Open AccessMethod of verification the correctness of the air object recognition process
Author(s) -
Oleksandr Tymochko,
Oleksander Timochko,
G. V. Dubovyk,
П. Г. Бердник
Publication year - 2020
Publication title -
telekomunìkacìjnì ta ìnformacìjnì tehnologìï
Language(s) - English
Resource type - Journals
ISSN - 2412-4338
DOI - 10.31673/2412-4338.2020.022512
Subject(s) - correctness , redundancy (engineering) , computer science , debugging , basis (linear algebra) , a priori and a posteriori , class (philosophy) , process (computing) , theoretical computer science , data mining , algorithm , artificial intelligence , pattern recognition (psychology) , programming language , mathematics , philosophy , geometry , epistemology , operating system
The basis of the developed procedure for verification the correctness of the process of recognition of airborne objects is the method of standards. The role of the standards is fulfilled by the introduced correctness constraints. During the control, the syntactic and semantic correctness of the recognition process are verified. The method differs from the known ones in the following. When verification certain types of semantic inaccuracy of descriptions of classes of alphabets, the concept of medium risk is used. The essence of the developed method for verification the differences in the descriptions of alphabet classes is as follows. The medium risk values are calculated when each pair of alphabet classes is recognized and the implementation of the restrictions introduced is verified. Using the method allows at the stage of debugging formalized knowledge to identify inaccuracies associated with the indistinguishability of alphabet classes and use the numerical value of the medium risk to identify other types of semantic inaccuracies. The essence of the developed method for verification the structural redundancy of alphabet class descriptions is as follows. The medium risk values are calculated during class recognition using various "fragments" of its description. The restriction introduced makes it possible to reveal indistinguishable “fragments” of class descriptions. Removing redundant descriptions reduces the time it takes to find solutions for classes of objects. The developed method for identifying the characteristic redundancy of class descriptions is also based on the procedure of calculating the medium risk value, adopted as a characteristic of the a priori information content of the signs. The method allows at the stage of filling the knowledge base to automate the identification and elimination of non-informative features in class descriptions, reduces the labor required to verify redundancy. At the stage of directly solving the recognition problem, the method allows to reduce computational costs by ranking the used features by their a priori information content and the corresponding organization of the search process for the decision on recognition classes of air objects.