نتایج جستجو برای: hydrology neural network and crop

تعداد نتایج: 16957948  

A functional relationship between two variables, applied mass to a weighing platform and estimated mass using Multi-Layer Perceptron Artificial Neural Networks is approximated by a linear function. Linear relationships and correlation rates are obtained which quantitatively verify that the Artificial Neural Network model is functioning satisfactorily. Estimated mass is achieved through recallin...

Ali Anvary Rostamy Mahdi Moradzadeh Fard Mohammad Ali Aghaei Nor Mousazadeh Abbasi

The jamor purpose of the present research is to predict the total stock market index of Tehran Stock Exchange, using a combined method of Wavelet transforms, Fuzzy genetics, and neural network in order to predict the active participations of finance market as well as macro decision makers.To do so, first the prediction was made by neural network, then a series of price index was decomposed by w...

Today for the expedition of the identification and timely correction of process deviations, it is necessary to use advanced techniques to minimize the costs of production of defective products. In this way control charts as one of the important tools for the statistical process control in combination with modern tools such as artificial neural networks have been used. The artificial neural netw...

Introduction: Acute appendicitis is one of the most common causes of emergency surgery especially in children. Proper and on-time diagnosis may decrease the unwanted complications. In despite of diagnostic methods, a significant number of patients yet and up with negative laparotomies. The aim of this study was to assess the role of artificial neural networks in diagnosis of acute appendicitis ...

Abdolrasoul Bardideh Amir Hossein Hashemian Behrouz Beiranvand, Eghbal Zand-Karimi Mansour Rezaei

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...

Journal: :nutrition and food sciences research 0
hajar abbasi islamic azad university, esfahan branch (khorasgan), arghavanieh, jey st., esfahan, iran. post code: 81551-39998, p.o.box: 81595-158 seyyed mahdi seyedain ardabili department of food science and technology, faculty of agriculture and natural resources, science and research branch, islamic azad university, tehran, iran mohammad amin mohammadifar department of food science and technology, faculty of nutrition sciences, food science and technology / national nutrition and food technology research institute, shahid beheshti university of medical sciences, po box 19395-47471, tehran, iran zahra emam-djomeh transfer phenomena laboratory, department of food science, technology and engineering, faculty of agricultural engineering and technology, agricultural campus of the university of tehran, po box 4111, 31587-11167 karadj, iran

background and objectives: rheological characteristics of dough are important for achieving useful information about raw-material quality, dough behavior during mechanical handling, and textural characteristics of products. our purpose in the present research is to apply soft computation tools for predicting the rheological properties of dough out of simple measurable factors. materials and met...

E. Salajegheh, R. Kamyab,

This study deals with predicting nonlinear time history deflection of scallop domes subject to earthquake loading employing neural network technique. Scallop domes have alternate ridged and grooves that radiate from the centre. There are two main types of scallop domes, lattice and continuous, which the latticed type of scallop domes is considered in the present paper. Due to the large number o...

سید علی عظیمی محسن شفیعی نیک آبادی

Abstract—the purpose of this paper is to compare two artificial intelligence algorithms for forecasting supply chain demand. In first step data are prepared for entering into forecasting models. In next step, the modeling step, an artificial neural network and support vector machine is presented. The structure of artificial neural network is selected based on previous researchers' results. For ...

A.R Mardookhpour

In order to determine hydrological behavior and water management of Sepidroud River (North of Iran-Guilan) the present study has focused on stream flow prediction by using artificial neural network. Ten years observed inflow data (2000-2009) of Sepidroud River were selected; then these data have been forecasted by using neural network. Finally, predicted results are compared to the observed dat...

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