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SUMMARYThis paper presents a multivariate forecasting method for electric short-term load using chaos theory and radial basis function (RBF) neural networks. To apply the method, the largest Lyapunov exponent and correlation dimension are firstly calculated which show the electric load series is essentially a chaotic time series. Then, a multivariate chaotic prediction method is proposed taking historical load and temperature into account. Phase space reconstruction of a univariate time series is extended to construct a multivariate time series. Delay time and embedding dimension of the historical load series and temperature series are determined by mutual information and minimal forecasting error, respectively. Finally, a three-layer RBF neural network is employed to forecast the load of one day ahead and one week ahead. Real load data of Chongqing Power Grid are tested. Daily and weekly forecasting results show that the proposed multivariate approach improves the accuracy of forecasting significantly comparing with the univariate methods. Discussion of forecasting error and future work are also presented. As an efficient and effective alternative for STLF, the chaos theory based multivariate forecasting is feasible for potential application.

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According to educating and training aim of ministry of education "outstanding engineers" and combining with professional characteristic of electrical subject, this paper introduces the "2+1+1" educating model of outstanding engineers for the department of electrical engineering and automation in Chongqing University of Technology(CQUT). The selecting principles and procedures of outstanding engineers are established, and the practical project of outstanding engineers training on electrical engineering and automation in CQUT is founded. As a result, the educating and training project of the department of electrical engineering and automation in CQUT is hoped to be continually perfected by exploration and practice.

Abstract-According to educating and training aim of ministry of education "outstanding engineers" and combining with professional characteristic of electrical subject, this paper introduces the "2+1+1" educating model of outstanding engineers for the department of electrical engineering and automation in Chongqing University of Technology(CQUT). The selecting principles and procedures of outstanding engineers are established, and the practical project of outstanding engineers training on electrical engineering and automation in CQUT is founded. As a result, the educating and training project of the department of electrical engineering and automation in CQUT is hoped to be continually perfected by exploration and practice.