Systems Modeling Using Deep Elman Neural Network
نویسندگان
چکیده
منابع مشابه
scour modeling piles of kambuzia industrial city bridge using hec-ras and artificial neural network
today, scouring is one of the important topics in the river and coastal engineering so that the most destruction in the bridges is occurred due to this phenomenon. whereas the bridges are assumed as the most important connecting structures in the communications roads in the country and their importance is doubled while floodwater, thus exact design and maintenance thereof is very crucial. f...
Forecasting Using Elman Recurrent Neural Network
Forecasting is an important data analysis technique that aims to study historical data in order to explore and predict its future values. In fact, to forecast, different methods have been tested and applied from regression to neural network models. In this research, we proposed Elman Recurrent Neural Network (ERNN) to forecast the Mackey-Glass time series elements. Experimental results show tha...
متن کاملModeling word perception using the Elman network
This paper presents an automatic acquisition process to acquire the semantic meaning for the words. This process obtains the representation vectors for stemmed words by iteratively improving the vectors, using a trained Elman network. Experiments performed on a corpus composed of Shakespeare’s writings show its linguistic analysis and categorization abilities. & 2008 Elsevier B.V. All rights re...
متن کاملNumerical Analysis of Modeling Based on Improved Elman Neural Network
A modeling based on the improved Elman neural network (IENN) is proposed to analyze the nonlinear circuits with the memory effect. The hidden layer neurons are activated by a group of Chebyshev orthogonal basis functions instead of sigmoid functions in this model. The error curves of the sum of squared error (SSE) varying with the number of hidden neurons and the iteration step are studied to d...
متن کاملA Fuzzy Elman Neural Network
A fuzzy Elman neural network (FENN) is proposed to identify and simulate nonlinear dynamic systems. Each of all the fuzzy rules used in FENN has a linear state-space equation as its consequence and the network, by use of firing strengths of input variables, combines these Takagi-Sugeno type rules to represent the modeled nonlinear system. The context nodes in FENN are used to perform temporal r...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Engineering, Technology & Applied Science Research
سال: 2019
ISSN: 1792-8036,2241-4487
DOI: 10.48084/etasr.2455