Genetic algorithms with sharing for multimodal function optimization
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Approximation and radial-basis-function networks
Neural Computation
Matrix computations (3rd ed.)
A statistical perspective on knowledge discovery in databases
Advances in knowledge discovery and data mining
Static, Dynamic, and Hybrid Neural Networks in Forecasting Inflation
Computational Economics
Time-series forecasting using GA-tuned radial basis functions
Information Sciences—Informatics and Computer Science: An International Journal - Special issue on evolutionary algorithms
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Knowledge Discovery and Data Mining: The Info-Fuzzy Network (Ifn) Methodology
Knowledge Discovery and Data Mining: The Info-Fuzzy Network (Ifn) Methodology
The GA-P: A Genetic Algorithm and Genetic Programming Hybrid
IEEE Expert: Intelligent Systems and Their Applications
Feature Selection for Machine Learning: Comparing a Correlation-Based Filter Approach to the Wrapper
Proceedings of the Twelfth International Florida Artificial Intelligence Research Society Conference
Investment using technical analysis and fuzzy logic
Fuzzy Sets and Systems - Special issue: Optimization and decision support systems
A bibliography of temporal, spatial and spatio-temporal data mining research
ACM SIGKDD Explorations Newsletter
An introduction to variable and feature selection
The Journal of Machine Learning Research
A review of genetic algorithms applied to training radial basis function networks
Neural Computing and Applications
Evolving RBF neural networks for time-series forecasting with EvRBF
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Informatics and computer science intelligent systems applications
Data Mining and Knowledge Discovery Handbook
Data Mining and Knowledge Discovery Handbook
Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents
Evolutionary Computation
Working Set Selection Using Second Order Information for Training Support Vector Machines
The Journal of Machine Learning Research
Biostatistical Analysis (5th Edition)
Biostatistical Analysis (5th Edition)
Forecasting airborne pollen concentration time series with neural and neuro-fuzzy models
Expert Systems with Applications: An International Journal
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
Automatic extraction and identification of chart patterns towards financial forecast
Applied Soft Computing
Forecasting Thailand's rice export: Statistical techniques vs. artificial neural networks
Computers and Industrial Engineering
Engineering Applications of Artificial Intelligence
A generalized model for financial time series representation and prediction
Applied Intelligence
Soft computing techniques applied to finance
Applied Intelligence
Feature Selection for Time Series Forecasting: A Case Study
HIS '08 Proceedings of the 2008 8th International Conference on Hybrid Intelligent Systems
KEEL: a software tool to assess evolutionary algorithms for data mining problems
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Evolutionary and Metaheuristics based Data Mining (EMBDM); Guest Editors: José A. Gámez, María J. del Jesús, José M. Puerta
Surveying stock market forecasting techniques - Part II: Soft computing methods
Expert Systems with Applications: An International Journal
An empirical methodology for developing stockmarket trading systems using artificial neural networks
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Temporal and Spatio-temporal Data Mining
Temporal and Spatio-temporal Data Mining
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
CO$^2$RBFN for short-term forecasting of the extra virgin olive oil price in the Spanish market
International Journal of Hybrid Intelligent Systems - Hybrid Fuzzy Models
Applying multiobjective RBFNNs optimization and feature selection to a mineral reduction problem
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
Designing Stock Market Trading Systems: with and without Soft Computing
Designing Stock Market Trading Systems: with and without Soft Computing
Evolutionary computation: comments on the history and current state
IEEE Transactions on Evolutionary Computation
Evolutionary optimization of radial basis function classifiers for data mining applications
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Neural Networks
Conditional fuzzy clustering in the design of radial basis function neural networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
A summary on the study of the medium-term forecasting of the extra-virgen olive oil price
CAEPIA'11 Proceedings of the 14th international conference on Advances in artificial intelligence: spanish association for artificial intelligence
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Time series forecasting is an important task for the business sector. Agents involved in the olive oil sector consider that, for the olive oil price, medium-term predictions are more important than short-term predictions. In collaboration with these agents the forecasting of the price of extra-virgin olive oil six months ahead has been established as the aim of this work. According to expert opinion, the use of exogenous variables and technical indicators can help in this task and must be included in the forecasting process. The amount of variables that can be considered makes necessary the use of feature selection algorithms in order to reduce the number of variables and to increase the interpretability and usefulness of the obtained forecasting system. Thus, in this paper CO2RBFN, a cooperative-competitive algorithm for Radial Basis Function Network design, and other soft computing methods have been applied to the data sets with the whole set of input variables and to the data sets with the selected set of input variables. The experimentation carried out shows that CO2RBFN obtains the best results in medium term forecasting for olive oil prices with the whole and with the selected set of input variables. Moreover, the feature selection methods applied to the data sets highlighted some influential variables which could be considered not only for the prediction but also for the description of the complex process involved in the medium-term forecasting of the olive oil price.