CN111680827B - Working method of cloud computing route planning system based on electronic ticketing - Google Patents
Working method of cloud computing route planning system based on electronic ticketing Download PDFInfo
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Abstract
The invention relates to a working method of a cloud computing route planning system based on electronic ticketing, which comprises the following steps: the tourist information of the ticket buying tourists is acquired at the ticket selling place of the tourist attraction and transmitted to the cloud server; the cloud server acquires historical ticket information of the user on the Internet according to the user information; the cloud server acquires the numerical value of recorded scenic spot classification information according to the historical ticket information, and the recorded scenic spot classification is applicable to scenic spot classification of the current scenic spot; the cloud server sorts the scenic spot classifications according to the recorded scenic spot classification information; uploading the current scenic spot information to a cloud server by tourists; the cloud server acquires all scenic spots of the current scenic spot and acquires scenic spot classification corresponding to the scenic spot; the cloud server sorts all scenic spots of the current scenic spot according to the classification of the recorded scenic spots; the cloud server screens and sorts the scenic spots in the first 50% according to all scenic spot sorting of the current scenic spot; the cloud server connects the scenic spots which are ranked at the first 50% in series to form a travel route; the cloud server inserts scenic spots which are recommended and ordered in the back 50% on the serially connected travel routes.
Description
Technical Field
The invention relates to the field of cloud computing and electronic ticketing, in particular to a working method of a cloud computing route planning system based on electronic ticketing.
Background
With the development of the tourism industry and business, more and more people like to travel after leisure. Before going out for tour, tourists will usually query the website for tourist attraction information, but the information that tourists can query on the website is limited and a lot of time and effort are spent. Each scenic spot is provided with a plurality of scenic spots, and the existing scenic spots cannot plan a tourist route of the scenic spot for the tourist according to the actual situation of each scenic spot in the scenic spot. Meanwhile, the existing scenic spot cannot provide personalized scenic spot tour routes for all tourists according to physical conditions and other practical conditions of all tourists. In summary, the main algorithms at present can be divided into traditional optimization algorithms and modern optimization algorithms. The conventional optimization algorithm can be divided into an optimal solution algorithm and an approximation method. Traditional optimization algorithms include branch-and-bound methods, modified loop methods, greedy algorithms, interpolation methods, and the like. Although the optimal solution algorithm can obtain an accurate solution, the calculation time is intolerable, so various approximation methods are generated, and although the approximation algorithm can obtain a feasible solution close to the optimal solution faster, the approximation algorithm is not satisfactory in the degree of approaching the optimal solution. Accordingly, there is a need to provide a system or method for tourist route planning according to the tourist's own situation.
Disclosure of Invention
The invention aims to:
aiming at the problem that a system or a method capable of carrying out tour route planning according to the self situation of tourists needs to be provided for the tourists, the invention provides a working method of a cloud computing route planning system based on electronic ticketing.
The technical scheme is as follows:
a working method of a cloud computing route planning system based on electronic ticketing is used for planning a route of tourists in scenic spots and comprises the following steps:
s01: the tourist information of the ticket buying tourists is acquired at the ticket selling place of the tourist attraction and transmitted to the cloud server;
s02: the cloud server acquires historical ticket information of the user on the Internet according to the user information;
s03: the cloud server acquires the numerical value of recorded scenic spot classification information according to the historical ticket information, and the recorded scenic spot classification is applicable to scenic spot classification of the current scenic spot;
s04: the cloud server sorts the scenic spot classifications according to the recorded scenic spot classification information;
s05: uploading the current scenic spot information to a cloud server by tourists;
s06: the cloud server acquires all scenic spots of the current scenic spot and acquires scenic spot classification corresponding to the scenic spot;
s07: the cloud server sorts all scenic spots of the current scenic spot according to the classification of the recorded scenic spots;
s08: the cloud server screens and sorts the scenic spots in the first 50% according to all scenic spot sorting of the current scenic spot;
s09: the cloud server connects the scenic spots which are ranked at the first 50% in series to form a travel route;
s10: the cloud server inserts scenic spots which are recommended and ordered in the back 50% on the serially connected travel routes.
As a preferred mode of the present invention, for S02, the cloud server searches the dynamic information presented by the tourist on the internet and judges the dynamic information classification corresponding to the recorded scenic spot classification according to the searched dynamic information, and the cloud server corrects the recorded scenic spot classification ranking in combination with the dynamic information classification.
As a preferred mode of the present invention, for the step S04, the cloud server obtains the city in which the scenic spot is located and the situation of the rest scenic spots in the city, and determines the classification of the rest scenic spots.
As a preferred mode of the present invention, for S04, for each city, the cloud server counts the number of user visits to the scenic spots in the city according to the historical ticket information of the user and sorts the number of user visits, and the cloud server corrects the sorting of scenic spots according to the occupation ratio of each scenic spot in the corresponding city.
As a preferred mode of the present invention, the method further comprises the steps of:
a01: the cloud server acquires information of an urban internal scenery region;
a02: the cloud server classifies scenic spots according to the scenic spot information;
a03: the cloud server calculates the proportion of each scenic spot classification of the city in all scenic spots of the city;
a04: the cloud server calculates the weight value of each scenic spot classification according to the duty ratio;
a05: and the cloud server corrects the ordering of the recorded scenic spots according to the weight value.
As a preferred mode of the present invention, for the a04, the weight value is calculated as the ratio of the number of times the user goes to the scenic spot classified by the same scenic spot in the city to the ratio of the scenic spot in the city to the ratio value.
As a preferable mode of the present invention, for S03, the cloud server replaces the value of the classification information of the recorded scenic spot obtained according to the historical ticket information of the same city with the weight value.
As a preferred mode of the present invention, for S10, when the cloud server inserts scenery spots, the number of visited tourists in the last 50% of scenery spots is obtained and sorted, and the interpenetration priority is determined by sorting.
The invention has the following beneficial effects:
the method has the advantages that when tourists go out in the past, the selection preference of scenic spots in scenic spots is recorded, the weight value of the number of tourist routes corresponding to the classification of the scenic spots in the scenic spots is calculated, the weight value is used for representing the selection bias of users under the condition of a large number of samples, so that the scenic spots biased by the users are selected, and the route planning is generated, and therefore the problem that a system or a method capable of carrying out the tourist route planning according to the self situation of the tourists is needed to be solved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure.
FIG. 1 is a step diagram of the present invention;
FIG. 2 is a diagram showing the steps of weight calculation according to the present invention;
fig. 3 is a frame diagram.
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.
Embodiment one:
reference is made to fig. 1-3. A working method of a cloud computing route planning system based on electronic ticketing is used for planning a route of tourists in scenic spots and comprises the following steps:
s01: the tourist information of the ticket buying tourists is acquired at the ticket selling place of the tourist attraction and transmitted to the cloud server;
s02: the cloud server acquires historical ticket information of the user on the Internet according to the user information;
s03: the cloud server acquires the numerical value of recorded scenic spot classification information according to the historical ticket information, and the recorded scenic spot classification is applicable to scenic spot classification of the current scenic spot;
s04: the cloud server sorts the scenic spot classifications according to the recorded scenic spot classification information;
s05: uploading the current scenic spot information to a cloud server by tourists;
s06: the cloud server acquires all scenic spots of the current scenic spot and acquires scenic spot classification corresponding to the scenic spot;
s07: the cloud server sorts all scenic spots of the current scenic spot according to the classification of the recorded scenic spots;
s08: the cloud server screens and sorts the scenic spots in the first 50% according to all scenic spot sorting of the current scenic spot;
s09: the cloud server connects the scenic spots which are ranked at the first 50% in series to form a travel route;
s10: the cloud server inserts scenic spots which are recommended and ordered in the back 50% on the serially connected travel routes.
As a preferred mode of the present invention, for S02, the cloud server searches the dynamic information presented by the tourist on the internet and judges the dynamic information classification corresponding to the recorded scenic spot classification according to the searched dynamic information, and the cloud server corrects the recorded scenic spot classification ranking in combination with the dynamic information classification.
As a preferred mode of the present invention, for the step S04, the cloud server obtains the city in which the scenic spot is located and the situation of the rest scenic spots in the city, and determines the classification of the rest scenic spots.
As a preferred mode of the present invention, for S04, for each city, the cloud server counts the number of user visits to the scenic spots in the city according to the historical ticket information of the user and sorts the number of user visits, and the cloud server corrects the sorting of scenic spots according to the occupation ratio of each scenic spot in the corresponding city.
As a preferred mode of the present invention, the method further comprises the steps of:
a01: the cloud server acquires information of an urban internal scenery region;
a02: the cloud server classifies scenic spots according to the scenic spot information;
a03: the cloud server calculates the proportion of each scenic spot classification of the city in all scenic spots of the city;
a04: the cloud server calculates the weight value of each scenic spot classification according to the duty ratio;
a05: and the cloud server corrects the ordering of the recorded scenic spots according to the weight value.
As a preferred mode of the present invention, for the a04, the weight value is calculated as the ratio of the number of times the user goes to the scenic spot classified by the same scenic spot in the city to the ratio of the scenic spot in the city to the ratio value.
As a preferable mode of the present invention, for S03, the cloud server replaces the value of the classification information of the recorded scenic spot obtained according to the historical ticket information of the same city with the weight value.
As a preferred mode of the present invention, for S10, when the cloud server inserts scenery spots, the number of visited tourists in the last 50% of scenery spots is obtained and sorted, and the interpenetration priority is determined by sorting.
In the implementation process, when tourists need to conduct scenic spot route planning of a scenic spot, the tourists upload user information, the cloud server obtains historical ticket information of the user on the Internet according to the user information, the historical ticket information comprises information of the tourists buying scenic spot tickets at all ticketing APP, ticketing websites, ticketing sites and ticketing windows, the cloud server records all acquired scenic spot ticket information, classifies scenic spots according to scenic spot classification, such as historical historic sites, cultural heritage, natural landscapes and the like, classifies scenic spots according to the classification, counts various scenic spots, namely records once according to the classification of the scenic spot when obtaining one scenic spot record, and accumulates the value.
The cloud server searches dynamic information displayed by tourists on the Internet and judges dynamic information classification corresponding to the classification of the recorded scenic spots according to the searched dynamic information, and the cloud server corrects the classification and sorting of the recorded scenic spots by combining the dynamic information classification, namely, the classification and sorting of the scenic spots are adjusted according to the additional counting through carrying out additional counting on historical ancient trace classification and XX homeland photo by carrying out additional counting on the information of users, such as XX ancient photo, which is publicly displayed in social software, on the Internet of the tourists.
When the scenic spot classification is carried out, the cloud server acquires the city in which the scenic spot is located and the conditions of other scenic spots in the city, judges the classification of the other scenic spots, and for each city, the cloud server counts the scenic spots in the city according to the historical ticket information of the user, sorts the scenic spots, and corrects the sorting of the scenic spots according to the occupation ratio of each scenic spot in the corresponding city. After the cloud server acquires the information of the scenic spots in a city, classifying the scenic spots according to the scenic spot information, calculating the proportion of each scenic spot classification in all scenic spots of the city, further calculating the weight value of each scenic spot classification according to the proportion, and correcting the recorded scenic spot sequence according to the weight value, namely directly replacing the numerical value of the scenic spot classification of the city in the whole classification, for example, the historical historic site proportion of the city A is a, the cultural heritage proportion is b, the natural landscape proportion is c, the historical historic site number of the user visiting the city A is M, calculating the weight to be M/a, and the weight is counted into the total sequence reference number instead of the number M. The weight value is calculated as the ratio of the number of times the user goes to the scenic spot classified by the same scenic spot in the city to the ratio of the scenic spot classified by the city.
And for scenic spot interleaving, namely, the cloud server acquires visit number of tourists of scenic spots ranked in the back 50% and ranks, and after the interleaving priority is judged through ranking, the planned route is acquired, so that scenic spots on the route are acquired, and scenic spots ranked in front are interleaved on the planned route according to the ranking.
The foregoing embodiments are merely illustrative of the technical concept and features of the present invention, and are intended to enable those skilled in the art to understand the present invention and to implement the same according to the present invention, not to limit the scope of the present invention. All changes and modifications that come within the meaning and range of equivalency of the invention are to be embraced within their scope.
Claims (7)
1. The working method of the cloud computing route planning system based on electronic ticketing is used for planning the route of tourists in scenic spots and is characterized by comprising the following steps:
s01: the tourist information of the ticket buying tourists is acquired at the ticket selling place of the tourist attraction and transmitted to the cloud server;
s02: the cloud server acquires historical ticket information of the user on the Internet according to the user information;
s03: the cloud server acquires the numerical value of recorded scenic spot classification information according to the historical ticket information, and the recorded scenic spot classification is applicable to scenic spot classification of the current scenic spot;
s04: the cloud server sorts the scenic spot classifications according to the recorded scenic spot classification information;
s05: uploading the current scenic spot information to a cloud server by tourists;
s06: the cloud server acquires all scenic spots of the current scenic spot and acquires scenic spot classification corresponding to the scenic spot;
s07: the cloud server sorts all scenic spots of the current scenic spot according to the classification of the recorded scenic spots;
s08: the cloud server screens and sorts the scenic spots in the first 50% according to all scenic spot sorting of the current scenic spot;
s09: the cloud server connects the scenic spots which are ranked at the first 50% in series to form a travel route;
s10: the cloud server inserts scenic spots which are recommended and sequenced in the back 50% on the travel route formed by the serial connection;
and for the S02, the cloud server searches dynamic information displayed by tourists on the Internet, judges dynamic information classification corresponding to the recorded scenic spot classification according to the searched dynamic information, and corrects the recorded scenic spot classification sequence by combining the dynamic information classification.
2. A method of operation of an electronic ticketing-based cloud computing route planning system as defined in claim 1, wherein: and for the S04, when the scenic spot classification is carried out, the cloud server acquires the city in which the scenic spot is located and the situation of the rest scenic spots of the city, and judges the classification of the rest scenic spots.
3. A method of operation of an electronic ticketing-based cloud computing route planning system as claimed in claim 2, wherein: for the step S04, for each city, the cloud server counts the number of user visits to scenic spots in the city according to the historical ticket information of the user and sorts the number of user visits, and the cloud server corrects the sorting of scenic spots according to the occupation ratio of each scenic spot in the corresponding city.
4. A method of operating an electronic ticketing-based cloud computing route planning system according to claim 3, characterized in that: the method also comprises the following steps:
a01: the cloud server acquires information of an urban internal scenery region;
a02: the cloud server classifies scenic spots according to the scenic spot information;
a03: the cloud server calculates the proportion of each scenic spot classification of the city in all scenic spots of the city;
a04: the cloud server calculates the weight value of each scenic spot classification according to the duty ratio;
a05: and the cloud server corrects the ordering of the recorded scenic spots according to the weight value.
5. The method for operating an electronic ticketing-based cloud computing route planning system of claim 4, wherein: and for the A04, calculating a weight value as the ratio of the number of times that the user goes to the scenic spot classified by the same scenic spot in the city to the ratio of the scenic spot classified by the city.
6. The method for operating an electronic ticketing-based cloud computing route planning system of claim 5, wherein: and for the S03, the cloud server replaces the numerical value of the classification information of the recorded scenic spots obtained according to the historical ticket information of the same city with the weight value.
7. A method of operation of an electronic ticketing-based cloud computing route planning system as defined in claim 1, wherein: and for the S10, when the cloud server performs scene penetration, the number of visited tourists of the scene which is ranked in the last 50% is obtained, the tourists are ranked, and the penetration priority is judged through the ranking.
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