Title: Prediction of oil production based on SVM optimised multi-objective particle swarm optimisation

Authors: Rong Wang-Yin; Rui Zhou; An Xian-Shao; Jing Yu-Pang

Addresses: Department of Basic Teaching and Experiment, HeFei University, Hefei 230601, China ' Department of Basic Teaching and Experiment, HeFei University, Hefei 230601, China ' Department of Basic Teaching and Experiment, HeFei University, Hefei 230601, China ' Department of Basic Teaching and Experiment, HeFei University, Hefei 230601, China

Abstract: The unstable availability and capacity exist in energy efficiency optimisation regarding to renewable energy supply for cellular network due to several factors, such as climate change, high oil resource consumption and energy safety etc. The energy supply sustainability problem is modelled as optimisation solution problem aiming at maximising NP-hard network energy residue ratio (ERR). The network ERR maximisation algorithm has been put forward through analysis of relationship between energy efficiency and energy depletion rate (EDR). This algorithm is worked by adopting cross-layer manner, which first maximises the link energy efficiency by the power control at physical (PHY) layer and then maximises network ERR by the access control at media access control (MAC). The simulation results show that the network ERR maximisation algorithm performs excellently in improving network lifetime as well as increasing the number of users served by renewable energy.

Keywords: energy efficiency; cellular network; renewable energy; energy residue rate; EDR; energy depletion rate.

DOI: 10.1504/IJISTA.2018.095099

International Journal of Intelligent Systems Technologies and Applications, 2018 Vol.17 No.4, pp.415 - 426

Received: 01 Jun 2017
Accepted: 10 Jul 2017

Published online: 01 Oct 2018 *

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