نتایج جستجو برای: decision neural network training

تعداد نتایج: 1402523  

Journal: :Informatica, Lith. Acad. Sci. 2004
Nerijus Remeikis Ignas Skucas Vida Melninkaite

Text categorization – the assignment of natural language documents to one or more predefined categories based on their semantic content – is an important component in many information organization and management tasks. Performance of neural networks learning is known to be sensitive to the initial weights and architecture. This paper discusses the use multilayer neural network initialization wi...

Journal: :Fuzzy Sets and Systems 2000
Hisao Ishibuchi Manabu Nii

This paper discusses various techniques for soft decision making by neural networks. Decision making problems are described as choosing an action from possible alternatives using available information. In the context of soft decision making, a single action is not always chosen. When it is di cult to choose a single action based on available information, the decision is withheld or a set of pro...

2005
Juha-Pekka Mäkelä Kaveh Pahlavan

This paper analyses the effects of training on the performance of neural network handoff algorithm in a micro-cellular environment. We first describe the neural network handoff decision algorithm as it is applied to the handoff scenario. Then we introduce the effects and performance of the number of training points used for the chosen algorithm. The performance criterion is the number and locat...

Journal: :journal of industrial strategic management 0
m kazami m esfandiyar h najjariyan

in recent years, the existing competitions between investment companies have been increased largely by entering private investors in capital market. large and powerful companies try to achieve the goals predicted to increase the competition capacity. to analyze the efficiency of investment companies, parametric and non-parametric methods are used. in this research, based on the dissociation pow...

انتظاری, علیرضا , جعفرزاده, مرتضی , حدادنیـا‌, جـواد , کورونـدی‌, ابـراهیم ,

This study, with the help of minimum temperature data, has addressed the prediction of frost during 21 years period by means of neural network in Kermanshah province. In order to forecast frost, data were converted to the values between 0 and 1 by means of a subjective and one to one (injective) function. We have used feed-forward neural network by one hidden interior layer with number of chang...

Journal: :journal of computer and robotics 0
mohammad talebi motlagh department of systems and control, industrial control center of excellence, k.n.toosi university of technology, tehran, iran hamid khaloozadeh department of systems and control, industrial control center of excellence, k.n.toosi university of technology, tehran, iran

modelling and forecasting stock market is a challenging task for economists and engineers since it has a dynamic structure and nonlinear characteristic. this nonlinearity affects the efficiency of the price characteristics. using an artificial neural network (ann) is a proper way to model this nonlinearity and it has been used successfully in one-step-ahead and multi-step-ahead prediction of di...

Journal: :journal of rangeland science 2011
a. ariapour m. nassaji zavareh

evaporation is one of the most important components of hydrologic cycle.accurate estimation of this parameter is used for studies such as water balance,irrigation system design, and water resource management. in order to estimate theevaporation, direct measurement methods or physical and empirical models can beused. using direct methods require installing meteorological stations andinstruments ...

In this study, artificial neural network was used to predict the surface tension of 20 hydrocarbon mixtures. Experimental data was divided into two parts (70% for training and 30% for testing). Optimal configuration of the network was obtained with minimization of prediction error on testing data. The accuracy of our proposed model was compared with four well-known empirical equations. The arti...

M. Vakili Alavijeh M.A. Norouzian,

A comparative study of artificial neural network (ANN) and multiple regression is made to predict the fat tail weight of Balouchi sheep from birth, weaning and finishing weights. A multilayer feed forward network with back propagation of error learning mechanism was used to predict the sheep body weight. The data (69 records) were randomly divided into two subsets. The first subset is the train...

Journal: :civil engineering infrastructures journal 0
fatemeh barzegari instructor of agricultural department, payam noor university, iran. mohsen yousefi m.sc., faculty of natural resources, yazd university, iran ali talebi associate professor, faculty of natural resources, yazd university, iran.

the aim of this study was to estimate suspended sediment by the ann model, dt with cart algorithm and different types of src, in ten stations from the lorestan province of iran. the results showed that the accuracy of ann with levenberg-marquardt back propagation algorithm is more than the two other models, especially in high discharges. comparison of different intervals in models showed that r...

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