Work place: Department of Basic Sciences (Mathematics), Central Institute of Technology Kokrajhar BTAD, Assam, India

E-mail: s.borgoyary@cit.ac.in

Website:

Research Interests: Computational Mathematics, Mathematics of Computing, Discrete Mathematics, Mathematics

Biography

**Sahalad Borgoyary** is an Assistant Professor of the Central Institute of Technology Kokrajhar, BTAD, Assam, India and presently doing research in the Bodoland University under the guidance of Dr. K. Priyokumar Singh and Dr. H K Baruah. He has already published two articles in the international journal and another more articles are under review in the different journals. His research interests are included Fuzzy mathematics, Operations Research, Fractional Calculus etc.

By Kangujam Priyokumar Singh Sahalad Borgoyary

DOI: https://doi.org/10.5815/ijisa.2016.10.04, Pub. Date: 8 Oct. 2016

We convert polynomial function of degree nth into imprecise form to obtain an important point called conversion point. For some particular region, we collect the finite number of data points to obtain the most economical function called imprecise function. Conversion point of the functions is shown with the help of MUPAD graph. Further we study the area of the imprecise function occurred by the multiplication of sine function to know how much variation of the imprecise functions are obtained for the respective intervals. For different imprecise polynomial we study level of the rate of convergence.

[...] Read more.DOI: https://doi.org/10.5815/ijieeb.2015.05.05, Pub. Date: 8 Sep. 2015

Discuss the real line fuzzy concept into multi- dimensional based on the reference function so as to get new imprecise numbers called the two-dimensional and three-dimensional imprecise numbers and their complements. Two and three dimensional imprecise numbers are obtained in the form of Cartesian product of fuzzy numbers. To study their character some necessary definitions like partial presence, construction of membership function, membership value ,Indicator function etc. of two and three-dimensional imprecise numbers are defined with own notation. As per as possible, try to show all the properties of classical set theory that can be hold good in the present imprecise numbers with some examples. Set Operations are defined by maximum and minimum operators just like defined in the real line imprecise numbers. Further bring out a few graphical examples to verify the intersection and union of two and three dimensional imprecise numbers are the empty and the universal set respectively. Basically Intersection and union are the operators to obtain their properties.

[...] Read more.DOI: https://doi.org/10.5815/ijisa.2015.08.02, Pub. Date: 8 Jul. 2015

This article introduces generalized form of extension definition of the Fuzzy set and its complement in the sense of reference function namely in imprecise set and its complement. Discuss Partial presence of element, Membership value of an imprecise number in the normal and subnormal imprecise numbers. Further on the basis of reference function define usual matrix into imprecise form with new notation. And with the help of maximum and minimum operators, obtain some new matrices like reducing imprecise matrices, complement of reducing imprecise matrix etc. Along with discuss some of the classical matrix properties which are hold good in the imprecise matrix also. Further bring out examples of application of the addition of imprecise matrices, subtraction of imprecise matrices etc. in the field of transportation problems.

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