Experiments and adaptive-network-based fuzzy inference system modelling in a hybrid up-flow anaerobic sludge blanket reactor to assess industrial azadirachtin effluent quality

被引：4

作者：

Mullai, P. ^{[1
]}

Vishali, S. ^{[2
]}

Sobiya, E. ^{[1
]}

机构：

[1] Annamalai Univ, Fac Engn & Technol, Dept Chem Engn, Annamalainagar 608002, Tamil Nadu, India

[2] SRM Inst Sci & Technol, Coll Engn & Technol, Dept Chem Engn, Chennai 603203, Tamil Nadu, India

来源：

BIORESOURCE TECHNOLOGY | 2022年 / 358卷

关键词：

Azadirachtin wastewater; ANFIS modelling; Hybrid up-flow anaerobic sludge blanket; reactor; BIOGAS PRODUCTION; WASTE-WATER; MICROBIAL COMMUNITY; ANFIS; BIODEGRADATION; DIGESTION; KINETICS; ANN;

D O I：

10.1016/j.biortech.2022.127395

中图分类号：

S2 [农业工程];

学科分类号：

0828 ;

摘要：

Experimental investigations were carried out for the treatment of industrial azadirachtin effluent in a hybrid upflow anaerobic sludge blanket (HUASB) reactor continuously for 115 days in three stages at mesophilic temperature (30 - 35C). An adaptive-network-based fuzzy inference system (ANFIS) modelling and statistical regression analysis were applied with the raw data. In the ANFIS modelling as well as in the statistical regression analysis, the operating parameters such as initial pH, influent COD, effluent COD and biogas generation (X1, X2, X3 and X4) were taken as variables and effluent BOD values as a response (Y). The average percentage error (APE) values of ANFIS modelling were 2.18, 12.29, and 0.01%, for stage-I, II and III respectively. These values indicated that ANFIS modelling performed well in all the three stages and provided more accurate results.

引用

页数：6

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