Search Results

You are looking at 11 - 20 of 24 items for :

  • "machine learning" x
  • Materials and Applied Sciences x
  • All content x
Clear All

During the production of gas one of the major problems is the formation of hydrate crystals in the pipeline. The growing hydrate crystals can form hydrate plugs in the pipeline. The hydrate plug effect lengthens production outages and results in the loss of money of the maintainer, because the removal of the plug is a time consuming procedure. One of the solutions used to prevent hydrate formation is the addition of modern compositions to the gas flow. The modern compositions help to dehydrate the gas, thus, the size of hydrate crystal does not increase. The substances, used in low concentrations, have to be locally injected at the gas well sites. Thus, an injector unit is required for this purpose. The production-related aspect that the consumers expect much more flexibility from gas provider cannot be neglected because of the habits of the users and the appearance of energy-saving technologies are different. The first part of the article a newly developed injection system is introduced. To achieve optimal dosage, not only the hardware of injection system is important, but also the software. In addition to the traditional control, a preventive inhibitor dosing system can be developed, based on model driven system. The nature of the model highly influences the quality of control system. In the second part of the article a machine learning based predictive detection system is introduced

Restricted access

References [1] Bansal N. , Blum A. , Chawla S. Correlation clustering , Machine Learning , Vol. 56 , No. 1-3 , 2004

Open access

) 2003 Goldberg, D. E. Genetic Algorithms in Search, Optimization, and Machine Learning Addison-Wesley Publishing Company, Inc., 1989

Restricted access

. Genetic algorithms in search, optimization, and machine learning, Addison-Wesley Publishing Company, Inc. 1989.

Restricted access

microbial spoilage of meat by Fourier transform infrared spectroscopy and machine learning. Appl. environ. Microbiol. , 68 , 2822–2828. Goodacre R. Rapid and quantative detection

Restricted access

, Distill , Vol. 1 , No. 10 , 2016 , Paper e2. [18] Van Der Maaten L. , Hinton G. Visualizing data using t-SNE , Journal of Machine

Restricted access

, No. 3 , 2012 , pp. 15 – 21 . [5] Goldberg D. E. Genetic algorithms in search optimization and machine

Restricted access
Pollack Periodica
Authors: Mykola Sysyn, Vitalii Kovalchuk, Ulf Gerber, Olga Nabochenko, and Andriy Pentsak

] Sysyn M. , Gruen , D. , Gerber , U. , Nabochenko , O. , Kovalchuk V. Turnout monitoring with vehicle based inertial measurements of operational trains: a machine learning approach , Communications

Full access

. [24] Bupe C. What is the difference between knowledge based approach and machine learning approach for sentiment analysis , Answer, Quora , 2016

Restricted access

. , Domingos P. , Weld D. S. Version space algebra and its application to programming by demonstration , Proceedings of the Seventeenth International Conference on Machine Learning, ICML '00 , 29 June - 2 July 2000 , pp. 527 – 534

Restricted access