CN106203712A - Optimal Decision-making guide systems based on big data - Google Patents
Optimal Decision-making guide systems based on big data Download PDFInfo
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- CN106203712A CN106203712A CN201610554304.1A CN201610554304A CN106203712A CN 106203712 A CN106203712 A CN 106203712A CN 201610554304 A CN201610554304 A CN 201610554304A CN 106203712 A CN106203712 A CN 106203712A
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- 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
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
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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
- G06Q50/20—Education
- G06Q50/205—Education administration or guidance
Abstract
Present invention Optimal Decision-making guide based on big data system includes curricula-variable MIM message input module；Assembled classification module；Arrange an order according to class and grade into a class MIM message input module；And basis row's class unit, it generates basis schedule aranging according to presetting constraints, described basis schedule aranging includes Jie Ci district, date field, Pai Kequ, described Pai Ke district includes multiple joint sub-cell, each joint sub-cell includes multiple classes of walking unit, the quantity wherein saving sub-cell depends on the quantity of described constraints, and the quantity of the class's of walking unit of described joint sub-cell is more than or equal to basis class quantity.The present invention provide a kind of reasonably carry out being layered arrange an order according to class and grade, be configured flexibly class size, student's composition, student are learned the Optimal Decision-making guide systems based on big data of resource matched well of combination, row's class and school.
Description
Technical field
The present invention relates to a kind of teaching system, particularly relate to a kind of teaching system for arranging class.
Background technology
Timetabling arithmetic as far back as the seventies turn out be calculating time of a np complete problem, i.e. algorithm be to be exponentially increased
, this judgement establishes the theoretical depth of timetabling arithmetic.It is the most mathematically neither one for np problem complete problem
General algorithm can solve well.Everybody is how to reduce it to calculate multiple to the main thought of np complete problem research at present
Miscellaneous degree.I.e. utilizing an approximate data to replace, the time so that solution problem of striving increases from exponential increase abbreviation to multinomial
Long.Be attached to arrange an order according to class and grade, timetabling problem sets up a suitable reality simple model exactly, utilizes this simple model can be significantly
Reduce the complexity of algorithm, it is simple to program realizes, and this is one technical scheme of the most up-to-date solution timetabling arithmetic.Based on new peak
Examine the practical situation of (7 select 3, and part saves and is slightly different, and such as Shanghai 6 selects 3) under policy, and the development side of following state education
To, student can be autonomous select oneself interested or be good at subject, academic program education, this makes to arrange an order according to class and grade, the difficulty of row's class
Being exponentially increased, the most each school (training organization etc.) distinctive teacher resource, classroom resources, time factor, personalization need
The many factors such as seeking, existing implementation can not meet.
Prior art shortcoming-automatic scheduling: cannot reasonably carry out layering and arrange an order according to class and grade, it is impossible to configure flexibly class size,
Combinations etc. selected by student composition (M-F, average achievement, just proportion by subtraction example etc.), student, arrange an order according to class and grade the resource (teacher with school
Resource, classroom resources, time etc.) cannot well mate, once discharge, it is impossible to carry out rational accommodation.
Prior art shortcoming-automatic curriculum scheduling: row's class has proved to be np complete problem, is the most mathematically neither one
General algorithm can solve well, replaces only with an approximate data, strive the time so that solution problem from
Exponential increase abbreviation to Polynomial Growth, so cause arranging an order according to class and grade, the result of row's class impracticable, be based particularly on choosing and examine policy (example 7
Select 3) under multifactor cross correlation pattern, even cannot produce result；Row's class result is the one of multiple exportable result, and
It it not optimal solution；Row's class result cannot meet the individual demand of school, such as some course and attend class the morning, on some afternoon,
Some teacher had no class in certain time；Row's class result cannot be carried out fine setting, owing to curricula-variable walks many data associations of class, leads one
And move whole body, may cause resetting；Row's class result cannot local directed complete set, such as Monday a few selected parts assess the work of an employee be adjusted to Wednesday
On a few joints.The output result of row's class cannot accurately individual (such as certain student or some student in which class, the how class of walking
Deng)；Row's class cannot well mate with the resource (teacher resource, classroom resources, time etc.) of school, once discharges, it is impossible to enter
The rational accommodation of row.
Summary of the invention
The technical problem to be solved in the present invention is to solve the workload labor huge, mental that traditional craft row's class brings
Dynamic big, the problems such as error in data cannot be avoided, solve the computational complexity of existing automatic curriculum scheduling high (NP causes completely simultaneously
Server is unavailable), output result undesirable (approximate data or other models), output result motility not (fine setting or office
Portion adjusts), the personalization problem that meets the aspects such as scarce capacity, it is achieved any school (educational institution or other), any factor
(space, time, resource, ambiguity strong), the intersection of any individual demand can obtain satisfied output result.Therefore, this
Bright offer one reasonably carry out layering arrange an order according to class and grade, be configured flexibly class size, student composition, student learned combination, arrange an order according to class and grade and
The resource matched well of school Optimal Decision-making guide systems based on big data.
Present invention Optimal Decision-making based on big data guide system, including curricula-variable MIM message input module, it is used for inputting choosing
Class information by curricula-variable information initializing, it generates the first aid decision data according to curricula-variable information；Assembled classification module, it is used
In the curricula-variable information of the combination that all students of display select, and, it generates the second aid decision according to the curricula-variable information of combination
Data；Arranging an order according to class and grade into a class MIM message input module, it is arranged an order according to class and grade into class information for input and will arrange an order according to class and grade into a class information initializing, its basis
Arrange an order according to class and grade into class information and generate the 5th aid decision data；And basis row's class unit, it generates basis row according to presetting constraints
School timetable, described basis schedule aranging includes that Jie Ci district, date field, Pai Kequ, described Pai Ke district include multiple joint sub-cell, Mei Gejie
Sub-cell includes multiple classes of walking unit, and the quantity wherein saving sub-cell depends on the quantity of described constraints, and described joint time is single
The quantity of the class's of walking unit of unit is more than or equal to basis class quantity, and it is single that basis row's class unit adjusts joint time by the first control module
Unit and/or the class's of walking unit basis schedule aranging in position and content.
Present invention Optimal Decision-making based on big data guide system difference from prior art is that the present invention is based on greatly
The Optimal Decision-making guide system of data passes through basis row's class unit every class of integration arrangement and the class's of walking situation of every class, thus
Curriculum schedule is made integrally to edit so that it is to edit more intelligent.And the advantage arranged an order according to class and grade is: one exports result surely, and
For meeting school's (educational institution or other) desired result；Layered shaping can be carried out, good-student class in such as arranging an order according to class and grade, pilot,
Experimental class, parallel class etc.；Can carry out processing for the combination selected by student flexibly and also can belong to originally at class according to student
Reason, forms, to the student of class, certain student that can refine；To the composition of class (combination composition, achievement composition, M-F,
Number of student, level composition etc.) configure flexibly；Whole row's class process all can be optimized adjustment, and that optimizes and revises is right
As can be combination composition, achievement composition, M-F, number of student, level composition etc., it is possible to refine to certain individuality or
Groupuscule, such as someone, a few individuals etc..Can farthest meet the actual feelings of each school (educational institution or other)
Condition and demand.The advantage of row's class is: the most any cross correlation factor (space, time, resource etc.), is based particularly on choosing and examines
Multifactor cross correlation pattern under policy (example 7 selects 3), all can the row's of generation class result；Row's class process data is rigorous accurately, speed
Hurry up, eliminate the mental work work of the work of the most loaded down with trivial details data compilation and rigorous thinking；Whole row's class row's class process all with
The Optimal Decision-making of big data is foundation, therefore output result is that the one in several optimal solution (fully meets school's practical situation
)；Row's class result fully meets the individual demand of school, such as some course and attends class the morning, on some afternoon, and some teacher
Have no class in certain time；Row's class result can carry out a few selected parts assessment of tuning, such as Monday and be adjusted to a few of Wednesday
On joint, or a few class of certain day are adjusted on other a few class；The output result of row's class refine to accurate individual (ratio
If certain student or some student are in which class, how class of walking etc.)；The resource of row's class and school (teacher resource, classroom resources,
Time etc.) well mate, and whole row's class process, all can carry out rational adaptive optimization adjustment.
Below in conjunction with the accompanying drawings the Optimal Decision-making guide systems based on big data of the present invention are described further.
Accompanying drawing explanation
Fig. 1 is the structural representation of Optimal Decision-making guide system based on big data；
Fig. 2 is the flow chart of Optimal Decision-making guide system based on big data.
Detailed description of the invention
As shown in Figure 1, 2, present invention Optimal Decision-making guide based on big data system includes
Curricula-variable MIM message input module, it is used for inputting curricula-variable information and by curricula-variable information initializing, and it is according to curricula-variable information
Generate the first aid decision data；
Assembled classification module, the curricula-variable information of its combination selected for showing all students, and, it is according to combination
Curricula-variable information generates the second aid decision data；
Arranging an order according to class and grade into a class MIM message input module, it is arranged an order according to class and grade into class information for input and will arrange an order according to class and grade into a class information initializing, its
The 5th aid decision data are generated according to arranging an order according to class and grade into class information；
Class's composite module, it is for showing the students' needs combination relevant information of all classes, and, it is according to combination
Curricula-variable information generate the 6th aid decision data；
Class's subject module, it is for showing the students' needs subject relevant information of all classes, and, it is according to combination
Curricula-variable information generate the 7th aid decision data；And
Basis row's class unit, it is according to presetting constraints generation basis schedule aranging, and described basis schedule aranging includes joint
District, date field, Pai Kequ, described Pai Ke district includes that multiple joint sub-cell, each joint sub-cell include multiple classes of walking unit, wherein
The quantity of joint sub-cell depends on the quantity of described constraints, and the quantity of the class's of walking unit of described joint sub-cell is more than or equal to base
Plinth class quantity, basis row's class unit adjusts joint sub-cell and/or the class's of walking unit at basis schedule aranging by the first control module
In position and content.
Some people of certain section's purpose in certain combination of certain class has been discharged to certain class's of walking unit of certain joint sub-cell
In, then on the premise of not carrying out recalling process, these people can not be at other class's of walking unit row's classes of this joint sub-cell, but can be
Other joint sub-cells arrange other section's purpose classes.
The total school timetable generated according to basis schedule aranging, can adjust certain or some according to constraints and school's real resource
Joint sub-cell position in total school timetable.
Wherein, arrange an order according to class and grade into class information to include but not limited to: class's quantity, class's total number of persons, class's number of combinations, class's combination
Situation, class respectively combine number.
Wherein, the 5th aid decision data examine subject including but not limited to: teacher resource information, classroom resources information, choosing
Number information, do not arrange class subject, personnel and affiliated combined information thereof, row's class and walk a class unit information, can for certain joint sub-cell
Row's subject, personnel and affiliated combined information, collision detection, row's class (the waiting to recall) combined information of personnel, name information, one-tenth
Achievement information, gender information, belong to class's information originally.
Wherein, constraints includes but not limited to: the curriculum character of row's class, available class, class hour information, current grade,
Rule is examined in choosing, rule is examined in curriculum character, choosing.It is 7 to select 3 that rule is examined in such as choosing, and curriculum character is choosing when examining, then joint sub-cell number is
3 joints；Curriculum character is when examining, then joint sub-cell number is 4 joints.
Wherein, the Jie Ci district of schedule aranging, basis, date field, Pai Ke district are editable.
Wherein, basis schedule aranging is as an entirety, and all choosings of all students are examined or learned and examine subject and must arrange on basis
A class unit drained class hour, and only arrange a class hour.
The present invention is by basis row's class unit every class of integration arrangement and the class's of walking situation of every class, so that curriculum schedule
Can integrally edit so that it is edit more intelligent.
The present invention be Optimal Decision-making based on big data carry out the row's of arranging an order according to class and grade class intelligence guiding, fully combine practical situation with
And the individual demand of each user, various dimensions process, and all use intellectual analysis at any one key business node, return
The mode receive, summed up, is aided with the mode of manual intervention, and at the manually row's of arranging an order according to class and grade class, (workload is big, mental work intensity is high, data
Inaccurate etc.) and automatic scheduling row's class (np complete problem) directly find an optimum balance, and create choosing and examine and (learn
Examine) row's class theory of basis row's class unit, it is achieved the row's of arranging an order according to class and grade class facilitation, accuracy, motility need with actual application personalization
The perfect adaptation asked.
Wherein, Optimal Decision-makings based on big data are arranged an order according to class and grade row's class, at any one service logic node, all export big data
Optimal Decision-making data, these data are objective business datums and school's (educational institution or other) practical situation and restraining factors
The Comprehensive analysis results of (space, time, resource etc.) etc., is all maximum to guarantee in the operation of any one service logic node
Change and meet reality application so that the output at next service logic node is several for this school (educational institution or other)
Plant one of optimal result, until guide completes；Meanwhile, during whole guide, system optimize flexibly including but not limited to
Multiple combination, a certain combination or the part of a certain combination, belong to originally class, teacher, classroom, the time, level, some student or certain
Student, achievement distribution, M-F etc..
The present invention solves the optimum meeting its specific resources and constraint that school's (educational institution or other) thirsts for solving
Arrange an order according to class and grade timetabling arithmetic；Overcome manual row's class inaccuracy, the present situation that the most rigorous, workload is big, mental work is big, overcome simultaneously
The row class result that the automatic scheduling of prior art and Course Automatic Arranging System bring is undesirable, it is impossible to maximized meet school
(educational institution or other) practical situation, it is impossible to the technology prejudice such as optimize and revise flexibly；The most prominent, new for country
Choosing under entrance examination policies is examined, is learned the row's of examining class process, and (such as, 7 select 3, then intend elective course for system general's plan elective course mesh number or plan subject mesh number
Mesh number is 3, intend subject mesh number be 4) as Xuan Kao section and Xue Kao section basic row's class unit (such as, 7 select 3, then choosing examine basis row
Class unit is 3 joints, and learning and examining basis row's class unit is 4 joints), must and only need to be at basis row's class unit all choosings of all of student
Examining or all is examined the subject the most drained class hour, the class period of each class of the most self-defined basis row's class unit is (such as
Which joint that week is several).
The form of SAAS of the present invention or software product for school (educational institution or other), and can simply, fast
Speed, generate and meet school's (educational institution or other) practical situation or the optimum results of individual demand accurately, flexibly, and can
In conjunction with actual demand, carry out profound tuning flexibly.It does not cause the serious waste of environmental pollution and the energy or resource,
Without compromising on health.
Advantage of the present invention-arrange an order according to class and grade: one exports result surely, and for meeting school's (educational institution or other) desired result；
Layered shaping can be carried out, good-student class in such as arranging an order according to class and grade, pilot, experimental class, parallel class etc.；Can be flexibly for selected by student
Combination carry out processing and also can belong to class originally according to student and process, the student of class is formed certain student that can refine；
The composition (combination composition, achievement composition, M-F, number of student, level composition etc.) of class is configured flexibly；Whole
Individual row's class process all can be optimized adjustment, and the object optimized and revised can be combination composition, achievement composition, M-F,
Stranger's number, level composition etc., it is possible to refine to certain individual or groupuscule, such as someone, a few individuals etc..Can maximum journey
The practical situation meeting each school (educational institution or other) of degree and demand.
Advantage of the present invention-row's class: the most any cross correlation factor (space, time, resource etc.), is based particularly on choosing
Examine multifactor cross correlation pattern under policy (example 7 selects 3), all can the row's of generation class result；Row's class process data is rigorous accurately, speed
Hurry up, eliminate the mental work work of the work of the most loaded down with trivial details data compilation and rigorous thinking；Whole row's class row's class process all with
The Optimal Decision-making of big data is foundation, therefore output result is that the one in several optimal solution (fully meets school's practical situation
)；Row's class result fully meets the individual demand of school, such as some course and attends class the morning, on some afternoon, and some teacher
Have no class in certain time；Row's class result can carry out a few selected parts assessment of tuning, such as Monday and be adjusted to a few of Wednesday
On joint, or a few class of certain day are adjusted on other a few class；The output result of row's class refine to accurate individual (ratio
If certain student or some student are in which class, how class of walking etc.)；The resource of row's class and school (teacher resource, classroom resources,
Time etc.) well mate, and whole row's class process, all can carry out rational adaptive optimization adjustment.
Preferably, present invention additionally comprises
Former class module, it generates the 3rd aid decision data according to the curricula-variable information of combination.
Preferably, present invention additionally comprises
Data analysis module, it is not arranged combination and/or subject information for real-time calculating, current does not arranges combination Zhong Liang section
The decision information that in identical decision information, the current combination do not arranged, branch is identical, the current personnel not arranging class and selected group
The information such as conjunction, subject, quantity, currently at combination, subject selected by the personnel of row's class, belong to the decision-makings such as class, sex, achievement originally and believe
Breath, currently can arrange the information such as personnel and selected combination, subject, quantity of class, currently do not arrange and the personnel that must arrange and genus thereof
Property decision information, collision detection.
Wherein, to built class, its details can be checked, and can carry out recalling optimization (including but not limited to all
Recall, part is recalled), revocation procedure will generate in real time including but not limited to the personnel's that arranged an order according to class and grade in this class (waiting to recall)
Combined information, name information, performance information, gender information, belong to the 4th aid decision data such as class's information originally.After recalling, number
According to by real-time loading to assembled classification module and former class module, it is optimized and arranges an order according to class and grade.
Preferably, present invention additionally comprises
Class's composite module/subject comprising modules, it is used for generating class's composition information.
Wherein, class composition information include but not limited to: class's information, combination configuration information, this combination personal information, can
Row's class information.Wherein, any combination of any one class, some people of any one section's purpose in this combination can be carried out row's class
Process (dragging including but not limited to mouse drag, mouse drag, gesture), be discharged to away in class unit, and at same time point only
One of them subject is carried out row's class process.
Wherein, when row's class processes, the object composition that the row's of can customize class processes, including but not limited to sex composition, achievement
Distribution, arrange how many people, arrange who etc..
Wherein, some people of certain section's purpose in certain combination of certain class has been discharged to certain class of walking of certain joint sub-cell
In unit, then on the premise of not carrying out recalling process, these people can not at other class's of walking unit row's classes of this joint sub-cell, but
Other section's purpose classes can be arranged at other joint sub-cells.
Preferably, present invention additionally comprises
Resource information module, it is examined or learns to examine currently do not arrange for all subject teachers of generation in real time and the choosing of this subject
Class number and attribute information thereof.
Preferably, present invention additionally comprises
Arrange an order according to class and grade into class MIM message input module and generate the 5th aid decision data by data analysis module.
Wherein, the first aid decision data, the second aid decision data, the 3rd aid decision data, the 4th aid decision
Data, the 5th aid decision data, the 6th aid decision data, the 7th aid decision data all can " basis row's class unit lead to
Cross first control module adjust joint sub-cell and/or the class's of walking unit basis schedule aranging in position and content " time for operation
Personnel carry out auxiliary direction.
The optional course quantity examined by choosing of quantity of joint sub-cell determines, the quantity of the class's of walking unit by each joint sub-cell,
That is, the actual class of the walking quantity in each subject determines.
Such as, if curricula-variable mode is m selects n, then load n joint sub-cell.If basis class quantity is 3 classes, i.e.
Originally three classes, the most each joint sub-cell were had to include that at least three walks a class unit.
Preferably, present invention additionally comprises
Class's subject module of class's composite module generates class's composition information.
Wherein, any subject of any one class, some people in this subject can be carried out row's class process (comprise but not
Be limited to mouse drag, gesture drags), it is discharged to away in class unit.
Wherein, when row's class processes, the object composition that the row's of can customize class processes, including but not limited to sex composition, achievement
Distribution, arrange how many people, arrange who etc..
Wherein, any one student, its all of choosing examines the subject that subject and this school offer and takes common factor, the knot of common factor
Really subject basis row's class unit must and the most drained class hour.
Wherein, some people of certain section's purpose of certain class has been discharged in certain class's of walking unit of certain joint sub-cell, has then existed
On the premise of not carrying out recalling process, these people at other class's of walking unit row's classes of this joint sub-cell, but can not save at other
Sub-cell arranges other section's purpose classes.
Wherein, row's class of class's composite module processes to process with row's class of class subject module and synchronization carries out.
To the class's of walking unit row's class data, its details can be checked, and can carry out recalling optimization and (comprise but do not limit
In all recalling, partly recalling), revocation procedure (is treated generating in real time including but not limited to row's class in this class's of walking unit
Recall) combined information of personnel, name information, performance information, gender information, belong to the aid decision number in real time such as class's information originally
According to.After recalling, data by real-time loading to class's composite module and class's subject module, the row's of being optimized class.
Optimized, after row's class terminates, carried out the setting of basis row's class unit, at basis row's class unit can date edited
District selectes Monday (or arbitrary sky on Monday to Sunday), and can edit the joint time area definition base section sub-cell joint in this day
Secondary.Further, the row's class continued a week is arranged.Further, week school timetable is generated, can be single to any one base section of some day time
Unit (can more piece) integral translation is on other certain class of any one day.
Preferably, present invention additionally comprises
Basis row's class unit module generates personnel to be recalled and all properties information thereof by data analysis module, generation the
Four aid decision data.
Preferably, present invention additionally comprises
Basis row's class unit module is generated when front-seat class district and/or when prosthomere time district does not arranges and must by data analysis module
The personnel that must arrange and the decision information of attribute thereof.
Preferably, present invention additionally comprises
By data analysis module by conversion automatically, generate can customize 21 rating achievement rating information of personnel.
Preferably, present invention additionally comprises
By data analysis module, each student must and can only drained assess the work of an employee for 1 class hour selected by it in Pai Ke district.
Preferably, present invention additionally comprises
6th decision-making assistant information and the 7th decision-making assistant information are synchrodata.
Preferably, present invention additionally comprises
A class school timetable information is walked, often by information generation total school timetable information of school of total school timetable, teacher's school timetable information, student
One school timetable of individual student, school timetable is not quite similar.Preferably, total school timetable information of school, teacher are generated by the information of total school timetable
School timetable information, student walk a class school timetable information, and one school timetable of each student, school timetable is not quite similar.
Preferably, present invention additionally comprises preference course determination module, its curricula-variable MIM message input module based on upper halves
The curricula-variable information of input, it is determined that the preference curricula-variable information that this time curricula-variable MIM message input module is to be inputted；Wherein, described preference curricula-variable
Information carries out cluster judgment；Preference curricula-variable information is shown in the position treating that curricula-variable information inputs by described preference course determination module
Put.
Such as: the curricula-variable information of the curricula-variable MIM message input module input of upper halves is: physics, chemistry, geography, preference is selected
Class MIM message input module according to course before account for arts and science number, by student's classification in arts and science, it is determined that literal arts be inclined to
Student or natural sciences tendency student.Above-mentioned student is judged as natural sciences tendency student, and preference curricula-variable MIM message input module is incited somebody to action:
Physics, chemistry, biology, geographical output are to the position treating that curricula-variable information inputs.
Preferably, preference course determination module of the present invention includes:
Preference subject unit, it exports preference subject coefficient a, wherein the preference subject coefficient a of physics according to subject type
=3, the preference subject coefficient a=2 of chemistry, biological preference subject coefficient a=1, the preference subject coefficient a=-2 of history, ground
The preference subject coefficient a=-2 of reason, the preference subject coefficient a=-2 etc. of politics；
Preference achievement unit, the repeatedly rating achievement rating of its crawl curricula-variable student institute curricula-variable, export rating achievement rating coefficient b, its
In when rating achievement rating is excellent, rating achievement rating coefficient b=4, when rating achievement rating is good, rating achievement rating coefficient b=3, work as achievement
When grade is for passing, rating achievement rating coefficient b=2；
Settling accounts output module, it obtains preference coefficient Y according to equation below,
Y=a1b1+a2b2+a3b3+a4b4+a5b5+a6b6
As Y > 0 time, then output preference curricula-variable information be the course learned physics, chemistry, biology and last term；
As Y, < when 0, then output preference curricula-variable information is the course learned history, geography, politics and last term.
The present invention can export preference curricula-variable information based on conventional curricula-variable subject and curricula-variable achievement by the way, thus
Student is helped to know the curricula-variable preference of oneself.
Preferably, of the present invention basis row's class unit row's class information include the main code of row's class, the block code of row's class,
Course types coding, the description of row's class event phenomenon, the first correspondence code, row's class reason, the second correspondence code, row's class type, row's class
Location and optimizing scheme, described optimizing scheme includes the class hour number of these row's class needs, title of preparing lessons and duration of preparing lessons；
The location of described row's class includes the school district at row's class place；
The backstage optimizing scheme evaluation module of basis row's class unit is just according to row's class application of curricula-variable MIM message input module
Information in the mode going out corresponding row's class number data for arranging the database retrieval of class is:
The described main code of row's class in the data base of motor vehicles row's class, the block code of row's class, course types are compiled
Code, row's class phenomenon, the first correspondence code, row's class reason, the second correspondence code, row's class type, the location of row's class and optimizing scheme
Field is respectively with the main code of row's class in the information of row's class application of curricula-variable MIM message input module, the block code of row's class, course
Type coding, the description of row's class event phenomenon, the first correspondence code, row's class reason, the second correspondence code, row's class type, the place of row's class
The record queries that ground is consistent with optimizing scheme, and in the total number of persons in the row's class number data in the record checked out
Most numbers, minimum number and average number as corresponding row's class number data.
Wherein, intelligent terminal is connected with preference course determination module.
Information for network sends framework, and the information conveyance figure place of its unit interval has had very than conventional homogeneous network
High improvement, is substantially all and can exceed that 3 megabits per second, but wireless link system is the most loaded down with trivial details, because the intensity of information reduces
Also has the impact of clutter, it becomes possible to make information conveyance stop temporarily and again carry, so allow information block, very
High quantity of information and real-time the lowest in the case of, this defect is the most serious, if this defect cannot be processed, necessarily will appear from very
The loss of the message group of multi information, allows information conveyance cannot realize correctness.
In order to prevent the loss defect of message group, the information also do not disposed often just first must be write the sudden strain of a muscle of intelligent terminal
In depositing, information described herein is the message of intelligent terminal's background server to be sent to, and described information is with the shape of message group
Formula exists, until network internal storage can link time just information is performed conveying, but the flash capacity of general intelligence terminal
Being little, so how the flash memory architecture of intelligent terminal is built the most critically important, former pattern is sized for arranging a pair
Flash memory space, the respectively first flash memory space and the second flash memory space, in the first flash memory space and the second equal nothing of flash memory space
When message group, just can receive the message group of information, and it is written to the first flash memory space, and in real time that the first flash memory is empty
Between message group perform disposal, synchronously can also then receive the message group of information, they are written to the second flash memory space,
By the time the message group in the first flash memory space dispose terminate after and conveying also terminate after, such first flash memory space can also be then
Receive the message group of information, synchronization can also perform the disposal to the second flash memory space, the carrying out thus gone round and begun again, so
The effect that achieves under conventional data delivery system of pattern, but under network condition, once there is the strong of information
Degree reduces the impact also having clutter, it becomes possible to make information conveyance stop temporarily and again carry, such a pair flash memory space
Message group even dispose finish, but also cannot be carried out conveying, the most just cannot then receive the message group of next group,
Because under conditions of being in network, the figure place of the message group of the information that the unit interval sends is many, if repeatedly cannot receive message
, i.e. there is the loss of a lot of information in group, so this quasi-mode is defective in network.
So, in order to solve this problem, it is proposed that following method:
The flash memory of described intelligent terminal contains Y the flash memory space being cleared, and Y is the positive integer not less than 3, at record machine
After the information of the maintenance application of motor-car, and at foreground maintenance program evaluation module, the information of the maintenance application of motor vehicles is being sent
Before in background server, carrying out the disposal of following steps, the information of the maintenance application of described motor vehicles is with message group
The information that form exists:
Step 1a: the first film micro area navigation module relies on the order of message group that gets and sequentially writes and be cleared
In flash memory space；
Step 2a: synchronize the message group of write to perform disposal, at this by the order of write when finishing step 1a
The mode put is exactly that the system time of intelligent terminal now is added to message group, disposes the message group after terminating the most sequentially
Performing conveying, described conveying is namely sent to server by network, after conveying End Of Text Block, flash memory space is emptied, makes
Become the flash memory space being cleared；
Step 3a: receive follow-up message group, circulation performs step 1a and step 2a so that flash memory space is adopted repeatedly
With.
When in the flash memory space that the write of message group has been cleared, the flash memory space being cleared can be for writing
Message group, the flash memory space being written with message group is the most then disposed, and disposes and performs conveying after terminating, and empties the report of flash memory space
Literary composition group, constitutes the flash memory space being cleared, it is achieved the disposal of a message group again.
The setting means of number Y of described flash memory space is:
Step 1b: the process received, dispose, carry of message group is implemented to build equation, receives in i.e. setting the unit interval
It is invariant P by the number of message group, and to receiving the message that the bit stream that message group formed was disposed within the unit interval
The number of group is V, reduce for the intensity of information also have the impact of clutter make again to carry message need time-consuming standard
Difference is
Step 2b: obtain number Y of flash memory space with formula (1), (2) and (3):
Here, q, Z are all middle coefficient；
The described intensity for information reduce also have the impact of clutter make again to carry message need time-consuming standard
DifferenceNumerical value by conventional practical situation realize amount to after and obtain.
The value of number Y of described flash memory space is 600,4 or 500.
And thus obtained embodiment is as follows:
The number receiving message group in setting the unit interval is invariant P, this invariant P=3*106/ L, wherein 3*106For
Receiving the figure place of message group in unit interval, L is the figure place of long message group, exists to receiving the bit stream that message group formed
The number disposed in unit interval is V=4.5*10 in the present embodiment6/ L, and the value of L can be according to the mark of actual message group
Standard obtains, the described intensity for information reduce also have the impact of clutter make again to carry message need time-consuming standard
DifferenceNumerical value by conventional practical situation realize amount to after and obtain.
So above-mentioned numerical value being substituted into formula (1), (2) and (3), just can know that, the intensity of information reduces the least also clutter
Impact the most no small in the case of, the number of times again carried is the most more, and the quantity of such flash memory space is the most, and strong in information
In the case of degree reduction also has the impact of clutter to ignore, under the state that namely K (Z) is zero, just can obtain N is 122.7,
Namely need at least 123 flash memory space could meet the conveying of safety.
The manner has thoroughly overturned existing mode, replaces with the pattern of regulation write flash memory space repeatedly, real efficiently
Show and prevented the loss of message group from making the incorrect defect of information.
Also have and be exactly, and for server, the most constantly heat up in the environment of a relative closure, and currently for
The chiller of server, for the important instrument maintaining server performance, and cooling effectiveness is for server, direct relation
The correctness run to it, but present chiller, be only merely and arrange aluminum alloy sheet below little region,
The higher position of aluminum alloy sheet sets up exhaust fan, yet with the space constraints of server, cooling range is little, inefficiency,
The correctness that server runs cannot be ensured；Although there being a kind of scheme to allow rhombus aluminum alloy sheet be held on support chip wall, cooling
Effect also has improvement, but speed is the unhappiest.
Being additionally provided with chiller otherwise for server, described chiller contains right angle folding rule shape and accommodates cold-producing medium
Cabinet, described cold-producing medium is used to server is assisted cooling, described in accommodate the cabinet of cold-producing medium and contain horizontal use
The cavity cooled down and longitudinal liquid storage pool, the described cavity being used for cooling down is all cuboid with the profile of longitudinal liquid storage pool
Framework, sets up the aluminum alloy sheet for shelving server, described aluminum in the more high position of the described cavity being used for cooling down
Alloy sheet is the metal that the coefficient of overall heat transmission is good, and the server on aluminum alloy sheet is spiraled pulls migration, in the horizontal chamber being used for cooling down
Setting up for the liquid booster to cold-producing medium supercharging in body, described is used for the liquid booster to cold-producing medium supercharging by institute
The position of the longitudinal liquid storage pool stated is arranged, and described being used for operationally can promote institute to the liquid booster of cold-producing medium supercharging
That states spirals movement for the cold-producing medium in the cavity that cools down, in the more high position of described aluminum alloy sheet in described longitudinal direction
Liquid storage pool in edge surface set up support platform, on described support platform install supply gas fan can be to described aluminum alloy sheet
Wall is supplied gas, described in fan of supplying gas be in the top of middle section of described aluminum alloy sheet, such framework can be to server
When performing cooling, server is sent the intensification hot-fluid passed out after intensification via the following several approach in framework:
A. server is transported to aluminum alloy sheet the intensification hot-fluid passed out after intensification, carries via aluminum alloy sheet；
B. server delivers to, via aluminum alloy sheet, the cold-producing medium that more lower position is calculated hot-fluid, and the cold-producing medium spiraled is hot-fluid
Send via the surface of the horizontal cavity being used for cooling down；
C. server fans the air-flow transmission via movement hot-fluid via supplying gas of more high position.
Such approach is also sent to server and performs cooling, and cooldown rate is the lowest, easily operates.
Gap is had, additionally in described gap with described longitudinal liquid storage pool on described longitudinal liquid storage pool
Keeping the powering shelf intercepted, described powering shelf can be set up in described longitudinal liquid storage pool top, also can be set up in
One of described longitudinal liquid storage pool top, additionally described powering shelf keeps right with the top of the liquid storage pool of described longitudinal direction
Together, described powering shelf plays plywood, described confession with the top of the liquid storage pool of described longitudinal direction with can open and close
Electricity cabinet in transformator via electric connector with the battery outside powering shelf be connected, also to supply gas fan with supercharger perform electricity
Power supplies.
Preferably, the described curricula-variable MIM message input module of the present invention includes that student's preference tests module, described student's preference
Test module includes
For capturing the preference field handling module of the subjective item purpose Repeating Field in student's paper；
For described Repeating Field divides classification, and each classification is provided with corresponding predetermined coefficient, and according to the weight captured
Multiple field is that each classification implements scoring for the distribution situation of each classification, and it is flat to export first according to the scoring of each classification
The meansigma methods output module of average Z；
Based on the first meansigma methods Z and preferential row's class module of equation below one row of output class preferred value N；
Wherein, N is row's class preferred value, and Z is the first meansigma methods, and S, D, L are for arranging coefficient, and D is more than 1, and G is each classification
The maximum of scoring, floor is for round algorithm downwards, and mod is the remainder after two numerical expressions make division arithmetic；With
Export row's class module of row's class order sequence number to the student inputting above-mentioned Repeating Field according to row class preferred value N.
Pass-through mode of the present invention can be based on the optimized algorithm of big data, when D is 1, different classes of row class preferred value N's
For increasing or decreasing.Working as S=6, when G=2, D=3, L=1, the curve of N rises for disconnected sequence.It has for the priority level of row's class
Important impact.That is, the keyword in the subjective exercise question of student is more concentrated, and the curricula-variable tendency of student is more concentrated, crucial with this
The course that word is corresponding just should be by prioritization.Popular course is so enable to enjoy more educational resource.
Preferably, basis of the present invention row's class unit includes course arrangement handling module, central processing module, sensor
Module, registration module；
Described course arrangement handling module: include successively in described course arrangement handling module intelligent terminal, communication module,
Information scratching device, information planning device, priority determination module, data conversion module, multiple flash memories；Wherein, described information is grabbed
Take device by the classroom location in the described communication module data base to server and name information, teacher's information, date and use
Temporal information, the data of information of giving lessons carry out unidirectional communication data transmission and collection successively, and teacher's information's data are by intelligence eventually
End inputs teacher's all-purpose card number, name, affiliated department, identity information data and is stored in the educational administration management system data of server
In storehouse；Then the row's class information data gathered by described information scratching device, passes sequentially through the series connection that described information planning device is built-in
Information data classification statistical module, information data category analysis module, information data classification evaluation module, by row's class Information Number
Aggregate into multiclass information data according to classification, carry out information data classification the most successively by described priority determination module the most again
Sequence, more successively by the multiple classification information data after sequence according to priority order from low to high, via corresponding data
Conversion module, preserves successively to corresponding multiple flash memories；
Described central processing module: described central processing module includes that information classification control unit, control information are cut successively
Change retransmission unit, all-purpose card card reader, access information communication transfer unit；Described access information communication transfer unit is built-in with and adds
The electronic lock of secret key, access information induction chip, access information identification chip, multiple spot distributed controlling and managing chip；Wherein, institute
State information classification control unit to above-mentioned course arrangement handling module preserves the row's class gathered to corresponding multiple flash memories
Information carries out corresponding classification, correspondence is assembled, corresponding compression processes, and then switches to via described control information switching retransmission unit
Physical address data is forwarded to described all-purpose card card reader and is identified, and the information data one-way communication after identifying pushes to institute
State access information communication transfer unit；
Described sensor assembly: described sensor assembly includes that multiple subscriber terminal unit, multistage planetary network connect successively
Enter dot element, network information detector unit, target information identification marking unit, unidentified information feedback unit, user authentication are awarded
Power administrative unit, wherein, by the Information Number pushing to described access information communication transfer unit in above-mentioned central processing module
According to, sent to above-mentioned multistage planetary network insertion by any one subscriber terminal unit in above-mentioned multiple subscriber terminal units
Dot element；Described network information detector unit includes information data analog-digital chip, noise filtering chip and infomation detection core
Sheet, wherein, described information data analog-digital chip carries out changing the bit stream of digital processing, through described noise filtering core
Sheet provides at least two analoglike signals after filtering, then in turn through described target information identification marking unit, unidentified
After information feedback unit is identified classification, feed back to user authentication empowerment management unit；
Described registration module: above-mentioned user authentication empowerment management unit to feedack data according to actual needs, enters
The Stochastic accessing of row real-time synchronization multiple access information；When user terminal is registered, multistage planetary network of network corresponding end is
Register successful user terminal reserve dispatch call control channel；User terminal controls on channel and net at reserved dispatch call
Network corresponding end carries out Signalling exchange；After Signalling exchange, network corresponding end releases dispatch call and controls the reserved of channel.
The present invention can allow student at course selected by registration in Internet by the way more easily.
Embodiment described above is only to be described the preferred embodiment of the present invention, the not model to the present invention
Enclosing and be defined, on the premise of designing spirit/design philosophy without departing from the present invention, any focal pointe of this area is to this
The solution of invention or application realize various deformation and the improvement made, and all should fall into the guarantor that claims of the present invention determines
In the range of protecting.
Claims (10)
1. an Optimal Decision-making guide system based on big data, it is characterised in that: include
Curricula-variable MIM message input module, it is used for inputting curricula-variable information and by curricula-variable information initializing, and it generates according to curricula-variable information
First aid decision data；
Assembled classification module, the curricula-variable information of its combination selected for showing all students, and, it is according to the curricula-variable of combination
Information generates the second aid decision data；Arranging an order according to class and grade into a class MIM message input module, it is arranged an order according to class and grade into class information for input and will arrange an order according to class and grade
Becoming class's information initializing, it generates the 5th aid decision data according to arranging an order according to class and grade into class information；
Class's composite module, it is for showing the students' needs combination relevant information of all classes, and, it is according to the choosing of combination
Class information generates the 6th aid decision data；
Class's subject module, it is for showing the students' needs subject relevant information of all classes, and, it is according to the choosing of combination
Class information generates the 7th aid decision data；And
Basis row's class unit, it is according to presetting constraints generation basis schedule aranging, and described basis schedule aranging includes Jie Ci district, day
Phase district, Pai Kequ, described Pai Ke district includes that multiple joint sub-cell, each joint sub-cell include multiple classes of walking unit, wherein joint
The quantity of unit depends on the quantity of described constraints, and the quantity of the class's of walking unit of described joint sub-cell is more than or equal to basis class
Number of stages, basis row's class unit adjusts joint sub-cell and/or the class's of walking unit in the schedule aranging of basis by the first control module
Position and content.
According to basis schedule aranging generate total school timetable, can according to constraints and school's real resource adjust certain or some joint time
Unit position in total school timetable.
Optimal Decision-making guide system based on big data the most according to claim 1, it is characterised in that: also include
Former class module, it generates the 3rd aid decision data according to the curricula-variable information of combination.
Optimal Decision-making guide system based on big data the most according to claim 1, it is characterised in that: also include
Data analysis module, it does not arranges combination and/or subject information for real-time calculating, current not arrange combination Zhong Liang section identical
Decision information, branch is identical in the combination currently do not arranged decision information, currently do not arrange personnel and selected combination, the section of class
The information such as mesh, quantity, currently at combination, subject selected by the personnel of row's class, belong to decision informations such as class, sex, achievement, currently originally
The information such as personnel and selected combination, subject, quantity of class can be arranged, currently do not arrange and the personnel that must arrange and attribute decision-making letter thereof
Breath, collision detection.
Optimal Decision-making guide system based on big data the most according to claim 1, it is characterised in that: also include
Class's composite module/subject comprising modules, it is used for generating class's composition information.
Optimal Decision-making guide system based on big data the most according to claim 1, it is characterised in that: also include
Resource information module, it is examined or learns to examine currently do not arrange class people for all subject teachers of generation in real time and the choosing of this subject
Number and attribute information thereof.
Optimal Decision-making guide system based on big data the most according to claim 1, it is characterised in that: also include
Arrange an order according to class and grade into class MIM message input module and generate the 5th aid decision data by data analysis module.
Optimal Decision-making guide system based on big data the most according to claim 1, it is characterised in that: also include
Class's subject module of class's composite module generates class's composition information.
Optimal Decision-making guide system based on big data the most according to claim 1, it is characterised in that: also include
Basis row's class unit module generates personnel to be recalled and all properties information thereof by data analysis module, generates the 4th auxiliary
Help decision data.
Optimal Decision-making guide system based on big data the most according to claim 1, it is characterised in that: also include
Basis row's class unit module is generated when front-seat class district and/or when prosthomere time district does not arranges and must arrange by data analysis module
Personnel and the decision information of attribute.
Optimal Decision-making guide system based on big data the most according to claim 1, it is characterised in that: also include
By data analysis module by conversion automatically, generate can customize 21 rating achievement rating information of personnel；
Preferably, also include
By data analysis module, each student must and can only drained assess the work of an employee for 1 class hour selected by it in Pai Ke district；
Preferably, also include
6th decision-making assistant information and the 7th decision-making assistant information are synchrodata；
Preferably, also include
A class school timetable information, Mei Gexue is walked by information generation total school timetable information of school of total school timetable, teacher's school timetable information, student
A raw school timetable, school timetable is not quite similar；
Preferably, also include preference course determination module, its curricula-variable based on the last curricula-variable MIM message input module input
Information, it is determined that the preference curricula-variable information that this time curricula-variable MIM message input module is to be inputted；Wherein, described preference curricula-variable information is gathered
Class judges；Preference curricula-variable information is shown in the position treating that curricula-variable information inputs by described preference course determination module；
Preferably, described preference course determination module includes:
Preference subject unit, it is according to subject type output preference subject coefficient a, wherein the preference subject coefficient a=3 of physics,
The preference subject coefficient a=2 of chemistry, biological preference subject coefficient a=1, the preference subject coefficient a=-2 of history, geographical
Preference subject coefficient a=-2, the preference subject coefficient a=-2 of politics；
Preference achievement unit, it captures the rating achievement rating of curricula-variable student institute curricula-variable, exports rating achievement rating coefficient b, wherein work as achievement
When grade is excellent, rating achievement rating coefficient b=4, when rating achievement rating is good, rating achievement rating coefficient b=3, when rating achievement rating be and
During lattice, rating achievement rating coefficient b=2；
Settling accounts output module, it obtains preference coefficient Y according to equation below,
Y=a1b1+a2b2+a3b3+a4b4+a5b5+a6b6
As Y > 0 time, then output preference curricula-variable information be the course learned physics, chemistry, biology and last term；
As Y, < when 0, then output preference curricula-variable information is the course learned history, geography, politics and last term；
Preferably, row's class information of described basis row's class unit includes that the main code of row's class, the block code of row's class, course types are compiled
Code, the description of row's class event phenomenon, the first correspondence code, row's class reason, the second correspondence code, row's class type, the location of row's class and row
Class scheme, described optimizing scheme includes the class hour number of these row's class needs, title of preparing lessons and duration of preparing lessons；
The location of described row's class includes the school district at row's class place；
The backstage optimizing scheme evaluation module of basis row's class unit is just according to the information of row's class application of curricula-variable MIM message input module
In the mode going out corresponding row's class number data for arranging the database retrieval of class it is:
The main code of row's class in the described data base for arranging class, the block code of row's class, course types coding, row's class now
As, the first correspondence code, row's class reason, the second correspondence code, row's class type, the location of row's class and optimizing scheme field respectively with
The main code of row's class in the information of row's class application of curricula-variable MIM message input module, the block code of row's class, course types coding, row
The description of class event phenomenon, the first correspondence code, row's class reason, the second correspondence code, row's class type, the location of row's class and optimizing scheme
Consistent record queries, and in the row's class number data in the record checked out total number of persons with in most numbers,
Minimum number and average number are as corresponding row's class number data；
Preferably, described curricula-variable MIM message input module includes that student's preference tests module, and described student's preference test module includes
For capturing the preference field handling module of the subjective item purpose Repeating Field in student's paper；
For described Repeating Field divides classification, and each classification is provided with corresponding predetermined coefficient, and according to the pleonasm captured
Section is that each classification implements scoring for the distribution situation of each classification, and exports the first meansigma methods according to the scoring of each classification
The meansigma methods output module of Z；
Based on the first meansigma methods Z and preferential row's class module of equation below one row of output class preferred value N；
Wherein, N is row's class preferred value, and Z is the first meansigma methods, and S, D, L are for arranging coefficient, and D is more than 1, and G is the scoring of each classification
Maximum, floor is for round algorithm downwards, and mod is the remainder after two numerical expressions make division arithmetic；With
Export row's class module of row's class order sequence number to the student inputting above-mentioned Repeating Field according to row class preferred value N；
Preferably, described basis row's class unit includes course arrangement handling module, central processing module, sensor assembly, registration
Module；
Described course arrangement handling module: include intelligent terminal, communication module, information successively in described course arrangement handling module
Grabber, information planning device, priority determination module, data conversion module, multiple flash memories；Wherein, described information scratching device
By the classroom location in the described communication module data base to server and name information, teacher's information, date and use time
Information, the data of information of giving lessons carry out unidirectional communication data transmission and collection successively, and teacher's information's data are defeated by intelligent terminal
Enter teacher's all-purpose card number, name, affiliated department, identity information data and be stored in the educational administration management system data base of server
In；Then the row's class information data gathered by described information scratching device, passes sequentially through the built-in series connection of described information planning device
Information data classification statistical module, information data category analysis module, information data classification evaluation module, by row's class information data
Classification aggregates into multiclass information data, carries out information data classification by described priority determination module the most again and successively arranges successively
Sequence, more successively by the multiple classification information data after sequence according to priority order from low to high, turn via corresponding data
Mould module, preserves successively to corresponding multiple flash memories；
Described central processing module: described central processing module includes that the switching of information classification control unit, control information turns successively
Bill unit, all-purpose card card reader, access information communication transfer unit；Described access information communication transfer unit is built-in with and adds secret key
Electronic lock, access information induction chip, access information identification chip, multiple spot distributed controlling and managing chip；Wherein, described letter
Breath sorting control is to preserving the row's class information gathered to corresponding multiple flash memories in above-mentioned course arrangement handling module
Carry out corresponding classification, correspondence is assembled, corresponding compression processes, and then switches to physics via described control information switching retransmission unit
Address date is forwarded to described all-purpose card card reader and is identified, and the information data one-way communication after identifying pushes to described door
Prohibit information communication transmission unit；
Described sensor assembly: described sensor assembly includes multiple subscriber terminal unit, multistage planetary Network Access Point successively
Unit, network information detector unit, target information identification marking unit, unidentified information feedback unit, user authentication mandate pipe
Reason unit is wherein, by the information data pushing to described access information communication transfer unit in above-mentioned central processing module, logical
Cross any one subscriber terminal unit in above-mentioned multiple subscriber terminal unit to send to above-mentioned multistage planetary Network Access Point list
Unit；Described network information detector unit includes information data analog-digital chip, noise filtering chip and infomation detection chip, its
In, described information data analog-digital chip carries out changing the bit stream of digital processing, enters through described noise filtering chip
Row provides at least two analoglike signals, then in turn through described target information identification marking unit, unidentified information after filtering
After feedback unit is identified classification, feed back to user authentication empowerment management unit；
Described registration module: above-mentioned user authentication empowerment management unit to feedack data according to actual needs, carries out reality
Time synchronize multiple access information Stochastic accessing；When user terminal is registered, multistage planetary network of network corresponding end is registration
Successfully user terminal reserves dispatch call control channel；User terminal controls on channel and network pair at reserved dispatch call
Should hold and carry out Signalling exchange；After Signalling exchange, network corresponding end releases dispatch call and controls the reserved of channel.
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