Block and parallel modelling of broad domain nonlinear continuous mapping based on NN

The necessity of the use of the block and parallel modeling of the nonlinear continuous mappings with NN is firstly expounded quantitatively. Then, a practical approach for the block and parallel modeling of the nonlinear continuous mappings with NN is proposed. Finally, an example indicating that the method raised in this paper can be realized by suitable existed software is given. The results of the experiment of the model discussed on the 3-D Mexican straw hat indicate that the block and parallel modeling based on NN is more precise and faster in computation than the direct ones and it is obviously a concrete example and the development of the large-scale general model established by Tu Xuyan.

Attenuate Class Imbalance Problem for Pneumonia Diagnosis Using Ensemble Parallel Stacked Pre-Trained Models

Pneumonia is an acute lung infection that has caused many fatalitiesglobally. Radiologists often employ chest X-rays to identify pneumoniasince they are presently the most effective imaging method for this purpose.Computer-aided diagnosis of pneumonia using deep learning techniques iswidely used due to its effectiveness and performance. In the proposed method,the Synthetic Minority Oversampling Technique (SMOTE) approach is usedto eliminate the class imbalance in the X-ray dataset. To compensate forthe paucity of accessible data, pre-trained transfer learning is used, and anensemble Convolutional Neural Network (CNN) model is developed. Theensemble model consists of all possible combinations of the MobileNetv2,Visual Geometry Group (VGG16), and DenseNet169 models. MobileNetV2and DenseNet169 performed well in the Single classifier model, with anaccuracy of 94%, while the ensemble model (MobileNetV2+DenseNet169)achieved an accuracy of 96.9%. Using the data synchronous parallel modelin Distributed Tensorflow, the training process accelerated performance by98.6% and outperformed other conventional approaches.

Parallel Inference for Real-Time Machine Learning Applications

Hyperparameter tuning is a key step in developing high-performing machine learning models, but searching large hyperparameter spaces requires extensive computation using standard sequential methods. This work analyzes the performance gains from parallel versus sequential hyperparameter optimization. Using scikit-learn’s Randomized SearchCV, this project tuned a Random Forest classifier for fake news detection via randomized grid search. Setting n_jobs to -1 enabled full parallelization across CPU cores. Results show the parallel implementation achieved over 5× faster CPU times and 3× faster total run times compared to sequential tuning. However, test accuracy slightly dropped from 99.26% sequentially to 99.15% with parallelism, indicating a trade-off between evaluation efficiency and model performance. Still, the significant computational gains allow more extensive hyperparameter exploration within reasonable timeframes, outweighing the small accuracy decrease. Further analysis could better quantify this trade-off across different models, tuning techniques, tasks, and hardware.

Hierarchical Bulk Synchronous Parallel Model and Performance Optimization

Based on the framework of BSP, a Hierarchical Bulk Synchronous Parallel (HBSP) performance model is introduced in this paper to capture the per formance optimization problem for various stages in parallel program development and to accurately predict the performance of a parallel program by considering fac tors causing variance at local computation and global communication. The related methodology has been applied to several real applications and the results show that HBSP is a suitable model for optimizing parallel programs.

Influence of heterogeneity on rock strength and stiffness using discrete element method and parallel bond model

The particulate discrete element method(DEM) can be employed to capture the response of rock,provided that appropriate bonding models are used to cement the particles to each other.Simulations of laboratory tests are important to establish the extent to which those models can capture realistic rock behaviors.Hitherto the focus in such comparison studies has either been on homogeneous specimens or use of two-dimensional(2D) models.In situ rock formations are often heterogeneous,thus exploring the ability of this type of models to capture heterogeneous material behavior is important to facilitate their use in design analysis.In situ stress states are basically three-dimensional(3D),and therefore it is important to develop 3D models for this purpose.This paper revisits an earlier experimental study on heterogeneous specimens,of which the relative proportions of weaker material(siltstone) and stronger,harder material(sandstone) were varied in a controlled manner.Using a 3D DEM model with the parallel bond model,virtual heterogeneous specimens were created.The overall responses in terms of variations in strength and stiffness with different percentages of weaker material(siltstone) were shown to agree with the experimental observations.There was also a good qualitative agreement in the failure patterns observed in the experiments and the simulations,suggesting that the DEM data enabled analysis of the initiation of localizations and micro fractures in the specimens.

Compliance Modeling and Analysis of a 3-RPS Parallel Kinematic Machine Module

The compliance modeling and rigidity performance evaluation for the lower mobility parallel manipulators are still to be remained as two overwhelming challenges in the stage of conceptual design due to their geometric complexities. By using the screw theory, this paper explores the compliance modeling and eigencompliance evaluation of a newly patented 1T2R spindle head whose topological architecture is a 3-RPS parallel mechanism. The kinematic definitions and inverse position analysis are briefly addressed in the first place to provide necessary information for compliance modeling. By considering the 3-RPS parallel kinematic machine（PKM） as a typical compliant parallel device, whose three limb assemblages have bending, extending and torsional deflections, an analytical compliance model for the spindle head is established with screw theory and the analytical stiffness matrix of the platform is formulated. Based on the eigenscrew decomposition, the eigencompliance and corresponding eigenscrews are analyzed and the platform＇s compliance properties are physically interpreted as the suspension of six screw springs. The distributions of stiffness constants of the six screw springs throughout the workspace are predicted in a quick manner with a piece-by-piece calculation algorithm. The numerical simulation reveals a strong dependency of platform＇s compliance on its configuration in that they are axially symmetric due to structural features. At the last stage, the effects of some design variables such as structural, configurational and dimensional parameters on system rigidity characteristics are investigated with the purpose of providing useful information for the structural design and performance improvement of the PKM. Compared with previous efforts in compliance analysis of PKMs, the present methodology is more intuitive and universal thus can be easily applied to evaluate the overall rigidity performance of other PKMs with high efficiency.

Simulation of rock deformation and mechanical characteristics using clump parallel-bond models

To properly simulate hard rock with a high ratio of the uniaxial compressive strength to tensile strength(UCS/TS) and realistic strength-failure envelope,the rock deformation and mechanical characteristics were discussed in detail when the particle simulation method with the clump parallel-bond model(CPBM) was used to conduct a series of numerical experiments at the specimen scale.Meanwhile,the effects of the loading procedure and crack density on the mechanical behavior of a specimen,which was modeled by the particle simulation method with the CPBM,were investigated.The related numerical results have demonstrated that:1) The uniaxial compressive strength(UCS),tensile strength(TS) and elastic modulus are overestimated when the conventional loading procedure is used in the particle simulation method with the CPBM; 2) The elastic modulus,strength and UCS/TS decrease,while Poisson ratio increases with the increase of the crack density in the particle simulation method with the CPBM; 3) The particle simulation method with the CPBM can be used to reproduce a high value of UCS/TS(>10),as well as a high friction angle and reasonable cohesion strength; 4) As the confining pressure increases,both the peak strength of the simulated specimen and the number of microscopic cracks increase,but the ratio of tensile cracks number to shear cracks number decreases in the particle simulation method with the CPBM; 5) Compared with the conventional parallel-bond model,the CPBM can be used to reproduce more accurate results for simulating the rock deformation and mechanical characteristics.

Dynamic Modeling and Experiment of a New Type of Parallel Servo Press Considering Gravity Counterbalance

The large capacity servo press is traditionally realized by means of redundant actuation, however there exist the over-constraint problem and interference among actuators, which increases the control difficulty and the product cost. A new type of press mechanism with parallel topology is presented to develop the mechanical servo press with high stamping capacity. The dynamic model considering gravity counterbalance is proposed based on the virtual work principle, and then the effect of counterbalance cylinder on the dynamic performance of the servo press is studied. It is found that the motor torque required to operate the press is a lot less than the others when the ratio of the counterbalance force to the gravity of ram is in the vicinity of 1.0. The stamping force of the real press prototype can reach up to 25 MN on the position of 13 mm away from the bottom dead center. The typical deep-drawing process with 1 200 mm stroke at 8 strokes per minute is proposed by means of five order polynomial. On this process condition, the driving torques are calculated based on the above dynamic model and the torque measuring test is also carried out on the prototype. It is shown that the curve trend of calculation torque is consistent to the measured result and that the average error is less than 15%. The parallel mechanism is introduced into the development of large capacity servo press to avoid the over-constraint and interference of traditional redundant actuation, and its dynamic characteristics with gravity counterbalance are presented.

Parallel Computation of Shallow-water Model on Workstations Cluster

ＰａｒａｌｌｅｌＣｏｍｐｕｔａｔｉｏｎｏｆＳｈａｌｌｏｗ－ｗａｔｅｒＭｏｄｅｌｏｎＷｏｒｋｓｔａｔｉｏｎｓＣｌｕｓｔｅｒＳｏｎｇＪｕｎｑｉａｎｇ；ＳｕｎＡｎ－ｃｌａｎｇ，；ＬｉＸｉａｏｍｅｉ（ｅｐａｒｔｍｅｎｔＯｆＣＯ，ｍｐ＇ｕｔｅｒＳｃｉｅｎｃｅ，...

Global SH-wave propagation in a 2D whole Moon model using the parallel hybrid PSM/FDM method

We present numerical modeling of SH-wave propagation for the recently proposed whole Moon model and try to improve our understanding of lunar seismic wave propagation. We use a hybrid PSM/FDM method on staggered grids to solve the wave equations and implement the calculation on a parallel PC cluster to improve the computing efficiency. Features of global SH-wave propagation are firstly discussed for a 100-km shallow and900-km deep moonquakes, respectively. Effects of frequency range and lateral variation of crust thickness are then investigated with various models. Our synthetic waveforms are finally compared with observed Apollo data to show the features of wave propagation that were produced by our model and those not reproduced by our models. Our numerical modeling show that the low-velocity upper crust plays significant role in the development of reverberating wave trains. Increasing frequency enhances the strength and duration of the reverberations.Surface multiples dominate wavefields for shallow event.Core–mantle reflections can be clearly identified for deep event at low frequency. The layered whole Moon model and the low-velocity upper crust produce the reverberating wave trains following each phases consistent with observation. However, more realistic Moon model should be considered in order to explain the strong and slow decay scattering between various phases shown on observation data.

Robustly stable model predictive control based on parallel support vector machines with linear kernel

Robustly stable multi-step-ahead model predictive control (MPC) based on parallel support vector machines (SVMs) with linear kernel was proposed. First, an analytical solution of optimal control laws of parallel SVMs based MPC was derived, and then the necessary and sufficient stability condition for MPC closed loop was given according to SVM model, and finally a method of judging the discrepancy between SVM model and the actual plant was presented, and consequently the constraint sets, which can guarantee that the stability condition is still robust for model/plant mismatch within some given bounds, were obtained by applying small-gain theorem. Simulation experiments show the proposed stability condition and robust constraint sets can provide a convenient way of adjusting controller parameters to ensure a closed-loop with larger stable margin.

The parallel 3D magnetotelluric forward modeling algorithm

3D 磁电机的工作量碲的向前当模特儿的算法那么大传统的连续算法花费一极其大计算时间。然而，向前为算法建模的 3D 能在频率域处理数据，它对平行计算很合适。与 MPI 并且基于 3D 磁电机的流动的分析的优点碲的连续前面的算法，我们建议平行计算的想法并且使用它。三个理论模型被测试，实行效率处于不同状况被比较。结果显示向前为计算建模的平行 3D 是正确的，效率极大地被改进。这个方法对大尺寸合适地球物理的计算。

Designing and optimizing a parallel neural network model for predicting the solubility of diosgenin in n-alkanols

Accurate estimation of the solubility of a chemical compound is an important issue for many industrial proce sses.To overcome the defects of some thermodynamic models and simple correlations,a parallel neural network(PNN) model was conceived and optimized to predict the solubility of diosgenin in seven n-alkanols(C_(1)-C_(7)).The linear regression analysis of the parity plots indicates that the PNN model can give more accurate descriptions of the solubility of diosgenin than the ordinary neural network(ONN) model.The comparison of the average root mean square deviation(RMSD) shows that the suggested model has a slight advantage over the thermodynamic NRTL model in terms of the calculating precision.Moreover,the PNN model can reflect the effects of the temperature and the chain length of the alcohol solvent on the solution behavior of diosgenin correctly and can estimate its solubility in the n-alkanols with more carbon atoms.

ON THE DYNAMIC MODELING AND CONTROL OF 2-DOF PLANAR PARALLEL MECHANISM WITH FLEXIBLE LINKS

The object of study is about dynamic modeling and control for a 2degree-of-freedom (DOF) planar parallel mechanism (PM) with flexible links. The kinematic anddynamic equations are established according to the characteristics of mixed rigid and flexiblestructure. By using the singular perturbation approach (SPA), the model of the mechanism can beseparated into slow and fast subsystems. Based on the feedback linearization theory and inputshaping technique, the large scale rigid motion controller and the flexible link vibrationcontroller can be designed separately to achieve fast and accurate positioning of the PM.

LARGE SIGNAL DISCRETE-TIME MODEL FOR PARALLELED BUCK CONVERTERS

As a number of switch combinations are involved in operation of multi converter system, conventional methods for obtaining discrete time large signal model of these converter systems result in a very complex solution. A simple sampled data technique for modeling distributed dc dc PWM converters system (DCS) was proposed. The resulting model is nonlinear and can be linearized for analysis and design of DCS. These models are also suitable for fast simulation of these networks. As the input and output of dc dc converters are slow varying, suitable model for DCS was obtained in terms of the finite order input/output approximation.

Solution and Application about Conversion Tensor of Motion in Dynamic Modeling of 6-HTRT Parallel Robot

Equivalent integrated finite element method is a canonical and efficient modeling method in dynamic analysis of complex mechanism. The key of establishing dynamic equations of spatial mechanism by the method is to confirm Jacobian matrix reflecting relations of all joints,nodes,and generalized coordinates,namely,relations of second-order and corresponding third-order conversion tensors. For complex motion relations of components in a parallel robot,it gives second-order and third-order conversion tensors of dynamic equations for the 6-HTRT parallel robot based on equivalent integrated finite element method. The method is suitable for the typical robots whose positions of work space and sizes of mechanism are different. The solving course of the method is simple and convenient,so the method lays the foundation of dynamic analysis for robots.

Parallel Computing of the Global Spectral Atmospheric Model on the YH－2 Supercomputer

A global spectral atmospheric model has been vectorized and multitasked on the YH-2 supercomputer. The model is used for the operational system of medium--range numerical weather prediction in National Meteorological Center(NMC), China. In this paper the vectorization algorithms of the spectral-grid transformation and multitasking schemes of the model are discussed in detail. The results show that high speed-up for tile model can be obtained.

Parallel Computing of a Climate Model on the Dawn 1000 by Domain Decomposition Method

In this paper the parallel computing of a grid-point nine-level atmospheric general circulation model on the Dawn 1000 is introduced. The model was developed by the Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences (CAS). The Dawn 1000 is a MIMD massive parallel computer made by National Research Center for Intelligent Computer (NCIC), CAS. A two-dimensional domain decomposition method is adopted to perform the parallel computing. The potential ways to increase the speed-up ratio and exploit more resources of future massively parallel supercomputation are also discussed.