Combination of activation functions in extreme learning machines for multivariate calibration

► ELM is applied in the spectroscopy data and a combinational ELM is proposed. ► Decision function of CELM consists of a linear and a nonlinear activation function. ► The CELM output weights can describe the linear and nonlinear regression relations. ► Experimental results show the proposed CELM outperforms the existing methods.