An efficient cluster-based tribes optimization algorithm for functional-link-based neurofuzzy inference systems

Chen, Cheng-Hung; Liao, Yen-Yun

doi:10.1016/j.asoc.2013.01.026

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Subtractive Clustering1

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Cited by 4 publications

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“…The subtractive clustering [3] is a fast algorithm in estimating the number of cluster and cluster center during a set of data. There are normalized data ) , , , (…”

Section: Subtractive Clusteringmentioning

confidence: 99%

Predictive Model of Energy Consumption in Beer Production

Pu¹,

Bai²

2013

JESTR

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The predictive model of energy consumption is presented based on subtractive clustering and Adaptive-Network-Based Fuzzy Inference System (for short ANFIS) in the beer production. Using the subtractive clustering on the historical data of energy consumption, the limit of artificial experience is conquered while confirming the number of fuzzy rules. The parameters of the fuzzy inference system are acquired by the structure of adaptive network and hybrid on-line learning algorithm. The method can predict and guide the energy consumption of the factual production process. The reducing consumption scheme is provided based on the actual situation of the enterprise. Finally, using concrete examples verified the feasibility of this method comparing with the Radial Basis Functions (for short RBF) neural network predictive model.

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“…The subtractive clustering [3] is a fast algorithm in estimating the number of cluster and cluster center during a set of data. There are normalized data ) , , , (…”

Section: Subtractive Clusteringmentioning

confidence: 99%