monitoring of the marine ecological environment.

[0042] The collected standard environmental judgment data are graded, assigned values ​​and encoded to obtain coding segments in the same form as the environmental identity coding sequence. The environmental identity coding sequence is comprehensively evaluated through the quality-level coding set to obtain the environmental judgment score. The collected detection data are converted into an integral form that is easy to observe, which is conducive to quickly measuring the ecological quality of marine blocks and improving the accuracy of evaluation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0045] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] like Figure 1 As shown, an artificial intelligence-based marine ecological environment assessment system includes a control center, and the control center is connected to an intelligent collection module, an ecological processing module, an environmental analysis module, and a comprehensive review module;

[0047] The intelligent acquisition module is used to collect marine environment data and quality standard data, and the specific process includes:

[0048] Divide the ocean area for collection and obtain ocean capture blocks;

[0049] Furthermore, the acquisition division means dividing the marine area that needs to be evaluated for the ecological environment into areas of fixed size, namely, marine capture blocks;

[0050] Setting a collection plan, performing field collection on the ocean capture block according to the obtained collection plan, obtaining ocean environmental data, and associating the obtained ocean environmental data with the corresponding ocean capture block;

[0051] The acquisition plan represents a plan for collecting information set for the ocean capture block, including acquisition location nodes, acquisition frequency, and acquisition data type;

[0052] The marine environmental data includes biological species, seawater sample data, environmental parameters and marine geological information, wherein biological species include the species and quantity of fish, plankton and benthic organisms, seawater sample data means extracting seawater samples from marine capture blocks to obtain sample data, environmental parameters include but are not limited to coral reef conditions, seagrass bed distribution, beach erosion conditions, etc., marine geological information includes but is not limited to sea surface temperature, wind speed, waves, tides, seabed topography, sediment types, etc., and the marine environmental data is data information related to the ecological environment of the corresponding marine capture block;

[0053] The acquired marine environment data is identity-tagged to obtain time-tagged points and position-tagged points, wherein the time-tagged points represent the time information corresponding to the acquisition of the marine environment data, and the position-tagged points represent the position information corresponding to the acquisition of the marine environment data, that is, the acquisition time point and the acquisition position information can be simultaneously obtained according to the marine environment data;

[0054] Setting a standard collection terminal, performing program collection through the standard collection terminal, and obtaining quality standard data, wherein the quality standard data includes chemical indicators, biological indicators, and water quality indicators;

[0055] Furthermore, the standardized collection end is standardized evaluation data collected through official channels, that is, each corresponding data has its limited range. The official channels include the standard content ranges corresponding to the qualified conditions and pollution conditions of the marine ecological environment formulated by research institutions and environmental protection organizations, that is, the quality standard data. The quality standard data is used to measure the assessment level of the marine ecological environment. The chemical indicators include but are not limited to chemical oxygen demand, chemical oxygen demand, biochemical oxygen demand, biochemical oxygen demand, total nitrogen, total nitrogen, total phosphorus, total phosphorus, heavy metal content (such as mercury, lead, cadmium, etc.) and organic pollutant content. The biological indicators include biodiversity index and biomass. The water quality indicators include but are not limited to dissolved oxygen concentration, pH value, water temperature, and salinity.

[0056] The ecological processing module is used to extract and analyze the marine environmental data and construct a standard environmental curve diagram for formal reconstruction to obtain a preprocessed environmental sequence. The specific process includes:

[0057] Perform quality extraction on the acquired marine environment data to obtain water quality relationship data and nutrient data;

[0058] Furthermore, the quality extraction means uploading the seawater sample data and the marine geological information in the marine environment data to the laboratory, and obtaining the water quality relationship data and the nutrient data through laboratory instrument analysis and chemical composition analysis. The water quality relationship data includes water temperature, salinity, pH value, dissolved oxygen, chemical oxygen demand, biochemical oxygen demand, and the nutrient data includes but is not limited to nutrient elements such as nitrogen, phosphorus, and silicon;

[0059] Conduct hazard analysis on the acquired marine environmental data to obtain pollutant content data;

[0060] The hazard analysis means uploading the obtained biological species, seawater sample data, and environmental parameters to the laboratory for analysis to obtain pollutant content data, which includes heavy metals, organic pollutants, bacteria, and viruses;

[0061] Extract species from the acquired marine environment data to obtain biodiversity data;

[0062] Further, the species extraction represents the evaluation of biological species in the marine environmental data, obtaining the species richness and species evenness in the marine capture block, and obtaining the species diversity index in the marine capture block through index analysis, wherein the index analysis represents the analysis method used to analyze the species indicators of the marine capture block, and the index analysis can use the Shannon-Wiener index to analyze the diversity index of the marine capture block, and the obtained species richness, species evenness and species diversity index are marked as biodiversity data;

[0063] Mark the obtained water quality relationship data, nutrient data, pollutant content data and biodiversity data as standard environmental data;

[0064] Constructing a two-dimensional rectangular coordinate system of time-dependent standard environment data, generating an environment data change line according to the obtained standard environment data, uploading the obtained environment data change line to the two-dimensional rectangular coordinate system, and obtaining a standard environment curve diagram;

[0065] Further, according to the water quality relationship data, nutrient data, pollutant content data and biodiversity data included in the standard environmental data, the environmental data change line includes the water quality relationship data line, the nutrient data line, the pollutant content data line and the biodiversity data line, and the obtained standard environmental curve diagram contains all environmental data change lines, and according to the time mark point corresponding to the marine environmental data, the horizontal axis in the standard environmental curve diagram is arranged according to the time mark point, and the intersection of the time mark point and the environmental data change line represents the standard environmental data corresponding to the time mark point;

[0066] Formally reconstructing the obtained standard environment curve map to obtain a preprocessing environment sequence;

[0067] The form reconstruction mark converts the environmental data change line in the standard environmental curve diagram into a sequence in signal form, that is, one change line corresponds to one sequence. According to the water quality relationship data line, nutrient data line, pollutant content data line and biodiversity data line included in the environmental data change line in the standard environmental curve diagram, the preprocessed environmental sequence includes a water quality relationship sequence, a nutrient sequence, a pollutant content sequence and a biodiversity sequence.

[0068] The environment analysis module is used to set the cyclic capture coefficient to capture the pre-processed environment sequence, obtain the balanced adjustment coefficient segment, perform cyclic decomposition extraction and sequence update on the pre-processed environment sequence according to the balanced adjustment coefficient segment, and obtain the environment identity coding sequence. The specific process includes:

[0069] Setting a loop capture coefficient, wherein the loop capture coefficient is expressed in a function form;

[0070] Sequence marking is performed on the obtained pre-processed environment sequence to obtain response sample points;

[0071] Furthermore, according to the expression form of the preprocessing environment sequence being a signal form, the sampling points in the signal are marked as response sample points, and the obtained response sample points are marked as i, where i=1, 2, 3, ..., v1, and v1 is a positive integer;

[0072] According to the obtained response sample points, the cyclic capture coefficient is cyclically divided to obtain a cyclic level, wherein the cyclic division means dividing the number of cycles of the cyclic capture coefficient to obtain a cyclic level, that is, the cyclic level is equal to the number of response sample points;

[0073] Performing shape adjustment on the obtained cycle capture coefficient to obtain a deployment parameter;

[0074] The shape adjustment means controlling the scaling and translation transformation of the loop capture coefficients in the time dimension and the frequency dimension, and recording the distance of the scaling and translation transformation to obtain the adjustment parameters;

[0075] Capture and divide the cyclic capture coefficient according to the obtained allocation parameters to obtain a balanced allocation coefficient segment;

[0076] It should be further explained that, in the specific implementation process, the capture and division process includes:

[0077] Perform spacing statistics on the loop capture coefficient based on the deployment parameters to obtain the deployment spacing;

[0078] The spacing statistics represent that the distance between two adjacent deployment parameters is counted in the cycle capture coefficient to obtain the deployment spacing;

[0079] The loop capture coefficient is divided and counted according to the obtained deployment parameters and deployment intervals to obtain a division statistic, and the obtained division statistic is marked as HT, where: , and the obtained partition statistic is rounded down, the obtained partition statistic is a positive integer, L represents the length of the loop capture coefficient, a represents the deployment spacing, m represents the number of deployment spacings in the loop capture coefficient, and b represents the deployment parameter;

[0080] According to the obtained partition statistics, the cycle capture coefficients are equally intercepted to obtain a balanced allocation coefficient segment;

[0081] The equal amount interception means that the cyclic capture coefficient is equally divided according to the number of the partition statistics to obtain equal length balanced adjustment coefficient segments, and the number of the balanced adjustment coefficient segments is the same as the number of the partition statistics;

[0082] Based on the cycle level, the preprocessed environment sequence is subjected to cyclic decomposition and extraction according to the obtained balanced allocation coefficient segments to obtain the environment identity sequence segments;

[0083] Furthermore, the process of loop decomposition and extraction includes:

[0084] Uploading the obtained balanced adjustment coefficient segments to each layer of the circulation level based on the order of the circulation level, wherein the arrangement order of the balanced adjustment coefficient segments in the circulation level is based on the order of equal interception;

[0085] The obtained pre-processing environment sequence is uploaded to the first layer of the loop level, and the pre-processing environment sequence is convolved with the balanced allocation coefficient segment to obtain the distribution processing coefficient segment, based on the order of equal interception, until all the balanced allocation coefficient segments are convolved with the pre-processing environment sequence, the obtained distribution processing coefficient segments are summed to obtain the environment level sequence;

[0086] The obtained environment level sequence is uploaded to the second loop level, the environment level sequence is convolved and summed through the equalization adjustment coefficient segment to obtain the environment level sequence, and the obtained environment level sequence is marked as the second environment level sequence;

[0087] The obtained second environment level sequence is uploaded to the next loop level, and the process of obtaining the environment level sequence is repeated until the last loop level is reached, and the environment level sequence obtained in the last loop level is marked as an environment identity sequence segment;

[0088] Performing sequence encoding on the obtained environment identity sequence segment to obtain an environment identity encoding segment;

[0089] It should be further explained that, in the specific implementation process, the sequence encoding means converting the obtained environment identity sequence segment into a string form, encoding the environment identity sequence segment through hash encoding, and obtaining the environment identity encoding segment;

[0090] Further, according to the water quality relationship sequence, nutrient sequence, pollutant content sequence and biodiversity sequence included in the pre-processed environment sequence, the environment identity coding segment is obtained according to the pre-processed environment sequence, and the environment identity coding segment also includes the water quality relationship coding segment, the nutrient coding segment, the pollutant content coding segment and the biodiversity coding segment;

[0091] The obtained marine environment data are sorted in chronological order based on the time mark points to obtain an environmental data time series, that is, the marine environment data in the environmental data time series are arranged in chronological order according to the time mark points;

[0092] Based on the environmental data time series, the obtained environmental identity coding segments are sequenced to obtain an environmental identity coding sequence;

[0093] Further, since the environmental identity coding segment is obtained from the environmental identity sequence segment, and the environmental identity sequence segment is obtained by processing the marine environment data, each environmental identity coding segment corresponds to one marine environment data, and in the environmental data time series, each marine environment data is replaced with the corresponding environmental identity coding segment, and the obtained sequence is the environmental identity coding sequence, and the environmental identity coding sequence contains the marine environment data corresponding to one marine capture block composed of the environmental identity coding segments;

[0094] The obtained environmental identity code sequences are associated with the ocean capture blocks associated with the marine environmental data.

[0095] The comprehensive review module is used to assign grades to quality standard data, obtain quality grade code sets, conduct comprehensive evaluation of environmental identity code sequences based on the quality grade code sets, and obtain environmental determination scores. The specific process includes:

[0096] The obtained quality standard data is divided into different levels to obtain the quality judgment grade;

[0097] The level segmentation means that the quality standard data is classified into ranges, that is, each quality standard data has several different content ranges, each range can correspond to a level, and the content ranges corresponding to different quality standard data of the same level are divided into a set, that is, the quality judgment level, and each quality judgment level contains the quality standard data of the corresponding level range;

[0098] For example, the ranges of biodiversity index are g1, g2, g3, and g4, and they decrease from high to low, that is, the range of biodiversity index in g1 is the best range, and g2 is the second best. The ranges of chemical oxygen demand are f1, f2, f3, and f4, and they decrease from high to low. The ranges of pH value are e1, e2, e3, and e4, and they decrease from high to low. Then the quality judgment levels are D1, D2, D3, and D4. The D1 quality judgment level includes the biodiversity index range of g1, the chemical oxygen demand range of f1, and the pH value range of e1. The D2 quality judgment level includes the biodiversity index range of g2, the chemical oxygen demand range of f2, and the pH value range of e2. The D3 quality judgment level includes the biodiversity index range of g3, the chemical oxygen demand range of f3, and the pH value range of e3. The D4 quality judgment level includes the biodiversity index range of g4, the chemical oxygen demand range of f4, and the pH value range of e4. That is, D1 is the best, D2 is the second best, and D4 is the worst.

[0099] Assigning a value to the obtained quality judgment grade to obtain quality grade points;

[0100] The determination and assignment means assigning values ​​to the content index corresponding to each quality standard data within the quality determination grade, and assigning different points to different grades, i.e., the quality grade points;

[0101] For example, k1 points are assigned to the D1 quality judgment level, k2 points are assigned to the D2 quality judgment level, and k3 points are assigned to the D3 quality judgment level, and k1, k2, and k3 decrease in sequence, that is, k1 points are the highest, k2 is the second, and k3 is the last;

[0102] Sequentially encoding the obtained quality standard data based on the quality determination level to obtain a quality standard code;

[0103] Furthermore, the sequence encoding is the same as the sequence encoding of the environmental identity sequence segment, and both are encoded using hash encoding. The quality standard encoding obtained is in the same form as the environmental identity encoding segment, both are in the form of a string, and the quality standard data contained in each quality determination level are sequence encoded. The quality standard encoding after sequence encoding is also in the same order as the quality determination level, and is still arranged in order of level.

[0104] Constructing a quality level code set according to the obtained quality standard codes, uploading the obtained quality standard codes to the quality level code set in the order of quality determination levels, obtaining quality level points corresponding to the quality determination levels, associating the obtained quality level points with the corresponding quality standard codes, and marking the quality level points corresponding to the quality standard codes in the quality level code set;

[0105] Performing a moving comparison on the environmental identity coding sequence according to the obtained quality level coding set to obtain a comparison matching coding;

[0106] It should be further explained that, in the specific implementation process, the mobile comparison process includes:

[0107] Uploading the quality standard code to the starting point of the environment identity code sequence based on the quality level code set, wherein the starting point represents the first character of the beginning origin of the environment identity code sequence;

[0108] Comparing the environmental identity coding sequence bit by bit through the quality standard coding to obtain a comparison result, wherein the comparison result includes a matching comparison and a difference comparison;

[0109] Furthermore, the bit-by-bit comparison means starting from the starting point of the environmental identity code sequence, comparing the quality standard code with the characters at the corresponding positions of the environmental identity code sequence, and if the characters of each bit are the same, the quality standard code is recorded as a matching comparison;

[0110] If the characters of each digit are not completely the same, the quality standard code is recorded as a difference comparison, and the quality standard code is moved to the second character of the environmental identity code sequence, and the quality standard code is compared with the corresponding position characters of the environmental identity code sequence. If the characters of each digit are completely the same, a matching comparison is obtained. If the characters of each digit are not completely the same, a difference comparison is obtained, and the quality standard code is continued to be moved to the next character of the environmental identity code sequence until it is moved to the last character of the environmental identity code sequence. If the characters of each digit corresponding to a certain character are the same, the movement is stopped, and the quality standard code is recorded as a comparison matching code;

[0111] If it is still a difference comparison when moving to the last character of the environmental identity code sequence, the next quality standard code of the quality level code set is uploaded to the starting point of the environmental identity code sequence, and the bit-by-bit comparison process is repeated. If the comparison result is a matching comparison, the second quality standard code is recorded as the comparison matching code. If the comparison result is a difference comparison, the next quality standard code of the quality level code set is uploaded to the starting point of the environmental identity code sequence until all quality standard codes in the quality code set are uploaded to the environmental identity code sequence, and compared bit by bit with the environmental identity code sequence, and the obtained comparison matching codes are counted;

[0112] Constructing a matching code set according to the obtained control matching code, uploading the obtained control matching code to the matching code set, and associating the obtained matching code set with the corresponding environment identity code sequence;

[0113] Based on the quality grade score, the quality of the ocean capture block is determined according to the obtained matching code set to obtain an environmental determination score;

[0114] Furthermore, the quality determination process includes:

[0115] According to a corresponding ocean capture block for an environmental identity coding sequence, the matching coding set corresponds to a quality standard code matched by an environmental identity coding sequence in the quality level coding set, and the quality level score corresponding to the quality standard code is obtained;

[0116] Based on the quality grade score, the obtained matching code set is scored and accumulated to obtain a total quality score, wherein the score accumulation means summing the quality grade scores corresponding to all quality standard codes in the matching code set, and the obtained sum is the total quality score, and the obtained total quality score is associated with the environmental identity code sequence, and the associated total quality score is recorded as the environmental judgment score, that is, the environmental judgment score represents the quality score of the marine capture block, and the ecological environment quality of the marine capture block can be evaluated according to the quality score, and the higher the value of the environmental judgment score, the better the ecological environment quality of the marine capture block, and the lower the value of the environmental judgment score, the worse the ecological environment quality of the marine capture block;

[0117] It should be further explained that, in the specific implementation process, the environmental judgment score represents a comprehensive evaluation of the ecological environment quality of the marine capture block. By setting a grade threshold to perform a graded evaluation on the environmental judgment score, the corresponding grade of the marine capture block can be obtained, that is, the evaluation result, wherein the grade threshold is a set integral threshold; for example, the grade threshold includes a first threshold and a second threshold, and the first threshold is greater than the second threshold;

[0118] The process of graded evaluation includes:

[0119] When the environmental judgment score is less than the second threshold, the ocean capture block corresponding to the environmental judgment score is recorded as a third-level assessment environment. When the second threshold ≤ environmental judgment score ≤ first threshold, the ocean capture block corresponding to the environmental judgment score is recorded as a second-level assessment environment. When the environmental judgment score is greater than the first threshold, the ocean capture block corresponding to the environmental judgment score is recorded as a first-level assessment environment, indicating that the ocean capture blocks are graded and evaluated by setting grade thresholds.

[0120] Based on the above-mentioned marine ecological environment assessment system based on artificial intelligence, the present invention also provides a marine ecological environment assessment method based on artificial intelligence, comprising the following steps:

[0121] Step 1: Collect marine environmental data and quality standard data;

[0122] Step 2: Extract and analyze the marine environment data to obtain standard environment data, construct a standard environment curve chart based on the standard environment data, reconstruct the standard environment curve chart in form, and obtain a preprocessed environment sequence;

[0123] Step 3: Set the cyclic capture coefficient to capture the pre-processed environment sequence to obtain the balanced adjustment coefficient segment, perform cyclic decomposition and extraction on the pre-processed environment sequence to obtain the environment identity sequence segment, perform sequence encoding and sequence update on the environment identity sequence segment to obtain the environment identity encoding sequence;

[0124] Step 4: Assign grades to the quality standard data to obtain a quality grade code set, perform mobile comparison on the environmental identity code sequence based on the quality grade code set to obtain a comparison matching code, evaluate and determine the marine capture block through the comparison matching code, and obtain an environmental determination score.

[0125] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An artificial intelligence-based marine ecological environment assessment system, comprising a control center, characterized in that: The control center is connected to an intelligent collection module, an ecological processing module, an environmental analysis module and a comprehensive review module; The intelligent acquisition module is used to collect marine environment data and quality standard data; The ecological processing module is used to extract and analyze the marine environment data to obtain standard environment data, construct a standard environment curve graph based on the standard environment data, reconstruct the standard environment curve graph in form, and obtain a pre-processed environment sequence; The environment analysis module is used to set the cyclic capture coefficient to capture the pre-processed environment sequence, obtain the balanced adjustment coefficient segment, perform cyclic decomposition and extraction on the pre-processed environment sequence, obtain the environment identity sequence segment, perform sequence encoding and sequence update on the environment identity sequence segment, and obtain the environment identity coding sequence; The comprehensive review module is used to assign grades to quality standard data to obtain a quality grade code set, perform mobile comparison on the environmental identity code sequence based on the quality grade code set to obtain a comparison matching code, evaluate and determine the marine capture block through the comparison matching code, and obtain an environmental determination score.

2. The marine ecological environment assessment system based on artificial intelligence according to claim 1 is characterized in that: The process of collecting marine environment data and quality standard data by the intelligent collection module includes: Divide the ocean area for collection and obtain ocean capture blocks; Set up a collection plan, conduct field collection in the ocean capture area according to the collection plan, obtain ocean environmental data, perform identity marking on the obtained ocean environmental data, and obtain time marking points; Set up a standard collection terminal, collect programs through the standard collection terminal, and obtain quality standard data.

3. The marine ecological environment assessment system based on artificial intelligence according to claim 2 is characterized in that: The process of obtaining a preprocessing environment sequence includes: Perform quality extraction on the obtained marine environmental data to obtain water quality relationship data and nutrient data, perform hazard analysis on the obtained marine environmental data to obtain pollutant content data, perform species extraction on the obtained marine environmental data to obtain biodiversity data; Mark the obtained water quality relationship data, nutrient data, pollutant content data and biodiversity data as standard environmental data; Constructing a two-dimensional rectangular coordinate system of time-dependent standard environment data, generating an environment data change line according to the obtained standard environment data, uploading the obtained environment data change line to the two-dimensional rectangular coordinate system, and obtaining a standard environment curve diagram; The obtained standard environment curve graph is formally reconstructed to obtain a preprocessing environment sequence.

4. The marine ecological environment assessment system based on artificial intelligence according to claim 3 is characterized in that: The process of setting the cyclic capture coefficient of the environment analysis module to capture the preprocessing environment sequence includes: Sequence marking is performed on the pre-processed environment sequence to obtain response sample points; Set the loop capture coefficient, and divide the loop capture coefficient according to the response sample points to obtain the loop level; The shape of the loop capture coefficient is adjusted to obtain the adjustment parameters, and the loop capture coefficient is captured and divided according to the obtained adjustment parameters to obtain the balanced adjustment coefficient segments.

5. The marine ecological environment assessment system based on artificial intelligence according to claim 4 is characterized in that: The process of obtaining the environment identity coding sequence includes: Based on the cycle level, the preprocessed environment sequence is subjected to cyclic decomposition and extraction according to the obtained balanced allocation coefficient segments to obtain the environment identity sequence segments; Performing sequence encoding on the obtained environment identity sequence segment to obtain an environment identity encoding segment; The marine environment data are sorted based on time marking points to obtain an environment data time series, and the environment identity coding segments are sequentially updated according to the environment data time series to obtain an environment identity coding sequence.

6. The marine ecological environment assessment system based on artificial intelligence according to claim 5 is characterized in that: The process of assigning grades to quality standard data by the comprehensive review module includes: The obtained quality standard data is graded to obtain quality judgment grades, and the quality judgment grades are assigned values ​​to obtain quality grade points; The obtained quality standard data is serially encoded based on the quality judgment level to obtain the quality standard code, a quality level code set is constructed according to the quality standard code, and the quality standard code is uploaded to the quality level code set.

7. The marine ecological environment assessment system based on artificial intelligence according to claim 6 is characterized in that: The process of moving and comparing the environmental identity code sequence according to the quality level code set and obtaining the comparison matching code includes: Upload the quality standard code to the environment identity code sequence based on the quality level code set; Comparing the environmental identity coding sequence bit by bit through the quality standard coding to obtain a comparison result, wherein the comparison result includes a matching comparison and a difference comparison; When the comparison result is a matching control, the quality standard code corresponding to the comparison result is recorded as the control matching code, and the bit-by-bit comparison is terminated; When the comparison result is a difference comparison, the quality standard code is moved to the next bit in the environmental identity code sequence for bit-by-bit comparison. If the comparison result is a match comparison, the bit-by-bit comparison ends. If the comparison result is a difference comparison, the quality standard code continues to be moved to the next bit until the last bit of the environmental identity code sequence is reached. If a comparison result is a match comparison, a comparison matching code is obtained. If the comparison results are all difference comparisons, the next quality standard code in the quality level code set is uploaded to the environmental identity code sequence. The process of obtaining the comparison result is repeated until all quality standard codes in the quality code set are uploaded to the environmental identity code sequence and compared bit by bit with the environmental identity code sequence. The quality standard code corresponding to the comparison result of a match comparison is recorded as a comparison matching code.

8. The marine ecological environment assessment system based on artificial intelligence according to claim 7 is characterized in that: The process of assessing and determining ocean catch blocks by comparing and matching codes includes: Construct a matching code set according to the comparison matching code, and upload the comparison matching code to the matching code set; Based on the quality grade score, the quality of the ocean capture block is judged according to the obtained matching code set to obtain the environmental judgment score.

9. The evaluation method of the marine ecological environment evaluation system based on artificial intelligence according to any one of claims 1 to 8, characterized in that: The following steps are involved: Step 1: Collect marine environmental data and quality standard data; Step 2: Extract and analyze the marine environment data to obtain standard environment data, construct a standard environment curve chart based on the standard environment data, reconstruct the standard environment curve chart in form, and obtain a preprocessed environment sequence; Step 3: Set the cyclic capture coefficient to capture the pre-processed environment sequence to obtain the balanced adjustment coefficient segment, perform cyclic decomposition and extraction on the pre-processed environment sequence to obtain the environment identity sequence segment, perform sequence encoding and sequence update on the environment identity sequence segment to obtain the environment identity encoding sequence; Step 4: Assign grades to the quality standard data to obtain a quality grade code set, perform mobile comparison on the environmental identity code sequence based on the quality grade code set to obtain a comparison matching code, evaluate and determine the marine capture block through the comparison matching code, and obtain an environmental determination score.

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