Fuzzy regression model with fuzzy input and output data for manpower forecasting
Fuzzy Sets and Systems
A neuro-fuzzy approach for prediction of human work efficiency in noisy environment
Applied Soft Computing
Prediction of building energy needs in early stage of design by using ANFIS
Expert Systems with Applications: An International Journal
Comparing ANFIS and SEM in linear and nonlinear forecasting of new product development performance
Expert Systems with Applications: An International Journal
A forecasting system for car fuel consumption using a radial basis function neural network
Expert Systems with Applications: An International Journal
| Hi-index | 12.06 |
An expert system for used cars price forecasting using adaptive neuro-fuzzy inference system (ANFIS) is presented in this paper. The proposed system consists of three parts: data acquisition system, price forecasting algorithm and performance analysis. The effective factors in the present system for price forecasting are simply assumed as the mark of the car, manufacturing year and engine style. Further, the equipment of the car is considered to raise the performance of price forecasting. In price forecasting, to verify the effect of the proposed ANFIS, a conventional artificial neural network (ANN) with back-propagation (BP) network is compared with proposed ANFIS for price forecast because of its adaptive learning capability. The ANFIS includes both fuzzy logic qualitative approximation and the adaptive neural network capability. The experimental result pointed out that the proposed expert system using ANFIS has more possibilities in used car price forecasting.