CN117238173A - Comprehensive ship accident space-time hot spot dynamic analysis method and system - Google Patents
Comprehensive ship accident space-time hot spot dynamic analysis method and system Download PDFInfo
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Abstract
The invention discloses a comprehensive ship accident space-time hot spot dynamic analysis method and a system, which relate to the technical field of offshore traffic safety and comprise the following steps: receiving ship accident data, and performing data filtering and data conversion on the ship accident data to obtain ship accident handling data, wherein the ship accident data comprises ship type, event abstract, total tonnage, class society, accident coordinates, accident occurrence time, traffic flow data of casualties and areas where the ship accidents are located in the ship accidents; positioning the ship accident based on the ship accident handling data to obtain the geographical position distribution of the ship accident, and performing density analysis, space autocorrelation analysis and three-dimensional space-time hot spot analysis on the ship accident based on the geographical position distribution of the ship accident; and respectively carrying out parameter adjustment on the density analysis, the space autocorrelation analysis and the three-dimensional space-time hot spot analysis, and obtaining a ship accident space-time hot spot output result through multiple screening.
Description
Technical Field
The invention relates to the technical field of marine traffic safety, in particular to a comprehensive ship accident space-time hot spot dynamic analysis method and system.
Background
With the rapid development of economic globalization, shipping plays an important role in world trade, with about 80% of the global cargo trade being accomplished by international shipping. Since shipping activities are performed in complex and dangerous water environments, accidents of ships are easy to occur, and serious economic losses, casualties and marine pollution can be caused, so that the safety of ships is always an important point of international shipping. The space-time hot spot distribution and evolution of the ship accidents are researched, the marine departments can be helped to intuitively know the traffic safety conditions of the ships in the jurisdiction, and the method has important significance in guaranteeing the navigation safety of the ships, particularly in the aspects of early warning, forecasting and the like.
Currently, research methods for distribution of ship accident hot spots mainly comprise traditional statistical analysis and spatial analysis based on a geographic information system. The method comprises the steps of determining a high-incidence area of an accident through statistical analysis according to geographic coordinates of the accident, and intuitively displaying hot spot distribution characteristics of the accident on a map through a geographic information system technology. Most of these studies conduct macroscopic analysis on accidents from a large-span time period to explore the two-dimensional spatial distribution characteristics of the accidents, however, few researchers focus on the three-dimensional space-time hot spot distribution of ship accidents and the evolution law of the hot spots of the accidents with time.
Disclosure of Invention
In order to solve the defects in the background art, the invention aims to provide a comprehensive ship accident space-time hot spot dynamic analysis method and system, which are used for more comprehensively and scientifically identifying the space-time distribution and evolution characteristics of ship accident hot spots by using a density analysis, a space autocorrelation analysis and a three-dimensional space-time hot spot analysis method based on the ship accident history big data from the angles of density, aggregation degree, trend and density of the space-time hot spots and the like.
The aim of the invention can be achieved by the following technical scheme: a comprehensive ship accident space-time hot spot dynamic analysis method comprises the following steps:
receiving ship accident data, and performing data filtering and data conversion on the ship accident data to obtain ship accident handling data, wherein the ship accident data comprises ship type, event abstract, total tonnage, class society, accident coordinates, accident occurrence time, traffic flow data of casualties and areas where the ship accidents are located in the ship accidents;
positioning the ship accident based on the ship accident handling data to obtain the geographical position distribution of the ship accident, and performing density analysis, space autocorrelation analysis and three-dimensional space-time hot spot analysis on the ship accident based on the geographical position distribution of the ship accident;
and respectively carrying out parameter adjustment on the density analysis, the space autocorrelation analysis and the three-dimensional space-time hot spot analysis, and obtaining a ship accident space-time hot spot output result through multiple screening.
Preferably, the data filtering comprises filtering out accident data without coordinates in ship accident data, clearing abnormal data and correcting error data, wherein the data is converted into longitude and latitude coordinate data of ship accidents in a bisection format, and the longitude and latitude coordinate data is converted into longitude and latitude coordinate data in a decimal form which can be identified by geographic information system software.
Preferably, the density analysis comprises; nuclear density estimation and point density analysis are used to determine the density level and risk boundaries of marine accidents.
Preferably, the calculation formula of the kernel density estimation is:
wherein f (x, y) is the estimated density at the (x, y) position, s is the number of positions, h is the bandwidth, K is the kernel function, lambda i Distance from position (x, y) to the i-th position;
the calculation formula of the dot density analysis F is:
wherein ρ is a neighborhood radius, N (ρ) is the number of ship accidents in a circle with the center of the unit k as the center, the neighborhood radius is ρ, and M is the ship traffic density.
Preferably, the spatial autocorrelation analysis comprises a global spatial autocorrelation analysis and a local spatial autocorrelation analysis.
Preferably, the global spatial autocorrelation analysis I has a calculation formula:
wherein,n is the total number of accidents in the investigation region, x i And x j Representing the i-th and j-th spatial observations respectively,w ij representing elements of a spatial binary adjacency matrix, the weights being neighborhood relations existing between a position i and its neighboring position j, W representing W ij Sum of all accidents in (a),>
local spatial autocorrelation analysisThe calculation formula is as follows:
wherein S is x j Is set in the standard deviation of (2),local spatial autocorrelation analysis classifies the degree of accident aggregation into seven categories, hot or cold spots with 90%, 95% and 99% confidence levels, and spots without significant aggregation.
Preferably, the three-dimensional spatiotemporal hotspot analysis comprises: emerging hot spot analysis, spatiotemporal hot spot trend analysis, and spatiotemporal kernel density estimation analysis.
Preferably, the emerging hot spot analysis can explain and classify the accident hot spot in more detail, and can also present the change of different types of hot spots, the emerging hot spot analysis divides the result into hot spots and cold spots which are added, continuous, enhanced, permanent, reduced, scattered, oscillated and historic, the space-time hot spot trend analysis can identify the change trend of the accident hot spot with statistical significance, the space-time hot spot trend analysis divides the trend of the z score of the hot spot or the cold spot to seven types with the rising or falling trend of 90%, 95% and 99% confidence level and no significant trend;
the calculation formula of the space-time kernel density estimation is as follows:
wherein,for density estimation at location (x, y, t), the x-and y-dimensions are space, the t-dimension is time, ds is space bandwidth, dt is time bandwidth, d s 2 d is the density estimate +.>The density value obtained by multiplying n is expressed by the number of events per unit space time, and the calculation formulas of the kernel functions Ls and Lt are as follows:
where u is the difference between longitude xi and xi+1, v is the difference between latitude yi and yi+1, and p is the difference between time ti and ti+1.
Preferably, the process of obtaining the output result of the space-time hot spot of the ship accident comprises the following steps:
in the parameter adjustment process of the nuclear density estimation, the result of the nuclear density estimation is jointly influenced by a nuclear function K, a bandwidth h and a unit size, the bandwidth influences the smoothness of a density surface, the unit size influences the roughness of a generated surface, and a group of nuclear density estimation output results which are most in line with a ship accident is finally obtained through multiple screening;
in the parameter adjustment process of the point density analysis, the result of the point density analysis is jointly influenced by the neighborhood radius rho and the ship traffic density M, and a group of output results which most accord with the ship accident point density analysis is finally obtained through multiple screening;
in the parameter adjustment process of creating a space-time cube, emerging space-time hot spot analysis, space-time hot spot trend analysis and space-time kernel density estimation, the analysis result is jointly influenced by the time and space of a space-time box, and multiple times of screening are needed, so that a group of analysis output results which are most in line with the space-time hot spot of the ship accident are finally obtained;
and combining the estimated output result of the nuclear density of the ship accident, the analysis output result of the most-accordant ship accident point density and the analysis output result of the most-accordant ship accident space-time hot spot to obtain the ship accident space-time hot spot output result.
In order to achieve the above object, the present invention discloses a comprehensive space-time hot spot dynamic analysis system for ship accidents, comprising:
and a data processing module: the system comprises a ship accident data receiving module, a ship accident data processing module and a ship accident data processing module, wherein the ship accident data receiving module is used for receiving the ship accident data, carrying out data filtering and data conversion on the ship accident data to obtain ship accident processing data, and the ship accident data comprise ship type, event abstract, total tonnage, class society, accident coordinates, accident occurrence time, casualties and traffic flow data of a region where the ship accident is located;
and an accident analysis module: the system is used for positioning the ship accident based on the ship accident handling data to obtain the geographical position distribution of the ship accident, and performing density analysis, spatial autocorrelation analysis and three-dimensional space-time hot spot analysis on the ship accident based on the geographical position distribution of the ship accident;
and a result output module: the method is used for respectively carrying out parameter adjustment on density analysis, space autocorrelation analysis and three-dimensional space-time hot spot analysis, and obtaining a ship accident space-time hot spot output result through multiple screening.
The invention has the beneficial effects that:
the invention can realize macro-fine analysis of the space distribution of the ship accident, can simultaneously carry out space hotspot analysis and three-dimensional dynamic space-time hotspot analysis on the accident, can intuitively and accurately present the space-time pattern of the ship accident, and identify the easy-to-occur areas of a plurality of accidents and the evolution process of the hotspot distribution along with time, thereby providing basic reference for establishing reasonable and effective ship accident management strategies for maritime safety departments, related governments and policy formulators and being beneficial to taking more targeted accident precaution measures.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described, and it will be obvious to those skilled in the art that other drawings can be obtained according to these drawings without inventive effort;
FIG. 1 is a schematic flow chart of the method of the present invention;
FIG. 2 is a schematic diagram of a comprehensive space-time hot spot dynamic analysis method and system flow for ship accidents according to the present invention;
FIG. 3 is a schematic view of the structure of the spatiotemporal cube of the present invention;
FIG. 4 is a diagram of a method and an example for converting accident longitude and latitude coordinate data in an authoritative ship accident database according to the present invention;
FIG. 5 is a schematic diagram of the system architecture of the present invention;
fig. 6 is a graph of the results of the global autocorrelation analysis of a marine accident of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but 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.
As shown in fig. 1, a comprehensive ship accident space-time hot spot dynamic analysis method comprises the following steps:
receiving ship accident data, and performing data filtering and data conversion on the ship accident data to obtain ship accident handling data, wherein the ship accident data comprises ship type, event abstract, total tonnage, class society, accident coordinates, accident occurrence time, traffic flow data of casualties and areas where the ship accidents are located in the ship accidents;
positioning the ship accident based on the ship accident handling data to obtain the geographical position distribution of the ship accident, and performing density analysis, space autocorrelation analysis and three-dimensional space-time hot spot analysis on the ship accident based on the geographical position distribution of the ship accident;
and respectively carrying out parameter adjustment on the density analysis, the space autocorrelation analysis and the three-dimensional space-time hot spot analysis, and obtaining a ship accident space-time hot spot output result through multiple screening.
It should be further described that, in the specific implementation process: the method specifically comprises the following steps:
and step 1, collecting original data.
1.1, raw data is derived from an authoritative ship accident database, including but not limited to ship types in ship accidents, accident results, event summaries, total tonnage, class agencies, accident coordinates, accident occurrence time, traffic flow data of casualties, areas where ship accidents are located, and the like. Reliable data sources are the basis for researching ship accidents, and ship accident databases can be divided into public databases managed by international maritime organizations, commercial databases managed by class societies and national databases managed by government departments and institutions, and the ship accident data collected from the databases is more comprehensive and accurate.
And 2, filtering and converting the data.
And 2.1, filtering data, namely filtering accident data without coordinates in ship accident data, removing abnormal data and correcting error data.
2.2, converting the data, namely converting the longitude and latitude coordinate data (such as 140 DEG 57.20') of the ship accident in the bisection format into longitude and latitude coordinate data (such as 140.96) in a decimal form which can be identified by geographic information system software. The geographic information system analysis software can only identify longitude and latitude coordinate data in decimal form, the data format of longitude and latitude coordinates of ship accidents is usually in degree score, and the filtered ship accident data is converted into coordinate data in decimal form.
And 3, establishing a space-time hot spot dynamic analysis method based on the geographic information system.
3.1, establishing a space-time hot spot dynamic analysis method based on a geographic information system, comprising the following steps: (1) Positioning the accident according to longitude and latitude coordinates in the ship accident data, visualizing the geographical position distribution of the ship accident, and displaying the geographical position distribution of the accident to provide a basis for subsequent hot spot analysis; (2) densitometry; (3) spatial autocorrelation analysis; and (4) three-dimensional space-time hot spot analysis.
3.2, density analysis, including; the nuclear density estimation and the point density analysis aim at determining the density level and the risk boundary of the ship accident, and the space analysis unit can be arbitrarily defined by using the nuclear density estimation and the point density analysis method.
The kernel density estimation is an effective accident density identification method, wherein a hot spot refers to a region with the highest accident density level, the kernel density estimation is a non-parameter method for estimating an unknown density function of a random variable, and compared with the parameter estimation method, the method does not need to assume the density function of a data set. The spatial distribution of the marine accident and the geographical area environment can be organically related through the nuclear density estimation, and the density level of the marine accident can be determined.
The calculation formula of the nuclear density estimation is as follows:
wherein f (x, y) is the estimated density at the (x, y) position, s is the number of positions, h is the bandwidth, K is the kernel function, lambda i Is the distance from position (x, y) to the i-th position.
The hot spot in the point density analysis refers to the area with the largest accident number in the neighborhood, the point density analysis is implemented by dividing the number of points in a certain neighborhood by the neighborhood area, and the calculation formula of the ship accident density of a certain unit in a certain time period is as follows in consideration of the ship traffic density in the neighborhood:
wherein ρ is a neighborhood radius, N (ρ) is the number of ship accidents in a circle with the center of the unit k as the center, the neighborhood radius is ρ, and M is the ship traffic density.
3.3, spatial autocorrelation analysis, which is an analysis method for determining consistent object groups according to the number of object attributes, comprising: the deficiency of lacking statistical significance in the density analysis results can be made up for by the global space autocorrelation analysis and the local space autocorrelation analysis.
The global autocorrelation analysis method is used for describing the overall distribution condition of a certain research object, judging whether the research object has a space aggregation characteristic on the whole, and is performed by using global Moran's I statistical analysis, and the global Moran's I method is based on the covariance relation of statistical correlation coefficients, and the calculation formula is as follows:
wherein n is the total number of accidents in the investigation region, x i And x j Representing the i-th and j-th spatial observations respectively,w ij representing elements of a spatial binary adjacency matrix, the weights being neighborhood relations existing between a position i and its neighboring position j, W representing W ij Sum of all accidents in (a),>
the local spatial autocorrelation analysis method can be used for defining a specific accident aggregation range and identifying a hot spot area of an accident, and the Getis-Ord Gi is a typical local spatial autocorrelation analysis technology, and the calculation formula is as follows:
wherein S is x j Is set in the standard deviation of (2),local spatial autocorrelation analysis classifies the degree of accident aggregation into seven categories, hot or cold spots with 90%, 95% and 99% confidence levels, and spots without significant aggregation;
3.4, three-dimensional space-time hotspot analysis, comprising: the method comprises the following steps of emerging hot spot analysis, space-time hot spot trend analysis and space-time nuclear density estimation analysis, and aims to comprehensively integrate the space and time attributes of accidents, analyze the extinction of old hot spots and the formation of new hot spots of the accidents, analyze the development trend of the accidents and analyze the change of the accident density along with time.
The emerging hot spot analysis and the space-time hot spot trend analysis method expand the statistics of the Getis-Ord Gi to combine the time dimension of accident data, and the two methods can evaluate the position and the degree of the accident space clustering and the change trend of the space-time box time sequence by combining the statistics of the Getis-Ord Gi and the Mann-Kendall trend test, and the input data sets of the two analysis methods are the space-time cubes of the NetCDF data format (namely the data format for storing multidimensional scientific data). The definition of hot spots in the emerging hot spot analysis and the space-time hot spot trend analysis is that the local summary statistics of a space-time box are significantly higher than the expected local statistics, namely the local statistics calculated based on the assumption of complete spatial randomness, and the difference is too large instead of the result of a random process, the emerging hot spot analysis can explain and classify the accident hot spots in more detail, and can also present the change of different types of hot spots, the emerging hot spot analysis divides the result into the hot spots and cold spots which are added, continuous, enhanced, permanent, reduced, scattered, oscillated and historical, and the space-time hot spot trend analysis can identify the change trend of the accident hot spots with statistical significance, and the space-time hot spot trend analysis divides the trend of z scores of the hot spots or cold spots with the increase or decrease of time into seven types, has the rising or falling trend with 90%, 95% and 99% level of confidence and no significant trend.
The space-time nuclear density estimation analysis breaks through the limitation that the hot spot analysis technology can not study the change of the ship accident density along with time, can realize microscopic analysis on the evolution process of the ship accident density along with time, and has the following calculation formula:
wherein,for density estimation at location (x, y, t), the x-and y-dimensions are space, the t-dimension is time, ds is space bandwidth, dt is time bandwidth, d s 2 d is the density estimate +.>The density value obtained by multiplying n is expressed by the number of events per unit space time, and the calculation formulas of the kernel functions Ls and Lt are as follows:
where u is the difference between longitude xi and xi+1, v is the difference between latitude yi and yi+1, and p is the difference between time ti and ti+1;
and 4, setting parameters to obtain a final space-time hot spot dynamic analysis method.
4.1, adjusting parameters based on the established space-time hot spot dynamic analysis method, and obtaining a final space-time hot spot dynamic analysis method, wherein the accuracy requirement is met;
4.2, in the parameter adjustment process of the nuclear density estimation, the result of the nuclear density estimation is influenced by the combination of a kernel function K, a bandwidth h and a unit size, wherein the commonly used kernel function comprises a Gaussian kernel function and a rectangular kernel function, the bandwidth influences the smoothness of the density surface, the unit size influences the roughness of the generated surface, multiple screening is needed, and a group of nuclear density estimation output results which most accord with the ship accident is finally selected;
in the parameter adjustment process of the point density analysis, the result of the point density analysis is jointly influenced by the neighborhood radius rho and the ship traffic density M, multiple screening is needed, and a group of the output results of the point density analysis most conforming to the ship accident is finally selected; in the parameter adjustment process of creating a space-time cube, emerging space-time hotspot analysis, space-time hotspot trend analysis and space-time core density estimation, the analysis result is jointly influenced by the time and space of a space-time box, multiple screening is needed, a group of analysis output results which are most in line with ship accident space-time hotspot is finally selected, and the analysis output results which are in line with the ship accident core density estimation output results, the analysis output results which are most in line with the ship accident point density and the analysis output results which are most in line with the ship accident space-time hotspot are combined to obtain the ship accident space-time hotspot output results.
In this embodiment, the spatiotemporal cube (x, y, t) is a three-dimensional cube composed of spatiotemporal boxes into which the tool can aggregate point input elements (i.e., coordinates and time information of a marine accident), where the x-dimension and y-dimension represent space and the t-dimension represents time. The space-time box time sequence can be obtained through space positioning, and the space-time box time sequence is a longitudinal column. The number of data points contained in each column is the number of geographic events occurring in a unit time step, each space-time box has a unique position ID and holds an aggregate value, the aggregate value comprises the number of the data points or other summarized statistical data of a designated attribute, and the time sequence of the space-time boxes can intuitively display the change trend of the number of ship accidents in the geographic position along with time.
In another aspect, as shown in fig. 5, the embodiment of the present invention further provides a comprehensive space-time hotspot dynamic analysis system for a ship accident, including:
and a data processing module: the system comprises a ship accident data receiving module, a ship accident data processing module and a ship accident data processing module, wherein the ship accident data receiving module is used for receiving the ship accident data, carrying out data filtering and data conversion on the ship accident data to obtain ship accident processing data, and the ship accident data comprise ship type, event abstract, total tonnage, class society, accident coordinates, accident occurrence time, casualties and traffic flow data of a region where the ship accident is located;
and an accident analysis module: the system is used for positioning the ship accident based on the ship accident handling data to obtain the geographical position distribution of the ship accident, and performing density analysis, spatial autocorrelation analysis and three-dimensional space-time hot spot analysis on the ship accident based on the geographical position distribution of the ship accident;
and a result output module: the method is used for respectively carrying out parameter adjustment on density analysis, space autocorrelation analysis and three-dimensional space-time hot spot analysis, and obtaining a ship accident space-time hot spot output result through multiple screening.
Based on the same inventive concept, the present invention also provides a computer apparatus comprising: one or more processors, and memory for storing one or more computer programs; the program includes program instructions and the processor is configured to execute the program instructions stored in the memory. The processor may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field-Programmable gate arrays (FPGAs) or other Programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc., which are the computational core and control core of the terminal for implementing one or more instructions, in particular for loading and executing one or more instructions within a computer storage medium to implement the methods described above.
It should be further noted that, based on the same inventive concept, the present invention also provides a computer storage medium having a computer program stored thereon, which when executed by a processor performs the above method. The storage media may take the form of any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electrical, magnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present disclosure. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing has shown and described the basic principles, principal features, and advantages of the present disclosure. It will be understood by those skilled in the art that the present disclosure is not limited to the embodiments described above, which have been described in the foregoing and description merely illustrates the principles of the disclosure, and that various changes and modifications may be made therein without departing from the spirit and scope of the disclosure, which is defined in the appended claims.
Claims (10)
1. A comprehensive ship accident space-time hot spot dynamic analysis method is characterized by comprising the following steps:
receiving ship accident data, and performing data filtering and data conversion on the ship accident data to obtain ship accident handling data, wherein the ship accident data comprises ship type, event abstract, total tonnage, class society, accident coordinates, accident occurrence time, traffic flow data of casualties and areas where the ship accidents are located in the ship accidents;
positioning the ship accident based on the ship accident handling data to obtain the geographical position distribution of the ship accident, and performing density analysis, space autocorrelation analysis and three-dimensional space-time hot spot analysis on the ship accident based on the geographical position distribution of the ship accident;
and respectively carrying out parameter adjustment on the density analysis, the space autocorrelation analysis and the three-dimensional space-time hot spot analysis, and obtaining a ship accident space-time hot spot output result through multiple screening.
2. The comprehensive ship accident space-time hot spot dynamic analysis method according to claim 1, wherein the data filtering comprises the steps of filtering out accident data without coordinates in ship accident data, clearing abnormal data and correcting error data, wherein the data is converted into the longitude and latitude coordinate data of the ship accident in a bisection format, and the longitude and latitude coordinate data is converted into decimal form identifiable by geographic information system software.
3. A comprehensive space-time hot spot dynamic analysis method for marine accidents according to claim 1, wherein the density analysis comprises; nuclear density estimation and point density analysis are used to determine the density level and risk boundaries of marine accidents.
4. A comprehensive space-time hot spot dynamic analysis method for ship accidents according to claim 3, wherein the calculation formula of the kernel density estimation is:
wherein f (x, y) is the estimated density at the (x, y) position, s is the number of positions, h is the bandwidth, K is the kernel function, lambda i Distance from position (x, y) to the i-th position;
the calculation formula of the dot density analysis F is:
wherein ρ is a neighborhood radius, N (ρ) is the number of ship accidents in a circle with the center of the unit k as the center, the neighborhood radius is ρ, and M is the ship traffic density.
5. A comprehensive space-time hot spot dynamic analysis method for marine vessel accidents according to claim 1, wherein the spatial autocorrelation analysis comprises global spatial autocorrelation analysis and local spatial autocorrelation analysis.
6. The comprehensive ship accident space-time hot spot dynamic analysis method according to claim 5, wherein the global space autocorrelation analysis I has a calculation formula:
wherein n is the total number of accidents in the investigation region, x i And x j Representing the i-th and j-th spatial observations respectively,w ij representing elements of a spatial binary adjacency matrix, the weights being neighborhood relations existing between a position i and its neighboring position j, W representing W ij Sum of all accidents in (a),>
local spatial autocorrelation analysisThe calculation formula is as follows:
wherein S is x j Is set in the standard deviation of (2),local spatial autocorrelation analysis classifies the degree of accident aggregation into seven categories, hot or cold spots with 90%, 95% and 99% confidence levels, and spots without significant aggregation.
7. The comprehensive space-time hotspot dynamic analysis method for ship accidents according to claim 1, wherein the three-dimensional space-time hotspot analysis comprises: emerging hot spot analysis, spatiotemporal hot spot trend analysis, and spatiotemporal kernel density estimation analysis.
8. The comprehensive ship accident space-time hot spot dynamic analysis method according to claim 7, wherein the emerging hot spot analysis can explain and classify accident hot spots in more detail and can also present changes of different types of hot spots, the emerging hot spot analysis divides the results into hot spots and cold spots which are added, continuous, reinforced, permanent, reduced, scattered, oscillated and historical, the space-time hot spot trend analysis can identify accident hot spot change trend with statistical significance, the space-time hot spot trend analysis divides the trend of z-score of hot spots or cold spots to seven types with rising or falling trend with 90%, 95% and 99% confidence level, and no significant trend;
the calculation formula of the space-time kernel density estimation is as follows:
wherein,for density estimation at location (x, y, t), the x-and y-dimensions are spaceThe dimension t is time, ds is spatial bandwidth, dt is temporal bandwidth, d s 2 d is the density estimate +.>The density value obtained by multiplying n is expressed by the number of events per unit space time, and the calculation formulas of the kernel functions Ls and Lt are as follows:
where u is the difference between longitude xi and xi+1, v is the difference between latitude yi and yi+1, and p is the difference between time ti and ti+1.
9. The comprehensive ship accident space-time hot spot dynamic analysis method according to claim 1, wherein the process of obtaining the ship accident space-time hot spot output result is as follows:
in the parameter adjustment process of the nuclear density estimation, the result of the nuclear density estimation is jointly influenced by a nuclear function K, a bandwidth h and a unit size, the bandwidth influences the smoothness of a density surface, the unit size influences the roughness of a generated surface, and a group of nuclear density estimation output results which are most in line with a ship accident is finally obtained through multiple screening;
in the parameter adjustment process of the point density analysis, the result of the point density analysis is jointly influenced by the neighborhood radius rho and the ship traffic density M, and a group of output results which most accord with the ship accident point density analysis is finally obtained through multiple screening;
in the parameter adjustment process of creating a space-time cube, emerging space-time hot spot analysis, space-time hot spot trend analysis and space-time kernel density estimation, the analysis result is jointly influenced by the time and space of a space-time box, and multiple times of screening are needed, so that a group of analysis output results which are most in line with the space-time hot spot of the ship accident are finally obtained;
and combining the estimated output result of the nuclear density of the ship accident, the analysis output result of the most-accordant ship accident point density and the analysis output result of the most-accordant ship accident space-time hot spot to obtain the ship accident space-time hot spot output result.
10. A comprehensive space-time hot spot dynamic analysis system for ship accidents, comprising:
and a data processing module: the system comprises a ship accident data receiving module, a ship accident data processing module and a ship accident data processing module, wherein the ship accident data receiving module is used for receiving the ship accident data, carrying out data filtering and data conversion on the ship accident data to obtain ship accident processing data, and the ship accident data comprise ship type, event abstract, total tonnage, class society, accident coordinates, accident occurrence time, casualties and traffic flow data of a region where the ship accident is located;
and an accident analysis module: the system is used for positioning the ship accident based on the ship accident handling data to obtain the geographical position distribution of the ship accident, and performing density analysis, spatial autocorrelation analysis and three-dimensional space-time hot spot analysis on the ship accident based on the geographical position distribution of the ship accident;
and a result output module: the method is used for respectively carrying out parameter adjustment on density analysis, space autocorrelation analysis and three-dimensional space-time hot spot analysis, and obtaining a ship accident space-time hot spot output result through multiple screening.
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