CN109615118A - Based on big data hazards control Informatization Service integrated control system and method - Google Patents
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Abstract
The invention belongs to hazards control technical fields, one kind is disclosed based on big data hazards control Informatization Service integrated control system and method, the big data hazards control Informatization Service integrated control system that is based on includes: rainfall monitoring module, mud position monitoring modular, vibration monitoring module, central control module, wireless communication module, Cloud Server, smart phone, disaster identification module, assessment of risks module, alarm module, display module.The present invention passes through disaster identification module for 3S technology, that is, GPS (global positioning system), RS (remote sensing), GIS (GIS-Geographic Information System) three combination, geological disaster generation area is positioned, is analyzed, final scale, the extent of injury for realizing identification geological disaster；Meanwhile it can play the role of preventing in advance to geological disaster by assessment of risks module, and then loss caused by geological disaster is minimized, the result of Risk Evaluation of Geological Hazard reliability with higher.
Description
Technical field
The invention belongs to hazards control technical fields, more particularly to one kind to be based on big data hazards control information
Change Services Integration control system and method.
Background technique
Geological disaster refers in the landslide evolution process of the earth, the disaster geology thing formed by various geologic processes
Part.The changes in distribution rule of geological disaster over time and space, is not only limited by natural environment, but also related with mankind's activity, past
Toward the result for being the mankind and nature interaction.Using geology motor activity or geological environment anomalous variation as main reason from
Right disaster.Earth internally-powered, outer power or artificial geology power effect under, the earth be abnormal energy release, the motion of matter,
Rock And Soil deformation displacement and environmental abnormality variation etc., endanger human life's property, life and economic activity or the destruction mankind rely
With the phenomenon that the resource of the survival and development, environment or process.Bad geological phenomenon is generally termed geological disaster, refers to nature geology
Deteriorate geological environment caused by effect and mankind's activity, reduce environmental quality, directly or indirectly endangers human security, and give society
The geologic event that can be caused damages with economic construction.Geological disaster refers to, is formed under the action of nature or human factor,
The geologic process (phenomenon) that human life's property, environment are damaged and lost.As avalanche, landslide, mud-rock flow, ground fissure,
Surface subsidence, surface collapse, rock burst, tunnel gushing water, prominent mud, prominent gas, spontaneous combustion of coal seam, Loess Collapsibility, ground expansion, sand liquid
Change, soil freeze thawing, soil erosion, desertification and bogginess, the salinization of soil and earthquake, volcano, underground heat evil etc..So
And it is existing cannot comprehensively, fast investigation understand Situation of geological disaster；Meanwhile the existing assessment to geological disaster is based on to geology
The impact factor that disaster is formed carries out grid cell superposition, and ignoring the formation of different geologic hazard types and failure mechanism has
Different motion features, obtained evaluation result tend not to directly apply in large-scale hazard assessment management.
In conclusion problem of the existing technology is:
(1) it is existing cannot comprehensively, fast investigation understand Situation of geological disaster；Meanwhile the existing assessment base to geological disaster
Grid cell superposition is carried out in the impact factor formed to geological disaster, and ignores the formation of different geologic hazard types and breaks
Bad mechanism has different motion features, and obtained evaluation result tends not to directly apply to large-scale hazard assessment pipe
In reason.
(2) during shock sensor real-time monitoring the earth vibration data information, shock sensor is easy to be interfered,
Traditional algorithm is used simultaneously, and the speed and stability of detection are relatively low.
(3) during precipitation rain fall sensor real-time monitoring rainfall product data information, using current algorithm, rain cannot be made
Quantity sensor, which has, preferably to be output and input, and causes the precision of measurement low.
(4) it during the altitude information information of thickness transducer real-time monitoring hillside bottom of trench sludge blanket, is easy by temperature
The influence of degree, causes sensitivity coefficient to reduce, to increase the error of measurement.
Summary of the invention
In view of the problems of the existing technology, the present invention provides one kind is taken based on the informationization of big data hazards control
Business integrated control system and method.
The invention is realized in this way a kind of be based on big data hazards control Informatization Service integrated control method,
It is described to include: based on big data hazards control Informatization Service integrated control method
The first step acquires rainfall product data information, the altitude information information and the earth vibration data of hillside bottom of trench sludge blanket
Information；
Second step analyzes above-mentioned data-signal, assessment of risks is carried out, when assessment of risks result reaches certain grade
Not, it is identified as that disaster can occur；
Third step is identified as that disaster can occur, will send information to Cloud Server and smart phone, provides phase for people
It should determine as a result, and being alarmed by alarm；
4th step, finally by the data and corresponding judgement result of display screen display detection.
Further, by precipitation rain fall sensor real-time monitoring rainfall product data information, using based on least square supporting vector
The Compensation for nonlinear dynamic system of transducer algorithm of machine, includes the following steps；
Step 1 carries out dynamic test to sensor, measures sensor input signal u (t) and output response y (t)；Simultaneously
It establishes ideal (expectation) response model and inputs signal u (t), obtain ideal response u ' (t)；
Step 2, u ' (t)=ωTIn η (t) formula: for mid-module parameter:
ω=[- a '1... ,-a 'n, β10..., β1m..., βp0..., βpm]T；
Sample data:
η (t)=[u ' (t-1) ..., u ' (t-n), y (t) ..., y (t-m) ..., yp(t) ..., yp(t-m)]T；
Desired compensation exports u ' (t), the output signal y (t) of actual measurement, form tissue training sample set { η (t), u
(t) }, and formula is substituted into:
ω=ηTα=ηT|ηηT+γ-1I|-1U；
It finds out mid-module parameter X and finds out mid-module parameter ω；
Step 3, referring to formula ΘTB=ΘTA or BTΘ=ATΘ；A=[1, a ' in formula1..., a 'n]T, B=[b '0, b
′1..., b 'm]T；With formula [b '1 b′2…b′m]=CBT；
C=[c ' in formula1..., c 'p]T；According to intermediate parameters vector ω, corresponding element structural matrix Φ, A, and generation
Enter formulaSeek the parameter of compensator nonlinear static gain to
Measure C and linear dynamic link parameter vector B；
Step 4 provides the mathematical solution of compensator model by non-linear compensator parameter vector A, B and the C identified
Analyse expression formula, nonlinear dynamic compensation device construction complete.
Further, by the altitude information information of thickness transducer real-time monitoring hillside bottom of trench sludge blanket, using population
Optimization neural network algorithm, detailed process are as follows:
Particle swarm optimization algorithm randomly initializes a particle group, the feature fitness of each particle first
Three value, position and speed index expressions, and optimal solution is found by iteration；
It is X=(X by the molecular population of n grain in the search space of D dimension1, X2..., Xn), each particle
I indicates a D dimensional vector, Xi=[xi1, xi2... xiD]T, the particle is represented in the position of D dimension search space, according to objective function
The shapes such as the corresponding fitness value objective function available standards of the position Xi for each particle being calculated are poor, mean square deviation or variance
Formula indicates that the speed of i-th of particle is Vi=[Vi1, Vi2..., ViD]T, individual extreme value is Pi=[Pi1, Pi2..., PiD]TKind
The global extremum of race is Pg=[Pg1, Pg2..., PgD]T；
Particle is as follows by the formula that individual extreme value and group's extreme value update itself speed and position:
In formula, ω is inertia weight；D=1,2 ..., D；I=1,2 ..., n；K is the present age
The number of iterations VidFor the speed of particle；c1And c2It for acceleration factor, and is nonnegative number；r1And r2To be distributed in
Random number between [0,1]；
Each time in iterative process, the adaptive value size of each particle is determined by objective function, particle optimal locationWith
Group's optimal locationIt is determined by fitness value, itself speed and position is updated by individual extreme value and group's extreme value according to particle
The formula set adjusts speed and the position of each particle, and when the position searched meets default minimum adaptive value or iteration is secondary
When number reaches the upper limit, then stop iterative process.
Another object of the present invention is to provide big data hazards control Informatization Service is based on described in a kind of implementation
Integrated control method based on big data hazards control Informatization Service integrated control system, it is described to be based on big data geology
Diaster prevention and control Informatization Service integrated control system includes:
Rainfall monitoring module, connect with central control module, for passing through precipitation rain fall sensor real-time monitoring rainfall product data
Information；
Mud position monitoring modular, connect with central control module, for dirty by thickness transducer real-time monitoring hillside bottom of trench
The altitude information information of mud layer；
Vibration monitoring module, connect with central control module, for passing through vibrating sensor real-time monitoring the earth vibration number
It is believed that breath；
Central control module, with rainfall monitoring module, mud position monitoring modular, vibration monitoring module, wireless communication module, calamity
Evil identification module, assessment of risks module, alarm module, display module connection are normal for controlling modules by single-chip microcontroller
Work；
Wireless communication module is connect, for passing through wireless transmitter with central control module, Cloud Server, smart phone
It sends the data of monitoring to and is handled with server centered big data resource, and be sent to smart phone and obtained in real time
Monitoring data；
Disaster identification module, connect with central control module, for being identified by data processing software according to satellite image
Geological disaster region；
Assessment of risks module, connect with central control module, for passing through appraisal procedure according to the data of monitoring to geology
Disasters danger assessment；
Alarm module is connect with central control module, for by alarm according to monitoring that it is timely that abnormal data carries out
Alarm；
Display module is connect with central control module, for the rain by display display control program interface and monitoring
Amount, mud position, vibration data information.
Another object of the present invention is to provide big data hazards control Informatization Service is based on described in a kind of application
The information data processing terminal of integrated control method.
Advantages of the present invention and good effect are as follows: the present invention passes through disaster identification module for 3S technology, that is, GPS (global location
System), the combination of RS (remote sensing), GIS (GIS-Geographic Information System) three, geological disaster generation area is positioned, is analyzed, most
Scale, the extent of injury for realizing identification geological disaster eventually, be it is a kind of it is convenient, fast, cost is relatively low and effective disaster identification and
The mode of judgement；Meanwhile it being adopted remote sensing techniques by assessment of risks module and can automatically extract a variety of geological disaster factors, and is right
The geological disaster factor of extraction carries out quantitative statistics analysis, accurately and efficiently realizes the assessment function to geological hazard dangerous
Can, it can play the role of preventing in advance to geological disaster, and then loss caused by geological disaster is minimized, geological disaster
The result of risk assessment reliability with higher, is conducive to the Geological Selection of Route of Construction of Highway Traffic.
It is right during vibration monitoring module is by shock sensor real-time monitoring the earth vibration data information in the present invention
Seismic wave is identified, in order to improve the anti-interference ability of shock sensor, the speed and stability of detection is improved, using improvement
High-order zero passage analysis and detection algorithm.
During rainfall monitoring modular passes through precipitation rain fall sensor real-time monitoring rainfall product data information in the present invention, in order to
There is precipitation rain fall sensor preferably to output and input, improve anti-interference ability, improve measurement accuracy, using based on least square branch
Hold the Compensation for nonlinear dynamic system of transducer algorithm of vector machine.Mud position monitoring modular passes through thickness transducer real-time monitoring in the present invention
During the altitude information information of hillside bottom of trench sludge blanket, thickness transducer is easy to be affected by temperature, and leads to sensitive system
Number reduces, and increases the error of measurement, in order to avoid the influence of temperature, using particle group optimizing neural network algorithm.
Detailed description of the invention
Fig. 1 is provided in an embodiment of the present invention based on big data hazards control Informatization Service integrated control method stream
Cheng Tu.
Fig. 2 is provided in an embodiment of the present invention based on big data hazards control Informatization Service integrated control system knot
Structure schematic diagram；
In figure: 1, rainfall monitoring module；2, mud position monitoring modular；3, vibration monitoring module；4, central control module；5, nothing
Line communication module；6, Cloud Server；7, smart phone；8, disaster identification module；9, assessment of risks module；10, alarm module；
11, display module.
Specific embodiment
In order to further understand the content, features and effects of the present invention, the following examples are hereby given, and cooperate attached drawing
Detailed description are as follows.
Structure of the invention is explained in detail with reference to the accompanying drawing.
As shown in Figure 1, provided in an embodiment of the present invention be based on the Informatization Service integrated control of big data hazards control
Method the following steps are included:
S101: acquisition rainfall product data information, the altitude information information of hillside bottom of trench sludge blanket and the earth vibration number first
It is believed that breath；
S102: above-mentioned data-signal is analyzed, and assessment of risks is carried out, when assessment of risks result reaches certain grade
Not, it is identified as that disaster can occur；
S103: it is identified as that disaster can occur, will send information to Cloud Server and smart phone, provided accordingly for people
Determine as a result, and being alarmed by alarm；
S104: finally by the data and corresponding judgement result of display screen display detection.
As shown in Fig. 2, provided in an embodiment of the present invention be based on the Informatization Service integrated control of big data hazards control
System includes: rainfall monitoring module 1, mud position monitoring modular 2, vibration monitoring module 3, central control module 4, wireless communication module
5, Cloud Server 6, smart phone 7, disaster identification module 8, assessment of risks module 9, alarm module 10, display module 11.
Rainfall monitoring module 1 is connect with central control module 4, for passing through precipitation rain fall sensor real-time monitoring rainfall number
It is believed that breath；
Mud position monitoring modular 2, connect with central control module 4, for passing through thickness transducer real-time monitoring hillside bottom of trench
The altitude information information of sludge blanket；
Vibration monitoring module 3 is connect with central control module 4, for being shaken by vibrating sensor real-time monitoring the earth
Data information；
Central control module 4, with rainfall monitoring module 1, mud position monitoring modular 2, vibration monitoring module 3, radio communication mold
Block 5, disaster identification module 8, assessment of risks module 9, alarm module 10, display module 11 connect, for being controlled by single-chip microcontroller
Modules work normally；
Wireless communication module 5 is connect with central control module 4, Cloud Server 6, smart phone 7, for by wirelessly sending out
Emitter sends the data of monitoring to concentrates big data resource to handle with server 6, and is sent to smart phone 7 and carries out reality
When obtain monitoring data；
Disaster identification module 8 is connect with central control module 4, for being known by data processing software according to satellite image
Other geological disaster region；
Assessment of risks module 9 is connect with central control module 4, for by appraisal procedure according to the data of monitoring over the ground
The assessment of matter disasters danger；
Alarm module 10 is connect with central control module 4, for by alarm according to monitor abnormal data carry out and
Alarm；
Display module 11 is connect with central control module 4, for passing through display display control program interface and monitoring
Rainfall, mud position, vibration data information.
During the rainfall monitoring module 1 passes through precipitation rain fall sensor real-time monitoring rainfall product data information, in order to make
Precipitation rain fall sensor, which has, preferably to be output and input, and anti-interference ability is improved, and improves measurement accuracy, is supported using based on least square
The Compensation for nonlinear dynamic system of transducer algorithm of vector machine, includes the following steps；
Step 1 carries out dynamic test to sensor, measures sensor input signal u (t) and output response y (t)；Together
Shi Jianli ideal (expectation) response model simultaneously inputs signal u (t), obtains ideal response u ' (t)；
Step 2, u ' (t)=ωTIn η (t) formula: for mid-module parameter
A ω=[- a '1... ,-a 'n, β10..., β1m, βp0..., βpm]T；
Sample data
η (t)=[u ' (t-1) ..., u ' (t-n), y (t) ..., y (t-m) ..., yp(t) ..., yp(t-m)]T；
Desired compensation exports u ' (t), the output signal y (t) of actual measurement, form tissue training sample set { η (t), u
(t) }, and formula is substituted into
ω=ηTα=ηT|ηηT+γ-1I|-1U；
It finds out mid-module parameter X and finds out mid-module parameter ω；
Step 3, referring to formula ΘTB=ΘTA or BTΘ=ATΘ；A=[1, a ' 1 ..., a ' in formulan]T, B=[b '0, b
′1..., b 'm]T；With formula [b '1 b′2 ... b′m]=CBT；
C=[c ' in formula1..., c 'p]T；According to intermediate parameters vector ω, corresponding element structural matrix Φ, A, and generation
Enter formula seek the parameter of compensator nonlinear static gain to
Measure C and linear dynamic link parameter vector B；
Step 4 provides the mathematical solution of compensator model by non-linear compensator parameter vector A, B and the C identified
Analyse expression formula, nonlinear dynamic compensation device construction complete.
Mud position monitoring modular 2 passes through the altitude information information of thickness transducer real-time monitoring hillside bottom of trench sludge blanket
In the process, thickness transducer is easy to be affected by temperature, and sensitivity coefficient is caused to reduce, thus increase the error of measurement, in order to
The influence for avoiding temperature, using particle group optimizing neural network algorithm, detailed process are as follows:
Particle swarm optimization algorithm randomly initializes a particle group, the feature fitness of each particle first
Three value, position and speed index expressions, and optimal solution is found by iteration；
It is assumed that being X=(X by the molecular population of n grain in the search space of D dimension1, X2..., Xn), it is each
A particle i indicates a D dimensional vector, Xi=[xi1, xi2..., xiD]T, the position that the particle ties up search space in D is represented, according to
The position X for each particle that objective function is calculatediCorresponding fitness value objective function available standards are poor, mean square deviation or
The forms such as variance indicate that the speed of i-th of particle is Vi=[Vi1, Vi2..., ViD]T, individual extreme value is Pi=[Pi1,
Pi2..., PiD]TThe global extremum of race is Pg=[Pg1, Pg2..., PgD]T；
Particle is as follows by the formula that individual extreme value and group's extreme value update itself speed and position:
In formula, ω is inertia weight；D=1,2 ..., D；I=1,2 ..., n；K is the present age
The number of iterations VidFor the speed of particle；c1And c2It for acceleration factor, and is nonnegative number；r1And r2To be distributed in
Random number between [0,1]；
Each time in iterative process, the adaptive value size of each particle is determined by objective function, particle optimal locationWith
Group's optimal locationIt is determined by fitness value, itself speed is then updated by individual extreme value and group's extreme value according to particle
Speed and the position that each particle is adjusted with the formula of position, when the position searched meets default minimum adaptive value or repeatedly
When generation number reaches the upper limit, then stop iterative process.
During the vibration monitoring module is by shock sensor real-time monitoring the earth vibration data information, to earthquake
Wave is identified, in order to improve the anti-interference ability of shock sensor, the speed and stability of detection is improved, using improved height
The analysis of rank zero passage and detection algorithm, specifically include following steps；
Step 1 meets threshold value firstly, being divided into signal according to zero crossing with common zero passage analysis method after going mean value
Length etc. wicket；
Step 2 calculates the Zero-crossing Number that each wicket improves, according to the Zero-crossing Number and basis of each wicket
The size relation of threshold value set by ring mirror noise is judged, if window Zero-crossing Number is greater than set threshold value, is shown at this
Without echo signal in the period of a window；It is opposite then indicate target appearance；
Step 3 is merged, to seismic signal, at two echo signal windows for successively having signal to generate
Reason, since the time interval between two each adjacent seismic signals is about 0.5s, as long as therefore if occurring twice in 1.5s
Signal, then report has target appearance always in this 1.5s；If only occurring the twinkling signal that a length is less than 0.3s in 1.5s,
It is considered that false-alarm, no target occur；If occurring signal always in 1.5s or occurring signal always in 0.5, also report has
Target occurs.
8 recognition methods of disaster identification module provided by the invention is as follows:
(1) according to historical disaster data and meteorological status, Primary Location is carried out to geological disaster region；
(2) according to the disaster position of Primary Location, the satellite image data of position is obtained；
(3) Computer Automatic Recognition is carried out to the geology generation area in satellite image, extracts the geological province of automatic identification
Domain；
(4) according to the position of the geologic province of automatic identification, the dem data of position is obtained；
(5) satellite image, dem data are carried out image co-registration, and carries out image enhancement, generate the 3D with elevation information
Landform image；
(6) it is based on 3D landform image, artificial correction is carried out to the geologic province of automatic identification；
(7) according to revised muddy ground matter identification region, geological disaster area image is drawn, and combines other data numbers
According to a possibility that judging disaster further occurrence, scale and resolution.
Step (1) provided by the invention carries out just mud-stone flow disaster region according to historical disaster data and meteorological status
Step positioning, specifically includes: according to data information, expert easily sends out geological disaster region by experience and carries out preliminary pre- measurement
Position carries out Primary Location to disaster region alternatively, technical staff, which carries GPS device, goes to geological-hazard-prone area area.
Step (2) provided by the invention, the satellite image data of acquisition are the TM image comprising 7 wave bands.
Step (3) provided by the invention, in satellite image mud-rock flow generation area carry out Computer Automatic Recognition it
Before, it further include that image preprocessing step is carried out to satellite image, described image pretreatment includes: geometric correction, multiband number
Synthesis, image mosaic.
9 appraisal procedure of assessment of risks module provided by the invention is as follows:
1) it is based on high resolution ratio satellite remote-sensing technology, establishes several zone digit ground models (DEM), meanwhile, if generating
The high-resolution orthography (DOM) in dry region, the remote sensing information data of record storage different zones simultaneously extract each region
The geological disaster factor；
2) quantitative statistics analysis is carried out to the geological disaster factor in step 1)；
3) two different data processing methods, including quantization are taken for the analysis of quantitative statistics described in step 2)
The quantitative expression to geological hazard dangerous is realized in processing and qualitative processing.
In step 1) provided by the invention, the method for extracting the geological disaster factor has the GIS based on DEM to analyze and based on shadow
The geolovic remote sensing of picture interprets.
GIS analytical procedure provided by the invention based on DEM is as follows:
Firstly, establishing ARCGIS platform and evaluation index system；
Then, grid is established using the CreateFishnet on ARCGIS platform；It recycles on ARCGIS platform
Intersect tool is superimposed each geological disaster factor graph dative net, i.e., so that the geological disaster factor and grid are established and closed
System.
The above is only the preferred embodiments of the present invention, and is not intended to limit the present invention in any form,
Any simple modification made to the above embodiment according to the technical essence of the invention, equivalent variations and modification, belong to
In the range of technical solution of the present invention.
Claims (5)
1. one kind is based on big data hazards control Informatization Service integrated control method, which is characterized in that described based on big
Data hazards control Informatization Service integrated control method includes:
The first step, acquisition rainfall product data information, the altitude information information of hillside bottom of trench sludge blanket and the earth vibration data information；
Second step analyzes above-mentioned data-signal, carries out assessment of risks, when assessment of risks result reaches certain rank,
It is identified as that disaster can occur；
Third step is identified as that disaster can occur, will send information to Cloud Server and smart phone, provides for people and accordingly sentence
Determine as a result, and being alarmed by alarm；
4th step, finally by the data and corresponding judgement result of display screen display detection.
2. being based on big data hazards control Informatization Service integrated control method as described in claim 1, feature exists
In non-using the sensor based on least square method supporting vector machine by precipitation rain fall sensor real-time monitoring rainfall product data information
Linear dynamic compensation algorithm, includes the following steps；
Step 1 carries out dynamic test to sensor, measures sensor input signal u (t) and output response y (t)；It establishes simultaneously
Ideal (expectation) response model simultaneously inputs signal u (t), obtains ideal response u ' (t)；
Step 2, u ' (t)=ωTIn η (t) formula: for mid-module parameter:
ω=[- a '1... ,-a 'n, β10..., β1m..., βp0..., βpm]T；
Sample data:
η (t)=[u ' (t-1) ..., u ' (t-n), y (t) ..., y (t-m) ..., yp(t) ..., yp(t-m)]T；
Desired compensation exports u ' (t), the output signal y (t) of actual measurement, form tissue training sample set { η (t), u (t) }, and
Substituted into formula:
ω=ηTα=ηT|ηηT+γ-1I|-1U；
It finds out mid-module parameter X and finds out mid-module parameter ω；
Step 3, referring to formula ΘTB=ΘTA or BTΘ=ATΘ；A=[1, a ' in formula1..., a 'n]T, B=[b '0, b '1...,
b′m]T；With formula [b '1 b′2 ... b′m]=CBT；
C=[c ' in formula1..., c 'p]T；According to intermediate parameters vector ω, corresponding element structural matrix Φ, A, and substitute into formulaSeek compensator nonlinear static gain parameter vector C and
Linear dynamic link parameter vector B；
Step 4 provides the mathematical analysis table of compensator model by non-linear compensator parameter vector A, B and the C identified
Up to formula, nonlinear dynamic compensation device construction complete.
3. being based on big data hazards control Informatization Service integrated control method as described in claim 1, feature exists
In by the altitude information information of thickness transducer real-time monitoring hillside bottom of trench sludge blanket, using particle group optimizing neural network
Algorithm, detailed process are as follows:
Particle swarm optimization algorithm randomly initializes a particle group, the feature fitness value of each particle, position first
Set with three index expressions of speed, and optimal solution is found by iteration；
It is X=(X by the molecular population of n grain in the search space of D dimension1, X2..., Xn), each particle i table
Show a D dimensional vector, Xi=[xi1, xi2..., xiD]T, the particle is represented in the position of D dimension search space, according to objective function meter
The position X of each obtained particleiThe forms such as corresponding fitness value objective function available standards are poor, mean square deviation or variance
It indicates, the speed of i-th of particle is Vi=[Vi1, Vi2..., ViD]T, individual extreme value is Pi=[Pi1, Pi2..., PiD]TRace
Global extremum be Pg=[Pg1, Pg2..., PgD]T；
Particle is as follows by the formula that individual extreme value and group's extreme value update itself speed and position:
In formula, ω is inertia weight；D=1,2 ..., D；I=1,2 ..., n；K is the present age
The number of iterations VidFor the speed of particle；c1And c2It for acceleration factor, and is nonnegative number；r1And r2To be distributed in [0,1]
Between random number；
Each time in iterative process, the adaptive value size of each particle is determined by objective function, particle optimal locationAnd group
Optimal locationIt is determined by fitness value, itself speed and position is updated by individual extreme value and group's extreme value according to particle
Formula adjusts speed and the position of each particle, and when the position searched meets default minimum adaptive value or the number of iterations reaches
When to the upper limit, then stop iterative process.
4. it is a kind of implement claim 1 described in based on big data hazards control Informatization Service integrated control method based on
Big data hazards control Informatization Service integrated control system, which is characterized in that described anti-based on big data geological disaster
Controlling Informatization Service integrated control system includes:
Rainfall monitoring module, connect with central control module, for passing through precipitation rain fall sensor real-time monitoring rainfall product data information；
Mud position monitoring modular, connect with central control module, for passing through thickness transducer real-time monitoring hillside bottom of trench sludge blanket
Altitude information information；
Vibration monitoring module, connect with central control module, for being believed by vibrating sensor real-time monitoring the earth vibration data
Breath；
Central control module is known with rainfall monitoring module, mud position monitoring modular, vibration monitoring module, wireless communication module, disaster
Other module, assessment of risks module, alarm module, display module connection, work normally for controlling modules by single-chip microcontroller；
Wireless communication module is connect with central control module, Cloud Server, smart phone, for that will be supervised by wireless transmitter
The data of survey are sent to be handled with server centered big data resource, and is sent to smart phone and is carried out obtaining monitoring in real time
Data；
Disaster identification module, connect with central control module, for identifying geology according to satellite image by data processing software
Disaster region；
Assessment of risks module, connect with central control module, for passing through appraisal procedure according to the data of monitoring to geological disaster
Risk assessment；
Alarm module is connect with central control module, for by alarm according to monitor abnormal data carry out and alarm；
Display module is connect with central control module, for rainfall, the mud by display display control program interface and monitoring
Position, vibration data information.
5. based on the integrated control of big data hazards control Informatization Service described in a kind of application claims 1 to 3 any one
The information data processing terminal of method processed.
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