Traditionally, models used in air traffic flow management are based on simulating the trajectories of individual aircraft. While practical, this approach does not offer any insights into the dynamics of the traffic flow. Recently, two different approaches, (1) aggregate traffic model approach and (2) Eulerian model approach, have been presented to generate linear dynamic models that represent t...

in this paper, we have proposed a study on controllability and optimal harvestingof a prey predator model and mathematical non linear formation of the equation equilibriumpoint of routh harvest stability analysis. the problem of determining the optimal harvestpolicy is solved by invoking pontryagin0s maximum principle dynamic optimization of theharvest policy is studied by taking the combined h...

In some applications, the response variable assumes values in the unit interval. The standard linear regression model is not appropriate for modelling this type of data because the normality assumption is not met. Alternatively, the beta regression model has been introduced to analyze such observations. A beta distribution represents a flexible density family on (0, 1) interval that covers symm...

There is disagreement among researchers about the distinction between dynamic and static spatial performance. Given that dynamic spatial performance is supposed to be important for some occupations, such as air traffic control (ATC), it is germane to have evidence about the likelihood of that distinction. In the present study, a battery of printed static spatial and reasoning tests were applied...

Dynamic segmentation is viewed as one of the most important functions of GIS for transportation applications. Although the road network and associated events (e.g. pavement material, traffic volume and incidents) can be referenced to both space and time, the spatial and temporal dimensions has not been well integrated. This paper explores how to model space-varying, time-varying and space-time-...

Spatial Clustering with Obstacles Constraints (SCOC) has been a new topic in Spatial Data Mining (SDM). Spatial Obstructed Distance (SOD) is the key to SCOC. The obstacles constraint is generally ignored in computing distance between two points, and it leads to the clustering result which is of no value, so obstructed distance has a great effect upon clustering result. In this paper, we propose...