Mining method selection by integrated AHP and PROMETHEE method

A hybrid GIS-MCDM approach for multi-level risk assessment and corresponding effective criteria in optimal solar power plant

This study aims to propose a hybrid method for suitability assessment with different risk levels to construct solar power plants (CSPPs) in southern Iran. The fuzzy-analytic hierarchy process (AHP) and fuzzy were applied to forecast and determine the suitable location for CSPPs. To extract suitable location maps with different risk levels for CSPPs, ordered weighted averaging (OWA) was implemented. In addition, the best subset regression method was used to determine the most effective factors in CSPPs. Based on the results of the fuzzy-AHP method, 42% of the southern regions of the area was suitable for CSPPs. Based on the results of the OWA method, the most suitable areas were located in the north and south in all of the risk areas with increasing values. The results demonstrated that the FCM and sub-clustering approaches can accurately predict land suitability classes (LSCs) for CSPPs. Moreover, the best subsets regression (BSR) results showed that distance to power transmission line (PTL) and temperature exhibited the strongest correlation. Finally, receiver operating characteristics (ROC) were used to determine the accuracy of these methods. The results showed that the area under the curve (AUC) values were highly accurate (AUC_Fuzzy-AHP = 85.0%, AUC_OWA = 83.0%).

An enhanced heuristic XoR network coding-based method for high quality video streaming over VANETs

One of the most important challenges in live video streaming in mobile vehicular networks is the optimal use of broadband and point-to-point packet delay. Recent studies show that the sheer use of frames flow compression methods (such as H.264 or HEVC) and the proper communication overlay, such as Peer-to-Peer (P2P), has no absolute influence on increasing the quality of received video in VANET networks. Therefore, the use of an appropriate data exchange method, such as network coding, seems to be of great importance. Compared to Random Network Coding (RNC), XoR Network Coding (XNC) method has the least computational load for the network which is an important factor in optimal use of limited energy of nodes in a wireless network. The basic problem in XNC is that when a node is supposed to combine several frames and transmit them through an encoded frame, how this combination could be made to enable other nodes of the network to be broadcasted through receiving this packet and how can the available packets in their buffers decode as well as extract the largest number of frames in order to experience a higher video quality. To fulfil this aim, an encoding intelligent method is required which is based on the buffers' status of neighbours. In the proposed method in this article, the best frame combination is reached through buffers status of neighbours and AHP methods or AHP-TOPSIS methods, and the encoded frames are broadcasted through XNC. Simulation results show that due to the reduction in number of transmitted packets in the network, parameters such as congestion and point-to-point delay are significantly reduced and vehicles experience a higher video quality compared with other similar methods.