In this study, a three–layer artificial neural network (ANN) model was developed to predict the pressure gradient in horizontal liquid–liquid separated flow. A total of 455 data points were collected from 13 data sources to develop the ANN model. Superficial velocities, viscosity ratio and density ratio of oil to water, and roughness and inner diameter of pipe were used as input parameters of ...

today, there arevarious statistical models for the discrete simulation of the rainfall occurrence/non-occurrence with more emphasizing on long-term climatic statistics. nevertheless, the accuracy of such models or predictions should be improved in short timescale. in the present paper, it is assumed that the rainfall occurrence/non-occurrence sequences follow a two-layer hidden markov model (hm...

this study shows the usefulness of artificial neural network (ann) in maintenance planning and man-agement. an ann model based on the multi-layer perceptron having three hidden layers and four processing elements per layer was built to predict the expected downtime resulting from a breakdown or a maintenance activity. the model achieved an accuracy of over 70% in predicting the expected downtime.

Precision irrigation and fertilization in agriculture are vital for sustainable crop production, relying on accurate determination of the crop’s nutritional status. However, there challenges optimizing traditional neural networks to achieve this accurately. This paper aims propose a rapid identification method water nitrogen content using optimized networks. addresses difficulty backpropagation...

The problem of learning Bayesian networks with hidden variables is known to be a hard problem. Even the simpler task of learning just the conditional probabilities on a Bayesian network with hidden variables is hard. In this paper, we present an approach that learns the conditional probabilities on a Bayesian network with hidden variables by transforming it into a multi-layer feedforward neural...

groundwater quality management is the most important issue in many arid and semi-arid countries, including iran.artificial neural network (ann) has an extensive range of applications in water resources management. in this study,artificial neural network was developed using matlab r2013 software package, and cl, ec, so4 and no3 qualitativeparameters were estimated and compared with the measured ...

In this study, a three–layer artificial neural network (ANN) model was developed to predict the pressure gradient in horizontal liquid–liquid separated flow. A total of 455 data points were collected from 13 data sources to develop the ANN model. Superficial velocities, viscosity ratio and density ratio of oil to water, and roughness and inner diameter of pipe were used as input parameters of ...

Linear threshold units (LTUs) were originally proposed as models of biological neurons. They were widely studied in the context of the perceptron (Rosenblatt, 1962). Due to the difficulties of finding a general algorithm for networks with hidden nodes, they never passed into general use. In this work we derive an algorithm in the context of probabilistic models and show how it may be applied in...

in this paper, the gain in ld-celp speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (pso) algorithms to optimize the structure and parameters of neural networks. elman, multi-layer perceptron (mlp) and fuzzy artmap are the candidate neural models. the optimized number of nodes in the first and second hidden layers of el...

Large neural network models have high predictive power but may suffer from overfitting if the training set is not large enough. Therefore, it desirable to select an appropriate size for networks. The destructive approach, which starts with a architecture and then reduces using Lasso-type penalty, has been used extensively this task. Despite its popularity, there no theoretical guarantee techniq...