in this paper, we propose a novel algorithm to enhance the noisy speech in the framework of dual-channel speech enhancement. the new method is a hybrid optimization algorithm, which employs the  combination of  the  conventional θ-pso and the shuffled sub-swarms particle optimization (sspso) technique. it is known that the θ-pso algorithm has better optimization performance than standard pso al...

In this paper, we propose a novel algorithm to enhance the noisy speech in the framework of dual-channel speech enhancement. The new method is a hybrid optimization algorithm, which employs the  combination of  the  conventional θ-PSO and the shuffled sub-swarms particle optimization (SSPSO) technique. It is known that the θ-PSO algorithm has better optimization performance than standard PSO al...

This paper introduces a Shuffled Frog-Leaping Algorithm based method for the optimization of machining parameters for milling operations. An objective function based on maximum profit in milling operation has been used. The algorithm is compared with others techniques and outperforms the results reached by standard shuffled frogleaping algorithm, differential evolution, particle swarm optimizat...

In order to overcome the drawbacks of standard shuffled frog leaping algorithm that converges slowly at the last stage and easily falls into local minima, this paper proposed two-phases learning shuffled frog leaping algorithm. The modified algorithm added the elite Gaussian learning strategy in the global information exchange phase, updated frog leaping rule and added the learning capability t...

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...

Article history: Received: 14.5.2015. Received in revised form: 28.11.2015. Accepted: 1.12.2015. Tool travel and tool switch scheduling are two major issues in hole-making operations. It is necessary to find the optimal sequence of operations to reduce the total processing cost of hole-making operations. In this work therefore, an attempt is made to use both a recently developed particle swarm ...

: This paper presents an algorithm for solving the multi-objective reactive power dispatch problem in a power system. Modal analysis of the system is used for static voltage stability assessment. Loss minimization and maximization of voltage stability margin are taken as the objectives. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer se...

Glowworm swarm optimization (GSO) algorithm is a new intelligent optimization algorithm. Based on the problems of GSO, such as easy to fall into local optimum, slow convergence speed and low optimization precision, an improved GSO with group division is presented. Using shuffled frog leaping algorithm (SFLA), glowworms are divide into different ethnic groups, and local search and global informa...

Shuffled frog-leaping algorithm (SFLA) is a heuristic optimization technique based on swarm intelligence that is inspired by foraging behavior of the swarm of frogs. The traditional SFLA is easy to be premature convergence. So, we present an improved shuffled frog-leaping algorithm with single step search strategy and interactive learning rule(called ‘SI-SFLA’). Single step search strategy enha...

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...