This paper proposes a novel algorithm to improve the lifetime of a wireless sensor network. This algorithm employs Swarm Intelligence algorithms in conjunction with compressive sensing theory to build up the routing trees and to decrease the communication rate respectively. The main contribution of this paper is to extend Swarm Intelligence algorithms to build a routing tree in such a way that ...

In the proposed work, authors have applied swarm intelligence based algorithms for the effective Co-ordination of Flexible AC transmission system (FACTS) devices with other existing Var sources present in the network. IEEE 30 and IEEE 57 bus systems are taken as standard test systems. SPSO (Simple Particle Swarm Optimization) and other two swarm based intelligence approaches like APSO (Adaptive...

In last decades, lots of nature-inspired optimization algorithms are developed and presented to the literature for solving optimization problems. Generally, these optimization algorithms can be grouped into two categories: evolutionary algorithms and swarm intelligence methods. Evolutionary methods try to improve the candidate solutions (chromosomes) using evolutionary operators such as crossov...

This paper explores research in progress on Swarm Intelligence related to Procedural Terrain Generation. Our aim is to develop means to provide useful and real-time terrain deformation using Swarm algorithms. We feel this could prove interesting for enhancing the experience of gameplay in some game genres such as Real Time Strategy (RTS), simulation or even platform games.

This chapter introduces some of the theoretical foundations of swarm intelligence. We focus on the design and implementation of the Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) algorithms for various types of function optimization problems, real world applications and data mining. Results are analyzed, discussed and their potentials are illustrated.

In this study it is presented a summarization of our research of possible ways of creating of complex networks from the inner dynamics of Swarm Intelligence based algorithms. The particle swarm optimization algorithm and the firefly algorithm are studied in this paper. Several methods of complex network creation are proposed and discussed alongside with possibilities for future research and app...

Swarm intelligence is a relatively new discipline that deals with the study of self-organizing processes both in nature and in artificial systems. Researchers in ethology and animal behavior have proposed many models to explain interesting aspects of social insect behavior such as self-organization and shape-formation. Recently, algorithms inspired by these models have been proposed to solve di...

Swarm intelligence forms the core of a new class of algorithms inspired by the social behavior of insects that live in swarms. Its attractive features include adaptation, robustness and a distributed, decentralized nature, rendering swarm-based algorithms well-suited for routing in wireless or satellite networks, where it is difficult it implement centralized network control. We propose one suc...

In this work we apply the recently proposed Unified Particle Swarm Optimization (UPSO) method to the search for Hadamard matrices of the Williamson type. The objective functions that arise from the classical Williamson construction, are ideally suited for UPSO algorithms. This is the first time that swarm intelligence methods are applied to this problem. Mathematics Subject Classification (2000...

This paper presents the design, implementation and experiences of a new three hour experimental course taught for a joint undergraduate and graduate class at the University of Missouri-Rolla, USA. The course covers the four main paradigms of Computational Intelligence (CI) and their integration to develop hybrid systems. The paradigms covered are artificial neural networks (ANNs), evolutionary ...