artificial immune system research paper-2
How to Boost Your Immune System
Your immune system consists of organs, cells, tissues, and proteins. When an alien microorganism enters your body, your immune system acts as a first responder. It fights hard to protect you from getting infected. However, if your immune system isn’t strong enough, it might lose the battle and let harmful bacteria have a feast in your body.
The healthier your immune system, the better it works. That’s why it’s so essential to keep it that way for as long as possible.
If you did end up getting Flu or any other common cold, you’re most likely to experience fever. Of course, it’s not a pleasant feeling at all, yet it means that your immune system is working and trying to get rid of that infection.
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Artificial immune systems
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In this position paper, we argue that the field of Artificial Immune Systems (AIS) has reached an impass. For many years, immune inspired algorithms, whilst having some degree of success, have been limited by the lack of theoretical advances, the adoption of a limited
Artificial immune systems: A bibliography
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Important Note: The field of Artificial Immune Systems (AIS) is becoming more popular and AIS-based works spanning from theoretical modeling and simulation to wide variety of applications. In particular, some of the references are of synthetic approaches to
Artificial immune systems: Survey and applications in ad hoc wireless networks
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Martin Drozda and Helena Szczerbicka University of Hannover, Department of Computer Science, FG Simulation und Modellierung, Welfengarten 1, 30167 Hannover, Germany. Email:{drozda, hsz} sim. uni-hannover. de Keywords: wireless ad hoc network,
Bankruptcy prediction using artificial immune systems
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In this paper we articulate the idea of utilizing Artificial Immune System (AIS) for the prediction of bankruptcy of companies. Our proposed AIS model considers the financial ratios as input parameters. The novelty of our algorithms is their hybrid nature, where we
Artificial immune systems for classification of petroleum well drilling operations
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This paper presents two approaches of Artificial Immune System for Pattern Recognition (CLONALG and Parallel AIRS2) to classify automatically the well drilling operation stages. The classification is carried out through the analysis of some mud-logging parameters. In
Artificial immune systems and kernel methods
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In this paper, we focus on the potential for applying Kernel Methods into Artificial Immune Systems. This is based on the fact that the commonly employed affinity functions can usually be replaced by kernel functions, leading to algorithms operating in the feature
On diversity and artificial immune systems: Incorporating a diversity operator into aiNet
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When constructing biologically inspired algorithms, important properties to consider are openness, diversity, interaction, structure and scale. In this paper, we focus on the property of diversity. Introducing diversity into biologically inspired paradigms is a key feature of
Multi-label hierarchical classification of protein functions with artificial immune systems
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This work proposes two versions of an Artificial Immune System (AIS)-a relatively recent computational intelligence paradigm–for predicting protein functions described in the Gene Ontology (GO). The GO has functional classes (GO terms) specified in the form of a
Constraint handling in genetic algorithms via artificial immune systems
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ABSTRACT The combination of an artificial immune system (AIS) with a genetic algorithm (GA) is proposed as an alternative to tackle constrained optimization problems. The AIS is inspired in the clonal selection principle and is embedded into a standard GA search
Construction of classifier ensembles by means of artificial immune systems
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ABSTRACT This paper presents the application of Artificial Immune Systems to the design of classifier ensembles. Ensembles of classifiers are a very interesting alternative to single classifiers when facing difficult problems. In general, ensembles are able to achieve better
Artificial immune systems applied to multiprocessor scheduling
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We propose an efficient method of extracting knowledge when scheduling parallel programs onto processors using an artificial immune system (AIS). We consider programs defined by Directed Acyclic Graphs (DAGs). Our approach reorders the nodes of the program
An Introduction to the Artificial Immune Systems
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Page 1. An Introduction to the Artificial Immune Systems ICANNGA 2001 Prague, 22-25th April, 2001 Leandro Nunes de Castro 2 • Part I – Introduction to the Immune System • Part II – Artificial Immune Systems (AIS) • Part III – Examples of AIS and Applications
An introduction to artificial immune systems
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• Initialisation: create an initial network from a sub-section of the antigens• Antigenic presentation: for each antigenic pattern, do: 2.1 Clonal selection and network interactions: for each network cell, determine its stimulation level (based on antigenic and network
Artificial Immune Systems: Theory and Applications
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• Ideas inspired by natural systems can and are being used to engineer (or develop) dedicate solutions to specific problems. Examples: artificial neural networks, evolutionary computation, DNA computation, etc.• The cooperation and competition among several
Application and benchmarking of artificial immune systems to classify fault-prone modules for software development projects
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ABSTRACT Software quality assurance is a crucial activity to enhance and ensure the quality of software development projects. Necessary budget, personnel and resource should be allocated for quality assurance activities to minimize the operational level faults by
Scale invariance of immune system response rates and times: perspectives on immune system architecture and implications for artificial immune systems
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ABSTRACT Most biological rates and times decrease systematically with increasing organism body size. We use an ordinary differential equation (ODE) model of West Nile Virus in birds to show that pathogen replication rates decline with host body size, but natural immune
Noisy Channel and Reaction-Diffusion Systems: Models for Artificial Immune Systems In this conceptual paper we present two paradigms to model Immune Algorithms: Noisy Channel, and Reaction Diffusion System. We describe a general framework which can be readjusted and retuned according to the applications at hand. For instance, one can use
Fuzzy rule induction and artificial immune systems in female breast cancer familiarity profiling
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Genomic DNA copy number aberrations are frequent in solid tumours although their underlying causes of chromosomal instability in tumours remain obscure. In this paper we show how Artificial Immune System (AIS) paradigm can be successfully employed in the
Energy Efficient Security in MANETs: A Comparison of Cryptographic and Artificial Immune Systems
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ABSTRACT MANET is characterised by a set of mobile nodes in an inherently insecure environment, having limited battery capacities. Provisioning of energy efficient security in MANETs is, therefore, an open problem for which a number of solutions have been
A new approach to artificial immune systems and its application in constructing on-line learning neuro-fuzzy systems
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ABSTRACT In this paper, we present an on-line learning neuro-fuzzy system which was inspired by parts of the mechanisms in immune systems. It illustrates how an on-line learning neuro-fuzzy system can capture the basic elements of the immune system and
Improving female breast cancer prognosis by means of fuzzy rule induction with artificial immune systems
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ABSTRACT Breast cancer is the second most common cause of deaths from cancer among women in the United States. Even if significant steps have been made in the field of cancer treatment there s still room for investigation when it comes to the modeling of metastatic
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