SO (complexity): Difference between revisions

From formulasearchengine
Jump to navigation Jump to search
Newer edit →
en>They
 
en>Yobot
m Reference before punctuation detected and fixed using AWB (9585)
Line 1: Line 1:
Break the difficulties of conformity as well as go all from a biking journey. Each hole is made up differently and your driver is not always the best way to start a hole. Check out bicycle repair tool reviews of the most popular tools that provide the best value for your dollar. noted, Valhalla was designed "by the people from Whistler" (the company Gravity Logic) so "it's special. Why would I want to change, even for a day, the most important and shaping event in my life. <br><br>
Bat-inspired algorithm is a [[metaheuristic]] [[optimization]] algorithm developed by Xin-She Yang in 2010.<ref>X. S. Yang, A New Metaheuristic Bat-Inspired Algorithm, in: Nature Inspired Cooperative Strategies for Optimization (NISCO 2010) (Eds. J. R. Gonzalez et al.), Studies
in Computational Intelligence, Springer Berlin, 284, Springer, 65-74 (2010). http://arxiv.org/abs/1004.4170</ref> This '''bat algorithm''' is based on the echolocation behaviour of [[microbats]] with varying pulse rates of emission and loudness.<ref>J. D. Altringham, Bats: Biology and Behaviour, Oxford University Press, (1996).</ref><ref>P. Richardson, Bats. Natural History Museum, London, (2008)</ref>


You can choose from many different suspensions on your bike, make sure the suspension you choose is going to fit the type of cycling you intend for it. 3 width are versatile, and can be used on low mountain trails and the alpencross. From free shipping on all the bikes across the US, the Road Bike Outlet makes consumers happy anywhere within 1 to 6 days. &ldquo;Whereas past research emphasized whether or not a relationship existed between bicycle riding on a saddle and erectile dysfunction, Schrader now says that the next step of contemporary research on the subject should focus on intervention. 4" wide Schwalbe that can run at 25 psi to behave as passive suspension. <br><br>However, they offer more versatility to riders as they can increase the amount of air to increase the pressure, making it harder to compress. Here are some of the more popular mountain bike wheels now available [*CO]. It is meant for leisurely riding, and some mountain biking. The bicycle you have to choose should be under the budget, saving enough for you to buy the necessary accessories for your men's mountain bike, like helmet, gloves, eye gear, etc. The users can enjoy these stills when travelling and offline as well. <br><br>Read product reviews and cycling magazines, research online, and ask for advice at your local bike shop. Cold and long winters at high altitude are perfect conditions for winter recreation. If the metal tubing below the paint has become exposed, then touch this up with a dab of enamel paint, using a very fine brush. There is no shortage of videos of mountain bike crashes from around the world, with many riders with appropriate safety equipment escaping serious injury, while others were not that fortunate. Cross country Nearly all of the mountain bikes available could be classed as cross country. <br><br>Getting stuck in a trap is one way beginners kill their scores.  For more in regards to [http://www.supershootergames.com/profile/motalbot Cannondale mountain bike sizing.] stop by our web site. They get used on the street which is not what it's built for. If riding on public roads in Australia, then the maximum motor wattage is 250W and the bike also then becomes speed limited. Suspension: Road bikes are built with a sole purpose of providing greater speed; they do not possess this feature, although they have certain materials which absorb the shocks of the uneven roads. They will provide you with a honest price, yet be ready to pay in between $650 and $4,000 on dual suspensions and in between $470 and $670 for hardtails.
== Algorithm Description ==
 
The idealization of the [[Animal echolocation|echolocation]] of microbats can be summarized as follows: Each virtual bat flies randomly with a velocity <math>v_i</math> at position (solution) <math>x_i</math> with a varying frequency or wavelength and loudness <math>A_i</math>. As it searches and finds its prey, it changes frequency, loudness and pulse emission rate <math>r</math>. Search is intensified by a local [[random walk]]. Selection of the best continues until certain stop criteria are met. This essentially uses a frequency-tuning technique to control the dynamic behaviour of a swarm of bats, and the balance between exploration and exploitation can be controlled by tuning algorithm-dependent parameters in bat algorithm.
 
A detailed introduction of metaheuristic algorithms including the bat algorithm is given by Yang <ref>Yang, X. S., Nature-Inspired Metaheuristic Algoirthms, 2nd Edition, Luniver Press, (2010).</ref> where a demo program in Matlab/Octave is available, while a comprehensive review is carried out by Parpinelli and Lopes.<ref>Parpinelli, R. S., and Lopes, H. S., New inspirations in swarm intelligence: a survey,Int. J. Bio-Inspired Computation, Vol. 3, 1-16 (2011).</ref> A further improvement is the development of an evolving bat algorithm (EBA) with better efficiency.<ref>P. W. Tsai, J. S. Pan, B. Y. Liao, M. J. Tsai, V. Istanda, Bat algorithm inspired algorithm for solving numerical optimization problems, Applied Mechanics and Materials, Vo.. 148-149, pp.134-137 (2012).</ref>
 
A Matlab demo is available at the Matlab exchange<ref>here http://www.mathworks.com/matlabcentral/fileexchange/37582</ref>
 
== Multi-objective Bat Algorithm (MOBA) ==
Using a simple weighted sum with random weights, a very effective but yet simple multiobjective bat algorithm (MOBA) has been developed to solve multiobjective engineering design tasks.<ref>X. S. Yang, bat algorithm for multi-objective optimisation, Int. J. Bio-Inspired Computation, Vol. 3, 267-274 (2011).</ref>  Another multiobjective bat algorithm by combining bat algorithm with
NSGA-II produces very competitive results with good efficiency.<ref>T. C. Bora, L. S. Coelho, L. Lebensztajn, Bat-inspired optimization
approach for the brushless DC wheel motor problem, IEEE Trans. Magnetics, Vol. 48 (2), 947-950 (2012).</ref>
 
== Applications ==
Bat algorithm has been used for engineering design,<ref>X. S. Yang and A. H. Gandomi, Bat algorithm: a novel approach for global engineering optimization, Engineering Computations, Vol. 29, No. 5, pp. 464-483 (2012).</ref> classifications.<ref>S. Mishra, K. Shaw, D. Mishra, A new metaheuristic classification approach for microarray data,Procedia Technology, Vol. 4, pp. 802-806 (2012).</ref>
A fuzzy bat clustering method has been developed to solve ergonomic workplace problems<ref>Khan, K., Nikov, A., Sahai A., A Fuzzy Bat Clustering Method for Ergonomic Screening of Office Workplaces,S3T 2011,
Advances in Intelligent and Soft Computing, 2011, Volume 101/2011, 59-66 (2011).</ref>
An interesting approach using fuzzy systems and bat algorithm has shown
a reliable match between prediction and actual data for exergy modelling.<ref>T. A. Lemma, Use of fuzzy systems and bat algorithm for exergy modelling in a gas turbine generator, IEEE Colloquium on Humanities, Science and Engineering (CHUSER'2011), pp. 305-310 (2011).</ref>
 
A detailed comparison of bat algorithm (BA) with genetic algorithm (GA), PSO and  other methods for training feed forward neural networks concluded clearly that BA has  advantages over other algorithms.<ref>K. Khan and A. Sahai, A comparison of BA, GA, PSO, BP and LM for
training feed forward neural networks in e-learning context, Int. J. Intelligent Systems and Applications (IJISA), Vol. 4, No. 7, pp. 23-29 (2012).</ref>
 
== References ==
{{Reflist|33em}}
 
{{swarming}}
 
[[Category:Heuristic algorithms]]
[[Category:Evolutionary algorithms]]

Revision as of 10:37, 8 November 2013

Bat-inspired algorithm is a metaheuristic optimization algorithm developed by Xin-She Yang in 2010.[1] This bat algorithm is based on the echolocation behaviour of microbats with varying pulse rates of emission and loudness.[2][3]

Algorithm Description

The idealization of the echolocation of microbats can be summarized as follows: Each virtual bat flies randomly with a velocity at position (solution) with a varying frequency or wavelength and loudness . As it searches and finds its prey, it changes frequency, loudness and pulse emission rate . Search is intensified by a local random walk. Selection of the best continues until certain stop criteria are met. This essentially uses a frequency-tuning technique to control the dynamic behaviour of a swarm of bats, and the balance between exploration and exploitation can be controlled by tuning algorithm-dependent parameters in bat algorithm.

A detailed introduction of metaheuristic algorithms including the bat algorithm is given by Yang [4] where a demo program in Matlab/Octave is available, while a comprehensive review is carried out by Parpinelli and Lopes.[5] A further improvement is the development of an evolving bat algorithm (EBA) with better efficiency.[6]

A Matlab demo is available at the Matlab exchange[7]

Multi-objective Bat Algorithm (MOBA)

Using a simple weighted sum with random weights, a very effective but yet simple multiobjective bat algorithm (MOBA) has been developed to solve multiobjective engineering design tasks.[8] Another multiobjective bat algorithm by combining bat algorithm with NSGA-II produces very competitive results with good efficiency.[9]

Applications

Bat algorithm has been used for engineering design,[10] classifications.[11] A fuzzy bat clustering method has been developed to solve ergonomic workplace problems[12] An interesting approach using fuzzy systems and bat algorithm has shown a reliable match between prediction and actual data for exergy modelling.[13]

A detailed comparison of bat algorithm (BA) with genetic algorithm (GA), PSO and other methods for training feed forward neural networks concluded clearly that BA has advantages over other algorithms.[14]

References

43 year old Petroleum Engineer Harry from Deep River, usually spends time with hobbies and interests like renting movies, property developers in singapore new condominium and vehicle racing. Constantly enjoys going to destinations like Camino Real de Tierra Adentro.

Template:Swarming

  1. ↑ X. S. Yang, A New Metaheuristic Bat-Inspired Algorithm, in: Nature Inspired Cooperative Strategies for Optimization (NISCO 2010) (Eds. J. R. Gonzalez et al.), Studies in Computational Intelligence, Springer Berlin, 284, Springer, 65-74 (2010). http://arxiv.org/abs/1004.4170
  2. ↑ J. D. Altringham, Bats: Biology and Behaviour, Oxford University Press, (1996).
  3. ↑ P. Richardson, Bats. Natural History Museum, London, (2008)
  4. ↑ Yang, X. S., Nature-Inspired Metaheuristic Algoirthms, 2nd Edition, Luniver Press, (2010).
  5. ↑ Parpinelli, R. S., and Lopes, H. S., New inspirations in swarm intelligence: a survey,Int. J. Bio-Inspired Computation, Vol. 3, 1-16 (2011).
  6. ↑ P. W. Tsai, J. S. Pan, B. Y. Liao, M. J. Tsai, V. Istanda, Bat algorithm inspired algorithm for solving numerical optimization problems, Applied Mechanics and Materials, Vo.. 148-149, pp.134-137 (2012).
  7. ↑ here http://www.mathworks.com/matlabcentral/fileexchange/37582
  8. ↑ X. S. Yang, bat algorithm for multi-objective optimisation, Int. J. Bio-Inspired Computation, Vol. 3, 267-274 (2011).
  9. ↑ T. C. Bora, L. S. Coelho, L. Lebensztajn, Bat-inspired optimization approach for the brushless DC wheel motor problem, IEEE Trans. Magnetics, Vol. 48 (2), 947-950 (2012).
  10. ↑ X. S. Yang and A. H. Gandomi, Bat algorithm: a novel approach for global engineering optimization, Engineering Computations, Vol. 29, No. 5, pp. 464-483 (2012).
  11. ↑ S. Mishra, K. Shaw, D. Mishra, A new metaheuristic classification approach for microarray data,Procedia Technology, Vol. 4, pp. 802-806 (2012).
  12. ↑ Khan, K., Nikov, A., Sahai A., A Fuzzy Bat Clustering Method for Ergonomic Screening of Office Workplaces,S3T 2011, Advances in Intelligent and Soft Computing, 2011, Volume 101/2011, 59-66 (2011).
  13. ↑ T. A. Lemma, Use of fuzzy systems and bat algorithm for exergy modelling in a gas turbine generator, IEEE Colloquium on Humanities, Science and Engineering (CHUSER'2011), pp. 305-310 (2011).
  14. ↑ K. Khan and A. Sahai, A comparison of BA, GA, PSO, BP and LM for training feed forward neural networks in e-learning context, Int. J. Intelligent Systems and Applications (IJISA), Vol. 4, No. 7, pp. 23-29 (2012).
Retrieved from "https://en.formulasearchengine.com/index.php?title=SO_(complexity)&oldid=25709"