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A Study on Mechanical, Electrical Properties and Morphology of Ps/Eoc/Cnt Nanocomposite Blends
, M.Sc. Thesis Sharif University of Technology ; Pircheraghi, Gholamreza (Supervisor) ; Seyed Reyhani, Morteza (Supervisor)
Abstract
Nowadays, the development of different polymer blend nanocomposites is of great importance for achieving electrical and antistatic properties for various applications such as auto parts and the packaging industry. Immiscible polymer blends with conductive nanoparticles such as carbon nanotube, graphene, etc. can reach the conductivity threshold with low amounts of nanoparticles and produce desired electrical properties. In the present study, we have attempted to develop a polystyrene(PS)/ethylene-octene copolymer(EOC)/carbon nanotube(CNT) blend nanocomposite with suitable electrical conductivity. The compounding was performed by melt mixing at two weight percent of 80/20 and 50/50 (PS/EOC)...
Locally linear neuro-fuzzy (LLNF) electricity price forecasting in deregulated power markets
, Article International Journal of Innovative Computing, Information and Control ; Volume 6, Issue 9 , 2010 , Pages 4203-4218 ; 13494198 (ISSN) ; Mahjoob, M. J ; Zarringhalam, R ; Miranian, A ; Sharif University of Technology
2010
Abstract
The disguise of traditional monopolistic electricity markets into deregulated competitive ones has made 'price forecasting' a crucial strategy for both producers and consumers: for the producers, to maximize their profit and hedge against price volatilities and for the consumers to manage their utility. Electricity price forecasting has thus emerged as a progressive field of study and numerous researches have been conducted to improve and optimize the price forecast methods. This paper proposes a precise and computationally efficient method to perform price forecasting in deregulated power markets. A locally linear neuro-fuzzy model is developed for price forecasting. The model is trained by...