Czasopismo | ELEKTRONIKA - KONSTRUKCJE, TECHNOLOGIE, ZASTOSOWANIA | Rocznik 2013 - zeszyt 8

The immune method for classifying objects on the basis of the target clonal selection

nr katalogowy: 78814

Currently in the field of artificial intelligence modeling a lot of attention is paid to systems of information processing, operating on the basis of the principles of biological algorithms. In connection with this great research interest are models of artificial immune systems (IMS) and their practical implementation. Various immune models and methods have been successfully used to solve the problems of classification and clustering of data [1, 2]. The process of classifying objects on the basis of IMS is divided into two stages: the first stage, the signs of recovery classes original objects through the use of immune operators cloning and selection of clones in the second stage, the definition of classes for objects that are not assigned to any class. The most frequently used methods immune labeling methods are functioning on the basis of pattern selection clones, and methods based on the immune network model [1, 2]. When using the CLON ALG [1, 2] for the classification of objects is provided by high speed at a low classification accuracy. When using the BCA [1] to provide high classification accuracy for very large investment of time. Using the method aiNet [1, 2] characterized by greater precision classification unlike CLON ALG, but less than the accuracy of BCA. In addition, the aiNet method is slower than the method of CLON ALG. In [3, 4] proposed a method of classification, the main feature of which is the priority consistent with the cloning of competitive target selection of clones, resulting in a reduction of redundant computation inherent immune listed methods. This brings it to a method for accuracy BCA, and the time spent on the classification, the method aiNet. The main disadvantages of the method proposed in [3, 4], the complexity of implementation is high, not optimal mutation that leads to an increase in the time of classification. The proposed method is immune in the classification of objects is a modificat[...]

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2013-8

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