Robust approach for optimized path selection in Monarch Butterfly Optimization

Nature Inspired Computing or (NIC) strives to develop new computing technologies by observing how nature can inspired to solve complex problems under various environmental conditions. This has produced unconventional research in new fields such as neural networks, swarm intelligence, evolutionary computing, and artificial immune systems. NIC technology is used in almost every branch of physics, biology, engineering, economics and even management. In this paper, one of the nature-inspired approach namely Monarch Butterfly Optimization (MBO)is used for modifying the chromosome parameter in it. The new conditional path selection criteria are developed for the movement of individual subpopulation along with the amplitude parameter. Ackley function is implemented by using conditional path selection mathematical model and the effect of amplitude parameter with adjusting ratio has been identified. The results show better performance among the conditional path selection criteria in terms of route optimization selection.

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Advancement in the twentieth century in artificial immune systems for optimization: Review and future outlook

2009 IEEE International Conference on Systems, Man and Cybernetics ◽

10.1109/icsmc.2009.5346835 ◽

2009 ◽

Cited By ~ 7

Author(s):

Eugene Y. C. Wong ◽

Henry Y. K. Lau

Keyword(s):

Twentieth Century ◽

Artificial Immune Systems ◽

Artificial Immune ◽

Future Outlook ◽

Immune Systems

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Independent Task Scheduling by Artificial Immune Systems, Differential Evolution, and Genetic Algorithms

2012 Fourth International Conference on Intelligent Networking and Collaborative Systems ◽

10.1109/incos.2012.76 ◽

2012 ◽

Cited By ~ 1

Author(s):

Pavel Kromer ◽

Jan Plato ◽

V'clav Snasel

Keyword(s):

Genetic Algorithms ◽

Differential Evolution ◽

Task Scheduling ◽

Artificial Immune Systems ◽

Artificial Immune ◽

Immune Systems ◽

Independent Task

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

10.21203/rs.3.rs-538798/v1 ◽

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.

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