Naturally ventilated tropical greenhouse is classified as a complex system because it involves with nonlinear process and multivariable system. The purpose of this study is to determine the mathematical model of NVTG climates to in order to describe and predict the dynamic behavior of temperature and humidity inside NVTG for development of its control system. The modeling of the system is divid...

erosion and sediment movement phenomena are one of the most complex issues in management of rivers drainage areas that in water projects are very important. that its measurement wants high time and cost. issue of surface runoff in river basin is a complex issue that human knowledge and understanding about its physical laws a viewpoint of some mathematical formulas is limited. in this study to i...

the fao penman - monteith (f-p-m) method is now broadly accepted as the standard for estimating the reference evapotranspiration (et0). the method is also now used for evaluating the temperature-based [blaney-criddle (b-c) and hargreaves-samani (h-s)] and radiation-based [jensen-haise (j-h) and turc (tc)] methods. the objective was to compare the et0 estimated by the b-c, h-s, j-h, tc methods w...

OBJECTIVES The 29-item Multiple Sclerosis Impact Scale (MSIS-29) is a psychometrically validated patient-reported outcome measure increasingly used in trials of treatments for multiple sclerosis. However, it is non-preference-based and not amenable for use across policy decision-making contexts. Our objective was to statistically map from the MSIS-29, version 2, to the EuroQol five-dimension (E...

In this paper, we present the application of the neural network for the identification of Reusable Software modules in Oriented Software System. Metrics are used for the structural analysis of the different procedures. The values of Metrics will become the input dataset for the neural network systems and Fuzzy Systems. Training Algorithm based on Neural Network and fuzzy clustering are experime...

We study the problem of short term wind speed prediction, which is a critical factor for effective wind power generation. This is a challenging task due to the complex and stochastic behavior of the wind environment. Observing various periods in the wind speed time series present different patterns, we suggest a nonlinear adaptive framework to model various hidden dynamic processes. The model i...

Several ANN models were developed to prediction of monthly precipitation data in Mashhad synoptic station. From the total 636 monthly precipitation data (from 1958 to 2008), 580 data has been used for training networks and the rest selected randomly has been used for validation of the models. To extract the precipitation dynamic of this station by ANN, a new approach of three-layer feed-forward...

This paper investigates the effectiveness of four different soft computing methods, namely radial basis neural network (RBNN), adaptive neuro fuzzy inference system (ANFIS) with subtractive clustering (ANFIS-SC), ANFIS with fuzzy c-means clustering (ANFIS-FCM) and M5 model tree (M5Tree), for predicting the ultimate strength and strain of concrete cylinders confined with fiber-reinforced polymer...

Rainfall is considered as one of the major components of the hydrological process; it takes significant part in evaluating drought and flooding events. Therefore, it is important to have an accurate model for rainfall prediction. Recently, several data-driven modeling approaches have been investigated to perform such forecasting tasks as multilayer perceptron neural networks (MLP-NN). In fact, ...