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M

M. Martínez-Ballesteros

University of Sevilla

19H指数
63论文数
827被引数
收录论文 20
发表时间
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Tree-based vs. deep learning in time series: A prescriptive framework for performance-driven model selection基于树的方法与深度学习在时间序列中的应用：一个以性能为导向的模型选择规范性框架
errApplied Soft Computing
IF6.6
err2026-03-12
err0
errOAAI
errPablo Reina-Jiménez; María Martínez-Ballesteros; José C. Riquelme
err分享
err收藏
Deep Learning or Trees? A Trade-off Analysis for Multivariate Time Series Forecasting深度学习还是树模型？多元时间序列预测的权衡分析
errADVANCES IN COMPUTATIONAL INTELLIGENCE, IWANN 2025, PT I
IF0
err2026-01-01
err0
PREAI
errReina-Jimenez, Pablo; Martinez-Ballesteros, Maria; Riquelme, Jose C.
err分享
err收藏
Feature Importance in Association Rule-Based Explanations for Time Series Forecasting基于关联规则解释的时间序列预测中的特征重要性
errINTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING-IDEAL 2025, PT II
IF0
err2026-01-01
err0
PREAI
errTroncoso-Garcia, A. R.; Martinez-Ballesteros, M.; Martinez-Alvarez, F.; Troncoso, A.
err分享
err收藏
Urban pollution impact assessment in six lithuanian cities with a focus on road traffic emissions - integrated framework for environmental health studies六座立陶宛城市城市污染影响评估，重点关注道路交通排放——环境健康研究综合框架
errJournal of Hazardous Materials
IF11.3
err2025-09-02
err0
errOAAI
errSimonas Kecorius; Leizel Madueño; Wolfram Birmili; Jakob Löndahl; Kristina Plauškaitė; Steigvilė Byčenkienė; Mario Lovrić; Valentino Petrić; Manuel Carranza-García; Manuel J. Jiménez-Navarro; María Martínez-Ballesteros; Magdalena Weiss; Otmar Schmid; Josef Cyrys; Annette Peters; Gaudentas Kecorius
err分享
err收藏
A novel approach based on clustering and optimized ensemble deep learning for energy consumption forecasting in Ethiopia一种基于聚类和优化集成深度学习的方法，用于埃塞俄比亚能源消耗预测
errNEUROCOMPUTING
IF6.5
err2025-07-01
err0
PREAI
errHabtemariam, E. Tefera; Martinez-Ballesteros, M.; Troncoso, A.; Martinez-Alvarez, F.
err分享
err收藏
Explainable deep learning on multi-target time series forecasting: An air pollution use case
errRESULTS IN ENGINEERING
IF7.9
err2024-12-01
err0
errOAAI
errJimenez-Navarro, Manuel J.; Lovric, Mario; Kecorius, Simonas; Nyarko, Emmanuel Karlo; Martinez-Ballesteros, Maria
err分享
err收藏
Explaining deep learning models for ozone pollution prediction via embedded feature selection通过嵌入式特征选择解释用于臭氧污染预测的深度学习模型
errAPPLIED SOFT COMPUTING
IF6.6
err2024-05-01
err6
errOAAI
errJimenez-Navarro, M. J.; Martinez-Ballesteros, M.; Martinez-Aalvarez, F.; Asencio-Cortes, G.
err分享
err收藏
A new approach based on association rules to add explainability to time series forecasting models一种基于关联规则的时间序列预测模型可解释性的新方法
errINFORMATION FUSION
IF15.5
err2023-06-01
err19
errOAAI
errTroncoso-Garcia, A. R.; Martinez-Ballesteros, M.; Martinez-Alvarez, F.; Troncoso, A.
err分享
err收藏
A new deep learning architecture with inductive bias balance for transformer oil temperature forecasting
errJOURNAL OF BIG DATA
IF6.4
err2023-05-28
err4
errOAAI
errJimenez-Navarro, Manuel J.; Martinez-Ballesteros, Maria; Martinez-Alvarez, Francisco; Asencio-Cortes, Gualberto
err分享
err收藏
Autoencoded DNA methylation data to predict breast cancer recurrence: Machine learning models and gene-weight significance
errARTIFICIAL INTELLIGENCE IN MEDICINE
IF6.2
err2020-11-01
err27
errOAAI
errMacias-Garcia, Laura; Martinez-Ballesteros, Maria; Luna-Romera, Jose Maria; Garcia-Heredia, Jose M.; Garcia-Gutierrez, Jorge; Riquelme-Santos, Jose C.
err分享
err收藏
Analysis of the Evolution of the Spanish Labour Market Through Unsupervised Learning
errIEEE ACCESS
IF3.6
err2019-01-01
err5
errOAAI
errMaria Luna-Romera, Jose; Nunez-Hernandez, Fernando; Martinez-Ballesteros, Maria; Riquelme, Jose C.; Usabiaga Ibanez, Carlos
err分享
err收藏
MRQAR: A generic MapReduce framework to discover quantitative association rules in big data problemsMRQAR: 用于发现大数据问题中的定量关联规则的通用MapReduce框架
errKNOWLEDGE-BASED SYSTEMS
IF7.6
err2018-08-01
err31
errOAAI
errMartin, D.; Martinez-Ballesteros, M.; Garcia-Gil, D.; Alcala-Fdez, J.; Herrera, F.; Riquelme-Santos, J. C.
err分享
err收藏
A study of the suitability of autoencoders for preprocessing data in breast cancer experimentation
errJOURNAL OF BIOMEDICAL INFORMATICS
IF4.5
err2017-08-01
err18
errOAAI
errMacias-Garcia, Laura; Maria Luna-Romera, Jose; Garcia-Gutierrez, Jorge; Martinez-Ballesteros, Maria; Riquelme-Santos, Jose C.; Gonzalez-Campora, Ricardo
err分享
err收藏
Machine learning techniques to discover genes with potential prognosis role in Alzheimer's disease using different biological sources
errINFORMATION FUSION
IF15.5
err2017-07-01
err18
errOAAI
errMartinez-Ballesteros, Maria; Garcia-Heredia, Jose M.; Nepomuceno-Chamorro, Isabel A.; Riquelme-Santos, Jose C.
err分享
err收藏
Obtaining optimal quality measures for quantitative association rules
errNEUROCOMPUTING
IF6.5
err2016-02-01
err10
errOAAI
errMartinez-Ballesteros, M.; Troncoso, A.; Martinez-Alvarez, F.; Riquelme, J. C.
err分享
err收藏
Enhancing the scalability of a genetic algorithm to discover quantitative association rules in large-scale datasets
errINTEGRATED COMPUTER-AIDED ENGINEERING
IF5.3
err2015-01-01
err35
errOAAI
errMartinez-Ballesteros, Maria; Bacardit, Jaume; Troncoso, Alicia; Riquelme, Jose C.
err分享
err收藏
Selecting the best measures to discover quantitative association rules
errNEUROCOMPUTING
IF6.5
err2014-02-01
err29
errOAAI
errMartinez-Ballesteros, M.; Martinez-Alvarez, F.; Troncoso, A.; Riquelme, J. C.
err分享
err收藏
Evolutionary association rules for total ozone content modeling from satellite observations
errCHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
IF3.8
err2011-12-01
err8
errOAAI
errMartinez-Ballesteros, M.; Salcedo-Sanz, S.; Riquelme, J. C.; Casanova-Mateo, C.; Camacho, J. L.
err分享
err收藏
An evolutionary algorithm to discover quantitative association rules in multidimensional time series
errSOFT COMPUTING
IF2.5
err2011-03-22
err35
errOAAI
errMartinez-Ballesteros, M.; Martinez-Alvarez, F.; Troncoso, A.; Riquelme, J. C.
err分享
err收藏
Mining quantitative association rules based on evolutionary computation and its application to atmospheric pollution
errINTEGRATED COMPUTER-AIDED ENGINEERING
IF5.3
err2010-07-28
err44
errOAAI
errMartinez-Ballesteros, M.; Troncoso, A.; Martinez-Alvarez, F.; Riquelme, J. C.
err分享
err收藏

研究方向

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合作学者
合作期刊
A
Annette Peters
H 指数: 176 · 论文数: 2.4K
F
Francisco Herrera
H 指数: 169 · 论文数: 1.3K
J
Josef Cyrys
H 指数: 78 · 论文数: 341
W
W. Birmili
H 指数: 68 · 论文数: 305
S
Sancho Salcedo‐Sanz
H 指数: 60 · 论文数: 509
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