{"text_format":"2","workbook":"xls","n_sheets":1,"sheets":["report2"],"not_rendered":{"charts":0,"images":0,"macros":0,"external_links":1,"defined_names":1,"comments":0,"pivot_tables":0},"unopened":[],"bounds":{"document_bytes":16777216,"sheet_cells":100000,"run_cost":"one","rows_first":2000,"rows_last":500,"rows_between":2000,"halvings":0,"cell_chars":16384,"cell_head_chars":4096},"cells_cut":0,"cells_raw":0,"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"report2","index":0,"n_rows":26,"n_cols":5,"rows_kept":26,"cut":false,"hidden":false,"merged":[[0,2,0,3],[0,4,0,5],[1,2,1,3],[1,4,1,5],[2,2,2,3],[3,2,3,3],[5,2,5,3],[6,2,6,3],[7,2,7,3],[8,2,8,3],[9,2,9,3],[19,2,19,3],[20,2,20,3],[23,2,23,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNINA9910983360403321"]
[null,null,"Titolo",null,"Energy Informatics : 4th Energy Informatics Academy Conference, EI.A 2024, Kuta, Bali, Indonesia, October 23–25, 2024, Proceedings, Part I / / edited by Bo Nørregaard Jørgensen, Zheng Grace Ma, Fransisco Danang Wijaya, Roni Irnawan, Sarjiya Sarjiya"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025"]
[null,null,"ISBN",null,"9783031747380"]
[{"$nulls":4},"3031747380"]
[null,null,"Edizione",null,"[1st ed. 2025.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XVII, 381 p. 141 illus., 122 illus. in color.)"]
[null,null,"Collana",null,"Lecture Notes in Computer Science, , 1611-3349 ; ; 15271"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Machine learning"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Business information services"]
[{"$nulls":4},"Computers, Special purpose"]
[{"$nulls":4},"Data mining"]
[{"$nulls":4},"Machine Learning"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Business Information Systems"]
[{"$nulls":4},"Special Purpose and Application-Based Systems"]
[{"$nulls":4},"Data Mining and Knowledge Discovery"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"IoT Edge Computing, and Software Innovations in Energy -- Scheduling Electric Currents in Converter-Dominated Power Grids with Time Slotted Energy Packets -- Symbiosis A Web Based Decision Support Tool for Achieving Symbiosis in Industrial Parks -- A Cost Effective Edge Computing Gateway for Smart Buildings -- Leveraging Internet of Things Network Metadata for Cost Effective Automatic Smart Building Visualization -- Process to Market A Web based Evaluation Tool for Electricity Market Participation -- IoT Based Smart Air Ventilation and Energy Management System -- Big Data Analytics and Cybersecurity in Energy -- Leveraging Open Data for Energy Source Selection in Bi Valent Industrial Processes -- Legal overview of latest developments in the Energy Sector regarding data protection and cybersecurity -- Energy Data Collection Protocol A Case Study on the ADRENALIN Project "]
[{"$nulls":4},"-- DataPro A Standardized Data Understanding and Processing Procedure A Case Study of an Eco-driving Project -- Detection of Municipal Heat Plan Documents Using Semantic Recognition Methods -- Digital Twin Technology and Energy Simulations -- Challenges in Transitioning from Co-Simulation to Practical Application A Case Study on Economic Emission Dispatch in a Greenhouse Compartment -- Multi Agent Based Simulation for Investigating Centralized Charging Strategies and their Impact on Electric Vehicle Home Charging Ecosystem -- Leveraging Digital Twins for Sustainable District Heating A Study on Waste Heat from Power to X Plants -- Hardware in the Loop Based Validation of Distribution System Control Applications with Grid Operators Customer and Market Participants -- Geospatial Semantic Enriched Digital Twin with Logical Reasoning Rules for Managing Control Loops -- Data Driven Digital Twin for Foundry Production Process Facilitating Best Practice Operations Investigation and Impact Analysis -- Energy data and consumer behaviors -- Automation level taxonomy for time series forecasting services Guideline for real world smart grid applications -- Enhanced Consumer Segmentation through Load Profile Analysis Using Auto encoder and K shape Cluster -- Occupants experiencing energy poverty Where are they in energy datasets and Time Use Surveys -- Extracting Daily Aggregate Load Profiles from Monthly Consumption -- Digitalization of District Heating and Cooling Systems -- Digitalization of District Heating Transforming Heat Networks for a Sustainable Future -- Fault detection in district heating substations overview of real life faults in residential heating installations -- Multi agent based modeling for investigating excess heat utilization from electrolyzer production to district heating network."]
[null,null,null,"Sommario/riassunto","Chapter “Automation Level Taxonomy for Time Series Forecasting Services: Guideline for Real-World Smart Grid Applications” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com."]