Title :
Financial forecasting using generalized neural method
Author :
Kumar, Sanjeev ; Chaturvedi, D.K.
Author_Institution :
Dayalbagh Educ. Inst., Agra, India
Abstract :
It is essential to estimate the financial index for the national welfare and people´s livelihood. In this paper, we present an artificial neural network method, adaptive neuro fuzzy inference system and generalized neural network method of forecasting financial index. Artificial neural networks can be used for predicting nonlinear, dynamic systems through learning, which can easily accommodate the nonlinearities. Adaptive neuro fuzzy inference system is hybridization of fuzzy and neural network with adaptive nature. Taking advantage of the characteristics of a generalized neuron (GN), that requires much smaller training data. The feasibility of this method is discussed by means of its application to a twenty years financial statistics data.
Keywords :
economic forecasting; economic indicators; fuzzy neural nets; fuzzy reasoning; learning (artificial intelligence); adaptive neuro fuzzy inference system; artificial neural network method; financial index forecasting; fuzzy neural network; generalized neural method; generalized neuron; Artificial neural networks; Computational modeling; Data models; Economic indicators; Forecasting; Neurons; Training; ANFIS; Forecasting; Fuzzy; Neural network;
Conference_Titel :
Computer Information Systems and Industrial Management Applications (CISIM), 2010 International Conference on
Conference_Location :
Krackow
Print_ISBN :
978-1-4244-7817-0
DOI :
10.1109/CISIM.2010.5643630