24 citations · 32 across the 4 of their papers we have counts for
5 papers
Training a Feed-forward Neural Network with Artificial Bee Colony Based Backpropagation Method
Sudarshan Nandy, Partha Pratim Sarkar, Achintya Das
Back-propagation algorithm is one of the most widely used and popular techniques to optimize the feed forward neural network training. Nature inspired meta-heuristic algorithms als…
Analysis of a Statistical Hypothesis Based Learning Mechanism for Faster crawling
Sudarshan Nandy, Partha Pratim Sarkar, Achintya Das
The growth of world-wide-web (WWW) spreads its wings from an intangible quantities of web-pages to a gigantic hub of web information which gradually increases the complexity of cra…
Analysis of Statistical Hypothesis based Learning Mechanism for Faster Crawling
Sudarshan Nandy, Partha Pratim Sarkar, Achintya Das
The growth of world-wide-web (WWW) spreads its wings from an intangible quantities of web-pages to a gigantic hub of web information which gradually increases the complexity of cra…
Analysis of a Nature Inspired Firefly Algorithm based Back-propagation Neural Network Training
Sudarshan Nandy, Partha Pratim Sarkar, Achintya Das
Optimization algorithms are normally influenced by meta-heuristic approach. In recent years several hybrid methods for optimization are developed to find out a better solution. The…
An Improved Gauss-Newtons Method based Back-propagation Algorithm for Fast Convergence
Sudarshan Nandy, Partha Pratim Sarkar, Achintya Das
The present work deals with an improved back-propagation algorithm based on Gauss-Newton numerical optimization method for fast convergence. The steepest descent method is used for…