We introduce several enhancements to deal with some of the weaknesses of previous artificial immune system models. Then, we present a framework for the accomplishment of several classical data mining tasks, such as frequent itemset discovery and robust clustering, based on ideas inspired from the natural immune system coupled with soft computing. For instance, we implement an artificial immune ...

Topology control protocols try to decrease average of node’s transition radius without decreasing network connectivity. In this paper, we propose a new Artificial Immune System-based topology control protocol for wireless sensor networks named AISTC. In this protocol, proper transition radius can be determined using Artificial Immune System algorithm. This protocol is simulated and compared its...

Artificial Immune technology, a resource limitedartificial immune classifier system,has performed well onelementary classification tasks. This paper presents oneform of mapping Artificial Immune Systems (AIS) intoLearning Classifier Systems for fault diagnosis. We proposea novel ideal to apply semantics in immune models. Similarto Learning Classifier Systems, a better un...

 Artificial immune system (AIS) approaches, which are used in this work, are learning and optimization methods that can be applied to find the solution of many types of optimization problems. This paper presents an AIS approach applied to optimize the design of an incremental discrete variable structure controller (VSC) for minimizing the generalized minimum variance (GMV) strategy. Control de...

This chapter aims to review the state of the art in algorithms of multiobjective optimization with artificial immune systems (MOAIS). As it will be focused in the chapter, Artificial Immune Systems (AIS) have some intrinsic characteristics which make them well suited as multiobjective optimization algorithms. Following this basic idea, different implementations have been proposed in the literat...

Copyright © 2002, Idea Group Publishing. The immune system is highly distributed, highly adaptive, self-organising in nature, maintains a memory of past encounters, and has the ability to continually learn about new encounters. From a computational viewpoint, the immune system has much to offer by way of inspiration. Recently there has been growing interest in the use of the natural immune syst...

The job shop scheduling problem (JSSP) is a notoriously difficult problem in combinatorial optimization. This paper presents a hybrid artificial immune system for the JSSP with the objective of minimizing makespan. The proposed approach combines the artificial immune system, which has a powerful global exploration capability, with the local search method, which can exploit the optimal antibody....

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...

Over the last decade, a new idea challenging the classical self-non-self viewpoint has become popular amongst immunologists. It is called the Danger Theory. In this conceptual paper, we look at this theory from the perspective of Artificial Immune System practitioners. An overview of the Danger Theory is presented with particular emphasis on analogies in the Artificial Immune Systems world. A n...

Database security is considered one of the major computer science research trends because of its importance in maintaining the privacy, integrity, and confidentiality of data. Human immune system is a set of defense mechanisms that can be used to defend the body against diseases caused by pathogens. Artificial immune system is the artificial simulation of human immunity that can be applied to c...