As is well known, estimating parameters of the tree-parameter weibull distribution is a complicated task and sometimes contentious area with several methods vying for recognition. Weibull distribution involves in reliability studies frequently and has many applications in engineering. However estimating the parameters of Weibull distribution is crucial in classical ways. This distribution has t...

Learning the conditional probability table (CPT) parameters of Bayesian networks (BNs) is a key challenge in real-world decision support applications, especially when there are limited data available. The traditional approach to this introducing domain knowledge/expert judgments that encoded as qualitative parameter constraints. In paper, we focus on multiplicative synergistic negative synergy ...

since many time series are not normal, it is required to normalize data by transformation functions prior to any analysis and modeling. in this study, the next month rainfall of abadeh county station was predicted using the average monthly rainfall, minimum and maximum temperatures and minimum and maximum humidity as inputs of mlp network, both normally and raw, at period 1976 to 2013. after sc...

The mechanical behavior of a poroelastic medium permeated by multiple interacting fluid networks can be described system time-dependent partial differential equations known as the multiple-network poroelasticity (MPET) or multiporosity/multipermeability systems. These generalize Biot's equations, which describe mechanics one network case. efficient numerical solution MPET is challenging, in par...

In this paper, a novel neuro-fuzzy system has been introduced for the use of approximation and prediction of complex plants. The proposed system uses a parameter estimation network to provide coefficients of a linear combination, dynamically and then identifies a plant by approximating its target signal. So we have called it PENTA which stands for Parameter Estimation Network for Target Approxi...