CN108510179A - Disaster assistance goods and materials method of adjustment and system - Google Patents
Disaster assistance goods and materials method of adjustment and system Download PDFInfo
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- 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
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- G06F18/2433—Single-class perspective, e.g. one-against-all classification; Novelty detection; Outlier detection
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- 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
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Abstract
The present invention relates to disaster assistance fields, are related to a kind of disaster assistance goods and materials method of adjustment, including：Obtain the Outliers Detection data set of the disaster achievement data and current relief goods distribution data that include devastated；Data normalization is carried out to the data in Outliers Detection data set；Outliers Detection parameter is set；Outliers Detection data set is mapped into metric space according to Outliers Detection parameter and carries out Outliers Detection, acquisition most possibly n devastated of relief goods unreasonable distribution occurs as Outliers Detection result；Whether the relief goods quantity allotted for verifying n region is reasonable, and disaster relief supplies quantity allotted is not adjusted if rationally if quantity allotted.The present invention goes back while proposing a kind of disaster assistance goods and materials adjustment system.The present invention can balance the weight of meteorological disaster achievement data, relief goods distribution two generic attribute of data, accelerate meteorological disaster relief goods and adjust reaction speed, improve the degree of automation, and can be compatible with different types of meteorological disaster using metric space algorithm.
Description
Technical field
The present invention relates to disaster assistance field, more particularly to a kind of disaster assistance goods and materials method of adjustment and system.
Background technology
Our times Hazard Evaluation for Weather Disaster increasingly refines, and ability of preventing and reducing natural disasters gradually has the possibility of quantization,
The distribution of disaster relief supplies and the foundation for being deployed with the science of comparison.Usually rely on the historical meteorological disaster system in disaster spot
It counts, disposes corresponding disaster relief supplies in different zones, loss is reduced as far as possible by way of providing for a rainy day.
Historical data has certain rule, by this deployment disaster relief supplies, is reasonable for most of region.But
Meteorology is changing always, and the meteorological disaster severity of especially respective regions is likely to unexpected, in this case can be with
Disaster relief supplies are reinforced in a manner of manually instructing or the disaster relief supplies between each region are adjusted by relevant departments.
The artificial mode for instructing meteorological disaster relief goods, reaction speed is slow and the degree of automation is relatively low.It is rescuing
The crucial moment that calamity is raced against time is very likely to that the opportune time can be delayed.When large-scale disaster relief supplies adjust, manually refer to
It leads speed slowly and is more prone to malfunction.Secondly, for different types of meteorological disaster, the people of different countermeasures is needed to have
Member could cope with different types of relief goods adjustment work respectively, and practical operation difficulty is larger.
Invention content
Embodiments of the present invention aim to solve at least one of the technical problems existing in the prior art.For this purpose, of the invention
Embodiment need to provide a kind of disaster assistance goods and materials method of adjustment and system.
The disaster assistance goods and materials method of adjustment of embodiment of the present invention, which is characterized in that including：
Step 10, obtain including distributing data including the disaster achievement data of devastated and current relief goods from
Group's detection data collection；
Step 11, data normalization is carried out to the data in Outliers Detection data set；
Step 13, Outliers Detection parameter is set；
Step 14, Outliers Detection data set is mapped to by metric space according to Outliers Detection parameter and carries out Outliers Detection, obtained
N devastated for relief goods unreasonable distribution most possibly occur is obtained as Outliers Detection result；
Step 15, whether the relief goods quantity allotted for verifying n region is reasonable, does not adjust and rescues if rationally if quantity allotted
Calamity goods and materials quantity allotted.
In one embodiment, further include after step 11：
Step 12, equalizing weight adjustment is implemented to normalized data, distributes disaster achievement data and relief goods to number
According to being separately adjusted to angularly default weight.
In one embodiment, the data normalization of step 11 carries out as follows：
Wherein, DIS (xi, xj) indicate i-th of data xiWith j-th of data xjDistance function, d indicate Outliers Detection number
According to the quantity of intensive data；
For the data of numerical attribute in Outliers Detection data set,
δ(xik, xjk)=(xik-xjk)2
xikWith xjkThe numerical value after normalization is indicated respectively；
For the data of nonumeric attribute in Outliers Detection data set,
δ(xik, xjk)=(xik-xjk)/max(x1k-x_k)
x_kIndicate k-th of attribute of any one data in Outliers Detection data set.
In one embodiment, Outliers Detection parameter includes the number of the quantity k and the maximum n data of degree of peeling off of arest neighbors
Measure n；
Outliers Detection includes in step 14：
Calculate k arest neighbors of each data in Outliers Detection data set；
Calculate the degree of peeling off of each data；Wherein, degree of peeling off indicates each data k arest neighbors corresponding with the data
Sum of the distance；
It is ranked up from big to small by degree of peeling off and obtains the maximum n data of degree of peeling off in Outliers Detection data set；Wherein,
Most possibly there is n devastated of relief goods unreasonable distribution to the n data in correspondence respectively.
In one embodiment, this method further includes：
Step 16, after the relief goods quantity allotted in n region of verification is unreasonable, then according to pre-set mode weight
New adjustment；
Step 17, new disaster relief supplies allocation plan is exported according to the result after adjustment.
The present invention also proposes a kind of disaster assistance goods and materials adjustment system, which is characterized in that including：
Acquisition module, for obtains include devastated disaster achievement data and current relief goods distribute data exist
Interior Outliers Detection data set；
Module is normalized, for carrying out data normalization to the data in Outliers Detection data set；
Parameter setting module, for Outliers Detection parameter to be arranged；
Outliers Detection module, for according to Outliers Detection parameter by Outliers Detection data set map to metric space carry out from
Most possibly there is n devastated of relief goods unreasonable distribution as Outliers Detection result in group's detection, acquisition；
Goods and materials adjust module, and whether the relief goods quantity allotted for verifying n region is reasonable, if quantity allotted is reasonable
Disaster relief supplies quantity allotted is not adjusted then.
In one embodiment, which further includes：
Weight adjusts module, for implementing equalizing weight adjustment to normalized data, by disaster achievement data and rescue
Goods and materials distribution data are separately adjusted to angularly default weight.
In one embodiment, the data normalization for normalizing module carries out as follows：
Wherein, DIS (xi, xj) indicate i-th of data xiWith j-th of data xjDistance function, d indicate Outliers Detection number
According to the quantity of intensive data；
For the data of numerical attribute in Outliers Detection data set,
δ(xik, xjk)=(xik-xjk)2
xikWith xjkIndicate the numerical value after normalization；
For the data of nonumeric attribute in Outliers Detection data set,
δ(xik, xjk)=(xik-xjk)/max(x1k-x_k)
x_kIndicate k-th of attribute of any one data in Outliers Detection data set.
In one embodiment, Outliers Detection parameter includes the number of the quantity k and the maximum n data of degree of peeling off of arest neighbors
Measure n；
Outliers Detection module includes：
Computing unit, the k arest neighbors for calculating each data in Outliers Detection data set；
Computing unit is additionally operable to calculate the degree of peeling off of each data；Wherein, degree of peeling off indicates each data and the data pair
The sum of the distance for the k arest neighbors answered；
Sequencing unit, it is maximum for being ranked up degree of peeling off in acquisition Outliers Detection data set from big to small by degree of peeling off
N data；Wherein, most possibly there is n devastated of relief goods unreasonable distribution to the n data in correspondence respectively.
In one embodiment, goods and materials adjust module, also particularly useful for verify n region relief goods quantity allotted not
After rationally, then readjusted according to pre-set mode；
The system further includes：
Scheme output module, for exporting new disaster relief supplies allocation plan according to the result after adjustment.
The disaster assistance goods and materials method of adjustment and system of embodiment of the present invention, this method can balance Meteorological Disaster Indexes
The weight of data, current relief goods distribution two generic attribute of data, accelerates meteorological disaster relief goods and adjusts reaction speed, improve
The degree of automation, and can be compatible with different types of meteorological disaster using metric space algorithm.
The advantages of additional aspect of the present invention, will be set forth in part in the description, and will partly become from the following description
Obviously, or practice through the invention is recognized.
Description of the drawings
The above-mentioned and/or additional aspect and advantage of embodiments of the present invention are from combination following accompanying drawings to embodiment
It will be apparent and be readily appreciated that in description, wherein：
Fig. 1 is the flow diagram of the disaster assistance goods and materials method of adjustment of embodiment of the present invention；
Fig. 2 is the composition schematic diagram of the disaster assistance goods and materials adjustment system of embodiment of the present invention.
Specific implementation mode
Embodiments of the present invention are described below in detail, the example of embodiment is shown in the accompanying drawings, wherein identical or class
As label indicate same or similar element or element with the same or similar functions from beginning to end.Below with reference to attached
The embodiment of figure description is exemplary, and can only be used to explain embodiments of the present invention, and should not be understood as to the present invention
Embodiment limitation.
Referring to Fig. 1, Fig. 1 is the flow diagram of the disaster assistance goods and materials method of adjustment of embodiment of the present invention.
A kind of disaster assistance goods and materials method of adjustment proposed by the present invention, including：
Step 10, obtain including distributing data including the disaster achievement data of devastated and current relief goods from
Group's detection data collection.
Step 11, data normalization is carried out to the data in Outliers Detection data set.
Step 13, Outliers Detection parameter is set.
Step 14, Outliers Detection data set is mapped to by metric space according to Outliers Detection parameter and carries out Outliers Detection, obtained
N devastated for relief goods unreasonable distribution most possibly occur is obtained as Outliers Detection result.
Step 15, whether the relief goods quantity allotted for verifying n region is reasonable, does not adjust and rescues if rationally if quantity allotted
Calamity goods and materials quantity allotted.
As shown in Fig. 2, the present invention goes back while proposing a kind of disaster assistance goods and materials adjustment system, including：
Acquisition module, for obtains include devastated disaster achievement data and current relief goods distribute data exist
Interior Outliers Detection data set.
Module is normalized, for carrying out data normalization to the data in Outliers Detection data set.
Parameter setting module, for Outliers Detection parameter to be arranged.
Outliers Detection module, for according to Outliers Detection parameter by Outliers Detection data set map to metric space carry out from
Most possibly there is n devastated of relief goods unreasonable distribution as Outliers Detection result in group's detection, acquisition.
Goods and materials adjust module, and whether the relief goods quantity allotted for verifying n region is reasonable, if quantity allotted is reasonable
Disaster relief supplies quantity allotted is not adjusted then.
The disaster assistance goods and materials method of adjustment of the present invention can be adjusted system as each step by disaster assistance goods and materials
Action subject is implemented, and can also specifically be implemented as the action subject of each step by each module of system.That is, step
10 are implemented by acquisition module, and step 11 is implemented by normalization module, and step 13 is implemented by parameter setting module, step 14
Implemented by Outliers Detection module, step 15 adjusts module to implement by goods and materials.
In step 10, acquisition module first obtains Outliers Detection data set, i.e. the disaster achievement data of devastated and current
Relief goods distribution data these data.The mode of data acquisition can be manually entered system, can also be that system passes through
Corresponding data-interface obtains corresponding data by way of network crawl.
In step 11, normalization module carries out data normalization to the data in Outliers Detection data set.Data normalization
Purpose be to ensure that different dimensions using different dimensions or different number grade when, the data of each dimension can play justice
Effect weaken the negative of the horizontal relatively low index of numerical value to avoid prominent effect of the higher index of numerical value in comprehensive analysis
Face acts on.
Data normalization is divided into three kinds of Numeric Attributes, Categorical attributes and mixed type data situations：
For Numeric Attributes：Numeric type data refers to the data that one or more numerical attributes can be used to describe, such as
Coordinate (1,2,3) is three-dimensional numerical value type data.Numeric Attributes can be made using min-max standardized methods at normalization
Reason, maps data into 0~1 section.Concrete operations：By taking three-dimensional numerical value type attribute data as an example, it is assumed that three dimensional attributes point
It is not A, B, C, and sets minimum value and maximum value that minA and maxA is respectively attribute A, an original value of A is passed through into min-
Max standardization is mapped to the new value in section [0,1], and formula is：
New value=(original value-minimum value)/(maximum value-minimum value)
It, need not normalization if the maxima and minima of the attribute is equal.
A same to the operation of attribute B, C.
For Categorical attributes：Nonumeric type data refer to then that can not or be difficult to be described with one or more numerical attributes
Data, for being compatible with more data types.Categorical attributes are usually randomly selected with any data, and (acquiescence takes first
Data) the attribute, the attribute of itself and the other all data of entire data set is calculated into distance, to obtain maximum distance
Value.When subsequently calculating the distance between the attribute, as a result all divided by the value.
The case where for Numeric Attributes and Categorical attributes mixed type：Above two method for normalizing, which is combined, to be made
With.
Specifically, module progress data normalization is normalized in step 11 to carry out as follows：
Wherein, DIS (xi, xj) indicate i-th of data xiWith j-th of data xjDistance function, d indicate Outliers Detection number
According to the quantity of intensive data.
δ(xik, xjk) value have following manner：
For the data of numerical attribute in Outliers Detection data set,
δ(xik, xjk)=(xik-xjk)2
xikWith xjkIndicate the numerical value after normalization.
For the data of nonumeric attribute in Outliers Detection data set,
δ(xik, xjk)=(xik-xjk)/max(x1k-x_k)
x_kIndicate k-th of attribute of any one data in Outliers Detection data set.Wherein, the minus sign of non-data attribute
"-" indicates its distance metric method.Such as bit string data uses Hamming distances (English：Hamming distance) it is used as distance
Measure.Bit string data, the data being exactly made of 0 and 1, such as 10101 and 00110, their Hamming distances are exactly two
The different digit of a bit string data, totally three differences, Hamming distances are exactly 3 to the 1st, 4,5 of 10101 and 00110.
For example, a certain data set includes 4 data, each data include 3 attributes, i.e. attribute A, B, C, wherein A, B, D
For Numeric Attributes, C is Categorical attributes, and attribute A, B, C indicate that Meteorological Disaster Indexes data, attribute D indicate current
Relief goods distribute two class data of data.
4 data difference are as follows：
First data：(1,2, c1,10)
Second data：(3,0, c2,4)
Third data：(4,4, c3,6)
Fourth data：(5,4, c4,8)
It is assumed that nonumeric attribute C calculates function DIS () using pre-set distance, and there is DIS (c1, c2)=2, DIS
(c1, c3)=4, DIS (c1, c4)=6, DIS (c2, c3)=2, DIS (c2, c4)=4, DIS (c3, c4)=2.Knowable attributes C
The distance between maximum value maxC=6.
And maximum, the minimum value of attribute A are maxA=5 respectively, minA=1；Maximum, the minimum value of attribute B be respectively
MaxB=4, minB=0；Maximum, the minimum value of attribute D is maxD=10, minD=4 respectively.Attribute A, B of first data,
D is normalized to respectivelyI.e. 0,0.5,1；And attribute A, B, D of second data are normalized respectively
ForI.e. 0.5,0,0.
First data is at a distance from second data after normalization：
In order to obtain balance between Meteorological Disaster Indexes data, current relief goods distribution two class data of data, avoid
The influence of any type of data is excessively zoomed in or out, the present invention implements equalizing weight after carrying out range normalization to data
Adjustment.
Further, disaster assistance goods and materials method of adjustment of the invention further includes after step 11：
Step 12, equalizing weight adjustment is implemented to normalized data, distributes disaster achievement data and relief goods to number
According to being separately adjusted to angularly default weight.
Accordingly, disaster assistance goods and materials of the invention adjustment system further includes：
Weight adjusts module, for implementing equalizing weight adjustment to normalized data, by disaster achievement data and rescue
Goods and materials distribution data are separately adjusted to angularly default weight.
I.e. step 12 can adjust system by disaster assistance goods and materials and be executed as action subject, can also be adjusted by weight
Module is executed as action subject.
For example, weight adjustment module carries out equalizing weight adjustment in step 12, Meteorological Disaster Indexes data after adjustment are rescued
It helps goods and materials distribution data this two classes data and respectively accounts for 50% weight, i.e., default weight is 50%.Above-mentioned example distance is implemented balanced
Weight adjusts, then the weight of attribute D is 50% (i.e. 0.5), and the sum of the weight of attribute A, B, C are also 50% (i.e. 0.5), individually
Weight is 0.167 respectively.Then first data is at a distance from second data after equalizing weight adjustment：
In step 13, Outliers Detection parameter is arranged in parameter setting module.
Several important key nouns in the present invention are described below：
Metric space, also referred to as metric space.If S is the data acquisition system of limited non-empty, DIS be defined on S apart from letter
Number, and there is following three property：
Orthotropicity：For arbitrary x, y ∈ S, DIS (x, y) >=0, and
Symmetry：For arbitrary x, y ∈ S, DIS (x, y)=DIS (y, x)
Triangle inequality：For arbitrary x, y, z ∈ S, DIS (x, y)+DIS (y, z) >=DIS (x, z).
So metric space can be defined as two tuple (S, DIS).
In simple terms, as long as in a data set definition there is the distance function of above-mentioned property, the data set can map
To metric space.Such as Euclidean distance is defined on cube, just form metric space.
Outliers Detection, outlier are exactly only a few and the dramatically different data of mainstream data, Outliers Detection in mass data
It is exactly from mass data or data centralized detecting outlier.
Degree of peeling off, the present invention regard the sum of distance value of each object in data set and its k arest neighbors as degree of peeling off.
Outlier, the present invention sort according to degree of peeling off and obtain maximum n object from big to small, are exactly TOP n outliers.
Metric space Outliers Detection, the Outliers Detection carried out completely within the scope of metric space, i.e., either outlier is fixed
Justice or Outliers Detection algorithm, are based entirely on the distance between object information, do not use the other information in addition to distance.This
The benefit of kind method is that have very strong data type versatility.
The mode of parameter setting module setting Outliers Detection parameter can be that disaster assistance goods and materials adjustment system receives user
Input realize, can also be parameter setting module is arranged automatically.
In step 14, Outliers Detection module according to Outliers Detection parameter by Outliers Detection data set map to metric space into
Most possibly there is n devastated of relief goods unreasonable distribution as Outliers Detection result in row Outliers Detection, acquisition.
Specifically, Outliers Detection parameter includes the quantity n of the quantity k and the maximum n data of degree of peeling off of arest neighbors.Then walk
The process of Outliers Detection module progress Outliers Detection includes in rapid 14：
Step 141, k arest neighbors of each data in Outliers Detection data set is calculated.
Step 142, the degree of peeling off of each data is calculated；Wherein, degree of peeling off indicates that each data are k corresponding with the data
The sum of the distance of arest neighbors.
Step 143, it is ranked up from big to small by degree of peeling off and obtains the maximum n number of degree of peeling off in Outliers Detection data set
According to；Wherein, most possibly there is n devastated of relief goods unreasonable distribution to the n data in correspondence respectively.
Outliers Detection data set is mapped into metric space, range normalization is carried out to data and implements equalizing weight tune
It is whole, then Outliers Detection parameter is set.Calculate k arest neighbors of each data in Outliers Detection data set again, such as data x
K arest neighbors indicates that k number evidence minimum with its distance data x does not include data x itself.
Each data and the sum of the distance of its k arest neighbors are degree of peeling off, i.e., by obtaining each data and corresponding k
Then this k distance value addition calculation can be obtained degree of peeling off by the distance value of a arest neighbors.
The maximum n data of entire data set degree of peeling off by being ranked up from big to small, then can be being obtained to degree of peeling off,
Since each data correspond to the region that disaster occurs for reality in data set, so most have can for correspondence respectively for the n data
N devastated of relief goods unreasonable distribution can occur.
In step 15, whether the relief goods quantity allotted that goods and materials adjust n region of module verification is reasonable, if quantity allotted
It is reasonable then do not adjust disaster relief supplies quantity allotted.The mode of verification can adjust module input nucleus by goods and materials after manually verifying
It is real as a result, for example rationally then system does not adjust disaster relief supplies quantity allotted to quantity allotted.
Further, disaster assistance goods and materials method of adjustment further includes：
Step 16, after the relief goods quantity allotted in n region of verification is unreasonable, then according to pre-set mode weight
New adjustment.
Step 17, new disaster relief supplies allocation plan is exported according to the result after adjustment.
Accordingly, in disaster assistance goods and materials adjustment system, goods and materials adjust module, also particularly useful for rescuing for n region of verification
Help goods and materials quantity allotted it is unreasonable after, then readjusted according to pre-set mode.
Disaster assistance goods and materials adjust system：Scheme output module, for being exported newly according to the result after adjustment
Disaster relief supplies allocation plan.
I.e. step 16 and step 17 can adjust system by disaster assistance goods and materials and be executed as action executive agent, also may be used
It is executed with adjusting the module of system by disaster assistance goods and materials respectively, step 16 is executed by goods and materials adjustment module, and step 17 is by side
Case output module executes.
In step 16, goods and materials adjust module verify n region relief goods quantity allotted it is unreasonable after, then according to pre-
The mode being first arranged is readjusted.Pre-set mode can be according to national regulation《Disaster relief supplies distribution, which is provided, to be used
Management method》It redistributes.
In step 17, scheme output module exports new disaster relief supplies allocation plan, i.e., most possibly rescues n
The disaster relief supplies in the region of goods and materials unreasonable distribution are distributed, according to national regulation《Disaster relief supplies distribution, which is provided, uses Management Office
Method》It redistributes, then the result after redistributing is included that other distribute rational region entirety output by scheme output module,
New complete disaster relief supplies allocation plan is formed, can be accelerated meteorological disaster by improving the degree of automation and rescue object in this way
Money adjustment reaction speed.
In the present invention, although by taking meteorological disaster as an example, it is not limited to meteorological disaster, for other disaster assistance goods and materials
Adjustment, also belong to the part of protection scope of the present invention.I.e. present invention is suitably applied to meteorological disasters to rescue scene, also may be used
Rescue scene applied to other disasters.
Any process described otherwise above or method description are construed as in flow chart or herein, and expression includes
It is one or more for realizing specific logical function or process the step of executable instruction code module, segment or portion
Point, and the range of the preferred embodiment of the present invention includes other realization, wherein can not press shown or discuss suitable
Sequence, include according to involved function by it is basic simultaneously in the way of or in the opposite order, to execute function, this should be of the invention
Embodiment person of ordinary skill in the field understood.
Expression or logic and/or step described otherwise above herein in flow charts, for example, being considered use
In the order list for the executable instruction for realizing logic function, may be embodied in any computer-readable medium, for
Instruction execution system, device or equipment (system of such as computer based system including processing module or other can be from instruction
Execute system, device or equipment instruction fetch and the system that executes instruction) use, or combine these instruction execution systems, device or
Equipment and use.For the purpose of this specification, " computer-readable medium " can be it is any can include, store, communicating, propagating or
Transmission program uses for instruction execution system, device or equipment or in conjunction with these instruction execution systems, device or equipment
Device.The more specific example (non-exhaustive list) of computer-readable medium includes following：With one or more wiring
Electrical connection section (electronic device), portable computer diskette box (magnetic device), random access memory (RAM), read-only memory
(ROM), erasable edit read-only storage (EPROM or flash memory), fiber device and portable optic disk is read-only deposits
Reservoir (CDROM).In addition, computer-readable medium can even is that the paper that can print described program on it or other are suitable
Medium, because can be for example by carrying out optical scanner to paper or other media, then into edlin, interpretation or when necessary with it
His suitable method is handled electronically to obtain described program, is then stored in computer storage.
It should be appreciated that each section of embodiments of the present invention can be with hardware, software, firmware or combination thereof come real
It is existing.In the above-described embodiment, multiple steps or method can use storage in memory and by suitable instruction execution system
The software or firmware of execution is realized.For example, if realized with hardware, in another embodiment, ability can be used
Any one of following technology or their combination well known to domain are realized：With for realizing logic function to data-signal
The discrete logic of logic gates, the application-specific integrated circuit with suitable combinational logic gate circuit, programmable gate array
(PGA), field programmable gate array (FPGA) etc..
Those skilled in the art are appreciated that realize all or part of step that above-described embodiment method carries
Suddenly it is that relevant hardware can be instructed to complete by program, the program can be stored in a kind of computer-readable storage medium
In matter, which includes the steps that one or a combination set of embodiment of the method when being executed.
In addition, each functional unit in various embodiments of the present invention can be integrated in a processing module, also may be used
To be that each unit physically exists alone, can also two or more units be integrated in a module.It is above-mentioned integrated
The form that hardware had both may be used in module is realized, can also be realized in the form of software function module.The integrated module
If being realized in the form of software function module and when sold or used as an independent product, a calculating can also be stored in
In machine read/write memory medium.
Storage medium mentioned above can be read-only memory, disk or CD etc..
Although the embodiments of the present invention has been shown and described above, it is to be understood that above-described embodiment is example
Property, it is not considered as limiting the invention, those skilled in the art within the scope of the invention can be to above-mentioned
Embodiment is changed, changes, replacing and modification.
Claims (10)
1. a kind of disaster assistance goods and materials method of adjustment, which is characterized in that including：
Step 10, the inspection that peels off including the disaster achievement data of devastated and current relief goods distribution data is obtained
Measured data collection；
Step 11, data normalization is carried out to the data in Outliers Detection data set；
Step 13, Outliers Detection parameter is set；
Step 14, Outliers Detection data set is mapped to by metric space according to Outliers Detection parameter and carries out Outliers Detection, obtained most
It is possible that there is n devastated of relief goods unreasonable distribution as Outliers Detection result；
Step 15, whether the relief goods quantity allotted for verifying n region is reasonable, and disaster relief object is not adjusted if rationally if quantity allotted
Provide quantity allotted.
2. disaster assistance goods and materials method of adjustment as described in claim 1, which is characterized in that further include after step 11：
Step 12, equalizing weight adjustment is implemented to normalized data, by disaster achievement data and relief goods distribution data point
It does not adjust to default weight.
3. disaster assistance goods and materials method of adjustment as claimed in claim 1 or 2, which is characterized in that the data normalization of step 11 is pressed
Following formula carries out：
Wherein, DIS (xi, xj) indicate i-th of data xiWith j-th of data xjDistance function, d indicate Outliers Detection data set in
The quantity of data；
For the data of numerical attribute in Outliers Detection data set,
δ(xik, xjk)=(xik-xjk)2
xikWith xjkThe numerical value after normalization is indicated respectively；
For the data of nonumeric attribute in Outliers Detection data set,
δ(xik, xjk)=(xik-xjk)/max(x1k-x_k)
x_kIndicate k-th of attribute of any one data in Outliers Detection data set.
4. disaster assistance goods and materials method of adjustment as claimed in claim 3, which is characterized in that Outliers Detection parameter includes arest neighbors
The quantity n of quantity k and the maximum n data of degree of peeling off；
Outliers Detection includes in step 14：
Calculate k arest neighbors of each data in Outliers Detection data set；
Calculate the degree of peeling off of each data；Wherein, degree of peeling off indicates each data with the data at a distance from corresponding k arest neighbors
The sum of；
It is ranked up from big to small by degree of peeling off and obtains the maximum n data of degree of peeling off in Outliers Detection data set；Wherein, the n
Most possibly there is n devastated of relief goods unreasonable distribution to a data in correspondence respectively.
5. disaster assistance goods and materials method of adjustment as described in claim 1, which is characterized in that this method further includes：
Step 16, it after the relief goods quantity allotted in n region of verification is unreasonable, is then adjusted again according to pre-set mode
It is whole；
Step 17, new disaster relief supplies allocation plan is exported according to the result after adjustment.
6. a kind of disaster assistance goods and materials adjust system, which is characterized in that including：
Acquisition module, for obtaining including the disaster achievement data of devastated and current relief goods distribution data
Outliers Detection data set；
Module is normalized, for carrying out data normalization to the data in Outliers Detection data set；
Parameter setting module, for Outliers Detection parameter to be arranged；
Outliers Detection module carries out the inspection that peels off for Outliers Detection data set to be mapped to metric space according to Outliers Detection parameter
It surveys, acquisition most possibly n devastated of relief goods unreasonable distribution occurs as Outliers Detection result；
Goods and materials adjust module, whether the relief goods quantity allotted for verifying n region reasonable, if quantity allotted rationally if not
Adjust disaster relief supplies quantity allotted.
7. disaster assistance goods and materials as claimed in claim 6 adjust system, which is characterized in that the system further includes：
Weight adjusts module, for implementing equalizing weight adjustment to normalized data, by disaster achievement data and relief goods
Distribution data are separately adjusted to angularly default weight.
8. disaster assistance goods and materials adjust system as claimed in claims 6 or 7, which is characterized in that normalize the data normalizing of module
Change carries out as follows：
Wherein, DIS (xi, xj) indicate i-th of data xiWith j-th of data xjDistance function, d indicate Outliers Detection data set in
The quantity of data；
For the data of numerical attribute in Outliers Detection data set,
δ(xik, xjk)=(xik-xjk)2
xikWith xjkIndicate the numerical value after normalization；
For the data of nonumeric attribute in Outliers Detection data set,
δ(xik, xjk)=(xik-xjk)/max(x1k-x_k)
x_kIndicate k-th of attribute of any one data in Outliers Detection data set.
9. disaster assistance goods and materials as claimed in claim 8 adjust system, which is characterized in that Outliers Detection parameter includes arest neighbors
The quantity n of quantity k and the maximum n data of degree of peeling off；
Outliers Detection module includes：
Computing unit, the k arest neighbors for calculating each data in Outliers Detection data set；
Computing unit is additionally operable to calculate the degree of peeling off of each data；Wherein, degree of peeling off indicates each data k corresponding with the data
The sum of the distance of a arest neighbors；
Sequencing unit obtains in Outliers Detection data set the maximum n of degree of peeling off for being ranked up from big to small by degree of peeling off
Data；Wherein, most possibly there is n devastated of relief goods unreasonable distribution to the n data in correspondence respectively.
10. disaster assistance goods and materials as claimed in claim 6 adjust system, which is characterized in that goods and materials adjust module, also particularly useful for
Verify n region relief goods quantity allotted it is unreasonable after, then readjusted according to pre-set mode；
The system further includes：
Scheme output module, for exporting new disaster relief supplies allocation plan according to the result after adjustment.
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