2021-04-122011-01-019780769546018SCOPUS;2-s2.0-84855915895http://hdl.handle.net/10784/27887The estimation of biomass production of d-endotoxins of the Bacillus thuringiensis (Bt) is a major problem in biotechnological processes, as bio-insecticides, which has been addressed with different methodologies such as extended Kalman filters (EKF), phenomenological observers, among others. This paper presents a comparison in the estimation of biomass concentration of d - endotoxins of the Bacillus thuringiensis (Bt), using Mamdani fuzzy inference systems (FIS), neural networks (NN) and adaptive neuro-fuzzy inference system (ANFIS) trained with differents clustering algorithms; and comparing the associated outcomes among these. © 2011 IEEE.enginfo:eu-repo/semantics/conferencePaperAdaptive neuro-fuzzy inference systemBacillus thuringiensisBatch bioreactorsBiomass concentrationsBiomass productionsBiotechnological processFuzzy inference systemsMamdaniArtificial intelligenceBacilliBacteriologyBiomassClustering algorithmsEstimationExtended Kalman filtersFuzzy inferenceFuzzy neural networksInference enginesFuzzy systems2021-04-12Muñoz, A.A.G.Quintero, O.L.10.1109/TAAI.2011.15