基于蕴涵算子族NM_p的α-三算法及约束度理论

研究了基于蕴涵算子NMp模糊推理的三I算法的约束度理论,分析了约束度的性质,给出了α-三I算法的FMP(FMT)上(下)确界的计算公式。

The algorithm of 3D multi-scale volumetric curvature and its application

To fully extract and mine the multi-scale features of reservoirs and geologic structures in time/depth and space dimensions, a new 3D multi-scale volumetric curvature （MSVC） methodology is presented in this paper. We also propose a fast algorithm for computing 3D volumetric curvature. In comparison to conventional volumetric curvature attributes, its main improvements and key algorithms introduce multi-frequency components expansion in time-frequency domain and the corresponding multi-scale adaptive differential operator in the wavenumber domain, into the volumetric curvature calculation. This methodology can simultaneously depict seismic multi-scale features in both time and space. Additionally, we use data fusion of volumetric curvatures at various scales to take full advantage of the geologic features and anomalies extracted by curvature measurements at different scales. The 3D MSVC can highlight geologic anomalies and reduce noise at the same time. Thus, it improves the interpretation efficiency of curvature attributes analysis. The 3D MSVC is applied to both land and marine 3D seismic data. The results demonstrate that it can indicate the spatial distribution of reservoirs, detect faults and fracture zones, and identify their multi-scale properties.

2D multi-scale hybrid optimization method for geophysical inversion and its application

Local and global optimization methods are widely used in geophysical inversion but each has its own advantages and disadvantages. The combination of the two methods will make it possible to overcome their weaknesses. Based on the simulated annealing genetic algorithm （SAGA） and the simplex algorithm, an efficient and robust 2-D nonlinear method for seismic travel-time inversion is presented in this paper. First we do a global search over a large range by SAGA and then do a rapid local search using the simplex method. A multi-scale tomography method is adopted in order to reduce non-uniqueness. The velocity field is divided into different spatial scales and velocities at the grid nodes are taken as unknown parameters. The model is parameterized by a bi-cubic spline function. The finite-difference method is used to solve the forward problem while the hybrid method combining multi-scale SAGA and simplex algorithms is applied to the inverse problem. The algorithm has been applied to a numerical test and a travel-time perturbation test using an anomalous low-velocity body. For a practical example, it is used in the study of upper crustal velocity structure of the A＇nyemaqen suture zone at the north-east edge of the Qinghai-Tibet Plateau. The model test and practical application both prove that the method is effective and robust.

SPEEDING-UP RE-SAMPLED ALGORITHM IN RAY CASTING VOLUME RENDERING OF MEDICAL IMAGES

Ray casting algorithm can obtain a better quality image in volume rendering, however, it exists some problems, such as powerful computing capacity and slow rendering speed. How to improve the re-sampled speed is a key to speed up the ray casting algorithm. An algorithm is introduced to reduce matrix computation by matrix transformation characteristics of re-sampling points in a two coordinate system. The projection of 3-D datasets on image plane is adopted to reduce the number of rays. Utilizing boundary box technique avoids the sampling in empty voxel. By extending the Bresenham algorithm to three dimensions, each re-sampling point is calculated. Experimental results show that a two to three-fold improvement in rendering speed using the optimized algorithm, and the similar image quality to traditional algorithm can be achieved. The optimized algorithm can produce the required quality images, thus reducing the total operations and speeding up the volume rendering.

Parallel rapid relaxation inversion of 3D magnetotelluric data

We implement a parallel algorithm with the advantage of MPI （Message Passing Interface） to speed up the rapid relaxation inversion for 3D magnetotelluric data. We test the parallel rapid relaxation algorithm with synthetic and real data. The execution efficiency of the algorithm for several different situations is also compared. The results indicate that the parallel rapid relaxation algorithm for 3D magnetotelluric inversion is effective. This parallel algorithm implemented on a common PC promotes the practical application of 3D magnetotelluric inversion and can be suitable for the other geophysical 3D modeling and inversion.

Three-dimensional forward modeling of DC resistivity using the aggregation-based algebraic multigrid method

To speed up three-dimensional （3D） DC resistivity modeling, we present a new multigrid method, the aggregation-based algebraic multigrid method （AGMG）. We first discretize the differential equation of the secondary potential field with mixed boundary conditions by using a seven-point finite-difference method to obtain a large sparse system of linear equations. Then, we introduce the theory behind the pairwise aggregation algorithms for AGMG and use the conjugate-gradient method with the V-cycle AGMG preconditioner （AGMG-CG） to solve the linear equations. We use typical geoelectrical models to test the proposed AGMG-CG method and compare the results with analytical solutions and the 3DDCXH algorithm for 3D DC modeling （3DDCXH）. In addition, we apply the AGMG-CG method to different grid sizes and geoelectrical models and compare it to different iterative methods, such as ILU-BICGSTAB, ILU-GCR, and SSOR-CG. The AGMG-CG method yields nearly linearly decreasing errors, whereas the number of iterations increases slowly with increasing grid size. The AGMG-CG method is precise and converges fast, and thus can improve the computational efficiency in forward modeling of three-dimensional DC resistivity.

Three-dimension path planning for UAV using improved A＊ algorithm in complicated threat environment

In order to improve the battle effectiveness of the unmanned aerial vehicle （UAV） under the increasingly complex threat environment, a three-dimension path planning method based on an A ＊ al- gorithm is proposed and simulated in this paper which makes the UAV satisfy requirements of different missions. At first, the digital map information is processed vdth an integrated terrain smoothing algorithm, and a safe flight surface which integrates the vehicle dynamic is built and added on the terrain, and then, models of the complicated threats are established and integrated into the digital terrain. At last, an improved A ＊ algorithm is used to plan the three-dimension path on the safe sur- face, and then smooth the path. Simulation results indicate that the approach has a good perform- ance in creating an optimal path in the three-dimension environment and the path planning algorithm is more simple, efficient and easily realized in the engineering field.

Optimization algorithm for rapid 3D gravity inversion

The practical application of 3D inversion of gravity data requires a lot of computation time and storage space.To solve this problem,we present an integrated optimization algorithm with the following components:(1)targeting high accuracy in the space domain and fast computation in the wavenumber domain,we design a fast 3D forward algorithm with high precision;and(2)taking advantage of the symmetry of the inversion matrix,the main calculation in gravity conjugate gradient inversion is decomposed into two forward calculations,thus optimizing the computational efficiency of 3D gravity inversion.We verify the calculation accuracy and efficiency of the optimization algorithm by testing various grid-number models through numerical simulation experiments.

Neural adaptive PSD decoupling controller and its application in three-phase electrode adjusting system of submerged arc furnace

Taking three-phase electrode adjusting system of submerged arc furnace as study object which has nonlinear, time-variant, multivariable and strong coupling features, a neural adaptive PSD(proportion, sum and differential) dispersive decoupling controller was developed by combining neural adaptive PSD algorithm with dispersive decoupling network. In this work, the production technology process and control difficulties of submerged arc furnace were simply introduced, the necessity of establishing a neural adaptive PSD dispersive decoupling controller was discussed, the design method and the implementation steps of the controller are expounded in detail, and the block diagram of the controlled system is presented. By comparison with experimental results of the conventional PID controller and the adaptive PSD controller, the decoupling ability, adaptive ability, self-learning ability and robustness of the neural adaptive PSD dispersive decoupling controller have been testified effectively. The controller is applicable to the three-phase electrode adjusting system of submerged arc furnace, and it will play an important role for achieving the power balance of three-phrase electrodes, saving energy and reducing consumption in the process of smelting.

New approach to develop a 3D non-isothermal computational framework for injection molding process based on level set method

The simulation of three-dimensional （3D） non-isothermal, non-Newtonian fluid filling process is an extremely difficult task and remains a challenging problem, which includes polymer melt flow with free surface coupled with transient heat transfer. This paper presents a full 3D non-isothermal two-phase flow model to predict the complex flow in melt filling process, where the Cross-WLF model is applied to characterize the rheological behav- ior of polymer melt. The governing equations are solved using finite volume method with SIMPLEC algorithm on collocated grids and the melt front is accurately captured by a high resolution level set method. A domain exten- sion technique is adopted to deal with the complex cavities, which greatly reduces the computational burden. To verify the validity of the developed 3D approach, the melts filling processes in two thin rectangular cavities （one of them with a cylindrical insert） are simulated. The predicted melt front interfaces are in good agreement with the experiment and commercial software prediction. For a case with a rather complex cavity, the dynamic filling process in a hemispherical shell is successfully simulated. All of the numerical results show that the developed numerical procedure can provide a reasonable orediction for injection molding process.

Modeling the Cysteine Rich Domain of Plant Metallothionein-like Protein

With the progress of plant genome research, more than 50 plant metallothionein_like (MT_L) genes have been found, but only several MT_L proteins have been detected and no experimental structural information for MT_L proteins has been reported so far. Since detailed knowledge of the protein tertiary structure is required to understand its biological function, a method is needed to determine the structure of these proteins. In this study, the structural data of known mammal MT was used to determine the interatomic distance constraints of the CXC and CXXC motifs and the metal_sulfur chelating cluster. Then several possible MT conformations were predicted using a distance geometry algorithm. The statistical analysis was used to select those with much lower target function values and lower conformation energies as the predicted tertiary structural models of the cysteine_rich (CR) domains of these proteins. A suitable prediction method for modeling the CR domain of the plant MT_L protein was constructed. The accurately predicted result for the known structure of an MT protein from blue crab suggests that this method is practicable. The tertiary structures of CR domains of rape MT_L protein LSC54 was then modeled with this method.

First-principles calculations of structural, electronic, elastic and thermal properties of phase M_2SiC(M=Ti,V,Cr,Zr,Nb,Mo,Hf,Ta and W)

The structural,electronic and elastic properties of the M_2SiC phases were studied,where M are 3d,4d,and 5d early transition metals.The valence electron concentration(VEC) effect of Ti,V,Cr,Zr,Nb,Mo,Hf,Ta and W on these properties was examined.The C_(44) saturates for a VEC value in surrounding of 8.5 for each serie.Hf-s,Ta-s and W-s electrons mainly contribute to the density of states at the Fermi level,and should be involved in the conduction properties.The distortion increases with increasing VEC and decreasing k_c/k_a factor except for the series M=Ti,V and Cr,where it is lower at the VEC value of 8.5(it follows a parabolic variation).The M_2SiC was characterized by a profound anisotropy for the shear planes(1010) and compressibility in the direction is higher than that along the cone except for W_2SiC,where it is lower.

Evapotranspiration Estimation Based on MODIS Products and Surface Energy Balance Algorithms for Land(SEBAL) Model in Sanjiang Plain,Northeast China

In this study,the Surface Energy Balance Algorithms for Land(SEBAL) model and Moderate Resolution Imaging Spectroradiometer(MODIS) products from Terra satellite were combined with meteorological data to estimate evapotranspiration(ET) over the Sanjiang Plain,Northeast China.Land cover/land use was classified by using a recursive partitioning and regression tree with MODIS Normalized Difference Vegetation Index(NDVI) time series data,which were reconstructed based on the Savitzky-Golay filtering approach.The MODIS product Quality Assessment Science Data Sets(QA-SDS) was analyzed and all scenes with valid data covering more than 75% of the Sanjiang Plain were selected for the SEBAL modeling.This provided 12 overpasses during 184-day growing season from May 1st to October 31st,2006.Daily ET estimated by the SEBAL model was misestimaed at the range of-11.29% to 27.57% compared with that measured by Eddy Covariance system(10.52% on average).The validation results show that seasonal ET from the SEBAL model is comparable to that from ground observation within 8.86% of deviation.Our results reveal that the time series daily ET of different land cover/use increases from vegetation on-going until June or July and then decreases as vegetation senesced.Seasonal ET is lower in dry farmland(average(Ave):491 mm) and paddy field(Ave:522 mm) and increases in wetlands to more than 586 mm.As expected,higher seasonal ET values are observed for the Xingkai Lake in the southeastern part of the Sanjiang Plain(Ave:823 mm),broadleaf forest(Ave:666 mm) and mixed wood(Ave:622 mm) in the southern/western Sanjiang Plain.The ET estimation with SEBAL using MODIS products can provide decision support for operational water management issues.

Inversion of 3D density interface with PSO-BP method

BP( Back Propagation) neural network and PSO( Particle Swarm Optimization) are two main heuristic optimization methods,and are usually used as nonlinear inversion methods in geophysics. The authors applied BP neural network and BP neural network optimized with PSO into the inversion of 3D density interface respectively,and a comparison was drawn to demonstrate the inversion results. To start with,a synthetic density interface model was created and we used the proceeding inversion methods to test their effectiveness. And then two methods were applied into the inversion of the depth of Moho interface. According to the results,it is clear to find that the application effect of PSO-BP is better than that of BP network. The BP network structures used in both synthetic and field data are consistent in order to obtain preferable inversion results. The applications in synthetic and field tests demonstrate that PSO-BP is a fast and effective method in the inversion of 3D density interface and the optimization effect is evident compared with BP neural network merely,and thus,this method has practical value.

RPL Based on Triangle Module Operator for AMI Networks

the routing protocol for low-power and lossy networks(RPL) has been used in advanced metering infrastructure(AMI)which could provide two-way communication between smart meters and city utilities.To improve the network performance of AMI networks, this paper proposed an improved algorithm of RPL based on triangle module operator(IAR-TMO). IAR-TMO proposes membership functions of the following five typical routing metrics: end-to-end delay, number of hops, expected transmission count(ETX),node remaining energy, and child node count.Moreover, IAR-TMO uses triangle module operator to fuse membership functions of these routing metrics. Then, IAR-TMO selects preferred parents(the next hop) based on the triangle module operator. Theoretical analysis and simulation results show that IAR-TMO has a great improvement when compared with two recent representative algorithms: ETXOF(ETX Objective Function) and OF-FL(Objective Function based on Fuzzy Logic), in terms of network lifetime, average end-to-end delay,etc. Consequently, the network performances of AMI networks can be improved effectively.

8-Weighted-Type Fractional Fourier Transform Based Three-Branch Transmission Method

To improve the bit error rate(BER) performance of multiple input multiple output(MIMO) systems with low complexity, a three-branch transmission scheme employing 8-weighted-type fractional Fourier transform(8-WFRFT) module is proposed. In the proposed scheme, the original signal is first decomposed into eight sub-signals and then merged into three component signals by the same carrier pattern. The three signals have mathematical constraint relations among themselves that can counteract the channel fading. They are simultaneously transmitted via three independent antennas after delay regulating. At the receiver, an inverse 8-WFRFT module is employed to obtain the estimated original signal by processing the received signal. Then, the bit error rate(BER) performance, transmitting power, transmission rate, power spectrum and computational complexity of the proposed scheme are analysed in detail. Numerical results show that the proposed scheme has a superior performance compared to STBC based three-antenna transmission scheme, in terms of BER performance.

Incremental learning of the triangular membership functions based on single-pass FCM and CHC genetic model

In order to improve the efficiency of learning the triangular membership functions( TMFs) for mining fuzzy association rule( FAR) in dynamic database,a single-pass fuzzy c means( SPFCM)algorithm is combined with the real-coded CHC genetic model to incrementally learn the TMFs. The cluster centers resulting from SPFCM are regarded as the midpoint of TMFs. The population of CHC is generated randomly according to the cluster center and constraint conditions among TMFs. Then a new population for incremental learning is composed of the excellent chromosomes stored in the first genetic process and the chromosomes generated based on the cluster center adjusted by SPFCM. The experiments on real datasets show that the number of generations converging to the solution of the proposed approach is less than that of the existing batch learning approach. The quality of TMFs generated by the approach is comparable to that of the batch learning approach. Compared with the existing incremental learning strategy,the proposed approach is superior in terms of the quality of TMFs and time cost.

Quasi-physical Algorithm for Protein Folding in an Off-Lattice Model

We study a three-dimensional off-lattice protein folding model, which involves two species of residues interacting through Lennard-Jones potentials. By incorporating an extra energy contribution into the original potential function, we replace the original constrained problem with an unconstrained minimization of a mixed potential function. As such an efficient quasi-physical algorithm for solving the protein folding problem is presented. We apply the proposed algorithm to sequences with up to 55 residues and compare the computational results with the putative lowest energy found by several of the most famous algorithms, showing the advantages of our method. The dynamic behavior of the quasi-physlcal algorithm is also discussed.

An improved Vibe algorithm for illumination mutations

The visual background extractor(Vibe)algorithm can lead to a large area of false detection in the extracted foreground target when the illumination is mutated.An improved Vibe method based on the YCbCr color space and improved three-frame difference is proposed in this paper.The algorithm detects the illumination mutation frames accurately based on the difference between the luminance components of two frames adjacent to a video frame.If there exists a foreground moving target in the previous frame of the mutated frame,three-frame difference method is utilized;otherwise,Vibe method using current frame is used to initialize background.Improved three-frame differential method based on the difference in brightness between two frames of the video changes the size of the threshold adaptively to reduce the interference of noise on the foreground extraction.Experiment results show that the improved Vibe algorithm can not only suppress the“ghost”phenomenon effectively but also improve the accuracy and completeness of target detection,as well as reduce error rate of detection when the illumination is mutated.

Optimized Triangulation Algorithm in Terrain Modeling

3D reconstruction of terrain model based on digital line graphics (DLG) is discussed. An auto-coupling triangles algo-rithm based on triangle topological relationship is put forward, and the topological data model of complicated terrain is developed. Based on this data model, automatic 3D topological reconstruction of terrain is realized.