Monte Carlo Statistical Methods (Springer Texts in Statistics)
Monte Carlo Statistical Methods (Springer Texts in Statistics)
Solving the nonlinear complementarity problem via an aggregate homotopy method
International Journal of Computer Applications in Technology
An evolutionary linear programming algorithm for solving the stock reduction problem
International Journal of Computer Applications in Technology
Research for the screw thread intensity of the fibreglass oil tubing
International Journal of Computer Applications in Technology
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This paper describes a mathematical model of hydrodynamic torque converter applied to construction optimisation using a genetic algorithm as an optimisation method. The model estimation was performed for a pre-selected hydrodynamic torque converter. A modelling error of steady-state characteristic was considered as the quality criterion. During estimation calculations, the Monte Carlo method and a genetic algorithm were applied as optimisation methods. Verification of the applied mathematical model of hydrodynamic torque converter revealed a modelling error of about 5.8%.