Abstract
This research article mainly explores on problems and perspectives of mathematical and stochastic modeling. There is a large element of compromise in mathematical modelling. The majority of interacting systems in the real world are far too complicated to model in their entirely.In this research paper an extensive discussion has been made on linear models,nonlinear models,static models,dynamic models.A comparative study is done between the pairs explicit and implicit model,discrete and continuous model,deterministic and probabilistic model. In this talk a brief discussion on different types of models has been proposed and the concept of stages of model building is extensively discussed.Problems of stochastic model building are presented in a lucid manner and this literature is highly helpful for young researchers in stochastic modeling.
Highlights
Modelling is a cyclic process of creating and modifying models of empirical situations to understand them better and improve decisions
We review a subset of the related literature; discuss benefits and challenges in teaching and learning mathematical modeling activities and implications for instruction and assessment as well as for research
Models describe our beliefs about how the world functions. We translate those beliefs into the language of mathematics
Summary
Modelling is a cyclic process of creating and modifying models of empirical situations to understand them better and improve decisions. The role of modelling and mathematical modelling has received increasing attention as generating authentic learning and revealing the ways of thinking that produced it. Models describe our beliefs about how the world functions. We translate those beliefs into the language of mathematics. (1) Mathematics is a very precise language This helps us to formulate ideas and identify underlying assumptions. The second level of compromise concerns the amount of mathematical manipulation which is worthwhile. Mathematics has the potential to prove general results, these results depend critically on the form of equations used. Using computers to handle the models equations may never lead to elegant results, but it is much more robust against alterations
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