Application of bioinspired algorithms for solving transcomputational tasks

Abstract

The paper investigates the pattern recognition task as one of the most important transcomputational problems. Pattern recognition is applied for statistical data analysis, signal processing, image analysis, bioinformatics, machine learning, and many other fields. The area of application is related to automated pattern detection in the data using computer algorithms and data classification in terms of different categories. The development of new ideas in the processing of large volumes of information creates a new trend in the pattern recognition area. A specific field is formed by the bioinspired algorithms as mathematical reorganization, that transform the initial information into the results based on simulating the evolution methods, natural analogies, and statistic approach. In terms of computer modelling based on the bioinspired algorithms, we can create and develop difficult concepts, for which we have no analytical description. The authors present the optimal bioinspired algorithms based on the ant, monkey, and bat behavior in nature and develop software based on the principle of pattern recognition using the uploaded photo and downloading the results into the file. The experiments demonstrate the effectiveness of the proposed approach.