@article{(Open Science Index):https://publications.waset.org/pdf/13379,
	  title     = {Predictive Clustering Hybrid Regression(pCHR) Approach and Its Application to Sucrose-Based Biohydrogen Production},
	  author    = {Nikhil and  Ari Visa and  Chin-Chao Chen and  Chiu-Yue Lin and  Jaakko A. Puhakka and  Olli Yli-Harja},
	  country	= {},
	  institution	= {},
	  abstract     = {A predictive clustering hybrid regression (pCHR)
approach was developed and evaluated using dataset from H2-
producing sucrose-based bioreactor operated for 15 months. The aim
was to model and predict the H2-production rate using information
available about envirome and metabolome of the bioprocess. Selforganizing
maps (SOM) and Sammon map were used to visualize the
dataset and to identify main metabolic patterns and clusters in
bioprocess data. Three metabolic clusters: acetate coupled with other
metabolites, butyrate only, and transition phases were detected. The
developed pCHR model combines principles of k-means clustering,
kNN classification and regression techniques. The model performed
well in modeling and predicting the H2-production rate with mean
square error values of 0.0014 and 0.0032, respectively.},
	    journal   = {International Journal of Biomedical and Biological Engineering},
	  volume    = {2},
	  number    = {1},
	  year      = {2008},
	  pages     = {1 - 11},
	  ee        = {https://publications.waset.org/pdf/13379},
	  url   	= {https://publications.waset.org/vol/13},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 13, 2008},
	}