Evaluation of emission characteristics and performance of pomegranate ethanol blended S. I. Engine using artificial neural network and rule learner classifier (Record no. 17667)

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control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220926152718.0
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fixed length control field 220926b xxu||||| |||| 00| 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency AIKTC-KRRC
Transcribing agency AIKTC-KRRC
100 ## - MAIN ENTRY--PERSONAL NAME
9 (RLIN) 18123
Author Dhande, D. Y.
245 ## - TITLE STATEMENT
Title Evaluation of emission characteristics and performance of pomegranate ethanol blended S. I. Engine using artificial neural network and rule learner classifier
250 ## - EDITION STATEMENT
Volume, Issue number Vol.103(2), June
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. New York
Name of publisher, distributor, etc. Springer
Year 2022
300 ## - PHYSICAL DESCRIPTION
Pagination 453-466p.
520 ## - SUMMARY, ETC.
Summary, etc. Waste 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 - SUBJECT ADDED ENTRY--TOPICAL TERM
9 (RLIN) 4642
Topical term or geographic name entry element Humanities and Applied Sciences
700 ## - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 18130
Co-Author Gaikwad, D. P.
773 0# - HOST ITEM ENTRY
International Standard Serial Number 2250-2149
Place, publisher, and date of publication Switzerland Springer
Title Journal of the institution of engineers (India): Series A
856 ## - ELECTRONIC LOCATION AND ACCESS
URL https://link.springer.com/article/10.1007/s40030-022-00639-z
Link text Click here
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Koha item type Articles Abstract Database
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Permanent Location Current Location Shelving location Date acquired Barcode Date last seen Price effective from Koha item type
          School of Engineering & Technology School of Engineering & Technology Archieval Section 2022-09-26 2022-1744 2022-09-26 2022-09-26 Articles Abstract Database
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