Listar1. Investigación por tema "Machine learning"
Mostrando ítems 1-20 de 117
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A classification and review of tools for developing and interacting with machine learning systems
(Association for Computing Machinery, 2022)[Abstract] In this paper we aim to bring some order to the myriad of tools that have emerged in the field of Artificial Intelligence (AI), focusing on the field of Machine Learning (ML). For this purpose, we suggest a ... -
A decision-making tool for port operations based on downtime risk and met-ocean conditions including infragravity wave forecast
(MDPI, 2023)[Abstract:] Port downtime leads to economic losses and reductions in safety levels. This problem is generally assessed in terms of uni-variable thresholds, despite its multidimensional nature. The aim of the present study ... -
A Fault-Detection System Approach for the Optimization of Warship Equipment Replacement Parts Based on Operation Parameters
(MDPI, 2023-03-23)[Abstract] Systems engineering plays a key role in the naval sector, focusing on how to design, integrate, and manage complex systems throughout their life cycle; it is therefore difficult to conceive functional warships ... -
A generalized linear model for cardiovascular complications prediction in PD patients
(ACM, 2018)[Abstract] This study was conducted using machine learning models to identify patient non-invasive information for cardiovascular complications prediction in peritoneal dialysis patients. Nowadays is well known that ... -
A hybrid intelligent model to predict the hydrogen concentration in the producer gas from a downdraft gasifier
(Elsevier, 2022-06-05)[Abstract] This research work presents an artificial intelligence approach to predicting the hydrogen concentration in the producer gas from biomass gasification. An experimental gasification plant consisting of an air-blown ... -
A Machine Learning Solution for Distributed Environments and Edge Computing
(MDPI AG, 2019-08-09)[Abstract] In a society in which information is a cornerstone the exploding of data is crucial. Thinking of the Internet of Things, we need systems able to learn from massive data and, at the same time, being inexpensive ... -
A methodology for the design of experiments in computational intelligence with multiple regression models
(Peer J, 2016-12-01)[Abstract] The design of experiments and the validation of the results achieved with them are vital in any research study. This paper focuses on the use of different Machine Learning approaches for regression tasks in the ... -
A Multi-Objective Approach for Anti-Osteosarcoma Cancer Agents Discovery through Drug Repurposing
(MDPI AG, 2020-11-22)[Abstract] Osteosarcoma is the most common type of primary malignant bone tumor. Although nowadays 5-year survival rates can reach up to 60–70%, acute complications and late effects of osteosarcoma therapy are two of the ... -
A novel framework for generic Spark workload characterization and similar pattern recognition using machine learning
(Elsevier, 2024-07)[Abstract]: Comprehensive workload characterization plays a pivotal role in comprehending Spark applications, as it enables the analysis of diverse aspects and behaviors. This understanding is indispensable for devising ... -
A One-Class Classification method based on Expanded Non-Convex Hulls
(Elsevier, 2023)[Abstract]: This paper presents an intuitive, robust and efficient One-Class Classification algorithm. The method developed is called OCENCH (One-class Classification via Expanded Non-Convex Hulls) and bases its operation ... -
A review on machine learning approaches and trends in drug discovery
(Research Network of Computational and Structural Biotechnology, 2021)Abstract: Drug discovery aims at finding new compounds with specific chemical properties for the treatment of diseases. In the last years, the approach used in this search presents an important component in computer science ... -
A scalable decision-tree-based method to explain interactions in dyadic data
(Elsevier, 2019-12)[Abstract]: Gaining relevant insight from a dyadic dataset, which describes interactions between two entities, is an open problem that has sparked the interest of researchers and industry data scientists alike. However, ... -
A Survey on Artificial Intelligence Techniques for Biomedical Image Analysis in Skeleton-Based Forensic Human Identification
(M D P I AG, 2002-07-08)[Abstract] This paper represents the first survey on the application of AI techniques for the analysis of biomedical images with forensic human identification purposes. Human identification is of great relevance in today’s ... -
Acceleration of a Feature Selection Algorithm Using High Performance Computing
(MDPI AG, 2020-09-01)[Abstract] Feature selection is a subfield of data analysis that is on reducing the dimensionality of datasets, so that subsequent analyses over them can be performed in affordable execution times while keeping the same ... -
Ambient Intelligence Systems for Personalized Sport Training
(Molecular Diversity Preservation International, 2010)Several research programs are tackling the use of Wireless Sensor Networks (WSN) at specific fields, such as e-Health, e-Inclusion or e-Sport. This is the case of the project “Ambient Intelligence Systems Support for ... -
Anomaly Detection on Natural Language Processing to Improve Predictions on Tourist Preferences
(MDPI, 2022)[Abstract] Argumentation-based dialogue models have shown to be appropriate for decision contexts in which it is intended to overcome the lack of interaction between decision-makers, either because they are dispersed, they ... -
Anti-money laundering main techniques and tools: a review of the literature
(2024)[Abstract]: Money laundering poses a significant threat to global financial integrity and sustainable economic development. This systematic review and meta-analysis examines state-of-the-art research on fraud and corruption, ... -
Application of Artificial Neural Networks for the Monitoring of Episodes of High Toxicity by DSP in Mussel Production Areas in Galicia
(MDPI AG, 2020-08-19)[Abstract] This study seeks to support, through the use of Artificial Neural Networks (ANN), the decision to perform closings after days without sampling in the Vigo estuary. The opening and closing of the mussel production ... -
Application of Functional Data Analysis for the Prediction of Maximum Heart Rate
(IEEE-Institute of Electrical and Electronics Engineers, 2019-08-29)[Abstract]: Maximum heart rate (MHR) is widely used in the prescription and monitoring of exercise intensity, and also as a criterion for the termination of sub-maximal aerobic _tness tests in clinical populations. Traditionally, ... -
Application of machine learning algorithms for the validation of a new CoAP-IoT anomaly detection dataset
(MDPI, 2023-04)[Abstract]: With the rise in smart devices, the Internet of Things (IoT) has been established as one of the preferred emerging platforms to fulfil their need for simple interconnections. The use of specific protocols such ...