Abstract For many wireless sensor networks applications, a powerful localization algorithm is required to determine the exact positions of nodes. In this paper, new presented which combines distance vector hop (DV-Hop) with shuffled shepherd optimization position for each unknown node within 3-D space. Studying problem in space more realistic, but challenging due enlarged search Comparison our ...

This paper studies wireless sensor networks node deployment problem and proposes intelligent single particle optimizer based wireless sensor networks adaptive coverage. According to the probability model measure characteristic of wireless sensor nodes, the method adaptively determines the optimal deployment of sensor nodes using intelligent single particle optimizer, achieving sensor node based...

Over the past few decades, many algorithms have been proposed to improve performance of speech encryption over un-secure channel (i.e., Internet). In this paper, security level was enhanced using a dynamic dual chaotic based on Hénon map. algorithm, elements are shuffled in random fashion. Moreover, when both state variables free be used for shuffling index is toggled randomly between them acco...

The Shuffled Complex Evolution—University of Arizona (SCE-UA) is a classical algorithm in the field hydrology and water resources, but it cannot solve constrained optimization problems directly. Using penalty functions has been preferred method to handle constraints, appropriate selection parameters can be challenging. To enhance universality SCE-UA, we propose Constrained Evolution Algorithm (...

Evolutionary Algorithms (EAs) are a set of probabilistic optimization algorithms based on an analogy between natural biological systems and engineered systems. In this paper, the computational performance a set of specific EAs (specifically, the Genetic Algorithm, Evolutionary Programming, Particle Swarm Optimization, Ant Colony Optimization and Shuffled Complex Evolution Algorithm) are compare...

To improve the unreasonable distribution of sensors' random deployment and increase network coverage rate, an optimization method of wireless sensor networks coverage based on improved shuffled frog leaping algorithm (ISFLA) was proposed in this paper.During the process of updating the frog, a novel learning strategy is introduced, in which the poor frog learns not only from the best frog of it...