Calculating the energy consumption of electrocoagulation using a generalized structure group method of data handling integrated with a genetic algorithm and singular value decomposition
- 37 Downloads
In this study, a hybrid data mining method for predicting energy consumption is proposed, namely the group method of data handling integrated with a genetic algorithm and singular value decomposition (GMDH-GA/SVD). As the randomness of renewable sources influences prediction methods, prediction model improvements are necessary for further development. Thus, GMDH-GA/SVD is introduced to model energy consumption as the primary criterion for process evaluation in finding the optimum condition to achieve the least energy consumption process. The parameters include the initial pH, the initial dye concentration, the applied voltage, the initial electrolyte concentration and the treatment time. The uncertainty analysis is applied to survey the quantitative performance of the new proposed model compared to existing popular reduced quadratic multiple regression models and two recently published models in the form of a Taylor diagram, indicating the proposed model is the most accurate. Moreover, partial derivative sensitivity analysis was done on the key parameters in the new model to provide insight into the calibration process of the new model.
KeywordsEnergy consumption Sensitivity analysis Biological treatment Formulation
- Ahlawat R, Srivastava VC, Mall ID, Sinha S (2008) Investigation of the electrocoagulation treatment of cotton blue dye solution using aluminium electrodes. CLEAN–Soil, Air. Water 36(10–11):863–869Google Scholar
- Azadeh A, Narimani A, Nazari T (2014) Estimating household electricity consumption by environmental consciousness. Int J Prod Qual Manage 15(1):1–19Google Scholar
- Farlow SJ (1984) Self-organizing methods in modeling: GMDH type algorithms, vol 54. CrC Press, Boca RatonGoogle Scholar
- Yari A, Hosseinzadeh S, Golneshan AA, Ghasemiasl R (2017) Numerical simulation for thermal design of a gas water heater with turbulent combined convection. ASME PS Appl CFD, ASMEGoogle Scholar