light of the characteristic of natural gas load for Shanghai, a series of data preprocessing methods are adopted and more …

of preprocessing methods but genetic algorithm, artificial neural network and fuzzy inference system require … preprocessing which could be a cumbersome task to deal with ambiguous data. The unique features of the proposed algorithm are three …

clusters or to identify known patterns, the role of the ANS here is in the early pre-processing stage, to produce a smaller … classify the companies in performance groups, using: a) minimal pre-processing of the original company data; b) dimensionality …-reduction through principal component analysis (PCA); c) variables resulting from the examined ANS-based pre-processing method. The …

relationship between number of passengers and factors affecting this quantity based on historical data. Relevant pre-processing …

the success of current algorithms. In addition, preprocessing is an essential step for efficiency in both simplex type and … interior-point methods. However, the theory and preprocessing techniques can fail for cone programming over nonpolyhedral cones … cone and the constraints. This provides a framework for preprocessing cone optimization problems in order to avoid both the …

, Entscheidungsbaum und Regression. Bei der Durchführung von Fallstudien wird u.a. auf das Pre-Processing eingegangen. …