This paper proposes a multi-level optimization strategy for the Negative Selection Algorithm (NSA) detectors, based on both the Genetic Algorithms (GA) and clonal selection principle. The NSA is a natural immune response-inspired pattern discrimination method. In our hierarchical optimization scheme, the NSA detectors are first optimized by the GA to occupy the maximal coverage of the nonself s...

The clonal selection principle explains the basic features of an adaptive immune response to a antigenic stimulus. It established the idea that only those cells that recognize the antigens are selected to proliferate and differentiate. This paper explains a computational implementation of the clonal selection principle that explicitly takes into account the affinity maturation of the immune res...

In this paper, we examine the clonal selection algorithm CLONALG and the suggestion that it is suitable for pattern recognition. CLONALG is tested over a series of binary character recognition tasks and its performance compared to a set of basic binary matching algorithms. A number of enhancements are made to the algorithm to improve its performance and the classification tests are repeated. Re...

Data mining is concerned with developing algorithms and computational tools and techniques to help people extract patterns from data. In this paper an efficient data mining approach, which is based on fuzzy set theory and clonal selection algorithm, is proposed. The main motivation is to benefit from the global search performed by this kind of algorithms. Experimental results show the number of...

Numerous scholars have submitted the theory and research of artificial immune systems (AISs) in recent years. Although AIS has been used in various fields, applying the AIS to medical images is very rare. The purpose of this study is using the clonal selection algorithm (CSA) of artificial immune systems for classifying the brain MRI, and displaying a single organism image which can finally off...

This article is distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract The paper is focused on the forecasting method for time series groups with the use of algorithms for cluster analysis. K-means algorithm is suggested to be a basic one for clustering. The ...

Premature convergence is one of the major difficulties with Clonal Selection Algorithm (CSA). It has been observed that this problem is closely tied to the problem of losing diversity in the population. In this paper, we propose a distance maintaining compact quantum crossover based CSA. The compact quantum crossover is useful for information exchanging between different solutions, whereas uses...

A clonal selection algorithm (CLONALG) inspires from Clonal Selection Principle used to explain the basic features of an adaptive immune response to an antigenic stimulus. In this study, a new method is proposed for optimization of the Multiple Input Single Output (MISO) fuzzy membership functions using CLONALG. The most appropriate placement of membership functions with respect to fuzzy variab...

This paper presents the Clonal selection algorithmic approach to minimize power loss and energy cost by optimal capacitor placement and sizing in Radial Distribution System (RDS). The clonal selection optimization for optimal capacitor allocation is considering the daily load curve, which is represented by a given number of load levels. As an important branch of the Artificial Immune Systems (A...

Artificial Immune System is applied as a Heuristic Algorithm for decades. Nevertheless, many of these applications took advantage of the benefit of this algorithm but seldom proposed approaches for enhancing the efficiency. In this paper, a Self-evolving Artificial Immune System is proposed via developing the T and B cell in Immune System and built a self-evolving mechanism for the complexities...