نتایج جستجو برای: using the neural network analysis
تعداد نتایج: 17160378 فیلتر نتایج به سال:
with the increase of the volume of information and the progress in technology, the deficiency of traditional algorithms for fast information retrieval becomes more clear. when large volumes of data are to be handled, the use of neural network as an artificial intelligent technique is a suitable method to increase the information retrieval speed. neural networks present a suitable representation...
abstract the purpose of this study was to find out the effect of applying the principles of group-dynamic assessment (g-da) on learning of conditional structures in english by iranian efl learners at the intermediate level, which according to the formal educational system in iran, includes students who are in their second year of studying in high schools of koohdasht city. this study was a qua...
Background: Modeling is one of the most important ways for explanation of relationship between dependent and independent response. Since data, related to number of blood donations are discrete, to explain them it is better to use discrete variable distribution like Poison or Negative binomial. This research tries to analyze numerical methods by using neural network approach and compare ...
this study was conducted to investigate the prediction of growth performance using linear regression and artificial neural network (ann) in broiler chicken. artificial neural networks (anns) are powerful tools for modeling systems in a wide range of applications. the ann model with a back propagation algorithm successfully learned the relationship between the inputs of metabolizable energy (kca...
This paper uses nonlinear regression, Artificial Neural Network (ANN) and Genetic Programming (GP) approaches for predicting an important tangible issue i.e. scours dimensions downstream of inverted siphon structures. Dimensional analysis and nonlinear regression-based equations was proposed for estimation of maximum scour depth, location of the scour hole, location and height of the dune downs...
Although, speech recognition systems are widely used and their accuracies are continuously increased, there is a considerable performance gap between their accuracies and human recognition ability. This is partially due to high speaker variations in speech signal. Deep neural networks are among the best tools for acoustic modeling. Recently, using hybrid deep neural network and hidden Markov mo...
Proper flood discharge forecasting is significant for the design of hydraulic structures, reducing the risk of failure, and minimizing downstream environmental damage. The objective of this study was to investigate the application of machine learning methods in Regional Flood Frequency Analysis (RFFA). To achieve this goal, 18 physiographic, climatic, lithological, and land use parameters were ...
Neural networks were used to estimate the cost of jet engine components, specifically shafts and cases. The neural network process was compared with results produced by the current conventional cost estimation software and linear regression methods. Due to the complex nature of the parts and the limited amount of information available, data expansion techniques such as doubling-data and data-cr...
introduction: evoked potentials arisen by stimulating the brain can be utilized as a communication tool between humans and machines. most brain-computer interface (bci) systems use the p300 component, which is an evoked potential. in this paper, we evaluate the use of the hidden markov model (hmm) for detection of p300. materials and methods: the wavelet transforms, wavelet-enhanced indepen...
strip tearing during cold rolling process has always been considered among the main concerns for steel companies. several works have been done so far regarding the examination of the issue. in this paper, experimental data from cold rolling tandem mill is used for detecting strip tearing. sensors are placed across the cold rolling tandem mill. they receive information on parameters (such as ang...
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