A review of classification problems and algorithms in renewable energy applications
Classification problems and their corresponding solving approaches constitute one of the
fields of machine learning. The application of classification schemes in Renewable Energy …
fields of machine learning. The application of classification schemes in Renewable Energy …
Revisiting evolutionary fuzzy systems: Taxonomy, applications, new trends and challenges
Abstract Evolutionary Fuzzy Systems are a successful hybridization between fuzzy systems
and Evolutionary Algorithms. They integrate both the management of imprecision …
and Evolutionary Algorithms. They integrate both the management of imprecision …
Ordinal regression methods: survey and experimental study
Ordinal regression problems are those machine learning problems where the objective is to
classify patterns using a categorical scale which shows a natural order between the labels …
classify patterns using a categorical scale which shows a natural order between the labels …
Sustainable group tourist trip planning: An adaptive large neighborhood search algorithm
The tourism industry is a key driver of economic growth and contributes to the achievement
of sustainability goals. This paper presents a multi-objective group tourist planning problem …
of sustainability goals. This paper presents a multi-objective group tourist planning problem …
[HTML][HTML] Soft labelling based on triangular distributions for ordinal classification
Recently, solving ordinal classification problems using machine learning and deep learning
techniques has acquired important attention. There are many real-world problems in …
techniques has acquired important attention. There are many real-world problems in …
[HTML][HTML] Deep learning based hierarchical classifier for weapon stock aesthetic quality control assessment
In the last years, multiple quality control tasks consist in classifying some items based on
their aesthetic characteristics (aesthetic quality control, AQC), where usually the aspect of …
their aesthetic characteristics (aesthetic quality control, AQC), where usually the aspect of …
[HTML][HTML] Unimodal regularisation based on beta distribution for deep ordinal regression
Currently, the use of deep learning for solving ordinal classification problems, where
categories follow a natural order, has not received much attention. In this paper, we propose …
categories follow a natural order, has not received much attention. In this paper, we propose …
Machine learning methods for binary and multiclass classification of melanoma thickness from dermoscopic images
Thickness of the melanoma is the most important factor associated with survival in patients
with melanoma. It is most commonly reported as a measurement of depth given in …
with melanoma. It is most commonly reported as a measurement of depth given in …
[HTML][HTML] An ordinal CNN approach for the assessment of neurological damage in Parkinson's disease patients
Abstract 3D image scans are an assessment tool for neurological damage in Parkinson's
disease (PD) patients. This diagnosis process can be automatized to help medical staff …
disease (PD) patients. This diagnosis process can be automatized to help medical staff …
Significant wave height and energy flux range forecast with machine learning classifiers
In this paper, the performance of different ordinal and nominal multi-class classifiers is
evaluated, in a problem of wave energy range prediction using meteorological variables …
evaluated, in a problem of wave energy range prediction using meteorological variables …