A data-driven intelligent decision support framework for process operation management. An application to gas turbine process

Authors: Bagherzade Ghazvini, Mina

Contributors: University/Department: Universitat Politècnica de Catalunya. Departament de Ciències de la Computació

Thesis Advisors: Sànchez-Marrè, Miquel, Angulo Bahón, Cecilio

Source: TDX (Tesis Doctorals en Xarxa)

Subject Terms: Industrial Process Management, Predictive Maintenance, Operational Data Preprocessing, DataDriven Decision Making, Clustering Techniques, Operational Mode Analysis, Transition Modelling, Machine Learning, Pattern Detection, Gas Turbines., Gestió de Processos Industrials, Manteniment Predictiu, Pre-processament de Dades Operatives, Presa de Decisions Basada en Dades, Tècniques de Clustering, Anàlisi de Mode d’Operació, Modelatge de Transicions, Aprenentatge Automàtic, Detecció de Patrons, Turbines de Gas, Gestión de Procesos Industriales, Mantenimiento Predictivo, Preprocesamiento de Datos de Operación, Toma de Decisiones Basada en Datos, Técnicas de Clustering, Análisis de Modos de Operación, Modelado de Transiciones, Aprendizaje Automático, Detección de Patrones, Turbinas de Gas, Àrees temàtiques de la UPC::Informàtica, Àrees temàtiques de la UPC::Enginyeria mecànica, 004 - Informàtica, 621 - Enginyeria mecànica en general. Tecnologia nuclear. Electrotècnia. Maquinària

File Description: application/pdf

Access URL: http://hdl.handle.net/10803/696109
https://dx.doi.org/10.5821/dissertation-2117-449005

AutoModelling: From BMS operational data to validated Modelica models for chillers

Authors: Jin, Zhineng ^a, Wang, Zhe ^{a, b, ⁎}

Source: In Energy 30 September 2026 360

Leveraging Geospatial Data Gateways to Support the Operational Application of Deep Learning Models : Vision Paper

Authors: Soliman, Aiman, Terstriep, Jeffrey

Source: Proceedings of the 28th International Conference on Advances in Geographic Information Systems. :593-596

Availability: http://dl.acm.org/doi/10.1145/3397536.3422232

Construction of leakage warning dataset for shield tail sealing systems: Innovative data preprocessing and feature extraction

Authors: Wang, Lintao, Fan, Xiyuan ^⁎, Ding, Xinkai, Yang, Yili, Cai, Jingrun

Source: In Measurement 21 April 2026 270

Evaluating the impact of data preprocessing on deep neural architectures for Remaining Useful Life estimation of turbofan engines

Authors: Ruvaifa, Mohammad ^a, Banerjee, Pragyan ^b, Habib, Anowarul ^{c, ⁎}

Source: In Array July 2026 30

A novel combined framework for short-term wind speed forecasting based on data preprocessing with sequence reconstruction and Grey Wolf optimization

Authors: Ghaffar, Abdul ^a, Huo, Weidong ^{b, ⁎}, Qamar, Yasmeen ^c, Garg, Harish ^{d, ⁎}, Ghafoor, Sadeen ^b

Source: In Energy Reports December 2025 14:1251-1272

HAD-QC: A Hybrid AI Approach for Automated Quality Control of Argo Float Data

Authors: Aiwale, Shivshankar^Aff9, Stahl, Frederic^Aff10, Sun, Lily^Aff9

Contributors: Goos, Gerhard, Founding Editor^Aff1, Hartmanis, Juris, Founding Editor^Aff2, Bertino, Elisa, Series Editor^Aff3, Gao, Wen, Series Editor^Aff4, Steffen, Bernhard, Series Editor^Aff5, Yung, Moti, Series Editor^Aff6, Bramer, Max, editor^Aff7, Stahl, Frederic, editor^Aff8

Source: Artificial Intelligence XLII : 45th SGAI International Conference on Artificial Intelligence, AI 2025, Cambridge, UK, December 16-18, 2025, Proceedings, Part II. 16302:94-107

A Critical Review on Data Preprocessing Techniques for Building Operational Data Analysis

Authors: Fan, Cheng, primary, Chen, Meiling, additional, Wang, Xinghua, additional, Huang, Bufu, additional, Wang, Jiayuan, additional

Source: Proceedings of the 25th International Symposium on Advancement of Construction Management and Real Estate. 2021/01/01

Analyzing Machining Cycle Time Anomalies via CNC and Operational Data

Authors: Vlaminck, Noémie ^a, Nicolas, Michel ^b, Benamara, Tariq ^a, Raddoux, Hervé ^b

Source: In Procedia CIRP 2025 133:471-476

Fuel-cycle-aware data structuring for predictive and diagnostic modeling of Co-58 CRUD activity in pressurized water reactors

Authors: Choi, Jinsoo ^a, Yun, Jong-Il ^{b, ⁎}

Source: In Annals of Nuclear Energy November 2026 237

AI-Powered analytics: generating interactive insights over unprocessed data

Authors: Padeiro, Ana Patrícia Correia

Contributors: Gomes, Ana Luísa Gonçalves Neves, Marques, Gonçalo Caetano, RCIPL

Source: urn:tid:203806166

Subject Terms: Machine learning big data, Data analytics, Unsupervised learning, AI-Powered analytics, Data preprocessing, BERTopic, Natural language processing, Clustering algorithms, Feature selection, Decision-Making, Operational efficiency, Data insights, Análise de dados, Aprendizagem não supervisionada, Análise impulsionada por IA, Pré-processamento de dados, Processamento de linguagem natural, Algoritmos de clustering, Seleção de variáveis, Tomada de decisões, Eficiência operacional, Insights de dados

File Description: application/pdf

Availability: http://hdl.handle.net/10400.21/21655

Monitoring Data for Anomaly Detection in Cloud-Based Systems: A Systematic Mapping Study

Authors: Hrusto, Adha, Author, Ali, Nauman Bin, Author, Engström, Emelie, Author, Wang, Yuqing, Author, Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: AI and Digitalization, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: AI och digitalisering, Originator, Lund University, Faculty of Engineering, LTH, Departments at LTH, Department of Computer Science, Software Engineering, Lunds universitet, Lunds Tekniska Högskola, Institutioner vid LTH, Institutionen för datavetenskap, Programvarusystem, Originator, Lund University, Faculty of Engineering, LTH, Competence centers, LTH, NEXTG2COM – a Vinnova Competence Centre in Advanced Digitalisation, Lunds universitet, Lunds Tekniska Högskola, Kompetenscentrum, LTH, NEXTG2COM – ett Vinnova kompetenscenter inom Avancerad Digitalisering, Originator, Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Natural and Artificial Cognition, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Naturlig och artificiell kognition, Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Originator

Contributors: Hrusto, Adha, Author, Ali, Nauman Bin, Author, Engström, Emelie, Author, Wang, Yuqing, Author, Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: AI and Digitalization, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: AI och digitalisering, Originator, Lund University, Faculty of Engineering, LTH, Departments at LTH, Department of Computer Science, Software Engineering, Lunds universitet, Lunds Tekniska Högskola, Institutioner vid LTH, Institutionen för datavetenskap, Programvarusystem, Originator, Lund University, Faculty of Engineering, LTH, Competence centers, LTH, NEXTG2COM – a Vinnova Competence Centre in Advanced Digitalisation, Lunds universitet, Lunds Tekniska Högskola, Kompetenscentrum, LTH, NEXTG2COM – ett Vinnova kompetenscenter inom Avancerad Digitalisering, Originator, Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Natural and Artificial Cognition, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Naturlig och artificiell kognition, Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), ELLIIT: the Linköping-Lund initiative on IT and mobile communication, Originator

Source: ACM Transactions on Software Engineering and Methodology. 35(4):1-36

Subject Terms: Natural Sciences, Computer and Information Sciences, Software Engineering, Naturvetenskap, Data- och informationsvetenskap (Datateknik), Programvaruteknik

Access URL: https://doi.org/10.1145/3744556

Deterministic and probabilistic ship pitch prediction using a multi-predictor integration model based on hybrid data preprocessing, reinforcement learning and improved QRNN

Authors: Wei, Yunyu ^a, Chen, Zezong ^{a, ⁎}, Zhao, Chen ^a, Chen, Xi ^b, Yang, Rui ^c, He, Jiangheng ^a, Zhang, Chunyang ^a, Wu, Sitao ^a

Source: In Advanced Engineering Informatics October 2022 54

Perception model of surrounding rock geological conditions based on TBM operational big data and combined unsupervised-supervised learning

Authors: Yin, Xin ^{a, b}, Liu, Quansheng ^{a, b, ⁎}, Huang, Xing ^c, Pan, Yucong ^{a, b}

Source: In Tunnelling and Underground Space Technology incorporating Trenchless Technology Research February 2022 120

Data-driven approach for predicting power and shaft RPM in seaways by principal component regression

Authors: Lee, Seungbeom ^a, Seo, Jeonghwa ^{a, b, ⁎}, Kim, Dong-Hwan ^c, Kim, Minchang ^a, Kim, Kwanwoo ^d, Han, Sangmin ^d, Chung, Sungwook ^d

Source: In Ocean Engineering 15 March 2026 349

SSA-SVR-NGO based hydrodynamic derivatives identification through full-scale sea trial data

Authors: Wang, Yuqing ^{a, b}, Fang, Tian ^c, Huang, Liang ^d, Wang, Xing ^{e, f}, Song, Lifei ^{a, b, ⁎}

Source: In Ocean Engineering 30 August 2026 364 Part 1

A modern workflow for energy consumption prediction: Comparative analysis of machine learning techniques

Authors: Ben Abdelaziz, Lotfi ^{a, b, ⁎}, Elmenreich, Wilfried ^b, Mami, Abdelkader ^a

Source: In Measurement: Energy June 2026 10

A novel anomaly data detection and correction method for renewable energy stations

Authors: Wen, Guanru ^{a, b}, Zhang, Yun ^{a, b, ⁎}, Han, Zifen ^c, Jia, Zimeng ^b, Ren, Zhaolu ^b, Tian, Biao ^b

Source: In Electric Power Systems Research December 2026 261

A data-driven approach to extract operational signatures of HVAC systems and analyze impact on electricity consumption

Authors: Yu, Xinran, Ergan, Semiha ^⁎, Dedemen, Gokmen

Source: In Applied Energy 1 November 2019 253

A non-intrusive net-load disaggregation framework for behind-the-meter DER capacity estimation using a generative adversarial network data curation

Authors: Kanchana, Wutthipum, Singh, Jai Govind ^⁎, Ongsakul, Weerakorn

Source: In Electric Power Systems Research November 2026 260