A particle algorithm for linear kinetic analysis in tokamak plasmas is developed. Linear kinetic stability of a tokamak plasma is analyzed as an initial value problem. particles are used to sample plasma elements alon...
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A particle algorithm for linear kinetic analysis in tokamak plasmas is developed. Linear kinetic stability of a tokamak plasma is analyzed as an initial value problem. particles are used to sample plasma elements along equilibrium characteristics in 4-dimensional phase space (R, z, v(parallel to), mu). Each particle is accompanied with a weight which is a function of the toroidal angle. Integrals in the phase space are evaluated through the weight function and the particle location in the 4-dimensional space. Destabilization of an n=2 toroidal Alfven eigenmode is investigated as a test of the algorithm, and convergence in number of used particles is assessed. (C) 1998 Academic Press.
Due to the lack of uniform standards for pathological cell detection, it is difficult to identify. In order to improve the accuracy of pathological cell identification, this study combines the actual situation of cell...
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Due to the lack of uniform standards for pathological cell detection, it is difficult to identify. In order to improve the accuracy of pathological cell identification, this study combines the actual situation of cell detection based on traditional particle algorithm to construct a C-V model based on level set algorithm and curve evolution theory, which realizes the effective separation of different substances inside the cell. At the same time, in order to effectively extract the characteristics of cell images, this paper uses the global research method to extract the features of the research object and adopts the improved gray level co-occurrence matrix to extract the texture features, thus effectively improving the feature extraction quality. In addition, in order to study the accuracy of the algorithm model identification in this study, this paper designs a comparative experiment for performance analysis. The research shows that the proposed algorithm model has good performance, can achieve accurate recognition and feature extraction of pathological cells, has certain practical effects, and can provide theoretical reference for subsequent related research.
When it comes to endoprosthesis pathologies, for example, implant-allergic/toxic problems, as a cause of implant failure, particle identification has an important role to play in the histopathological diagnostics of t...
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In order to ensure that the unmanned ship can be quickly controlled during its voyage on the water, the PID parameters of the control system are adjusted by intelligent way. Intelligent optimization particle algorithm...
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Hybrid or algorithm refinement (AR) schemes have focused mainly on the mean behavior of system states. However, variances in these behaviors, such as spontaneous fluctuations, are important for modeling certain phenom...
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Hybrid or algorithm refinement (AR) schemes have focused mainly on the mean behavior of system states. However, variances in these behaviors, such as spontaneous fluctuations, are important for modeling certain phenomena. This article discusses the effects of statistical fluctuations on hybrid computational methods that combine a particle algorithm with a partial differential equation solver.
In order to optimize the quality of service (QoS) and execution time of task, a new resource scheduling based on improved particle swarm optimization (IPSO) is proposed to improve the efficiency and superiority. In cl...
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In order to optimize the quality of service (QoS) and execution time of task, a new resource scheduling based on improved particle swarm optimization (IPSO) is proposed to improve the efficiency and superiority. In cloud computing, the first principle of resource scheduling is to meet the needs of users, and the goal is to optimize the resource scheduling scheme and maximize the overall efficiency. This requires that the scheduling of cloud computing resources should be flexible, real-time and efficient. In this way, the mass resources of cloud computing can effectively meet the needs of the cloud users. Field Programmable Gate Arrays (FPGA), high performance and energy efficiency in one field. Most of them would have been the particle algorithm. The current technological development is still in-depth at super-resolution image research at an unprecedentedly fast pace. In particular, systemic origin applications get a lot of attention because they have a wide range of abnormal results. The scientific resource scheduling algorithm is the key to improve the efficiency of cloud computing resources distribution and the level of cloud services. In addition, the physical model of cloud computing resource scheduling is established. The performance of the IPSO algorithm applied to cloud computing resource scheduling is analysed in the design experiment. The comparison result shows that the new algorithm improves the PSO by taking full account of the user's Qu's requirements and the load balance of the cloud environment. In conclusion, the research on cloud computing resource scheduling based on IPSO can solve the problem of resource scheduling to a certain extent.
For the complexity of the ship feature classification and sensitivity of optical sensor to weather, airspace, illumination and other marine environment, we propose a new unsupervised multi-ship image segmentation algo...
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ISBN:
(纸本)9781479905614
For the complexity of the ship feature classification and sensitivity of optical sensor to weather, airspace, illumination and other marine environment, we propose a new unsupervised multi-ship image segmentation algorithm of remote sensing platforms, including separation from the target area of the adaptive multi threshold criterion, algorithm based on multiscale Ncut hierarchical, multi-objective analysis of ship motion. Finally, through verification and analysis by experiment, comparing with other relevant segmentation methods, our method has better robustness and recognition effect.
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