introduction rainfall is considered as one of the most important factures in water cycle. prediction of monthly rainfall is important for many purposes such as estimating torrent, drought, run-off, sediment, irrigation programming and also management of drainage basins. rainfall prediction in each area is mediated by punctual data measured as humidity, temperature, wind speed and etc. as iran i...

This work reports the results of four ensemble approaches with the M5 model tree as the base regression model to anticipate Sodium Adsorption Ratio (SAR). Ensemble methods that combine the output of multiple regression models have been found to be more accurate than any of the individual models making up the ensemble. In this study additive boosting, bagging, rotation forest and random subspace...

M5 is a method developed by Quinlan [10] for inducing trees of linear regression models (model trees). The paper addresses the flexibility and optimality in M5 model tree by proposing two new algorithms, namely M5flex and M5opt. M5flex algorithm brings in domain knowledge by enabling the user to choose split attributes and split values for important nodes in a model tree so that the resulting m...

physiographic characteristics and climatic conditions are factors which contributing to river flow regime and understanding of relations between these factors and river flow in a basin result in its application for the ungauged sub-basins river flow prediction. in this research the relation between physiographic and climatic parameters of golestan province and rivers flow were examined by appli...

Model trees, which are a type of decision tree with linear regression functions at the leaves, form the basis of a recent successful technique for predicting continuous numeric values. They can be applied to classiication problems by employing a standard method of transforming a classiication problem into a problem of function approximation. Surprisingly, using this simple transformation the mo...

The applicability and performance of the so-called M5 model tree machine learning technique is investigated in a flood forecasting problem for the upper reach of the Huai River in China. In one of configurations this technique is compared to multilayer perceptron artificial neural network (ANN). It is shown that model trees, being analogous to piecewise linear functions, have certain advantages...

Reliable estimation of discharge in a river is the crucial component of efficient flood management and surface water planning. Hydrologists use historical data to establish a relationship between water level and discharge, which is known as a rating curve. Once a relationship is established it can be used for predicting discharge from future measurements of water level only. Successful applicat...