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» Explaining inferences in Bayesian networks
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BMCBI
2008
174views more  BMCBI 2008»
13 years 7 months ago
Evolutionary approaches for the reverse-engineering of gene regulatory networks: A study on a biologically realistic dataset
Background: Inferring gene regulatory networks from data requires the development of algorithms devoted to structure extraction. When only static data are available, gene interact...
Cédric Auliac, Vincent Frouin, Xavier Gidro...
SIGCOMM
2006
ACM
14 years 1 months ago
Jigsaw: solving the puzzle of enterprise 802.11 analysis
The combination of unlicensed spectrum, cheap wireless interfaces and the inherent convenience of untethered computing have made 802.11-based networks ubiquitous in the enterprise...
Yu-Chung Cheng, John Bellardo, Péter Benk&o...
RECOMB
2003
Springer
14 years 7 months ago
Physical network models and multi-source data integration
We develop a new framework for inferring models of transcriptional regulation. The models in this approach, which we call physical models, are constructed on the basis of verifiab...
Chen-Hsiang Yeang, Tommi Jaakkola
ARTCOM
2009
IEEE
14 years 2 months ago
ANFIS Approach for Navigation of Mobile Robots
— This paper, discusses about navigation control of mobile robot using adaptive neuro-fuzzy inference system (ANFIS) in a real word dynamic environment. In the ANFIS controller a...
Mukesh Kumar Singh, Dayal R. Parhi, Jayanta Kumar ...
EUSFLAT
2009
312views Fuzzy Logic» more  EUSFLAT 2009»
13 years 5 months ago
Forecasting Exchange Rates: A Neuro-Fuzzy Approach
This paper presents an adaptive neuro-fuzzy inference system (ANFIS) for USD/JPY exchange rates forecasting. Previous work often used time series techniques and neural networks (NN...
Meysam Alizadeh, Roy Rada, Akram Khaleghei Ghoshe ...