A Unique Variable Selection Approach in Fuzzy Modeling to Predict Biogas Production in Upflow Anaerobic Sludge Blanket R
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RESEARCH ARTICLE-CHEMICAL ENGINEERING
A Unique Variable Selection Approach in Fuzzy Modeling to Predict Biogas Production in Upflow Anaerobic Sludge Blanket Reactor (UASBR) Treating Distillery Wastewater Mital J. Dholawala1 · R. A. Christian1 Received: 10 May 2019 / Accepted: 26 April 2020 © King Fahd University of Petroleum & Minerals 2020
Abstract The upflow anaerobic sludge blanket reactor is known to carry out a complex high-rate anaerobic process used to treat distillery wastewater and is met with many conflicts because of continuous fluctuations in quantity and quality of wastewater, and therefore, it incorporates a lot of uncertainties in operating, controlling and measuring different parameters. In this paper, a multiple-input and single-output fuzzy knowledge-based model was developed to predict biogas production in realscale upflow anaerobic sludge blanket reactor treating distillery wastewater incorporating seven input variables such as pH (effluent), COD load, COD reduction, temperature, alkalinity-to-acidity ratio, pH (influent) and spent flow rate. Trapezoidal and triangular membership functions were classified to represent the fuzzy sets, and a Mamdani type of fuzzy inference system was used in Matlab fuzzy toolbox. A total of 270 IF–THEN rules have been generated in the fuzzy rule editor using a knowledge-based system. Furthermore, an innovative sequential variable selection approach has been proposed to recognize the most significant parameters in the fuzzy model to predict biogas production which makes the model more practical, manageable and efficient. As a result of the sequential variable selection approach, a combination of five variables such as temperature, COD reduction, COD load, pH(I) and alkalinity-to-acidity ratio has been chosen as the optimal set of variables. The results of the root mean square error and coefficient of determination clearly indicated the better predictive ability of the fuzzy model with the five most important input variables obtained from the sequential variable selection approach than the one with all seven variables. Keywords Fuzzy modeling · Biogas production · Variable selection · Distillery wastewater · UASBR
1 Introduction Distillery industries produce highly polluted wastewater known as spent wash during the process of alcohol production and are therefore known to be one of the most pollution-causing industries. Spent wash refers to the wastewater containing molasses which are the common raw material used in this kind of industry due to its low cost and easy availability. Every liter of alcohol production generates 8–15 L of effluent. India has 319 distilleries through which 3.25 billion liters of alcohol is produced and 40.4 billion liters of wastewater is generated annually [1]. According to * Mital J. Dholawala [email protected] 1
Civil Engineering Department, Sardar Vallabhbhai National Institute of Technology, Surat, Gujarat, India
the Ministry of Environment and Forests (MoEF), distilleries are categorized at the top in the “red ca
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