CN108280210A - A kind of traffic route based on fireworks algorithm determines method and system - Google Patents

A kind of traffic route based on fireworks algorithm determines method and system Download PDF

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CN108280210A
CN108280210A CN201810092424.3A CN201810092424A CN108280210A CN 108280210 A CN108280210 A CN 108280210A CN 201810092424 A CN201810092424 A CN 201810092424A CN 108280210 A CN108280210 A CN 108280210A
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path
traffic
frequent
tree
route
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CN108280210B (en
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王春枝
潘尚
叶志伟
师恒
王毅超
宗欣露
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Hubei University of Technology
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    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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Abstract

The invention discloses a kind of traffic routes based on fireworks algorithm to determine method and system.The method includes:Passenger's trip data collection is obtained, passenger's trip data collection includes the traffic path of passenger in multiple regions;The occurrence number of each traffic path in staqtistical data base;Occurrence number is ranked up;Frequent item collection list is obtained, frequent item collection list is made of occurrence number more than the traffic path of minimum occurrence number;Frequent item collection list is grouped according to area classification, obtains multiple frequent item collection groups;Frequent pattern tree (fp tree) is built according to frequent item collection group;The interference route in frequent pattern tree (fp tree) is deleted using fireworks algorithm, obtains condition subtree, interference route is the route that the transfer stop number of traffic path is less than default transfer stop number, and condition subtree indicates the incidence relation between traffic path;Traffic route is determined according to incidence relation.The present invention can rapidly realize the association mining to traffic route, improve the efficiency that traffic route determines.

Description

A kind of traffic route based on fireworks algorithm determines method and system
Technical field
The present invention relates to data mining technology fields, more particularly to a kind of traffic route determination side based on fireworks algorithm Method and system.
Background technology
With the rapid development of computer technology, R.Agrawal in 1993 et al. is in the investigation to market shopping basket problem In analysis and research, it has been put forward for the first time and has obtained rule knowledge with correlation rule expression formula.The main target of correlation rule extraction is hair The association of intension or dependence between existing item set, i.e., found out from the data largely accumulated hiding data pattern or Knowledge.
Currently, the mining algorithm of generally use correlation rule realizes the determination to traffic route, that is, pass through correlation rule Mining algorithm is associated excavation to traffic route, by analyzing the trip requirements of resident, obtains the planning of traffic route.Priori Property algorithm is one of the mining algorithm of existing correlation rule, which needs Multiple-Scan database, memory consumption big, big It excavates quite time-consuming in data volume, causes digging efficiency not high.Apriority algorithm is used for the determination of traffic route, it cannot be quick The association mining to traffic route is realized on ground, causes traffic route to determine inefficient.
Invention content
Based on this, it is necessary to provide a kind of traffic route based on fireworks algorithm and determine method and system, with rapidly real Now to the association mining of traffic route, the efficiency that traffic route determines is improved.
To achieve the above object, the present invention provides following schemes:
A kind of traffic route based on fireworks algorithm determines method, including:
Passenger's trip data collection is obtained, passenger's trip data collection includes the traffic path of passenger in multiple regions;
The occurrence number of the traffic path of each in staqtistical data base;
The occurrence number is ranked up;
Frequent item collection list is obtained, the frequent item collection list is to be more than the institute of minimum occurrence number by occurrence number State traffic path composition;
The frequent item collection list is grouped according to the area classification, obtains multiple frequent item collection groups;
Frequent pattern tree (fp tree) is built according to the frequent item collection group;
The interference route in the frequent pattern tree (fp tree) is deleted using fireworks algorithm, obtains condition subtree, the interference route Be less than the route of default transfer stop number for the transfer stop number of the traffic path, the condition subtree indicate the traffic path it Between incidence relation;
Traffic route is determined according to the incidence relation.
Optionally, described to delete the interference route in the frequent pattern tree (fp tree) using fireworks algorithm, condition subtree is obtained, is had Body includes:
Bottom-up search frequent pattern tree (fp tree) obtains multiple frequent subtrees, and each frequently subtree includes mulitpath, every One traffic path of the path representation;
Judge whether the fitness function of the corresponding traffic path in every path is more than 1;
If so, being to indicate to retain the path by the label in the path, surviving path is obtained;
If it is not, being then 1 by the path tag, indicate to delete the path;
Condition subtree is built by the surviving path.
Optionally, fitness function described in the method is determined according to support and confidence level, specially
Wherein, i=1,2 ..., n, fitnessiIndicate the fitness function of i-th traffic path, SupportiIndicate the The support of i traffic path;ConfidenceiIndicate the confidence level of i-th traffic path;MinSupport indicates most ramuscule Degree of holding;MinConfidence indicates min confidence.
The present invention also provides a kind of traffic routes based on fireworks algorithm to determine system, the system comprises:
Data set acquisition module, for obtaining passenger's trip data collection, passenger's trip data collection includes multiple regions The traffic path of interior passenger;
Statistical module, the occurrence number for each traffic path in staqtistical data base;
Sorting module, for being ranked up to the occurrence number;
Frequent item collection list acquisition module, for obtaining frequent item collection list, the frequent item collection list be by Occurrence number is more than the traffic path composition of minimum occurrence number;
Frequent item collection group acquisition module, for dividing the frequent item collection list according to the area classification Group obtains multiple frequent item collection groups;
Frequent pattern tree (fp tree) builds module, for building frequent pattern tree (fp tree) according to the frequent item collection group;
Condition subtree acquisition module is obtained for being deleted the interference route in the frequent pattern tree (fp tree) using fireworks algorithm Condition subtree, the interference route are that the transfer stop number of the traffic path is less than the route of default transfer stop number, the condition Subtree indicates the incidence relation between the traffic path;
Traffic route determining module, for determining traffic route according to the incidence relation.
Optionally, the condition subtree acquisition module, specifically includes:
Frequent subtree acquiring unit, bottom-up search frequent pattern tree (fp tree) obtain multiple frequent subtrees, each frequent subtree Including mulitpath, one traffic path of every path representation;
Judging unit, for judging whether the fitness function of the corresponding traffic path in every path is more than 1;
First marking unit, for when the fitness function is more than 1, being then 0 by the path tag, indicating to retain The path, obtains surviving path;
Second marking unit, for when the fitness function is less than 1, being then 1 by the path tag, indicating to delete The path;
Condition subtree construction unit, for building condition subtree by the surviving path.
Optionally, fitness function described in the system is determined according to support and confidence level, specially
Wherein, i=1,2 ..., n, fitnessiIndicate the fitness function of i-th traffic path, SupportiIndicate the The support of i traffic path;ConfidenceiIndicate the confidence level of i-th traffic path;MinSupport indicates most ramuscule Degree of holding;MinConfidence indicates min confidence.
Compared with prior art, the beneficial effects of the invention are as follows:
The present invention proposes a kind of traffic route based on fireworks algorithm and determines method and system, the method includes:It obtains It includes the traffic path of passenger in multiple regions to take passenger's trip data collection, passenger's trip data collection;It is each in staqtistical data base The occurrence number of a traffic path;Occurrence number is ranked up;Obtain frequent item collection list, frequent item collection list be by Occurrence number is more than the traffic path composition of minimum occurrence number;Frequent item collection list is divided according to area classification Group obtains multiple frequent item collection groups;Frequent pattern tree (fp tree) is built according to frequent item collection group;Using fireworks algorithm to frequent mode Tree carries out beta pruning, obtains condition subtree, and condition subtree indicates the incidence relation between traffic path;It is determined and is handed over according to incidence relation Access line.This method carries out beta pruning using fireworks algorithm to frequent pattern tree (fp tree), can rapidly realize the association to traffic route It excavates, improves the efficiency that traffic route determines, and the omission of the correlation rule in mining process can also be reduced.
Description of the drawings
It in order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, below will be to institute in embodiment Attached drawing to be used is needed to be briefly described, it should be apparent that, the accompanying drawings in the following description is only some implementations of the present invention Example, for those of ordinary skill in the art, without having to pay creative labor, can also be according to these attached drawings Obtain other attached drawings.
Fig. 1 is the flow chart that a kind of traffic route based on fireworks algorithm of the embodiment of the present invention determines method;
Fig. 2 is the structure chart that a kind of traffic route based on fireworks algorithm of the embodiment of the present invention determines system.
Specific implementation mode
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete Site preparation describes, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other Embodiment shall fall within the protection scope of the present invention.
In order to make the foregoing objectives, features and advantages of the present invention clearer and more comprehensible, below in conjunction with the accompanying drawings and specific real Applying mode, the present invention is described in further detail.
Fig. 1 is the flow chart that a kind of traffic route based on fireworks algorithm of the embodiment of the present invention determines method.
Referring to Fig. 1, the traffic route based on fireworks algorithm of embodiment determines method, including:
Step S1:Passenger's trip data collection is obtained, passenger's trip data collection includes the trip of passenger in multiple regions Route.
Step S2:The occurrence number of the traffic path of each in staqtistical data base.
Step S3:The occurrence number is ranked up.
Step S4:Frequent item collection list is obtained, the frequent item collection list is to be more than minimum appearance by occurrence number The traffic path composition of number.
Step S5:The frequent item collection list is grouped according to the area classification, obtains multiple frequent one Collection group.
Step S6:Frequent pattern tree (fp tree) is built according to the frequent item collection group.
Step S7:The interference route in the frequent pattern tree (fp tree) is deleted using fireworks algorithm, obtains condition subtree, it is described dry The route that the transfer stop number that route is the traffic path is less than default transfer stop number is disturbed, the condition subtree indicates the trip Incidence relation between route.
The specific building process of the condition subtree is as follows:
Bottom-up search frequent pattern tree (fp tree) obtains multiple frequent subtrees, and each frequently subtree includes mulitpath, every One traffic path of the path representation;
Judge whether the fitness function of the corresponding traffic path in every path is more than 1;
If so, being to indicate to retain the path by the label in the path, surviving path is obtained;
If it is not, being then 1 by the path tag, indicate to delete the path;
Condition subtree is built by the surviving path.
The wherein described fitness function is according to support and confidence level determination, specially
Wherein, i=1,2 ..., n, fitnessiIndicate the fitness function of i-th traffic path, SupportiIndicate the The support of i traffic path;ConfidenceiIndicate the confidence level of i-th traffic path;MinSupport indicates most ramuscule Degree of holding;MinConfidence indicates min confidence.
Step S8:Traffic route is determined according to the incidence relation.
The traffic route based on fireworks algorithm in the present embodiment determines method, using fireworks algorithm to frequent pattern tree (fp tree) into Row beta pruning can rapidly realize the association mining to traffic route, improve the efficiency that traffic route determines, and can also reduce The omission of correlation rule in mining process.
The present invention also provides a kind of traffic routes based on fireworks algorithm to determine that system, Fig. 2 are the embodiment of the present invention one Kind determines the structure chart of system based on the traffic route of fireworks algorithm.
Referring to Fig. 2, the traffic route based on fireworks algorithm of embodiment determines system 20, including:
Data set acquisition module 201, for obtaining passenger's trip data collection, passenger's trip data collection includes multiple areas The traffic path of passenger in domain.
Statistical module 202, the occurrence number for each traffic path in staqtistical data base.
Sorting module 203, for being ranked up to the occurrence number.
Frequent item collection list acquisition module 204, for obtaining frequent item collection list, the frequent item collection list is It is made of more than the traffic path of minimum occurrence number occurrence number.
Frequent item collection group acquisition module 205, for being carried out to the frequent item collection list according to the area classification Grouping, obtains multiple frequent item collection groups.
Frequent pattern tree (fp tree) builds module 206, for building frequent pattern tree (fp tree) according to the frequent item collection group.
Condition subtree acquisition module 207 is obtained for being deleted the interference route in the frequent pattern tree (fp tree) using fireworks algorithm To condition subtree, the interference route is that the transfer stop number of the traffic path is less than the route of default transfer stop number, the item Part subtree indicates the incidence relation between the traffic path.
The condition subtree acquisition module 207, specifically includes:
Frequent subtree acquiring unit, bottom-up search frequent pattern tree (fp tree) obtain multiple frequent subtrees, each frequent subtree Including mulitpath, one traffic path of every path representation;
Judging unit, for judging whether the fitness function of the corresponding traffic path in every path is more than 1;
First marking unit, for when the fitness function is more than 1, being then 0 by the path tag, indicating to retain The path, obtains surviving path;
Second marking unit, for when the fitness function is less than 1, being then 1 by the path tag, indicating to delete The path;
Condition subtree construction unit, for building condition subtree by the surviving path.
Traffic route determining module 208, for determining traffic route according to the incidence relation.
The traffic route based on fireworks algorithm in the present embodiment determines system, using fireworks algorithm to frequent pattern tree (fp tree) into Row beta pruning can rapidly realize the association mining to traffic route, improve the efficiency that traffic route determines, and can also reduce The omission of correlation rule in mining process.
In this specification for system disclosed in embodiment, since it is corresponded to the methods disclosed in the examples, institute With the fairly simple of description, reference may be made to the description of the method.
Principle and implementation of the present invention are described for specific case used herein, and above example is said The bright method and its core concept for being merely used to help understand the present invention;Meanwhile for those of ordinary skill in the art, foundation The thought of the present invention, there will be changes in the specific implementation manner and application range.In conclusion the content of the present specification is not It is interpreted as limitation of the present invention.

Claims (6)

1. a kind of traffic route based on fireworks algorithm determines method, which is characterized in that including:
Passenger's trip data collection is obtained, passenger's trip data collection includes the traffic path of passenger in multiple regions;
The occurrence number of the traffic path of each in staqtistical data base;
The occurrence number is ranked up;
Frequent item collection list is obtained, the frequent item collection list is to be more than described in minimum occurrence number by occurrence number Walking along the street line composition;
The frequent item collection list is grouped according to the area classification, obtains multiple frequent item collection groups;
Frequent pattern tree (fp tree) is built according to the frequent item collection group;
The interference route in the frequent pattern tree (fp tree) is deleted using fireworks algorithm, obtains condition subtree, the interference route is institute The transfer stop number for stating traffic path is less than the route of default transfer stop number, and the condition subtree indicates between the traffic path Incidence relation;
Traffic route is determined according to the incidence relation.
2. a kind of traffic route based on fireworks algorithm according to claim 1 determines method, which is characterized in that the profit The interference route in the frequent pattern tree (fp tree) is deleted with fireworks algorithm, condition subtree is obtained, specifically includes:
Bottom-up search frequent pattern tree (fp tree) obtains multiple frequent subtrees, and each frequently subtree includes mulitpath, described in every One traffic path of path representation;
Judge whether the fitness function of the corresponding traffic path in every path is more than 1;
If so, being to indicate to retain the path by the label in the path, surviving path is obtained;
If it is not, being then 1 by the path tag, indicate to delete the path;
Condition subtree is built by the surviving path.
3. a kind of traffic route based on fireworks algorithm according to claim 2 determines method, which is characterized in that described suitable Response function is according to support and confidence level determination, specially
Wherein, i=1,2 ..., n, fitnessiIndicate the fitness function of i-th traffic path, SupportiIndicate i-th The support of traffic path;ConfidenceiIndicate the confidence level of i-th traffic path;MinSupport indicates minimum and supports Degree;MinConfidence indicates min confidence.
4. a kind of traffic route based on fireworks algorithm determines system, which is characterized in that the system comprises:
Data set acquisition module, for obtaining passenger's trip data collection, passenger's trip data collection includes multiplying in multiple regions The traffic path of visitor;
Statistical module, the occurrence number for each traffic path in staqtistical data base;
Sorting module, for being ranked up to the occurrence number;
Frequent item collection list acquisition module, for obtaining frequent item collection list, the frequent item collection list is by occurring Number is more than the traffic path composition of minimum occurrence number;
Frequent item collection group acquisition module is obtained for being grouped to the frequent item collection list according to the area classification To multiple frequent item collection groups;
Frequent pattern tree (fp tree) builds module, for building frequent pattern tree (fp tree) according to the frequent item collection group;
Condition subtree acquisition module obtains condition for deleting the interference route in the frequent pattern tree (fp tree) using fireworks algorithm Subtree, the interference route are that the transfer stop number of the traffic path is less than the route of default transfer stop number, the condition subtree Indicate the incidence relation between the traffic path;
Traffic route determining module, for determining traffic route according to the incidence relation.
5. a kind of traffic route based on fireworks algorithm according to claim 4 determines system, which is characterized in that the item Part subtree acquisition module, specifically includes:
Frequent subtree acquiring unit, bottom-up search frequent pattern tree (fp tree) obtain multiple frequent subtrees, and each frequently subtree includes Mulitpath, one traffic path of every path representation;
Judging unit, for judging whether the fitness function of the corresponding traffic path in every path is more than 1;
First marking unit, for when the fitness function is more than 1, being then 0 by the path tag, indicating described in reservation Path obtains surviving path;
Second marking unit, for when the fitness function is less than 1, being then 1 by the path tag, indicating described in deletion Path;
Condition subtree construction unit, for building condition subtree by the surviving path.
6. a kind of traffic route based on fireworks algorithm according to claim 5 determines system, which is characterized in that described suitable Response function is according to support and confidence level determination, specially
Wherein, i=1,2 ..., n, fitnessiIndicate the fitness function of i-th traffic path, SupportiIndicate i-th The support of traffic path;ConfidenceiIndicate the confidence level of i-th traffic path;MinSupport indicates minimum and supports Degree;MinConfidence indicates min confidence.
CN201810092424.3A 2018-01-31 2018-01-31 Traffic route determination method and system based on firework algorithm Active CN108280210B (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109902796A (en) * 2019-03-14 2019-06-18 重庆邮电大学 A kind of improved wolf pack algorithm based on fireworks explosion
CN110503234A (en) * 2019-07-03 2019-11-26 广东工业大学 A kind of method, system and the equipment of logistics transportation scheduling

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20110096302A (en) * 2010-02-22 2011-08-30 숭실대학교산학협력단 Apparatus and method for association rule mining using frequent pattern-tree for incremental data processing
CN102867408A (en) * 2012-09-17 2013-01-09 北京理工大学 Method and system for selecting bus trip route
CN103258049A (en) * 2013-05-27 2013-08-21 重庆邮电大学 Association rule mining method based on mass data
CN105488597A (en) * 2015-12-28 2016-04-13 中国民航信息网络股份有限公司 Passenger destination prediction method and system
CN106776900A (en) * 2016-11-30 2017-05-31 百度在线网络技术(北京)有限公司 Traveling method and device
CN106991141A (en) * 2017-03-21 2017-07-28 北京邮电大学 A kind of association rule mining method based on depth pruning strategy

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20110096302A (en) * 2010-02-22 2011-08-30 숭실대학교산학협력단 Apparatus and method for association rule mining using frequent pattern-tree for incremental data processing
CN102867408A (en) * 2012-09-17 2013-01-09 北京理工大学 Method and system for selecting bus trip route
CN103258049A (en) * 2013-05-27 2013-08-21 重庆邮电大学 Association rule mining method based on mass data
CN105488597A (en) * 2015-12-28 2016-04-13 中国民航信息网络股份有限公司 Passenger destination prediction method and system
CN106776900A (en) * 2016-11-30 2017-05-31 百度在线网络技术(北京)有限公司 Traveling method and device
CN106991141A (en) * 2017-03-21 2017-07-28 北京邮电大学 A kind of association rule mining method based on depth pruning strategy

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109902796A (en) * 2019-03-14 2019-06-18 重庆邮电大学 A kind of improved wolf pack algorithm based on fireworks explosion
CN110503234A (en) * 2019-07-03 2019-11-26 广东工业大学 A kind of method, system and the equipment of logistics transportation scheduling

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