@inproceedings{scholars140,
           title = {Short term load forecast using burg autoregressive technique},
           pages = {912--916},
         address = {Kuala Lumpur},
             doi = {10.1109/ICIAS.2007.4658519},
         journal = {2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007},
            year = {2007},
            note = {cited By 14; Conference of 2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007 ; Conference Date: 25 November 2007 Through 28 November 2007; Conference Code:74506},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-58049108070&doi=10.1109\%2fICIAS.2007.4658519&partnerID=40&md5=a0b9dcd7648b2a19ce0aa23193948b61},
            isbn = {1424413559; 9781424413553},
        keywords = {Autoregressive (AR); Autoregressive moving average (ARMA); Burg; MAPE; Short term load forecasting (STLF), Electric power systems; Forecasting, Electric load forecasting},
          author = {Kamel, N. and Baharudin, Z.},
        abstract = {Short-term load forecasting plays an important role in planning and operation of power system. The accuracy of this forecasted value is necessary for economically efficient operation and also for effective control. This paper describes a method of autoregressive Burg in solving one week ahead of short term load forecasting. The proposed method is tested based from historical load data of Malaysia Grid system. The accuracy of proposed method, i.e., the forecast error, which is the difference between the forecast value and actual value of the load, is obtained and reported. {\^A}{\copyright}2007 IEEE.}
}