A system which provides prediction of the consumption of electricity for rural region by considering the climatic conditions.

The input parameters of which will be :

Relative Humidity
Wind speed
Max Temperature
Min Temperature
Sunshine hours
Air pressure

The output will be the electricity consumption in kWh for the region (graphical form and numeric value)
Using ANFIS algorithm will be applied on the datasets to obtain estimates of the consumption which will give an estimate of the energy requirements of the area

Platform to be used: MATLAB

The main requirements of prediction of the consumption of electricity for rural regionwill be:
1.Complete training of the data by applying the neuro-fuzzy model
2.The gui with user side page showing options for selecting the month ,year ,region which will
then produce a graph showing the estimated values of electricity consumption along with
comparison with actual values to show accuracy
3.The fuzzy rule set and neural model code. (we have been told by our mentor to avoid to use
any inbuilt functions and code the rule set use in Fuzzy logic and neural network algorithms and
rule sets.)
The user side should be able to login to the system so the gui should also include login page
after which it asks the user to enter the region for which consumption is to be known
5. The application should be able to predict at the electrical load one week and month ahead
6.The coding should be done for feed forward network or bpn for neural part for the given data.
7. Minimum rule sets required for fuzzification of the data for clustering.
8. Output required in charts and numeric value

The basic outline for the neural-fuzzy network.Neural training takes place in the input layer.
10.Minimum tuples required 500-600 for training