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This paper proposes a clustering-analysis-based membership functions formation method for fuzzy controller of ball mill pulverizing system. An improved density-based clustering algorithm is presented to detect the clusters in the field database and the clusters are agglomerated or divided to form the new clusters according to the proximity or the dissimilarity between objects. Then, the new clusters...
Discretization algorithms have played an important role in data mining, which is widely applied in industrial control. Since the current discretization methods can not accurately reflect the degree of the class-attribute interdependency of the industrial database, a new discretization algorithm, which is based on information distance criterion and ant colony optimization algorithm(ACO), is proposed...
Hybridization is a useful method to enhance the performance of particle swarm optimizer (PSO). In this paper, a novel particle swarm optimizer (NHPSO) combining PSO with a constriction factor (CF-PSO) and the fully informed particle swarm optimizer (FIPSO) in cycles is proposed, in order to balance the convergence speed and search accuracy. Six most commonly used benchmarks are used to evaluate the...
Precise load measurement is important for the supervision of the pulverizing process in thermal power plant. This paper presents an adaptive soft sensor based on PCA and FasArt neural networks to achieve this purpose. PCA is firstly used to compress the input secondary variables and the dimension is reduced from 9 to 3 with little loss of information. Then FasArt model derive the knowledge from the...
Quantitative attribute partition is an important work of association rule mining, which is widely applied in industrial control at present, and the current partition methods are not suitable for the industrial database, which is generally large, high-dimensional and coupling. The paper proposes a density-based quantitative attribute partition algorithm for industrial database. The proposed algorithm...
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