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6943584 
Journal Article 
Improved Particle Swarm Optimization Based Adaptive Neuro-Fuzzy Inference System for Benzene Detection 
Pannu, HS; Singh, D; Malhi, AK; , 
2018 
Yes 
CLEAN - Soil, Air, Water
ISSN: 1863-0650
EISSN: 1863-0669 
WILEY 
HOBOKEN 
46 
5 
English 
WOS:000431978000001 
has retraction 10504290 (Retraction of Vol 46, art no 1700162, 2018)
Benzene is a carcinogen and employing hardware sensors to detect its concentration is expensive, along with limited operational efficiency. There is a relation among various atmospheric gas concentrations and therefore, some heuristic regression approaches can be applied for benzene forecasting, if given the concentration level of other gases. This paper proposes a new adaptive benzene prediction model using an improved particle swarm optimization (PSO) based adaptive neuro fuzzy inference system (ANFIS). Improved PSO enhances the performance of ANFIS by considering the multi-objective fitness function involving accuracy, root mean squared error (RMSE), and coefficient of determination (r(2)). The proposed technique has been tested on both publicly available air quality datasets and a real world dataset of Patiala City in India. Extensive analysis reveals that the proposed technique outperforms other state-of-the-art techniques, making it well suited for building effective and economical benzene prediction models.