نتایج جستجو برای: multilayer feed forward
تعداد نتایج: 194892 فیلتر نتایج به سال:
Even for models of very simple networks, like those in Chapters 2 and 3, describing the system requires many parameters. These parameters are often unknown or uncertain. Consequently, predicting the response of a gene circuit may require infering gene circuit function from data on circuit structure alone. By using the feed-forward loop as a model system, this chapter introduces a technique for ...
A new approach to robust estimation of signals, prediction of time{series and robust feedforward control is considered. Signal and system parameter deviations are represented as random variables, with known covariances. A robust design is obtained by minimizing the squared estimation error, averaged both with respect to model errors and the noise. A polynomial equations approach, based on avera...
In this chapter we study two naturally occurring feed-forward loops that are involved in galactose metabolism and transport. Despite having network structures that are capable of a producing dynamic, temporally diverse responses we find, by measuring dynamic noise correlations, that in their natural context these feed-forward loops are inactive. By perturbing genetic conditions the activity can...
An artificial neural network (ANN) modeling of gas drying by adsorption in fixed bed of composite materials is presented in this paper. The experimental investigations were carried out at two values of relative humidity and three values of air flow rate respectively. The experimental data were employed in the design of the feed forward neural networks for modeling the evolution in time of some ...
Hemoglobin A1c (HbA1c) is the gold-standard measure for diagnosing and managing diabetes. Given importance of data-driven decisions, this paper aimed to develop a method elucidating predicting HbA1c levels. We developed comprehensive analyzing multiple linear regression through R syntax, embedding multilayer feedforward neural networks (MLFFNN) bootstrapping. The success proposed was determined...
This paper presents the application of feed-forward multilayer perceptron networks and multiple regression models, to forecast hourly nitrogen dioxide levels 24 hours in advance. Input data are traffic and meteorological variables, and nitrogen dioxide hourly levels. The introduction of four periodic components (sine and cosine terms for the daily and weekly cycles), and nitrogen oxide hourly l...
OBJECTIVE The main goal of this paper is to obtain a classification model based on feed-forward multilayer perceptrons in order to improve postpartum depression prediction during the 32 weeks after childbirth with a high sensitivity and specificity and to develop a tool to be integrated in a decision support system for clinicians. MATERIALS AND METHODS Multilayer perceptrons were trained on d...
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