the purpose of this study was to evaluate three models of artificial neural networks (ann), regression trees (m5) and hargrives-samani (hg) in estimation of reference evapotranspiration. for this purpose was used climate information of sistan va baloochestan, kerman, yazd and khorasan jonoobi from 1998 to 2008. in addition to effect of wind (u) on evapotranspiration (et0), estimation of et0 was...

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...

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...

difference aspects of multinomial statistical modelings and its classifications has been studied so far. in these type of problems y is the qualitative random variable with t possible states which are considered as classifications. the goal is prediction of y based on a random vector x ? ir^m. many methods for analyzing these problems were considered. one of the modern and general method of cla...

Many problems encountered when applying machine learning in practice involve predicting a \class" that takes on a continuous numeric value, yet few machine learning schemes are able to do this. This paper describes a \rational reconstruction" of M5, a method developed by Quinlan (1992) for inducing trees of regression models. In order to accommodate data typically encountered in practice it is ...

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...

Run off resulted from rainfall is the main way of receiving water in most parts of the World. Therefore, prediction of runoff volume resulted from rainfall is getting more and more important in control, harvesting and management of surface water. In this research a number of machine learning and data mining methods including support vector machines, regression trees (CART algorithm), model tree...

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...