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Keywords: PSO QPSO Mean best position Weight parameter WQPSO a b s t r a c t Quantum-behaved particle swarm optimization (QPSO) algorithm is a global convergence guaranteed algorithms, which outperforms original PSO in search ability but has fewer parameters to control. In this paper, we propose an improved quantum-behaved particle swarm optimization with(More)
Based on the quantum-behaved particle swarm optimization (QPSO) algorithm, we formulate the philosophy of QPSO and introduce a so-called mainstream thought of the population to evaluate the search scope of a particle and thus propose a novel parameter control method of QPSO. After that, we test the revised QPSO algorithm on several benchmark functions and(More)
We first briefly review the state of the art of digital in-line holographic microscopy (DIHM) with numerical reconstruction and then discuss some technical issues, such as lateral and depth resolution, depth of field, twin image, four-dimensional tracking, and reconstruction algorithm. We then present a host of examples from microfluidics and biology of(More)
Adaptive infinite impulse response (IIR) filters have shown their worth in a wide range of practical applications. Because the error surface of IIR filters is multimodal in most cases, global optimization techniques are required for avoiding local minima. In this paper, we employ a global optimization algorithm, Quantum-behaved particle swarm optimization(More)
BACKGROUND An outbreak of hand, foot, and mouth disease (HFMD) included 1149 people in Linyi City, Shandong Province, China, in 2007: three children died. OBJECTIVES To characterize the pathogens responsible for this outbreak and to analyze their genetic features. STUDY DESIGN A total of 233 clinical specimens were collected from 105 hospitalized(More)
The endoplasmic reticulum (ER) is the cellular organelle responsible for protein folding and assembly, lipid and sterol biosynthesis, and calcium storage. The unfolded protein response (UPR) is an adaptive intracellular stress response to accumulation of unfolded or misfolded proteins in the ER. In this study, we show that the most conserved UPR sensor(More)
Quantum-behaved particle swarm optimization (QPSO), motivated by concepts from quantum mechanics and particle swarm optimization (PSO), is a probabilistic optimization algorithm belonging to the bare-bones PSO family. Although it has been shown to perform well in finding the optimal solutions for many optimization problems, there has so far been little(More)
The mutation mechanism is introduced into quantum-behaved particle swarm optimization to increase its global search ability and escape from local minima. Based on the characteristic of QPSO algorithm, the variable of gbest and mbest is mutated with Cauchy distribution respectively. The experimental results on test functions show that QPSO with gbest and(More)