CN117786604B - Fused safety toughness measurement analysis system based on harbor disaster data - Google Patents
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Abstract
The invention discloses a fused safety toughness measurement analysis system based on harbor disaster data, and relates to the technical field of computers. This a fusion safety toughness measurement analysis system based on district disaster data through setting up data acquisition module, data fusion analysis module, safety toughness evaluation module, visual show module, has realized through calculating district safety toughness index, help the overall security of aassessment district when facing various disasters comprehensively, help more rationally distribute the resource, ensure to throw into sufficient fund and manpower in the key field, improve the district and to the overall resistance of all kinds of disasters, reduce potential loss, the safety toughness ability of analysis district when facing the disaster, help discernment district's vulnerability, improve the overall stability of system, formulate more scientific prevention through providing disaster risk and safety toughness's analysis result, response and recovery, in order to furthest reduce the harm of disaster.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a fused safety toughness measurement analysis system based on harbor disaster data.
Background
With the acceleration of urban and international trade growth, urban developments and densely populated harbors are faced with increasingly complex and diverse disaster threats, including but not limited to natural disasters, human accidents. These disasters not only pose a threat to people's lives and properties, but may also lead to paralysis of the urban infrastructure and confusion of social order.
With the rapid development of digitization and information technology, society's desire to be able to better utilize data to improve urban security is also increasing, while at the same time the sensitivity of society to disaster risk is increasing as some large-scale natural disaster events occur. There is therefore a great deal of interest, but there is a lack of fused safety and toughness metric analysis for estuary disaster data to aid estuary decisions and planning.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a fused safety toughness measurement analysis system based on harbor disaster data, which solves the problems of the background art.
In order to achieve the above purpose, the invention is realized by the following technical scheme: a fused safety toughness measurement analysis system based on harbor disaster data comprises the following modules: the system comprises a data acquisition module, a data fusion analysis module, a safety toughness evaluation module and a visual display module; the data acquisition module is used for acquiring historical disaster data of the harbor district, including historical natural disaster data and historical artificial disaster data; the data fusion analysis module is used for carrying out standardized processing and formatting fusion on the collected harbor historical disaster data, calculating a harbor disaster risk index and analyzing the safety toughness capability of the harbor when the harbor is faced with disasters; the safety toughness assessment module is used for assessing the safety toughness of the harbor based on the analysis result of the safety toughness capability of the harbor when the harbor faces disasters, calculating the safety toughness index of the harbor and measuring the safety toughness of the harbor; the visual display module is used for visually displaying the acquired harbor disaster data and the safety toughness index of the harbor.
Further, the specific process of obtaining the harbour area historical disaster data, including the historical natural disaster data and the historical artificial disaster data is as follows: initializing a historical natural disaster array and a historical artificial disaster array, and inserting historical natural disaster data and historical artificial disaster data into the historical natural disaster array and the historical artificial disaster array respectively; the historical natural disaster data includes: the type, date, location, disaster intensity index, economic loss index and casualty index of the historical natural disasters, the historical artificial disaster data comprises: the type, date, location, disaster intensity index, economic loss index and casualty index of the historical artificial disasters; the historical natural disaster data and the historical artificial disaster data are inserted into a database through the foreach circulation traversal of the historical natural disaster array and the historical artificial disaster array, the historical information of the type, date, place, disaster intensity index, economic loss index and casualty index of the historical natural disaster and the historical artificial disaster is extracted from each array element, and the historical information is respectively inserted into a historical natural disaster table and a historical artificial disaster table.
Further, the specific process of carrying out standardized processing and formatting fusion on the collected port area historical disaster data is as follows: initializing a $ DISASTERDATA empty array for storing standardized historical disaster data, carrying out standardized processing on each piece of data by circularly traversing a history natural disaster table and a history artificial disaster table, judging whether current data exist in the $ DISASTERDATA array through an in_array function, if so, skipping the next circulation, judging whether key fields in the data are empty, converting date fields into a standard annual and monthly format by using a date function, and adding the processed data into the $ DISASTERDATA array.
Further, the specific calculation method for calculating the harbour disaster risk index is as follows:
In the method, in the process of the invention, The harbour disaster risk index, q disaster intensity index, r economic loss index, p casualty index and e natural constant are shown.
Further, the specific process of analyzing the safety toughness capability of the harbor district when facing disasters is as follows: analyzing vulnerability of harbor infrastructure based on data of historical disaster events by utilizing big data and machine learning technology based on harbor disaster risk indexes, and recovering time after disaster and efficiency of emergency response; based on the vulnerability of the harbor infrastructure, the time of recovery after disaster and the efficiency of emergency response, and evaluating the coping capability of the harbor system, calculating the harbor safety toughness index, the safety toughness of the harbor when facing disaster comprises: the method comprises the steps of establishing a dependence relationship between safety toughness capability of a harbor area when facing disasters and toughness of the infrastructure of the area, recovery capability of the harbor area after disasters and emergent response speed of the harbor area by using Gephi network analysis tools.
Further, based on the result of analysis of the safety toughness capability of the harbor when the harbor is faced with disasters, the safety toughness of the harbor is evaluated, and the specific process of calculating the harbor safety toughness index is as follows:
In the method, in the process of the invention, Indicating harbour area safety toughness index,/>Representing harbour area infrastructure toughness index,/>Representing the post-disaster recovery index of harbor district/(Indicating harbour area emergency response toughness index,/>Weight factor representing port infrastructure toughness index versus port safety toughness index,/>Weight factor representing corresponding harbor safety toughness index of harbor disaster recovery indexAnd e represents a natural constant.
Further, the specific calculation method of the harbour area infrastructure toughness index is as follows: accessing a database by using mysql statement, acquiring the total quantity of the infrastructure of each disaster harbor area and the loss quantity of the infrastructure of each disaster harbor area, and numbering in sequenceCalculating a harbor infrastructure toughness index, storing a calculation result in a variable recovery, and outputting a harbor disaster recovery index by using a print statement; the specific calculation formula of the harbour area infrastructure toughness index is as follows:
In the method, in the process of the invention, Representing harbour area infrastructure toughness index,/>Representing the total amount of infrastructure in a harbor district per disaster,/>Representing the number of infrastructure losses per disaster harbour area.
Further, the method for specifically calculating the post-harbor disaster recovery index comprises the following steps: accessing a database by using a mysql statement, acquiring the post-harbor disaster infrastructure perfection, the post-harbor disaster social economic recovery degree and the post-harbor disaster ecological environment recovery degree, calculating a post-harbor disaster recovery index, storing the calculation result in a variable recovery, and outputting the post-harbor disaster recovery index by using a print statement; the specific calculation formula of the post-harbor disaster recovery index is as follows:
In the method, in the process of the invention, The method is characterized in that the method is used for representing the post-harbor disaster recovery index, wherein I represents the perfection of post-harbor disaster infrastructure, S represents the post-harbor disaster socioeconomic recovery degree, S represents the post-harbor disaster ecological environment recovery degree, and e represents the natural constant.
Further, the specific calculation method of the harbour area emergency response toughness index is as follows: accessing a database by using mysql statement, obtaining emergency rescue response efficiency and medical rescue coverage rate after each disaster in a harbor district, and numbering in sequenceCalculating a harbor emergency response toughness index, storing a calculation result in a variable recovery, and outputting a harbor disaster recovery index by using a print statement; the specific calculation formula of the post-harbor disaster recovery index is as follows:
In the method, in the process of the invention, Indicating harbour area emergency response toughness index,/>Representing the response efficiency of each emergency rescue,/>Represents coverage rate of medical rescue each time, e represents natural constant,/>Weight factor representing harbour district emergency response toughness index corresponding to emergency rescue response efficiency each time,/>And a weight factor representing the toughness index of the emergency response of the harbor district corresponding to the emergency response efficiency of each emergency rescue.
Further, the specific process of visually displaying the collected harbor disaster data and the safety toughness index of the harbor is as follows: creating two lists named as harbour disaster data and harbour safety toughness indexes, respectively drawing a histogram and a line graph for the harbour disaster data and the harbour safety toughness indexes by using Matplotlib, respectively generating the histogram and the line graph on a webpage by Flask routing, embedding the histogram and the line graph into an HTML template of a homepage in a PNG format, accessing the two charts through a browser, realizing the generation and rendering of the charts by using Matplotlib, and displaying the charts on the webpage.
The invention has the following beneficial effects:
(1) According to the fused safety toughness measurement analysis system based on the harbor disaster data, the harbor safety toughness index is calculated, so that the overall safety of the harbor in the face of various disasters can be comprehensively evaluated, and a decision maker can be helped to determine which aspects of safety toughness need to be strengthened more so as to cope with potential threats. Through identifying weaknesses, the harbor district can pertinently improve corresponding measures, improves holistic coping ability, helps more reasonable distribution of resources, ensures to put into sufficient funds and manpower in key fields. This helps to increase the overall resistance of the harbor to various disasters and reduce potential losses.
(2) According to the harbour disaster data-based fused safety toughness measurement analysis system, the harbour disaster risk index is calculated, the safety toughness capability of the harbour disaster is analyzed, the vulnerability of the harbour disaster can be identified by analyzing the safety toughness capability, measures can be taken to relieve the vulnerability, the overall stability of the system is improved, and a more scientific prevention, response and recovery plan is formulated by providing analysis results of disaster risks and safety toughness so as to reduce damage of the disaster to the greatest extent.
Of course, it is not necessary for any one product to practice the invention to achieve all of the advantages set forth above at the same time.
Drawings
Fig. 1 is a flow chart of a fused safety toughness measurement analysis system based on harbor disaster data.
FIG. 2 is a flow chart of the method for calculating the harbour safety toughness index according to the invention.
Detailed Description
The embodiment of the application realizes the problem of comprehensive analysis of the harbor safety toughness through a fused safety toughness measurement analysis system based on harbor disaster data.
The problems in the embodiment of the application have the following general ideas:
firstly, acquiring historical disaster data of a harbor area, wherein the historical disaster data comprise historical natural disaster data and historical artificial disaster data, carrying out standardized processing and formatting fusion on the collected historical disaster data of the harbor area, calculating a harbor area disaster risk index, and analyzing the safety toughness capability of the harbor area when the harbor area faces disasters.
Based on the analysis result of the safety toughness capability of the harbor district when facing disasters, the safety toughness of the harbor district is evaluated, and the harbor district safety toughness index is calculated and used for measuring the safety toughness of the harbor district.
And visually displaying the collected harbor disaster data and the safety toughness index of the harbor.
Referring to fig. 1, the embodiment of the invention provides a technical scheme: a fused safety toughness measurement analysis system based on harbor disaster data comprises the following steps: the system comprises a data acquisition module, a data fusion analysis module, a safety toughness evaluation module and a visual display module; the data acquisition module is used for acquiring historical disaster data of the harbor district, including historical natural disaster data and historical artificial disaster data; the data fusion analysis module is used for carrying out standardized processing and formatting fusion on the collected harbor historical disaster data, calculating a harbor disaster risk index and analyzing the safety toughness capability of the harbor when the harbor is faced with disasters; the safety toughness assessment module is used for assessing the safety toughness of the harbor based on the analysis result of the safety toughness capability of the harbor when the harbor faces disasters, calculating the safety toughness index of the harbor and measuring the safety toughness of the harbor; the visual display module is used for visually displaying the acquired harbor disaster data and the safety toughness index of the harbor.
Specifically, the specific process of acquiring harbour area historical disaster data, including historical natural disaster data and historical artificial disaster data, is as follows: initializing a historical natural disaster array and a historical artificial disaster array, and inserting historical natural disaster data and historical artificial disaster data into the historical natural disaster array and the historical artificial disaster array respectively; the historical natural disaster data includes: the type, date, location, disaster intensity index, economic loss index and casualty index of the historical natural disasters, the historical artificial disaster data comprises: the type, date, location, disaster intensity index, economic loss index and casualty index of the historical artificial disasters; the historical natural disaster data and the historical artificial disaster data are inserted into a database through the foreach circulation traversal of the historical natural disaster array and the historical artificial disaster array, the historical information of the type, date, place, disaster intensity index, economic loss index and casualty index of the historical natural disaster and the historical artificial disaster is extracted from each array element, and the historical information is respectively inserted into a historical natural disaster table and a historical artificial disaster table.
In the embodiment, by initializing and inserting a historical natural disaster array and a historical artificial disaster array, the system can collect and sort the historical disaster data of the harbor district, and provides basic data for the measurement of the safety toughness; the method comprises the steps of integrating and standardizing various index types, dates, places, disaster intensity indexes, economic loss indexes and casualty indexes of historical natural disasters and historical artificial disasters, so that data have consistency and comparability in a system; and traversing the history natural disaster array and the history artificial disaster array by using the foreach circulation, and extracting the history information of each index from the history natural disaster array and the history artificial disaster array. This helps the system extract useful information from the large amount of historical data, providing support for subsequent analysis.
Specifically, the specific process of carrying out standardized processing and formatting fusion on the collected port area historical disaster data is as follows: initializing a $ DISASTERDATA empty array for storing standardized historical disaster data, carrying out standardized processing on each piece of data by circularly traversing a history natural disaster table and a history artificial disaster table, judging whether current data exist in the $ DISASTERDATA array through an in_array function, if so, skipping the next circulation, judging whether key fields in the data are empty, converting date fields into a standard annual and monthly format by using a date function, and adding the processed data into the $ DISASTERDATA array.
In the embodiment, each piece of data is subjected to standardized processing by circularly traversing the history natural disaster table and the history artificial disaster table, so that each index is ensured to have consistency and standardization. This helps to eliminate inconsistencies in the data, making the data easier to compare and analyze; the standardized data is added into the empty array $ DISASTERDATA, so that the formatting fusion of the historical natural disaster and the historical artificial disaster data is realized. The system is provided with a consistent data structure, so that subsequent measurement and analysis of the safety toughness are convenient; an in_array function is used to determine if the current data already exists in the $ DISASTERDATA array, thereby avoiding duplicate records. This ensures that the historical disaster data in the system is unique, avoiding repeated calculations and analysis; determining whether critical fields in the data are empty helps ensure that the data in the system is complete and reliable. Missing data may affect the accuracy of the metrics and analysis; the date field is converted to a standard year, month, and day format using a date function, which helps to maintain consistency of date data, enabling the system to more conveniently conduct time series analysis and trend identification.
Specifically, the specific calculation method for calculating the harbour disaster risk index is as follows:
In the method, in the process of the invention, The method is used for measuring the disaster degree of the harbor, q represents the disaster intensity index, r represents the economic loss index, p represents the casualty index and e represents the natural constant.
In this embodiment, the regional government of harbor, meteorological department, professional institution provide the regional disaster intensity index of harbor, economic loss index, casualties index data, and a plurality of factors such as disaster intensity, economic loss and casualties have been considered to the regional disaster risk index of harbor comprehensively, and this helps the system to evaluate the disaster risk of harbor more comprehensively, carries out the calculation of regional disaster risk index through carrying out the historical data, can carry out trend analysis, knows the trend of change of regional disaster risk of different time quantum harbor. The system is helpful for better understanding the evolution rule of the disaster of the harbor, so that future safety toughness measures are planned better, and data support is provided for analyzing the safety toughness capability of the harbor when the disaster is faced.
Specifically, the specific process of analyzing the safety toughness capability of the harbor district in the face of disasters is as follows: analyzing vulnerability of harbor infrastructure based on data of historical disaster events by utilizing big data and machine learning technology based on harbor disaster risk indexes, and recovering time after disaster and efficiency of emergency response; based on the vulnerability of the harbor infrastructure, the time of recovery after disaster and the efficiency of emergency response, and evaluating the coping capability of the harbor system, calculating the harbor safety toughness index, the safety toughness of the harbor when facing disaster comprises: the method comprises the steps of establishing a dependence relationship between safety toughness capability of a harbor area when facing disasters and toughness of the infrastructure of the area, recovery capability of the harbor area after disasters and emergent response speed of the harbor area by using Gephi network analysis tools.
In this embodiment, by systematically analyzing the data of the historical disaster event based on the big data of the harbor disaster risk index and the machine learning technology, a plurality of factors including disaster risk, infrastructure vulnerability, post-disaster recovery time and emergency response efficiency can be comprehensively considered. This helps to fully evaluate the safety toughness of the harbor system in the face of disasters; by analyzing the vulnerability of the harbor infrastructure, weaknesses of the critical infrastructure can be identified and precautions taken to enhance its toughness. This helps to improve the capacity of the harbor system to resist disasters; analyzing the recovery time and efficiency after disaster, and evaluating the quick recovery capability of the harbor district system after disaster occurrence; the Gephi network analysis tool can be used for establishing the dependency relationship between the safety toughness capability of the harbor district when facing disasters, the district infrastructure toughness, the post-disaster recovery capability and the emergency response speed. This aids in a thorough understanding of the interactions between the various factors.
Referring to fig. 2, specifically, based on the result of analysis of the safety toughness capability of the harbor when the harbor is faced with a disaster, the safety toughness of the harbor is evaluated, and the specific process of calculating the harbor safety toughness index is as follows:
In the method, in the process of the invention, Indicating harbour area safety toughness index,/>Representing a harbour infrastructure toughness index for measuring harbour security toughness,/>Representing the post-disaster recovery index of harbor district/(Indicating harbour area emergency response toughness index,/>Weight factor representing port infrastructure toughness index versus port safety toughness index,/>Weight factor representing corresponding harbor safety toughness index of harbor disaster recovery indexAnd e represents a natural constant.
In the embodiment, a hierarchical structure is established by comparing the importance among the harbour area infrastructure toughness indexes, the harbour area post-disaster recovery indexes and the harbour area emergency response toughness indexes through a hierarchical analysis method, and weights are calculated by using a judgment matrix to determine the weights of different factors; by introducing the weight factors, factors in the aspects of infrastructure toughness, post-disaster recovery index and emergency response toughness are comprehensively considered. This helps to create a comprehensive and comprehensive safety toughness assessment; the safety toughness index is used as a quantitative index, a powerful decision support tool is provided, safety toughness performances of different harbors can be compared by using the index, and a disaster management strategy and investment planning are formulated.
Specifically, the method for specifically calculating the harbour infrastructure toughness index is as follows: accessing a database by using mysql statement, acquiring the total quantity of the infrastructure of each disaster harbor area and the loss quantity of the infrastructure of each disaster harbor area, and numbering in sequenceCalculating a harbor infrastructure toughness index, storing a calculation result in a variable recovery, and outputting a harbor disaster recovery index by using a print statement; the specific calculation formula of the harbour area infrastructure toughness index is as follows:
In the method, in the process of the invention, Represents the harbour infrastructure toughness index, is used for measuring the resistance of the harbour infrastructure to disasters,Representing the total amount of infrastructure in a harbor district per disaster,/>Representing the number of infrastructure losses per disaster harbour area.
In this embodiment, by obtaining the total amount of infrastructure and the amount of loss of disaster infrastructure from the database, real-time harbor infrastructure conditions can be provided, facilitating rapid understanding of disaster impact, supporting emergency response and decision making, and comparing the total amount of infrastructure and the amount of loss to quantify the toughness level of the harbor infrastructure. Such metrics help assess the resistance of the harbor infrastructure system to disasters.
Specifically, the method for specifically calculating the post-harbor disaster recovery index comprises the following steps: accessing a database by using a mysql statement, acquiring the post-harbor disaster infrastructure perfection, the post-harbor disaster social economic recovery degree and the post-harbor disaster ecological environment recovery degree, calculating a post-harbor disaster recovery index, storing the calculation result in a variable recovery, and outputting the post-harbor disaster recovery index by using a print statement; the specific calculation formula of the post-harbor disaster recovery index is as follows:
In the method, in the process of the invention, The method is characterized by comprising the steps of representing a post-harbor disaster recovery index for measuring the post-harbor disaster recovery degree, wherein I represents the post-harbor disaster infrastructure perfection degree, S represents the post-harbor disaster social economic recovery degree, S represents the post-harbor disaster ecological environment recovery degree, and e represents a natural constant.
In this embodiment, the system can provide a comprehensive assessment of the post-harbor disaster recovery by comprehensively considering the recovery metrics of the infrastructure, socioeconomic and ecological environment; the calculation of the post-disaster recovery index provides a quantified measure that allows the decision maker to better understand the extent of post-disaster recovery.
Specifically, the method for specifically calculating the harbour area emergency response toughness index comprises the following steps: accessing a database by using mysql statement, obtaining emergency rescue response efficiency and medical rescue coverage rate after each disaster in a harbor district, and numbering in sequenceCalculating a harbor emergency response toughness index, storing a calculation result in a variable recovery, and outputting a harbor disaster recovery index by using a print statement; the specific calculation formula of the post-harbor disaster recovery index is as follows:
In the method, in the process of the invention, Representing harbour emergency response toughness index for measuring harbour emergency response quality,/>Representing the response efficiency of each emergency rescue,/>Represents coverage rate of medical rescue each time, e represents natural constant,/>Weight factor representing harbour district emergency response toughness index corresponding to emergency rescue response efficiency each time,/>And a weight factor representing the toughness index of the emergency response of the harbor district corresponding to the emergency response efficiency of each emergency rescue.
In this embodiment, by comprehensively evaluating various factors, the situation of post-disaster reconstruction can be more comprehensively known, and references can be provided for future countermeasures. The mysql statement is used for accessing the database, the post-harbor disaster emergency rescue response efficiency and the medical rescue coverage rate are obtained, the harbor disaster emergency response toughness index is calculated, the calculated result is stored in the variable recovery, the post-harbor disaster recovery index is output by the print statement, automatic calculation and result output can be achieved, and the evaluation efficiency and accuracy are improved. Based on the indexes and the calculation method, more accurate and scientific post-disaster reconstruction evaluation and coping schemes are provided for governments, organizations and research institutions; by means of analytic hierarchy process, a hierarchy structure is established by comparing importance between emergency rescue response efficiency and medical rescue coverage rate after disaster, and weights are calculated by using a judgment matrix to determine weights of different factors.
Specifically, the specific process of visually displaying the collected harbor disaster data and the safety toughness index of the harbor is as follows: creating two lists named as harbour disaster data and harbour safety toughness indexes, respectively drawing a histogram and a line graph for the harbour disaster data and the harbour safety toughness indexes by using Matplotlib, respectively generating the histogram and the line graph on a webpage by Flask routing, embedding the histogram and the line graph into an HTML template of a homepage in a PNG format, accessing the two charts through a browser, realizing the generation and rendering of the charts by using Matplotlib, and displaying the charts on the webpage.
In this embodiment, a Matplotlib library was used to draw a histogram and a line graph of harbour disaster data and harbour safety toughness index, respectively. A bar function can be used to draw a histogram, and a plot function is used to draw a line graph; a Flask-based Web application is created and routes are set. Two different routes can be created, in the HTML template, the generated chart file is embedded into the webpage by setting the src attribute of the img label, and the URL of the chart file can be acquired by using the url_for method provided by Flask and used for generating a histogram and a line graph respectively; by creating two lists and using Matplotlib to draw a histogram and a line graph, the collected harbor disaster data and the harbor safety and toughness index can be presented in a graph form. The visual display mode can display the data more intuitively, and the user can understand the meaning and trend behind the data more easily. Meanwhile, by embedding the chart into the webpage through Flask routes, online display and interaction can be realized, clearer and visual post-disaster reconstruction evaluation and coping schemes are provided, the safety toughness level of the harbor area is better known, and corresponding measures are taken to improve the safety toughness.
In summary, the present application has at least the following effects:
Through a fused safety toughness measurement analysis system based on harbor disaster data, the safety toughness capability of a harbor in the face of disasters is analyzed, the harbor safety toughness index is calculated, the vulnerability of the harbor is helped to be identified, measures can be taken to relieve the vulnerability, the overall stability of the system is improved, and more scientific prevention, emergency response and recovery plans are formulated by providing disaster risk and safety toughness analysis results, so that damage caused by the disasters is reduced to the greatest extent, the overall safety of the harbor in the face of various disasters is helped to be comprehensively evaluated, and a decision maker can be helped to determine which aspects of safety toughness need to be more strengthened to cope with potential threats. Through identifying weaknesses, the harbor district can pertinently improve corresponding measures, improves holistic coping ability, helps more reasonable distribution of resources, ensures to put into sufficient funds and manpower in key fields. This helps to increase the overall resistance of the harbor to various disasters and reduce potential losses.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of systems, apparatuses (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (6)
1. The fused safety toughness measurement analysis system based on harbor disaster data is characterized by comprising the following modules: the system comprises a data acquisition module, a data fusion analysis module, a safety toughness evaluation module and a visual display module;
The data acquisition module is used for acquiring historical disaster data of the harbor district, including historical natural disaster data and historical artificial disaster data;
The data fusion analysis module is used for carrying out standardized processing and formatting fusion on the collected harbor historical disaster data, calculating a harbor disaster risk index and analyzing the safety toughness capability of the harbor when the harbor is faced with disasters;
The safety toughness assessment module is used for assessing the safety toughness of the harbor based on the analysis result of the safety toughness capability of the harbor when the harbor faces disasters, calculating the safety toughness index of the harbor and measuring the safety toughness of the harbor;
the visual display module is used for visually displaying the acquired harbor disaster data and the safety toughness index of the harbor;
Based on the analysis result of the safety toughness capability of the harbor area when facing disasters, the safety toughness of the harbor area is evaluated, and the specific process for calculating the harbor area safety toughness index is as follows:
In the method, in the process of the invention, Indicating harbour area safety toughness index,/>Representing harbour area infrastructure toughness index,/>Representing the post-disaster recovery index of harbor district/(Indicating harbour area emergency response toughness index,/>Weight factor representing port infrastructure toughness index versus port safety toughness index,/>Weight factor representing corresponding harbor safety toughness index of harbor disaster recovery indexA weight factor representing the port emergency response toughness index corresponding to the port safety toughness index, and e represents a natural constant;
the specific calculation method of the harbour area infrastructure toughness index is as follows:
Accessing a database by using mysql statement, acquiring the total quantity of the infrastructure of each disaster harbor area and the loss quantity of the infrastructure of each disaster harbor area, and numbering in sequence Calculating a harbor infrastructure toughness index, storing a calculation result in a variable recovery, and outputting a harbor disaster recovery index by using a print statement;
The specific calculation formula of the harbour area infrastructure toughness index is as follows:
In the method, in the process of the invention, Representing harbour area infrastructure toughness index,/>Representing the total amount of infrastructure in a harbor district per disaster,/>Representing the number of infrastructure losses per disaster harbor area;
The method for specifically calculating the post-disaster recovery index of the harbor district is as follows:
Accessing a database by using a mysql statement, acquiring the post-harbor disaster infrastructure perfection, the post-harbor disaster social economic recovery degree and the post-harbor disaster ecological environment recovery degree, calculating a post-harbor disaster recovery index, storing the calculation result in a variable recovery, and outputting the post-harbor disaster recovery index by using a print statement;
the specific calculation formula of the post-harbor disaster recovery index is as follows:
In the method, in the process of the invention, The method comprises the steps of representing a post-harbor disaster recovery index, wherein I represents the perfection of an infrastructure after harbor disaster, S represents the social and economic recovery degree after harbor disaster, S represents the ecological environment recovery degree after harbor disaster, and e represents a natural constant;
the specific calculation method of the harbor emergency response toughness index is as follows:
Accessing a database by using mysql statement, obtaining emergency rescue response efficiency and medical rescue coverage rate after each disaster in a harbor district, and numbering in sequence Calculating a harbor emergency response toughness index, storing a calculation result in a variable recovery, and outputting the harbor emergency response toughness index by using a print statement;
The specific calculation formula of the harbor district emergency response toughness index is as follows:
In the method, in the process of the invention, Indicating harbour area emergency response toughness index,/>Representing the response efficiency of each emergency rescue,/>Represents coverage rate of medical rescue each time, e represents natural constant,/>Weight factor representing harbour district emergency response toughness index corresponding to emergency rescue response efficiency each time,/>And a weight factor representing the toughness index of the emergency response of the corresponding harbor district at each medical rescue coverage rate.
2. A fused safety-toughness-metric analysis system based on port disaster data as set forth in claim 1, wherein: the specific process of acquiring the harbour area historical disaster data comprising the historical natural disaster data and the historical artificial disaster data is as follows:
Initializing a historical natural disaster array and a historical artificial disaster array, and inserting historical natural disaster data and historical artificial disaster data into the historical natural disaster array and the historical artificial disaster array respectively;
The historical natural disaster data includes: the type, date, location, disaster intensity index, economic loss index and casualty index of the historical natural disasters, the historical artificial disaster data comprises: the type, date, location, disaster intensity index, economic loss index and casualty index of the historical artificial disasters;
The historical natural disaster data and the historical artificial disaster data are inserted into a database through the foreach circulation traversal of the historical natural disaster array and the historical artificial disaster array, the historical information of the type, date, place, disaster intensity index, economic loss index and casualty index of the historical natural disaster and the historical artificial disaster is extracted from each array element, and the historical information is respectively inserted into a historical natural disaster table and a historical artificial disaster table.
3. A fused safety-toughness-metric analysis system based on port disaster data as set forth in claim 1, wherein: the specific process of carrying out standardized processing and formatting fusion on the collected harbor district historical disaster data is as follows:
Initializing a $ DISASTERDATA empty array for storing standardized historical disaster data, carrying out standardized processing on each piece of data by circularly traversing a history natural disaster table and a history artificial disaster table, judging whether current data exist in the $ DISASTERDATA array through an in_array function, if so, skipping the next circulation, judging whether key fields in the data are empty, converting date fields into a standard annual and monthly format by using a date function, and adding the processed data into the $ DISASTERDATA array.
4. A fused safety-toughness-metric analysis system based on port disaster data as set forth in claim 1, wherein: the concrete calculation method for calculating the harbour disaster risk index is as follows:
In the method, in the process of the invention, The harbour disaster risk index, q disaster intensity index, r economic loss index, p casualty index and e natural constant are shown.
5. A fused safety-toughness-metric analysis system based on port disaster data as set forth in claim 1, wherein: the specific process for analyzing the safety toughness capability of the harbor district in the face of disasters is as follows:
analyzing vulnerability of harbor infrastructure based on data of historical disaster events by utilizing big data and machine learning technology based on harbor disaster risk indexes, and recovering time after disaster and efficiency of emergency response;
Based on the vulnerability of the harbor infrastructure, the time of recovery after disaster and the efficiency of emergency response, and evaluating the coping capability of the harbor system, calculating the harbor safety toughness index, the safety toughness of the harbor when facing disaster comprises: the method comprises the steps of establishing a dependence relationship between safety toughness capability of a harbor area when facing disasters and toughness of the infrastructure of the area, recovery capability of the harbor area after disasters and emergent response speed of the harbor area by using Gephi network analysis tools.
6. A fused safety-toughness-metric analysis system based on port disaster data as set forth in claim 1, wherein: the specific process for visually displaying the collected harbor disaster data and the safety toughness index of the harbor is as follows:
creating two lists named as harbour disaster data and harbour safety toughness indexes, respectively drawing a histogram and a line graph for the harbour disaster data and the harbour safety toughness indexes by using Matplotlib, respectively generating the histogram and the line graph on a webpage by Flask routing, embedding the histogram and the line graph into an HTML template of a homepage in a PNG format, accessing the two charts through a browser, realizing the generation and rendering of the charts by using Matplotlib, and displaying the charts on the webpage.
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