CN103136389A - Parameter optimization method and parameter optimization device for metamaterial unit structure - Google Patents
Parameter optimization method and parameter optimization device for metamaterial unit structure Download PDFInfo
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- CN103136389A CN103136389A CN2011103842027A CN201110384202A CN103136389A CN 103136389 A CN103136389 A CN 103136389A CN 2011103842027 A CN2011103842027 A CN 2011103842027A CN 201110384202 A CN201110384202 A CN 201110384202A CN 103136389 A CN103136389 A CN 103136389A
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Abstract
The invention discloses a parameter optimization method and a parameter optimization device for a metamaterial unit structure. The parameter optimization method of the metamaterial unit structure comprises the steps: selecting equally distributed random numbers in preset parameter space, wherein each random number in the parameter space serves as a grain, calculating fitness value of each grain and recording global best fitness value, the gbest of the corresponding grain of the global optimum value and the pbest of each grain according to the results, updating grain state according to the gbest and the pbest, sequencing the fitness value of grains, selecting high fitness value grains according to a preset proportion and updating the index value of the high fitness value grains, and repeating the above steps to obtain a grain with the best pbest as a matching result. By means of the parameter optimization method and the parameter optimization device for the metamaterial unit structure, the grain which complies best with the design requirement is searched through auto-match, the whole process can be controlled by a computer, and problems that study and design of metamaterials are manually adjusted only by experience and effect is low are solved.
Description
Technical field
The present invention relates to super Material Field, relate in particular to a kind of parameter optimization method and device of super material cell structure.
Background technology
" super material " refers to artificial composite structure or the compound substance that some have the not available extraordinary physical property of natural material.Structurally ordered design by on the key physical yardstick of material can break through the restriction of some apparent natural law, thereby obtains to exceed the meta-materials function of the intrinsic common character of nature.
Obtain desirable " super material ", the selection of " material " is vital.Mathematical description for metamaterial structure unit electromagnetic property is an important step indispensable in super material the Automation Design process.
But, at present the research of super material and design still being rested on the stage of manual adjustment and design by rule of thumb, shortage standardization optimal design method has hindered extensive design and the commercial application of super material.Standardization optimal design scheme for artificial electromagnetic material structural unit electromagnetic property is to need at present the difficult problem of solution badly.
Summary of the invention
Embodiment of the present invention technical matters to be solved is, a kind of parameter optimization method and device of super material cell structure are provided, can carry out optimal design to metamaterial structure unit electromagnetic property, seek the particle that meets designing requirement most by Auto-matching, whole process can be by computer control, overcome at present the research of super material and design full manual adjustment by rule of thumb, the problem of inefficiency.Parameter optimization method and the device of the super material cell structure that the embodiment of the present invention provides utilize the mathematics method, can realize the extensive the Automation Design of super material.
In order to solve the problems of the technologies described above, the embodiment of the present invention provides a kind of parameter optimization method of super material cell structure, comprising:
A, choose equally distributed random number in the parameter preset space, each random number in described parameter space is as a particle;
B, calculate the fitness value of each particle, and according to result of calculation, the fitness value that the record overall situation is best and corresponding particle state gbest thereof, and the current best condition pbest of each particle till current;
C, according to described gbest and pbest, upgrade particle state;
After D, the fitness value sequence to described particle, choose the high particle of fitness value and upgrade its index value by preset ratio;
E, repeat above-mentioned steps B-D, to obtain have best pbest particle as matching result.
Wherein, described steps A comprises:
The nonparametric model F that a1, structure shine upon from the described parameter space of super material cell structure to refractive index spatial, i.e. n=F (s), the parameter of s representative unit structure wherein, n represents refractive index;
The refractive index n of a2, setting expectation
0
A3, choose equally distributed random number in the parameter preset space, each random number in described parameter space is as a particle.
Wherein, the formula of described renewal particle state is:
V(t+1)＝w*V(t)+c1*rand*(S(t)-pbest)+c2*rand*(S(t)-gbest)+n1
S(t+1)＝S(t)+V(t+1)+n2
Wherein V represents flying speed of partcles, and w represents inertia constant, c1, the c2 representative study factor, rand representative [0,1] produce equally distributed random number between, S represents particle state, and t is current time, t+1 is next moment, and n1, n2 are that the obedience average is 0, and variance is the Gaussian noise of designation number.
Wherein, described step D comprises:
D1, the fitness value of particle is sorted, and choose the high particle of fitness value by preset ratio;
The index value of the particle that d2, record are selected, equally distributed random number between the index value of each particle superior [0,1];
D3, the result of calculation forward of d2 is rounded, the former index value of substitution obtains the new index value of particle.
Wherein, preset ratio described in step D is 50%.
Correspondingly, the embodiment of the present invention also provides a kind of parameter optimization device of super material cell structure, comprising:
Particle is chosen module, is used for choosing equally distributed random number in the parameter preset space, and each random number in described parameter space is as a particle;
The optimum state logging modle be used for to be calculated the fitness value of each particle, and according to result of calculation, the fitness value that the record overall situation is best and corresponding particle state gbest thereof, and the current best condition pbest of each particle till current;
The particle state update module is used for according to described gbest and pbest, upgrades particle state;
The index upgrade module after being used for the fitness value sequence to described particle, being chosen the high particle of fitness value and upgrades its index value by preset ratio;
The match control module is used for controlling described optimum state logging modle, particle state update module, index upgrade module circular treatment successively, until obtain particle conduct and the n with best pbest
0The result of mating most.
Wherein, described particle is chosen module and is comprised:
The Construction of A Model unit is used for the nonparametric model F that structure shines upon to refractive index spatial from the parameter space of super material cell structure, i.e. n=F (s), and the parameter of s representative unit structure wherein, n represents refractive index;
Refractive index is preset the unit, is used for setting the refractive index n of expectation
0
Random number is chosen the unit, is used for choosing equally distributed random number in the parameter preset space, and each random number in described parameter space is as a particle.
Wherein, described particle state update module is according to formula:
V(t+1)＝w*V(t)+c1*rand*(S(t)-pbest)+c2*rand*(S(t)-gbest)+n1
S(t+1)＝S(t)+V(t+1)+n2
Upgrade particle state; Wherein V represents flying speed of partcles, and w represents inertia constant, c1, the c2 representative study factor, rand representative [0,1] produce equally distributed random number between, S represents particle state, and t is current time, t+1 is next moment, and n1, n2 are that the obedience average is 0, and variance is the Gaussian noise of designation number.
Wherein, described index upgrade module comprises:
The ranking fitness unit is used for the fitness value of particle is sorted, and chooses the high particle of fitness value by preset ratio;
The index value computing unit is used for record by the index value of the selected particle in described ranking fitness unit, equally distributed random number between the index value of each particle superior [0,1];
The index value updating block is used for the result of calculation forward of described index value computing unit is rounded, and the former index value of substitution, obtains the new index value of particle.
Wherein, described ranking fitness unit is used for the fitness value of particle is sorted, and chooses 50% higher particle of fitness value.
Parameter optimization method and the device of the super material cell structure that the embodiment of the present invention provides, can carry out optimal design to metamaterial structure unit electromagnetic property, seek the particle that meets designing requirement most by Auto-matching, whole process can be by computer control, overcome at present the research of super material and design full manual adjustment by rule of thumb, the problem of inefficiency.Parameter optimization method and the device of the super material cell structure that the embodiment of the present invention provides utilize the mathematics method, can realize the extensive the Automation Design of super material.
Description of drawings
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, the below will do to introduce simply to the accompanying drawing of required use in embodiment or description of the Prior Art, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skills, under the prerequisite of not paying creative work, can also obtain according to these accompanying drawings other accompanying drawing.
Fig. 1 is the schematic diagram of cellular construction;
Fig. 2 is the parameter optimization method first embodiment schematic flow sheet of super material cell structure provided by the invention;
Fig. 3 is the parameter optimization method second embodiment schematic flow sheet of super material cell structure provided by the invention;
Fig. 4 is the parameter optimization device first example structure schematic diagram of super material cell structure provided by the invention;
Fig. 5 is the parameter optimization device second example structure schematic diagram of super material cell structure provided by the invention.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is clearly and completely described, obviously, described embodiment is only the present invention's part embodiment, rather than whole embodiment.Based on the embodiment in the present invention, those of ordinary skills belong to the scope of protection of the invention not making the every other embodiment that obtains under the creative work prerequisite.
Please in the lump referring to Fig. 1 and Fig. 2, be the parameter optimization method first embodiment schematic flow sheet of super material cell structure provided by the invention, the method comprises:
Step S99 builds parameter space, and wherein, described parameter space is the multidimensional coordinate space take the various structural parameters of super material cell structure as a dimension formation, and the every bit in the multidimensional coordinate space represents a kind of cellular construction.
Referring to Fig. 1, super material also claims artificial electromagnetic material, is periodically to arrange the compound substance that has the cellular construction of certain geometrical shape and consist of on medium substrate.Each cellular construction can be made of the artificial microstructure that tinsel consists of.The geometric configuration of each cellular construction is by one group of Parametric Representation.The cellular construction of " work " font as shown in Figure 1 can be defined out by the high a of its integral body, long b and live width w, and we can be with parameter space of various geometric parameter structure of cellular construction like this.This parameter space is a multidimensional coordinate space, and wherein each geometric parameter is as a dimension.Each point in this multidimensional coordinate space represents a cellular construction that meets the geometric parameter of current coordinate position.
The corresponding cellular construction of each point of parameter space has different effective dielectric constant ε and/or equivalent permeability μ simultaneously, and refractive index
So can obtain the corresponding relation of structural parameters space and refractive index: n=F (s).
Step S100 chooses equally distributed random number in the parameter preset space, each random number in described parameter space is as a particle.We regard the every bit in parameter space as random number optimize a random number in thought, its corresponding particle.
Step S101 calculates the fitness value of each particle, and according to result of calculation, the fitness value that the record overall situation is best and corresponding particle state gbest thereof, and the current best condition pbest of each particle till current.
Step S102 according to described gbest and pbest, upgrades particle state.
Step S103 after the fitness value sequence to described particle, chooses the high particle of fitness value and upgrades its index value by preset ratio.
Step S104 repeats above-mentioned steps S101-S103, to obtain have best pbest particle as matching result.
The parameter optimization method of the super material cell structure that the embodiment of the present invention provides, can carry out optimal design to metamaterial structure unit electromagnetic property, seek the particle that meets designing requirement most by Auto-matching, whole process can be by computer control, overcome at present the research of super material and design full manual adjustment by rule of thumb, the problem of inefficiency.The parameter optimization method of the super material cell structure that the embodiment of the present invention provides utilizes the mathematics method, can realize the extensive the Automation Design of super material.
Referring to Fig. 3, be the parameter optimization method second embodiment schematic flow sheet of super material cell structure provided by the invention, in the present embodiment, with the flow process of the parameter optimization method of this super material cell structure of more detailed description, as shown in Figure 2, the method comprises:
Step S200, the nonparametric model F that structure shines upon from the parameter space of super material cell structure to refractive index spatial, i.e. n=F (s), the parameter of s representative unit structure wherein, n represents refractive index.Because the parameter of super material cell structure has a plurality ofly, have some complicated characteristics, therefore function F does not have concrete analytic expression, we have used the thought that random number is optimized here.
Step S201 sets the refractive index n of expecting
0More specifically, after this nonparametric model F construction complete, the n that the user can a given expectation
0, n
0Represent that the user expects the refractive index that obtains.Basic thought of the present invention is to concern that by hinting obliquely at F seeks and n
0The structural parameters s that mates most.
Step S202 chooses equally distributed random number in the parameter preset space.More specifically, the every bit in the parameter preset space represents a particle, namely in this step each random number in selected parameter space as a particle.We regard the every bit in parameter space as random number optimize a random number in thought, its corresponding particle.
Step S203, the fitness value of the particle that calculation procedure 202 is chosen, the preferred Gaussian function of the fitness function of particle.
Step S204, according to the result of calculation of step S203, the fitness value that the record overall situation is best and corresponding particle state gbest thereof, and the current best condition pbest of each particle till current.Generally, fitness value represents the poor of expectation value and actual value, therefore will make difference little, and what fitness value was larger is exactly good fitness value.
Step S205, the current best condition pbest according to the state gbest of global optimum and each particle till current upgrades particle state.More specifically, the formula of described renewal particle state is:
V(t+1)＝w*V(t)+c1*rand*(S(t)-pbest)+c2*rand*(S(t)-gbest)+n1
S(t+1)＝S(t)+V(t+1)+n2
Wherein V represents flying speed of partcles, w represents inertia constant, c1, the c2 representative study factor, rand representative [0,1] produce equally distributed random number between, S represents particle state, and t is current time, t+1 be next constantly, n1, n2 obey that average is 0, variance is the Gaussian noise of designation number.
Step S206 sorts to the fitness value of particle, and chooses the high particle of fitness value by preset ratio; More specifically, in the present embodiment, from big to small particle is sorted by fitness value, described preset ratio is preferably: 50%.Namely after the fitness value to particle sorts from big to small, choose 50% larger particle of fitness value.
Step S207, the index value of the particle that is selected of record, equally distributed random number between the index value of each particle superior [0,1] then rounds the result of calculation forward, the former index value of substitution, thus obtain the new index value of particle.
Need explanation to be, step S205 and step S206, S207 do not have strict sequencing relation, as long as before step S208, complete S205 and---to the renewal of particle state---get final product.
Step S208, repeated execution of steps S203 are to step S207, until obtain particle conduct and the n with best pbest
0The result of mating most.More specifically, 50% the particle that the fitness value chosen in step S207 is higher is as the basis, and generation returns in step S203, recomputates the fitness value after these particles upgrade.That is, each iteration, all choose from particle before fitness value higher 50%, recomputate after renewal, repeatedly after iteration, can obtain a highest particle of fitness value, the point of the parameter space of this particle representative is namely corresponding refractive index n
0Optimal geometrical parameter, thereby obtain the geometric configuration of super material cell structure.
The parameter optimization method of the super material cell structure that the embodiment of the present invention provides, can carry out optimal design to metamaterial structure unit electromagnetic property, seek the particle that meets designing requirement most by Auto-matching, whole process can be by computer control, overcome at present the research of super material and design full manual adjustment by rule of thumb, the problem of inefficiency.The parameter optimization method of the super material cell structure that the embodiment of the present invention provides utilizes the mathematics method, can realize the extensive the Automation Design of super material.
Referring to Fig. 4, be the parameter optimization device first example structure schematic diagram of super material cell structure provided by the invention, as shown in Figure 4, this device comprises:
The space builds module 6, is used for building parameter space, and wherein, described parameter space is the multidimensional coordinate space take the various structural parameters of super material cell structure as a dimension formation, and the every bit in the multidimensional coordinate space represents a kind of cellular construction.
Particle is chosen module 1, be used for choosing equally distributed random number in the parameter preset space, with each random number in described parameter space as a particle.
Optimum state logging modle 2 be used for to be calculated the fitness value of each particle, and according to result of calculation, the fitness value that the record overall situation is best and corresponding particle state gbest thereof, and the current best condition pbest of each particle till current.
Particle state update module 3 is used for according to described gbest and pbest, upgrades particle state.
The parameter optimization device of the super material cell structure that the embodiment of the present invention provides, can carry out optimal design to metamaterial structure unit electromagnetic property, seek the particle that meets designing requirement most by Auto-matching, whole process can be by automatic control, overcome at present the research of super material and design full manual adjustment by rule of thumb, the problem of inefficiency.The parameter optimization device of the super material cell structure that the embodiment of the present invention provides can be realized the extensive the Automation Design of super material.
Referring to Fig. 5, be the parameter optimization device second example structure schematic diagram of super material cell structure provided by the invention, in the present embodiment, with the structure of the parameter optimization device of this super material cell structure of more detailed description, as shown in Figure 5, this device comprises:
Particle is chosen module 1, is used for choosing equally distributed random number in the parameter preset space, and each random number in described parameter space is as a particle.More specifically, this particle is chosen module 1 and is comprised:
Construction of A Model unit 11 is used for the nonparametric model F that structure shines upon to refractive index spatial from the parameter space of super material cell structure, i.e. n=F (s), and the parameter of s representative unit structure wherein, n represents refractive index.Because the parameter of super material cell structure has a plurality ofly, have some complicated characteristics, therefore function F does not have concrete analytic expression, we have used the thought that random number is optimized here.
Refractive index is preset unit 12, is used for setting the refractive index n of expectation
0More specifically, after this nonparametric model F construction complete, the default unit 12 given n of reception user of refractive index
0, n
0Represent that the user expects the refractive index that obtains.Basic thought of the present invention is to concern that by hinting obliquely at F seeks and n
0The structural parameters s that mates most.
Random number is chosen unit 13, is used for choosing equally distributed random number in the parameter preset space.More specifically, the every bit in the parameter preset space represents a particle, therefore random number is chosen corresponding particle of each random number that unit 13 is chosen in the parameter space.
Optimum state logging modle 2, be used for calculating the fitness value that particle is chosen each selected particle of module 1, and according to result of calculation, the fitness value that the record overall situation is best and corresponding particle state gbest thereof, and the current best condition pbest of each particle till current.Generally, fitness value represents the poor of expectation value and actual value, therefore will make difference little, and what fitness value was larger is exactly good fitness value.The preferred Gaussian function of the fitness function of particle.
Particle state update module 3 is used for according to described gbest and pbest, upgrades particle state.More specifically, the formula of particle state update module 3 renewal particle states is:
V(t+1)＝w*V(t)+c1*rand*(S(t)-pbest)+c2*rand*(S(t)-gbest)+n1
S(t+1)＝S(t)+V(t+1)+n2
Wherein V represents flying speed of partcles, w represents inertia constant, c1, the c2 representative study factor, rand representative [0,1] produce equally distributed random number between, S represents particle state, and t is current time, t+1 be next constantly, n1, n2 obey that average is 0, variance is the Gaussian noise of designation number.
Ranking fitness unit 41 is used for the fitness value of particle is sorted, and chooses the high particle of fitness value by preset ratio; More specifically, in the present embodiment, from big to small particle is sorted by fitness value, described preset ratio is preferably: 50%.Be ranking fitness unit 41 after the fitness value to particle sorts from big to small, choose 50% larger particle of fitness value.
Index value computing unit 42 is used for record by the index value of the selected particle in ranking fitness unit 41, equally distributed random number between the index value of each particle superior [0,1].
Index value updating block 43 is used for the result of calculation forward of index value computing unit 42 is rounded, and the former index value of substitution, thereby obtains the new index value of particle.
The parameter optimization device of the super material cell structure that the embodiment of the present invention provides, can carry out optimal design to metamaterial structure unit electromagnetic property, seek the particle that meets designing requirement most by Auto-matching, whole process can be by automatic control, overcome at present the research of super material and design full manual adjustment by rule of thumb, the problem of inefficiency.The parameter optimization device of the super material cell structure that the embodiment of the present invention provides can be realized the extensive the Automation Design of super material.
One of ordinary skill in the art will appreciate that all or part of flow process that realizes in above-described embodiment method, to come the relevant hardware of instruction to complete by computer program, described program can be stored in a computer read/write memory medium, this program can comprise the flow process as the embodiment of above-mentioned each side method when carrying out.Wherein, described storage medium can be magnetic disc, CD, read-only store-memory body (Read-Only Memory, ROM) or random store-memory body (Random Access Memory, RAM) etc.
Above disclosed is only a kind of preferred embodiment of the present invention, certainly can not limit with this interest field of the present invention, and the equivalent variations of therefore doing according to claim of the present invention still belongs to the scope that the present invention is contained.
Claims (10)
1. the parameter optimization method of a super material cell structure, is characterized in that, comprising:
A, choose equally distributed random number in the parameter preset space, with each random number in described parameter space as a particle;
B, calculate the fitness value of each particle that is selected, and according to result of calculation, the fitness value that the record overall situation is best and corresponding particle state gbest thereof, and the current best condition pbest of each particle till current;
C, according to described gbest and pbest, upgrade particle state;
After D, the fitness value sequence to described particle, choose the high particle of fitness value and upgrade its index value by preset ratio;
E, repeat above-mentioned steps B-D, to obtain have best pbest particle as matching result.
2. the parameter optimization method of super material cell structure as claimed in claim 1, is characterized in that, described steps A comprises:
The nonparametric model F that a1, structure shine upon from the described parameter space of super material cell structure to refractive index spatial, i.e. n=F (s), the parameter of s representative unit structure wherein, n represents refractive index;
The refractive index n of a2, setting expectation
0
A3, choose equally distributed random number in the parameter preset space, each random number in described parameter space is as a particle.
3. the parameter optimization method of super material cell structure as claimed in claim 1, is characterized in that, the formula of described renewal particle state is:
V(t+1)＝w*V(t)+c1*rand*(S(t)-pbest)+c2*rand*(S(t)-gbest)+n1
S(t+1)＝S(t)+V(t+1)+n2
Wherein V represents flying speed of partcles, and w represents inertia constant, c1, the c2 representative study factor, rand representative [0,1] produce equally distributed random number between, S represents particle state, and t is current time, t+1 is next moment, and n1, n2 are that the obedience average is 0, and variance is the Gaussian noise of designation number.
4. the parameter optimization method of super material cell structure as claimed in claim 1, is characterized in that, described step D comprises:
D1, the fitness value of particle is sorted, and choose the high particle of fitness value by preset ratio;
The index value of the particle that d2, record are selected, equally distributed random number between the index value of each particle superior [0,1];
D3, the result of calculation forward of d2 is rounded, the former index value of substitution obtains the new index value of particle.
5. the parameter optimization method of super material cell structure as described in any one in claim 1 to 4, is characterized in that, preset ratio described in step D is 50%.
6. the parameter optimization device of a super material cell structure, is characterized in that, comprising:
Particle is chosen module, be used for choosing equally distributed random number in the parameter preset space, with each random number in described parameter space as a particle;
The optimum state logging modle be used for to be calculated the fitness value of each particle that is selected, and according to result of calculation, the fitness value that the record overall situation is best and corresponding particle state gbest thereof, and the current best condition pbest of each particle till current;
The particle state update module is used for according to described gbest and pbest, upgrades particle state;
The index upgrade module after being used for the fitness value sequence to described particle, being chosen the high particle of fitness value and upgrades its index value by preset ratio;
The match control module is used for controlling described optimum state logging modle, particle state update module, index upgrade module circular treatment successively, until obtain particle conduct and the n with best pbest
0The result of mating most.
7. the parameter optimization device of super material cell structure as claimed in claim 6, is characterized in that, described particle is chosen module and comprised:
The Construction of A Model unit is used for the nonparametric model F that structure shines upon to refractive index spatial from the parameter space of super material cell structure, i.e. n=F (s), and the parameter of s representative unit structure wherein, n represents refractive index;
Refractive index is preset the unit, is used for setting the refractive index n of expectation
0
Random number is chosen the unit, is used for choosing equally distributed random number in the parameter preset space, and each random number in described parameter space is as a particle.
8. the parameter optimization device of super material cell structure as claimed in claim 6, is characterized in that, described particle state update module is according to formula:
V(t+1)＝w*V(t)+c1*rand*(S(t)-pbest)+c2*rand*(S(t)-gbest)+n1
S(t+1)＝S(t)+V(t+1)+n2
Upgrade particle state; Wherein V represents flying speed of partcles, and w represents inertia constant, c1, the c2 representative study factor, rand representative [0,1] produce equally distributed random number between, S represents particle state, and t is current time, t+1 is next moment, and n1, n2 are that the obedience average is 0, and variance is the Gaussian noise of designation number.
9. the parameter optimization device of super material cell structure as claimed in claim 6, is characterized in that, described index upgrade module comprises:
The ranking fitness unit is used for the fitness value of particle is sorted, and chooses the high particle of fitness value by preset ratio;
The index value computing unit is used for record by the index value of the selected particle in described ranking fitness unit, equally distributed random number between the index value of each particle superior [0,1];
The index value updating block is used for the result of calculation forward of described index value computing unit is rounded, and the former index value of substitution, obtains the new index value of particle.
10. the parameter optimization device of super material cell structure as claimed in claim 9, is characterized in that, described ranking fitness unit is used for the fitness value of particle is sorted, and choose 50% higher particle of fitness value.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN105372807A (en) * | 2015-09-18 | 2016-03-02 | 中国科学院紫金山天文台 | An H-beta composite optimization method for primary mirror side support for an astronomical optical telescope |
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