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UAI
1998
15 years 7 months ago
Learning the Structure of Dynamic Probabilistic Networks
Dynamic probabilistic networks are a compact representation of complex stochastic processes. In this paper we examine how to learn the structure of a DPN from data. We extend stru...
Nir Friedman, Kevin P. Murphy, Stuart J. Russell
GLOBECOM
2008
IEEE
15 years 6 months ago
Influence of Node Location Distributions on the Structure of Ad Hoc and Mesh Networks
We study the impact of the distribution of node locations on key properties of wireless networks. In particular, using Monte Carlo simulations we study in detail the behavior of av...
Janne Riihijärvi, Marina Petrova, Petri M&aum...
IJNSEC
2007
171views more  IJNSEC 2007»
15 years 6 months ago
Preventing DoS Attacks in Wireless Sensor Networks: A Repeated Game Theory Approach
In this paper we formulate the prevention of Denial of Service (DoS) attacks in wireless sensor networks as a repeated game between an intrusion detector and nodes of a sensor net...
Afrand Agah, Sajal K. Das
ICRA
2010
IEEE
158views Robotics» more  ICRA 2010»
15 years 4 months ago
Towards optimally efficient field estimation with threshold-based pruning in real robotic sensor networks
Abstract-- The efficiency of distributed sensor networks depends on an optimal trade-off between the usage of resources and data quality. The work in this paper addresses the probl...
Amanda Prorok, Christopher M. Cianci, Alcherio Mar...
EUSFLAT
2009
195views Fuzzy Logic» more  EUSFLAT 2009»
15 years 4 months ago
Optimization of an Oil Production System using Neural Networks and Genetic Algorithms
This paper proposes an optimization strategy which is based on neural networks and genetic algorithms to calculate the optimal values of gas injection rate and oil rate for oil pro...
Guillermo Jimenez de la Cruz, Jose A. Ruz-Hernande...