|1 Handwritten Multiscript Numeral Recognition using Artificial Neural Network, Stuti Asthana, Farha Haneef, Rakesh K Bhujade
Handwritten Numeral recognition plays a vital role in postal automation services especially in countries like India where multiple languages and scripts are used .Because of intermixing of these languages; it is very difficult to understand the script in which the pin code is written. Objective of this paper is to resolve this problem through Multilayer feed-forward back-propagation algorithm using two hidden layer. This work has been tested on five different popular Indian scripts namely Devnagri, English, Urdu, Tamil and Telugu. Network was trained to learn its behavior by adjusting the connection strengths on every iteration. The resultant of each presented training pattern was calculated to identify the minima on the error surface for each training pattern. Experiments were performed on samples by using two hidden layers and the results revealed that as the number of hidden layers is increased, more accuracy is achieved in large number of epochs
|2 Fuzzy Dominance Matrix and its Application in Decision Making Problems 2, Sulekha Gope, Sujit Das
This paper introduces the concept of fuzzy dominance matrix (FDM) for solving multiple attribute decision making (MADM) problems. During decision making process, dominance of one expert over others plays an important role to find out the optimal alternative(s). In uncertain decision making problems, often dominances are expressed using linguistic variables which can be represented by fuzzy dominance degree. We have proposed an algorithmic approach to solve multiple attribute decision making problems using FDM. Finally the proposed algorithm is illustrated using a numerical example.