Facets of Uncertainties and Applications

Computational Method for High-order Weighted Fuzzy Time Series Forecasting Based on Multiple Partitions.- Chapter 23. Portfolio Selection with Possibilistic Kurtosis.- Chapter 24. Conflicting Bifuzzy Preference Relations based Method for Multi Criteria Decision Making Problems.- Chapter 25. A Linear Goal Programming Method for Solving Chance Constrained Multi objective Problems with Interval Data Uncertainty.

Indian Rough Set Society.

ANDRZEJ SKOWRON, European Coordination Committee for Artificial Intelligence (ECCAI) Fellow, received his PhD and D.Sc. (Habilitation) from the University of Warsaw, Poland. In 1991, he received the Scientific Title of Professor. He is full professor in the Faculty of Mathematics, Computer Science and Mechanics at the University of Warsaw, and honorary professor of Chongqing University of Posts and Telecommunications, China. He is the author of more than 400 scientific publications and editor of many books. His areas of expertise include reasoning with incomplete information, approximate reasoning, soft computing methods and applications, rough sets, rough mereology, granular computing, intelligent systems, knowledge discovery and data mining, decision support systems, adaptive and autonomous systems, perception based computing, and interactive computational systems. He supervised more than 20 PhD theses, was the editor-in-chief of the journal Fundamenta Informaticae during 1995-2009. Professor Skowron is also on editorial boards of many international journals. During 1996-2000, he was the president of the International Rough Set Society. He delivered numerous invited talks at international conferences including plenary talk at the 16-th IFIP World Computer Congress (Beijing, 2000) and served as the program chair of more than 200 international conferences. He was involved to numerous research and commercial projects.

MANORANJAN MAITI, PhD, has earlier worked at Indian Institute of Tropical Meteorology, Poona; Structural Engineering Division, Vikram Sarabhai Space Centre, ISRO, Trivandrum;  Department of Mathematics, Calcutta University Post Graduate Centre (presently, Tripura University), Agartala; Department of Applied Mathematics, Vidyasagar University, West Bengal. He was also dean, Faculty Council of Science, for a period of ten years and vice-chancellor (pro-tempore) of Vidyasagar University, for a short period. Twenty six students have been awarded PhD degree in mathematics under his guidance at Vidyasagar University and NIT Durgapur, West Bengal, as well as several students are doing PhD under him. He has published more than 250 research papers in several international journals. He was associate editor of Applied Mathematical Modelling. His fields of interest are inventory control system, supply chain, fuzzy optimization, transportation, etc. 

SAMARJIT KAR has done two PhDs in mathematics, one from Presidency College in Calcutta University, and the second from Vidyasagar University, West Bengal. He is associate professor at the Department of Mathematics, National Institute of Technology, Durgapur, India. With over 15 years of experience in teaching, Professor Kar was earlier visiting professor at the Department of Mathematical Sciences, Tsinghua University, China. As well as he has visited several universities and institutes in India and abroad. He has authored more than 100 technical articles in international journals, contributed volumes, and conference proceedings. He has published 2 textbooks and edited 5 contributed books with Springer, American Institute of Physics, Narosa and U.N. Dhur Publication. Professor Kar has guided 9 PhD students. He is the associate editor of Journal of Uncertainty Analysis and Application (Springer), and is presently associated with an ongoing project, Hybrid modelling of uncertainty analysis in environmental risk assessments under BRNS, Department of Atomic Energy (DAE), Government of India. His research interests include operations research and optimization, soft computing, uncertainty theory and financial modelling.