This paper models the process of a recommender system as a multiobjective optimization problem, a discrete particle swarm optimization framework is established and has been integrated into multiobjective optimization, consequently, a multiobjective discrete particle swarm optimization algorithm is proposed to solve the modeled optimization problem. Each run of the current mainstream recommender...

Particle swarm optimization algorithm in solving complex functions, such as slow convergence, accuracy is not high, easily falling into local optimum problem. Based on the chaos optimization is introduced into particle swarm optimization algorithm, given the chaotic particle swarm optimization algorithm. In order to improve the image quality of CMOS image sensor, the image of the main noise sou...

-Particle swarm optimization (PSO) is undoubtedly one of the most widely used swarm intelligence algorithm. Generally, each particle is assigned an initial value randomly. In this paper an improved PSO clustering algorithm based on affinity propagation (APPSO) is proposed which provides new ideas and methods for cluster analysis. Firstly the proposed algorithm get initial cluster centers by aff...

in this article, a multi-objective memetic algorithm (ma) for rule learning is proposed. prediction accuracy and interpretation are two measures that conflict with each other. in this approach, we consider accuracy and interpretation of rules sets. additionally, individual classifiers face other problems such as huge sizes, high dimensionality and imbalance classes’ distribution data sets. this...

global optimization methods play an important role to solve many real-world problems. flower pollination algorithm (fp) is a new nature-inspired algorithm, based on the characteristics of flowering plants. in this paper, a new hybrid optimization method called hybrid flower pollination algorithm (fppso) is proposed. the method combines the standard flower pollination algorithm (fp) with the par...