An Optimized K-Harmonic Means Algorithm Combined with Modified Particle Swarm Optimization and Cuckoo Search Algorithm

Abstract

Abstract. Among the data clustering algorithms, k-means (KM) algorithm is one of the most popular clustering techniques due to its simplicity and efficiency. However, k-means is sensitive to initial centers and it has the local optima problem. K-harmonic-means (KHM) clustering algorithm solves the initialization problem of k-means algorithm, but it also has local optima problem. In this paper, we develop a new algorithm for solving this problem based on an improved version of particle swarm optimization (IPSO) algorithm and KHM clustering. In the proposed algorithm, IPSO is equipped with Cuckoo Search algorithm and two new concepts used in PSO in order to improve the efficiency, fast convergence and escape from local optima. IPSO updates positions of particles based on a combination of global worst, global best with personal worst and personal best to dynamically be used in each iteration of the IPSO. The experimental result on five real-world datasets and two artificial datasets confirms that this improved version is superior to k-harmonic means and regular PSO algorithm. The results of the simulation show that the new algorithm is able to create promising solutions with fast convergence, high accuracy and correctness while markedly improving the processing time.

An Integration of Neural Network and Shuffled Frog-Leaping Algorithm for CNC Machining Monitoring

“…(a) SFLA-ANN is the most efficient for the data fusion with the objective to predict the potency of the periodic component of the signal from the sensors, (b) SFLA is a leading optimization method for ANN, particularly in the presence of numerous local minima of the objective function, (c) SFLA-ANN model incorporates the local search capability of the ANN and global searching capability of SFLA. As one of the main possible future research directions, other efficient metaheuristics may be integrated with ANN and tested compared to the existing methods such as Ant Colony Optimization (ACO) algorithm [39], Cuckoo Optimization Algorithm (COA) [7,30] Particle…”