نتایج جستجو برای: this study employs a gmdh neural network model
تعداد نتایج: 14627899 فیلتر نتایج به سال:
Objective (s): Artificial Neural Networks (ANN) are widely used for predicting systems’ behavior. GMDH is a type of ANNs which has remarkable ability in pattern recognition. The aim the current study is proposing a model to predict dynamic viscosity of silver/water nanofluid which can be used as antimicrobial fluid in several medical purposes.Materials and Methods: In order to have precise mode...
       This paper proposes a new forecasting model for investigating relationship between the price of crude oil, as an important energy source and GDP of the US, as the largest oil consumer, and the UK, as the oil producer. GMDH neural network and MLFF neural network approaches, which are both non-linear models, are employed to forecast GDP responses to the oil price changes. The resul...
The objective of this study was to apply an improved Group Method of Data Handling (GMDH) network model for prediction of debris flow by integrating dynamic rainfall data and environmental factors. The rainfall data were collected from weather information, and the environmental data were extracted from RS, GIS, drilling data, and geophysical data. The input variables used in the SAGA-GMDH model...
this study considers the level of increase in customer satisfaction by supplying the variant customer requirements with respect to organizational restrictions. in this regard, anp, qfd and bgp techniques are used in a fuzzy set and a model is proposed in order to help the organization optimize the multi-objective decision-making process. the prioritization of technical attributes is the result ...
in this thesis, we consider a mathematical model of cancer with completely unknown parameters. we study the stability of critical points which are biologically admissible. then we consider a control on the system and introduce situations at which solutions are attracted to critical points and so the cancer disease has auto healing. the lyapunov stability method is used for estimating the un...
one of the most important factors in study of project’s , is the study of environmental opportunities factors the permanent study of environmental opportunity factors . the study of permanent environmental changing and knowing golden threats’ cooperate with possible threats and at the result in structure forming and future skeleton of organization has a vital effects . the petrochemical industr...
in this work, a hybrid gmdh–neural network model was developed in order to predict the moisture content of papaya slices during hot air drying in a cabinet dryer. for this purpose, parameters including drying time, slices thickness and drying temperature were considered as the inputs and the amount of moisture ratio (mr) was estimated as the output. exactly 50% of the data points were used for ...
abstract this study aimed at investigating the effect of bilingual teaching of cognate words (persian-english) on iranian upper intermediate efl learners’ knowledge of lexical development. for this purpose,100 subjects participated in this study out of which 40 learners were selected for this study and they were assigned into two groups, control and experimental. cross-language cognates (wor...
A feedback Group Method of Data Handling (GMDH)-type neural network algorithm is proposed, and is applied to nonlinear system identification and medical image analysis of liver cancer. In this feedback GMDH-type neural network algorithm, the optimum neural network architecture is automatically selected from three types of neural network architectures, such as sigmoid function neural network, ra...
Prediction of the production rate of the cutting dimensional stone process is crucial, especially when chain saw machines are used. The cutting dimensional rock process is generally a complex issue with numerous effective factors including variable and unreliable conditions of the rocks and cutting machines. The Group Method of Data Handling (GMDH) type of neural network and Radial Basis Functi...
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