id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_ps7ltaslkvb7hj7qgt6uhrcbni	P Dash	Building a Fuzzy Expert System for Electric Load Forecasting Using a Hybrid Neural Network	1995	15	.pdf	application/pdf	8354	2010	85	Abstract-This paper presents the development of a hybrid neural network to model a fuzzy expert The hybrid neural network is trained to develop fuzzy logic rules andjind optimal inputloutput membership values of load and weather parameters. observed that the fuzzy expert system using the Kalman $lter-based algorithm gives faster convergence ANN-based load forecasts give large errors when the input and output linguistic parameters of the fuzzy expert An alternative to the neural network-based load forecast approach for load forecast consists of rules similar to the Hybrid neural network modelled as a fuzzy expert system. Learned membership functions for 24 h ahead peak load forecasting, in January (winter) using FES,. develop fuzzy logic rules and find input/output membership functions. Hybrid Neural Network for Fuzzy Expert System 421 Forecasting of a load time series using a fuzzy expert system and the application of neural networks for short term load forecasting, 	./cache/work_ps7ltaslkvb7hj7qgt6uhrcbni.pdf	./txt/work_ps7ltaslkvb7hj7qgt6uhrcbni.txt