Application of Fuzzy Regression Analysis in Predicting the Performance of the Anaerobic Reactor Co-digesting Spent Tea Waste with Cow Manure

  • Naseem KhayumEmail author
  • Amruta Rout
  • B. B. V. L. Deepak
  • S. Anbarasu
  • S. Murugan
Original Paper


Modelling and optimization of production of different renewable energy sources are receiving great interest by researchers; as they are used to provide gross information on the possibilities of harnessing energy from variety of resources. Spent tea waste (STW) is one of the potential organic wastes remarkably available in India. In this research work, possibility of producing biogas by co-digesting STW with cow manure (CM) was predicted through a novel fuzzy regression approach. Triangular membership functions with five levels were considered for the fuzzy subsets and a Mamdani-type of fuzzy approach was used to implement a total of 125 rules in the IF–THEN format. The digestion time, carbon to nitrogen (C/N) ratio and pH were considered as input parameters, while the biogas yield was considered as an output. Experimental data obtained from the lab scale reactors were used to predict the biogas yield using fuzzy logic methodology. The obtained results were validated with the experimental results by carrying out a regression analysis. The results indicated that a good agreement found between experimental and predicted data with a coefficient of determination R2 = 0.994.

Graphic Abstract


Spent tea waste Cow manure Fuzzy logic Biogas Mamdani approach Regression analysis 



Actual values


Absolute average relative error


Adaptive neuro-fuzzy inference system


Artificial neural network


Anaerobic reactor


Average relative error


Cow manure


Carbon to nitrogen ratio


Firely algorithm


Fuzzy inference system


Genetic algorithm






Mean squared normalised error




Predicted values


Random forest


Root mean squared error


Revolutions per minute


Response surface methodology


Standard deviation


Spent tea waste


Total solid



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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • Naseem Khayum
    • 1
    Email author
  • Amruta Rout
    • 2
  • B. B. V. L. Deepak
    • 2
  • S. Anbarasu
    • 1
  • S. Murugan
    • 1
  1. 1.Department of Mechanical EngineeringNational Institute of Technology RourkelaRourkelaIndia
  2. 2.Department of Industrial DesignNational Institute of Technology RourkelaRourkelaIndia

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