Titlebook: Advances in Artificial Intelligence; 20th Conference of t Amparo Alonso-Betanzos,Bertha Guijarro-Berdi?as,Al Conference proceedings 2024 Th

Figate

Ground-Level Ozone Forecasting Using Explainable Machine Learning,. In this study various machine learning models for ground-level ozone forecasting are optimised using a Bayesian technique. Predictions are obtained 24?h in advance using historical ozone data and related environmental variables, including meteorological measurements and other air quality indicator

Melodrama

,Multi-Objective Lagged Feature Selection Based on?Dependence Coefficient for?Time-Series Forecastinlity. Within this context, filter methods have gained recognition for their effectiveness in assessing features through statistical metrics. A recently introduced metric, the Conditional Dependence Coefficient, aims to assess the dependence between subsets of features and a target variable, enhancin

Matrimony

,FuSDG: A Proposal for?a?Fuzzy Assessment of?Sustainable Development Goals Achievement,ndicators and, in very basic terms, the degree of achievement of the 17 SDGs for a country, the so called SDG Index, is calculated with a weighted sum without taking into account any priorities among the goals..Besides this, several facts are not considered: the different situations and priorities o

發(fā)現(xiàn)

Predigest

,A Path Relinking-Based Approach for?the?Bi-Objective Double Floor Corridor Allocation Problem,lem, which has been a challenge for exact and metaheuristic approaches, involves optimizing the layout of the given facilities to minimize material handling cost and the length of the corridor considering more than one floor. This paper introduces a new approach based on the combination of two greed

觀察

,An Experimental Comparison of?Qiskit and?Pennylane for?Hybrid Quantum-Classical Support Vector Machudy compares two prominent quantum development frameworks, Qiskit and Pennylane, focusing on their suitability for hybrid quantum-classical support vector machines with quantum kernels. Our analysis reveals that Qiskit requires less theoretical information to be used, while Pennylane demonstrates su

LATHE

aesthetician

,Iterated Local Search for?the?Facility Location Problem with?Limited Choice Rule,d/or distances with clients in order to determine the best location for them. However, a different problem arises when the distribution of clients among the open facilities is considered and the cost of opening the facilities is also taken into account. In this paper, we study a problem with these f

玷污

,Driven PCTBagging: Seeking Greater Discriminating Capacity for?the?Same Level of?Interpretability,n exploit more the possibilities of the inner ensembles, and obtain higher levels of interpretability, or can exploit more the possibilities of the ensembles, and obtain higher discriminant capacity. Thus, at the extreme values, with a consolidation percentage of 100% it obtains a consolidated tree

Chauvinistic

,Semi-supervised Learning Methods for?Semantic Segmentation of?Polyps,ed by physicians to detect it are based on the visual detection of polyps in colonoscopy, a task that can be tackled by means of semantic segmentation methods. However, the amount of data necessary to train deep learning models for these problems is a barrier for their adoption. In this work, we stu