formulasearchengine - User contributions [en]

Selection algorithm

2014-12-18T06:23:04Z

69.181.196.207: /* Selection by sorting */ change sentence structure

I'm Jaclyn and I live in a seaside city in northern Italy, Nocciano. I'm 23 and I'm will soon finish my study at Arts. Feel free to surf to my web-site ... [http://www.youtube.com/watch?v=ZkfjYK3K9nk Arthur Falcone]

Tree traversal

2014-03-04T03:12:54Z

69.181.39.31: /* Pre-order */

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Vienna Standard Mean Ocean Water

2013-12-02T20:05:54Z

69.181.70.104:

[[Image:HypotrochoidOutThreeFifths.gif|thumb|450px|
The red curve is a hypotrochoid drawn as the smaller black circle rolls around inside the larger blue circle (parameters are ''R'' = 5, ''r'' = 3, ''d'' = 5).]]
A '''hypotrochoid''' is a [[roulette (curve)|roulette]] traced by a point attached to a [[circle]] of [[radius]] ''r'' rolling around the inside of a fixed circle of radius ''R'', where the point is a [[distance]] ''d'' from the center of the interior circle.

The [[parametric equation]]s for a hypotrochoid are:{{fact|date=February 2012}}

:<math>x (\theta) = (R - r)\cos\theta + d\cos\left({R - r \over r}\theta\right)</math>
:<math>y (\theta) = (R - r)\sin\theta - d\sin\left({R - r \over r}\theta\right).</math>

Where <math>\theta</math> is the angle formed by the horizontal and the center of the rolling circle (note that these are not polar equations because <math>\theta</math> is not the polar angle).

Special cases include the hypocycloid with ''d'' = ''r'' and the [[ellipse]] with ''R'' = 2''r''.

[[Image:Ellipse as hypotrochoid.gif|right|400|thumb|The [[ellipse]] (drawn in red) may be expressed as a special case of the hypotrochoid, with R = 2r; here R = 10, r = 5, d = 1.]]

The classic [[Spirograph]] toy traces out hypotrochoid and [[epitrochoid]] curves.

==See also==

* [[List of periodic functions]]
* [[Epitrochoid]]
* [[Cycloid]]
* [[Hypocycloid]]
* [[Epicycloid]]
* [[Spirograph]]

==References==
* {{cite book | author=J. Dennis Lawrence | title=A catalog of special plane curves | publisher=Dover Publications | year=1972 | isbn=0-486-60288-5 | pages=165–168 }}

==External links==

*[http://www.mekanizmalar.com/hypocycloid.html Flash Animation of Hypocycloid]
*[http://xahlee.org/SpecialPlaneCurves_dir/Hypotrochoid_dir/hypotrochoid.html Hypotrochoid] from Visual Dictionary of Special Plane Curves, Xah Lee
*[http://www.geogebra.org/de/upload/files/dynamische_arbeitsblaetter/yiorisos/g10.html Interactive hypotrochoide animation]
*{{MacTutor|class=Curves|id=Hypotrochoid|title=Hypotrochoid}}
{{Geometry-stub}}

[[Category:Curves]]

[[de:Zykloide#Epi- und Hypozykloide]]
[[ja:トロコイド#内トロコイド]]

Robust optimization

2013-10-26T21:35:12Z

69.181.223.105: Removed obviously promotional link to commercial product

[[File:DART ion source capsule.jpg|thumb|right||A [[Capsule (pharmacy)|capsule]] being analyzed is held in the sample chamber between the DART ion source (right) and the spectrometer inlet (cone on left).|200px]]
'''DART''' ('''Direct Analysis in Real Time''') is an [[atmospheric pressure]] [[ion source]] that instantaneously ionizes gases, liquids and solids in open air under [[Ambient pressure|ambient]] conditions.<ref>{{cite journal |author=R.B. Cody, J.A. Laramée, H.D. Durst |journal=Anal. Chem. |year=2005 |volume=77 |issue=8 |pages=2297–2302 |pmid=15828760 |doi=10.1021/ac050162j |title=Versatile New Ion Source for the Analysis of Materials in Open Air under Ambient Conditions}}</ref> It was developed in 2005 by Laramee and Cody and is now marketed commercially by [[JEOL]] and [[IonSense]].<ref>[http://jeolusa.com/tabid/230/Default.aspx 2. “Direct Analysis in Real Time (DARTtm) Mass Spectrometry” Cody, R. B.; Laramée, J. A.; Nilles, J.M.; Durst, H. D. JEOL News; 2005]</ref> It was among the first [[ambient ionization]] techniques not requiring sample preparation, so solid and liquid materials can be analyzed by [[mass spectrometry]] in their native state. [[Ionization]] can take place directly on the sample surface, such as, currency bills, tablets, bodily fluids (blood, saliva and urine), glass, plant leaves, fruits & vegetables and even clothing. Liquids are analyzed by dipping an object (such as a glass rod) into the liquid sample and then presenting it to the DART ion source. Vapors are introduced directly into the DART gas stream.

== Principle of operation ==
=== Ionization process ===

The ionization process involves an interaction between the [[analyte]] [[molecule]] (S) and electronically excited atoms or vibronically excited molecules (metastable species – M*):{{Citation needed|date=May 2010}}

:<math>M^* + S \to S^{+\bullet} + M + e^-\,</math>

Upon [[collision]] between the excited gas molecule (M*) and the surface of the sample, an energy transfer takes place, from the excited gas molecule (M*) to the neutral analyte molecule (S). This causes an [[electron]] to be released from the analyte molecule, producing a [[Radical (chemistry)|radical]] [[ion|cation]]. The molecular cation is then ejected from the sampling surface and travels to the mass analyzer along with the gas stream (typically [[Nitrogen|N2]] or [[Neon|Ne]]). The process presented in the above equation is called [[Penning ionization]]. For this ionization process to take place, the energy of the excited state gas molecule must be higher than the [[ionization potential]] of the neutral molecule.

When [[Helium|He]] is used as the carrier gas, the ionization process occurs by the following mechanism:
First an excited state He atom collides with an atmospheric pressure [[water]] molecule and ionizes it:

:<math>He(2^3S) + H_2O \to H_2O^{+\bullet} + He(1^1S) + e^-</math>

The ionized water molecule then undergoes several reactions with other neutral water molecules resulting in the formation of a [[protonation|protonated]] water [[Cluster (physics)|cluster]]:

:<math>H_2O^{+\bullet} + H_2O \to H_3O^+ + OH^{\bullet}</math>

:<math>H_3O^+ + nH_2O \to \left[(H_2O\right)_{n}H]^{+}</math>

The water cluster then interacts with the analyte molecule (S) generating a protonated molecule.

:<math>\left[(H_2O\right)_nH]^{+} + S \to SH^+ + nH_2O</math>

DART can also operate in the negative ion mode by which negatively charged species are formed. The negative ion formation process is under current discussion and investigation.

[[File:DART ion source schematic.gif|thumb|right|400 px|Schematic diagram of the DART ion source]]

=== Formation of metastable species ===

As the gas (N2, Ne or He) enters the ion source, an [[electric potential]] in the range of +1 to +5 kV is applied. This generates a glow discharge containing ionized gas, electrons and excited state atoms/molecules (metastable species). A potential of 100 V applied to the [[Electrostatics|electrostatic]] lenses removes charged particles from the gas stream and only excited state species flow to the third chamber. The gas stream in the third chamber can be heated from RT to 250 °C. Heating is optional but may be necessary depending on the surface or chemical being analyzed. An insulator cap at the terminal end of the ion source protects the operator from harm.

The excited-state species can interact directly with the sample which can be a solid, liquid or gas to desorb and ionize the analyte.

The distance between the ion source and the inlet of the mass spectrometer is 5 to 25 mm.
The ions formed are directed to the mass spectrometer inlet by both the gas flow and a slight vacuum in the spectrometer inlet. Although optimum geometries exist for specific applications, the exact positioning, distance and angle of DART ion source with respect to the sample surface and the mass spectrometer inlet are not critical.

== Source to analyzer interface ==

Ions entering the mass spectrometer first go through a source - to - analyzer interface, which was designed in order to minimize spectrometer contamination.
The ions are directed to the ion guide through orifice 1 and 2 by applying a slight potential difference between them: orifice 1 - 30V and orifice 2 - 5V.
It is clear from the diagram that the space between the two orifices is not horizontal but rather diagonal. Species containing charge (ions) are attracted to the second orifice, but neutral molecules travel in a straight pathway and thus get trapped in that region. The contamination is then removed by the pump.

== Mass spectra ==

DART produces relatively simple mass spectra, dominated by protonated molecules [M+H]+ in positive-ion mode, or deprotonated molecules [M-H]- in negative-ion mode. Depending on the nature of the molecule, other species may be formed, such as M+. from polynuclear aromatic hydrocarbons. Fragmentation may occasionally be observed for some molecules. Multiple-charge ions and alkali metal cation aducts are never observed, but addition of ammonia or other "dopants" to the DART gas stream can be used to form single-charge adducts such as [M+NH4]+ or [M+Cl]- for compounds that would not readily form molecular ions or protonated molecules. For example, the explosives nitroglycerin and HMX do not form [M-H]-, but readily form [M+Cl]- if chloride is present.

== Applications ==
DART can be applied to a wide range of applications, such as, the fragrance industry, pharmaceutical industry, foods and spices, forensic science and health.

In forensic science, DART has been used for analysis of sexual assault evidence<ref>{{cite journal |author=Musah RA, Cody RB, Dane AJ, Vuong AL, Shepard JR|year=2012|month= |title=Direct analysis in real time mass spectrometry for analysis of sexual assault evidence|journal= Rapid Communications in Mass Spectrometry|volume= 26|issue= |pages= 1039–1046|id= |doi=10.1002/rcm.6198 |pmid=22467453}}</ref> and of synthetic cannabinoids in herbal samples.<ref>{{cite journal |author=Musah RA, Domin MA, Walling MA, Shepard JR|year=2012|month= |title=Rapid identification of synthetic cannabinoids in herbal samples via direct analysis in real time mass spectrometry|journal= Rapid Communications in Mass Spectrometry|volume= 26|issue= 9|pages= 1109–1114|id= |doi=10.1002/rcm.6205 |pmid=22467461}}</ref>

In the fragrance industry, the deposition and release of a fragrance on surfaces such as, fabric and hair is often studied. Use of DART compared to traditional methods minimizes sample amount, sample preparation, eliminates extraction steps, decreases limit of detection and analysis time.<ref>{{cite journal |author=O.P. Haefliger, N. Jeckelmann|journal=Rapid Commun. Mass Spectrom.|year=2007 |volume=21 |pages=1361–1366 |doi=10.1002/rcm.2969 |title=Direct mass spectrometric analysis of flavors and fragrances in real applications using DART |pmid=17348088 |issue=8}}</ref>

In the pharmaceutical industry, the production and destruction of counterfeit drugs is becoming an international problem.<ref>{{cite news|url=http://www.cbc.ca/correspondent/feature_051211.html|publisher=CBC News|title=Bad Medicine|date=December 11, 2005}} {{Dead link|date=September 2010|bot=RjwilmsiBot}}</ref><ref>{{cite news|url=http://www.who.int/mediacentre/factsheets/fs275/en|publisher=World Health Organization|title=Counterfeit medicines|date=November 14, 2006}}</ref> Some countries in which this occurs are United Kingdom, China, Russia, Argentina, Nigeria and India. Dart can detect active ingredients in medicine in a tablet form; there is no need for sample preparation such as, crushing or extracting.

DART was used to directly analyze a red pepper pod in three different places: the membrane (white part holding the seeds), the seeds and the flesh of the pepper. The analyte of interest was capsaicin, a natural ingredient of a red pepper pod that is responsible for the burning sensation when eating chilies. The spectrum obtained revealed that the highest concentration of capsaicin is in the membrane.

DART has been used in the study of genus ''[[Allium]]'' plants, e.g., to identify the lachrymatory compound, [[syn-propanethial-S-oxide]], C2H5CH=S=O, in onion, ''[[Allium cepa]]'',<ref name=Block2010>{{cite book|author=Block, E.|title=Garlic and Other Alliums: The Lore and the Science |url=http://books.google.com/?id=6AB89RHV9ucC&printsec=frontcover|publisher=Royal Society of Chemistry|year=2010|isbn=0-85404-190-7}}</ref> a previously unknown lachrymatory compound, ''syn''-butanethial ''S''-oxide, C3H7CH=S=O, in ''[[Allium siculum]]'',<ref>{{cite journal |author=Kubec R, Cody RB, Dane AJ, Musah RA, Schraml J, Vattekkatte A, Block E|year=2010|month= |title=Applications of DART Mass Spectrometry in ''Allium'' Chemistry. (''Z'')-Butanethial ''S''-Oxide and 1-Butenyl Thiosulfinates and their ''S''-(''E'')-1-Butenylcysteine ''S''-Oxide Precursor from ''Allium siculum''|journal= Journal of Agricultural and Food Chemistry|volume= 58|issue= 2|pages= 1121–1128|id= |doi=10.1021/jf903733e |pmid=20047275}}</ref> pyrithione fron ''[[Allium stipitatum]]''<ref name=Block2011>{{Cite journal |last1=Block |first1=E. |last2=Dane |first2=A.J. |last3=Cody |first3=R.B. |year=2011 |title= Crushing Garlic and Slicing Onions: Detection of Sulfenic Acids and Other Reactive Organosulfur Intermediates from Garlic and Other Alliums Using Direct Analysis in Real Time-Mass Spectrometry (DART-MS) |journal= Phosphorus, Sulfur, Silicon and the Related Elements |volume=186 |issue=5 |pages=1085–1093|doi=10.1080/10426507.2010.507728 |lastauthoramp=yes |postscript={{inconsistent citations}} }}</ref> and syn-propanethial-S-oxide isomer 2-propene[[sulfenic acid]], CH2=CHCH2SOH, which is the very short-lived precursor to [[allicin]] from cutting [[garlic]], ''Allium sativum''.<ref name=Block2011b>{{cite journal |author=Block E, Dane AJ, Thomas S, Cody RB|year=2010|month= |title=Applications of Direct Analysis in Real Time–Mass Spectrometry (DART-MS) in ''Allium'' Chemistry. 2-Propenesulfenic and 2-Propenesulfinic Acids, Diallyl Trisulfane ''S''-Oxide and Other Reactive Sulfur Compounds from Crushed Garlic and Other Alliums|journal= Journal of Agricultural and Food Chemistry|volume= 58|issue= 8|pages= 4617–4625|id= |doi =10.1021/jf1000106 |pmid=20225897}}</ref> Recently, a so-called "cDART" (confined-DART) interface has been developed, in which the plasma generated by the atmospheric pressure glow discharge collides and ionizes the gas-phase molecules in a Tee-shaped flow tube instead of in open air. The confined ion source, which significantly improves ionization efficiency of gaseous molecules, was applied in the real time analysis of [[volatile organic compound]]s of [[lemon]] and onion. The onion was cut with a steel rod in a sample container continuously swept by nitrogen flow. While many of the onion volatiles found by cDART were identical to those found in the earlier DART study of onions,<ref name=Block2011b></ref> several previously unknown higher mass ions were also seen, presumably due to the increased sensitivity of cDART.<ref>{{cite journal |author=Li Y|year=2012|month= |title=Confined direct analysis in real time ion source and its applications in analysis of volatile organic compounds of ''Citrus limon'' (lemon) and ''Allium cepa'' (onion) |journal= Rapid Communications in Mass Spectrometry|volume= 26|issue= |pages= 1194–1202|id= |doi =10.1002/rcm.6217 |pmid= }}</ref>

==See also==
*[[Desorption electrospray ionization]]
*[[Electric glow discharge]]
*[[Atmospheric pressure chemical ionization]]
*[[Desorption atmospheric pressure photoionization]]

== References ==
{{Reflist}}

== Patents ==
*Robert B. Cody and James A. Laramee, “Method for atmospheric pressure ionization” {{US patent|6949741}} issued September 27, 2005. (Priority date: April 2003).
*James A. Laramee and Robert B. Cody “Method for Atmospheric Pressure Analyte Ionization” {{US patent|7,112,785 }} issued September 26, 2006.

{{Mass spectrometry}}

[[Category:Ion source]]
[[Category:Measuring instruments]]

On-balance volume

2013-05-11T03:51:54Z

69.181.243.14: /* Application */ changed spelling from vignolia to vignola. reference - me....i am their grandson.

In [[computer science]], '''differential evolution''' (DE) is a method that [[optimization (mathematics)|optimizes]] a problem by [[iterative method|iteratively]] trying to improve a [[candidate solution]] with regard to a given measure of quality. Such methods are commonly known as [[metaheuristic]]s as they make few or no assumptions about the problem being optimized and can search very large spaces of candidate solutions. However, metaheuristics such as DE do not guarantee an optimal solution is ever found.

DE is used for multidimensional real-valued [[function (mathematics)|functions]] but does not use the [[gradient]] of the problem being optimized, which means DE does not require for the optimization problem to be [[differentiable]] as is required by classic optimization methods such as [[gradient descent]] and [[quasi-newton methods]]. DE can therefore also be used on optimization problems that are not even [[:wikt:continuous|continuous]], are noisy, change over time, etc.<ref name=elediadereview/>

DE optimizes a problem by maintaining a population of candidate solutions and creating new candidate solutions by combining existing ones according to its simple formulae, and then keeping whichever candidate solution has the best score or fitness on the optimization problem at hand. In this way the optimization problem is treated as a black box that merely provides a measure of quality given a candidate solution and the gradient is therefore not needed.

DE is originally due to Storn and Price.<ref name=storn97differential/><ref name=storn96usage/> Books have been published on theoretical and practical aspects of using DE in [[parallel computing]], [[multiobjective optimization]], [[constrained optimization]], and the books also contain surveys of application areas.<ref name=price05differential/><ref name=feoktistov06differential/><ref name=chakraborty08advances/>

== Algorithm ==


A basic variant of the DE algorithm works by having a population of [[candidate solutions]] (called agents). These agents are moved around in the search-space by using simple mathematical [[formula]]e to combine the positions of existing agents from the population. If the new position of an agent is an improvement it is accepted and forms part of the population, otherwise the new position is simply discarded. The process is repeated and by doing so it is hoped, but not guaranteed, that a satisfactory solution will eventually be discovered.

Formally, let <math>f: \Bbb{R}^n \to \Bbb{R}</math> be the cost function which must be minimized or fitness function which must be maximized. The function takes a candidate solution as argument in the form of a [[Row vector|vector]] of [[real number]]s and produces a real number as output which indicates the fitness of the given candidate solution. The [[gradient]] of <math>f</math> is not known. The goal is to find a solution <math>m</math> for which <math>f(m) \leq f(p)</math> for all <math>p</math> in the search-space, which would mean <math>m</math> is the global minimum. Maximization can be performed by considering the function <math>h := -f</math> instead.

Let <math>\mathbf{x} \in \Bbb{R}^n</math> designate a candidate solution (agent) in the population. The basic DE algorithm can then be described as follows:

* Initialize all agents <math>\mathbf{x}</math> with random positions in the search-space.
* Until a termination criterion is met (e.g. number of iterations performed, or adequate fitness reached), repeat the following:
** For each agent <math>\mathbf{x}</math> in the population do:
*** Pick three agents <math>\mathbf{a},\mathbf{b}</math>, and <math>\mathbf{c}</math> from the population at random, they must be distinct from each other as well as from agent <math>\mathbf{x}</math>
*** Pick a random index <math>R \in \{1, \ldots, n\}</math> (<math>n</math> being the dimensionality of the problem to be optimized).
*** Compute the agent's potentially new position <math>\mathbf{y} = [y_1, \ldots, y_n]</math> as follows:
**** For each <math>i</math>, pick a uniformly distributed number <math>r_i \equiv U(0,1)</math>
**** If <math>r_i < \text{CR}</math> or <math>i = R</math> then set <math>y_i = a_i + F(b_i-c_i)</math> otherwise set <math>y_i = x_i</math>
**** (In essence, the new position is outcome of binary crossover of agent <math>\mathbf{x}</math> with intermediate agent <math>\mathbf{z} = \mathbf{a} + F(\mathbf{b}-\mathbf{c})</math>.)
*** If <math>f(\mathbf{y}) < f(\mathbf{x})</math> then replace the agent in the population with the improved candidate solution, that is, replace <math>\mathbf{x}</math> with <math>\mathbf{y}</math> in the population.
* Pick the agent from the population that has the highest fitness or lowest cost and return it as the best found candidate solution.

Note that <math>F \in [0,2]</math> is called the ''differential weight'' and <math>\text{CR} \in [0,1]</math> is called the ''crossover probability'', both these parameters are selectable by the practitioner along with the population size <math>\text{NP} \geq 4</math> see below.

== Parameter selection ==

[[Image:DE Meta-Fitness Landscape (Sphere and Rosenbrock).JPG|thumb|Performance landscape showing how the basic DE performs in aggregate on the Sphere and Rosenbrock benchmark problems when varying the two DE parameters <math>\text{NP}</math> and <math>\text{F}</math>, and keeping fixed <math>\text{CR}</math>=0.9.]]

The choice of DE parameters <math>F, \text{CR}</math> and <math>\text{NP}</math> can have a large impact on optimization performance. Selecting the DE parameters that yield good performance has therefore been the subject of much research. [[Rules of thumb]] for parameter selection were devised by Storn et al.<ref name=storn96usage/><ref name=price05differential/> and Liu and Lampinen.<ref name=liu02setting/> Mathematical convergence analysis regarding parameter selection was done by Zaharie.<ref name=zaharie02critical/> [[Meta-optimization]] of the DE parameters was done by Pedersen <ref name=pedersen08thesis/><ref name=pedersen10good-de/> and Zhang et al.<ref name=zhang11fitting/>

== Variants ==



Variants of the DE algorithm are continually being developed in an effort to improve optimization performance. Many different schemes for performing crossover and mutation of agents are possible in the basic algorithm given above, see e.g.<ref name=storn96usage/> More advanced DE variants are also being developed with a popular research trend being to perturb or adapt the DE parameters during optimization, see e.g. Price et al.,<ref name=price05differential/> Liu and Lampinen,<ref name=liu05fuzzy/> Qin and Suganthan,<ref name=qin05selfadaptive/> Civicioglu <ref name=civici/> and Brest et al.<ref name=brest06selfadapting/>

== See also ==

* [[CMA-ES]]
* [[Artificial bee colony algorithm]]
* [[Evolution strategy]]
* [[Genetic algorithm]]
* [[Differential search algorithm]] <ref name=civici/>
* [[Biogeography-based optimization]]

==References==
{{Reflist|refs=
<ref name=storn97differential>
{{cite journal
|last=Storn
|first=R.
|coauthors=Price, K.
|title=Differential evolution - a simple and efficient heuristic for global optimization over continuous spaces
|journal=Journal of Global Optimization
|year=1997
|volume=11
|pages=341–359
|doi=10.1023/A:1008202821328
}}
</ref>

<ref name=storn96usage>
{{cite conference
|last=Storn
|first=R.
|title=On the usage of differential evolution for function optimization
|booktitle=Biennial Conference of the North American Fuzzy Information Processing Society (NAFIPS)
|year=1996
|pages=519–523
}}
</ref>

<ref name=price05differential>
{{cite book
|title=Differential Evolution: A Practical Approach to Global Optimization
|url=http://www.springer.com/computer/theoretical+computer+science/foundations+of+computations/book/978-3-540-20950-8
|last1=Price
|first1=K.
|last2=Storn
|first2=R.M.
|last3=Lampinen
|first3=J.A.
|year=2005
|publisher=Springer
|isbn=978-3-540-20950-8
}}
</ref>

<ref name=feoktistov06differential>
{{cite book
|title=Differential Evolution: In Search of Solutions
|url=http://www.springer.com/mathematics/book/978-0-387-36895-5
|last=Feoktistov
|first=V.
|year=2006
|publisher=Springer
|isbn=978-0-387-36895-5
}}
</ref>

<ref name=chakraborty08advances>
{{citation
|title=Advances in Differential Evolution
|url=http://www.springer.com/engineering/book/978-3-540-68827-3
|editor-last=Chakraborty
|editor-first=U.K.
|year=2008
|publisher=Springer
|isbn=978-3-540-68827-3
}}
</ref>

<ref name=liu02setting>
{{cite conference
|title=On setting the control parameter of the differential evolution method
|booktitle=Proceedings of the 8th International Conference on Soft Computing (MENDEL)
|last=Liu
|first=J.
|last2=Lampinen
|first2=J.
|year=2002
|pages=11–18
|location=Brno, Czech Republic
}}
</ref>

<ref name=zaharie02critical>
{{cite conference
|title=Critical values for the control parameters of differential evolution algorithms
|booktitle=Proceedings of the 8th International Conference on Soft Computing (MENDEL)
|last=Zaharie
|first=D.
|year=2002
|pages=62–67
|location=Brno, Czech Republic
}}
</ref>

<ref name=brest06selfadapting>
{{cite journal
|last1=Brest
|first1=J.
|last2=Greiner
|first2=S.
|last3=Boskovic
|first3=B.
|last4=Mernik
|first4=M.
|last5=Zumer
|first5=V.
|title=Self-adapting control parameters in differential evolution: a comparative study on numerical benchmark functions
|journal=IEEE Transactions on Evolutionary Computation
|year=2006
|volume=10
|issue=6
|pages=646–657
}}
</ref>

<ref name=qin05selfadaptive>
{{cite conference
|last1=Qin
|first1=A.K.
|last2=Suganthan
|first2=P.N.
|title=Self-adaptive differential evolution algorithm for numerical optimization
|booktitle=Proceedings of the IEEE congress on evolutionary computation (CEC)
|year=2005
|pages=1785–1791
}}
</ref>

<ref name=liu05fuzzy>
{{cite journal
|last1=Liu
|first1=J.
|last2=Lampinen
|first2=J.
|title=A fuzzy adaptive differential evolution algorithm
|journal=Soft Computing
|year=2005
|volume=9
|issue=6
|pages=448–462
}}
</ref>

<ref name=pedersen08thesis>
{{cite book
|type=PhD thesis
|title=Tuning & Simplifying Heuristical Optimization
|url=http://www.hvass-labs.org/people/magnus/thesis/pedersen08thesis.pdf
|last=Pedersen
|first=M.E.H.
|year=2010
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}}

==External links==
* [http://www.icsi.berkeley.edu/~storn/code.html Storn's Homepage on DE] featuring source-code for several programming languages.
* [http://www.sciencedirect.com/science/article/pii/S0957417410010493 Fast DE Algorithm] A Fast Differential Evolution Algorithm using k-Nearest Neighbour Predictor.
* [http://www.sciencedirect.com/science/article/pii/S0957417413000857 MODE Application] Parameter Estimation of a Pressure Swing Adsorption Model for Air Separation Using Multi-objective Optimisation and Support Vector Regression Model.

{{Major subfields of optimization}}

{{DEFAULTSORT:Differential Evolution}}
[[Category:Optimization algorithms and methods]]
[[Category:Evolutionary algorithms]]
[[Category:Mathematical optimization]]
[[Category:Operations research]]

Constant Q transform

2011-12-18T05:01:16Z

69.181.119.41: Undo.

Hello and welcome. My title is Ling. What she loves doing is taking part in croquet and she is attempting to make it a occupation. His day occupation is a monetary officer but he ideas on changing it. Years in the past we moved to Arizona but my wife wants us to transfer. Also visit my web-site; extended car warranty ([http://panda-craft.eu/index.php?mod=users&action=view&id=17668 Full Article])

Template:Quantum mechanics

2008-10-18T01:30:20Z

69.181.118.165: its not h-bar over 2 but simply h-bar

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