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A recent innovation in artificial intelligence research has been the integration of multiple artificial intelligence techniques into hybrid intelligent systems. Hybrid artificial intelligent systems seek to overcome the deficiencies of traditional artificial techniques by combining techniques with complementary capabilities. Using these hybrid systems, researchers have been able to solve a vari...

Artificial feelings and emotions are beginning to play an increasingly important role as mechanisms for facilitating learning in intelligent systems. Here we present an architectural framework for artificial neural emotions through the use of an emotional memory system, based on Dr. Peter Levine's Autonomic Nervous System States. Tying the notions of Human Autonomic Nervous System States to an ...

today, stock investment has become an important mean of national finance. apparently, it is significant for investors to estimate the stock price and select the trading chance accurately in advance, which will bring high return to stockholders. in the past, long-term trading processes and many technical analysis methods for stock market were put forward. however, stock market is a nonlinear sys...

the method of artificial neural network is used as a suitable tool for intelligent interpretation of gravity data in this paper. we have designed a hopfield neural network to estimate the gravity source depth. the designed network was tested by both synthetic and real data. as real data, this artificial neural network was used to estimate the depth of a qanat (an underground channel) located at...

uniaxial compressive strength (ucs) and internal friction coefficient (µ) are the most important strength parameters of rock. they could be determined either by laboratory tests or from empirical correlations. the laboratory analysis sometimes is not possible for many reasons. on the other hand, due to changes in rock compositions and properties, none of the correlations could be applied as an ...