The vertebrate immune system is a decentralized and adaptive system with high complexity. The information processing mechanism extracted from vertebrate immune system can be used for solving many complex engineering problems. After reviewing the mechanism of immune system, an artificial immune data clustering algorithm based on clone selective principle and immune network theory from the verteb...

This document exposes a new Artificial Immune System (AIS) algorithm, inspired in the Natural Immune System (NIS) and certain characteristics. The algorithm presented emulates certain procedures and utilizes concepts such as learning from demonstration and reinforcement learning. The algorithm is designed to produce new knowledge in form of antibodies from limited data samples as antigens. The ...

BACKGROUND There is a high risk of tuberculosis (TB) disease diagnosis among conventional methods. OBJECTIVES This study is aimed at diagnosing TB using hybrid machine learning approaches. MATERIALS AND METHODS Patient epicrisis reports obtained from the Pasteur Laboratory in the north of Iran were used. All 175 samples have twenty features. The features are classified based on incorporatin...

Inspired by the cooperation mechanisms of Th cells, we propose a new algorithm named cooperation artificial immune system and apply it to traveling salesman problem (TSP). Simulation results show that the cooperation immune model has better performance than the model without cooperation.

This paper describes an artificial immune system algorithm which implements a fairly close analogue of the memory mechanism proposed by Jerne(1) (usually known as the Immune Network Theory). The algorithm demonstrates the ability of these types of network to produce meta-stable structures representing populated regions of the antigen space. The networks produced retain their structure indefinit...

The word wide sharply increase in the number of smartphones user, the Android platform pose to becoming a market fugleman that makes the need for malware analysis on this platform an urgent issue. The current Artificial Immune Based malware detection systems they focus on traditional computers that uses information from OS or network, but the smartphone software behavior has its own structure a...

Artificial immune systems (AIS) have become popular among researchers and have been applied to a variety of tasks. Developing supervised learning algorithms based on metaphors from the immune system is still an area in which there is much to explore. In this paper a novel supervised immune algorithm based on clonal selection framework is proposed. It evolves a population of linear classifiers u...

Negative Selection Algorithm (NSA) is an important artificial immune data classifiers generation method in Artificial Immune System (AIS) research. However, with the increase of the data dimensions, the current data classification algorithms which based on NSA exist the problems of excessive number of generated classifiers and too low classifier generation efficiency. In this paper, the Dual Ne...

Artificial immune systems are a collection of algorithms inspired by the hu-man immune system. Over the past 15 years, extensive research has been per-formed regarding the application of artificial immune systems to computer secu-rity. However, existing immune-inspired techniques have not performed as wellas expected when applied to the detection of intruders in computer systems...

In recent years, bio-inspired algorithms have increasingly been used by researchers for solving various optimization problems increasingly. Many real world problems are mostly time varying optimization problems, which require special mechanisms for detecting changes in environment and then responding to them. The present paper has been proposed to combination the learning automata and artificia...