Fuzzy time series and its models
Fuzzy Sets and Systems
Forecasting enrollments with fuzzy time series—part I
Fuzzy Sets and Systems
Forecasting enrollments with fuzzy time series—part II
Fuzzy Sets and Systems
Induction of fuzzy decision trees
Fuzzy Sets and Systems
Forecasting enrollments based on fuzzy time series
Fuzzy Sets and Systems
Machine Learning
Forecasting enrollments using high-order fuzzy time series and genetic algorithms: Research Articles
International Journal of Intelligent Systems
Expert Systems with Applications: An International Journal
A dynamic approach to adjusting lengths of intervals in fuzzy time series forecasting
Intelligent Data Analysis
Multi-attribute fuzzy time series method based on fuzzy clustering
Expert Systems with Applications: An International Journal
A bivariate fuzzy time series model to forecast the TAIEX
Expert Systems with Applications: An International Journal
A type-2 fuzzy rule-based expert system model for stock price analysis
Expert Systems with Applications: An International Journal
Soft decision trees: A genetically optimized cluster oriented approach
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Forecasting in high order fuzzy times series by using neural networks to define fuzzy relations
Expert Systems with Applications: An International Journal
A new approach for determining the length of intervals for fuzzy time series
Applied Soft Computing
AN ENHANCED DETERMINISTIC FUZZY TIME SERIES FORECASTING MODEL
Cybernetics and Systems
A computational method of forecasting based on high-order fuzzy time series
Expert Systems with Applications: An International Journal
Mathematics of FuzzinessBasic Issues
Mathematics of FuzzinessBasic Issues
Forecasting TAIFEX based on fuzzy time series and particle swarm optimization
Expert Systems with Applications: An International Journal
KNN-kernel density-based clustering for high-dimensional multivariate data
Computational Statistics & Data Analysis
Finding an optimal interval length in high order fuzzy time series
Expert Systems with Applications: An International Journal
Trend-weighted fuzzy time-series model for TAIEX forecasting
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
Multi-level thresholding using entropy-based weighted FCM algorithm in color image
ISVC'05 Proceedings of the First international conference on Advances in Visual Computing
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Temperature prediction using fuzzy time series
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Designing decision trees with the use of fuzzy granulation
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Handling forecasting problems based on two-factors high-order fuzzy time series
IEEE Transactions on Fuzzy Systems
Hi-index | 12.05 |
Followed with Song and Chissom's fuzzy time series model, many fuzzy time series models have been proposed for forecasting combined with some technologies or theories. This study presents a new forecast model on basis of fuzzy time series and improved C-fuzzy decision trees for forecasting stock index which is one of the most interesting issues for researchers. There are two main improvements for C-fuzzy decision trees in this paper. The first one is that a new stop condition is introduced to reduce the computational cost. The other one is fuzzy clustering with weight distance computed with information gain. And then weighted C-fuzzy decision tree (WCDT), a novel forecast model armed with k nearest neighbors, has been proposed and experimented on Shanghai Composite Index over a ten-year period, from 1997 to 2006. The empirical analysis not only demonstrates the forecasting procedure and the way to obtain the suitable parameters, but also shows that the proposed model significantly outperforms the conventional counterparts.