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In this paper, we present an algorithm to improve the reliability of digital combinational circuits based on evolutionary approach.
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Novel control approaches based on evolutionary mismatches – A species that evolves in one part of the world is unlikely to be perfectly suited to conditions within some other area that it invades.
In this study, we developed an original distributed approach based on evolutionary cooperative algorithms driven by agents' communication.
In this paper, a novel simulation approach based on evolutionary facts called MLP FFA is adopted in this study for the simulation processes.
The proposed Fuzzy CA (FCA) model adopts a data-driven approach, based on evolutionary optimization, which allows incorporating knowledge from real wildfires in order to enhance its accuracy.
In order to be able to solve the optimization model for realistic large systems, a metaheuristic approach based on evolutionary algorithms is developed.
A multi-objective optimization approach based on evolutionary algorithms is used to find the Pareto surface that minimizes the mass and maximizes the damping.
We propose a Visual Learning approach based on evolutionary computation that solves the first two tasks simultaneously using a single evolving process.
This work presents a new approach, based on evolutionary polynomial regression (EPR), for developing a simple and easy-to-use formula for prediction of ultimate pure bending of steel circular tubes.
These forms are based on evolutionary considerations, while for our approach, which is based on the present state of correlations, the Hamming distance is the metric of choice.
We believe it provides a promising approach, based on evolutionary game theory, for including the behavior dynamics into epidemic transmission models.
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