Industrial process condition forecasting methodology based on neo-fuzzy neuron and self-organizing maps
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The condition forecasting of industrial processes represents a key factor to allow the future generation of industrial manufacturing plants. In this regard, this paper presents a novel soft-computing based methodology for the assessment of the current and future condition of industrial processes by the combination of Neo Fuzzy Neuron (NFN) and Self-Organizing Maps (SOM) data-driven based modelling. The proposed method models, individually, the critical signals describing the industrial process.
CitationZurita, D. [et al.]. Industrial process condition forecasting methodology based on neo-fuzzy neuron and self-organizing maps. "Journal of scientific and industrial research", 1 Agost 2019, vol. 78, núm. 8, p. 504-508.