@Article{2018.100000014,
AUTHOR = {M. Carmel Sobia, A. Abudhahir},
TITLE = {An Efficient Adaptive Network-Based Fuzzy Inference System with  Mosquito Host-Seeking For Facial Expression Recognition},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {24},
YEAR = {2018},
NUMBER = {4},
PAGES = {869--881},
URL = {http://www.techscience.com/iasc/v24n4/39811},
ISSN = {2326-005X},
ABSTRACT = {In this paper, an efficient facial expression recognition system using ANFIS-MHS 
(Adaptive Network-based Fuzzy Inference System with Mosquito Host-Seeking) 
has been proposed. The features were extracted using MLDA (Modified Linear 
Discriminant Analysis) and then the optimized parameters are computed by 
using mGSO (modified Glow-worm Swarm Optimization).The proposed system 
recognizes the facial expressions using ANFIS-MHS. The experimental results 
demonstrate that the proposed technique is performed better than existing 
classification schemes like HAKELM (Hybridization of Adaptive Kernel based 
Extreme Learning Machine), Support Vector Machine (SVM) and Principal 
Component Analysis (PCA). The proposed approach is implemented in MATLAB.},
DOI = {10.31209/2018.100000014}
}