Aircraft initial mass estimation using Bayesian inference method

Aircraft mass is a crucial piece of information for studies on aircraft performance, trajectory prediction, and many other topics of aircraft traffic management. However, It is a common challenge for researchers, as well as air traffic control, to access this proprietary information. Previously, several studies have proposed methods to estimate aircraft weight based on specific parts of the flight. Due to inaccurate input data or biased assumptions, this often leads to less confident or inaccurate estimations. In this paper, combined with a fuel-flow model, different aircraft initial masses are computed independently using the total energy model and reference model at first. It then adopts a Bayesian approach that uses a prior probability of aircraft mass based on empirical knowledge and computed aircraft initial masses to produce the maximum a posteriori estimation. Variation in results caused by dependent factors such as prior, thrust and wind are also studied. The method is validated using 50 test flights of a Cessna Citation II aircraft, for which measurements of the true mass were available. The validation results show a mean absolute error of 4.3% of the actual aircraft mass.     

一种自适应网格模糊交互多模型算法（英文）

This paper studies the algorithm of the adaptive grid and fuzzy interacting multiple model(AGFIMM) for maneuvering target tracking, while focusing on the problems of the fixed structure multiple model(FSMM) algorithm's cost-efficiency ratio being not high and the Markov transition probability of the interacting multiple model(IMM) algorithm being difficult to determine exactly. This algorithm realizes the adaptive model set by adaptive grid adjustment, and obtains each model matching degree in the model set by fuzzy logic inference. The simulation results show that the AGFIMM algorithm can effectively improve the accuracy and cost-efficiency ratio of the multiple model algorithm, and as a result is suitable for engineering applications.     

分布式水下多传感器多目标模糊跟踪融合方法

水下多传感器多目标跟踪系统往往是一个不同类传感器融合系统,且其目标航迹包含有不确定和模糊信息.本文首先利用模糊隶属度函数和模糊逻辑推理技术,进行分布式水下多传感器多目标航迹模糊融合关联决策,并利用有效数据处理和分层融合估计相结合的方法,以实现不同类传感器高精度融合跟踪估计.     

英语阅读中含蓄意义探析

把握好阅读中语意暗含，是读者必须掌握的较复杂的高层次阅读技能之一，从4个方面以实例阐析了如何挖掘阅读理解中语意暗含，以帮助读者全面准确地理解原文．     

Probe vehicle based real-time traffic monitoring on urban roadways

Travel time estimation and prediction on urban arterials is an important component of Active Traffic and Demand Management Systems (ATDMS). This paper aims in using the information of GPS probes to augment less dynamic but available information describing arterial travel times. The direction followed in this paper chooses a cooperative approach in travel time estimation using static information describing arterial geometry and signal timing, semi-dynamic information of historical travel time distributions per time of day, and utilizes GPS probe information to augment and improve the latter. First, arterial travel times are classified by identifying different travel time states, then link travel time distributions are approximated using mixtures of normal distributions. If prior travel time data is available, travel time distributions can be estimated empirically. Otherwise, travel time distribution can be estimated based on signal timing and arterial geometry. Real-time GPS travel time data is then used to identify the current traffic condition based on Bayes Theorem. Moreover, these GPS data can also be used to update the parameters of the travel time distributions using a Bayesian update. The iterative update process makes the posterior distributions more and more accurate. Finally, two comprehensive case studies using the NGSIM Peachtree Street dataset, and GPS data of Washington Avenue in Minneapolis, were conducted. The first case study estimated prior travel time distributions based on signal timing and arterial geometry under different traffic conditions. Travel time data were classified and corresponding distributions were updated. In addition, results from the Bayesian update and EM algorithm were compared. The second case study first tested the methodologies based on real GPS data and showed the importance of sample size. In addition, a methodology was proposed to distinguish new traffic conditions in the second case study.     

混凝土搅拌运输车液压系统主要元件选型

液压系统是混凝土搅拌运输车传递动力的主要部分。以10m3混凝土搅拌运输车为研究对象,通过逆向推理用两种方法确定搅拌罐的驱动阻力矩。根据驱动阻力矩通过减速机传动比确定液压马达的型号,根据选取的液压马达的型号确定液压泵的型号,最后确定补油泵的型号。同时改进了操纵杆面板,减小了快速切换搅拌罐转向时对液压系统的冲击,提高了主要液压元件的寿命。     

Automatic two-dimensional layout using a rule-based heuristic algorithm

 Efficient layout strategies are introduced for automatic nesting using a rule-based heuristic approach to improve the layout efficiency. Since a large portion of the complexity of the parts layout problem results from the overlapping computation, geometric redesign techniques are also suggested to reduce the complexity of the problem for a fast and reliable means of performing overlapping computation. A new heuristic sliding technique is developed to find a near-optimum layout location from all the feasible arrangements in such a manner that two or more arbitrary parts do not overlap or intersect. An identification method with a pivoting point is suggested to calculate the boundary of the overlap region in a fast computation time-frame. Resource plate clipping using virtual memory, based on a polygon clipping algorithm, is also proposed as a technique to reduce the geometric conditions of the resource plate and the overlap computation time by updating a new stock boundary of the resource plate for the layout space of the next part after each part is placed. The aim of this article is to develop a rule-based heuristic nesting system to achieve a new automatic layout on the AutoCAD system. For this implementation, some nesting examples are demonstrated. A rule-based heuristic approach can be desirable in terms of the layout efficiency and considering the computational time for nesting problems, and is proposed as a real-time layout simulation method in the industrial field. Received: October 7, 2002 / Accepted: March 27, 2003 RID="*"     

微机模糊控制(1) 第一讲 微机模糊控制的发展概况

阐明了有关模糊控制的基本概念、模糊控制器较之传统的PID调节器的主要优点,以及计算机在模糊控制中的应用。最后介绍了模糊控制的一些应用实例及其发展动向。     

Intelligent collision warning using license plate segmentation

Given the increase of vehicles in traffic, traffic accidents have become a crucial and urgent issue for some countries. Particularly, in heavy traffic conditions, rear-end collisions make up the majority of traffic accidents, which make the traffic jam worse. This article proposes a novel approach to rear-end collision warning systems using areas of license plates acquired with a single camera mounted on a car. The edges of the front car's license plate are segmented and a rectangle is sketched to calculate the area, which is used for estimating distance between the cars. Relative speed of the front car is computed using the differences of the rectangles in a specific time. Distance and relative speed are obtained from the estimated areas of the license plates and transferred to the fuzzy inference system to send a warning signal to the driver for collision prevention, in emergency cases. The experiments are greatly encouraging, indicating that number plate segmentation can be utilized to estimate the distance and fuzzy inference system can be developed to create a warning signal to the drivers.     

基于模糊推理的高速公路软基处理技术决策专家系统研究

针对高速公路软基处理技术的方案决策问题,结合人工智能原理和软基处理的知识特点,建立了基于模糊推理的高速公路软基处理技术决策专家系统推理模型,重点阐述了系统参数的确定方法,并运用实例进行了推理验证。