Papers by Bhavesh Chauhan
Analytical assessment of implementation aspect of regional rapid transit system
Decision Analytics Journal
Timetable rationalization & Operational improvements by human intervention in an urban rail transit system: An exploratory study
Transportation Research Interdisciplinary Perspectives, 2022
Ensemble Learning based Age Invariant Fea-ture Recognition Using Soft Computing
Design Engineering, 2021
Face recognition system is a state-of-the-art computer vision application within the artificial i... more Face recognition system is a state-of-the-art computer vision application within the artificial intelligence arena. Face recognition is the automated recognition of humans for their names/unique ID. The age invariant face recognition is a challenge task in the field of face recog-nition. In this work, we have introduced a stacked support vector machine where kernel activation of prototype examples is combined in nonlinear ways. The proposed work integrates soft compu-ting-based support vector machine (SVM) with deep SVM. The proposed model uses the implied relation between the variables described above in order to optimize their overall performance. Specifically, our method uses three different stages of complex convolution neural networks that detect and analyze the location of faces position and landmarks. This work has introduced cross-age celebrity dataset (CACD) for both single as well as cross-database enabling the transition of age. The proposed work has been implemented in t...
American Journal of Electrical and Electronic Engineering, 2016
Aadaptability and self-organization of a system is two key factors, when it comes to how well the... more Aadaptability and self-organization of a system is two key factors, when it comes to how well the system is surviving for the changes to the environment and how these work within the plant. Different tuning methods and soft computing techniques improve these two factors in controllers. Considering the increasing complexity of dynamic systems along with their need for feedback controls, using more complicated controls has become necessary and these techniques can be a suitable response to this necessity. This paper briefly describes a review on different techniques used for PID tuning as well as soft computing algorithm for hybrid controllers. This paper provides a comprehensive reference source for people working with hybrid controllers.
Electric Load Forecasting Using Fuzzy Knowledge Base System with Improved Accuracy
Intelligent Learning for Computer Vision, 2021
International Journal of Computer and Electrical Engineering, 2013
Neuro-Fuzzy Approach Based Short Term Electric Load Forecastig
2005 IEEE/PES Transmission & Distribution Conference & Exposition: Asia and Pacific
Abstract The basic problem for electric utilities and system operators is to maximize the short a... more Abstract The basic problem for electric utilities and system operators is to maximize the short and long term operations system performance given the operating and economic characteristics generating units, the transmission line constraints and the limited amounts ...
Power Grids in India: A Paradigm Shift from Dumb to Smart Grids
2013 IEEE Green Technologies Conference (GreenTech), 2013
This study concerns with the developments in the field of power grids in India. It traces its evo... more This study concerns with the developments in the field of power grids in India. It traces its evolution, the need to upgrade and its current state of affairs in terms of various initiatives being undertaken to realize significant transformation in the area of power grids development.
2014 IEEE Students' Conference on Electrical, Electronics and Computer Science, 2014
Brushless DC Motor (BLDCM) has been widely used in industries because of its properties such as h... more Brushless DC Motor (BLDCM) has been widely used in industries because of its properties such as high efficiency, reliability, high starting torque, less electrical noise and high weight to torque ratio. In order to control the speed of BLDCM, a number of controllers are used. In this paper, transient performances of BLDCM with conventional controller like PID have been evaluated and the results have been compared with fuzzy based controllers. Compared to PID controller, fuzzy controllers provide better speed response but conventional controllers offer better response with changing load at the cost of long settling time. MATLAB/SIMULINK environment is used to carry out the above investigation.
IEEE Transactions on Power Systems, 2011
This paper presents two hybrid neural networks derived from fuzzy neural networks (FNN): wavelet ... more This paper presents two hybrid neural networks derived from fuzzy neural networks (FNN): wavelet fuzzy neural network (WFNN) using the fuzzified wavelet features as the inputs to FNN and fuzzy neural network (FNCI) employing the Choquet integral as the outputs of FNN. The learning through FNCI is simplified by the use of q-measure and the speed of convergence of the parameters is increased by reinforced learning. The underlying fuzzy models of these hybrid networks are a modified form of fuzzy rules of Takagi-Sugeno model. The number of fuzzy rules is found from a fuzzy curve corresponding to each input-output by counting the total number of peaks and troughs in the curve. The models can forecast hourly load with a lead time of 1 h as they deal with short-term load forecasting. The results of the two hybrid networks using Indian utility data are compared with ANFIS and other conventional methods. The performance of the proposed WFNN is found superior to all the other compared methods. Index Terms-Fuzzy systems, neural networks, short-term load forecasting, wavelet transforms and Choquet integral.
Load forecasting using wavelet fuzzy neural network
International Journal of Knowledge-based and Intelligent Engineering Systems, 2010
This paper presents a Wavelet Fuzzy Neural Network (WFNN) that takes the fuzzified wavelet featur... more This paper presents a Wavelet Fuzzy Neural Network (WFNN) that takes the fuzzified wavelet features as inputs to Fuzzy Neural Network. This network is constructed from the fuzzy rules which are modified form of the fuzzy rules of Takagi-Sugeno fuzzy model. The ...
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Papers by Bhavesh Chauhan