CN110990440A - Cloud analysis method and system based on traffic violation data - Google Patents
Cloud analysis method and system based on traffic violation data Download PDFInfo
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- CN110990440A CN110990440A CN201911328811.3A CN201911328811A CN110990440A CN 110990440 A CN110990440 A CN 110990440A CN 201911328811 A CN201911328811 A CN 201911328811A CN 110990440 A CN110990440 A CN 110990440A
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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Abstract
The invention discloses a cloud analysis method based on traffic violation data, which comprises the following steps: s1 is used for obtaining the traffic violation data; s2 is used for carrying out the step of number conversion processing on the traffic violation data; s3, the method has the following beneficial effects that: compared with the prior art, the traffic violation data analysis program developed based on the design can accurately analyze the traffic violation data, does not need manpower to analyze the traffic violation data, enables the data analysis efficiency to be high, prevents inaccurate data analysis results due to human factors, and enables people to observe the occurrence situation of traffic violation behaviors more intuitively, so that adjustment and prevention can be made according to data information.
Description
Technical Field
The invention discloses a cloud analysis method and system based on traffic violation data, and belongs to the technical field of computers.
Background
The big data is a general name of a series of technologies, and through development of many years, the big data forms a series of links such as data acquisition, arrangement, transmission, storage, safety, analysis, presentation and application, and the links relate to a plurality of big data work posts which are closely related to the Internet of things and cloud computing.
Disclosure of Invention
The technical problem to be solved by the invention is to overcome the defects of the traditional paint remover and provide a cloud analysis method and system based on traffic violation data, so that the problems are solved.
In order to achieve the purpose, the invention provides the following technical scheme:
a cloud analysis method based on traffic violation data comprises the following steps:
s1: a step for acquiring traffic violation data;
s2: a step for carrying out numbering conversion processing on the traffic violation data;
s3: and analyzing and processing the obtained traffic violation data.
Preferably, the step of S1 for acquiring traffic violation data includes:
s11: storing the data inside a data memory;
s12: extracting data to be analyzed from the interior of the data storage;
s13: the data to be analyzed which is proposed out is transmitted into a data conversion module.
Preferably, the step of S3 analyzing and processing the obtained traffic violation data includes:
s31: inputting the analyzed data into the data processing system;
s32: the data processing module groups the traffic violation data corresponding to each serial number;
s33, subdividing the data from the cableway according to the pre-classification information such as time and place;
s34: and processing by the data production module according to the obtained grouping condition of the traffic violation data to obtain a traffic violation data analysis chart.
A system based on traffic violation data comprises a data module, a data extraction module, a data conversion module, an analysis module, a data processing module and a data generation module.
The data module is used for storing various traffic violation behavior data;
the analysis module is used for analyzing and processing the traffic violation behaviors to be analyzed according to the serial numbers of the traffic violation behaviors generated by the data conversion module;
the data processing module is used for grouping the data information generated by the analysis module;
and the data generation module is used for generating the traffic violation data information grouped and completed by the data processing module into a traffic violation data map.
Preferably, the analysis module comprises a data numbering module and a data comparison module, wherein the data numbering module is used for creating more accurate traffic violation data numbers according to the traffic violation behaviors, so that each traffic violation behavior feature corresponds to a specific number, and the numbers are stored; and the data comparison module is used for comparing and selecting the traffic violation data numbers generated by the data conversion module.
Preferably, the data processing module includes a data information processing module and a data grouping module, the data information processing module arranges the traffic illegal activity feature numbers generated by the analysis module, and the data grouping module groups the traffic illegal activity feature numbers arranged by the data information processing module according to a preset grouping type.
Compared with the prior art, the invention has the following beneficial effects:
compared with the prior art, the traffic violation data analysis program developed based on the design can accurately analyze the traffic violation data, so that the data analysis efficiency is higher, and meanwhile, people can observe the occurrence situation of traffic violation behaviors more intuitively, so that adjustment and prevention can be made according to data information.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a flowchart of a cloud analysis method based on traffic violation data according to an embodiment of the present invention;
fig. 2 is a flowchart illustrating a step of S1 for obtaining traffic violation data in a cloud analysis method based on traffic violation data according to an embodiment of the present invention;
fig. 3 is a flowchart illustrating the step of analyzing and processing the obtained traffic violation data by the S3 in the cloud analysis method based on traffic violation data according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a cloud analysis system based on traffic violation data according to an embodiment of the present invention;
fig. 5 is a flowchart illustrating a cloud analysis method based on traffic violation data according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example one
As shown in fig. 1 and fig. 5, the present embodiment provides a cloud analysis method based on traffic violation data, including the following steps:
s1: a step for acquiring traffic violation data;
s2: a step for carrying out numbering conversion processing on the traffic violation data;
s3: and analyzing and processing the obtained traffic violation data.
As will be appreciated by those skilled in the art, the cloud analysis method based on traffic violation data provided by the above embodiments, the obtained traffic violation data information is stored, then the traffic violation data information is obtained from the database, the data to be analyzed is compared with various traffic violation serial numbers contained in the processor database, then grouping the traffic violation data of the same type, and then grouping the traffic violation data of the same place and the same time, then, according to the analysis and processing, the traffic violation data map of the traffic violation behaviors in each region and time is obtained, and large-batch traffic violation data does not need to be processed manually, so that a large amount of manpower resources are saved, and the speed of processing the traffic violation data is higher in efficiency.
Further, as shown in fig. 2, the step of S1 for acquiring traffic violation data includes:
s11: storing the data inside a data memory;
s12: extracting data to be analyzed from the interior of the data storage;
s13: the data to be analyzed which is proposed out is transmitted into a data conversion module.
The technical personnel in the field can understand that the collected traffic violation data are concentrated in the data memory, so that when the traffic violation data need to be analyzed, the traffic violation data only need to be called out from the data memory, the operation is convenient and fast, the analysis efficiency of the traffic violation data is effectively improved, and the traffic violation data does not need to be found out from a messy traffic violation data group.
Further, as shown in fig. 3, the step of analyzing and processing the obtained traffic violation data by S3 includes:
s31: inputting the analyzed data into the data processing system;
s32: the data processing module groups the traffic violation data corresponding to each serial number;
s33, subdividing the data from the cableway according to the pre-classification information such as time and place;
s34: and processing by the data production module according to the obtained grouping condition of the traffic violation data to obtain a traffic violation data analysis chart.
The skilled person in the art can understand that the data processing module adopts various traffic violation data classification models constructed by a naive Bayesian algorithm to classify the obtained traffic violation data serial numbers by time, place and traffic violation behaviors, and has a significant effect on improving the analysis and processing efficiency of the traffic violation data.
Example two
As shown in fig. 4, the embodiment provides a cloud analysis system based on traffic violation data, which includes a data module, a data extraction module, a data conversion module, an analysis module, a data processing module, and a data generation module.
The data module is used for storing various traffic law violation data;
the data extraction module is used for extracting the traffic violation data to be analyzed from the inside of the data module;
the analysis module is used for analyzing and processing the traffic violation behaviors to be analyzed according to the serial numbers of the traffic violation behaviors generated by the data conversion module;
the data processing module is used for grouping the data information generated by the analysis module;
and the data generation module is used for generating the traffic violation data information grouped and completed by the data processing module into a traffic violation data map.
It can be understood by those skilled in the art that, in the cloud analysis method based on traffic violation data provided in the foregoing embodiment, the obtained traffic violation data information is stored, then the traffic violation data information is obtained from the database through the data extraction module, the data to be analyzed is compared with various traffic violation serial numbers contained in the processor database through the analysis module, the same type of traffic violation data is grouped through the data processing module, then the traffic violation data at the same location and at the same time is grouped, then the traffic violation data map of the traffic violation occurring at each location and at each time is obtained through the data generation module according to the analysis processing, a large amount of traffic violation data does not need to be processed manually, and a large amount of human resources are saved, meanwhile, the speed of processing the traffic violation data is higher and the efficiency is higher.
Further, the analysis module comprises a data numbering module and a data comparison module, wherein the data numbering module is used for creating more accurate traffic violation data numbers according to the traffic violation behaviors, so that each traffic violation behavior feature corresponds to a specific number, and the numbers are stored; and the data comparison module is used for comparing and selecting the traffic violation data numbers generated by the data conversion module.
The technical personnel in the field can understand that a relatively accurate traffic violation data serial number is established according to the traffic violation big data, so that each traffic violation behavior characteristic corresponds to a specific serial number, the data to be analyzed is compared with various traffic violation behavior serial numbers contained in the processor database, and the traffic violation data to be analyzed comprises one or more traffic violation behavior serial numbers, so that the traffic violation data is more accurately analyzed, and the analysis and the processing of the traffic violation data by people are facilitated.
Further, the data processing module comprises a data information processing module and a data grouping module, the data information processing module arranges the traffic illegal action characteristic numbers generated by the analysis module, and the data grouping module groups the traffic illegal action characteristic numbers arranged by the data information processing module according to a preset grouping type.
The skilled person can understand that the traffic violation data obtained after the analysis is classified according to time, place and traffic violation behaviors through various traffic violation data classification models constructed by adopting a naive Bayesian algorithm, so that the data analysis diagram generated by the data generation module is more accurate, and people can visually observe the occurrence conditions of various traffic violation behaviors conveniently.
Compared with the prior art, the invention has the following beneficial effects:
compared with the prior art, the traffic violation data analysis program developed based on the design can accurately analyze the traffic violation data, does not need manpower to analyze the traffic violation data, enables the data analysis efficiency to be high, prevents inaccurate data analysis results due to human factors, and enables people to observe the occurrence situation of traffic violation behaviors more intuitively, so that adjustment and prevention can be made according to data information.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (6)
1. A cloud analysis method based on traffic violation data is characterized by comprising the following steps:
s1: a step for acquiring traffic violation data;
s2: a step for carrying out numbering conversion processing on the traffic violation data;
s3: and analyzing and processing the obtained traffic violation data.
2. The cloud analysis method based on traffic violation data as set forth in claim 1, wherein: the step of S1 for obtaining traffic violation data includes:
s11: storing the data inside a data memory;
s12: extracting data to be analyzed from the interior of the data storage;
s13: the data to be analyzed which is proposed out is transmitted into a data conversion module.
3. The cloud analysis method based on traffic violation data as set forth in claim 1, wherein: the step of S3 analyzing and processing the obtained traffic violation data includes:
s31: inputting the analyzed data into the data processing system;
s32: the data processing module groups the traffic violation data corresponding to each serial number;
s33, subdividing the data from the cableway according to the pre-classification information such as time and place;
s34: and processing by the data production module according to the obtained grouping condition of the traffic violation data to obtain a traffic violation data analysis chart.
4. A cloud analysis system based on traffic violation data is characterized in that: the device comprises a data module, a data extraction module, a data conversion module, an analysis module, a data processing module and a data generation module.
The data module is used for storing various traffic violation behavior data;
the data extraction module is used for extracting the traffic violation data to be analyzed from the inside of the data module;
the data conversion module is used for numbering the traffic illegal behavior data to be analyzed from the inside of the data module according to the set characteristic numbers of various traffic illegal behaviors;
the analysis module is used for analyzing and processing the traffic violation behaviors to be analyzed according to the serial numbers of the traffic violation behaviors generated by the data conversion module;
the data processing module is used for grouping the data information generated by the analysis module;
and the data generation module is used for generating the traffic violation data information grouped and completed by the data processing module into a traffic violation data map.
5. The cloud analysis system based on traffic violation data as set forth in claim 8, wherein: the analysis module comprises a data numbering module and a data comparison module, wherein the data numbering module is used for creating more accurate traffic violation data numbers according to traffic violations, so that each traffic violation behavior feature corresponds to a specific number, and the numbers are stored; and the data comparison module is used for comparing and selecting the traffic violation data numbers generated by the data conversion module.
6. The cloud analysis system based on traffic violation data as set forth in claim 9, wherein: the data processing module comprises a data information processing module and a data grouping module, the data information processing module arranges the traffic illegal action characteristic numbers generated by the analysis module, and the data grouping module groups the traffic illegal action characteristic numbers arranged by the data information processing module according to a preset grouping type.
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| US20060235833A1 (en) * | 2005-04-19 | 2006-10-19 | Airsage, Inc. | Method and system for an integrated incident information and intelligence system |
| CN104700610A (en) * | 2013-12-06 | 2015-06-10 | 大连灵动科技发展有限公司 | Intelligent transportation business management method |
| CN105160899A (en) * | 2015-08-18 | 2015-12-16 | 青岛华高软件科技有限公司 | Internet-of-things intelligent traffic law violation management device |
| CN106530738A (en) * | 2016-12-06 | 2017-03-22 | 清华大学 | Real-time traffic information generation and service method in tunnel and system thereof |
| CN107122480A (en) * | 2017-05-04 | 2017-09-01 | 山东浪潮云服务信息科技有限公司 | A kind of cloud analysis method and system based on traffic violation data |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060235833A1 (en) * | 2005-04-19 | 2006-10-19 | Airsage, Inc. | Method and system for an integrated incident information and intelligence system |
| CN104700610A (en) * | 2013-12-06 | 2015-06-10 | 大连灵动科技发展有限公司 | Intelligent transportation business management method |
| CN105160899A (en) * | 2015-08-18 | 2015-12-16 | 青岛华高软件科技有限公司 | Internet-of-things intelligent traffic law violation management device |
| CN106530738A (en) * | 2016-12-06 | 2017-03-22 | 清华大学 | Real-time traffic information generation and service method in tunnel and system thereof |
| CN107122480A (en) * | 2017-05-04 | 2017-09-01 | 山东浪潮云服务信息科技有限公司 | A kind of cloud analysis method and system based on traffic violation data |
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