Three-dimensional (3D) reconstruction of electron tomography (ET) has emerged as an important technique in analyzing structures of complex biological samples. However most of existing reconstruction methods are not suitable for extremely noisy and incomplete data conditions. We present an adaptive simultaneous algebraic reconstruction technique (ASART) in which a modified multilevel access scheme and an adaptive relaxation parameter adjustment method are developed to improve the quality of the reconstructed 3D structure. The reconstruction process is facilitated by using a column-sum substitution approach. This modified multilevel access scheme is adopted to arrange the order of projections so as to minimize the correlations between consecutive views within a limited angle range. In the adaptive relaxation parameter adjustment method, not only the weight matrix (as in the existing methods) but the gray levels of the pixels are employed to adjust the relaxation parameters so that the quality of the reconstruction is improved while the convergence process of the reconstruction is accelerated. In the column-sum substitution approach, the computation to obtain the reciprocal of the sum for the columns in each view is avoided so that the needed computations for each iteration can be reduced. Experimental results show that the proposed technique ASART is better based on objective quality measures than other methods, especially when data is noisy and limited in tilt angles. At the same time, the reconstruction by ASART outperforms that of simultaneous algebraic reconstruction technique (SART) in speed.