Future paths for integer programming and links to artificial intelligence
Computers and Operations Research - Special issue: Applications of integer programming
Reducing bias and inefficiency in the selection algorithm
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Applying tabu search to the job-shop scheduling problem
Annals of Operations Research - Special issue on Tabu search
Fuzzy Systems as Universal Approximators
IEEE Transactions on Computers
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Tabu Search
Proceedings of the First International Workshop on Pattern Recognition with Support Vector Machines
SVM '02 Proceedings of the First International Workshop on Pattern Recognition with Support Vector Machines
Uniform Crossover in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Further Research on Feature Selection and Classification Using Genetic Algorithms
Proceedings of the 5th International Conference on Genetic Algorithms
Using Genetic Algorithms with Small Populations
Proceedings of the 5th International Conference on Genetic Algorithms
A Theory of Networks for Approximation and Learning
A Theory of Networks for Approximation and Learning
An analysis of the behavior of a class of genetic adaptive systems.
An analysis of the behavior of a class of genetic adaptive systems.
Hybrid Genetic Algorithms for Feature Selection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parametric tabu-search for mixed integer programs
Computers and Operations Research - Anniversary focused issue of computers & operations research on tabu search
Feature Extraction: Foundations and Applications (Studies in Fuzziness and Soft Computing)
Feature Extraction: Foundations and Applications (Studies in Fuzziness and Soft Computing)
A tabu search algorithm with a new neighborhood structure for the job shop scheduling problem
Computers and Operations Research
Analysis of selection algorithms: A markov chain approach
Evolutionary Computation
A review of feature selection techniques in bioinformatics
Bioinformatics
Finding the embedding dimension and variable dependencies in time series
Neural Computation
Genetic algorithms and artificial life
Artificial Life
A tabu search heuristic for the truck and trailer routing problem
Computers and Operations Research
Effective input variable selection for function approximation
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
Extracting minimum unsatisfiable cores with a greedy genetic algorithm
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
Dimensionality reduction using genetic algorithms
IEEE Transactions on Evolutionary Computation
Markov chain models of parallel genetic algorithms
IEEE Transactions on Evolutionary Computation
Parallelism and evolutionary algorithms
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
Variable selection in a GPU cluster using delta test
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part I
Multistart strategy using delta test for variable selection
ICANN'11 Proceedings of the 21st international conference on Artificial neural networks - Volume Part II
On the Curse of Dimensionality in Supervised Learning of Smooth Regression Functions
Neural Processing Letters
Parametric and non-parametric feature selection for kidney transplants
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advences in computational intelligence - Volume Part II
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The problem of selecting an adequate set of variables from a given data set of a sampled function becomes crucial by the time of designing the model that will approximate it. Several approaches have been presented in the literature although recent studies showed how the delta test is a powerful tool to determine if a subset of variables is correct. This paper presents new methodologies based on the delta test such as tabu search, genetic algorithms and the hybridisation of them, to determine a subset of variables which is representative of a function. The paper considers as well the scaling problem where a relevance value is assigned to each variable. The new algorithms were adapted to be run in parallel architectures so better performances could be obtained in a small amount of time, presenting great robustness and scalability.