Télécharger The Swarm: A Novel of the Deep Livre audio

Titre	The Swarm: A Novel of the Deep
Une longueur de temps	55 min 34 seconds
Taille du fichier	1,195 KB
Libéré	3 years 8 months 20 days ago
Qualité	RealAudio 44.1 kHz
Des pages	106 Pages
Fichier	the-swarm-a-novel-of_t5Lp5.epub
	the-swarm-a-novel-of_Z3TCY.aac

The Swarm: A Novel of the Deep

Catégorie: Livres pour enfants, Sciences humaines
Auteur: Irving Geis, Naughty Dog
Éditeur: Neil Gaiman
Publié: 2017-09-14
Écrivain: Ryan Ottley, Adrian Tomine
Langue: Tchèque, Turc, Anglais, Suédois
Format: pdf, Livre audio

Death and the devil - Frank Schätzing - Quercus Publishing - Poche - Lucioles VIENNE - It's the year 1260 and the great cathedral the most ambitious building in all of Christendom is rising above the streets of Cologne. Far below its soaring spires and flying buttresses, an assassin of unnatural talent surveys his new hunting ground.

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- The Swarm: A Novel of the Deep - Schätzing, Frank, Schatzing, Frank, Spencer, Sally-Ann - Livres - The Swarm: A Novel of the Deep

Adam Slowik - ‪Koszalin University of Technology‬ - ‪‪Cité(e) 859 fois‬‬ - ‪computer science‬ - ‪artificial intelligence‬ - ‪soft computing‬ - ‪electronics‬ - ‪digital circuits‬

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Proton Exchange Membrane Fuel Cells Prognostic Strategy Based on Navigation Sequence Driven Long Short-term Memory Networks - Lifetime and reliability seriously affect the applications of proton exchange membrane fuel cell (PEMFC). Performance degradation prediction of PEMFC is the basis for improving the lifetime and reliability of PEMFC. To overcome the lower prediction accuracy caused by uncertainty and nonlinearity characteristics of degradation voltage data, this article proposes a novel deep belief network (DBN) and extreme learning machine (ELM) based performance degradation prediction method for PEMFC. A DBN based fuel cell degradation features extraction model is designed to extract high-quality degradation features in the original degradation data by layer-wise learning. To tackle the issues of overfitting and instability in fuel cell performance degradation prediction, an ELM with good generalization performance is introduced as a nonlinear prediction model, which can get some enhancement of prediction precision and reliability. Based on the designed DBN-ELM model, the particle swarm optimization (PSO) algorithm is used i

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