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[null,"1.","Record Nr.",null,"UNISA996387664203316"]
[null,null,"Autore",null,"Perkins William <1558-1602.>"]
[null,null,"Titolo",null,"The workes of that famous and worthy minister of Christ in the Universitie of Cambridge, M. VV. Perkins . The third and last volume [[electronic resource] ] : containing his learned expositions of sundry choice places of Scripture, with some little tractates, the particulars whereof thou maist see in the next page, with the order of their placing : hereto is adjoyned a two-fold table, one of the chiefe points and questions, the other of choice places of Scripture"]
[null,null,"Pubbl/distr/stampa",null,"London, : Printed by Iohn Haviland, for Iames Boler, 1631"]
[null,null,"Edizione",null,"[Newly corrected and amended.]"]
[null,null,"Descrizione fisica",null,"[8], 264, [14], 206, [12], 207-370, [10], 371-409, [7], 411-427, [7], 429-439, [5], 441-463, [5], 465-477, [10], 479-605, [11], 607-652, [2], 653-667, [3], 669-700, [14] p., [1] folded leaf"]
[null,null,"Soggetti",null,"Theology"]
[{"$nulls":4},"Theology - History - 16th century"]
[{"$nulls":4},"Sermons, English - 16th century"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Each part has special t.p. and first part has separate pagination."]
[{"$nulls":4},"Imprints vary, but all are dated 1631."]
[{"$nulls":4},"Signatures: A⁸ B-4T⁶ 4V⁴."]
[{"$nulls":4},"Reproduction of original in the Oriel College. Library."]
[null,null,null,"Sommario/riassunto","eebo-0105"]
[null,"2.","Record Nr.",null,"UNINA9910988385203321"]
[null,null,"Autore",null,"Sarmas Elissaios"]
[null,null,"Titolo",null,"Artificial Intelligence for Energy Systems : Driving Intelligent, Flexible and Optimal Energy Management / / by Elissaios Sarmas, Vangelis Marinakis, Haris Doukas"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025"]
[null,null,"ISBN",null,"3-031-85209-5"]
[null,null,"Edizione",null,"[1st ed. 2025.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XVII, 266 p. 49 illus., 40 illus. in color.)"]
[null,null,"Collana",null,"Learning and Analytics in Intelligent Systems, , 2662-3455 ; ; 46"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Computational intelligence"]
[{"$nulls":4},"Engineering - Data processing"]
[{"$nulls":4},"Energy policy"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Computational Intelligence"]
[{"$nulls":4},"Data Engineering"]
[{"$nulls":4},"Energy Policy, Economics and Management"]
[{"$nulls":4},"Artificial Intelligence"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"1.The Climate Crisis and the Four Pillars of Energy Transition: Decarbonization, Digitization, Decentralization, and Democratization -- 2.The Role of Artificial Intelligence in Transforming the Energy Sector: A Comprehensive Review -- 3.Scalable Framework for Intelligent System Architecture to Address Challenges in the Energy Sector -- 4.Deep Learning Models for Short-Term Forecasting of Photovoltaic Energy Production -- 5.Machine Learning-Driven Energy Consumption Forecasting for Building Profiling -- 6.Meta-Learning Approaches for Assessing Energy Efficiency Investments in Buildings -- 7.Ensemble Machine Learning Models for Estimating Energy Savings from Efficiency Measures in Buildings -- 8.Optimization Model for Scheduling Flexible Loads to Mitigate Energy Peaks -- 9.Optimization Model for Electric Vehicle Integration and Energy Storage to Achieve Energy Autonomy -- 10.Future Directions of Intelligent Energy Management and the Role of Generative AI."]
[null,null,null,"Sommario/riassunto","This book focuses on creating an integrated library of learning models and optimization techniques to assist decision-making on issues in the "]
[{"$nulls":4},"energy and building sector. It provides modern solutions to energy management and efficiency while addressing a scientific gap in the development of advanced algorithmic methods to solve these problems. More specifically, the focus is on the development of models and algorithms for problems falling into three broader categories, namely: (a) Distributed Energy Generation, (b) Microgrid Flexibility, and (c) Building Energy Efficiency. Artificial Intelligence models and mathematical optimization techniques are developed and presented for applications related to each of these categories, through a thorough analysis of the fundamental parameters of each application as well as the interactions among them. Professors, researchers, scientists, engineers, and students in energy sector-related disciplines are expected to be inspired and benefit from this book, along with readers from other disciplines wishing to learn more about this exciting new field of research."]