Monte Carlo methods and applications : proceedings of the 8th IMACS Seminar on Monte Carlo Methods, August 29-September 2, 2011, Borovets, Bulgaria / edited by Karl K. Sabelfeld, Ivan Dimov.

"This is the proceedings of the "8th IMACS Seminar on Monte Carlo Methods" held from August 29 to September 2, 2011 in Borovets, Bulgaria, and organized by the Institute of Information and Communication Technologies of the Bulgarian Academy of Sciences in cooperation with the Internat...

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Bibliographic Details
Corporate Author: IMACS Seminar on Monte Carlo Methods Borovet︠s︡, Bulgaria
Other Authors: Sabelʹfelʹd, K. K. (Karl Karlovich) (Editor), Dimov, Ivan, 1963- (Editor)
Format: eBook
Language:English
Published: Berlin : De Gruyter, 2013.
Series:Proceedings in mathematics.
Subjects:
Online Access:Click for online access

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111 2 |a IMACS Seminar on Monte Carlo Methods  |n (8th :  |d 2011 :  |c Borovet︠s︡, Bulgaria) 
245 1 0 |a Monte Carlo methods and applications :  |b proceedings of the 8th IMACS Seminar on Monte Carlo Methods, August 29-September 2, 2011, Borovets, Bulgaria /  |c edited by Karl K. Sabelfeld, Ivan Dimov. 
260 |a Berlin :  |b De Gruyter,  |c 2013. 
300 |a 1 online resource (xiii, 233 pages) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a De Gruyter proceedings in mathematics 
504 |a Includes bibliographical references. 
520 |a "This is the proceedings of the "8th IMACS Seminar on Monte Carlo Methods" held from August 29 to September 2, 2011 in Borovets, Bulgaria, and organized by the Institute of Information and Communication Technologies of the Bulgarian Academy of Sciences in cooperation with the International Association for Mathematics and Computers in Simulation (IMACS). Included are 24 papers which cover all topics presented in the sessions of the seminar: stochastic computation and complexity of high dimensional problems, sensitivity analysis, high-performance computations for Monte Carlo applications, stochastic metaheuristics for optimization problems, sequential Monte Carlo methods for large-scale problems, semiconductor devices and nanostructures."--Publisher's website. 
588 0 |a Print version record. 
505 0 |a Preface; 1 Improvement of Multi-population Genetic Algorithms Convergence Time; 1.1 Introduction; 1.2 Short Overview of MpGA Modifications; 1.3 Parameter Identification of S. cerevisiae Fed-Batch Cultivation Using Different Kinds of MpGA; 1.4 Analysis and Conclusions; 2 Parallelization and Optimization of 4D Binary Mixture Monte Carlo Simulations Using Open MPI and CUDA; 2.1 Introduction; 2.2 The Metropolis Monte Carlo Method; 2.3 Decomposition into Subdomains and the Virtual Topology Using OpenMPI; 2.4 Management of Hypersphere Coordinate Migration Between Domains. 
505 8 |a 2.4.1 Communication between the CPU and the GPU2.5 Pseudorandom Number Generation; 2.6 Results of Running the Modified Code; 2.7 Conclusions; 3 Efficient Implementation of the Heston Model Using GPGPU; 3.1 Introduction; 3.2 Our GPGPU-Based Algorithm for Option Pricing; 3.3 Numerical Results; 3.4 Conclusions and Future Work; 4 On a Game-Method for Modeling with Intuitionistic Fuzzy Estimations. Part 2; 4.1 Introduction; 4.2 Short Remarks on the Game-Method for Modeling from Crisp Point of View; 4.3 On the Game-Method for Modeling with Intuitionistic Fuzzy Estimations; 4.4 Main Results. 
505 8 |a 4.5 Conclusion5 Generalized Nets, ACO Algorithms, and Genetic Algorithms; 5.1 Introduction; 5.2 ACO and GA; 5.3 GN for Hybrid ACO-GA Algorithm; 5.4 Conclusion; 6 Bias Evaluation and Reduction for Sample-Path Optimization; 6.1 Introduction; 6.2 Problem Formulation; 6.3 Taylor-Based Bias Correction; 6.4 Impact on the Optimization Bias; 6.5 Numerical Experiments; 6.6 Conclusions; 7 Monte Carlo Simulation of Electron Transport in Quantum Cascade Lasers; 7.1 Introduction; 7.2 QCL Transport Model; 7.2.1 Pauli Master Equation; 7.2.2 Calculation of Basis States; 7.2.3 Monte Carlo Solver. 
505 8 |a 7.3 Results and Discussion7.4 Conclusion; 8 Markov Chain Monte Carlo Particle Algorithms for Discrete-Time Nonlinear Filtering; 8.1 Introduction; 8.2 General Particle Filtering Framework; 8.3 High Dimensional Particle Schemes; 8.3.1 Sequential MCMC Filtering; 8.3.2 Efficient Sampling in High Dimensions; 8.3.3 Setting Proposal and Steering Distributions; 8.4 Illustrative Examples; 8.5 Conclusions; 9 Game-Method for Modeling and WRF-Fire Model Working Together; 9.1 Introduction; 9.2 Description of the Game-Method for Modeling. 
505 8 |a 9.3 General Description of the Coupled Atmosphere Fire Modeling and WRF-Fire9.4 Wind Simulation Approach; 9.5 Conclusion; 10 Wireless Sensor Network Layout; 10.1 Introduction; 10.2 Wireless Sensor Network Layout Problem; 10.3 ACO for WSN Layout Problem; 10.4 Experimental Results; 10.5 Conclusion; 11 A Two-Dimensional Lorentzian Distribution for an Atomic Force Microscopy Simulator; 11.1 Introduction; 11.2 Modeling Oxidation Kinetics; 11.3 Development of the Lorentzian Model; 11.3.1 Algorithm for the Gaussian Model; 11.3.2 Development of the Lorentzian Model; 11.4 Conclusion. 
546 |a In English. 
650 0 |a Monte Carlo method  |v Congresses. 
650 0 |a Mathematics  |v Congresses. 
650 7 |a MATHEMATICS  |x Numerical Analysis.  |2 bisacsh 
650 7 |a Mathematics  |2 fast 
650 7 |a Monte Carlo method  |2 fast 
655 7 |a Conference papers and proceedings  |2 fast 
700 1 |a Sabelʹfelʹd, K. K.  |q (Karl Karlovich),  |e editor. 
700 1 |a Dimov, Ivan,  |d 1963-  |e editor. 
776 0 8 |i Print version:  |a IMACS Seminar on Monte Carlo Methods (8th : 2011 : Borovet︠s, Bulgaria).  |t Monte Carlo methods and applications.  |d [Berlin] : De Gruyter, 2013  |z 9783110293470  |w (OCoLC)816818796 
830 0 |a Proceedings in mathematics. 
856 4 0 |u https://ebookcentral.proquest.com/lib/holycrosscollege-ebooks/detail.action?docID=893307  |y Click for online access 
903 |a EBC-AC 
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