Entity

Time filter

Source Type


Dubey H.M.,Madhav Institute of technology and Science Gwalior | Pandit M.,Madhav Institute of technology and Science Gwalior | Panigrahi B.K.,Indian Institute of Technology Delhi | Udgir M.,Madhav Institute of technology and Science Gwalior
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013

In this article swarm Intelligence based gravitational search algorithm (PSOGSA) is used to solve combined economic and emission dispatch (CEED) problems. The CEED problem is modeled with the objective of minimizing fuel cost as well as emission level while satisfying associated operational constraints. Here the multi-objective function is converted into single objective function using price penalty method. The performance of PSOGSA approach is investigated on standard 10 unit system, 6 unit system and 40 unit system .The results obtained by simulation are compared with the recent reported results. The simulation result shows the fast convergence and its potential to solve complicated problems in power system. © 2013 Springer International Publishing. Source


Dubey H.M.,Madhav Institute of technology and Science Gwalior | Panigrahi B.K.,Indian Institute of Technology Delhi | Pandit M.,Madhav Institute of technology and Science Gwalior | Udgir M.,Shri Vaishnav Institute of Technology and Science
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2015

This article presents a nature inspired optimization algorithm to solve complex economic load dispatch problem using hybrid PSOGSA algorithm. The hybrid PSOGSA utilizes the ability of social thinking in PSO to strengthen the search ability of GSA. The performance of the algorithm is verified by implementation on three test systems having different complexity levels and dimensions; the standard 6 unit system have non smooth cost curve, the 26-unit system is modeled with cubical cost function and a large scale 110 unit system is selected for validation. Results obtained are compared with the methods available in the recent literature. The findings affirm the capability of hybrid PSOGSA in obtaining higher quality solutions efficiently over other existing methods. © Springer International Publishing Switzerland 2015. Source


Dubey H.M.,Madhav Institute of technology and Science Gwalior | Pandit M.,Madhav Institute of technology and Science Gwalior | Panigrahi B.K.,Indian Institute of Technology Delhi
Lecture Notes in Electrical Engineering | Year: 2015

This paper presents a novel nature inspired cuckoo search algorithm (CSA) to solve short term hydrothermal scheduling problems. The effectiveness of CSA algorithm is examined on three different test cases considering quadratic cost with and without prohibited discharge zones (PDZ), quadratic cost with prohibited discharge zones and valve point loading (VPL) effect in thermal unit. The outcome of simulation were compared with other recent reported approaches demonstrates the superiority of CSA algorithm. © Springer India 2015. Source


Yadav M.,Madhav Institute of technology and Science Gwalior | Wadhwani S.,Madhav Institute of technology and Science Gwalior
International Journal of Engineering and Technology | Year: 2011

In this work an automatic fault classification system is developed for bearing fault classification of three phase induction motor. The system uses the wavelet packet decomposition using 'db8' mother wavelet function for feature extraction from the vibration signal, recorded for various bearing fault conditions. The selection of best node of wavelet packet tree is performed by using best tree algorithm along with minimum Shannon entropy criteria. The ten statistical features such as peak value, root mean square value (RMS), kurtosis, skewness etc. are extracted from the wavelet packet coefficient of optimal node. The extracted feature then was used to train and test neural network fault classification. The artificial neural network system was designed to classify the rolling element bearing condition: healthy bearing (HB) rolling element fault (REF), inner race fault (IRF) and Outer race fault (ORF) for fault classification. The over all fault classification rate is 98.33% of the artificial neural network fault classifier. Source


Vimal J.,Motilal Nehru National Institute of Technology | Srivastava R.K.,Motilal Nehru National Institute of Technology | Bhatt A.D.,Motilal Nehru National Institute of Technology | Sharma A.K.,Madhav Institute of technology and Science Gwalior
Engineering Solid Mechanics | Year: 2014

Finite element method is used to study the free vibration analysis of functionally graded skew plates. The material properties of the skew plates are assumed to vary continuously through their thickness according to a power-law distribution of the volume fractions of the plate constituents. The first order shear deformation theory is used to incorporate the effects of transverse shear deformation and rotary inertia. Convergence study with respect to the number of nodes has been carried out and the results are compared with those from past investigations available in the literature. Two types of functionally graded skew plates - Al/ZrO2 and Al/Al2O3 are considered in this study and the effects of the volume fraction, different external boundary conditions and thickness ratio on the natural frequencies are studied in detail. © 2014 Growing Science Ltd. All rights reserved. Source

Discover hidden collaborations