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SNPs were thus chosen from the largest scaffolds available, with 100 Kb bases interval on scaffolds larger that 100 Kb, or only one SNP per scaffold, for scaffolds smaller than 100 Kb.
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A prediction based interval model control algorithm was then implemented to control the resultant interval models.
Simultaneously, an iterative algorithm based interval analysis method (IA-IAM) is presented to solve this model.
Two methods, i.e., sensitivity based interval analysis method and iterative algorithm based interval analysis method, are proposed to solve this model in the framework of interval analysis theory.
The MDS, IPS and speedup LC techniques are embedded into a branch-and-bound based interval search to guarantee optimality.
adaptive Taylor methods and direct optimisation based interval finite element approach are used in the present work to obtain time-history response of the structure with uncertain parameters.
The proposed controller is designed by combining an adaptive Mamdani linguistic based interval type-2 fuzzy logic system (IT2-FLS) with sliding mode control technique.
However, this rule considers measured samples twice at the 10-min border by synchronizing the first base interval to each border.
The intervals were presented pseudorandomly for each base interval, and ten repetitions were collected for one implicit middle base interval before moving to the next interval.
Thus, one repetition of the task for each implicit middle base interval included the categorization of the eight intervals.
Thus, the subject was required to push one of the keys to indicate his/her categorical decision for eight intervals using acquired category boundaries and an implicit middle base interval set during the training period (Fig 1A).
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