综放高瓦斯矿井煤层瓦斯涌出量综合预测

为了成功预测竹林山煤矿综放高瓦斯矿井大采高工作面煤层瓦斯涌出量,以主采3号煤层为主要研究对象,针对3号煤层以往开采情况,通过布设测点测量其煤层瓦斯含量和了解相邻矿井瓦斯含量,采用分源预测法、回归法及统计法等预测方法得到了3号煤层瓦斯含量的分布规律,并绘制了3号煤层的瓦斯含量等值线图。对矿井不同生产时期的瓦斯含量进行预测,得到了生产前期、中期及后期采区的最大绝对瓦斯涌出量和最大相对瓦斯涌出量,说明了竹林山煤矿各个时期均属于高瓦斯矿井。     

A bat-neural network multi-agent system (BNNMAS) for stock price prediction: Case study of DAX stock price

Creating an intelligent system that can accurately predict stock price in a robust way has always been a subject of great interest for many investors and financial analysts. Predicting future trends of financial markets is more remarkable these days especially after the recent global financial crisis. So traders who access to a powerful engine for extracting helpful information throw raw data can meet the success. In this paper we propose a new intelligent model in a multi-agent framework called bat-neural network multi-agent system (BNNMAS) to predict stock price. The model performs in a four layer multi-agent framework to predict eight years of DAX stock price in quarterly periods. The capability of BNNMAS is evaluated by applying both on fundamental and technical DAX stock price data and comparing the outcomes with the results of other methods such as genetic algorithm neural network (GANN) and some standard models like generalized regression neural network (GRNN), etc. The model tested for predicting DAX stock price a period of time that global financial crisis was faced to economics. The results show that BNNMAS significantly performs accurate and reliable, so it can be considered as a suitable tool for predicting stock price specially in a long term periods.     

Human mobility synthesis using matrix and tensor factorizations

Human mobility prediction is of great advantage in route planning and schedule management. However, mobility data is a high-dimensional dataset in which multi-context prediction is difficult in a single model. Mobility data can usually be expressed as a home event, a work event, a shopping event and a traveling event. Previous works have only been able to learn and predict one type of mobility event and then integrate them. As the tensor model has a strong ability to describe high-dimensional information, we propose an algorithm to predict human mobility in tensors of location context data. Using the tensor decomposition method, we extract human mobility patterns with multiple expressions and then synthesize the future mobility event based on mobility patterns. The experiment is based on real-world location data and the results show that the tensor decomposition method has the highest accuracy in terms of prediction error among the three methods. The results also prove the feasibility of our multi-context prediction model.     

Stereo matching cost computation based on nonsubsampled contourlet transform

A new matching cost computation method based on nonsubsampled contourlet transform (NSCT) for stereo image matching is proposed in this paper. Firstly, stereo image is decomposed into high frequency sub-band images at different scales and along different directions by NSCT. Secondly, by utilizing coefficients in high frequency domain and grayscales in RGB color space, the computation model of weighted matching cost between two pixels is designed based on the gestalt laws. Lastly, two types of experiments are carried out with standard stereopairs in the Middlebury benchmark. One of the experiments is to confirm optimum values of NSCT scale and direction parameters, and the other is to compare proposed matching cost with nine known matching costs. Experimental results show that the optimum values of scale and direction parameters are respectively 2 and 3, and the matching accuracy of the proposed matching cost is twice higher than that of traditional NCC cost.     

基于注意力机制与文本信息的用户关系抽取

随着社交媒体的发展,用户之间的关系网络对于社交媒体的分析有很大的帮助。因此,该文主要研究用户好友关系检测。以往的关于用户好友关系抽取的研究主要基于社交媒体上的结构化信息,比如其他好友关系,用户的不同属性等。但是,很多时候用户本身并没有大量的好友信息存在,同时也不一定有很多确定的属性。因此,我们希望基于用户发表的文本信息来对用户关系进行预测。不同于以往的潜在好友推荐算法,该文提出了一种基于注意力机制以及长短时记忆网络(long short-term memory,LSTM)的好友关系预测模型,将好友之间的评论分开处理,通过分析用户之间的评论来判断是否具备一定的好友关系。该模型将好友双方信息拼接后的结果作为输入,并将注意力机制应用于LSTM的输出。实验表明,用户之间的评论对于好友关系预测确实有较大的实际意义,该文提出的模型较之于多个基准系统的效果,取得了明显的提升。在不加入任何其它非文本特征的情况下,实验结果的准确率达到了77%。     

储层泥浆侵入深度预测方法研究

泥浆侵入半径的确定尚缺乏严格的验证标准.以油水两相渗流理论和离子扩散方程为基础,结合储集层特点,研究了不同储层参数下泥浆滤液对地层的侵入特性.数值模拟侵入时间选取10 d和20 d.数值模拟结果表明,侵入半径在渗透率不变的情况下随孔隙度的增大而减小,在孔隙度不变的情况下随渗透率的增大而增大;当渗透率和孔隙度都发生变化时,泥浆侵入半径一般随孔隙度的增加呈幂函数增加.依据这种关系对测井资料约束处理,得到的泥浆侵入半径较客观地反映了地层的真实情况.     

δ－Al_2O_3纤维／Al－12Si复合材料室温拉伸强度分析

对δ－Ａｌ２Ｏ３纤维／Ａｌ－１２Ｓｉ复合材料室温拉伸强度的分析表明，在实验条件下该复合材料存在δ－Ａｌ２Ｏ３纤维的最小体积分数Ｖｍｉｎ和临界体积分数Ｖｃｒｉｔ，并求出其基体强度σ＇ｍ和室温强度σｃ－δ－Ａｌ２Ｏ３纤维体积分数Ｖｆ直线方程及纤维的临界长度ｌｃ和复合材料的剪切应力τｉ．确定复合材料的ＲＯＭ预测曲线，应首先判断σ＇ｍ是否等于未增强合金的强度σｕｍ才能得出正确的结论     

测井新技术在四川油气勘探开发中的应用

综述随着四川盆地油气勘探深入所面临的油气领域复杂和困难的技术问题，介绍应用测井新技术为四川油气开发解决了大量的技术难题，特别是在复杂缝，洞型储层的评价，井旁地质构造形态精细分析和地质，测井，地震多学科结合储层横向预测等3个方面所取得的良好应用效果。     

Effects of solidification structure on fatigue crack initiation and fatigue strength in Al−Si−Mg cast alloys

Rotating-bending uniaxial fatigue tests and micro-fatigue crack initiation tests were carried out using a permanent mold cast (PMC) and semi-solid die cast (SDC) with Al−7%Si−0.35%Mg composition in order to examine the relationship between solidification structures and fatigue behaviors. The crack length was measured using a replication method. Fatigue strength was improved in SDC, which was almost consistent with the predicted fatigue strength using the size of Si particle cluster. Resistance to fatigue crack initiation and fatigue strength were improved in SDC owing to the finer Si cluster and to higher ultimate tensile strength. Fatigue crack in PMC was preferentially initiated at pores. For SDC, the fatigue crack was initiated at the Si particle/matrix interface, and then sucessively grew along eutectic cell boundaries.     

Precision equipment for symmetrical bending— Part 1. The loading system

The design and performance of precision bending equipment for testing straight beams with constant rectangular section under a pure bending moment is described. Part 1 deals with the loading arrangements and Part 2 with the rig for measuring beam deflection. The methods for recording deflection of strain gauges applied on the beam have been described elsewhere.^1–4
The reactions to the deadweight gravity loads are taken via ball bearings. The total bending moment inaccuracy, i.e. the sum of estimated systematic errors and random errors, the latter expressed as the 2Ga confidence interval about the mean (2G_cim), is about ± 25 x. 10^-4%, for 23 tests with a steel beam with 15 mm × 75 mm cross sectional dimensions, loaded to 1-1.5 mm/m strain.
The measuring rig stands on the beam via hardened and polished spherical segment feet and uses a capacitive transducer system with less than 5nm resolution. Various application tasks are described. The total inaccuracy of the measured deflection, i.e. apart from bending moment inaccuracy, is about ± 35 times 10^4% for about 10 reproduced, not repeated, tests with the same steel beam. The deflection for such a beam is of the order of 2 to 4 mm.