| 摘要 |
The method for a sequential prediction of a binary element's state in a binary process and the system for the method implementation are based on the binary process representation by a unique sequence of binary elementary behavioral functions. These elementary behavioral functions are used for building a genotype of the binary process' behaviors. The behavioral genotype is periodically updated through the analysis of the binary process history. The behavioral genotype set defines a set of predicting functions with respect of an evaluation of the binary process' current instability level. The natural selection algorithm that operates upon the set of predicting functions is used in predicting procedures for a non-iterative determination of a state of the forthcoming binary process' element. If the binary process is non-stationary, then a cardinal number of the set of predicting functions is equal or less than a cardinal number of the behavioral genotype set.The method allows performing real time predictions of binary processes, including non-stationary processes, regardless of the possible speed and memory limitations of computing means.The predicting system for the method implementation increases the efficiency of functioning of any entity that includes this system as a subsystem.
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