000			a
999			_c17667 _d17667
003			OSt
005			20220926152718.0
008			220926b xxu||||| |||| 00| 0 eng d
040			_aAIKTC-KRRC _cAIKTC-KRRC
100			_918123 _aDhande, D. Y.
245			_aEvaluation of emission characteristics and performance of pomegranate ethanol blended S. I. Engine using artificial neural network and rule learner classifier
250			_aVol.103(2), June
260			_aNew York _bSpringer _c2022
300			_a453-466p.
520			_aWaste pomegranate fruit is one of the new sources of ethanol. Using four different ethanol mixes, the emission performance of S.I. engine was measured at varied running speeds. Ethanol mixed gasoline enhances the quality of engine exhaust emissions, except for nitrogen oxides. Engine performance was found optimum using a 15% ethanol blend and a 1500 rpm speed. The emission characteristics were further examined using artificial neural network and rule learner classifiers. Experiments yielded data sets in which emission characteristics of engines were mapped in relation to engine speed and ethanol/petrol mixtures. These datasets were utilised to train artificial neural networks and rule learner classifiers to establish relationships among emission characteristics, speeds, and ethanol combinations. Both models were tested, and the rule learner classifier was found to be more accurate than the artificial neural network. Emission characteristics, speed, and ethanol combinations can all be correlated using the proposed rule learner algorithm.
650		0	_94642 _aHumanities and Applied Sciences
700			_918130 _a Gaikwad, D. P.
773	0		_x 2250-2149 _dSwitzerland Springer _tJournal of the institution of engineers (India): Series A
856			_uhttps://link.springer.com/article/10.1007/s40030-022-00639-z _yClick here
942			_2ddc _cAR