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Detection of early warning signals in paleoclimate data using a genetic time series segmentation algorithm
(2017)
This paper proposes a time series segmentation algorithm combining a clustering technique and a genetic algorithm to automatically find segments sharing common statistical characteristics in paleoclimate time series. The ...
Semi-supervised Learning for Ordinal Kernel Discriminant Analysis
(Elsevier, 2016)
Ordinal classication considers those classication problems where the labels of
the variable to predict follow a given order. Naturally, labelled data is scarce
or di_cult to obtain in this type of problems because, in ...
Object-Based Image Classification of Summer Crops with Machine Learning Methods
(MDPI, 2014)
The strategic management of agricultural lands involves crop field monitoring each year. Crop discrimination via remote sensing is a complex task, especially if different crops have a similar spectral response and cropping ...
A Review of Classification Problems and Algorithms in Renewable Energy Applications
(MDPI, 2016)
Classification problems and their corresponding solving approaches constitute one of the
fields of machine learning. The application of classification schemes in Renewable Energy (RE) has
gained significant attention in ...
A guided data projection technique for classi cation of sovereign ratings: the case of European Union 27
(2017-01-20)
Sovereign rating has had an increasing importance since the beginning of the
nancial crisis. However, credit rating agencies opacity has been criticised by
several authors highlighting the suitability of designing more ...
A hybrid dynamic exploitation barebones particle swarm optimisation algorithm for time series segmentation
(Elsevier, 2019)
This paper proposes new methods based on time series segmentation, including the adaptation of the particle swarm optimisation algorithm (PSO) to this problem, and more advanced PSO versions, such as barebones PSO (BBPSO) ...
An Extended Approach of a Two-Stage Evolutionary Algorithm in Artificial Neural Networks for Multiclassification Tasks
(Springer, 2016)
This chapter considers a recent algorithm to add broader diversity at the beginning of the evolutionary process and extends it to sigmoidal neural networks. A simultaneous evolution of architectures and weights is performed ...
A two-stage algorithm in evolutionary product unit neural networks for classification
(Elsevier, 2011)
This paper presents a procedure to add broader diversity at the beginning of the evolutionary process. It consists of creating two initial populations with different parameter settings, evolving them for a small number of ...