scholarly journals Application of the theory of danger for modeling market barriers based on artificial immune system

2015 ◽  
Vol 5 (1) ◽  
pp. 299-309
Author(s):  
Степанов ◽  
Leonid Stepanov ◽  
Сербулов ◽  
Yuriy Serbulov ◽  
Глухов ◽  
...  
Keyword(s):  
Immune System ◽  
Artificial Immune System ◽  
Artificial Immune Systems ◽  
Protective Mechanism ◽  
Economic Systems ◽  
Artificial Immune ◽  
Human Immune System ◽  
Mathematical Methods ◽  
Foreign Agent ◽  
The Impact

Artificial immune system is a complex of mathematical methods to simulate the basic func-tions of the human immune system, and used to determine the parameters and (or) their values that can minimize the impact of certain factors (external or internal) to the production and economic ent-ity. The main characteristic that distinguishes the immune system of a foreign agent is an antigen that is any molecule which can be recognized by cellular elements of immunity (lymphocytes) using specific sensitive receptors. Otherwise, the antigen is a separate index that distinguishes foreign agent. Despite all this, there are examples where this approach fails. There are cases where the im-mune system does not work on "friend or foe", but uses a protective mechanism of hazard recogni-tion, which is a key method of the theory of danger. This theory does not deny the existence of dif-ferentiation in the "friend or foe", and argues that there are other factors that lead to the initiation of the immune response. For example, the theory of danger determines the nature of data on the beha-vior of competing industrial and economic systems, which must be submitted and processed in the artificial immune systems. Application of the theory of danger increases the efficiency of mathe-matical models, forming an artificial immune system of the market, which in its turn allows recog-nition of a new competitor in the market, assess the risk on its part for the competitors, and deter-mine the values of the characteristics of companies that will dominate over the parameters of a new competitor.

scholarly journals Modeling market barriers based on artificial immune system

10.12737/2208 ◽  
2014 ◽  
Vol 3 (4) ◽  
pp. 223-231
Author(s):  
Степанов ◽  
Leonid Stepanov ◽  
Сербулов ◽  
Yuriy Serbulov ◽  
Глухов ◽  
...  
Keyword(s):  
Immune System ◽  
Artificial Immune System ◽  
Artificial Immune ◽  
Human Immune System ◽  
Mathematical Methods ◽  
Human Immune ◽  
The Impact

The article considers the artificial immune system, which is a complex of mathematical methods to model the main functions of the human immune system, and used to determine the parameters and (or) their values which ​​can minimize the impact of certain factors (ex-ternal or internal) to any object. If such a system is functioning as the "observer", its antibodies correspond to the properties of a competitor. Then "interesting" competitors are those whose properties correspond to the antibodies of the immune system. Signal "danger" arises. It is important that an understanding of "interesting" competitor can promptly adapt to such changes.

Mathematical Formulation of Public Electric Transport Scheduling Task for Artificial Immune Systems

2009 ◽  
Vol 25 (25) ◽  
pp. 159-164 ◽  
Author(s):  
Mikhail Gorobetz ◽  
Ivars Alps ◽  
Anatoly Levchenkov
Keyword(s):  
Immune System ◽  
Artificial Immune System ◽  
Flow Shop ◽  
Mathematical Formulation ◽  
Artificial Immune Systems ◽  
Optimal Schedule ◽  
Electric Transport ◽  
Artificial Immune ◽  
Human Immune System ◽  
Immune Systems

Mathematical Formulation of Public Electric Transport Scheduling Task for Artificial Immune SystemsThis paper describes mathematical formulation and application of artificial immune system for scheduling tasks for public electric transport. Artificial immune system is inspired by human immune system to simulate the process of interaction between antigens and antibodies. The task of scheduling in transport system is represented as one of the most well-known flow shop problem. Artificial immune system as a genetic based method is used to solve such task. Mathematical model and algorithm is proposed to create optimal schedule for public electric transport for minimization of electric energy consumption and time. Numerical example shows several steps of algorithm for artificial immune system for scheduling task solution.

Developing an Algorithm for the Application of Bayesian Method to Software Using Artificial Immune Systems

2021 ◽  
Author(s):  
Shafagat Mahmudova
Keyword(s):  
Immune System ◽  
Artificial Immune System ◽  
Bayesian Method ◽  
Artificial Immune Systems ◽  
Artificial Immune ◽  
Computational System ◽  
Malicious Software ◽  
Immune Systems ◽  
Advantages And Disadvantages ◽  
Protection Systems

Abstract This study provides information on artificial immune systems. The artificial immune system is an adaptive computational system that uses models, principles, mechanisms and functions to describe and solve the problems in theoretical immunology. Its application in various fields of science is explored. The theory of natural immune systems and the key features and algorithms of artificial immune system are analyzed. The advantages and disadvantages of protection systems based on artificial immune systems are shown. The methods for malicious software detection are studied. Some works in the field of artificial immune systems are analyzed, and the problems to be solved are identified. A new algorithm is developed for the application of Bayesian method in software using artificial immune systems, and experiments are implemented. The results of the experiment are estimated to be good. The advantages and disadvantages of AIS were shown. To eliminate the disadvantages, perfect AISs should be developed to enable the software more efficient and effective.

THE MODEL AND ALGORITHM ARTIFICIAL IMMUNE SYSTEM

2016 ◽  
Vol 8 (3) ◽  
pp. 5-10
Author(s):  
Астахова ◽  
I. Astakhova ◽  
Ушаков ◽  
S. Ushakov
Keyword(s):  
Neural Networks ◽  
Immune System ◽  
Artificial Immune System ◽  
Artificial Immune Systems ◽  
Artificial Immune ◽  
Program Complex ◽  
Immune Systems ◽  
The Creation

In particular, models had only one type of cages , they applied V-lymphocytes. The distribution and a decentralization were the second feature for using artificial immune systems. This article is devoted to creation the artificial immune system (AIS), the creation model and algorithm of IIS is considered. The model for realization of a problem is consid-ered. Accuracy of calculations is compared to other methods, especially to neural networks. The structure of a program complex is described.

scholarly journals The Artificial Immune System Approach for Smart Air-Conditioning Control

2012 ◽  
Vol 58 (2) ◽  
pp. 193-199
Author(s):  
Zenon Chaczko ◽  
Shahrzad Aslanzadeh ◽  
Jonathan Kuleff
Keyword(s):  
Immune System ◽  
System Approach ◽  
Air Conditioning ◽  
Artificial Immune System ◽  
Immune Memory ◽  
Artificial Immune ◽  
Air Conditioning System ◽  
System Solution ◽  
The Impact ◽  
Conditioning Control

The Artificial Immune System Approach for Smart Air-Conditioning ControlBiologically inspired computing that looks to nature and biology for inspiration is a revolutionary change to our thinking about solving complex computational problems. It looks into nature and biology for inspiration rather than conventional approaches. The Human Immune System with its complex structure and the capability of performing pattern recognition, self-learning, immune-memory, generation of diversity, noise tolerance, variability, distributed detection and optimisation - is one area that has been of strong interest and inspiration for the last decade. An air conditioning system is one example where immune principles can be applied. This paper describes new computational technique called Artificial Immune System that is based on immune principles and refined for solving engineering problems. The presented system solution applies AIS algorithms to monitor environmental variables in order to determine how best to reach the desired temperature, learn usage patterns and predict usage needs. The aim of this paper is to explore the AIS-based artificial intelligence approach and its impact on energy efficiency. It will examine, if AIS algorithms can be integrated within a Smart Air Conditioning System as well as analyse the impact of such a solution.

SPAM DETECTION USING GENETIC ASSISTED ARTIFICIAL IMMUNE SYSTEM

2011 ◽  
Vol 25 (08) ◽  
pp. 1275-1295 ◽  
Author(s):  
RAED ABU ZITAR ◽  
ADEL HAMDAN MOHAMMAD
Keyword(s):  
Immune System ◽  
Artificial Immune System ◽  
Spam Detection ◽  
Artificial Immune ◽  
Human Immune System ◽  
Network Bandwidth ◽  
Lost Productivity ◽  
Human Immune ◽  
Almost All ◽  
New Machine

This work presents a novel system based on artificial immune system for spam detection. A relatively new machine learning method inspired by the human immune system called Artificial Immune System (AIS) has been emerging recently. This method is currently undergoing intense investigation and demonstration. Core modifications were applied on the standard AIS with the aid of the Genetic Algorithm (GA). SpamAssassin corpus is used in all our simulations. Spam is a serious universal problem which causes problems for almost all computer users. This issue affects not only normal users of the internet, but also causes problems for companies and organizations due to expensive costs in lost productivity, wasting users' time and network bandwidth. Many studies on spam indicate that it costs organizations billions of dollars annually. We introduce a GA assisted AIS in spam detection, and compare between two methods. Encouraging results were achieved when comparing to commercially available anti-spam software.

IMMUNOLOGY AND ARTIFICIAL IMMUNE SYSTEMS

2012 ◽  
Vol 21 (06) ◽  
pp. 1250031 ◽  
Author(s):  
MUHAMMAD ROZI MALIM ◽  
FARIDAH ABDUL HALIM
Keyword(s):  
Immune System ◽  
Network Theory ◽  
Negative Selection ◽  
Artificial Immune System ◽  
Clonal Selection ◽  
Artificial Immune Systems ◽  
Selection Mechanism ◽  
Artificial Immune ◽  
Time Line ◽  
Immune Systems

Artificial immune system is inspired by the natural immune system for solving computational problems. The immunological principles that are primarily used in artificial immune systems are the clonal selection principle, the immune network theory, and the negative selection mechanism. These principles have been applied in anomaly detection, pattern recognition, computer and network security, dynamic environments and learning, robotics, data analysis, optimization, scheduling, and timetabling. This paper describes how these three immunological principles were adapted by previous researchers in their artificial immune system models and algorithms. Finally, the applications of various artificial immune systems to various domains are summarized as a time-line.

scholarly journals Intrusion detection based on the artificial immune system

2020 ◽  
Vol 68 (4) ◽  
pp. 790-803
Author(s):  
Danijela Protić
Keyword(s):  
Immune System ◽  
Dendritic Cell ◽  
Intrusion Detection ◽  
Anomaly Detection ◽  
Negative Selection ◽  
Artificial Immune System ◽  
Artificial Immune Systems ◽  
Artificial Immune ◽  
Immune Systems ◽  
The Way

Introduction/purpose: The artificial immune system is a computational model inspired by the biological or human immune system. Of particular interest in artificial immune systems is the way the human body reacts to new pathogens and adapts to remain immune for a long period after a disease has been combated, which refers to the recognition of known malicious attacks and the way the immune system identifies self-cells not to be reacted to, which refers to the anomaly detection. Methods: Negative selection, positive selection, clonal selection, immune networks, danger theory, and dendritic cell algorithm are presented. Results: A variety of algorithms and models related to artificial immune systems and two classification principles are presented; one based on the detection of a particular attack and the other based on anomaly detection. Conclusion: Artificial immune systems are often used in intrusion detection since they are accurate and fast. Experiments show that the models can be used in both known attack and anomaly detection. Eager machine learning classifiers show better results in the decision, which is an advantage if runtime is not a significant parameter. Dendritic cell and negative selection algorithms show better results for real-time detection.

scholarly journals An Evaluation of a Metaheuristic Artificial Immune System for Household Energy Optimization

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Maria Navarro-Caceres ◽  
Pramod Herath ◽  
Gabriel Villarrubia ◽  
Francisco Prieto-Castrillo ◽  
G. Kumar Venyagamoorthy
Keyword(s):  
Immune System ◽  
Artificial Immune System ◽  
Optimization Problems ◽  
Artificial Immune Systems ◽  
Energy Optimization ◽  
Management Problem ◽  
Artificial Immune ◽  
Household Energy ◽  
Save Energy ◽  
Bioinspired Algorithms

Devices in a smart home should be connected in an optimal way; this helps save energy and money. Among numerous optimization models that can be found in the literature, we would like to highlight artificial immune systems, which use special bioinspired algorithms to solve optimization problems effectively. The aim of this work is to present the application of an artificial immune system in the context of different energy optimization problems. Likewise, a case study is performed in which an artificial immune system is incorporated in order to solve an energy management problem in a domestic environment. A thorough analysis of the different strategies is carried out to demonstrate the ability of an artificial immune system to find a successful optima which satisfies the problem constraints.

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