Keywords : Mathematics

An Analytical Study of Applied Mathematical Model towards Several Ecological Systems

Gangadhar Kishanrao Patil; Jaya Singh

International Research Journal on Advanced Science Hub, 2020, Volume 2, Issue Special Issue ICAMET 10S, Pages 101-107
DOI: 10.47392/irjash.2020.206

This paper focuses on those parts of 20th century applied mathematics that have entered into the toolkit of ecology. Historically, the recent trend of applying mathematics to ecology is discussed. It is proposed that this new development can be seen in the extension of its application as the natural development of applied mathematics. There is no assumption that the mathematical concepts and methods employed would be significantly different from those used in mainstream applied mathematics. In terms of estimates for reference to empirical data, conventional concepts and methods of statistical physics can be successfully applied. A case study on the history of statistics and operational research discusses several ways to integrate the development of applied mathematics of the twentieth century into an ecological context.

Machine learning amalgamation of Mathematics, Statistics and Electronics

Trupti S. Gaikwad; Snehal A. Jadhav; Ruta R. Vaidya; Snehal H. Kulkarni

International Research Journal on Advanced Science Hub, 2020, Volume 2, Issue 7, Pages 100-108
DOI: 10.47392/irjash.2020.72

Interdisciplinary research is a manner of research carried out by an individual or group of persons. The knowledge, data, techniques, concepts are incorporated from two or more disciplines. In this paper we tried to throw light on this concept. Machine learning is a branch of computer science which uses the information, tools for collection of data, methods for analysis from the subjects like Electronics, Mathematics and Statistics. Why we use machine learning? Because it plays an influential role in prediction of data. Machine learning is used to find hidden patterns and essential ideas from data as well as it solve complex problems. In today’s world, many applications have large volume of data like structured, unstructured and semi structured. This unexploited resource of knowledge can be used to improve business decisions. As data diversifies many are adapting to machine learning tool for analysis of data, so that, they can exploit intelligence and benefit from that data at most. Machine learning adopts different algorithms and each algorithm performs different functionality. In this paper, we tried to explain through example, how Electronics is used for collection of data while Mathematics and Statistics are used for analysis and finally using Machine learning results can be predicted.