基于链式多重插补的WOA-ELM煤与瓦斯突出预测模型

为了提高缺失数据下煤与瓦斯突出预测准确率,提出1种基于链式支持向量机多重插补(MICE_SVM)的鲸鱼优化算法(WOA)-极限学习机(ELM)预测模型,以淮南朱集矿区为例,选取5个煤与瓦斯突出影响指标作为模型特征,采用提出的MICE_SVM算法插补突出事故数据中缺失值,利用WOA优选ELM输入层权值及隐含层阈值,构建煤与瓦斯突出预测模型,将插补后数据用于WOA-ELM模型的训练与测试,并与其他模型的预测效果对比。研究结果表明:MICE_SVM插补前、后的有突出数据预测准确率分别为83.02%,90.41%,MICE_SVM显著提高了有突出预测准确率,对无突出和整体的预测准确率提高不明显;数据插补后WOA优化ELM对无突出、有突出和整体的预测准确率分别为97.94%,96.25%,96.48%,较优化前分别提高了5.79%,5.84%,5.55%,数据插补后WOA-ELM为最佳预测模型。

R*-Tree强制重插算法的改进

为了提高检索速度,在分析R-Tree及R*-Tree的基础上,提出一种强制重插算法,通过改进R*-Tree多维空间索引结构加速搜索过程。实验结果表明,相比传统算法,该算法在索引空间利用率、动态创建索引、索引检索方面具有更高性能。

利用内插/重采样器实现全数字码元同步

以采样定理和采样恢复为理论依据,分析了利用内插/重采样技术从基带采样信号中恢复数字信号最佳判决点的可行性。给出了采用该技术实现全数字码元同步的方法,并对其关键组成模块:内插/重采样器、码元误差检测、环路滤波器以及DDS等给出了详尽的设计说明和参数计算方法。该方案对软件和硬件实现有着普遍的适用性,其正确性和有效性经过了仿真验证。

马铃薯重茬种植技术

介绍了马铃薯重插种植技术,包括品种选择、整地播种、施肥、田间管理、病虫害防治、收获等内容,以期促进马铃薯优质、高产,为农户提供参考。

基于机载三维激光扫描的实时一体化摄影测量及数据处理

课题结合机载三维激光扫描实时一体化技术研究,从系统设计、航测规划、空中测量、地面监控、质量检查、DEM重采样等核心环节按“实时一体化”要求进行了详细设计和深入实践。从而为实时一体化测量提供了前中后期的配套模块,为机载三维激光扫描具体应用提供了详细的应用方案,为快速精确获取全方位、立体化地理数据提供了技术支持。实验表明,该方案能最大限度满足军事地理数据的实时获取要求。

1例改良导尿管防尿渗的护理体会

留置导尿管术是在导尿后,将尿管保留在膀胱内,引流尿液的方法。其目的之一是为尿失禁及尿潴留患者行膀胱排尿和膀胱训练。

Spatial interpolation method based on integrated RBF neural networks for estimating heavy metals in soil of a mountain region

A novel spatial interpolation method based on integrated radial basis function artificial neural networks （IRBFANNs） is proposed to provide accurate and stable predictions of heavy metals concentrations in soil at un- sampled sites in a mountain region. The IRBFANNs hybridize the advantages of the artificial neural networks and the neural networks integration approach. Three experimental projects under different sampling densities are carried out to study the performance of the proposed IRBFANNs-based interpolation method. This novel method is compared with six peer spatial interpolation methods based on the root mean square error and visual evaluation of the distribution maps of Mn elements. The experimental results show that the proposed method performs better in accuracy and stability. Moreover, the proposed method can provide more details in the spatial distribution maps than the compared interpolation methods in the cases of sparse sampling density.

Reconstruction of shock wave pressure field based on distributed test system

A new distributed test system composed of multiple test nodes was designed by adopting storage test technology to test shock waves in explosion field. The advantage of the system is the application of sensor lattice whose rise time is microsecond level, which can quickly response to transient shock wave signals. In order to reduce dynamic response error, shock tube is employed to conduct dynamic calibration on the system. The overpressure peak values of the explosion shock wave collected by sensor lattice were used to construct a shock wave pressure field with B-spline interpolation algorithm.

200 MHz带宽基带信号发生器的设计与实现

介绍了基于FPGA的基带信号发生器设计方案,主要叙述了成型滤波以及任意重采样内插比等关键技术。该基带信号发生器不仅实现了标准数字调制格式的基带信号发生,而且通过FPGA内部的并行架构设计,实现了500 MHz的高速数据速率,I/Q带宽达到200 MHz。将其应用于矢量信号发生器中,既实现了PSK、ASK、FSK、MSK、QAM等标准数字调制格式的矢量信号,又实现了400 MHz矢量调制带宽。经过测试,在4 M码元速率的情况下,QPSK和512QAM调制格式的EVM分别达到0.7%和1.0%;400 MHz带宽的矢量调制信号频响小于1dB。

多目标多约束混合流水车间插单重调度问题研究

研究了多目标多阶段混合流水车间的紧急订单插单重调度问题,综合考虑工件批量、刀具换装时间、运输能力等约束.先以最小化订单完工时间和最小化总运输时间为双目标建立静态初始订单调度模型,再针对紧急订单插单干扰,增加最小化总加工机器偏差值目标,建立三目标重调度优化模型,并分别用NSGA-Ⅱ算法与融合基于事件驱动的重调度策略和重排插单策略的NSGA-Ⅲ算法对两个模型进行求解.最后,以某实际船用管类零件生产企业为案例,先对NSGA-Ⅱ算法和NSGA-Ⅲ算法的性能进行评估,得到NSGA-Ⅱ算法更适用于解决双目标优化问题而NSGA-Ⅲ算法在解决三目标优化问题时表现更优的结论,再将所建模型与所提算法应用于该企业的十组插单案例中,所得优化率接近三分之一,验证了实用性和有效性.

Nuclear magnetic resonance T_2 spectrum:multifractal characteristics and pore structure evaluation

Pore structure characteristics are important to oil and gas exploration in complex low-permeability reservoirs. Using multifractal theory and nuclear magnetic resonance （NMR）, we studied the pore structure of low-permeability sandstone rocks from the 4th Member （Es4） of the Shahejie Formation in the south slope of the Dongying Sag. We used the existing pore structure data from petrophysics, core slices, and mercury injection tests to classify the pore structure into three categories and five subcategories. Then, the T2 spectra of samples with different pore structures were interpolated, and the one- and three-dimensional fractal dimensions and the multifractal spectrum were obtained. Parameters a （intensity of singularity） andf（a） （density of distribution） were extracted from the multifractal spectra. The differences in the three fractal dimensions suggest that the pore structure types correlate with a andf（a）. The results calculated based on the multifractal spectrum is consistent with that of the core slices and mercury injection. Finally, the proposed method was applied to an actual logging profile to evaluate the pore structure of low-permeability sandstone reservoirs.

A Low Resolution Image Restoration Method based on BP Neural Network

In order to investigate the restoration of low resolution images, the linear and nonlinear interpolation methods were applied for the interpolation of the com- mon information matrix obtained from a series of pictures, getting the restructuring matrix. The characteristic block with the best restoration effect was determined by analyzing the pixel difference of the common information of each image at the same position. Then the characteristic blocks and their original blocks were used to build and train neural network. Finally, images were restored by the neural network and the differences between pictures were reduced. Experimental results showed that this method could significantly improve the efficiency and precision of algorithm.

A method of reconstructing complex stratigraphic surfaces with multitype fault constraints

The construction of complex stratigraphic surfaces is widely employed in many fields, such as petroleum exploration, geological modeling, and geological structure analysis. It also serves as an important foundation for data visualization and visual analysis in these fields. The existing surface construction methods have several deficiencies and face various difficulties, such as the presence of multitype faults and roughness of resulting surfaces. In this paper, a surface modeling method that uses geometric partial differential equations （PDEs） is introduced for the construction of stratigraphic surfaces. It effectively solves the problem of surface roughness caused by the irregularity of stratigraphic data distribution. To cope with the presence of multitype complex faults, a two-way projection algorithm between three- dimensional space and a two-dimensional plane is proposed. Using this algorithm, a unified method based on geometric PDEs is developed for dealing with multitype faults. Moreover, the corresponding geometric PDE is derived, and an algorithm based on an evolutionary solution is developed. The algorithm proposed for constructing spatial surfaces with real data verifies its computational efficiency and its ability to handle irregular data distribution. In particular, it can reconstruct faulty surfaces, especially those with overthrust faults.

机载三维激光扫描的实时一体化摄影测量及数据处理

结合机载三维激光扫描实时一体化技术进行研究,从系统设计、航测规划、空中测量、地面监控、质量检查、DEM重采样等核心环节按“实时一体化”要求进行了详细设计和深入实践。从而为实时一体化测量提供了前中后期的配套模块,为机载三维激光扫描具体应用提供了详细的应用方案,为快速精确获取全方位、立体化地理数据提供了技术支持。实验表明,该方案能最大程度地满足军事地理数据的实时获取要求。

Bernoulli-based random undersampling schemes for 2D seismic data regularization

Seismic data regularization is an important preprocessing step in seismic signal processing. Traditional seismic acquisition methods follow the Shannon–Nyquist sampling theorem, whereas compressive sensing（CS） provides a fundamentally new paradigm to overcome limitations in data acquisition. Besides the sparse representation of seismic signal in some transform domain and the 1-norm reconstruction algorithm, the seismic data regularization quality of CS-based techniques strongly depends on random undersampling schemes. For 2D seismic data, discrete uniform-based methods have been investigated, where some seismic traces are randomly sampled with an equal probability. However, in theory and practice, some seismic traces with different probability are required to be sampled for satisfying the assumptions in CS. Therefore, designing new undersampling schemes is imperative. We propose a Bernoulli-based random undersampling scheme and its jittered version to determine the regular traces that are randomly sampled with different probability, while both schemes comply with the Bernoulli process distribution. We performed experiments using the Fourier and curvelet transforms and the spectral projected gradient reconstruction algorithm for 1-norm（SPGL1）, and ten different random seeds. According to the signal-to-noise ratio（SNR） between the original and reconstructed seismic data, the detailed experimental results from 2D numerical and physical simulation data show that the proposed novel schemes perform overall better than the discrete uniform schemes.

A New method for selecting multi-scale road network objects

Aimed at solving the problems of road network object selection at any unknown scale, the existing methods on object selection are integrated and extended in this paper, and a new object interpolation method is proposed, which reflects the inheritable and transferable characteristics of related information among multi-scale representation objects, and takes the attribute effects into account. Then the basic idea, the overall framework and the technical flow of the interpolation are put forward, at the samet：me synthetical weight function of the interpolation method is defined and described. The method and technical strategies of object selection are extended, and the key problems are solved, including the dejign of the objective quantitative and structural selections based on the weight values, the interpolation experiment strategies and technical flows, the result of the test shows that the object interpolation method not only inherits the objects at smaller scales, but also takes the attribute effect into account when deriving objects from larger scales according to the road importance, which is a guarantee to objective selection of the road objects at middle scales.

Key technologies for the novel distributed numerical control integrated system

A novel distributed numerical control (DNC) integrated system based on plug-in software technology is proposed. It connects new or old numerical control (NC) machine tools which have inhomogeneous numerical control systems with CAD/CAM system by CANbus network. A DNC computer is able to control 15 sets of NC machine tools reliably at the same time. The novel DNC system increases the efficiency of machine tools and improve the production management level by realizing non-paper production, agile manufacturing, networked manufacturing and so on in the near future. Key technologies to construct the novel DNC integrated system include the integration of inhomogeneous numerical control systems, NC program restart, and algorithm for communication competition. Such system has demonstrated successful applications in some corporations that have acquired good economic benefits and social effects.

3D Medical Image Interpolation Based on Parametric Cubic Convolution

In the process of display, manipulation and analysis of biomedical image data, they usually need to be converted to data of isotropic discretization through the process of interpolation, while the cubic convolution interpolation is widely used due to its good tradeoff between computational cost and accuracy. In this paper, we present a whole concept for the 3D medical image interpolation based on cubic convolution, and the six methods, with the different sharp control parameter,which are formulated in details. Furthermore, we also give an objective comparison for these methods using data sets with the different slice spacing. Each slice in these data sets is estimated by each interpolation method and compared with the original slice using three measures: mean-squared difference, number of sites of disagreement, and largest difference. According to the experimental results, we present a recommendation for 3D medical images under the different situations in the end.

Storage and Density of Soil Organic Carbon in Urban Topsoil of Hilly Cities:A Case Study of Chongqing Municipality of China

Rapid urbanization results in the conversion of natural soil to urban soil,and consequently,the storage and density of the soil carbon pools change.Taking Chongqing Municipality of China as a study case,this investigation attempts to better understand soil carbon pools in hilly cities.First,the vegetated areas in the study area were derived from QuickBird images.Then,topsoil data from 220 soil samples(0-20 cm) in the vegetated areas were collected and their soil organic carbon(SOC) densities were analyzed.Using the Kriging interpolation method,the spatial pattern of SOC was estimated.The results show that the SOC density exhibited high spatial variability in the urban topsoil of Chongqing.First,the SOC density in topsoil decreased according to slope in the order 2°-6° < 25°-90° < 0°-2° < 6°-15° < 15°-25°.Second,the newly developed areas during 2001-2010 had a lower SOC density than the areas built before 1988.Third,urban parks and gardens had a higher SOC density in topsoil,residential green land followed,and scattered street green land ranked last.For hilly cities,the variability of terrain affects the distribution of SOC.The Kriging results indicate that Kriging method combining slope with SOC density produced a high level of accuracy.The Kriging results show that the SOC density to the north of the Jialing River was higher than the south.The vegetated areas were estimated to amount to 73.5 km2 across the study area with an SOC storage of 0.192 Tg and an average density of 2.61 kg/m2.

Downhole microseismic data reconstruction and imaging based on combination of spline interpolation and curveletsparse constrained interpolation

When cause of the aliasing lack probl using borehole sensors and microseimic events to image, spatial aliasing often occurred be- of sensors underground and the distance between the sensors which were too large. To solve em, data reconstruction is often needed. Curvelet transform sparsity constrained inversion was widely used in the seismic data reconstruction field for its anisotropic, muhiscale and local basis. However, for the downhole ease, because the number of sampling point is mueh larger than the number of the sensors, the advantage of the cnrvelet basis can＇t perform very well. To mitigate the problem, the method that joints spline and curvlet-based compressive sensing was proposed. First, we applied the spline interpolation to the first arri- vals that to be interpolated. And the events are moved to a certain direction, such as horizontal, which can be represented by the curvelet basis sparsely. Under the spasity condition, curvelet-based compressive sensing was applied for the data, and directional filter was also used to mute the near vertical noises. After that, the events were shifted to the spline line to finish the interpolation workflow. The method was applied to a synthetic mod- el, and better result was presented than using curvelet transform interpolation directly. We applied the method to a real dataset, a mieroseismic downhole observation field data in Nanyang, using Kirchhoff migration method to image the microseimic event. Compared with the origin data, artifacts were suppressed on a certain degree.