15,113 Hits in 6.9 sec

Controlling the weights of simulation particles: adaptive particle management using k-d trees

Jannis Teunissen, Ute Ebert
2014 Journal of Computational Physics  
With a k-d tree, close neighbors can be searched for efficiently, and independently of the mesh used in the simulation.  ...  Pairwise merging reduces the number of particles by combining two particles into one. To find particles that are 'close' to each other, we use a k-d tree data structure.  ...  Adaptive particle management and k-d trees As stated in the introduction, it is typically impossible to simulate all the physical particles in a system individually.  ... 
doi:10.1016/ fatcat:3ftwdhvyvnaevbikclcaxswrvm

Particle-In-Cell Simulation of Field-Reversed Configuration with Adaptive Particle Management

Kento NISHIDA, Xuehan GUO, Ritoku HORIUCHI, Yasushi ONO
2018 Plasma and Fusion Research  
Adaptive Particle Management (APM) method originally developped by Assous is improved for cylindrical 2-dimensional Particle-In-Cell code with 2nd-order shape function.  ...  In order to minimize the deformation of velocity distribution function, phase-space resampling of refinement particles was introduced.  ...  Teunissen et al. improved Lapenta's method by choosing 2 coalescence particles close enough in phase-space using K-d trees [5] .  ... 
doi:10.1585/pfr.13.3401060 fatcat:3aalhtn3hnbwtd2poumvo3ii74

Wireless Sensor Network Congestion Control Based on Standard Particle Swarm Optimization and Single Neuron PID

Xiaoping Yang, Xueying Chen, Riting Xia, Zhihong Qian
2018 Sensors  
Then, the self-learning and self-organizing ability of neurons was used to achieve online adjustment of weights to adjust the proportion, integral and differential parameters of the PID controller.  ...  Firstly, PID control theory was applied to the queue management of wireless sensor nodes.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s18041265 pmid:29671822 pmcid:PMC5948835 fatcat:majxx3n4fnftnh3tanunombhjm

Optimization of Decision Tree for Classification Using a Particle Swarm

Yun-Ju Cho, Hye-Seon Lee, Chi-Hyuck Jun
2011 Industrial Engineering & Management Systems  
This paper proposes a procedure of optimally determining thresholds of the chosen variables for a decision tree using an adaptive particle swarm optimization (APSO).  ...  The proposed algorithm consists of two phases. First, we construct a decision tree and choose the relevant variables.  ...  ACKNOWLEDGMENT This research was supported with Basic Science Research Program through the National Research Foundation of Korea (NRF) from the Ministry of Education, Science and Technology (MEST) (Project  ... 
doi:10.7232/iems.2011.10.4.272 fatcat:4b3jdszgobenzidnwqztxfh4x4

GPU-Assisted High Quality Particle Rendering

Deukhyun Cha, Sungjin Son, Insung Ihm
2009 Computer graphics forum (Print)  
To fully harness its massively parallel computing power, we transform input particles into a volumetric density field using a GPU-assisted, adaptive density estimation technique that iteratively adapts  ...  It is demonstrated that high quality volume renderings can be easily produced from large particle datasets in time frames of a few seconds to less than a minute.  ...  Recall that our scheme controls the overall accuracy of density estimation using the target particle number, N * .  ... 
doi:10.1111/j.1467-8659.2009.01502.x fatcat:6kaychggcvhhriiw3yeszrfelu

Flow simulations using particles

Petros Koumoutsakos, Georges-Henri Cottet, Diego Rossinelli
2008 ACM SIGGRAPH 2008 classes on - SIGGRAPH '08  
Using these bases the function q(x) is expressed as q(x) = kK 0 c 0 k ϕ 0 k (x) + L−1 l=0 kK l 2 d −1 µ=1 d l,µ k ψ l,µ k (x) . (50) The scaling coefficients c l k and detail coefficients d l,µ k can  ...  In that case, particles weights are written using (10) .  ... 
doi:10.1145/1401132.1401166 dblp:conf/siggraph/KoumoutsakosCR08 fatcat:fb6gcmerdnfa5alyj2m3iux35y

Improving Tree-Based Classification Rules Using a Particle Swarm Optimization [chapter]

Chi-Hyuck Jun, Yun-Ju Cho, Hyeseon Lee
2013 IFIP Advances in Information and Communication Technology  
This paper proposes a procedure of optimally determining the splitting variables and their thresholds for a decision tree using an adaptive particle swarm optimization.  ...  The proposed method consists of three phases -tree construction, threshold optimization and rule simplification. To validate the proposed algorithm, several artificial and real datasets are used.  ...  Then, the number of variables to be considered in the proposed method is  = = K k k J D 1 (5) Also, the total number of cells to be partitioned in the adaptive PSO is J 1 J 1 … J K 1 .  ... 
doi:10.1007/978-3-642-40361-3_2 fatcat:7lo7mzou7jhpxjikw44pi26ffy

Two particle-in-grid realisations on spacetrees

T. Weinzierl, B. Verleye, P. Henri, D. Roose
2016 Parallel Computing  
The present paper studies two particle management strategies for dynamically adaptive Cartesian grids at hands of a particle-in-cell code.  ...  We show that the merger of an analysed tree grammar with PIDT allows us to predict particle movements among several levels and to skip parts of this global communication a priori.  ...  This work also made use of the facilities of N8 HPC provided and funded by the N8 consortium and EPSRC (Grant No. N8HPC DUR TW PEANO).  ... 
doi:10.1016/j.parco.2015.12.007 fatcat:6nv33jtfxzcmtodz454n3vm6rq

A portable parallel particle program

Michael S. Warren, John K. Salmon
1995 Computer Physics Communications  
We describe our implementation of the parallel hashed oct-tree (HOT) code, and in particular its application to neighbor finding in a smoothed particle hydrodynamics (SPH) code.  ...  Performance of the program on a variety of problems (including gravity, SPH, vortex method and panel method) is measured on several parallel and sequential machines.  ...  This research was performed in part using the Intel Touchstone Delta System and the Intel Paragon operated by Caltech on behalf of the Concurrent Supercomputing Consortium.  ... 
doi:10.1016/0010-4655(94)00177-4 fatcat:c4z7vfd4obalnnm5vgmogeiaum

Multi-objective Particle Swarm Optimisation for Cargo Packaging in Large Containers [chapter]

Vinod Chandra S S, S. Anand Hareendran, Saju Sankar S
2020 Lecture Notes in Computer Science  
The way in which an optimal allocation of packages in different containers are done using a software controlled method.  ...  There are multiple factors that will affect this allocation -size, shape, weight of the cargo packets and the container.  ...  We thank to Girish Chandran, CEO of Kefi Tech Solutions, Technopark, Thiruvananthapuram for the help and test assistance that he had offered even between his busy schedule for data analysis and knowledge  ... 
doi:10.1007/978-3-030-53956-6_37 fatcat:kjbzy32ourfdxdoockamd24kpa

Optimization techniques for laser-based 3D particle filter SLAM

Jochen Welle, Dirk Schulz, Thomas Bachran, Armin B Cremers
2010 2010 IEEE International Conference on Robotics and Automation  
To gain control of the high memory requirements for the particles' 3D map representations, we introduce a memory efficient search structure and adapt a technique to efficiently organize and share maps  ...  In contrast to these approaches, we propose to use a particle filter transferring the concept of the 2D Rao-Blackwellized particle filter SLAM to 3D.  ...  A = ANN, K = KDTREE2, D = DELTAOCTREE, D2 WITH TWO THREADS Scn.  ... 
doi:10.1109/robot.2010.5509992 dblp:conf/icra/WelleSBC10 fatcat:4rzdcl7yn5e5tngasec25pwf7e

Particle Methods For Stochastic Optimal Control Problems [article]

Pierre Carpentier, Guy Cohen, Anes Dallagi
2009 arXiv   pre-print
To tackle the difficulties faced by both stochastic dynamic programming and scenario tree methods, we present some variational approach for numerical solution of stochastic optimal control problems.  ...  An adaptative mesh discretization method will be used to propose a tractable solution algorithm. An application to a hydro-electric dam production management problem will be presented.  ...  The optimal solution consists of state and control particles at each node of the tree.  ... 
arXiv:0907.4663v1 fatcat:sfvm6je4ifbapfwuykqc2gvacm

OpenFPM: A scalable open framework for particle and particle-mesh codes on parallel computers

Pietro Incardona, Antonio Leo, Yaroslav Zaluzhnyi, Rajesh Ramaswamy, Ivo F. Sbalzarini
2019 Computer Physics Communications  
As its main innovation, OpenFPM makes use of C++ Template Meta Programming in order to enable simulations in arbitrary-dimensional spaces, distribution of arbitrary user-defined C++ objects, and compile-time  ...  Additional comments including restrictions and unusual features: OpenFPM is a software library based on which users can implement their simulation codes at a fraction of the development cost.  ...  Acknowledgments We thank all members of the MOSAIC Group for the many fruitful discussions.  ... 
doi:10.1016/j.cpc.2019.03.007 fatcat:c54vzuy5pvbcvmt4zr2rjqlhka

WHIZARD—simulating multi-particle processes at LHC and ILC

Wolfgang Kilian, Thorsten Ohl, Jürgen Reuter
2011 European Physical Journal C: Particles and Fields  
The program automatically computes complete tree-level matrix elements, integrates them over phase space, evaluates distributions of observables, and generates unweighted event samples that can be used  ...  There is no principal limit on the process complexity; using current hardware, the program has successfully been applied to hard scattering processes with up to eight particles in the final state.  ...  There are two options: weighted and unweighted events. The effort for unweighting the Monte-Carlo events grows with the number of external particles, but is well under control.  ... 
doi:10.1140/epjc/s10052-011-1742-y fatcat:msnsqfdhxrd5djkhlalmgfmrsq

Strategy creation, decomposition and distribution in particle navigation

Ulaş Beldek, Kemal Leblebicioğlu
2007 Information Sciences  
In this study, genetic programming has been used to evolve rule-based hierarchical structures to move the particles in a grid region to accomplish navigation tasks.  ...  Strategy planning is crucial to control a group to achieve a number of tasks in a closed area full of obstacles.  ...  This is as expected since all the particles are controlled by a different tree structure and this increases the adaptability of the particles to various environments.  ... 
doi:10.1016/j.ins.2006.07.008 fatcat:h2m3me5wz5bflkecz24qofveti
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