Implementing Sensible Algorithmic Decisions in Manufacturing Luis Asunción Pérez-Domínguez, Dynhora-Danheyda Ramírez-Ochoa, David Luviano-Cruz, Erwin-Adán Martínez-Gómez, Vicente García-Jiménez, et al. Applied Sciences Switzerland, 2025 A significant component of making intelligent decisions is optimizing algorithms. In this context, it is imperative to develop algorithms that are more efficient in order to efficiently and accurately process large quantities of intricate data. In addition, the main contribution of this study lies in the integration of optimization theory with swarm intelligence through multicriteria decision-making methods (MCDMs). This study indicates that combining dimensional analysis (DA) with particle swarm optimization (PSO) can smartly and efficiently improve analysis and decision making, resolving PSO’s shortcomings. A convergence investigation between the bat algorithm (BA), MOORA-PSO, TOPSIS-PSO, DA-PSO, and PSO is carried out to substantiate this assertion. Additionally, the ANOVA method is used to validate data dependability in order to evaluate the algorithms’ correctness.
Cash Flow Forecasting for Self-employed Workers: Fuzzy Inference Systems or Parametric Models? Luis Palomero, Vicente García, J. Salvador Sánchez Computational Economics, 2025 Cash flow forecasting is an important task for any organization, but it becomes crucial for self-employed workers. In this paper, we model the cash flow of three real self-employed workers as a time series problem and compare the performance of conventional parametric methods against two types of fuzzy inference systems in terms of both prediction error and processing time. Our evaluation demonstrates that there is no winning model, but that each forecasting method’s performance depends on the characteristics of the cash flow data. However, experimental results suggest that parametric methods and Mamdani-type fuzzy inference systems outperform Takagi–Sugeno–Kang-type systems.
Data-Centric Solutions for Addressing Big Data Veracity with Class Imbalance, High Dimensionality, and Class Overlapping Armando Bolívar, Vicente García, Roberto Alejo, Rogelio Florencia-Juárez, J. Salvador Sánchez Applied Sciences Switzerland, 2024 An innovative strategy for organizations to obtain value from their large datasets, allowing them to guide future strategic actions and improve their initiatives, is the use of machine learning algorithms. This has led to a growing and rapid application of various machine learning algorithms with a predominant focus on building and improving the performance of these models. However, this data-centric approach ignores the fact that data quality is crucial for building robust and accurate models. Several dataset issues, such as class imbalance, high dimensionality, and class overlapping, affect data quality, introducing bias to machine learning models. Therefore, adopting a data-centric approach is essential to constructing better datasets and producing effective models. Besides data issues, Big Data imposes new challenges, such as the scalability of algorithms. This paper proposes a scalable hybrid approach to jointly addressing class imbalance, high dimensionality, and class overlapping in Big Data domains. The proposal is based on well-known data-level solutions whose main operation is calculating the nearest neighbor using the Euclidean distance as a similarity metric. However, these strategies may lose their effectiveness on datasets with high dimensionality. Hence, the data quality is achieved by combining a data transformation approach using fractional norms and SMOTE to obtain a balanced and reduced dataset. Experiments carried out on nine two-class imbalanced and high-dimensional large datasets showed that our scalable methodology implemented in Spark outperforms the traditional approach.
Sustainable Digital Transformation for SMEs: A Comprehensive Framework for Informed Decision-Making Rafael Martínez-Peláez, Marco A. Escobar, Vanessa G. Félix, Rodolfo Ostos, Jorge Parra-Michel, et al. Sustainability Switzerland, 2024 This study presents a sustainable digital transformation framework to integrate sustainable practices into digital transformation initiatives within Small and Medium Enterprises (SMEs). The methodology includes a literature review, a framework creation, and a case study with passive participation. The framework was structured to help industries implement responsible digitalization initiatives in five key stages: setting objectives, fostering stakeholder-focused engagement, defining sustainable objectives and dimensions, creating a sustainable model, and executing the project. Validating the proposal in the context of an SME allowed us to discern the tangible benefits of sustainability practices for the organization, further reinforcing the relevance and applicability of the framework. In conclusion, this research offers valuable information for SMEs considering starting a sustainable digitalization process.
Deep Neural Network to Detect Gender Violence on Mexican Tweets Grisel Miranda, Roberto Alejo, Carlos Castorena, Eréndira Rendón, Javier Illescas, et al. Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2021
My Personal Images as My Graphical Password Pablo Abraham Sosa Valles, Javier Gerardo Villalobos-Serrano, Rafael Martínez-Peláez, Vicente García, Jorge Ramon Parra Michel, et al. IEEE Latin America Transactions, 2018
Prototype selectioninimbalanced data for dissimilarity representation: A preliminary study Icpram 2012 Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods, 2012
On the suitability of numerical performance measures for class imbalance problems Icpram 2012 Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods, 2012
Non-invasive melanoma diagnosis using multispectral imaging Icpram 2012 Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods, 2012
Use of ensemble based on GA for imbalance problem Laura Cleofas, Rosa Maria Valdovinos, Vicente García, Roberto Alejo Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2009
An empirical study of the behavior of classifiers on imbalanced and overlapped data sets Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2007
When overlapping unexpectedly alters the class imbalance effects V. García, R. A. Mollineda, J. S. Sánchez, R. Alejo, J. M. Sotoca Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2007
Learning from imbalanced sets through resampling and weighting R. Barandela, J. S. Sánchez, V. García, F. J. Ferri Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2003
RECENT SCHOLAR PUBLICATIONS
Addressing the balance between fairness and performance in glioma grade prediction using bias mitigation techniques R Sánchez-Marqués, V García, JS Sánchez Scientific Reports , 2026 2026
A Comparative Study of BERT-Based Models for Sarcasm Detection in Social Media Texts R Jiménez Castro, JP Sánchez Solís, V García Jiménez, G Rivera Zárate, ... International Journal of Combinatorial Optimization Problems and Informatics … , 2026 2026
Implementing Sensible Algorithmic Decisions in Manufacturing LA Pérez-Domínguez, DD Ramírez-Ochoa, D Luviano-Cruz, ... Applied Sciences 15 (16), 8885 , 2025 2025 Citations: 1
Empirical study of editing sampling on deep learning hidden layers space to classify imbalanced hyperspectral remote sensing images. D Cervantes Ambriz, CM Castorena Lara, R Alejo Eleuterio, ... International Journal of Combinatorial Optimization Problems & Informatics … , 2025 2025
Cash Flow Forecasting for Self-employed Workers: Fuzzy Inference Systems or Parametric Models? L Palomero, V García, JS Sánchez Computational Economics 66, 645-679 , 2025 2025 Citations: 4
Enhancing financial risk prediction with symbolic classifiers: addressing class imbalance and the accuracy–interpretability trade–off L Mena, V García, VG Félix, R Ostos, R Martínez-Pélaez, A Ochoa-Brust, ... Humanities and Social Sciences Communications 11 (1540), 1-11 , 2024 2024 Citations: 7
Using Compensatory Fuzzy Logic to Model an Investor’s Preference Regarding Portfolio Stock Selection within Markowitz’s Mean–Variance Framework L Cisneros, R Porras, G Rivera, R Espin-Andrade, V García Computación y Sistemas 28 (3), 1349-1359 , 2024 2024 Citations: 1
A data-centric machine learning approach to improve prediction of glioma grades using low-imbalance TCGA data R Sánchez-Marqués, V García, JS Sánchez Scientific Reports 14 (1), 17195 , 2024 2024 Citations: 19
Data-Centric Solutions for Addressing Big Data Veracity with Class Imbalance, High Dimensionality, and Class Overlapping A Bolívar, V García, R Alejo, R Florencia-Juárez, JS Sánchez Applied Sciences 14 (13), 5845 , 2024 2024 Citations: 6
Optimizing Social Security Contributions for Spanish Self-Employed Workers: Combining Data Preprocessing and Ensemble Models for Accurate Revenue Estimation L Palomero, V García, JS Sánchez Engineering Proceedings 68 (5), 1-9 , 2024 2024 Citations: 1
Sustainable Digital Transformation for SMEs: A Comprehensive Framework for Informed Decision-Making R Martínez-Peláez, MA Escobar, VG Félix, R Ostos, J Parra-Michel, ... Sustainability 16 (11), 1-25 , 2024 2024 Citations: 91
On the Links between Forecasting Performance and Statistical Features of Time Series Applied to the Cash Flow of Self-Employed Workers L Palomero, V García, JS Sánchez 7th International Conference on Applied Economics and Business, Copenhagen … , 2024 2024 Citations: 1
Detection of violent speech against women in Mexican tweets using an active learning approach G Miranda-Piña, R Alejo, E Rendón-Lara, V García IEEE Latin America Transactions 22 (4), 276-285 , 2024 2024 Citations: 1
A survey on uncertainty quantification in deep learning for financial time series prediction T Blasco, JS Sánchez, V García Neurocomputing 576 (0), 127339 , 2024 2024 Citations: 68
Improving the Calculation of Social Security Contributions for Spanish Self-Employed Workers Through an Adjusted Revenue Estimate L Palomero, V Garcıa, J Traver, JS Sánchez 2024 Citations: 5
Degradation modeling based on the gamma process with random initial degradation level and random threshold LA Rodríguez-Picón, LC Méndez-González, VH Flores-Ochoa, ... Quality Technology & Quantitative Management 20 (6), 730-750 , 2023 2023 Citations: 14
The additive Perks distribution and its applications in reliability analysis LC Méndez-González, LA Rodríguez-Picón, IJC Perez Olguin, V García, ... Quality Technology & Quantitative Management 20 (6), 784-808 , 2023 2023 Citations: 15
Abriendo camino hacia nuevas fronteras el futuro en la investigación y la innovación en la UACJ V García Instituto de Ingeniería y Tecnología , 2023 2023
Data Augmentation Techniques for Facial Image Generation: A Brief Literature Review BE Cazares, R Florencia, V García, JP Sánchez-Solís Data Analytics and Computational Intelligence: Novel Models, Algorithms and … , 2023 2023 Citations: 2
Minería de sentimientos con detección de sarcasmo en un ambiente streaming de Big Data: 5CP23-21 RJ Castro, RF Juárez, VG Jiménez Memorias Científicas y Tecnológicas 2 (1), 42-43 , 2023 2023
MOST CITED SCHOLAR PUBLICATIONS
Strategies for learning in class imbalance problems R Barandela, JS Sánchez, V García, E Rangel Pattern Recognition 36 (3), 849-851 , 2003 2003 Citations: 817
On the effectiveness of preprocessing methods when dealing with different levels of class imbalance V García, JS Sánchez, RA Mollineda Knowledge-Based Systems 25 (1), 13-21 , 2012 2012 Citations: 491
Index of balanced accuracy: A performance measure for skewed class distributions V García, RA Mollineda, JS Sánchez Iberian conference on pattern recognition and image analysis, 441-448 , 2009 2009 Citations: 311
On the k -NN performance in a challenging scenario of imbalance and overlapping V García, RA Mollineda, JS Sánchez Pattern Analysis and Applications 11 (3), 269-280 , 2008 2008 Citations: 308
Exploring the behaviour of base classifiers in credit scoring ensembles AI Marqués, V García, JS Sánchez Expert Systems with Applications 39 (11), 10244-10250 , 2012 2012 Citations: 220
The class imbalance problem in pattern classification and learning V García, JS Sánchez, RA Mollineda, JM Sotoca, R Alejo II Congreso Español de Informática , 2007 2007 Citations: 206
On the suitability of resampling techniques for the class imbalance problem in credit scoring AI Marqués, V García, JS Sánchez Journal of the Operational Research Society 64 (7), 1060-1070 , 2013 2013 Citations: 205
An empirical study of the behavior of classifiers on imbalanced and overlapped data sets V García, J Sánchez, R Mollineda Iberoamerican congress on pattern recognition, 397-406 , 2007 2007 Citations: 178
A literature review on the application of evolutionary computing to credit scoring AI Marqués, V García, JS Sánchez Journal of the Operational Research Society 64 (9), 1384-1399 , 2013 2013 Citations: 175
Exploring the synergetic effects of sample types on the performance of ensembles for credit risk and corporate bankruptcy prediction V García, AI Marqués, JS Sánchez Information Fusion 47, 88-101 , 2019 2019 Citations: 170
Two-level classifier ensembles for credit risk assessment AI Marqués, V García, JS Sánchez Expert Systems with Applications 39 (12), 10916-10922 , 2012 2012 Citations: 150
An insight into the experimental design for credit risk and corporate bankruptcy prediction systems V García, AI Marqués, JS Sánchez Journal of Intelligent Information Systems 44 (1), 159-189 , 2015 2015 Citations: 122
Understanding the apparent superiority of over-sampling through an analysis of local information for class-imbalanced data V García, JS Sánchez, AI Marqués, R Florencia, G Rivera Expert Systems with Applications 15 (0), 1-19 , 2020 2020 Citations: 114
Financial distress prediction using the hybrid associative memory with translation L Cleofas-Sánchez, V García, AI Marqués, JS Sánchez Applied Soft Computing 44, 144–152 , 2016 2016 Citations: 108
Using regression models for predicting the product quality in a tubing extrusion process V García, JS Sánchez, LA Rodríguez-Picón, LC Méndez-Gónzalez, ... Journal of Intelligent Manufacturing 30 (6), 2535–2544 , 2019 2019 Citations: 106
Theoretical Analysis of a Performance Measure for Imbalanced Data V Garcıa, RA Mollineda, JS Sánchez 2010 20th International Conference on Pattern Recognition (ICPR), 617-620 , 2010 2010 Citations: 101
A hybrid method to face class overlap and class imbalance on neural networks and multi-class scenarios R Alejo, RM Valdovinos, V García, JH Pacheco-Sanchez Pattern Recognition Letters 34 (1), 380-388 , 2013 2013 Citations: 94
Sustainable Digital Transformation for SMEs: A Comprehensive Framework for Informed Decision-Making R Martínez-Peláez, MA Escobar, VG Félix, R Ostos, J Parra-Michel, ... Sustainability 16 (11), 1-25 , 2024 2024 Citations: 91
Ranking-based MCDM models in financial management applications: analysis and emerging challenges AI Marqués, V García, JS Sánchez Progress in Artificial Intelligence 9, 171-193 , 2020 2020 Citations: 86
Surrounding neighborhood-based SMOTE for learning from imbalanced data sets V García, JS Sánchez, R Martín-Félez, RA Mollineda Progress in Artificial Intelligence, 1-16 , 2012 2012 Citations: 86
