Data mining has become an essential tool during the last decade to analyze large sets of
data. The variety of techniques it includes and the successful results obtained in many …

This study proposes a hierarchical pattern recognition method for tourism demand
forecasting. The hierarchy consists of three tiers: the first tier recognizes the calendar pattern …

Electricity, an indispensable resource in daily life and industrial production, is hard to store,
so accurate short-term load forecasting (STLF) plays a vital role in resource allocation …

A software tool developed in Matlab for short-term load forecasting (STLF) is presented.
Different forecasting methods such as artificial neural networks, multiple linear regression …

Electrical demand forecasting is a key element within the electrical power system. STLF is
considered the most significant for many processes in the Power Grid. A slight improve in the …

The power of artificial neural networks to form predictive models for phenomenon that exhibit
non-linear relationships is a given fact. Despite this advantage, artificial neural networks are …

This paper presents an artificial neural network (ANN) based model with a back-propagation
algorithm for short-term load forecasting in microgrid power systems. Owing to the significant …

A software tool developed in Matlab for short-term load forecasting (STLF) is presented.
Different forecasting methods such as artificial neural networks, multiple linear regression …

TO DEVELOP AN ANALYTICAL LRAMLWORK OL ELECTRICAL POWER CONSUMER’S
BEHAVIOUR TO ASSIST IN THE IDENTIFICATION, DETECTION AND PRE Page 1 TO …

This paper presents an artificial neural network (ANN) based model with a back-propagation
algorithm for short-term load forecasting in microgrid power systems. Owing to the significant …