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  • Search: isPartOf:"Mathematics and Computers in Simulation (MATCOM)"
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Simulation 66 Stability 43 Neural networks 34 Finite element method 29 Solitons 26 Monte Carlo 23 Inverse problem 22 Optimization 22 Computer algebra 21 Monte Carlo method 21 Solitary waves 20 Chaos 19 Modelling 19 Monte Carlo simulation 19 Synchronization 18 Computer simulation 15 Domain decomposition 15 Finite volume method 15 Bifurcation 14 Convergence 14 Lattice Boltzmann method 14 Monte Carlo methods 14 Partial differential equations 14 Soliton 14 Finite elements 13 Fuzzy logic 13 GARCH 13 Numerical integration 13 Numerical simulation 13 Adaptive control 12 Bootstrap 12 Cointegration 12 Modeling 12 Optimal control 12 Sensitivity analysis 12 Genetic algorithm 11 Genetic algorithms 11 Neural network 11 Nonlinear systems 11 Parameter estimation 11
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Undetermined 4,054
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Article 4,054
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McAleer, Michael 54 Kevrekidis, P.G. 17 Oxley, Les 17 Vichnevetsky, R. 16 Mesnard, Guy 15 Tzafestas, S.G. 15 Evans, D.J. 14 Jakeman, A.J. 14 Korn, Granino A. 14 Roanes-Lozano, Eugenio 14 Chang, Chia-Lin 12 Pasadas, M. 12 Taha, Thiab R. 12 Ames, W.F. 11 Brezinski, C. 11 Laita, Luis M. 10 McKenzie, C.R. 10 Ohkita, Masaaki 10 Van Remoortere, P. 10 Al-Haddad, Kamal 8 Chan, Felix 8 Christov, C.I. 8 Hadjidimos, A. 8 Lim, Christine 8 Malomed, B.A. 8 Nedjalkov, M. 8 Sbibih, D. 8 Walter, Eric 8 Adomian, G. 7 Chan, W.S. 7 Egidi, N. 7 Frantzeskakis, D.J. 7 Hernando, Antonio 7 Kosina, H. 7 Ludu, A. 7 Maponi, P. 7 Steinberg, Stanly 7 Aiyoshi, Eitaro 6 Borne, Pierre 6 Carver, M.B. 6
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Mathematics and Computers in Simulation (MATCOM) 4,054
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Showing 3,511 - 3,520 of 4,054
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Modeling and simulation as a tool for optimizing the treatment of tumor diseases
Düchting, Werner; Vogelsaenger, Thomas - In: Mathematics and Computers in Simulation (MATCOM) 24 (1982) 6, pp. 548-557
The main point of this paper is to show how ideas of control theory, automata theory and computer science can be applied to the field of oncology. We are stressing the modeling of three-dimensional tumor growth and the simulation of different kinds of tumor therapy (restricted energy supply,...
Persistent link: https://www.econbiz.de/10011050873
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Simulation and optimal control of large water distribution systems
Gyergyek, L.; Pres̆ern, S. - In: Mathematics and Computers in Simulation (MATCOM) 24 (1982) 5, pp. 385-392
In effective planning a new water distribution system or enlarging an existing one we need to simulate the circumstances of the system on a computer and determine the best possible solutions. On the other hand if we have an existing water distribution system we want to run it as optimally as...
Persistent link: https://www.econbiz.de/10011051064
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Asymptotic behavior and best approximation in computational fluid dynamics
Cheng, Sin-I. - In: Mathematics and Computers in Simulation (MATCOM) 24 (1982) 1, pp. 37-48
Computational fluid dynamics has many successes for the solution of simple standard problems. For relatively complex problems, especially if nonlinear and of mixed type, the computed approximate solutions are mostly of dubious accuracy and credibility. The difficulty appears fundamental. Model...
Persistent link: https://www.econbiz.de/10011051110
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Software for solving identification and identifiability problems, E.G. in compartmental systems
Pohjanpalo, H.; Wahlström, B. - In: Mathematics and Computers in Simulation (MATCOM) 24 (1982) 6, pp. 490-493
The identification problem for a system with a known structure is considered. The mathematical background of the identifiability problem is shortly discussed. Two minicomputer programs which have been used in several studies to solve the identifiability and the identification problem for...
Persistent link: https://www.econbiz.de/10011051131
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Manipulation robots: Computer aided design and control synthesis
Vukobratović, M.; Cvetković, V. - In: Mathematics and Computers in Simulation (MATCOM) 24 (1982) 4, pp. 292-302
Concept and brief description of major program modules for realization of general manipulation system “simulator”, i.e. programming system for the design, dynamic analysis, synthesis and verification of control algorithms for manipulation systems of arbitrary mechanical configuration is...
Persistent link: https://www.econbiz.de/10011051216
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Parameter identifiability for partial differential equations
Travis, C.C.; White, L.W. - In: Mathematics and Computers in Simulation (MATCOM) 24 (1982) 6, pp. 487-489
Persistent link: https://www.econbiz.de/10010748507
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Modeling cellular agign and tumorigenic transformation
Witten, Matthew - In: Mathematics and Computers in Simulation (MATCOM) 24 (1982) 6, pp. 572-584
Numerous diverse mathematical models have been proposed, in an effort to explain and study the variety of aging processes which occur at the cellular level. This paper will detail the formalization of a framework for studying the propagation of a collection of biological properties through an...
Persistent link: https://www.econbiz.de/10010748593
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The effect of fresh water discharges from artificial reservoirs on the water quality in a polluted river
Nihoul, Jacques C.J. - In: Mathematics and Computers in Simulation (MATCOM) 24 (1982) 2, pp. 204-207
Persistent link: https://www.econbiz.de/10010748642
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Early desire
Korn, Granino A. - In: Mathematics and Computers in Simulation (MATCOM) 24 (1982) 1, pp. 30-36
EARLY DESIRE (Direct Executing SImulation in REal time) is the first of a series of entirely new floating-point equation-language systems for interactive continuous-system simulation. DESIRE systems combine high computing speed (1.3 to 4 times faster that threaded FORTRAN) with immediate direct...
Persistent link: https://www.econbiz.de/10010748646
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Optimal multicompartmental sampling designs for parameter estimation: Practical aspects of the identification problem
Landaw, Elliot M. - In: Mathematics and Computers in Simulation (MATCOM) 24 (1982) 6, pp. 525-530
A computer program is described for the determination of optimal multicompartmental sampling designs as a handle on numerical identifiability. A design measure approach is used which automatically chooses the number of sample times and sites of sampling. A two-input four-pool output example is...
Persistent link: https://www.econbiz.de/10010748661
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