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[null,"1.","Record Nr.",null,"UNINA990007034010403321"]
[null,null,"Autore",null,"Renzoni Governatori, Laura"]
[null,null,"Titolo",null,"La Separazione tra Stato e Chiese in Francia e la tutela degli interessi religiosi / Laura Governatori Renzoni"]
[null,null,"Pubbl/distr/stampa",null,"Milano : Dott. A. Giuffrè, 1977"]
[null,null,"Descrizione fisica",null,"357 p. ; 25 cm"]
[null,null,"Collana",null,"Università di Macerata pubblicazioni della Facoltà di Giurisprudenza ; 13"]
[null,null,"Locazione",null,"DCEC"]
[null,null,"Collocazione",null,"II HH 34"]
[null,null,"Lingua di pubblicazione",null,"Italiano"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,"2.","Record Nr.",null,"UNINA9911002551703321"]
[null,null,"Autore",null,"Suhaimi Shafiq Bin"]
[null,null,"Titolo",null,"Flapping Wing Micro Air Vehicles : Bio-Inspired Aerodynamics / / by Shafiq Bin Suhaimi, Solehuddin Shuib, Hamid Yusoff"]
[null,null,"Pubbl/distr/stampa",null,"Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025"]
[null,null,"ISBN",null,"981-9629-08-X"]
[null,null,"Edizione",null,"[1st ed. 2025.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XVII, 78 p. 57 illus., 44 illus. in color.)"]
[null,null,"Collana",null,"SpringerBriefs in Applied Sciences and Technology, , 2191-5318"]
[null,null,"Disciplina",null,"610.28"]
[null,null,"Soggetti",null,"Biomedical engineering"]
[{"$nulls":4},"Biomechanics"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Vehicles"]
[{"$nulls":4},"Biomechanical Analysis and Modeling"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Vehicle Engineering"]
[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,"-- Introduction.  -- Bat Inspired Wing Design.  -- Bat Inspired Wing Performance.  -- Final thoughts."]
[null,null,null,"Sommario/riassunto","This book highlights the design and performance of bio-inspired approach to a flying drone design. The flying drone design in this book is a micro-air vehicle (MAV) where the wingspan of the drone is less than 15cm. It focuses on the wing design of the MAV which is a flapping wing that is based on bat wings. In the first part, this book delves into the past work that has been done in this area and gives a bigger picture of the design approach as well as the blind spots that are in the field. In the second part, the book presents a novel design process with experiments that have been done to measure the performance of the design."]
[null,"3.","Record Nr.",null,"UNINA9911015633903321"]
[null,null,"Autore",null,"Guérillot Dominique"]
[null,null,"Titolo",null,"Artificial Intelligence Proxy Models: Applications in Geosciences / / by Dominique Guérillot"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025"]
[null,null,"ISBN",null,"9783031904479"]
[{"$nulls":4},"9783031904462"]
[null,null,"Edizione",null,"[1st ed. 2025.]"]
[null,null,"Descrizione fisica",null,"1 online resource (67 pages)"]
[null,null,"Collana",null,"SpringerBriefs in Computational Intelligence, , 2625-3712"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Computational intelligence"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Earth sciences"]
[{"$nulls":4},"Computational Intelligence"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Earth Sciences"]
[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,"Methodology to Build an Artificial Neural Network for Reservoir Engineering Problems -- Artificial Neural Networks for Reservoir Engineering Problems -- Application to these Advanced Workflows to the Brugge Field Case -- Description of the Brugge Fiel."]
[null,null,null,"Sommario/riassunto","This Springer Brief focuses on the use of artificial intelligence (AI) in geosciences and reservoir engineering. This concise yet comprehensive work explores how AI-driven proxy models can effectively tackle the computational challenges associated with reservoir simulations, history matching, production optimization, and uncertainty analysis. In reservoir engineering, a key challenge is reproducing observed production and pressure data using forward simulation models, known as reservoir simulators. However, the inverse problem of history matching requires running hundreds of simulations, each demanding significant computational resources. Full-scale reservoir simulators are often too time-consuming, making proxy models—such as second-order polynomials, kriging, and artificial neural networks (ANN)—essential alternatives. This Springer Brief emphasizes the power of AI, particularly ANN, as the most pragmatic approach for addressing real-world reservoir engineering problems. ANN has already gained widespread acceptance in computationally intensive fields such as "]
[{"$nulls":4},"aerospace, defense, and security due to its ability to model nonlinearities. Given the highly nonlinear nature of reservoir simulations, this book demonstrates how artificial neural networks-based proxies provide efficient and accurate solutions. To illustrate these concepts, the methodology is applied to a synthetic field inspired by real-world data: the Brugge field dataset. This widely used open-source dataset enables practitioners to familiarize themselves with AI-driven workflows in reservoir simulation. The Brief covers key applications, including history matching, production optimization (e.g., well placement and production rates), and uncertainty analysis, with detailed explanations of the workflows for each case. This Brief offers high-quality scientific content aligned with international research standards. It is now available in both print and digital formats."]