منابع مشابه
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...
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The problem of short-term electric load forecasting (STLF) is considered. A modified architecture of Elman-type recurrent neural network is proposed. It utilizes a special fuzzification layer to deal with quantitative as well as ordinal and nominal data. The second hidden layer of the network consists of standard Rosenblatt-type neurons with sigmoidal activation functions. The context layer is ...
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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...
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Cardiac arrhythmia refers to any abnormal electrical activity in the heart that causes irregular heartbeat. Under clinical settings, the arrhythmias can be monitored non-invasively using the electrocardiogram (ECG). Although reliable, the method is still prone to error due to its dependence on visual interpretation. Further, ECG data is enormous in dimension and increases as the data sampling r...
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ژورنال
عنوان ژورنال: MATEC Web of Conferences
سال: 2016
ISSN: 2261-236X
DOI: 10.1051/matecconf/20165405007