The cascade-correlation learning architecture
Advances in neural information processing systems 2
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
FuNN/2—a fuzzy neural network architecture for adaptive learning and knowledge acquisition
Information Sciences: an International Journal - Special issue on advanced neuro-fuzzy techniques and their applications
Neural adaptive tracking control of a DC motor
Information Sciences: an International Journal
Information Sciences: an International Journal - Special issue on frontiers in evolutionary algorithms
Neural networks for HREM image analysis
Information Sciences—Informatics and Computer Science: An International Journal
Time-series forecasting using GA-tuned radial basis functions
Information Sciences—Informatics and Computer Science: An International Journal - Special issue on evolutionary algorithms
Combining GP operators with SA search to evolve fuzzy rule based classifiers
Information Sciences: an International Journal - Recent advances in genetic fuzzy systems
Neuro-Control and Its Applications
Neuro-Control and Its Applications
Time Series Analysis, Forecasting and Control
Time Series Analysis, Forecasting and Control
Evolving neural networks through augmenting topologies
Evolutionary Computation
Dynamic system identification via recurrent multilayer perceptrons
Information Sciences—Informatics and Computer Science: An International Journal
Population-Based Incremental Learning: A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning
Probabilistic incremental program evolution
Evolutionary Computation
Evolutionary induction of sparse neural trees
Evolutionary Computation
Evolutionary programming made faster
IEEE Transactions on Evolutionary Computation
Forecasting time series with genetic fuzzy predictor ensemble
IEEE Transactions on Fuzzy Systems
A new approach to fuzzy-neural system modeling
IEEE Transactions on Fuzzy Systems
A new evolutionary system for evolving artificial neural networks
IEEE Transactions on Neural Networks
Use of a quasi-Newton method in a feedforward neural network construction algorithm
IEEE Transactions on Neural Networks
Flexible neural trees ensemble for stock index modeling
Neurocomputing
Information Sciences: an International Journal
A neural network ensemble method with jittered training data for time series forecasting
Information Sciences: an International Journal
Using multiple indexes for efficient subsequence matching in time-series databases
Information Sciences: an International Journal
Investigating generalization in parallel evolutionary artificial neural networks
AIAP'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: artificial intelligence and applications
Information Sciences: an International Journal
Information Sciences: an International Journal
Time series forecasting with a non-linear model and the scatter search meta-heuristic
Information Sciences: an International Journal
A non-symbolic implementation of abdominal pain estimation in childhood
Information Sciences: an International Journal
Data gravitation based classification
Information Sciences: an International Journal
A neural network with a case based dynamic window for stock trading prediction
Expert Systems with Applications: An International Journal
Online hybrid traffic classifier for Peer-to-Peer systems based on network processors
Applied Soft Computing
Fuzzy wavelet neural network for prediction of electricity consumption
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Information Sciences: an International Journal
Neural Networks
An artificial neural network (p,d,q) model for timeseries forecasting
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Hi-index | 0.08 |
Time-series forecasting is an important research and application area. Much effort has been devoted over the past several decades to develop and improve the time-series forecasting models. This paper introduces a new time-series forecasting model based on the flexible neural tree (FNT). The FNT model is generated initially as a flexible multi-layer feed-forward neural network and evolved using an evolutionary procedure. Very often it is a difficult task to select the proper input variables or time-lags for constructing a time-series model. Our research demonstrates that the FNT model is capable of handing the task automatically. The performance and effectiveness of the proposed method are evaluated using time series prediction problems and compared with those of related methods.