Foundations of Swarm Intelligence: From Principles to Practice

Fleischer, Mark

doi:10.21236/ada440801

Cited by 35 publications

(26 citation statements)

References 37 publications

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“…Although there is normally no centralized control structure dictating how individual agents should behave, local interactions between such agents often lead to the emergence of global behavior. Examples of systems like this can be found in nature, including ant colonies, bird flocking, animal herding, bacteria molding and fish schooling [27]. Optimization techniques inspired by swarm intelligence have become increasingly popular during the last decade [28].…”

Section: Swarm Intelligencementioning

confidence: 99%

Bio-inspiring Techniques in Watermarking Medical Images: A Review

Soliman

Hassanien

Onsi

2014

Bio-Inspiring Cyber Security and Cloud Services: Trends and Innovations

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Bio-inspiring (BI) is a well-established paradigm with current systems having many of the characteristics of biological computers and capable of performing a variety of tasks that are difficult to do using conventional techniques. BI is considered as one of the most important increasing fields, which attract a large number of researchers and scientists working in areas such as neuro-computing, global optimization, swarms and evolutionary computing. On the other hand, digital radiological modalities in modern hospitals have led to the producing a variety of a vast amount of digital medical files. Therefore, for the medical imaging, the authenticity needs to ensure the image belongs to the correct patient, the integrity check to ensure the image has not been modified, and safe transfer are very big challenges. The integrity of the images must be protected by using watermarking, which is called integrity watermark. At the same time the copyright and intellectual property of the medical images should be also protected, which is called copyright watermark. This chapter presents a brief overview of well known Bio-inspiring techniques including neural networks, genetic algorithm, swarms and evolutionary algorithms and show how BI techniques could be successfully employed to solve watermarking problem. Challenges to be addressed and future directions of research are also presented and an extensive bibliography is included.

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Section: Swarm Intelligencementioning

confidence: 99%

Bio-inspiring Techniques in Watermarking Medical Images: A Review

Soliman

Hassanien

Onsi

2014

Bio-Inspiring Cyber Security and Cloud Services: Trends and Innovations

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“…Real distance was used as a measurement in calculating distances for Euclidean datasets, while integer distance was used as the basis of the distance calculation for GEO datasets. Table 1 shows the parameter settings for the DACS3 experiment, which is a similar setup from research on the ACS and DACS algorithms [2,5,10,13,16] . Table 2 shows the experimental results of DACS3 compared to several other algorithms.…”

Section: Dynamic Ant Colony System 3 Level Updates (Dacs3)mentioning

confidence: 99%

“…The algorithm is inspired by the foraging behavior of a colony of ants, which communicate through chemical substances called pheromones, acting as a memory preservation mechanism and providing guidance for ants in searching for shortest paths [2] . The principle of cooperation is the backbone of these algorithms.…”

Section: Introductionmentioning

confidence: 99%

Embedding Malaysian House Red Ant Behavior into an Ant Colony System

Othman

Rais

Hamdan

2008

J. of Computer Science

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Problem statement: Ant Colony System (ACS) is the most popular algorithm used to find a shortest path solution in Traveling Salesman Problem (TSP). Several ACS versions have been proposed which aim to achieve an optimum solution by adjusting pheromone levels. However, it still has a room on an improvement. This research aims to improve the algorithm by embedding individual Malaysian House Red Ant behavior into ACS. Approach: Modeling individual ants' ability reconstructing a path can provide a general idea on how such behavior can improve existing basic ACS ability in finding solution. This study presents a model of Dynamic Ant Colony System with Three Level Update (DACS3) which developed by embedding such behavior into ACS. The three level phases of pheromone updates are: local construction, local reinforcement and global reinforcement. The performance of DACS3 is measured by its shortest distance and time taken to reach the solution against several ant colony optimization algorithms (ACO) on TSP ranging from 14 to 100 cities by running the algorithm in c language. Results: The result shows that DACS3 has reached the shortest distance benchmark for dataset 14, 30 and 57 and has 0.5% differences for data set 100. While, others ACO manage to reach for data set 14 and 30 only and reached about 2.5% differences for data set 100. For dataset 57, DACS has reached 4.6% differences whilst ACS has reached 2.5% differences. Conclusion: Embedding a simple behavior of a single ant into ACS influences an achievement to reach an optimal distance and also can perform considerably faster compare to other ACO's algorithms.

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“…This is a successful application of the philosophy of bounded rationality and decentralized decisionmaking to solve the global optimization problems [8][9] [10]. A swarm of birds or insects searches for food, protection, etc.…”

Section: A Optimization Algorithmmentioning

confidence: 99%

An approach for stability analysis of nonlinear electrical network using antioptimization

Kuhn¹,

Ji²,

Joos³

et al. 2008

2008 IEEE Power Electronics Specialists Conference

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In this paper an optimization based approach for stability analysis of electrical networks is addressed. The stability problem is transferred to an optimization problem for finding worst performance regarding stability criteria for a parameters range. If a violation of the criteria is found, instability of the system is proven. For design, the maximal possible design parameters can be scaled until a boundary is reached. In contrast to other present methods of stability analysis -Modal Analysis and μ Analysis which are only suitable for linearized models -nonlinear models may be used directly by the optimization approach without the necessity of any averaging technique and linearization. This is necessary for systems like power electrical components with usually high nonlinear and wide ranging dynamics due to the very fast switching and a good solution for the stability analysis with industrial specified standards. The application of the proposed approach is illustrated via a regulated buck converter as a typical critical nonlinear component of the electrical network in the "More Electric Aircraft" architecture (MEA).

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Foundations of Swarm Intelligence: From Principles to Practice

Cited by 35 publications

References 37 publications

Bio-inspiring Techniques in Watermarking Medical Images: A Review

Bio-inspiring Techniques in Watermarking Medical Images: A Review

Embedding Malaysian House Red Ant Behavior into an Ant Colony System

An approach for stability analysis of nonlinear electrical network using antioptimization

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