A data driven nonlinear stochastic model for blood glucose dynamics

A Data-driven Method for Crowd Simulation using a Holonification Model

In this paper, we present a data-driven method for crowd simulation with holonification model. With this extra module, the accuracy of simulation will increase and it generates more realistic behaviors of agents. First, we show how to use the concept of holon in crowd simulation and how effective it is. For this reason, we use simple rules for holonification. Using real-world data, we model the...

Data driven discovery of nonlinear dynamics

We demonstrate that sparse regression and compressive sensing techniques are capable of accurately determining a set of functions governing a nonlinear dynamical system. We analyze a technique introduced by Brunton, Proctor, and Kutz, 2016 [1] that builds a sparse representation of a dynamical system by computing sequential least squares fittings of the data to identify the governing equations....

Proposing A stochastic model for spread of corona virus dynamics in Nigeria

The emergence of corona virus (COVID-19) has create a great public concern as the outbreak is still ongoing and government are taking actions such as holiday extension, travel restriction, temporary closure of public work place, borders, schools, quarantine/isolation, social distancing and so on. To mitigate the spread, we proposed and analyzed a stochastic model for the continue spread of coro...

A Stochastic Optimization Model for Groundwater Management

A Stochastic Model for Water Resources Management

Irrigation water management is crucial for agricultural production and livelihood security in many regions and countries throughout the world. Over the past decades, controversial and conflictladen water-allocation issues among competing municipal, industrial and agricultural interests have raised increasing concerns. Particularly, growing population, varying natural conditions and shrinking wa...