comparison of artificial neural and wavelet neural networks for prediction of barley breakage in combine harvester

Comparison of Artificial Neural Networks and Cox Regression Models in Prediction of Kidney Transplant Survival

Cox regression model serves as a statistical method for analyzing the survival data, which requires some options such as hazard proportionality. In recent decades, artificial neural network model has been increasingly applied to predict survival data. This research was conducted to compare Cox regression and artificial neural network models in prediction of kidney transplant survival. The prese...

Comparison of Artificial Neural Networks and Cox Regression Models in Prediction of Kidney Transplant Survival

Cox regression model serves as a statistical method for analyzing the survival data, which requires some options such as hazard proportionality. In recent decades, artificial neural network model has been increasingly applied to predict survival data. This research was conducted to compare Cox regression and artificial neural network models in prediction of kidney transplant survival. The prese...

scour modeling piles of kambuzia industrial city bridge using hec-ras and artificial neural network

today, scouring is one of the important topics in the river and coastal engineering so that the most destruction in the bridges is occurred due to this phenomenon. whereas the bridges are assumed as the most important connecting structures in the communications roads in the country and their importance is doubled while floodwater, thus exact design and maintenance thereof is very crucial. f...

Prediction of Gas Lift Parameters Using Artificial Neural Networks

Uncertainty of Artificial Neural Networks for Daily Evaporation Prediction (Case Study: Rasht and Manjil Stations)

This research uses the multilayer perceptron (MLP) model to predict daily evaporation at two synoptic stations located in Rasht and Manjil, Guilan province, in north-west of Iran. Initially the most important combinations of climatic parameters for both of the stations were identified using the gamma test; and daily evaporation were modeled based on the obtained optimal combination. The results...

Comparison of Genetic and Hill Climbing Algorithms to Improve an Artificial Neural Networks Model for Water Consumption Prediction

No unique method has been so far specified for determining the number of neurons in hidden layers of Multi-Layer Perceptron (MLP) neural networks used for prediction. The present research is intended to optimize the number of neurons using two meta-heuristic procedures namely genetic and hill climbing algorithms. The data used in the present research for prediction are consumption data of water...