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ORCIDEnrico De Santis
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2020 – today
- 2024
[j16]Enrico De Santis
, Antonello Rizzi:
Modeling failures in smart grids by a bilinear logistic regression approach. Neural Networks 174: 106245 (2024)- [j15]Enrico De Santis, Alessio Martino, Antonello Rizzi:
Human Versus Machine Intelligence: Assessing Natural Language Generation Models Through Complex Systems Theory. IEEE Trans. Pattern Anal. Mach. Intell. 46(7): 4812-4829 (2024) - [c24]Sabereh Taghdisi Rastkar, Saeid Jamili, Enrico De Santis, Antonello Rizzi:
Improving Prediction Performances by Integrating Second Derivative in Microgrids Energy Load Forecasting. IJCNN 2024: 1-8 - [c23]Danial Zendehdel, Antonino Capillo, Enrico De Santis, Antonello Rizzi:
An Extended Battery Equivalent Circuit Model for an Energy Community Real Time EMS. IJCNN 2024: 1-9 - [i4]Antonino Capillo, Enrico De Santis, Fabio Massimo Frattale Mascioli, Antonello Rizzi:
An Online Hierarchical Energy Management System for Energy Communities, Complying with the Current Technical Legislation Framework. CoRR abs/2402.01688 (2024) - 2023
- [j14]Enrico De Santis, Antonello Rizzi:
Prototype Theory Meets Word Embedding: A Novel Approach for Text Categorization via Granular Computing. Cogn. Comput. 15(3): 976-997 (2023) - [j13]Enrico De Santis, Alessio Martino, Francesca Ronci, Antonello Rizzi:
An Unsupervised Graph-Based Approach for Detecting Relevant Topics: A Case Study on the Italian Twitter Cohort during the Russia-Ukraine Conflict. Inf. 14(6): 330 (2023) - [j12]Enrico De Santis, Giovanni De Santis, Antonello Rizzi:
Multifractal Characterization of Texts for Pattern Recognition: On the Complexity of Morphological Structures in Modern and Ancient Languages. IEEE Trans. Pattern Anal. Mach. Intell. 45(8): 10143-10160 (2023) - [j11]Alessio Martino, Enrico De Santis, Antonello Rizzi:
On Information Granulation via Data Filtering for Granular Computing-Based Pattern Recognition: A Graph Embedding Case Study. SN Comput. Sci. 4(3): 314 (2023) - [c22]Sabereh Taghdisi Rastkar, Danial Zendehdel, Enrico De Santis, Antonello Rizzi:
A Comparison Between Seasonal and Non-Seasonal Forecasting Techniques for Energy Demand Time Series in Smart Grids. IJCCI 2023: 459-467 - [c21]Enrico De Santis, Alessio Martino, Francesca Ronci, Antonello Rizzi:
A Comparison of Neural Word Embedding Language Models for Classifying Social Media Users in the Healthcare Context. IJCNN 2023: 1-9 - 2022
- [j10]Enrico De Santis, Parisa Naraei, Alessio Martino, Alireza Sadeghian, Antonello Rizzi:
Multifractal Characterization and Modeling of Blood Pressure Signals. Algorithms 15(8): 259 (2022) - [j9]Enrico De Santis, Alessio Martino, Antonello Rizzi:
On component-wise dissimilarity measures and metric properties in pattern recognition. PeerJ Comput. Sci. 8: e1106 (2022) - [j8]Enrico De Santis, Francesco Arnò, Antonello Rizzi:
Estimation of fault probability in medium voltage feeders through calibration techniques in classification models. Soft Comput. 26(15): 7175-7193 (2022) - [c20]Emanuele Ferrandino, Antonino Capillo, Enrico De Santis, Fabio Massimo Frattale Mascioli, Antonello Rizzi:
A Comparison between Crisp and Fuzzy Logic in an Autonomous Driving System for Boats. FUZZ-IEEE 2022: 1-8 - [c19]Antonino Capillo, Enrico De Santis, Fabio Massimo Frattale Mascioli, Antonello Rizzi:
Synthesis of an Evolutionary Fuzzy Multi-objective Energy Management System for an Electric Boat. IJCCI 2022: 199-208 - [c18]Enrico De Santis, Francesco Arnò, Alessio Martino, Antonello Rizzi:
A statistical framework for labeling unlabelled data: a case study on anomaly detection in pressurization systems for high-speed railway trains. IJCNN 2022: 1-8 - 2021
- [c17]Emanuele Ferrandino, Antonino Capillo, Enrico De Santis, Fabio Massimo Frattale Mascioli, Antonello Rizzi:
A Modular Autonomous Driving System for Electric Boats based on Fuzzy Controllers and Q-Learning. IJCCI 2021: 185-195 - 2020
- [j7]Enrico De Santis, Alessio Martino, Antonello Rizzi:
An Infoveillance System for Detecting and Tracking Relevant Topics From Italian Tweets During the COVID-19 Event. IEEE Access 8: 132527-132538 (2020) - [j6]Alessio Martino, Enrico De Santis, Alessandro Giuliani, Antonello Rizzi:
Modelling and Recognition of Protein Contact Networks by Multiple Kernel Learning and Dissimilarity Representations. Entropy 22(7): 794 (2020) - [c16]Antonino Capillo, Enrico De Santis, Fabio Massimo Frattale Mascioli, Antonello Rizzi:
Mining M-Grams by a Granular Computing Approach for Text Classification. IJCCI 2020: 350-360 - [c15]Enrico De Santis, Antonino Capillo, Fabio Massimo Frattale Mascioli, Antonello Rizzi:
Classification and Calibration Techniques in Predictive Maintenance: A Comparison between GMM and a Custom One-Class Classifier. IJCCI 2020: 503-511 - [c14]Mauro Giampieri, Luca Baldini, Enrico De Santis, Antonello Rizzi:
Facing Big Data by an Agent-Based Multimodal Evolutionary Approach to Classification. IJCNN 2020: 1-8 - [c13]Alessio Martino, Enrico De Santis, Antonello Rizzi:
An Ecology-based Index for Text Embedding and Classification. IJCNN 2020: 1-8
2010 – 2019
- 2019
- [c12]Alessio Martino, Enrico De Santis, Luca Baldini, Antonello Rizzi:
Calibration Techniques for Binary Classification Problems: A Comparative Analysis. IJCCI 2019: 487-495 - 2018
- [j5]Enrico De Santis, Antonello Rizzi, Alireza Sadeghian:
A cluster-based dissimilarity learning approach for localized fault classification in Smart Grids. Swarm Evol. Comput. 39: 267-278 (2018) - [c11]Mauro Giampieri, Enrico De Santis, Antonello Rizzi, Fabio Massimo Frattale Mascioli:
A Supervised Classification System based on Evolutive Multi-Agent Clustering for Smart Grids Faults Prediction. IJCNN 2018: 1-8 - [c10]Enrico De Santis, Alessio Martino, Antonello Rizzi, Fabio Massimo Frattale Mascioli:
Dissimilarity Space Representations and Automatic Feature Selection for Protein Function Prediction. IJCNN 2018: 1-8 - [c9]Enrico De Santis, Maurizio Paschero, Antonello Rizzi, Fabio Massimo Frattale Mascioli:
Evolutionary Optimization of an Affine Model for Vulnerability Characterization in Smart Grids. IJCNN 2018: 1-8 - 2017
- [j4]Enrico De Santis, Antonello Rizzi, Alireza Sadeghian:
Hierarchical genetic optimization of a fuzzy logic system for energy flows management in microgrids. Appl. Soft Comput. 60: 135-149 (2017) - [j3]Enrico De Santis, Alireza Sadeghian, Antonello Rizzi:
A Smoothing Technique for the Multifractal Analysis of a Medium Voltage Feeders Electric Current. Int. J. Bifurc. Chaos 27(14): 1750211:1-1750211:25 (2017) - [c8]Enrico De Santis, Antonello Rizzi, Alireza Sadeghian:
A learning intelligent System for classification and characterization of localized faults in Smart Grids. CEC 2017: 2669-2676 - 2016
- [b1]Enrico De Santis:
Computational Intelligence Techniques for Complex Systems with Applications to Smart Grids. Sapienza University of Rome, Italy, 2016 - [c7]Stefano Leonori, Enrico De Santis, Antonello Rizzi, F. M. Frattale Mascioli:
Multi objective optimization of a fuzzy logic controller for energy management in microgrids. CEC 2016: 319-326 - [c6]Stefano Leonori, Enrico De Santis, Antonello Rizzi, F. M. Frattale Mascioli:
Optimization of a microgrid energy management system based on a Fuzzy Logic Controller. IECON 2016: 6615-6620 - [i3]Enrico De Santis, Alireza Sadeghian, Antonello Rizzi:
A Hierarchical Genetic Optimization of a Fuzzy Logic System for Flow Control in Micro Grids. CoRR abs/1604.04789 (2016) - 2015
- [j2]Filippo Maria Bianchi, Enrico De Santis, Antonello Rizzi, Alireza Sadeghian:
Short-Term Electric Load Forecasting Using Echo State Networks and PCA Decomposition. IEEE Access 3: 1931-1943 (2015) - [j1]Enrico De Santis, Lorenzo Livi, Alireza Sadeghian, Antonello Rizzi:
Modeling and recognition of smart grid faults by a combined approach of dissimilarity learning and one-class classification. Neurocomputing 170: 368-383 (2015) - [c5]Enrico De Santis, Antonello Rizzi, Alireza Sadeghian, Fabio Massimo Frattale Mascioli:
A learning intelligent system for fault detection in Smart Grid by a One-Class Classification approach. IJCNN 2015: 1-8 - [i2]Filippo Maria Bianchi, Enrico De Santis, Hedieh Montazeri, Parisa Naraei, Alireza Sadeghian:
Position paper: a general framework for applying machine learning techniques in operating room. CoRR abs/1511.09099 (2015) - 2014
- [c4]Enrico De Santis, Gianluca Distante, Fabio Massimo Frattale Mascioli, Alireza Sadeghian, Antonello Rizzi:
Evolutionary Optimization of a One-Class Classification System for Faults Recognition in Smart Grids. IJCCI (ECTA) 2014: 95-103 - [c3]Enrico De Santis, Fabio Massimo Frattale Mascioli, Alireza Sadeghian, Antonello Rizzi:
A Dissimilarity Learning Approach by Evolutionary Computation for Faults Recognition in Smart Grids. IJCCI (Selected Papers) 2014: 113-130 - [c2]Enrico De Santis, Lorenzo Livi, Fabio Massimo Frattale Mascioli, Alireza Sadeghian, Antonello Rizzi:
Fault recognition in smart grids by a one-class classification approach. IJCNN 2014: 1949-1956 - [i1]Enrico De Santis, Lorenzo Livi, Alireza Sadeghian, Antonello Rizzi:
Modeling and Recognition of Smart Grid Faults by a Combined Approach of Dissimilarity Measures and One-Class Classification. CoRR abs/1407.7008 (2014) - 2013
- [c1]Enrico De Santis, Antonello Rizzi, Alireza Sadeghian, Fabio Massimo Frattale Mascioli:
Genetic optimization of a fuzzy control system for energy flow management in micro-grids. IFSA/NAFIPS 2013: 418-423
Coauthor Index
aka: F. M. Frattale Mascioli
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