Performance of neural networks in managerial forecasting
International Journal of Intelligent Systems in Accounting and Finance Management - Special issue on neural networks
Neural networks in applied statistics
Technometrics
Neural network models for time series forecasts
Management Science
Industrial Applications of Fuzzy Control
Industrial Applications of Fuzzy Control
An investigation of neural networks for linear time-series forecasting
Computers and Operations Research
Time Series Analysis, Forecasting and Control
Time Series Analysis, Forecasting and Control
Forecasting airborne pollen concentration time series with neural and neuro-fuzzy models
Expert Systems with Applications: An International Journal
Hybrid neural network models for hydrologic time series forecasting
Applied Soft Computing
A neuro-fuzzy based forecasting approach for rush order control applications
Expert Systems with Applications: An International Journal
An expert system for predicting aeration performance of weirs by using ANFIS
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
An adaptive neuro-fuzzy inference system (ANFIS) model for wire-EDM
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
IEEE Transactions on Fuzzy Systems
Self-adaptive neuro-fuzzy inference systems for classification applications
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Neural Networks
International Journal of Intelligent Information and Database Systems
Comparing ANFIS and SEM in linear and nonlinear forecasting of new product development performance
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Computers and Industrial Engineering
Hi-index | 12.06 |
This paper presents a hybrid adaptive network based fuzzy inference system (ANFIS), computer simulation and time series algorithm to estimate and predict electricity consumption estimation. The difficulty with electricity consumption estimation modeling approach such as time series is the reason for proposing the hybrid approach of this study. The algorithm is ideal for uncertain, ambiguous and complex estimation and forecasting. Computer simulation is developed to generate random variables for monthly electricity consumption. Various structures of ANFIS are examined and the preferred model is selected for estimation by the proposed algorithm. Finally, the preferred ANFIS and time series models are selected by Granger-Newbold test. Monthly electricity consumption in Iran from 1995 to 2005 is considered as the case of this study. The superiority of the proposed algorithm is shown by comparing its results with genetic algorithm (GA) and artificial neural network (ANN). This is the first study that uses a hybrid ANFIS computer simulation for improvement of electricity consumption estimation.