Fuzzy Logic and Statistical Based Modelling to Predict Rural Solid Waste Generation of West Bengal
Anshuman Pal1, Pankaj Kr. Roy2
1Anshuman Pal*, School of Water Resources Engineering, Jadavpur University, Kolkata India.
2Pankaj Kr. Roy, School of Water Resources Engineering, Jadavpur University, Kolkata India.
Manuscript received on June 10, 2020. | Revised Manuscript received on June 25, 2020. | Manuscript published on July 10, 2020. | PP: 44-49 | Volume-9 Issue-9, July 2020 | Retrieval Number: 100.1/ijitee.I6829079920 | DOI: 10.35940/ijitee.I6829.079920
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Waste generation prediction is a vital component to planning of rural solid waste management. Based on the past statistical data mathematical model can be develop but incorporation of new data cannot be done. In this situation advance model need to be developed, which can predict. Fuzzy logic may be one option for develop such model because dynamic and linguistic date can be used as an input parameter. A mathematical model has been developed to predicting the total. Rural waste generation using fuzzy logic if west Bengal study area. House hold, population, per capita income, district wise domestic product, literacy rate were considered as an independent variable for predicting rural solid waste generation. To described the dependent and independent variable triangular and trapezoidal shaped membership function are used. To described the defuzzification centroid method has been applied. Initially two input variables have been used to identify the correlation with rural solid waste generation Finally all input variable considered for the mathematical model. Per-capita waste generation in rural west Bengal average 150 to 300 gm day. The statistical analysis rebuilds that age group wise population and income model is the best fitted model.
Keywords: Rural Solid waste Generation, Per capita, Fuzzy logic, Modelling.
Scope of the Article: Fuzzy Logics