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Since initial solutions constructed by the CS algorithm are improved using a local search technique such as random pair-wise exchange method used in the SA algorithm, they are subject to randomly change at each iteration of the SA method.
They must also be reversible in order to use the SA method.
The SA method offers an excellent alternative in designing phase II trials with continuous monitoring.
These algorithms resemble in their structure the formerly studied TA and the SA method.
VT values from the SA method demonstrated an overall constant and small negative bias (−0.76%) compared to theoretical values.
The algorithm for FLC optimal tuning based on the SA method is applied and the resulting controller parameters are set.
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The temporal autocorrelation (TA) for lag τ and the SA methods are defined as shown in Equations 1 and 2 [18] 18].
It is concluded that the refined SA method possesses the advantages of the traditional SA method, whereas it does not exhibit its unacceptable inaccuracies.
The former SA method allows the definite spatial arrangement by controlling the ratio between the materials and copolymers [10].
We also found that the local SA method produced segments with a greater variation in size, indicating the method is effective for achieving multi-scale segmentation.
Demonstrating this approach, we examine the parametric sensitivity of an advanced agroecosystem model (Landscape-DNDC) using a framework that is based on (1) the Sobol SA method, (2) model simulations at three UK arable sites and (3) the grouping of the model's parameters according to the processes they affect.
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