Weed is a phenomenon which is looks for optimality and finds the best environment for life and quickly adapts itself to environmental conditions and resists changes. Considering these features, a powerful optimization algorithm is developed in this study. The invasive weed optimization algorithm (IWO) is a population-based evolutionary optimization method inspired by the behavior of weed colonies. In this paper, the IWO algorithm is based on chaos theory. Among parameters of weed optimization algorithm, standard deviation affects the performance of the algorithm significantly. Therefore, chaotic maps are used in the standard deviation parameter. Performance of the chaotic invasive weed development method is investigated on five benchmark functions, using logistic chaotic mapping. Additionally, the problem of setting the PID controller parameters for a DC motor using the proposed method is discussed. The statistical results on optimization problems show that the improved chaotic weed algorithm has gained fast convergence rate and high accuracy.
Highlights Improved Invasive weed optimization Algorithm (IWO) based on Chaos theory. Improved setting the parameters of PID controller uses Chaotic IWO Algorithm.
A new image encryption scheme, based on a total shuffling and parallel encryption algorithm is proposed in this paper. Two chaotic systems have been used in the encryption algorithm to confuse the relationship between the plain-image and the cipherimage. To make the encryption procedure more confusing and complex, the plain-image is first divided into 4 sub-images and then the position of each subimage is changed pseudo-randomly according to a logistic map. Next, a total shuffling matrix is used to shuffle the position of pixels in the whole image and then sub-images are encrypted simultaneously in a parallel manner. The experimental results on USC data base demonstrate that the proposed encryption algorithm has a low time complexity and has the advantages of large key space and high security. Moreover, the robustness of this locally encryption method is much more in contrast with other encryption schemes and the distribution of gray values has a random-like behavior in the encrypted image.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.