Application of Artificial Immune System Algorithm to Electromagnetics Problems

Abstract

Abstract-This paper investigates the use of clonal selection principles based on our immune system for optimization applications in electromagnetics. This concept is based on our immune system's ability to respond to an antigen and produce a pool of anti-body secreting cells. In addition to the common implementations of this algorithm where the affinity maturation and cloning principles of clonal selection principles are used, we utilize memory and the cross-over concepts that are common to other bio-inspired methods. The performance of the algorithm is investigated for well known mathematical test functions and its potential is demonstrated in the context of the design of a radar absorbing material and a planar phased array antenna with specific radiation and null characteristics.

Adaptive immune‐inspired energy‐efficient and high coverage cross‐layer routing protocol for wireless sensor networks

“…After the mutation process cloning is taken place, in which every clone in the sub‐population undertakes the mutation process. For the next generation, the best of every subpopulation exchanges the original Ab and Abs, which are not cloned are interchanged by the random selection of new Abs [31, 32] (Fig. 4).…”

Determination of Optimal Parameters for the Immune Algorithm Used for Solving Inverse Heat Conduction Problems with and without a Phase Change

“…The number of active lymphocytes increases quickly, so that the specific immunity of the organism is created. The immune algorithms have turned out to be a useful tool of data analysis, for solving combinatorial optimization problems and technical problems of various kinds [5][6][7][8][9]. It should be noted that the values of immune algorithm parameters influence its performance.…”