A review of artificial intelligent approaches applied to part accuracy prediction

Es aquí donde nos es de utilidad el método que estamos estudiando, pues la optimización Bayesiana permite optimizar funciones cuya expresión analítica no se

Experimental results have demonstrated that artificial neural networks can substantially reduce the number of model parameters and surpass the performance of previous approaches

Computational Methods in Neural Modeling: 7th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2003 Maó, Menorca, Spain,. June 3–6, 2003 Proceedings,

For some, moral philosophers have a good claim to be moral experts [2, 5], even if their expertise does not include (qua philosophers) the necessary knowledge of factual matters..

The key point of Table 6 is that most groups of voice parameters (reflecting pitch, voice signal spectrum, and voice quality) differ in episodes of illness (depression, mania) from

accuracy  and  prevent  the  device  from  damage  at  high  accelerations  using  an  artificial  neural  network  [17].  First,  a  nonlinear  dynamic 

In this paper, an artificial cooperative search (ACS) algorithm tuned adaptive network-based fuzzy inference system (ANFIS) controller for optimal gain tuning of load frequency

Keywords: Artificial neural networks, neural threshold, neural variability, heterogeneity, homogeneity, olfactory system, pattern recognition, generalist neuron, specialist neuron,