Fishery resource ecological data analysis system and method based on multi-source analysis and medium

Abstract

The invention belongs to the field of fishery resource ecological analysis, relates to a data processing and analysis technology, is used for solving the problem that abnormal factor analysis cannot be carried out when fishery ecology is abnormal in the prior art, and particularly relates to a fishery resource ecological data analysis system and method based on multi-source analysis and a medium. Comprising a resource data acquisition module, a resource evaluation module, an anomaly analysis module and a database, the source data acquisition module is used for regularly acquiring fishery resource data: generating a plurality of acquisition time points, time differences between any two adjacent acquisition time points are equal, dividing a fishery coverage area into a plurality of evaluation areas, and acquiring fishery resource data and external influence data of the evaluation areas at the acquisition time points; the fishery resource data is analyzed and subjected to numerical processing to obtain a resource coefficient, the fishery resource state of the evaluation area at the acquisition time point is fed back according to the resource coefficient, and data support is provided for the fishery resource data evaluation analysis process and the fishery resource data prediction analysis process.

Description

Technical Field

[0001] The present invention belongs to the field of fishery resource ecology analysis, and relates to data processing and analysis technology, in particular to a fishery resource ecology data analysis system, method and medium based on multi-source analysis. Background Art

[0002] Fisheries are an extremely important part of the human and even global economy and ecosystem. With the rapid development of science and technology and the increasing amount of information, data analysis has become an important means of insight into market trends and opportunities. By analyzing fishery data, we can understand the distribution of fish resources, fishing seasons, price fluctuations and other factors, thereby predicting the supply and demand relationship and price trends in the market, and providing decision-making basis for the production and operation of fishermen and fishery enterprises.

[0003] The invention patent with announcement number CN115456490B discloses a fishery resource data analysis method and system based on geographic information. The fishery resource data analysis method can obtain production evaluation information of marine fisheries through hierarchical analysis of marine fishery production areas and real-time analysis of catch data, so as to more intuitively grasp the economic benefits and ecological impacts of the marine production process, which is helpful to further achieve the goal of sustainable development of the ocean; however, the fishery resource data analysis method cannot analyze abnormal factors when the fishery ecology is abnormal, nor can it provide data basis for the prediction and analysis process of fishery resource development trends, resulting in low efficiency in the management and control of fishery resources and inability to timely optimize resource development.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The purpose of the present invention is to provide a fishery resource ecological data analysis system, method and medium based on multi-source analysis, which is used to solve the problem that the prior art cannot perform abnormal factor analysis when the fishery ecology is abnormal;

[0006] The technical problem to be solved by the present invention is: how to provide a fishery resource ecological data analysis system, method and medium based on multi-source analysis that can perform abnormal factor analysis when fishery ecology is abnormal.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A fishery resource ecological data analysis system based on multi-source analysis, including a resource data collection module, a resource assessment module, an abnormal analysis module and a database;

[0009] The resource data collection module is used to collect fishery resource data regularly: generate a number of collection time points, the time difference between any two adjacent collection time points is equal, the fishery coverage area is divided into a number of assessment areas, and the fishery resource data and external impact data of the assessment area are collected at the collection time point. The fishery resource data includes fish species data YZ, fish quantity data YL and distribution data FB. The fish species data YZ, fish quantity data YL and distribution data FB are numerically calculated to obtain the resource coefficient ZY of the assessment area at the collection time point; the resource coefficient ZY of all assessment areas at the collection time point is sent to the resource evaluation module, and the external impact data is sent to the abnormal analysis module;

[0010] The resource assessment module is used to assess and analyze the fishery resource data and mark the assessment area as an ecologically abnormal area or an ecologically normal area, mark the ratio of the number of ecologically abnormal areas to the number of assessment areas at the collection time point as the ecologically abnormal coefficient at the collection time point, and determine whether the overall fishery resources in the fishery coverage area at the collection time point meet the requirements through the ecologically abnormal coefficient;

[0011] The abnormal analysis module is used to analyze abnormal influencing factors on fishery resource data, generate water temperature impact signals or pollution impact signals according to the abnormal influencing factor analysis results, and send them to the mobile phone terminal of the manager.

[0012] Furthermore, the fish species data YZ is the number of fish species in the assessment area, the fish quantity data YL is the total number of fish in the assessment area, and the distribution data FB is the variance value of the corresponding number of all fish species in the assessment area.

[0013] Furthermore, external impact data include water temperature data and pollution data;

[0014] The process of obtaining water temperature data includes: setting up several monitoring points in the assessment area, obtaining the water temperature values ​​of the monitoring points at the collection time point, and summing and averaging the water temperature values ​​of all monitoring points in the assessment area to obtain water temperature data; the process of obtaining pollution data includes: obtaining the total value of organic matter content at the monitoring point at the collection time point, and summing and averaging the total value of organic matter content of all monitoring points in the assessment area to obtain pollution data.

[0015] Furthermore, the specific process of marking the assessment area as an ecological anomaly area or an ecological normal area includes: obtaining the resource threshold ZYmin through the database, and comparing the resource coefficient ZY of the assessment area at the collection time point with the resource threshold ZYmin: if the resource coefficient ZY is less than the resource threshold ZYmin, the assessment area is marked as an ecological anomaly area; if the resource coefficient ZY is greater than or equal to the resource threshold ZYmin, the assessment area is marked as an ecological normal area.

[0016] Furthermore, the specific process of determining whether the overall fishery resources in the fishery coverage area at the collection time point meet the requirements includes: obtaining the ecological anomaly threshold through the database, and comparing the ecological anomaly coefficient at the collection time point with the ecological anomaly threshold: if the ecological anomaly coefficient is less than the ecological anomaly threshold, then it is determined that the overall fishery resources in the fishery coverage area at the collection time point meet the requirements; if the ecological anomaly coefficient is greater than or equal to the ecological anomaly threshold, then it is determined that the overall fishery resources in the fishery coverage area at the collection time point do not meet the requirements, and an abnormal analysis signal is generated and sent to the abnormal analysis module.

[0017] Furthermore, the specific process of the abnormal analysis module analyzing the abnormal influencing factors of fishery resource data includes: arranging all the assessment areas in the order of resource coefficient ZY values ​​from large to small to obtain a resource sequence, arranging all the assessment areas in the order of water temperature data values ​​from large to small to obtain a water temperature sequence, arranging all the assessment areas in the order of pollution data values ​​from small to large to obtain a pollution sequence, marking the absolute value of the difference between the sequence number of the assessment area in the resource sequence and the sequence number in the water temperature sequence as the water temperature impact value of the assessment area, summing and averaging the water temperature impact values ​​of all assessment objects to obtain a water temperature impact coefficient; marking the absolute value of the difference between the sequence number of the assessment area in the resource sequence and the sequence number in the pollution sequence as the pollution impact value of the assessment area, summing and averaging the pollution impact values ​​of all assessment objects to obtain the pollution impact coefficient; comparing the water temperature impact coefficient with the pollution impact coefficient: if the water temperature impact coefficient is greater than the pollution impact coefficient, a water temperature impact signal is generated and the water temperature impact signal is sent to the mobile phone terminal of the manager; otherwise, a pollution impact signal is generated and the pollution impact signal is sent to the mobile phone terminal of the manager.

[0018] The fishery resource data analysis method based on multi-source analysis includes the following steps:

[0019] Step 1: Regularly collect fishery resource data: generate several collection time points, divide the fishery coverage area into several assessment areas, and collect fishery resource data and external impact data in the assessment areas at the collection time points;

[0020] Step 2: Evaluate and analyze the fishery resource data and mark the assessment area as an ecologically abnormal area or an ecologically normal area. The ratio of the number of ecologically abnormal areas to the number of assessment areas at the collection time point is marked as the ecologically abnormal coefficient at the collection time point. The ecologically abnormal coefficient is used to determine whether the overall fishery resources in the fishery coverage area at the collection time point meet the requirements;

[0021] Step 3: Analyze the abnormal influencing factors of fishery resource data and obtain the water temperature influence coefficient and the pollution influence coefficient. Compare the water temperature influence coefficient with the pollution influence coefficient and mark the abnormal influencing factors according to the comparison results.

[0022] A computer storage medium stores a computer program, which, when executed by a processor, implements a fishery resource data analysis method based on multi-source analysis.

[0023] The present invention has the following beneficial effects:

[0024] 1. Through the resource data collection module, fishery resource data can be collected regularly, and the fishery resource data can be analyzed and numerically processed to obtain the resource coefficient. According to the resource coefficient, the fishery resource status of the assessment area at the collection time point can be fed back, providing data support for the fishery resource data assessment and analysis process and the prediction and analysis process;

[0025] 2. The resource assessment module can be used to evaluate and analyze fishery resource data, differentiate the assessment areas according to the resource coefficient, and then provide feedback and evaluation on the overall fishery resource status through the proportion of ecological abnormal areas in the assessment area, and issue early warnings in time when abnormalities occur;

[0026] 3. The abnormal analysis module can be used to analyze abnormal influencing factors of fishery resource data, combine fishery resource data with external influencing data to investigate abnormal influencing factors, and then generate targeted processing signals based on the investigation results to improve the management and control efficiency of fishery resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] 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.

[0028] Figure 1 is the overall system block diagram of the present invention;

[0029] Figure 2 is a system block diagram of Embodiment 1 of the present invention;

[0030] Figure 3 is a system block diagram of Embodiment 2 of the present invention;

[0031] Figure 4 This is a method flow chart of embodiment 3 of the present invention. DETAILED DESCRIPTION

[0032] 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.

[0033] like Figure 1 As shown, the fishery resources ecological data analysis system based on multi-source analysis includes an evaluation subsystem, a prediction subsystem and a database.

[0034] Embodiment 1: Figure 2 As shown, the evaluation subsystem includes a resource data acquisition module, a resource evaluation module and an abnormality analysis module. The resource data acquisition module, the resource evaluation module and the abnormality analysis module are communicatively connected in sequence. The resource data acquisition module is also communicatively connected with the abnormality analysis module and the prediction subsystem.

[0035] The resource data collection module is used to collect fishery resource data regularly: generate several collection time points, the time difference between any two adjacent collection time points is equal, divide the fishery coverage area into several assessment areas, collect fishery resource data and external impact data in the assessment area at the collection time points, the fishery resource data includes fish species data YZ, fish quantity data YL and distribution data FB, the external impact data includes water temperature data and pollution data, the collection technology of fishery resource data includes remote sensing collection technology, the collection technology of external impact data includes sensor technology, the fish species data YZ is the number of fish species in the assessment area, the fish quantity data YL is the total number of fish in the assessment area, and the distribution data FB is the variance value of the corresponding number of all fish species in the assessment area; through the formula The resource coefficient ZY of the assessment area at the collection time point is obtained, wherein m1, m2 and m3 are all proportional coefficients, and m1>m2>m3>1; the process of obtaining water temperature data includes: setting a number of monitoring points in the assessment area, obtaining the water temperature value of the monitoring point at the collection time point, and summing and averaging the water temperature values ​​of all monitoring points in the assessment area to obtain water temperature data; the process of obtaining pollution data includes: obtaining the total value of organic matter content at the monitoring point at the collection time point, and summing and averaging the total value of organic matter content of all monitoring points in the assessment area to obtain pollution data; sending the resource coefficient ZY of all assessment areas at the collection time point to the resource assessment module and the prediction subsystem, and sending the external impact data to the abnormal analysis module; regularly collecting fishery resource data, analyzing and numerically processing the fishery resource data to obtain the resource coefficient, and providing feedback on the fishery resource status of the assessment area at the collection time point according to the resource coefficient, so as to provide data support for the fishery resource data evaluation and analysis process and the prediction and analysis process.

[0036] The resource assessment module is used to evaluate and analyze fishery resource data: obtain the resource threshold ZYmin through the database, compare the resource coefficient ZY of the assessment area at the collection time point with the resource threshold ZYmin: if the resource coefficient ZY is less than the resource threshold ZYmin, the assessment area is marked as an ecological abnormal area; if the resource coefficient ZY is greater than or equal to the resource threshold ZYmin, the assessment area is marked as an ecological normal area, and the ratio of the number of ecological abnormal areas at the collection time point to the number of assessment areas is marked as the ecological abnormality coefficient at the collection time point, obtain the ecological abnormality threshold through the database, and compare the ecological abnormality coefficient at the collection time point with the ecological abnormality threshold: if the ecological abnormality coefficient is less than the ecological abnormality threshold, it is determined that the overall fishery resources in the fishery coverage area at the collection time point meet the requirements; if the ecological abnormality coefficient is greater than or equal to the ecological abnormality threshold, it is determined that the overall fishery resources in the fishery coverage area at the collection time point do not meet the requirements, generate an abnormal analysis signal and send the abnormal analysis signal to the abnormal analysis module; the assessment area is differentially marked according to the resource coefficient, and then the overall fishery resource status is fed back and evaluated by the proportion of the number of ecological abnormal areas in the assessment area, and timely warning is issued in case of abnormalities.

[0037] The abnormal analysis module is used to analyze abnormal influencing factors of fishery resource data: all assessment areas are arranged in descending order according to the resource coefficient ZY value to obtain a resource sequence, all assessment areas are arranged in descending order according to the water temperature data value to obtain a water temperature sequence, all assessment areas are arranged in descending order according to the pollution data value to obtain a pollution sequence, the absolute value of the difference between the sequence number of the assessment area in the resource sequence and the sequence number in the water temperature sequence is marked as the water temperature impact value of the assessment area, the water temperature impact values ​​of all assessment objects are summed and averaged to obtain the water temperature impact coefficient; the sequence number of the assessment area in the resource sequence is marked as the water temperature impact value of the assessment area, and the water temperature impact coefficient is obtained by averaging the water temperature impact coefficient of the assessment area. The absolute value of the difference between the number and the number in the pollution sequence is marked as the pollution impact value of the assessment area, and the pollution impact values ​​of all assessment objects are summed and averaged to obtain the pollution impact coefficient; the water temperature impact coefficient is compared with the pollution impact coefficient: if the water temperature impact coefficient is greater than the pollution impact coefficient, a water temperature impact signal is generated and sent to the mobile phone terminal of the manager; otherwise, a pollution impact signal is generated and sent to the mobile phone terminal of the manager; abnormal influencing factors are checked in combination with fishery resource data and external influencing data, and then targeted processing signals are generated according to the investigation results to improve the management and control efficiency of fishery resources.

[0038] Embodiment 2: Figure 3As shown, the prediction subsystem includes an object screening module and a prediction analysis module. The object screening module is communicatively connected to the prediction analysis module and the resource data acquisition module. When the resource data acquisition module sends the resource coefficient ZY to the resource evaluation module at the acquisition time point, the resource coefficient ZY is synchronously sent to the object screening module.

[0039] The object screening module is used to screen and analyze the prediction templates of the assessment area: when the number of collection time points that complete the collection task reaches K1, K1 is a numerical constant, and the specific value of K1 is set by the management personnel; the first K1 collection time points are marked as benchmark time points, and the resource coefficient ZY, water temperature data and pollution data corresponding to the assessment area at the benchmark time points are marked as resource benchmark values, water temperature benchmark values ​​and pollution benchmark values ​​respectively. The resource benchmark value, water temperature benchmark value and pollution benchmark value constitute the benchmark parameters of the assessment area at the benchmark time point.

[0040] When the resource coefficient ZY and external impact data of the collection time point are received again after K1 benchmark time points, a random evaluation area is selected and marked as the prediction area, and K2 groups of benchmark parameters collected in the prediction area at the latest K2 benchmark time points are extracted and marked as prediction parameters. The prediction parameters are sorted in chronological order to obtain a prediction sequence, and the prediction parameters are screened and compared with the benchmark parameters of all remaining evaluation areas: a random evaluation area is selected and marked as a comparison area, and all benchmark parameters of the comparison area are arranged in chronological order to obtain a comparison sequence. Starting from the first benchmark parameter of the comparison sequence, a subsequence with a number of benchmark parameters of K2 is intercepted, where K2 is a numerical constant. The specific value of K2 is set by the management personnel, and k2 <k1。

[0041] The prediction parameters in the prediction sequence are compared with the benchmark parameters in the subsequence according to the sequence numbers: the absolute value of the difference between the resource benchmark value in the prediction parameter with the same sequence number and the resource benchmark value in the benchmark parameter is marked as the resource deviation value of the corresponding sequence number, the absolute value of the difference between the water temperature benchmark value in the prediction parameter with the same sequence number and the water temperature benchmark value in the benchmark parameter is marked as the water temperature deviation value of the corresponding sequence number, the absolute value of the difference between the pollution benchmark value in the prediction parameter with the same sequence number and the pollution benchmark value in the benchmark parameter is marked as the pollution deviation value of the corresponding sequence number, the resource deviation values ​​of all the sequences are summed and averaged to obtain the resource deviation data ZP of the subsequence, the water temperature deviation values ​​of all the sequences are summed and averaged to obtain the water temperature deviation data SP of the subsequence, and the pollution deviation values ​​of all the sequences are summed and averaged to obtain the pollution deviation data WP of the subsequence;

[0042] The deviation coefficient PC of the subsequence is obtained by the formula PC = c1*ZP+c2*SP+c3*WP; wherein c1, c2 and c3 are all proportional coefficients, and c1>c2>c3>1; then, starting from the second benchmark of the comparison sequence, a subsequence with K2 benchmark parameters is intercepted, and the predicted parameters in the prediction sequence are compared with the benchmark parameters in the subsequence according to the sequence number and the deviation coefficient PC of the subsequence is re-obtained; and so on, until the subsequence is intercepted with the last benchmark parameter of the comparison sequence;

[0043] The subsequence with the smallest deviation coefficient PC value is marked as the overlapping sequence of the comparison area, and the deviation coefficient PC of the overlapping sequence is marked as the overlapping performance value of the comparison area; then the next remaining evaluation area is randomly selected and marked as the comparison area, and the overlapping sequence and overlapping performance value of the comparison area are obtained, and so on, until all the remaining evaluation areas have completed the marking of the comparison area; the comparison area with the smallest overlapping performance value in all the comparison areas is marked as the screening area, and the overlapping sequence of the screening area is marked as the template sequence of the prediction area.

[0044] The prediction and analysis module is used to predict and analyze the development trend of fishery resources in the prediction area: the analysis subsequence is composed of the first benchmark parameter to the K3th benchmark parameter of the template sequence after the corresponding comparison sequence, K3 is a numerical constant, and the specific value of K3 is set by the management personnel; the resource benchmark values ​​of all benchmark parameters in the template sequence are summed and averaged to obtain the preceding resource value of the prediction area, and the resource benchmark values ​​of all benchmark parameters in the analysis subsequence are summed and averaged to obtain the succeeding resource value of the prediction area, and the difference between the preceding resource value and the succeeding resource value is marked as the resource warning value of the prediction area.

[0045] The resource warning threshold is obtained through the database, and the resource warning value of the prediction area is compared with the resource warning threshold: if the resource warning value is less than the resource warning threshold, it is determined that the fishery resource prediction result in the prediction area meets the requirements; if the resource warning value is greater than or equal to the resource warning threshold, it is determined that the fishery resource prediction result in the prediction area does not meet the requirements, and the corresponding prediction area is marked as a warning area; a warning signal is generated and the warning signal and all warning areas are sent to the mobile phone terminal of the manager.

[0046] Embodiment 3: Figure 4 As shown, the fishery resource ecological data analysis method based on multi-source analysis includes the following steps:

[0047] Step 1: Regularly collect fishery resource data: generate several collection time points, divide the fishery coverage area into several assessment areas, and collect fishery resource data and external impact data in the assessment areas at the collection time points;

[0048] Step 2: Evaluate and analyze the fishery resource data and mark the assessment area as an ecologically abnormal area or an ecologically normal area. The ratio of the number of ecologically abnormal areas to the number of assessment areas at the collection time point is marked as the ecologically abnormal coefficient at the collection time point. The ecologically abnormal coefficient is used to determine whether the overall fishery resources in the fishery coverage area at the collection time point meet the requirements;

[0049] Step 3: Analyze the abnormal influencing factors of fishery resource data and obtain the water temperature influence coefficient and the pollution influence coefficient, compare the water temperature influence coefficient with the pollution influence coefficient and mark the abnormal influencing factors according to the comparison results;

[0050] Step 4: Screen and analyze the prediction templates of the evaluation area and obtain the template sequence of each evaluation area;

[0051] Step 5: Carry out forecast analysis on the development trend of fishery resources in the forecast area. If the forecast results of fishery resources in the forecast area do not meet the requirements, a warning signal will be generated and sent to the mobile phone terminal of the manager.

[0052] The present invention also includes a readable storage medium on which a computer program is stored. When the program is executed by a processor, the above-mentioned fishery resource data analysis method based on multi-source analysis is implemented. A person of ordinary skill in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to the computer program. The aforementioned computer program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk and other media that can store program codes.

[0053] The fishery resource ecological data analysis system based on multi-source analysis generates several collection time points when working, divides the fishery coverage area into several evaluation areas, collects fishery resource data and external impact data of the evaluation area at the collection time point; evaluates and analyzes the fishery resource data and marks the evaluation area as an ecological abnormal area or an ecological normal area, marks the ratio of the number of ecological abnormal areas to the number of evaluation areas at the collection time point as the ecological abnormality coefficient at the collection time point, and judges whether the overall fishery resources in the fishery coverage area at the collection time point meet the requirements through the ecological abnormality coefficient; analyzes the abnormal influencing factors of the fishery resource data and obtains the water temperature influence coefficient and the pollution influence coefficient, compares the water temperature influence coefficient with the pollution influence coefficient and marks the abnormal influencing factors according to the comparison results; screens and analyzes the prediction templates of the evaluation area and obtains the template sequence of each evaluation area; predicts and analyzes the development trend of fishery resources in the prediction area, generates an early warning signal if the prediction results of fishery resources in the prediction area do not meet the requirements, and sends the early warning signal to the mobile phone terminal of the manager.

[0054] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0055] The above formulas are obtained by collecting a large amount of data and performing software simulation to select a formula close to the actual value. The coefficients in the formula are set by technicians in this field according to actual conditions; for example: Formula A technician in this field collects multiple groups of sample data and sets corresponding resource coefficients for each group of sample data; substitutes the set resource coefficients and the collected sample data into the formula, and any three formulas constitute a three-variable linear equation system. The calculated coefficients are screened and averaged, and the values ​​of m1, m2, and m3 are obtained to be 3.51, 2.68, and 2.23, respectively;

[0056] The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the preliminary setting of the corresponding resource coefficient for each set of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantified value, such as the resource coefficient is proportional to the value of the fish species data.

[0057] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0058] 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. The fishery resource ecological data analysis system based on multi-source analysis is characterized by: It includes resource data collection module, resource assessment module, abnormal analysis module and database; The resource data collection module is used to collect fishery resource data regularly: generate a number of collection time points, the time difference between any two adjacent collection time points is equal, the fishery coverage area is divided into a number of assessment areas, and the fishery resource data and external impact data of the assessment area are collected at the collection time point. The fishery resource data includes fish species data YZ, fish quantity data YL and distribution data FB. The fish species data YZ, fish quantity data YL and distribution data FB are numerically calculated to obtain the resource coefficient ZY of the assessment area at the collection time point; the resource coefficient ZY of all assessment areas at the collection time point is sent to the resource evaluation module, and the external impact data is sent to the abnormal analysis module; The resource assessment module is used to assess and analyze the fishery resource data and mark the assessment area as an ecologically abnormal area or an ecologically normal area, mark the ratio of the number of ecologically abnormal areas to the number of assessment areas at the collection time point as the ecologically abnormal coefficient at the collection time point, and determine whether the overall fishery resources in the fishery coverage area at the collection time point meet the requirements through the ecologically abnormal coefficient; The abnormal analysis module is used to analyze abnormal influencing factors on fishery resource data, generate water temperature impact signals or pollution impact signals according to the abnormal influencing factor analysis results, and send them to the mobile phone terminal of the manager.

2. The fishery resource ecological data analysis system based on multi-source analysis according to claim 1 is characterized in that: The fish species data YZ is the number of fish species in the assessment area, the fish quantity data YL is the total number of fish in the assessment area, and the distribution data FB is the variance value of the corresponding number of all fish species in the assessment area.

3. The fishery resource ecological data analysis system based on multi-source analysis according to claim 2 is characterized in that: External impact data include water temperature data and pollution data; The process of obtaining water temperature data includes: setting up several monitoring points in the assessment area, obtaining the water temperature values ​​of the monitoring points at the collection time point, and summing and averaging the water temperature values ​​of all monitoring points in the assessment area to obtain water temperature data; the process of obtaining pollution data includes: obtaining the total value of organic matter content at the monitoring point at the collection time point, and summing and averaging the total value of organic matter content of all monitoring points in the assessment area to obtain pollution data.

4. The fishery resource ecological data analysis system based on multi-source analysis according to claim 3 is characterized in that: The specific process of marking the assessment area as an ecological anomaly area or an ecological normal area includes: obtaining the resource threshold ZYmin through the database, and comparing the resource coefficient ZY of the assessment area at the collection time point with the resource threshold ZYmin: if the resource coefficient ZY is less than the resource threshold ZYmin, the assessment area is marked as an ecological anomaly area; if the resource coefficient ZY is greater than or equal to the resource threshold ZYmin, the assessment area is marked as an ecological normal area.

5. The fishery resource ecological data analysis system based on multi-source analysis according to claim 4 is characterized in that: The specific process of determining whether the overall fishery resources in the fishery coverage area at the collection time point meet the requirements includes: obtaining the ecological anomaly threshold through the database, and comparing the ecological anomaly coefficient at the collection time point with the ecological anomaly threshold: if the ecological anomaly coefficient is less than the ecological anomaly threshold, it is determined that the overall fishery resources in the fishery coverage area at the collection time point meet the requirements; if the ecological anomaly coefficient is greater than or equal to the ecological anomaly threshold, it is determined that the overall fishery resources in the fishery coverage area at the collection time point do not meet the requirements, and an abnormal analysis signal is generated and sent to the abnormal analysis module.

6. The fishery resource ecological data analysis system based on multi-source analysis according to claim 5 is characterized in that: The specific process of the abnormal analysis module analyzing the abnormal influencing factors of fishery resource data includes: arranging all the assessment areas in the order of resource coefficient ZY values ​​from large to small to obtain a resource sequence, arranging all the assessment areas in the order of water temperature data values ​​from large to small to obtain a water temperature sequence, arranging all the assessment areas in the order of pollution data values ​​from small to large to obtain a pollution sequence, marking the absolute value of the difference between the sequence number of the assessment area in the resource sequence and the sequence number in the water temperature sequence as the water temperature impact value of the assessment area, summing and averaging the water temperature impact values ​​of all assessment objects to obtain the water temperature impact coefficient; marking the absolute value of the difference between the sequence number of the assessment area in the resource sequence and the sequence number in the pollution sequence as the pollution impact value of the assessment area, summing and averaging the pollution impact values ​​of all assessment objects to obtain the pollution impact coefficient; comparing the water temperature impact coefficient with the pollution impact coefficient: if the water temperature impact coefficient is greater than the pollution impact coefficient, a water temperature impact signal is generated and sent to the mobile phone terminal of the manager; otherwise, a pollution impact signal is generated and sent to the mobile phone terminal of the manager.

7. A fishery resource data analysis method based on multi-source analysis, characterized in that: The following steps are involved: Step 1: Regularly collect fishery resource data: generate several collection time points, divide the fishery coverage area into several assessment areas, and collect fishery resource data and external impact data in the assessment areas at the collection time points; Step 2: Evaluate and analyze the fishery resource data and mark the assessment area as an ecologically abnormal area or an ecologically normal area. The ratio of the number of ecologically abnormal areas to the number of assessment areas at the collection time point is marked as the ecologically abnormal coefficient at the collection time point. The ecologically abnormal coefficient is used to determine whether the overall fishery resources in the fishery coverage area at the collection time point meet the requirements; Step 3: Analyze the abnormal influencing factors of fishery resource data and obtain the water temperature influence coefficient and the pollution influence coefficient. Compare the water temperature influence coefficient with the pollution influence coefficient and mark the abnormal influencing factors according to the comparison results.

8. A computer storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, it implements the fishery resource data analysis method based on multi-source analysis as described in claim 7.

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