Railway Passenger Flow Forecasting by Integrating Passenger Flow Relationship and Spatiotemporal Similarity

Railway passenger flow forecasting can help to develop sensible railway schedules,make full use of railway resources,and meet the travel demand of passengers.The structure of passenger flow in railway networks and the spatiotemporal relationship of passenger flow among stations are two distinctive features of railway passenger flow.Most of the previous studies used only a single feature for prediction and lacked correlations,resulting in suboptimal performance.To address the above-mentioned problem,we proposed the railway passenger flow prediction model called Flow-Similarity Attention Graph Convolutional Network(F-SAGCN).First,we constructed the passenger flow relations graph(RG)based on the Origin-Destination(OD).Second,the Passenger Flow Fluctuation Similarity(PFFS)algorithm is used to measure the similarity of passenger flow between stations,which helps construct the spatiotemporal similarity graph(SG).Then,we determine the weights of the mutual influence of different stations at different times through an attention mechanism and extract spatiotemporal features through graph convolution on the RG and SG.Finally,we fused the spatiotemporal features and the original temporal features of stations for prediction.The comparison experiments on a railway bureau’s accurate railway passenger flow data show that the proposed F-SAGCN method improved the prediction accuracy and reduced the mean absolute percentage error(MAPE)of 46 stations to 7.93%.

Flows’ Similarities between Tornadoes or Cyclones Kinematics and Motions Resulting from Weather Phenomena Coupling Geostrophic Wind with Passive Convection

Tornadoes and cyclones, as is stated in numerous literary and audiovisual works dedicated to these out of balance physical systems, are two powerful and spectacular atmospheric phenomena whose vertical and horizontal profiles of winds and temperatures are not yet well known. Indeed, data and routine observations accumulated in the World Meteorological Organization (WMO) databases, regardless of their diversity and perfection of the instruments used to achieve these data (e.g. satellites, onboard cameras, wind profilers, ultra modern calculators, etc.), offer mind-blowing performances on the extent of damage caused by these disturbances, but information provided by these ground and space based observations will never allow access to real profiles of winds associated with tornadoes and cyclones both at the ground’s surface and aloft. The works recently carried out by C. Mbane Biouele allow us to discover that winds associated with tornadoes and hurricanes result from vectors addition of troposphere’s horizontal geostrophic winds and vertical movements associated with passive convection. Unfortunately, geostrophic wind and passive convection are two familiar meteorological phenomena described with much awkwardness and monumental mistakes by all scientific books written by authors who have remained loyal to Hadley principle which states (for centuries) that hot air is lighter than cold air. It is very important to know that C. Mbane Biouele’s very recent publications demonstrate that Hadley principle is not valid in the troposphere’s regions occupied by Ferrell cells. Indeed, it is urgent for the development of meteorology to highlight with great insistence to everyone that there is a Physics principle diametrically opposed to popular Hadley one which provides thermodynamic reasons of the formation of Ferrell cells. This Principle will be named Mbane Biouele Principe and be clearly stated in this paper.

NEW SCALING METHOD FOR COMPRESSOR MAPS USING AVERAGE INFINITESIMAL STAGE

The estimation of the precise performance of existing multistage axial-flow compressors of gas turbine engines is fast becoming a great concern, as the use of gas turbine engines in the power generation and in the military industry increases, in order to reduce the analysis performance error of the traditional scaling method, a new scaling method for estimating the characteristics of multistage axial flow compressors is proposed. This novel method is based on experimental and partial data provided by engine manufacturers. Taking the effect of density-change into account, we introduce the average infinitesimal stage concept, and thereby divide the compression process into an infinite number of infinitesimal processes corresponding to infinitesimal stages. Subsequently, we adopt the corrected Reynolds analogy method for compressible flow calculation in order to ensure much better compliance with the similarity criterion, Validation checks show that the proposed method has enough precision to predict the off-design performance characteristics of multistage axial flow compressors.

Consistent Depth Maps Estimation from Binocular Stereo Video Sequence

In the paper, an approach is proposed for the problem of consistency in depth maps estimation from binocular stereo video sequence. The consistent method includes temporal consistency and spatial consistency to eliminate the flickering artifacts and smooth inaccuracy in depth recovery. So the improved global stereo matching based on graph cut and energy optimization is implemented. In temporal domain, the penalty function with coherence factor is introduced for temporal consistency, and the factor is determined by Lucas-Kanade optical flow weighted histogram similarity constraint(LKWHSC). In spatial domain, the joint bilateral truncated absolute difference(JBTAD) is proposed for segmentation smoothing. The method can smooth naturally and uniformly in low-gradient region and avoid over-smoothing as well as keep edge sharpness in high-gradient discontinuities to realize spatial consistency. The experimental results show that the algorithm can obtain better spatial and temporal consistent depth maps compared with the existing algorithms.