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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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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 2,651 - 2,660 of 4,054
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Some applications of computer algebra to problems in theoretical physics
Eilbeck, J.C.; Enol'skii, V.Z. - In: Mathematics and Computers in Simulation (MATCOM) 40 (1996) 3, pp. 443-452
We consider some examples of the use of computer algebra packages, specifically Maple and Mathematica, applied to some problems in integrable and nonintegrable systems in nonlinear continuous and lattice wave models.
Persistent link: https://www.econbiz.de/10010870524
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Model based control of a one degree of freedom workpiece manipulator for welding of nozzles
Lauridsen, J.K.; Madsen, O.; Holm, H.; Hafsteinsson, I.; … - In: Mathematics and Computers in Simulation (MATCOM) 41 (1996) 5, pp. 407-417
This paper presents an automatic control system for welding the root-pass in a seam joining a nozzle perpendicular onto a large diameter pipe. The system is based on the use of a geometry model of the welding seam and on inverse welding process models (i.e. models that map desired weld quality,...
Persistent link: https://www.econbiz.de/10010870541
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Mapping disease risk using a joint probability distribution
Hollinger, Steven E.; Kuchar, Leszek - In: Mathematics and Computers in Simulation (MATCOM) 42 (1996) 2, pp. 293-298
A major determinant of plant disease occurrence is the temperature and relative humidity experienced during the growing season. Historical temperature and relative humidity data may be used to determine the probable risk of specific crop diseases occurring in a particular region or country....
Persistent link: https://www.econbiz.de/10010870552
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A real-time simulator of the perceptive system of a mobile vehicle
Gharapetian, VahéDer; Rombaut, Michèle - In: Mathematics and Computers in Simulation (MATCOM) 41 (1996) 3, pp. 321-328
Simulating a dynamic complex system consists in splitting the system into a number of elementary pieces and describing the behavior of each element and the interactions between these elements during a finite interval of time. Simulation is useful when the real system is not always available or...
Persistent link: https://www.econbiz.de/10010870571
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The CRONE path planning
Oustaloup, A.; Linarès, H. - In: Mathematics and Computers in Simulation (MATCOM) 41 (1996) 3, pp. 209-217
This article presents a trajectory planning strategy with a time law which, using a generalized potential, makes it possible to take into account the risk presented by each obstacle. Section 2 defines the generalized potential at a given point created by an obstacle, the risk coefficient of...
Persistent link: https://www.econbiz.de/10010870583
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Power and limitations of model based bioprocess optimization
Impe, Jan F.M. Van - In: Mathematics and Computers in Simulation (MATCOM) 42 (1996) 2, pp. 159-169
Since the last few decades the application of system theory concepts and modern model based control techniques to the optimization of biotechnological processes has received a lot of attention. This represents a challenging field of research for the following reasons. First, the dynamics of...
Persistent link: https://www.econbiz.de/10010870630
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Application of a neural network based classifier system to AGV obstacle avoidance
Ball, N.R. - In: Mathematics and Computers in Simulation (MATCOM) 41 (1996) 3, pp. 285-296
This paper describes the application of a neural network based classifier system to the control of a simulated autonomous guided vehicle (AGV) in a simple obstacle avoidance task. A mechanism for concurrent exploration and exploitation of a maze environment based on Kohonen feature maps is...
Persistent link: https://www.econbiz.de/10010870633
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Parameter estimation in dynamic systems
Stortelder, Walter J.H. - In: Mathematics and Computers in Simulation (MATCOM) 42 (1996) 2, pp. 135-142
In this paper we present an approach to the solution of parameter estimation problems in systems described mathematically by differential algebraic equations. The numerical solution of these equations is compared with measurements from experiments. By adaptation of the parameters in the...
Persistent link: https://www.econbiz.de/10010870661
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Computer algebra and differential equations
MacCallum, M.A.H. - In: Mathematics and Computers in Simulation (MATCOM) 42 (1996) 4, pp. 385-386
Persistent link: https://www.econbiz.de/10010870683
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Quantitative aspects of sustainable agriculture
Richter, O.; Seppelt, R. - In: Mathematics and Computers in Simulation (MATCOM) 42 (1996) 2, pp. 263-269
Control theory provides methods to calculate optimal control of agricultural ecosystems based on dynamic models. Optimization problems formulated with these models can focus either on small time scales (one vegetation period) or significant larger scales (crop rotations). Performance criteria...
Persistent link: https://www.econbiz.de/10010870708
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