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
—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...
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...
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...
Thispaperpresentsan artificial neuralnetwork(ANN)approach to electric energyconsumption(EEC)forecasting. In order providethe forecastedenergyconsumption,the ANNinterpolates betwee...