Results 1 to 10 of about 71,942 (280)

Many-objective BAT algorithm. [PDF]

PLoS One, 2020
Dans de nombreux problèmes d'optimisation des objectifs (MaOP), plus de trois objectifs distincts sont optimisés. La partie difficile des MaOP est d'obtenir l'approximation de Pareto (AP) avec une grande diversité et une bonne convergence. Dans la littérature, afin de résoudre la question de la diversité et de la convergence dans les MaOP, de ...
Perwaiz U, Younas I, Anwar AA.
europepmc   +5 more sources

Cloud model bat algorithm. [PDF]

ScientificWorldJournal, 2014
Bat algorithm (BA) is a novel stochastic global optimization algorithm. Cloud model is an effective tool in transforming between qualitative concepts and their quantitative representation. Based on the bat echolocation mechanism and excellent characteristics of cloud model on uncertainty knowledge representation, a new cloud model bat algorithm (CBA ...
Zhou Y, Xie J, Li L, Ma M.
europepmc   +5 more sources

Bat Algorithm for Multi-objective Optimisation [PDF]

International Journal of Bio-Inspired Computation, 2011
Engineering optimization is typically multiobjective and multidisciplinary with complex constraints, and the solution of such complex problems requires efficient optimization algorithms.
Yang, Xin-She
core   +3 more sources

Bat Algorithm: Literature Review and Applications [PDF]

International Journal of Bio-Inspired Computation, 2013
Bat algorithm (BA) is a bio-inspired algorithm developed by Yang in 2010 and BA has been found to be very efficient. As a result, the literature has expanded significantly in the last 3 years.
Yang, Xin-She
core   +3 more sources

A novel hybrid self-adaptive bat algorithm. [PDF]

ScientificWorldJournal, 2014
Nature-inspired algorithms attract many researchers worldwide for solving the hardest optimization problems. One of the newest members of this extensive family is the bat algorithm. To date, many variants of this algorithm have emerged for solving continuous as well as combinatorial problems.
Fister I, Fong S, Brest J, Fister I.
europepmc   +6 more sources

Modified Bat Algorithm

Elektronika ir Elektrotechnika, 2014
Heuristic optimization algorithms which are inspired by nature have become very popular for solving real world problems recently. The use of these algorithms increases day by day in the literature because of their flexible structures and non-containing confusing mathematical terms. One of these algorithms is Bat Algorithm (BA).
KÜÇÜKSİLLE, Ecir Uğur, CENGIZ, Yavuz, Yilmaz, S.   +2 more
openaire   +4 more sources

An improved discrete bat algorithm for symmetric and asymmetric traveling salesman problems [PDF]

, 2015
Bat algorithm is a population metaheuristic proposed in 2010 which is based on the echolocation or bio-sonar characteristics of microbats. Since its first implementation, the bat algorithm has been used in a wide range of fields.
Carballedo, Roberto, Diaz, Fernando, Lopez-Garcia, Pedro, Osaba, Eneko, Yang, Xin-She   +4 more
core   +2 more sources

A first Experimental Investigation of the Practical Efficiency of Battery Scheduling [PDF]

, 2010
Nowadays, mobile devices are used more and more, and their battery lifetime is a key concern. In this paper, we concentrate on a method called battery scheduling with the aim to optimize the battery lifetime of mobile devices.
Graaf, Maurits de, Haverkort, Boudewijn, Hoekstra, Gerard, Jongerden, Marijn, Miliche, Damien   +4 more
core   +13 more sources

Long-term multi-wavelength variability and correlation study of Markarian 421 from 2007 to 2009 [PDF]

, 2016
We study the multi-band variability and correlations of the TeV blazar Mrk 421 on year time scales, which can bring additional insight on the processes responsible for its broadband emission.
Ahnen, M. L., Ansoldi, S., Antonelli, L. A., Antoranz, P., Babic, A., Banerjee, B., Bangale, P., Barrio, J. A., Bednarek, W., Bernardini, E., Biasuzzi, B., Biland, A., Blanch, O., Blinov, D. A., Bonnefoy, S., Bonnoli, G., Borracci, F., Bretz, T., Buson, S., Carosi, A., Chatterjee, A., Chen, W. P., Clavero, R., Colin, P., Colombo, E., Contreras, J. L., Cortina, J., Covino, S., Da Vela, P., Dazzi, F., de Almeida, U. Barres, De Angelis, A., De Lotto, B., Di Pierro, F., Domínguez, A., Dorner, D., Doro, M., Efimova, N. V., Einecke, S., Elsaesser, D., Fernández-Barral, A., Fidalgo, D., Fonseca, M. V., Font, L., Forné, E., Frantzen, K., Fruck, C., Galindo, D., Garcia, J. Rodriguez, Garczarczyk, M., Gaug, M., Giammaria, P., Glawion, D. Eisenacher, Godinović, N., González, J. Becerra, Gora, D., Grishina, T. S., Guberman, D., Hadasch, D., Hahn, A., Hanabata, Y., Hayashida, M., Herrera, J., Hose, J., Hovatta, T., Hrupec, D., Hughes, G., Idec, W., Jordan, B., Kimeridze, G. N., Kodani, K., Konno, Y., Kopatskaya, E. N., Koptelova, E., Kubo, H., Kurtanidze, O. M., Kurtanidze, S. O., Kushida, J., La Barbera, A., Larionov, V. M., Larionova, E. G., Larionova, L. V., Lelas, D., Ligustri, R., Lin, H. C., Lindfors, E., Lombardi, S., Longo, F., Lähteenmaäki, A., López, M., López, R. J. García, López-Coto, R., MAGIC Collaboration, Majumdar, P., Makariev, M., Mallot, K., Maneva, G., Manganaro, M., Mannheim, K., Maraschi, L., Marcote, B., Mariotti, M., Martínez, M., Mazin, D., McBreen, B., Menzel, U., Miranda, J. M., Mirzoyan, R., Moralejo, A., Moretti, E., Moroni, P. G. Prada, Morozova, D. A., Muñoz, A. González, Nakajima, D., Neustroev, V., Niedzwiecki, A., Nikolashvili, M. G., Nilsson, K., Nishijima, K., Noda, K., Nogués, L., Orito, R., Overkemping, A., Paiano, S., Palacio, J., Palatiello, M., Paneque, D., Paoletti, R., Paredes, J. M., Paredes-Fortuny, X., Pedaletti, G., Perri, L., Persic, M., Poutanen, J., Prandini, E., Prester, D. Dominis, Puljak, I., Raiteri, C. M., Rhode, W., Ribó, M., Rico, J., Ros, J. A., Rosillo, M. Nievas, Sadun, A. C., Saito, T., Satalecka, K., Schultz, C., Schweizer, T., Shore, S. N., Sigua, L. A., Sillanpää, A., Sitarek, J., Snidaric, I., Sobczynska, D., Stamerra, A., Steinbring, T., Strzys, M., Takalo, L., Takami, H., Tavecchio, F., Temnikov, P., Terrats, D. Garrido, Terzić, T., Tescaro, D., Teshima, M., Thaele, J., Tornikoski, M., Torres, D. F., Toyama, T., Treves, A., Troitsky, I. S., Verguilov, V., Villata, M., Vovk, I., Ward, J. E., Wilhelmi, E. de Oña, Will, M., Wu, M. H., Zanin, R.   +178 more
core   +4 more sources

BAT-BP: A new BAT based back-propagation algorithm for efficient data classification [PDF]

, 2016
Training neural networks particularly back propagation algorithm is a complex task of great importance in the field of supervised learning. One of the nature inspired meta-heuristic Bat algorithm is becoming a popular method in solving many complex ...
Hafifi, Nurfarian, Khan, Abdullah, M. Z., Rehman, Mohd. Nawi, Nazri, Siming, Insaf Ali   +4 more
core   +1 more source