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In the last two decades the efficient traffic-flow prediction of vehicles has been significant in curbing traffic congestions at freeways and road intersections and it is among the many advantages of applying intelligent transportation systems in road intersections. However, transportation researchers have not focused on prediction of vehicular traffic flow at road intersections using hybrid algorithms such as adaptive neuro-fuzzy inference systems optimized by genetic algorithms. In this research, we propose two models, namely the adaptive neuro-fuzzy inference system (ANFIS) and the adaptive neuro-fuzzy inference system optimized by genetic algorithm (ANFIS-GA), to model and predict vehicles at signalized road intersections using the South African public road transportation system. The traffic data used for this research were obtained via up-to-date traffic data equipment. Eight hundred fifty traffic datasets were used for the ANFIS and ANFIS-GA modelling. The traffic data comprised traffic volume (output), speed of vehicles, and time (inputs). We used 70% of the traffic data for training and 30% for testing. The ANFIS and ANFIS-GA results showed training performance of (R2) 0.9709 and 0.8979 and testing performance of (R2) 0.9790 and 0.9980. The results show that ANFIS-GA is more appropriate for modelling and prediction of traffic flow of vehicles at signalized road intersections. This research adds further to our knowledge of the application of hybrid genetic algorithms in traffic-flow prediction of vehicles at signalized road intersections.

Cyclone separators are used extensively in diverse applications and research domains to collect particle-laden flows. Despite the technological advances in this field, no bibliometric reports on this topic have been documented. Understanding the state of the art in this field is crucial for future research. Using bibliometric mapping techniques, this study examined the quality, quantity, and development of research on cyclone separators. Relevant data were extracted in plain text formats through search queries refined by publication year (2000–2021) and document type (article and review articles). A sample of 487 publications, limited to the Web of Science Core Collection (WoSCC) database was used for the bibliometric analysis. Data analysis was performed using RStudio software package (R Bibliometrix tool). Of the 487 publications that appeared during this period, China had the highest number, followed by the Islamic Republic of Iran, whereas chemical engineering journals dominated the cyclone separator research publications. Collaboration among the researchers was low (MCPR < 0.5000). Furthermore, the pattern of single-author publications was found to outstrip that of the multiple-author publications. The findings suggest that researchers in various parts of the world, particularly Africa and the Middle East, should route their research efforts towards this field, in light of the lack of publications from these regions on this subject. The aim of this study was to serve as a seminal reference for potential technological research directions and collaboration among researchers in this and other related fields.

The influence of variable operational conditions affects the performance of particle collection and separation of a regenerative air vacuum sweeper. Therefore, the purpose of this paper was to numerically investigate the factors affecting the particle suction efficiency of the pick-up head. Using computational fluid dynamics (CFD), a model of an integrated pick-up head was developed based on the particle suction process to evaluate the particle removal performance. The realizable k-ε and discrete particle models were utilized to study the gas flow field and solid particle trajectories. The particle structure, sweeping speed, secondary airflow, pressure drop, and distance between the particle suction port and the road surface, as factors that affect the particle removal efficiency, were investigated. The results indicate that the particle suction efficiency increases with decreasing sweeper speed. Furthermore, the particle overall removal efficiency increased with a reduction in the distance between the suction port and the road surface as well as the control of the secondary airflow in the system. By increasing the airflow rate at the suction port, high efficiencies were achieved at a high sweeper speed and high particle densities. At a sweeper speed of 6–10 km/h, the results showed that the secondary airflow recirculation varied between 60 to 80 %, while the high-pressure drop ranged from 2200 to 2400 Pa, and the particle suction efficiency recorded was 95%. The numerical analysis results provide a better understanding of the particle suction process and hence could lead to an improvement in the design of the pick-up head.