Regression and ANN Models of Pulse Rate for Tricycle Rickshaw
Mahesh S. Gorde1, Atul B. Borade2

1Mahesh S. Gorde*, Assistant Professor, Jawaharlal Darda Institute of Engineering & Technology, Yavatmal, Maharashtra, India.
2Dr. Atul B. Borade, Principal, Government Polytechnic, Gadchiroli, Maharashtra, India.
Manuscript received on December 15, 2019. | Revised Manuscript received on December 20, 2019. | Manuscript published on January 10, 2020. | PP: 3236-3243 | Volume-9 Issue-3, January 2020. | Retrieval Number: C8809019320/2020©BEIESP | DOI: 10.35940/ijitee.C8809.019320
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Abstract: Designing for the oppressed part of the generalized public is one of the fundamental prerequisites for comprehensive design in a developing nation like India. With a spurt being developing inside a nation, the financial distance between those who are well off and the wealthy not are expanding and this divergence is making social agitation in the nation. Tricycles rickshaw is a small-scale ordinary means principally utilized for transportation. Numerous deficiencies were reported in the existing type of tricycle. For optimization of those deficiencies, three different models of cycle rickshaw were utilized, and the input parameter that regulates the consumption of human energy and performance was identified. Regression Analysis (RA) and Artificial Neural Networks (ANN) were utilized for analysis of the experimental data. Both RA and ANN modeling were assessed statistically with the aid of a software tool. RA of the experimental data reveals that input variable load is a most prominent parameter to be focused on tor achieving the objective of expending minimum human energy by a rickshaw puller whereas ANN studies acknowledged the assistance of multiple factors in individual energy. However, load is a most prominent parameter for minimization of individual energy as Outcome. Optimization of input variables using Min-Max principle for various regression models yielded the optimal solution at crank length 167 mm and wheel diameter 675mm for human energy for all linear regression models. 
Keywords: ANN, Chain, Pedaling Mechanism, Regression Analysis, Sprocket, Tricycle.
Scope of the Article: Regression and Prediction