Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Using Artificial Neural Network Techniques for Prediction of Electric
  Energy Consumption   Due to imprecision and uncertainties in predicting real world problems,
artificial neural network (ANN) techniques have become increasingly useful for
modeling and optimization. This paper presents an artificial neural network
approach for forecasting electric energy consumption. For effective planning
and operation of power systems, optimal forecasting tools are needed for energy
operators to maximize profit and also to provide maximum satisfaction to energy
consumers. Monthly data for electric energy consumed in the Gaza strip was
collected from year 1994 to 2013. Data was trained and the proposed model was
validated using 2-Fold and K-Fold cross validation techniques. The model has
been tested with actual energy consumption data and yields satisfactory
performance.

6
The categories of this paper are: astro-ph
34
The categories of this paper are: chem-ph
3
The categories of this paper are: physics
16
The categories of this paper are: stat
5
The categories of this paper are: gr-qc
37
The categories of this paper are: supr-con
9
The categories of this paper are: nlin
14
The categories of this paper are: math-ph
18
The categories of this paper are: econ
23
The categories of this paper are: solv-int
35
The categories of this paper are: mtrl-th
31
The categories of this paper are: ao-sci
22
The categories of this paper are: chao-dyn
11
The categories of this paper are: hep-lat
27
The categories of this paper are: comp-gas
30
The categories of this paper are: q-alg