Evolution of Simulation

Finite element simulation of microstructure evolution during friction stir welding of automotive aluminum parts

7000 series Aluminum alloys are widely used in the automotive industries for structural lightweight components due to their exceptional high strength to weight ratio. However, this class of aluminum alloy is difficult to join by conventional fusion welding techniques so Friction stir welding (FSW) widely is used for welding this alloys. The process has been demonstrated to be effective and is c...

Fuzzy logic controlled differential evolution to solve economic load dispatch problems

In recent years, soft computing methods have generated a large research interest. The synthesis of the fuzzy logic and the evolutionary algorithms is one of these methods. A particular evolutionary algorithm (EA) is differential evolution (DE). As for any EA, DE algorithm also requires parameters tuning to achieve desirable performance. In this paper tuning the perturbation factor vector of DE ...

Cooperative Co-Evolving Neural Networks for Robosoccer Simulation

Fuzzy logic controlled differential evolution to solve economic load dispatch problems

In recent years, soft computing methods have generated a large research interest. The synthesis of the fuzzy logic and the evolutionary algorithms is one of these methods. A particular evolutionary algorithm (EA) is differential evolution (DE). As for any EA, DE algorithm also requires parameters tuning to achieve desirable performance. In this paper tuning the perturbation factor vector of DE ...

Wave Evolution in Water Bodies using Turbulent MPS Simulation

Moving Particle Semi-implicit (MPS) which is a meshless and full Lagrangian method is employed to simulate nonlinear hydrodynamic behavior in a wide variety of engineering application including free surface water waves. In the present study, a numerical particle-based model is developed by the authors using MPS method to simulate different wave problems in the coastal waters. In this model flui...

Increasing the Accuracy of Recommender Systems Using the Combination of K-Means and Differential Evolution Algorithms

Recommender systems are the systems that try to make recommendations to each user based on performance, personal tastes, user behaviors, and the context that match their personal preferences and help them in the decision-making process. One of the most important subjects regarding these systems is to increase the system accuracy which means how much the recommendations are close to the user int...