Bilinear models can approximate a large class of nonlinear systems adequately and usually with considerable parsimony in the number of coefficients required. This paper presents the application of Particle Swarm Optimization (PSO) algorithm to solve both offline and online parameter estimation problem for bilinear systems. First, an Adaptive Particle Swarm Optimization (APSO) is proposed to inc...

Because of computational drawbacks of conventional numerical methods in solving complex optimization problems, researchers may have to rely on meta-heuristic algorithms. Particle swarm optimization (PSO) is one of the most widely used algorithms due to its simplicity of implementation and fast convergence speed. Also, the cuckoo search algorithm is a recently developed meta-heuristic optimizati...

Flowshop scheduling is an interdisciplinary challenge of addressing major optimality criteria of minimizing makespan and total-flow-time. The enumerations for finding the probabilities for improving the utilization of resources turn this problem towards NP-Hard. Particle Swam Optimization (PSO) has proven its ability to find of near optimal solution when problem size is large. Local search tech...

This paper presents an Improved Particle Swarm Optimization (IPSO) to solve the Economic Dispatch (ED) problem with line flow constraints, bus voltage limits and generator operating constraints. In the proposed IPSO method, a new velocity strategy equation is formulated suitable for large scale system and the features of the Constriction Factor Approach (CFA) are also incorporated into the prop...

The position information is becoming more and more important for application in WSNs. So aiming at the location problem, the paper proposes a localization algorithm based on PSO (particle swarm optimization) and Quasi-Newton algorithm, which use PSO to get a satisfying value and then use it as the initial value of Quasi-Newton algorithm to iterate. The simulation experiments are carried out. Th...

This paper presents an optimal design of linear phase digital high pass finite impulse response (FIR) filter using Improved Particle Swarm Optimization (IPSO). In the design process, the filter length, pass band and stop band frequencies, feasible pass band and stop band ripple sizes are specified. FIR filter design is a multi-modal optimization problem. An iterative method is introduced to fin...

In recent years, the problem of network security has been more and more people's attention, as one of the most important technology of network security, intrusion detection technology has gone through nearly thirty years of development, but it still exists some deficiency factors. Aiming at the defects of the traditional BP neural network intrusion detection model in the detection rate and the ...

Radial Basis Function Neural Networks (RBFNNs) have been widely used for classification and function approximation tasks. Hence, it is worthy to try improving and developing new learning algorithms for RBFNNs in order to get better results. This paper presents a new learning method for RBFNNs. An improved algorithm for center adjustment of RBFNNs and a novel algorithm for width determination ha...