CN117909691B - Ocean engineering design data acquisition system and method - Google Patents
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Abstract
The invention relates to the field of electric digital data processing, in particular to a system and a method for acquiring ocean engineering design data. The method specifically comprises the following steps: firstly, evaluating and screening input data of a multidimensional heterogeneous data fusion network, preprocessing the screened data, and carrying out data fusion by adopting a multi-level fusion strategy to obtain a fused data set; and then, comprehensively analyzing the fused data set, and dynamically adjusting parameters of the multidimensional heterogeneous data fusion network based on the comprehensive analysis result and the self-adaptive adjustment mechanism. The method solves the problem that the accuracy and the reliability of input data cannot be ensured due to the lack of an effective data validity assessment mechanism in the prior art; the treatment efficiency is low, and the treatment speed is slow; the data characteristic analysis is not deep enough, the flexibility and the self-adaptive capacity are lacking, the diversity and the variability of ocean engineering data are difficult to deal with, and the accuracy and the efficiency of data processing are affected.
Description
Technical Field
The invention relates to the field of electric digital data processing, in particular to a system and a method for acquiring ocean engineering design data.
Background
In the current field of marine engineering, one major challenge is how to efficiently and accurately process and analyze large amounts of complex marine data to support accurate engineering design and efficient decision making. Oceanographic engineering data includes, but is not limited to, physical, chemical, biological, geographic, and meteorological data, which are typically highly heterogeneous, complex, and voluminous. Conventional data processing methods tend to be inefficient in processing such data and difficult to adequately capture complex relationships and patterns between the data, resulting in insufficient accuracy and reliability of the final analysis results.
The existing data processing technology generally faces the problems of limited data fusion capability, low processing efficiency, insufficient understanding of complex data characteristics and the like, and is particularly obvious when processing multi-source and multi-type ocean engineering data. Therefore, a new method for effectively integrating and analyzing these complex data is urgently needed to improve the accuracy and efficiency of marine engineering design.
Chinese patent application number: CN201911396378.7, publication date: 2020.05.19 discloses a method, a system, a medium and equipment for acquiring ocean engineering design data; the acquisition method comprises the following steps: generating preliminary design data; forming data transmission flows corresponding to different professions according to the preliminary design data; outputting analysis and calculation data corresponding to different professions according to the data transmission flow; storing the analysis calculation data into the preliminary design data to obtain final design data; the invention takes the data covering all ocean engineering designs as the only source for acquiring the input data of all professions, ensures the uniformity of the data sources, ensures the rationality of each professional design, ensures that the same data adopted by the related designs among the professions is the same data in all ocean engineering design data, and further ensures the accuracy of the ocean engineering design data.
However, the above technology has at least the following technical problems: the prior art lacks an effective data validity assessment mechanism, so that the accuracy and the reliability of input data cannot be ensured; the treatment efficiency is low, and the treatment speed is slow; the data characteristic analysis is not deep enough, the flexibility and the self-adaptive capacity are lacking, the diversity and the variability of ocean engineering data are difficult to deal with, and the accuracy and the efficiency of data processing are affected.
Disclosure of Invention
The invention provides a system and a method for acquiring ocean engineering design data, which solve the problem that the accuracy and the reliability of input data cannot be ensured due to the lack of an effective data validity assessment mechanism in the prior art; the treatment efficiency is low, and the treatment speed is slow; the data characteristic analysis is not deep enough, the flexibility and the self-adaptive capacity are lacking, the diversity and the variability of ocean engineering data are difficult to deal with, and the accuracy and the efficiency of data processing are affected. The method for acquiring the ocean engineering design data is efficient, accurate and flexible, and the efficiency and quality of data processing and analysis are optimized through the multidimensional heterogeneous data fusion network.
The invention relates to a system and a method for acquiring ocean engineering design data, which concretely comprise the following technical scheme:
an acquisition system of ocean engineering design data, comprising the following parts:
The system comprises a data validity evaluation module, a multidimensional data preprocessing module, a heterogeneous data fusion module, a comprehensive analysis module and a self-adaptive parameter adjustment module;
The data validity evaluation module is used for checking the validity of the collected ocean engineering data and evaluating and screening the input data of the multidimensional heterogeneous data fusion network; data screening is carried out by calculating a validity score; the data validity evaluation module is connected with the multidimensional data preprocessing module in a data transmission mode;
The multidimensional data preprocessing module is used for preprocessing physical and chemical parameter data in the screened data; the physical and chemical parameter data include temperature, salinity, flow rate, dissolved oxygen content and nutrient salt level; the multidimensional data preprocessing module is connected with the heterogeneous data fusion module in a data transmission mode;
The heterogeneous data fusion module is used for fusing other screened ocean engineering data, including submarine topography data, water body physical data and meteorological data, with the preprocessed data, and extracting data characteristics based on statistical properties, space and time relativity of the data by adopting a multi-level fusion strategy to obtain a fused data set; the heterogeneous data fusion module is connected with the comprehensive analysis module in a data transmission mode;
the comprehensive analysis module is used for analyzing the statistical characteristics and modes of the fused data set, applying nonlinear transformation and calculating the interrelationship among the features; the comprehensive analysis module is connected with the self-adaptive parameter adjusting module in a data transmission mode;
The self-adaptive parameter adjusting module is used for dynamically adjusting parameters of the multidimensional heterogeneous data fusion network; the self-adaptive parameter adjusting module is connected with the multidimensional data preprocessing module and the heterogeneous data fusion module in a data transmission mode.
The ocean engineering design data acquisition method comprises the following steps:
S1, evaluating and screening input data of a multidimensional heterogeneous data fusion network, preprocessing the screened data, and carrying out data fusion by adopting a multi-level fusion strategy to obtain a fused data set;
s2, comprehensively analyzing the fused data set, and dynamically adjusting parameters of the multidimensional heterogeneous data fusion network based on a comprehensive analysis result and a self-adaptive adjustment mechanism;
the system is applied to an ocean engineering design data acquisition system.
Preferably, the S1 specifically includes:
collecting and evaluating marine engineering data, including checking the integrity, consistency, and outliers of the marine engineering data; data screening was performed by calculating a validity score.
Preferably, the S1 further includes:
pretreatment is performed on physical and chemical parameter data in the screened data, including temperature, salinity, flow rate, and dissolved oxygen content and nutrient salt level.
Preferably, the S1 further includes:
Fusing other ocean engineering data in the screened data, including submarine topography data, water body physical data and meteorological data, with the preprocessed data; based on the statistical properties, spatial and temporal correlations of the data, a multi-level fusion strategy is introduced.
Preferably, the S2 specifically includes:
analyzing the statistical characteristics and modes of the fused data set; calculating the interrelationship and the action between different characteristics by applying nonlinear transformation; and defining a comprehensive analysis formula to obtain a comprehensive analysis result.
Preferably, the S2 further includes:
And taking the comprehensive analysis result as an actual value of the fusion data, extracting data characteristics and an internal mode, and adjusting parameters of the multidimensional heterogeneous data fusion network by taking the extracted characteristics as the actual value to obtain the network parameter adjustment quantity.
Preferably, the S2 further includes:
Dynamically adjusting parameters of the multidimensional heterogeneous data fusion network through a self-adaptive adjustment mechanism; and designing an adjustment function based on the network parameter adjustment amount to update the parameters of the multidimensional heterogeneous data fusion network.
The technical scheme of the invention has the beneficial effects that:
1. By introducing the data validity assessment module, the accuracy and the reliability of input data can be ensured, and the data assessment mechanism effectively screens and corrects low-quality or wrong data, so that the output quality of the whole system is remarkably improved; the multidimensional data preprocessing module accelerates the speed of subsequent machine learning processing through processing and standardization of physical and chemical parameter data, and the data preprocessing flow is beneficial to improving the overall efficiency of data processing;
2. the heterogeneous data fusion module adopts a multi-level fusion strategy, so that ocean engineering data from different sources are effectively integrated, and the fusion of statistical characteristics, space and time relativity of the data is comprehensively considered, so that the depth and breadth of data analysis are enhanced; the comprehensive analysis module reveals key characteristics and potential association in the data through deep analysis of the fused data set, and is beneficial to more accurately understanding and utilizing ocean engineering data; the adaptive parameter adjustment module is capable of dynamically adjusting network parameters to achieve an optimal balance between data accuracy and processing efficiency.
Drawings
FIG. 1 is a block diagram of a marine engineering design data acquisition system according to an embodiment of the present invention;
fig. 2 is a flowchart of a method for acquiring ocean engineering design data according to an embodiment of the present invention.
Detailed Description
In order to further illustrate the technical means and effects adopted by the present invention to achieve the preset purpose, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The following specifically describes a specific scheme of the system and method for acquiring ocean engineering design data provided by the invention with reference to the accompanying drawings.
Referring to fig. 1, there is shown a block diagram of a marine engineering design data acquisition system according to an embodiment of the present invention, the system includes:
The system comprises a data validity evaluation module, a multidimensional data preprocessing module, a heterogeneous data fusion module, a comprehensive analysis module and a self-adaptive parameter adjustment module;
the data validity evaluation module is used for carrying out validity check on the collected ocean engineering data and evaluating and screening the input data of the multidimensional heterogeneous data fusion network; the integrity, consistency and abnormal value of the ocean engineering data are evaluated by using a statistical method and a data quality index, the accuracy and reliability of the input data are ensured, and low-quality or erroneous data are removed or corrected, so that high-quality input is provided for the multidimensional heterogeneous data fusion network; calculating a validity score, carrying out data screening according to the validity score, and connecting a data validity evaluation module with a multidimensional data preprocessing module in a data transmission mode;
The multidimensional data preprocessing module is used for preprocessing physical and chemical parameter data in the screened data, wherein the preprocessing comprises standardization, normalization and preliminary nonlinear conversion, so that the data is suitable for subsequent complex analysis and model processing; physical and chemical parameter data such as temperature, salinity, flow rate, dissolved oxygen content and nutrient salt level; the multidimensional data preprocessing module is connected with the heterogeneous data fusion module in a data transmission mode;
The heterogeneous data fusion module is used for fusing other ocean engineering data in the screened data, such as submarine topography data, water body physical data and meteorological data, with the preprocessed data, adopting a multi-level fusion strategy, taking the statistical characteristics, space and time relativity of the data into consideration to extract and highlight each type of data characteristics so as to obtain a fused data set, and the heterogeneous data fusion module is connected with the comprehensive analysis module in a data transmission mode;
The comprehensive analysis module is used for carrying out deep statistics and pattern analysis on the fused data set, analyzing the statistical attribute of each feature, applying nonlinear transformation, calculating the interrelation between the features so as to reveal key features and potential association in the data, and is connected with the self-adaptive parameter adjustment module in a data transmission mode;
The self-adaptive parameter adjusting module is used for dynamically adjusting parameters of the multi-dimensional heterogeneous data fusion network so as to optimize the processing of the data by the network, and adjusting the parameters of the multi-dimensional heterogeneous data fusion network by using a self-adaptive adjusting mechanism to better adapt to different data processing scenes, and is connected with the multi-dimensional data preprocessing module and the heterogeneous data fusion module in a data transmission mode.
Referring to fig. 2, a flowchart of a method for acquiring marine engineering design data according to an embodiment of the present invention is shown, where the method includes the following steps:
S1, evaluating and screening input data of a multidimensional heterogeneous data fusion network, preprocessing the screened data, and carrying out data fusion by adopting a multi-level fusion strategy to obtain a fused data set;
In the current field of ocean engineering, efficient acquisition and processing of data is critical to ensure accurate design and efficient decision-making. To address this challenge, a data processing framework, a multidimensional heterogeneous data fusion network, was designed. By integrating and analyzing ocean engineering data of various sources, the efficiency and accuracy of data processing are improved.
In order to ensure the accuracy and reliability of the data, a data validity assessment module is introduced and is responsible for assessing and screening the input data of the multidimensional heterogeneous data fusion network, so that the accuracy and reliability of the input data are ensured. A variety of statistical methods and data quality metrics are used to evaluate marine engineering data, for example, to check the integrity, consistency, and outliers of the data. Therefore, low-quality or erroneous data are removed or corrected, and the output quality of the whole multi-dimensional heterogeneous data fusion network is improved. The evaluation formula is:
，
Wherein, Representing data validity score,/>Is a single data point,/>Is the average of the data,/>Is the total number of data points,/>Is an indication function for identifying that the predetermined range is exceeded/>Abnormal value of/>Respectively the upper and lower limit values of the predetermined range,/>And/>Is a weighting factor used to balance the importance of the different assessment indicators.
According to the effectiveness score, a preset threshold value is set based on an expert experience method, data with the score higher than the preset threshold value are screened out to serve as reliable data, and for data with the score lower than the preset threshold value, the following measures are taken:
correcting or deleting outliers: and correcting or deleting the detected abnormal value or inconsistent data according to specific conditions.
And (3) data interpolation: for missing data points, data interpolation techniques, such as mean interpolation, linear interpolation, or more complex methods (e.g., interpolation based on neighboring data points) may be used to fill in the missing values.
The screened data is further subjected to pretreatment operation, and the multidimensional data pretreatment module is used for treating physical and chemical parameter data such as temperature, salinity, flow rate, dissolved oxygen content and nutrient salt level. Physical and chemical parameter data are collected in real time through ocean buoys and underwater sensor networks and obtained through hydrological and submersible surveys. The key to preprocessing is to process and normalize the different types of marine data so that it is suitable for subsequent processing. The data was preprocessed using the following formula:
，
Wherein, Representing the pre-processed parameter data,/>Is the parameter data before pretreatment,/>Is the mean value of parameter data,/>Is the variance of the parameter data,/>Is a positive number between 0,1 to avoid division by zero,/>、/>、/>And a nonlinear adjustment factor for adjusting the degree of nonlinear transformation of the data. By means of double nonlinear transformation, the nonlinear expression capacity of the model on data is enhanced.
The heterogeneous data fusion module fuses other ocean engineering data in the screened data, such as submarine topography data, water body physical data and meteorological data, with the preprocessed parameter data. In order to realize heterogeneous data fusion, a multi-level fusion strategy is adopted, so that not only is the statistical property of the data considered, but also the spatial and temporal relevance of the data is included. Specifically, a different processing strategy is applied to each type of data to highlight its characteristics, and data fusion is performed using the following formula:
，
Wherein, Representing a fused dataset,/>Representing the i-th preprocessed parameter data/>Weight coefficient of/>Represents j other marine engineering data/>Weight coefficient of/>Representing feature extraction functions,/>Representing the mean value of other ocean engineering data,/>Representing variances of other ocean engineering data,/>Is a fusion operation,/>、/>、/>All are the adjustment coefficients of each item.
S2, comprehensively analyzing the fused data set, and dynamically adjusting parameters of the multidimensional heterogeneous data fusion network based on the comprehensive analysis result and the self-adaptive adjustment mechanism.
The comprehensive analysis module analyzes the statistical properties and patterns of the fused dataset to identify key features and potential associations in the fused dataset. First, the statistical properties, such as mean and variance, of each feature in the fused dataset are analyzed to understand the basic distribution of the features and identify potential outliers or special patterns. Nonlinear transformation (such as Sigmoid function) is applied to capture the response of the features relative to the mean value, reveal hidden nonlinear relations and modes in the features, and enhance the nonlinear recognition capability of the features, so that complex ocean engineering data features are better processed. The interrelationship and effect between different features are calculated, and potential interdependencies are revealed by comprehensively analyzing the relation among a plurality of features. The comprehensive analysis formula is as follows:
，
Wherein, Is the comprehensive analysis result and represents the output after deep analysis of the fused data set,/>Is/>Weight coefficient of each feature for balancing influence of different features,/>And/>Is/>Mean and variance of individual features describing the fundamental statistical properties of the data,/>Is a small amount for ensuring the stability of the value, avoiding zero removal errors,/>And/>Is a parameter for adjusting Sigmoid function, captures nonlinear characteristics in data,/>Is the/>, of the data before preprocessingCharacteristic value/>Is a global weighting factor for balancing interactions between different features,/>Is/>Features and/>Correlation coefficients between individuals indicate interdependencies between different features,/>Is the total number of features/>，/>Is an exponential parameter, enhances nonlinear processing power, and reveals complex data structures. Comprehensive analysis ensures that the multi-dimensional heterogeneous data fusion network can deeply understand and utilize the inherent characteristics of the data when processing the ocean engineering design data.
In order to realize dynamic balance between data precision and processing efficiency, the self-adaptive parameter adjusting module dynamically adjusts the parameters of the multidimensional heterogeneous data fusion network so as to realize optimal balance between data precision and processing efficiency. The comprehensive analysis result is used as the actual value of the fusion data, the key characteristics and the internal mode of the data are extracted from the data characteristics through perception analysis, and the processed characteristics are used as the actual value, so that the capturing capability of the complexity of the data can be enhanced, and especially the deep layer characteristics which are not easy to directly observe in the data can be enhanced. The following formula is used to adjust the multidimensional heterogeneous data fusion network parameters:
，
Wherein, Is the adjustment quantity of network parameters,/>、/>、/>And/>Is an adjustment coefficient for controlling the manner and magnitude of parameter adjustment,/>Is the ith feature in the comprehensive analysis result,/>Is the target value for the ith feature. The network parameter adjustment formula forms a self-adaptive adjustment mechanism, so that parameter adjustment is more dynamic and flexible, and the system is suitable for various data processing scenes. Designing an adjustment function based on the network parameter adjustment amount to update the parameter set:
，
Wherein, And/>Respectively representing parameter sets before and after updating, wherein the parameter sets refer to parameters needing to be adjusted in all steps of the multidimensional heterogeneous data fusion network,/>Is learning rate, controls the step length of parameter update,/>Is the decay rate used to reduce the scale of the parameter,/>Is/>For implementing L1 regularization.
In summary, the system and the method for acquiring the ocean engineering design data are completed.
The sequence of the embodiments of the invention is merely for description and does not represent the advantages or disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
In this specification, each embodiment is described in a progressive manner, and the same or similar parts of each embodiment are referred to each other, and each embodiment mainly describes differences from other embodiments.
The above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention.
Claims (7)
1. An ocean engineering design data acquisition system, comprising the following parts:
The system comprises a data validity evaluation module, a multidimensional data preprocessing module, a heterogeneous data fusion module, a comprehensive analysis module and a self-adaptive parameter adjustment module;
the data validity evaluation module is used for checking the validity of the collected ocean engineering data and evaluating and screening the input data of the multidimensional heterogeneous data fusion network; the evaluation formula is:
，
Wherein, Representing data validity score,/>Is a single data point,/>Is the average of the data,/>Is the total number of data points,/>Is an indication function for identifying that the predetermined range is exceeded/>Abnormal value of/>Respectively the upper and lower limit values of the predetermined range,/>And/>Is a weighting coefficient used for balancing the importance of different evaluation indexes;
data screening is carried out by calculating a validity score; the data validity evaluation module is connected with the multidimensional data preprocessing module in a data transmission mode;
The multidimensional data preprocessing module is used for preprocessing physical and chemical parameter data in the screened data; the physical and chemical parameter data include temperature, salinity, flow rate, dissolved oxygen content and nutrient salt level; the multidimensional data preprocessing module is connected with the heterogeneous data fusion module in a data transmission mode;
The heterogeneous data fusion module is used for fusing other screened ocean engineering data, including submarine topography data, water body physical data and meteorological data, with the preprocessed data, and extracting data characteristics based on statistical properties, space and time relativity of the data by adopting a multi-level fusion strategy to obtain a fused data set; the specific formula is as follows:
，
Wherein, Representing a fused dataset,/>Representing the i-th preprocessed parameter data/>Weight coefficient of/>Represents j other marine engineering data/>Weight coefficient of/>Representing feature extraction functions,/>Representing the mean value of other ocean engineering data,/>Representing variances of other ocean engineering data,/>Is a fusion operation,/>、/>、/>All are adjusting coefficients of each item; the heterogeneous data fusion module is connected with the comprehensive analysis module in a data transmission mode;
The comprehensive analysis module is used for analyzing the statistical characteristics and modes of the fused data set, applying nonlinear transformation and calculating the interrelationship among the features, and the specific formula is as follows:
，
Wherein, Is the result of comprehensive analysis,/>Is/>Weight coefficient of each feature,/>And/>Is/>Mean and variance of individual features,/>For avoiding zero errors,/>And/>Is a parameter for adjusting Sigmoid function,/>Is the/>, of the data before preprocessingCharacteristic value/>Is a global weighting factor,/>Is/>Features and/>Correlation coefficient between individuals,/>Is the total number of features that are present,，/>Is an exponential parameter; the comprehensive analysis module is connected with the self-adaptive parameter adjusting module in a data transmission mode;
The self-adaptive parameter adjusting module is used for dynamically adjusting parameters of the multidimensional heterogeneous data fusion network through a self-adaptive adjusting mechanism, and the specific implementation formula is as follows:
，
Wherein, Is the adjustment quantity of network parameters,/>、/>、/>And/>Is an adjustment coefficient,/>Is the ith feature in the comprehensive analysis result,/>Is the target value of the ith feature; designing an adjustment function based on the network parameter adjustment amount to update the parameter set:
，
Wherein, And/>Respectively representing parameter sets before and after updating, wherein the parameter sets refer to parameters needing to be adjusted in all steps of the multidimensional heterogeneous data fusion network,/>Is learning rate,/>Is the attenuation rate,/>Is/>Is a sign function of (2); the self-adaptive parameter adjusting module is connected with the multidimensional data preprocessing module and the heterogeneous data fusion module in a data transmission mode.
2. A method for acquiring marine engineering data, applied to the marine engineering data acquisition system as claimed in claim 1, comprising the steps of:
S1, evaluating and screening input data of a multidimensional heterogeneous data fusion network, preprocessing the screened data, and carrying out data fusion by adopting a multi-level fusion strategy to obtain a fused data set;
s2, comprehensively analyzing the fused data set, and dynamically adjusting parameters of the multidimensional heterogeneous data fusion network based on the comprehensive analysis result and the self-adaptive adjustment mechanism.
3. The method for obtaining ocean engineering design data according to claim 2, wherein the step S1 specifically comprises:
collecting and evaluating marine engineering data, including checking the integrity, consistency, and outliers of the marine engineering data; data screening was performed by calculating a validity score.
4. The method for obtaining ocean engineering design data according to claim 3, wherein S1 further comprises:
pretreatment is performed on physical and chemical parameter data in the screened data, including temperature, salinity, flow rate, and dissolved oxygen content and nutrient salt level.
5. The method for obtaining ocean engineering design data according to claim 4, wherein S1 further comprises:
Fusing other ocean engineering data in the screened data, including submarine topography data, water body physical data and meteorological data, with the preprocessed data; based on the statistical properties, spatial and temporal correlations of the data, a multi-level fusion strategy is introduced.
6. The method for obtaining ocean engineering design data according to claim 2, wherein the step S2 specifically comprises:
analyzing the statistical characteristics and modes of the fused data set; calculating the interrelationship and the action between different characteristics by applying nonlinear transformation; and defining a comprehensive analysis formula to obtain a comprehensive analysis result.
7. The method for obtaining ocean engineering design data according to claim 6, wherein S2 further comprises:
And taking the comprehensive analysis result as an actual value of the fusion data, extracting data characteristics and an internal mode, and adjusting parameters of the multidimensional heterogeneous data fusion network by taking the extracted characteristics as the actual value to obtain the network parameter adjustment quantity.
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| CN110134675A (en) * | 2019-05-23 | 2019-08-16 | 大连海事大学 | A kind of data cleaning method and system towards oceanographic data stream |
| CN115393540A (en) * | 2022-08-30 | 2022-11-25 | 无锡九方科技有限公司 | Intelligent fusion method and system of three-dimensional marine environment field based on deep learning |
| CN117391641A (en) * | 2023-12-12 | 2024-01-12 | 珠海行知生物科技有限公司 | Pilatory production flow management method and system |
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| CN115393540A (en) * | 2022-08-30 | 2022-11-25 | 无锡九方科技有限公司 | Intelligent fusion method and system of three-dimensional marine environment field based on deep learning |
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