Abstract. Load forecasting has become in recent years one of the major areas of research in electrical engineering. Most traditional forecasting models and artificial intelligence neural network techniques have been tried out in this task. Artificial neural networks (ANN) have lately received much attention, and a great number of papers have reported successful experiments and practical tests. This paper presents the development of an ANN-based short-term load forecasting model with improved generalization technique for the Regional Power Control Center of Saudi Electricity Company, Western Operation Area (SEC-WOA). The proposed ANN is trained with weather-related data, special events indexes and historical electric load-related data using the data from the calendar years 2003, to 2007 for training. The models tested for one week at two different seasons, typically, summer and Ramadan seasons, the mean absolute average error for day-ahead load forecasting are found 1.57% and 1.82% respectively.

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Abstract. Load forecasting has become in recent years one of the major areas of research in electrical engineering. Most traditional forecasting models and artificial intelligence neural network techniques have been tried out in this task. Artificial neural networks (ANN) have lately received much attention, and a great number of papers have reported successful experiments and practical tests. This paper presents the development of an ANN-based short-term load forecasting model with improved accuracy for the Regional Power Control Centre of Saudi Electricity Company, Western Operation Area (SEC-WOA). The proposed ANN is trained with weather-related data, special events indexes and historical electric load-related data using the data from the calendar years 2003, to 2007 for training. Different neural networks topologies have been trained and tested for achieve the optimal topology and ranking the input variables in terms of their importance. Based on the optimal NN topology, the network has been trained to predict the ahead load at different time intervals.

A student information system provides a simple interface for the easy collation and maintenance of all manner of student information. The creation and management of accurate, up-to-date information regarding students' academic careers is critical students and for the faculties and administration ofSebha University in Libya and for any other educational institution. A student information system deals with all kinds of data from enrollment to graduation, including program of study, attendance record, payment of fees and examination results to name but a few. All these dataneed to be made available through a secure, online interface embedded in auniversity's website. To lay the groundwork for such a system, first we need to build the student database to be integrated with the system. Therefore we proposed and implementedan online web-based system, which we named the student data system (SDS),to collect and correct all student data at Sebha University. The output of the system was evaluated by using a similarity (Euclidean distance) algorithm. The results showed that the new data collected by theSDS can fill the gaps and correct the errors in the old manual data records.