support vector regression (svr) solves regression problems based on the concept of support vector machine (svm). in this paper, a new model of svr with probabilistic constraints is proposed that any of output data and bias are considered the random variables with uniform probability functions. using the new proposed method, the optimal hyperplane regression can be obtained by solving a quadrati...

in this research, a two-phase algorithm based on the artificial neural network (ann) and a harmony search (hs) algorithm has been developed with the aim of assessing the reliability of structures with implicit limit state functions. the proposed method involves the generation of datasets to be used specifically for training by finite element analysis, to establish an ann model using a proven an...

two statistical downscaling models, the non-homogeneous hidden markov model (nhmm) and the statistical down–scaling model (sdsm) were used to generate future scenarios of both mean and extremes in the tarim river basin,which were based on nine combined scenarios including three general circulation models (gcms) (csiro30, echam5,and gfdl21) predictor sets and three special report on emission sce...