Temat: multi-layer - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Advanced coating of interior of tanks for rising environmental safety - novel applications of polyurethanes
Autorzy:: Datta, J.
Haponiuk, J. T.
Powiązania:: https://bibliotekanauki.pl/articles/963383.pdf
Data publikacji:: 2008
Wydawca:: Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:: polyurethane elastomers
multi-layer constructions
adhesives
recycling
Opis:: The aim of this study was to develop urethane elastomers of predefined properties to be used as elastic coating in the cargo tanks of tankers. A method for coating the liquid polyurethane system onto steel and steel-concrete elements, and a way to join polyurethane coating with the aforementioned elements, were elaborated. The technique of injection the reactive liquid polyurethane system onto cold steel elements was used. The method for utilization and recovery of urethane oligomerols from the waste polyurethane coating in chemical recycling by using low molecular weight glycols as glycolysis agents was proposed.
Źródło:: Polish Maritime Research; 2008, S 1; 8-13
1233-2585
Pojawia się w:: Polish Maritime Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Fuzzy method and neural network model parallel implementation of multi-layer neural network based on cloud computing for real time data transmission in large offshore platform
Autorzy:: Zhang, H..
Qin, W.
Powiązania:: https://bibliotekanauki.pl/articles/259083.pdf
Data publikacji:: 2017
Wydawca:: Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:: parallel implementation
multi-layer neural network
cloud computing
Opis:: With the rapid development of electronic technology, network technology and cloud computing technology, the current data is increasing in the way of mass, has entered the era of big data. Based on cloud computing clusters, this paper proposes a novel method of parallel implementation of multilayered neural networks based on Map-Reduce. Namely in order to meet the requirements of big data processing, this paper presents an efficient mapping scheme for a fully connected multi-layered neural network, which is trained by using error back propagation (BP) algorithm based on Map-Reduce on cloud computing clusters (MRBP). The batch-training (or epoch-training) regimes are used by effective segmentation of samples on the clusters, and are adopted in the separated training method, weight summary to achieve convergence by iterating. For a parallel BP algorithm on the clusters and a serial BP algorithm on uniprocessor, the required time for implementing the algorithms is derived. The performance parameters, such as speed-up, optimal number and minimum of data nodes are evaluated for the parallel BP algorithm on the clusters. Experiment results demonstrate that the proposed parallel BP algorithm in this paper has better speed-up, faster convergence rate, less iterations than that of the existed algorithms.
Źródło:: Polish Maritime Research; 2017, S 2; 39-44
1233-2585
Pojawia się w:: Polish Maritime Research
Dostawca treści:: Biblioteka Nauki

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