Recently, Combined Heat and Power (CHP) systems have been utilized increasingly in power systems. With the addition penetration of CHP-based co-generation of electricity and heat, the determination of economic dispatch of power and heat becomes a more complex and challenging issue. The optimal operation of CHP-based systems is inherently a nonlinear and non-convex optimization problem with a lo...

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...

This paper proposes a study of quality of service (QoS) in cognitive radio networks. This study is based on a stochastic optimization method called shuffled frog leaping algorithm (SFLA). The interest of the SFLA algorithm is to guarantee a better solution in a multi-carrier context in order to satisfy the requirements of the secondary user (SU).

this paper presents a new damping controller design based on fuzzy wavelet neural network (fwnn) to damp the multi-machine power system low frequency oscillations. the error between the desired system output and the output of control object is directly utilized to tune the network parameters. the orthogonal least square (ols) algorithm is used to purify the wavelets for each rule and determine ...

clustering is one of the known techniques in the field of data mining where data with similar properties is within the set of categories. k-means algorithm is one the simplest clustering algorithms which have disadvantages sensitive to initial values of the clusters and converging to the local optimum. in recent years, several algorithms are provided based on evolutionary algorithms for cluster...

The frequency modulation sound parameter identification is a complex multimodal optimization problem. This problem is modeled in the form of a cost function that is the sum-squared error between the samples of estimated wave and the samples of real wave. In this research, the authors propose a shuffled particle swarm optimization algorithm to solve this problem. In the shuffled particle swam op...