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A new particle swarm optimization (PSO) algorithm has been developed, and combined with the differential evolution (DE) method. The novel evolutionary technique is utilized to approximate the sine and Gaussian functions of a Gabor filter, as polynomial functions, by the stochastic computation of an optimal set of coefficients. The new stochastic algorithm achieves a lower root mean square error of...
This paper deals with a multimodal approach to identifying species in a Versatile Service-Oriented Wireless Mesh Sensor Network. This type of network is distinguished by the presence of heterogeneous networks, which may posses low storage capabilities. Hence, an optimal multimodal classifier is introduced, which employs audio and image features to enhance its performance in noisy environments. The...
In this paper the case study of a smart home powered by solar and wind energy is presented. The benefits of having a smart home that can control the amount of power needed, according to the context of the usage, are also shown. Simulation shows that with a good control of the load it might be possible to reduce the installation costs of the Green Energy System. Furthermore, to support the results,...
Particle Swarm Optimization (PSO) is a promising evolutionary algorithm, which has been used in a wide range of applications, due to its simple implementation, fast convergence, parallel behavior, and versatility in working with continuous and discrete domains. In this paper, we consider its application to the load balancing problem, in green smart homes. Specifically, an adapted version of the Binary...
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