@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}, }