In this paper, two new cluster analysis methods based on glowworm swarm optimization (GSO) algorithm are proposed. The first algorithm showed how GSO can be used to self-organization cluster analysis. The second algorithm is hybrid the GSO clustering analysis with the K-means algorithm to accelerate classification. Two clustering algorithms are tested on three data sets; experimental results sh...

To better regulate the speed of brushless DC motors, an improved algorithm based on original Glowworm Swarm Optimization is proposed. The proposed solves problems poor robustness, slow convergence, and low accuracy exhibited by traditional PID controllers. When selecting glowworm neighborhood set, optimization scheme growth competition behavior weeds applied to a single prevent falling into loc...

To make glowworm swarm optimization (GSO) algorithm solve multi-extremum global optimization more effectively, taking into consideration the disadvantages and some unique advantages of GSO, the paper proposes a hybrid algorithm of Broyden–Fletcher–Goldfarb– Shanno (BFGS) algorithm and GSO, i.e., BFGS-GSO by adding BFGS local optimization operator in it, which can solve the problems effectively ...

In this paper, the state estimation (SE) problem is formulated as a general nonlinear programming problem with equality constraints and boundary limits on the state variables. The objective of this paper is to incorporate the Unified Power Flow Controller (UPFC) into the SE algorithm. UPFC has the potential to independently control the voltage, active and reactive power flows in the system. In ...

We research maximum range expansion using a fixed number of mobile wireless nodes along a line which do distributed MIMO (Multiple Input Multiple Output) in diversity configuration, also known as cooperative transmission (CT). The emphasis is on optimal clusters and locations of these clusters to maximize the multi-hop reach along the line based on the swarm intelligence algorithms which are th...