Traffic conditions vary over time, and therefore, traffic behavior should be modeled as a stochastic process. In this study, a probabilistic approach utilizing Autocorrelation is proposed to model the stochastic variation of traffic conditions, and subsequently, predict the traffic conditions. Using autocorrelation of the time series samples of density and flow which are collected from segments...

D ecision support systems (DSSs) are software products that help users apply analytical and scientific methods to decision making. They work by using models and algorithms from disciplines such as decision analysis, mathematical programming and optimization, stochastic modeling, simulation, and logic modeling. DSS products can execute, interpret, visualize, and interactively analyze these model...

We investigate the dynamical properties of an associative memory network consisting of stochastic neurons and dynamic synapses that show short-term depression and facilitation. In the stochastic neuron model used in this study, the efficacy of the synaptic transmission changes according to the short-term depression or facilitation mechanism. We derive a macroscopic mean field model that capture...

a r t i c l e i n f o We introduce a multiple scenario, multiple period, optimization-based decision support system (DSS) for strategic planning in a process industry. The DSS is based on a two stage stochastic linear program (SLP) with recourse for strategic planning. The model can be used with little or no knowledge of Management Sciences. The model maximizes the expected contribution (to pro...

More than half a century after the debut of CPM and PERT, we still lack a project scheduling system with calibrated and validated distributions and without requiring complex user input. Modern decision support systems (DSS) for project management are more sophisticated and comprehensive than PERT/CPM. Nonetheless, in terms of stochastic analysis, they show insufficient progress. PERT 21 offers ...

The present study sustainable management of Guilan Saravan Sylvan Park was planned. The used method in the form of decision support model in three10-year period was studied for parks of various states and with considering the economic, ecological and social criteria during the years 2008 to 2038. By using hierarchical fuzzy analysis method, the reaching to an optimal level of economic, ecologic...

Stochastic dynamic control systems relate in a probabilistic fashion the space of control signals to the space of corresponding future states. Consequently, stochastic dynamic systems can be interpreted as an information channel between the control space and the state space. In this work we study this control-to-state informartion capacity of stochastic dynamic systems in continuous-time, when ...