_NEURAL NETS FOR PREDICTING BEHAVIOR_
by James F. Farley and Peter D. Varhol

[LISTING ONE]

#if __STDC__
#define  ARGS(x) x
#else
#define  ARGS(x) ()
#endif /* __STDC__ */

/* --- External Routines --- */
extern double tanh  ARGS((double));

#if __STDC__
int NN_Recall( void *NetPtr, float Yin[1], float Yout[1] )
#else
int NN_Recall( NetPtr, Yin, Yout )
void  *NetPtr; /* Network Pointer (not used) */
float Yin[1], Yout[1];  /* Data */
#endif /* __STDC__ */
{
    float  Xout[8];  /* work arrays */
    long   ICmpT;  /* temp for comparisons */

    /* Read and scale input into network */
    Xout[2] = Yin[0] * (1.4204544) + (-3.3721588);
LAB110:

    /* Generating code for PE 0 in layer 3 */
    Xout[3]  = (float)(-0.079340167) + (float)(1.0320195) * Xout[2];
    Xout[3] = tanh( Xout[3] );

    /* Generating code for PE 1 in layer 3 */
    Xout[4]  = (float)(3.1511722) + (float)(-3.2430165) * Xout[2];
    Xout[4] = tanh( Xout[4] );

    /* Generating code for PE 2 in layer 3 */
    Xout[5]  = (float)(-0.095040455) + (float)(1.0205934) * Xout[2];
    Xout[5] = tanh( Xout[5] );

    /* Generating code for PE 3 in layer 3 */
    Xout[6]  = (float)(-0.076126046) + (float)(1.0341249) * Xout[2];
    Xout[6] = tanh( Xout[6] );

    /* Generating code for PE 0 in layer 4 */
    Xout[7]  = (float)(0.41889122) + (float)(0.31151304) * Xout[3] +
        (float)(-0.79348314) * Xout[4] + (float)(0.30291474) * Xout[5] +
        (float)(0.31325051) * Xout[6];
    Xout[7] = tanh( Xout[7] );

    /* De-scale and write output from network */
    Yout[0] = Xout[7] * (35.937499) + (31.25);
    return( 0 );
}