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GECCO
2008
Springer
261views Optimization» more  GECCO 2008»
15 years 5 months ago
SSNNS -: a suite of tools to explore spiking neural networks
We are interested in engineering smart machines that enable backtracking of emergent behaviors. Our SSNNS simulator consists of hand-picked tools to explore spiking neural network...
Heike Sichtig, J. David Schaffer, Craig B. Laramee
JSW
2010
83views more  JSW 2010»
15 years 3 months ago
Estimating Model Parameters of Conditioned Soils by using Artificial Network
—The parameter identification of nonlinear constitutive model of soil mass is based on an inverse analysis procedure, which consists of minimizing the objective function represen...
Zichang Shangguan, Shouju Li, Wei Sun, Maotian Lua...
IJCNN
2000
IEEE
15 years 9 months ago
On MCMC Sampling in Bayesian MLP Neural Networks
Bayesian MLP neural networks are a flexible tool in complex nonlinear problems. The approach is complicated by need to evaluate integrals over high-dimensional probability distri...
Aki Vehtari, Simo Särkkä, Jouko Lampinen
EUSFLAT
2009
195views Fuzzy Logic» more  EUSFLAT 2009»
15 years 2 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...
FLAIRS
2001
15 years 6 months ago
Neural Networks in Forecasting Electrical Energy Consumption
Thispaperpresentsan artificial neuralnetwork(ANN)approach to electric energyconsumption(EEC)forecasting. In order providethe forecastedenergyconsumption,the ANNinterpolates betwee...
George E. Nasr, E. A. Badr, M. R. Younes