An Algorithm Based on the Simulated Annealing Genetic Algorithm for Multiple Sequence Alignment
The mixed algorithms of genetic algorithms and simlutated annealing algorithm are put forward.The new algorithm not only sufficiently exerts the advantages of the two algorithms,but also improves the computing precision and speed.The algorithm simulates the recurrence of nature evolution process,and solves the contradiction between the diversity of population and the convergence speed.The experiment shows that the algorithm is effective.
We present a method for synthesising control strategies for continuous dynamical systems. We use Uppaal Tiga for the synthesis in combination with a set-based Euler method for guaranteeing that the synthesis is safe. We present both a general method and a method which provides tighter bounds for monotone systems. As a case-study, we synthesize a guaranteed safe strategy for a simplified adaptive cruise control application. We show that the guaranteed strategy is only slightly more conservative than the strategy generated in the original adaptive cruise control paper which uses a discrete non guaranteed strategy. Also, we show how reinforcement learning may be used to obtain optimal sub-strategies.