Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A biofilter is a biological reactor in which a certain pollutant is eliminated by the action of microorganisms. In this work, the removal efficiency of a lab-scale biofilter for eliminating hydrogen sulphide (H 2 S) has been modelled. To that end, multilayer perceptron (MLP) neural networks and multiple linear regression (MLR) have been used and then, results obtained with both techniques have been compared. The biofilter has been operating during 194 days and for modelling purposes, it has been considered as a system in which changes in the flow and concentration of H 2 S entering the biofilter are follod by changes in the removal efficiency of the reactor. In all cases, to obtain true representative values corresponding to the different equilibrium situations, before removal efficiencies (outputs) re measured, 24 hours re allod after the H 2 S load was changed by altering the inlet concentration and flow. The results shod that a multilayer perceptron 2-2-1 (MLP) model was able to explain 92% (R 2 =0.92) of the overall variability detected in the removal efficiency of the biofilter corresponding to a wide range of operating conditions. The MLR model yielded a value of R 2 =0.72. The MLP outperforms the MLR though not dramatically. The explanation might be that the combination of a great number of highly non-linear mechanisms tends to linearize the overall effect, at least to a certain extent. As a conclusion, the use of neural networks and more specifically, MLP models can describe the behaviour of a biofilter more accurately than simple linear regression models.
['Gabriel Ibarra-Berastegi', 'A. Elias', 'R. Arias', 'Astrid Barona']
I am writing a research paper on a idea Artificial Neural Networks vs Linear Regression in a Fluid Mechanics and Chemical Modelling Problem: Elimination of Hydrogen Sulphide in a Lab-Scale Biofilter
[{"from": "human", "value": "I am writing a research paper on a idea Artificial Neural Networks vs Linear Regression in a Fluid Mechanics and Chemical Modelling Problem: Elimination of Hydrogen Sulphide in a Lab-Scale Biofilter"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A biofilter is a biological reactor in which a certain pollutant is eliminated by the action of microorganisms. In this work, the removal efficiency of a lab-scale biofilter for eliminating hydrogen sulphide (H 2 S) has been modelled. To that end, multilayer perceptron (MLP) neural networks and multiple linear regression (MLR) have been used and then, results obtained with both techniques have been compared. The biofilter has been operating during 194 days and for modelling purposes, it has been considered as a system in which changes in the flow and concentration of H 2 S entering the biofilter are follod by changes in the removal efficiency of the reactor. In all cases, to obtain true representative values corresponding to the different equilibrium situations, before removal efficiencies (outputs) re measured, 24 hours re allod after the H 2 S load was changed by altering the inlet concentration and flow. The results shod that a multilayer perceptron 2-2-1 (MLP) model was able to explain 92% (R 2 =0.92) of the overall variability detected in the removal efficiency of the biofilter corresponding to a wide range of operating conditions. The MLR model yielded a value of R 2 =0.72. The MLP outperforms the MLR though not dramatically. The explanation might be that the combination of a great number of highly non-linear mechanisms tends to linearize the overall effect, at least to a certain extent. As a conclusion, the use of neural networks and more specifically, MLP models can describe the behaviour of a biofilter more accurately than simple linear regression models."}]