TY - JFULL AU - Joseph S. Ojo and Vincent A. Akpan and Oladayo G. Ajileye and Olalekan L and Ojo PY - 2017/10/ TI - QoS Improvement Using Intelligent Algorithm under Dynamic Tropical Weather for Earth-Space Satellite Applications T2 - International Journal of Computer and Information Engineering SP - 1098 EP - 1105 VL - 11 SN - 1307-6892 UR - https://publications.waset.org/pdf/10008802 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 129, 2017 N2 - In this paper, the intelligent algorithm (IA) that is capable of adapting to dynamical tropical weather conditions is proposed based on fuzzy logic techniques. The IA effectively interacts with the quality of service (QoS) criteria irrespective of the dynamic tropical weather to achieve improvement in the satellite links. To achieve this, an adaptive network-based fuzzy inference system (ANFIS) has been adopted. The algorithm is capable of interacting with the weather fluctuation to generate appropriate improvement to the satellite QoS for efficient services to the customers. 5-year (2012-2016) rainfall rate of one-minute integration time series data has been used to derive fading based on ITU-R P. 618-12 propagation models. The data are obtained from the measurement undertaken by the Communication Research Group (CRG), Physics Department, Federal University of Technology, Akure, Nigeria. The rain attenuation and signal-to-noise ratio (SNR) were derived for frequency between Ku and V-band and propagation angle with respect to different transmitting power. The simulated results show a substantial reduction in SNR especially for application in the area of digital video broadcast-second generation coding modulation satellite networks. ER -