In this paper, a reliability approach on reconfiguration decisions in a supply chain network is studied based on coupling the simulation concepts and artificial neural network. In other words, due to the limited budget for warehouse relocation in a supply chain, the failure probability is assessed for determining the robust decision for future supply chain configuration. Traditional solving ...

Unconstrained growth of synaptic activity and lack of references to synaptic depression in Hebb‟s postulate have diminished its value as a learning algorithm. The existing synaptic scaling mechanisms such as weight normalization, threshold updating, and spike time dependent plasticity have greatly contributed to address these issues in Hebb‟s postulate. However, all these mechanisms are based o...

Abstract Evidence shows that adolescents do not enough physical activity (PA), which could contribute to childhood overweight and obesity. Studies have shown both the built environment social networks influence adolescents’ PA, but more studies are needed investigate their combined using longitudinal data. We used a stochastic actor-based model analyzing two waves of Add Health data test if (1)...

wind power generation is variable and uncertain. in the power systems with high penetration of wind power, determination of equivalent operating reserve is the main concern of systems operator. in this paper, a model is proposed to determine operating reserves in simultaneous market clearing of energy and reserve by stochastic programming based on scenarios generated via monte carlo simulation ...

This paper addresses the application of neural network research to a theory of autonomous systems. Neural networks , while enjoying considerable success in autonomous systems applications, have failed to provide a rm theoretical underpinning to neural systems embedded in their natural ecological context. This paper proposes a stochastic formulation of such an embedding. A neural system derived ...

This paper addresses the application of neural network research to a theory of autonomous systems Neural net works while enjoying considerable success in autonomous systems applications have failed to provide a rm the oretical underpinning to neural systems embedded in their natural ecological context This paper proposes a stochastic formulation of such an embedding A neural system derived from...

We study the effects of periodic subthreshold pacemaker activity and time-delayed coupling on stochastic resonance over scale-free neuronal networks. As the two extreme options, we introduce the pacemaker, respectively, to the neuron with the highest degree and to one of the neurons with the lowest degree within the network, but we also consider the case when all neurons are exposed to the peri...

Problem statement: Identifying critical tasks in a project network is easily done when task times are deterministic, but doing so under stochastic task times is problematic. The few methods that have been proposed contain serious drawbacks which lead to identifying critical tasks incorrectly, leaving project managers without the means to (1) identify and rank the most probable sources of projec...

Brain rhythms contribute to every aspect of brain function. Here, we study critical and resonance phenomena that precede the emergence of brain rhythms. Using an analytical approach and simulations of a cortical circuit model of neural networks with stochastic neurons in the presence of noise, we show that spontaneous appearance of network oscillations occurs as a dynamical (non-equilibrium) ph...