THERMAL SCIENCE

International Scientific Journal

Thermal Science - Online First

online first only

K-nearest neighbour technique for the effective prediction of refrigeration parameter compatible for automobile

ABSTRACT
Manufacturing Simulation is an encouraging research area in resent decade. Creation or development of better simulation tool or technique is one of the major intension in manufacturing simulation. In resent research most of the manufacturing processes are simulated successfully. But some processes are not yet simulated effectively, especially automatic air conditioning system or refrigeration system. The automatic AC system for the passenger vehicle are not yet effectively simulated. Hence in this paper a machine learning technique is adopted for the effective prediction of parameter of automatic AC system. The proposed system uses KNN technique for the prediction of parameter will less error and high accuracy. The proposed system is implemented using Matlab and its performance is compared with the SVM and ANN in terms of MSE and accuracy. The proposed technique outperforms the conventional technique and suggest that the KNN become the most suitable technique for the modelling and performance analysis of automatic AC system.
KEYWORDS
PAPER SUBMITTED: 2019-04-13
PAPER REVISED: 2019-05-12
PAPER ACCEPTED: 2019-06-03
PUBLISHED ONLINE: 2019-11-17
DOI REFERENCE: https://doi.org/10.2298/TSCI190623436P
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