CN109152097A - Agriculture Tourism Garden of Ecological wireless sensing net node layout method based on social force model - Google Patents
Agriculture Tourism Garden of Ecological wireless sensing net node layout method based on social force model Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
- H04W16/18—Network planning tools
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/23—Clustering techniques
- G06F18/232—Non-hierarchical techniques
- G06F18/2321—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions
- G06F18/23213—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions with fixed number of clusters, e.g. K-means clustering
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Mining
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/14—Travel agencies
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/35—Services specially adapted for particular environments, situations or purposes for the management of goods or merchandise
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
Abstract
The present invention relates to a kind of agriculture Tourism Garden of Ecological wireless sensing net node layout method based on social force model, it is characterized in that, the following steps are included: firstly, obtain spatial distribution of the tourist in agriculture Tourism Garden of Ecological by social force model, and store data into database.Then, according to tourist's spatial distribution data of acquisition, the final placement location of node is obtained using improved K-means algorithm.Method provided by the invention can optimize layout of the wireless sensing net node in Tourism Garden of Ecological, and wireless sensor node is made preferably to service tourist, to promote tourist experience.
Description
Technical field
The present invention relates to a kind of sides that agriculture Tourism Garden of Ecological wireless sensing net node layout can be carried out by social force model
Method can be obtained in agriculture Tourism Garden of Ecological convenient for providing the wireless sensing net node position of service for tourist by this method, mention
Tourist is risen to visit a park experience.
Background technique
The paces that China's agricultural industry upgrading in recent years, management mode optimize constantly are accelerated.China's agricultural industry is gradually
It shows and is gradually converted into the situation that production and service are laid equal stress on by biasing toward productivity business activities.Agriculture industrialization upgrade,
Under the collectively promoting of external causes such as internal causes and society consumption demand such as economic benefit driving, China's sight-seeing agriculture has been obtained quickly
Development.Sight-seeing agriculture combines agricultural production process with sightseeing, leisure, education and culture, to meet the polynary need of consumer
It asks.Sight-seeing agriculture should be attached most importance to promoting tourist experience, and then promote the level and range of service.
The fast development of agriculture technology of Internet of things provides new technical support hand for the industrial upgrading and optimization of sight-seeing agriculture
Section.Sightseeing tour guide, example education and agricultural production process body can be provided for tourist by the intelligent movables such as smart phone equipment
The service of testing etc. significantly promotes tourist experience effect.But it is flexible by maintenance cost, garden layout, information architecture and service
Property etc. factors limitation, can not fully rely on the mobile communications networks such as the short-distance wireless such as WiFi networking mode or 3G, 4G provide clothes
Business.And intelligent movable equipment is combined in the widely applied wireless sensor network of agriculture field, building mixed type without
Line sensor network can not only be compatible with traditional Agricultural Information monitoring management function, also can be in service field directly by node
It is provided intuitively effectively by the technologies such as the short-distance wireless communications such as intelligent movable equipment utilization bluetooth and NFC label read-write for tourist
Information service.In order to make wireless sensor node preferably service tourist, tourist experience is promoted, the layout optimization of node has weight
The meaning wanted.In previous research, the emphasis that domestic and foreign scholars study wireless sensor network layout optimization is to improve network to cover
Lid rate and reduction network energy consumption.So far, rarely seen in wireless sensor network node layout method to be carried out based on visitor behavior mode
The project study of node layout.The present invention proposes a kind of suitable for sightseeing garden hybrid wireless from social force model
The method of sensor network nodes layout optimization.
Summary of the invention
The purpose of the present invention is: optimize wireless sensor network node in agriculture Tourism Garden of Ecological based on tourist's spatial distribution
Layout makes node placement location be convenient for providing service for tourist, is effectively matched the sightseeing process of tourist, promotes tourist experience, be
The service-oriented hybrid wireless sensor network construction in agriculture sightseeing garden provides corresponding support.
In order to achieve the above object, the technical solution of the present invention is to provide a kind of, and the agricultural based on social force model is gone sightseeing
Garden wireless sensing net node layout method, which comprises the following steps:
Step 1, on the basis of original social force model, in conjunction with agriculture sightseeing garden ring border be laid out, establish the following equation a group institute
Tourist's behavior model in the Tourism Garden of Ecological shown:
In formula, rαThe spatial position vector for being tourist α in Tourism Garden of Ecological；vαIt (t) is traveling speed of the tourist α in Tourism Garden of Ecological
Degree；mαFor the quality of tourist α；fαIt (t) is social force suffered by tourist；ζαIt (t) is the disturbance term of reflection random behavior deviation；The motivation for being moved to somewhere sight spot in Tourism Garden of Ecological is thirsted for for tourist；fαβ(rα) between tourist α and Tourism Garden of Ecological path boundary
Active force；fαβ(rα, vα, rβ, vβ) active force between tourist α and tourist β；fαi(rα, ri, t) and it is sightseeing garden to tourist
Attraction effect；
Different types of functional area in step 2, the visitor behavior models coupling agricultural Tourism Garden of Ecological obtained using step 1
The layout (tour guide's facility, amusement facility and educational alternative etc.) of facility, pedestrian in (Fruit-Picking Area, Catering Area and service area etc.), garden
Traffic demand data (pedestrian's arriving amt-Annual distribution and pedestrian's composition ratio etc.) and pedestrian traffic performance data (pedestrian's speed
Degree, queue waiting time and pedestrian's Path selection etc.) etc., the relevant parameter in visitor behavior model is set, using based on society
The Anylogic emulation platform of power model carries out pedestrian simulation, obtains representative T days tourist's spatial distribution data D
[(x11, y11), (x12, y12) ..., (xTN, yTN)], in formula, N is tourist stop place number in Tourism Garden of Ecological, by tourist space point
Cloth data are stored into database；
Step 3, using the improvement K-means clustering algorithm for agriculture Tourism Garden of Ecological wireless sensing net node layout to T days
Tourist's spatial distribution data carries out clustering, obtains daily tourist's aggregation zone center d [(xt1, yt1), (xt2, yt2) ...,
(xtc, ytc)] node candidate placement location as garden, t=1: T, c=1: C, C is cluster number, the number of cluster in formula
It equal to the number that garden interior joint is placed, is determined by the size of garden and the communication range of node, on its basis by calculating T
The mean value of its node candidate position determines final placement location the S [(x of wireless sensing net node in agriculture Tourism Garden of Ecological1, y1), (x2,
y2) ..., (xC, yC)]。
Preferably, in step 3, using improving, K-means clustering algorithm is final to agriculture Tourism Garden of Ecological wireless sensing net node
The determination of placement location specifically includes the following steps:
Step 301, hierarchical clustering obtain initial cluster center
The initial cluster center of traditional K-means algorithm is randomly choosed from data set, and cluster centre is caused to be easily trapped into
Locally optimal solution, and cluster result is not unique.For the defect for overcoming traditional K-means clustering algorithm, the present invention uses first
Agglomerative Hierarchical Clustering algorithm based on minimum range respectively clusters T days tourist's spatial distribution datas, the number of cluster
The number C for as placing node calculates after cluster tourist's spatial distribution data mean value in every class and obtains uniquely determine initial and gathers
Class center dt[(x1, y1), (x2, y2) ..., (xC, yC)]；
Step 302 divides the affiliated class of tourist's spatial distribution data according to minimum range
Poll tourist's spatial distribution data, calculate the t days gardens in each cluster centre with all tourist's spatial distribution numbers
Euclidean distance (dist betweenc1, distc2..., distcn), wherein n=1: N, c=1: C.
According to minimum range formula dmin=min (dist1n, dist2n..., distcn), calculate tourist's spatial distribution data
It is divided into the corresponding class of the cluster centre to the minimum range of each cluster centre, and by its data.In addition, in cluster process
Object number in class is limited, is rounded the mean value of the number P total number in each class (downwards, remaining data are put
Enter apart from the nearest affiliated class of cluster centre)；
Step 303, calculating mean value obtain new cluster centre
The each tourist's spatial distribution data being divided into each class in step 302 is subjected to coordinate mean value computation, is obtained
New cluster centre d [(xt1, yt1), (xt2, yt2) ..., (xtc, ytc)]；
Step 304 repeats step 302 and step 303 until new cluster centre is small at a distance from last cluster centre
In threshold value, end of clustering, using finally obtained cluster centre as node candidate placement location；
Step 305 summarizes all both candidate nodes, the final placement location of calculate node:
Node candidate position daily in T days is summarized, the mean value by calculating corresponding class node candidate position obtains nothing
Final placement location the S [(x of line sensing net node1, y1), (x2, y2) ..., (xC, yC)]。
Preferably, the initial cluster center of c-th of class can be calculated by following formula in step 301:
In formula, M is the number of every class data after hierarchical clustering, (Dxcm, Dycm) representational level cluster c class in m-th trip
Objective spatial distribution position coordinates.
Preferably, in step 303, the cluster centre of c-th of class can be calculated by following formula:
In formula,It indicates to improve p-th of tourist's spatial distribution position coordinates in K-means cluster c class.
Preferably, in step 305, the final placement location of c-th of node can be obtained by following formula:
Method provided by the invention can optimize layout of the wireless sensing net node in Tourism Garden of Ecological, make node placement location
Positioned at the aggregation zone of tourist, convenient for providing service for tourist, it is effectively matched the sightseeing process of tourist, promotes tourist experience.
Detailed description of the invention
Fig. 1 is a kind of agriculture Tourism Garden of Ecological wireless sensing net node layout method flow chart based on social force model；
Fig. 2 is tourist's behavior model schematic diagram in apple orchard；
Fig. 3 is apple garden tourist's one day spatial distribution data cluster result figure；
Specific embodiment
In order to make the present invention more obvious and understandable, hereby with preferred embodiment, and attached drawing is cooperated to be described in detail below.
In conjunction with Fig. 1, a kind of agriculture Tourism Garden of Ecological wireless sensing net node layout based on social force model provided by the invention
Method comprising the following specific steps
By taking apple garden in the agriculture Tourism Garden of Ecological in the city S as an example, on the basis of original social force model, in conjunction with agriculture Tourism Garden of Ecological
Environment layout and infrastructure, apple garden middle reaches visitor's behavior model are indicated with following equation group:
In formula, rαThe spatial position vector for being tourist α in apple garden；vαIt (t) is row of the tourist α in apple garden
Into speed；mαFor the quality of tourist α；fαIt (t) is social force suffered by tourist；ζαIt (t) is the disturbance of reflection random behavior deviation
?；The motivation for being moved to certain sight spot in apple garden is thirsted for for tourist；fαB(rα) it is tourist α and apple garden path side
Active force between boundary；fαβ(rα, vα, rβ, vβ) active force between tourist α and tourist β；fαi(rα, ri, t) and it is apple garden
To the attraction effect of tourist.
Consider that itself motivation of tourist, the factors such as the effect of surrounding tourist and external environment are false in visitor behavior model
If tourist's individual is drive visitor movement by the effect of social force.Social force include three aspect, i.e., driving force, person to person it
Between interaction force and people and boundary (barrier) between active force.Driving force refers to influence of tourist's subjective consciousness to behavior
It is converted into suffered " social force " itself applied, tourist is reflected and wishes the wish arrived at the destination with desired speed.People
Active force between people mainly includes the contact between the social mentality's power for attempting between tourist that certain distance is kept to generate and body
Power.Active force between people and boundary mainly includes that tourist and garden path boundary, wall etc. attempt that certain distance is kept to generate
Contact force between repulsive force and body and barrier.
Tourist's behavior model schematic diagram in apple orchard is as shown in Figure 2.
Utilize functional area (Fruit-Picking Area, Catering Area kimonos different types of in visitor behavior models coupling agricultural Tourism Garden of Ecological
Be engaged in area etc.), the layout (tour guide's facility, amusement facility and educational alternative etc.) of facility in garden, (pedestrian arrives pedestrian traffic demand data
Up to quantity-Annual distribution and pedestrian's composition ratio etc.) and pedestrian traffic performance data (pedestrian's speed, queue waiting time and row
People's Path selection etc.) etc., the relevant parameter in visitor behavior model is set, such as according to Tourism Garden of Ecological pedestrian traffic demand data
Finding, to tourist, different zones Path selection probability is configured in Tourism Garden of Ecological, determines tourist's track route；According to sight
The florescence and collecting period of crop in the Fruit-Picking Area of light garden, visiting time obedience of the setting tourist in different gardens are uniformly distributed
Uniform (min, max)；According to specific sight spot facility in the public place of entertainment, Catering Area, Fruit-Picking Area, the attraction of waiting area is set
Sub- position.Pedestrian simulation is carried out to tourist in agriculture Tourism Garden of Ecological using the Anylogic emulation platform based on social force model, is obtained
Accurately and reliably tourist's spatial distribution data into apple garden, and by the storage of tourist's spatial distribution data into database.
The spatial distribution data of apple garden tourist's one day is read from database, and utilizes MATLAB emulation platform logarithm
According to being marked, clustering is then carried out using improvement K-means algorithm.It clusters number and is equal to placement sensor section in garden
The number of point is determined in apple garden under the premise of meeting inter-node communication range using average area covering deployment strategy
The node number for needing to place is 10.
First with MATLAB emulation platform using the Agglomerative Hierarchical Clustering algorithm based on minimum range to apple garden
Day, the spatial distribution data of tourist carried out clustering, and the mean value for calculating every class tourist spatial distribution data after clustering obtains uniquely
Determining initial cluster center, initial cluster center position coordinates are as shown in table 1.
1 apple garden tourist's one day spatial distribution data initial cluster center position coordinates of table
| Node | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
| Abscissa | 103.74 | 102.46 | 112.09 | 91.04 | 50.98 | 69.67 | 48.38 | 75.06 | 73.82 | 117.53 |
| Ordinate | 131.81 | 110.99 | 51.71 | 57.34 | 147.11 | 137.86 | 110.61 | 104.78 | 77.57 | 85.86 |
The Euclidean distance for calculating tourist's spatial distribution data and each initial cluster center, according to minimum range formula dmin=
min(dist1n, dist2n..., distcn), obtain tourist's spatial distribution data to each cluster centre minimum range, and by its
Data are divided into the corresponding class of the cluster centre.Then take mean value as new cluster centre data in obtained class again,
Successively iteration, until new cluster centre is less than threshold value at a distance from last cluster centre, then algorithm terminates, and what is obtained is final
Cluster centre is Tourism Garden of Ecological node candidate placement location.Using improvement K-means algorithm to apple garden tourist's one day space
The cluster result of distributed data is as shown in figure 3, wherein filled square is final cluster centre.Apple garden tourist's one day is empty
Between the node candidate placement location coordinate that clusters of distributed data it is as shown in table 2.
2 apple garden node candidate one day position coordinates of table
| Node | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
| Abscissa | 102.92 | 107.45 | 109.96 | 90.71 | 54.86 | 76.67 | 57.74 | 85.80 | 75.60 | 117.82 |
| Ordinate | 128.50 | 109.09 | 52.46 | 54.33 | 144.23 | 134.71 | 107.38 | 89.40 | 69.01 | 82.71 |
The difference that the Tourism Garden of Ecological Various Seasonal daily tourist's arrival time is distributed causes the spatial distribution of tourist in Tourism Garden of Ecological
There are great differences.Therefore, it in order to which the node for meeting placement can provide effective service for tourist whole year, should select in whole year
Representative tourist's distributed data clusters.Randomly select one day tourist space point every month in the middle of the month from annual 12
Cloth data are respectively adopted and improve K-means algorithm progress clustering, obtain 12 group node candidate's placement locations.Then to this
12 group node position candidates seek corresponding mean value, the final placement location as node.The apple garden node is finally placed
Position coordinates are as shown in table 3.
3 apple garden finish node placement location coordinate of table
| Node | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
| Abscissa | 101.73 | 108.46 | 110.36 | 91.82 | 53.91 | 73.78 | 53.08 | 83.45 | 74.61 | 117.93 |
| Ordinate | 131.52 | 109.72 | 51.71 | 56.28 | 146.64 | 135.23 | 106.82 | 92.34 | 71.38 | 84.25 |
Using identical method, different function garden wireless sensing net node in the agricultural Tourism Garden of Ecological can be obtained and finally put
Seated position.
Claims (5)
1. a kind of agriculture Tourism Garden of Ecological wireless sensing net node layout method based on social force model, which is characterized in that including with
Lower step:
Step 1, on the basis of original social force model, in conjunction with agriculture sightseeing garden ring border be laid out, establish the following equation shown in group
Tourist's behavior model in Tourism Garden of Ecological:
In formula, rαThe spatial position vector for being tourist α in Tourism Garden of Ecological；vαIt (t) is travel speed of the tourist α in Tourism Garden of Ecological；mα
For the quality of tourist α；fαIt (t) is social force suffered by tourist；ζαIt (t) is the disturbance term of reflection random behavior deviation；For
Tourist thirsts for the motivation for being moved to somewhere sight spot in Tourism Garden of Ecological；fαB(rα) effect between tourist α and Tourism Garden of Ecological path boundary
Power；fαβ(rα, vα, rβ, vβ) active force between tourist α and tourist β；fαi(rα, ri, t) and it is attraction of the sightseeing garden to tourist
Effect；
Different types of functional area in step 2, the visitor behavior models coupling agricultural Tourism Garden of Ecological obtained using step 1, in garden
Layout, pedestrian traffic demand data and the pedestrian traffic performance data of facility are arranged the relevant parameter in visitor behavior model, adopt
Pedestrian simulation is carried out with the Anylogic emulation platform based on social force model, obtains representative T days tourist spaces point
Cloth data D [(x11, y11), (x12, y12) ..., (xTN, yTN)], in formula, N is tourist stop place number in Tourism Garden of Ecological, by tourist
Spatial distribution data is stored into database；
Step 3, using the improvement K-means clustering algorithm for agriculture Tourism Garden of Ecological wireless sensing net node layout to T days tourists
Spatial distribution data carries out clustering, obtains daily tourist's aggregation zone center d [(xt1, yt1), (xt2, yt2) ..., (xtc,
ytc)] node candidate placement location as garden, t=1: T, c=1: C, C is cluster number in formula, and the number of cluster is equal to garden
The number that area's interior joint is placed, is determined by the size of garden and the communication range of node, on its basis by calculating T days nodes
The mean value of position candidate determines final placement location the S [(x of wireless sensing net node in agriculture Tourism Garden of Ecological1, y1), (x2,
y2) ..., (xC, yC)]。
2. a kind of agriculture Tourism Garden of Ecological wireless sensing net node layout method based on social force model as described in claim 1,
It is characterized in that, finally being placed using K-means clustering algorithm is improved to agriculture Tourism Garden of Ecological wireless sensing net node in step 3
Position determine specifically includes the following steps:
Step 301, hierarchical clustering obtain initial cluster center
T days tourist's spatial distribution datas are gathered respectively using the Agglomerative Hierarchical Clustering algorithm based on minimum range first
Class, the number of cluster are to place the number C of node, and the acquisition of tourist's spatial distribution data mean value is unique in every class after calculating cluster
Determining initial cluster center dt[(x1, y1), (x2, y2) ..., (xC, yc)]；
Step 302 divides the affiliated class of tourist's spatial distribution data according to minimum range
Poll tourist's spatial distribution data, calculate the t days gardens in each cluster centre with all tourist's spatial distribution datas it
Between Euclidean distance (distc1, distc2..., distcn), wherein n=1: N, c=1: C.
According to minimum range formula dmin=min (dist1n, dist2n..., disten), tourist's spatial distribution data is calculated to respectively
The minimum range of cluster centre, and its data is divided into the corresponding class of the cluster centre.In addition, to class in cluster process
Middle object number is limited, and the mean value of the number P total number in each class is made, downwards be rounded, remaining data be put into away from
From the nearest affiliated class of cluster centre；
Step 303, calculating mean value obtain new cluster centre
The each tourist's spatial distribution data being divided into each class in step 302 is subjected to coordinate mean value computation, is obtained new
Cluster centre d [(xt1, yt1), (xt2, yt2) ..., (xtc, ytc)]；
Step 304 repeats step 302 and step 303 until new cluster centre is less than threshold at a distance from last cluster centre
Value, end of clustering, using finally obtained cluster centre as node candidate placement location；
Step 305 summarizes all both candidate nodes, the final placement location of calculate node:
Finish node position candidate daily in T days is summarized, the mean value by calculating every class finish node position candidate obtains
Final placement location the S [(x of wireless sensing net node1, y1), (x2, y2) ..., (xC, yC)]。
3. a kind of agriculture Tourism Garden of Ecological wireless sensing net node layout method based on social force model as claimed in claim 2,
It is characterized by:
The initial cluster center of c-th of class is calculated by following formula in step 301:
In formula, M is the number of every class data after hierarchical clustering,It is empty that representational level clusters m-th of tourist in c class
Between distributing position coordinate.
4. a kind of agriculture Tourism Garden of Ecological wireless sensing net node layout method based on social force model as claimed in claim 2,
It is characterized by: the cluster centre of c-th of class is calculated by following formula in step 303:
In formula,It indicates to improve p-th of tourist's spatial distribution position coordinates in K-means cluster c class.
5. a kind of agriculture Tourism Garden of Ecological wireless sensing net node layout method based on social force model as claimed in claim 2,
It is characterized by: the final placement location of c-th of node is obtained by following formula in step 305:
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112991082A (en) * | 2021-02-06 | 2021-06-18 | 河北农业大学 | Facility environment monitoring sensor deployment optimization method |
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