scholarly journals Investigation of a New Artificial Immune System Model Applied to Pattern Recognition

10.5772/6254 ◽  
2008 ◽  
Author(s):  
Jos Lima ◽  
Cleber Zanchettin ◽  
Edson C. de B. Carvalho Filho
Keyword(s):  
Pattern Recognition ◽  
Immune System ◽  
Artificial Immune System ◽  
System Model ◽  
Artificial Immune

Improved pattern recognition with complex artificial immune system

2009 ◽  
Vol 13 (12) ◽  
pp. 1209-1217 ◽  
Author(s):  
Wei Wang ◽  
Shangce Gao ◽  
Zheng Tang
Keyword(s):  
Pattern Recognition ◽  
Immune System ◽  
Artificial Immune System ◽  
Artificial Immune

A method of multiobjective optimization using a genetic algorithm and an artificial immune system

2009 ◽  
Vol 223 (5) ◽  
pp. 1243-1252 ◽  
Author(s):  
H Park ◽  
N-S Kwak ◽  
J Lee
Keyword(s):  
Genetic Algorithm ◽  
Pattern Recognition ◽  
Immune System ◽  
Artificial Immune System ◽  
Affinity Maturation ◽  
Pareto Optimal ◽  
Mathematical Function ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Artificial Immune

The immune system has pattern recognition capabilities based on reinforced learning, memory, and affinity maturation interacting between antigens (Ags) and antibodies (Abs). This article deals with an adaptation of artificial immune system (AIS) into genetic-algorithm (GA)-based multi-objective optimization. The present study utilizes the pattern recognition from an AIS and the evolution from a GA. Using affinity measures between Ags and Abs, GA-based immune simulation discovers a generalist Ab that represents the common pattern among Ags. Non-dominated Pareto-optimal solutions are obtained via GA-based immune simulation in which dominated designs are considered as Ags, whereas non-dominated designs are assigned to Abs. This article discusses the procedure of identifying Pareto-optimal solutions through the immune system-based pattern recognition. A number of mathematical function problems that are described by discontinuity or disconnection in the shape of Pareto surface are first examined as test examples. Subsequently, engineering optimization problems such as rotating flywheel disc and ten-bar planar truss are explored to support the present study.

An Improved Artificial Immune System Model

2013 ◽  
Vol 420 ◽  
pp. 311-317
Author(s):  
Gui Yang Li ◽  
Tao Guo
Keyword(s):  
Immune System ◽  
Artificial Immune System ◽  
Experimental Results ◽  
Learning Ability ◽  
System Model ◽  
Generic Model ◽  
Receptor Editing ◽  
Artificial Immune ◽  
Immune Receptor ◽  
Improved Model

nspired by the theory of biological immune receptor editing/revision, an improved artificial immune system model is proposed. Different from generic model, the improved model does not need to set the detectors detection radius, but it gives the detector a certain degree of learning ability through receptor editing and receptor revision. This makes the detector has a capability to adjust the detection position and detection radius automatically. Experimental results show that the improved model achieves better detection performance than generic model.

P2.9.14 An artificial immune system model for gas sensors drift mitigation

2012 ◽  
Author(s):  
Gabriele Magna ◽  
Eugenio Martinelli ◽  
Alexandro Catini ◽  
Arnaldo D'Amico ◽  
Corrado Di Natale ◽  
...  
Keyword(s):  
Immune System ◽  
Gas Sensors ◽  
Artificial Immune System ◽  
System Model ◽  
Artificial Immune

Artificial Immune System Based Recognition of Handwritten Kannada Numerals

2012 ◽  
Vol 433-440 ◽  
pp. 900-906 ◽  
Author(s):  
H.R. Mamatha ◽  
Murthy K. Srikanta ◽  
K.S. Amrutha ◽  
P. Anusha ◽  
R. Azeemunisa
Keyword(s):  
Pattern Recognition ◽  
Immune System ◽  
Artificial Immune System ◽  
Nearest Neighbor ◽  
Recognition Accuracy ◽  
K Nearest Neighbor ◽  
Artificial Immune ◽  
Classification Approach ◽  
New Information ◽  
Extraction Algorithm

Artificial immune system (AIS) based classification approach is relatively new in the field of pattern recognition (PR). The capability of AIS for learning new information, recalling what has been learned and recognizing a decentralized pattern are reasons why numerous models have been developed, implemented and used in various types of problems. This paper explores this paradigm in the context of recognition of handwritten Kannada numerals. In this paper, the AIS is used for training the extracted features of handwritten Kannada numerals. Zonal based feature extraction algorithm is being used and K-Nearest Neighbor (K-NN) classifier is used for classification. The performance of the proposed algorithm has been investigated in detail on nearly 1250 samples of Handwritten Kannada Numerals and an recognition accuracy of 98.11% has been obtained.

An Affinity Based Complex Artificial Immune System and its Application on Trademark Retrieval

2012 ◽  
Vol 616-618 ◽  
pp. 2166-2170
Author(s):  
Wei Wang ◽  
Chia Hung Wei ◽  
Yue Li ◽  
Li Wang
Keyword(s):  
Immune System ◽  
Immune Cells ◽  
Artificial Immune System ◽  
System Model ◽  
Artificial Immune ◽  
Excellent Performance ◽  
Proposed Model ◽  
Trademark Images

Recently, artificial immune system (AIS) inspired by the theory or immunology, has been developed rapidly and steadily. In this paper, we proposed an affinity based complex artificial immune system model considering the fact that the different eptitopes located on the surface of antigen can be recognized by a set of different paratopes expressed on the surface of immune cells. The experiment on trademark retrieval is performed to prove that the model proposed model has an excellent performance on retrieving the trademark images and outperforms the previously proposed algorithm.

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