An Essential Assessment on Computational Intelligence Based Optimization Algorithms in Various Types of Cancer Treatments

Watermarking algorithms are the one of the effective methods to protect the copyright of digital products. There are many types of watermarking algorithms, in this paper, methods based on optimization algorithms, also named computational intelligence, are surveyed. The detail procedure of watermark embedding and the watermarking extraction is described, and the basic theory application of computational intelligence is also analyzed. Finally, the advice of these types of watermarking algorithm is given.

Download Full-text

Modeling of missing data prediction: Computational intelligence and optimization algorithms

2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC) ◽

10.1109/smc.2014.6974111 ◽

2014 ◽

Cited By ~ 20

Author(s):

Collins Leke ◽

Bhekisipho Twala ◽

Tshilidzi Marwala

Keyword(s):

Missing Data ◽

Computational Intelligence ◽

Optimization Algorithms ◽

Data Prediction ◽

Missing Data Prediction

Download Full-text

A Brief Survey on Nature Inspired Algorithms: Clever Algorithms for Optimization

Asian Journal of Computer Science and Technology ◽

10.51983/ajcst-2018.7.1.1835 ◽

2018 ◽

Vol 7 (1) ◽

pp. 27-32

Author(s):

P. Sindhuja ◽

P. Ramamoorthy ◽

M. Suresh Kumar

Keyword(s):

Research And Development ◽

Computational Intelligence ◽

Optimization Algorithms ◽

Optimal Solutions ◽

Existing Problems ◽

Nature Inspired Computing ◽

Nature Inspired Algorithms

This paper presents a brief survey on various optimization algorithms. To be more precise, the paper elaborates on clever Algorithms – a class of Nature inspired Algorithms. The Nature Inspired Computing (NIC) is an emerging area of research that focuses on Physics and Biology Based approach to the Algorithms for optimization. The Algorithms briefed in this paper have understood, explained, adapted and replicated the phenomena of Nature to replicate them in the artificial systems. This Cross – fertilisation of Nature Inspired Computing (NIC) and Computational Intelligence (CI) will definitely provide optimal solutions to existing problems and also open up new arenas in Research and Development. This paper briefs the classification of clever algorithms and the key strategies employed for optimization.

Download Full-text

An extensive review of computational intelligence-based optimization algorithms: trends and applications

Soft Computing ◽

10.1007/s00500-020-04958-w ◽

2020 ◽

Vol 24 (21) ◽

pp. 16519-16549

Author(s):

Lavika Goel

Keyword(s):

Computational Intelligence ◽

Optimization Algorithms ◽

Extensive Review

Download Full-text

Coupling of Optimization Algorithms Based on Swarm Intelligence

Nature-Inspired Intelligent Techniques for Solving Biomedical Engineering Problems - Advances in Bioinformatics and Biomedical Engineering ◽

10.4018/978-1-5225-4769-3.ch002 ◽

2018 ◽

pp. 27-50 ◽

Cited By ~ 1

Author(s):

Kamalanand Krishnamurthy ◽

Mannar Jawahar Ponnuswamy

Keyword(s):

Swarm Intelligence ◽

Optimization Algorithm ◽

Computational Intelligence ◽

Biomedical Engineering ◽

Optimization Algorithms ◽

Bacterial Foraging Optimization ◽

Complex Problems ◽

Bacterial Foraging

Swarm intelligence is a branch of computational intelligence where algorithms are developed based on the biological examples of swarming and flocking phenomena of social organisms such as a flock of birds. Such algorithms have been widely utilized for solving computationally complex problems in fields of biomedical engineering and sociology. In this chapter, two different swarm intelligence algorithms, namely the jumping frogs optimization (JFO) and bacterial foraging optimization (BFO), are explained in detail. Further, a synergetic algorithm, namely the coupled bacterial foraging/jumping frogs optimization algorithm (BFJFO), is described and utilized as a tool for control of the heroin epidemic problem.

Download Full-text