In this age of wireless communication, micro strip antennas have drawn maximum attention of antenna community because of its compact size, light weight and low profile configuration. In this paper the problem of locating feed point of an inset fed microstrip patch antenna designed for wireless communication is dealt with. The optimization is done using three techniques: Genetic Optimization (GA...

Particle Swarm Optimization algorithm is based on iterative optimization tools, system initialization of a group of random solutions, through iterative search for the optimal value. The basic idea of the fuzzy C-means clustering algorithm is to determine each sample data belonging to a certain degree of clustering, and the degree of membership of sample data is grouped into a cluster. Favor opt...

This paper assumes each user has more than one queue, derives a new packet dependent proportional fairness power allocation pattern based on the sum of weight capacity and the packet’s priority in users’ queues, and proposes 4 new schemes of cross-layer packet dependent OFDM scheduling for heterogeneous classes of traffic based on proportional fairness. Scenario 1, scenario 2 and scenario 3 lea...

This paper presents a new approach to particle swarm optimization (PSO) using digital pheremones to coordinate the movements of the swarm within an n-dimensional design space. In traditional PSO, an initial randomly generated population swarm propagates towards the global optimum over a series of iterations. Each particle in the swarm explores the design space based on the information provided ...

The development of mathematical neural networks was based on an analogy with biological neural networks found in nature. Recently there has been a resurgence in research and understanding in self-organizing networks that are based on other metaphors: genetics, immune systems etc. In this paper a new methodology is presented for creating Complex Adaptive Functional Networks (CAFN) that are based...

This article presents a fuzzy self-adaptive particle swarm optimization (FSAPSO) learning algorithm to extract a near optimum codebook of vector quantization (VQ) for carrying on image compression. The fuzzy self-adaptive particle swarm optimization vector quantization (FSAPSOVQ) learning schemes, combined advantages of the fuzzy inference method (FIM), the simple VQ concept and the efficient s...

Wireless Sensor Network (WSN) is a collection of tiny sensor nodes capable of sensing and processing the data. These sensors are used to collect the information from the environment and pass it on to the base station. A WSN is more vulnerable to various attacks. Among the different types of attacks, sinkhole attack is more vulnerable because it leads to a variety of attacks further in the netwo...

In recent days, Swarm Intelligence plays an important role in solving many real life optimization problems. Particle Swarm Optimization (PSO) is swarm intelligence based search and optimization algorithm which is used to solve global optimization problems. But due to lack of population diversity and premature convergence it is often trapped into local optima. We can increase diversity and preve...

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...

A novel optimization algorithm, called accelerated particle swarm optimization (APSO), is proposed to be used for dynamic spectrum sensing in cognitive radio networks. While modified swarm-based optimization algorithms focus on slight variations of the standard mathematical formulas, in APSO, the acceleration variable of the particles is also considered in the search space. We show that the pro...