By far, different models for determining the relationship between the flow rate  and amount of precipitation have been developed. many models are based on regression models with limited assumptions. one of the most common methods for estimating  sediment of rivers is sediment rating curve. for better estimation of the amount of sediment based of sediment curve  rating equation, it is possible t...

Production of highly viscous tar sand bitumen using Steam Assisted Gravity Drainage (SAGD) with a pair of horizontal wells has advantages over conventional steam flooding. This paper explores the use of Artificial Neural Networks (ANNs) as an alternative to the traditional SAGD simulation approach. Feed forward, multi-layered neural network meta-models are trained through the Back-...

Estimating the final price of products is of great importance. For manufacturing companies proposing a final price is only possible after the design process over. These companies propose an approximate initial price of the required products to the customers for which some of time and money is required. Here using the existing data of already designed transformers and utilizing the bayesian anal...

Models for which the likelihood function can be evaluated only up to a parameter-dependent unknown normalizing constant, such as Markov random field models, are used widely in computer science, statistical physics, spatial statistics, and network analysis. However, Bayesian analysis of these models using standard Monte Carlo methods is not possible due to the intractability of their likelihood ...

data envelope analysis (dea) is an approach to estimate the relative efficiency of decision making units (dmus). several studies were conducted in order to prioritize efficient units and some useful models such as cross-efficiency matrix (cem) were presented.  besides, a number of dea models with interval data have been developed and ranking dmus with such data was solved. however, presenting a...