Od immunologii do modelowania, przetwarzania i analiz danych
From immunology to modeling, processing and analysis of data

Summary/Abstract: Observation of nature is often the inspiration for unconventional and innovative ideas, proposals, suggestions, overall concepts for carrying out modeling phenomena and technical processes, economic, processing and analysis of statistical data. Artificial neural networks, genetic algorithms and evolutionary algorithms were created as an imitation of biological solutions. In recent years, the rapid development of immunological algorithms which are based on the action of the human immune system, has occurred. These algorithms are used in mathematics, engineering, problem solving in decision making, management, economics, finance. At the beginning of this article we describe the action of the human immune system, which is the basis for the construction of immune algorithms. Then we present the most important mechanisms influencing the operation and construction of the algorithms based on biological mechanisms of the immune system, in particular the negative selection, immune network, clonal selection. Then we describe how the elements and mechanisms of artificial immune system algorithms are represented to enable modeling, processing and analysis of data. In the last part of the article to illustrate the wide range of possibilities of using immune algorithms to solve various sorts of problems from a completely different fields, we present examples of applications that involve the assessment of bank borrowers, the task of coloring a graph belonging to combinatorial optimization problems, a multi-dimensional classification, fault detection.

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