One of the main issues regarding the monitoring of persons in a smart home environment is the accuracy of the daily control of the person, the health prevention and the timely prediction of abnormal situations. To tackle this problem, this work proposes the use of an improved version of the Elman Neural Network (Elman-NN). In order to minimize the error between inputs and desired outputs, we op...

This paper presents a new recurrent neural network (RNN) structure called ENEM for dynamic system identification. ENEM structure is based on Elman network and NARX neural network. In order to show the performance of ENEM for system identification, the results were also compared to the results of Elman network, Jordan network and their modified models. The identification results of linear and no...

Abstract The estimation of state health (SOH) a lithium-ion battery (LIB) is great significance to system safety and economic development. This paper proposes SOH method based on the SSA-Elman model for first time. To improve correlation rates between features capacity, combining median absolute deviation filtering Savitzky–Golay proposed process data. Based aging characteristics LIB, five with...

In order to implement the national need for optimal allocation of power resources, load forecasting, as an important research topic, has theoretical and practical significance. The purpose this study is construct a prediction model considering climate factors based on large amount historical data, prove that accuracy related both regularity. results forecasting are affected by many factors, so ...

A context-based attention task is employed in this paper. An Elman-type recurrent neural network is utilized to extract and keep the context information, and only the reinforcement signal that indicates whether the answer is correct or not is given. Through this learning, the function of an associative memory is observed in the Elman-type neural network. Adaptive formation of the basins are exa...

The condition monitoring data of gears is asymmetric distributed, moreover, sampling is usually conducted discontinuously in practice. Thus makes it difficult to predict gear remaining useful life accurately considering the two reasons above. In this paper, a fusion method is proposed using Elman Neural Network to modify residual series of grey model since Elman Neural Network performs better o...

As the air-conditioning control system has the nonlinearity, large time delay and time variation and other characteristics.In this paper,we put forward a method of self-adjusting PID algorithm based on the modified Elman neural network, and the output of the network adjust the three parameters of the PID controller online, so that it has the high controlling precision, good dynamic characterist...

In this paper, in order to categorize ORL database face pictures, principle Component Analysis (PCA) and Kernel Principal Component Analysis (KPCA) methods by using Elman neural network and Support Vector Machine (SVM) categorization methods are used. Elman network as a recurrent neural network is proposed for modeling storage systems and also it is used for reviewing the effect of using PCA nu...