Sentence examples for stochastic strategy from inspiring English sources

A numerical stochastic strategy for optimising composite elastic shells undergoing buckling is presented.

Method 2 is a ranking method of possibility degrees with a stochastic strategy and enriches the comparisons among the expected losses.

Therefore, they tend to choose between a deterministic strategy (i.e. with the use of sheepdogs) and a stochastic strategy (i.e. without sheepdogs) which may or may not result in herd losses.

Different from the existing stochastic strategy that keeps the forward velocity constant and controls only the angular velocity, we design a stochastic extremum seeking controller to regulate both forward and angular velocities simultaneously in this work.

The evolutionary approach (EA), which is based on genetic algorithms (GA), is a well-proven stochastic strategy here used as a reference to evaluate our library optimization method (CLOM), which is based upon the optimal design of experiments (ODOE).

Another important conclusion is that the number of solutions is significantly more predictable in the case of α-stable mutation, which is a very advantageous feature from the point of view of the application of a stochastic strategy in the inverse problem solution.

Core of this study is to consider the design problems for the residual generator and residual evaluation under two well-developed model-based FD strategies, i.e. deterministic and stochastic strategies.

However, these methods have not been applied and compared with respect to other stochastic strategies such as Simulated Annealing (SA), Differential Evolution (DE) and Genetic Algorithm (GA) in the context of parameter estimation for VLE data modeling.

Many problems are not that well-defined so stochastic strategies are popular including stochastic gradient descent [ 21], simulated annealing [ 22- 24], evolutionary computation [ 25], and other heuristics.

As the local optimum found strongly depends on some initial guess, such approaches are often combined with stochastic strategies to achieve some desired global property [ 11- 13].

However, both HASH and HapCut algorithms use stochastic strategies and therefore are not guaranteed to find optimal solutions for the haplotype assembly problem.