In solving application problems, the data sets used to train a neural network may not be hundred percent precise but within certain ranges. Representing data sets with intervals, ...
This work is a suitability study of the different optimization methods for automated parameter estimation (fitting) in the context of neuronal signaling networks. The Gepasi simul...
This paper studies an evolutionary multiobjective optimization algorithm, called EVOLT, which heuristically optimizes QoS (quality of service) in communication networks for electr...
—We have currently reached a phase where big shifts in the network traffic might impose to rethink the design of current architectures, and where new technologies, being pushed ...
— We put forth a unified framework for downlink and uplink scheduling of multiple connections with diverse qualityof-service requirements, where each connection transmits using ...