Paresh Chandra Deka

Work place: National Institute of Technology Karnataka, Surathkal, 575025, India



Research Interests: Artificial Intelligence, Neural Networks, Network Architecture, Decision Support System, Algorithm Design


Dr. Paresh Chandra Deka received the Bachelor Degree of Engineering in National Institute of Technology, Silchar, Assam and M.E (Watershed management & Flood control) Gauhati University, Assam. Completed Ph.D in IIT Guwahati. Presently working as Associate Professor, Department of Applied Mechanics and Hydraulics, National Institute of Technology Karnataka, Surathkal, Mangalore 575025. Research interests include, Artificial neural network, Fuzzy logic, Genetic algorithm, Wavelet transform, Support Vector Machine.

Author Articles
Modeling of Air Temperature using ANFIS by Wavelet Refined Parameters

By Karthika. B. S Paresh Chandra Deka

DOI:, Pub. Date: 8 Jan. 2016

The precise modeling of average air temperature is a significant and much essential parameter in frame of reference for decision-making in agriculture field, drought detection and environmental related issues. The aim of this research is to construct an accurate model to modeling average air temperature using hybrid Wavelet-ANFIS techniques. Being cognizant of the fact, uncertainty handling capability is achieved with ANFIS technique; a cognitive approach to integrate ANFIS technique along with pre-processed data by using Wavelet transformation. Detailing on approach, in this work utilized Discrete Wavelet transform under Daubechies mother Wavelet up to 3rd level of decomposition. This study extends up to seven station’s meteorological data records. The following developed hybrid model’s performance is compared with single ANFIS models for all seven stations. The obtained results were evaluated using correlation coefficient, root mean square error and scatter index These results confirmed that the proposed hybridized Wavelet- ANFIS model has estimable potential in terms of modeling temperature than ANFIS model alone.

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