Title :
Time series forecasting by means of SOM aided Fuzzy Inference Systems
Author :
Zurita, Daniel ; Carino, Jesus A. ; Sala, Enric ; Delgado-Prieto, Miguel ; Ortega, Juan A.
Author_Institution :
Dept. of Electron. Eng., Tech. Univ. of Catalonia, Terrassa, Spain
Abstract :
The forecast of industrial process time series represents a critical factor in order to assure a proper operation of the whole manufacturing chain, as it allows to act against any process deviation before it affects the final manufactured product. In this paper, in order to take advantage from process relations and improve forecasting performance, a prediction method based in Adaptive Neuro Fuzzy Inference System (ANFIS) and Self-Organizing Maps is presented. The novelties of the proposed method are based on considering, as an input of an ANFIS model, the interrelations of process variables regarding the signal that wants to be forecasted, by means of topology preservation SOM. An experimental study performed with real industrial data from a cooper manufacturing plant indicated the suitability of the proposed method in time series forecasting applications.
Keywords :
forecasting theory; fuzzy reasoning; fuzzy set theory; manufacturing industries; manufacturing processes; production engineering computing; self-organising feature maps; time series; topology; ANFIS model; SOM; adaptive neuro fuzzy inference system; cooper manufacturing plant; industrial process time series forecasting; manufacturing chain; prediction method; self-organizing map; topology preservation; Data models; Forecasting; Fuzzy logic; Manufacturing; Neurons; Predictive models; Training; Artificial intelligence; Condition monitoring; Fuzzy neural networks; Machine learning; Predictive models; Prognosis; Time series analysis;
Conference_Titel :
Industrial Technology (ICIT), 2015 IEEE International Conference on
Conference_Location :
Seville
DOI :
10.1109/ICIT.2015.7125354
