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The work deals with renewable energy project, in the context of the deregulated energy market. Special attention is focused on renewables and on the situation in Italy from the standards point of view. The set up of a wind farm and a PV plant in coastal Sardinian area for both electricity and desalinated water production is studied. The convenience of fuelling desalination plants through renewables is investigated by taking into account additional on-side trading instruments. A model to simulate the operation wind and PV systems is applied both to calculate the produced energy and to assess the performance of a desalination plant, namely a reverse osmosis plant driven with PV and wind sources that works in a small island site.
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The work deals with renewable energy project, in the context of the deregulated energy market. Special attention is focused on renewables and on the situation in Italy from the standards point of view. The set up of a wind farm and a PV plant in coastal Sardinian area for both electricity and desalinated water production is studied. The convenience of fuelling desalination plants through renewables is investigated by taking into account additional on-side trading instruments. A model to simulate the operation wind and PV systems is applied both to calculate the produced energy and to assess the performance of a desalination plant, namely a reverse osmosis plant driven with PV and wind sources that works in a small island site.
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The class of semi-Markov processes includes strong Markov processes, Le;vy and Smith stepped semi-Markov processes, and some other subclasses. Extensive coverage is devoted to non-Markovian semi-Markov processes with continuous trajectories and, in particular, to semi-Markov diffusion processes. Readers looking to enrich their knowledge on Markov processes will find this book a valuable resource.
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Hidden semi-Markov models (HSMMs) are among the most important models in the area of artificial intelligence / machine learning. Since the first HSMM was introduced in 1980 for machine recognition of speech, three other HSMMs have been proposed, with various definitions of duration and observation distributions. Those models have different expressions, algorithms, computational complexities, and applicable areas, without explicitly interchangeable forms. Hidden Semi-Markov Models: Theory, Algorithms and Applications provides a unified and foundational approach to HSMMs, including various HSMMs (such as the explicit duration, variable transition, and residential time of HSMMs), inference and estimation algorithms, implementation methods and application instances. Learn new developments and state-of-the-art emerging topics as they relate to HSMMs, presented with examples drawn from medicine, engineering and computer science. Discusses the latest developments and emerging topics in the field of HSMMs Includes a description of applications in various areas including, Human Activity Recognition, Handwriting Recognition, Network Traffic Characterization and Anomaly Detection, and Functional MRI Brain Mapping. Shows how to master the basic techniques needed for using HSMMs and how to apply them.
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