Comparison of SCIPUFF Plume Prediction with Particle Filter Assimilated Prediction for Dipole Pride 26 Data

نویسندگان

  • Gabriel Terejanu
  • Yang Cheng
  • Tarunraj Singh
  • Peter D. Scott
چکیده

This paper presents the application of a particle filter for data assimilation in the context of puff-based dispersion models. Particle filters provide estimates of the higher moments, and are well suited for strongly nonlinear and/or nonGaussian models. The Gaussian puff model SCIPUFF, is used in predicting the chemical concentration field after a chemical incident. This model is highly nonlinear and evolves with variable state dimension and, after sufficient time, high dimensionality. While the particle filter formalism naturally supports variable state dimensionality high dimensionality represents a challenge in selecting an adequate number of particles, especially for the Bootstrap version. We present an implementation of the Bootstrap particle filter and compare its performance with the SCIPUFF predictions. Both the model and the Particle Filter are evaluated on the Dipole Pride 26 experimental data. Since there is no available ground truth, the data has been divided in two sets: training and testing. We show that even with a modest number of particles, the Bootstrap particle filter provides better estimates of the concentration field compared with the process model, without excessive increase in computational complexity.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

PREDICTION OF EARTHQUAKE INDUCED DISPLACEMENTS OF SLOPES USING HYBRID SUPPORT VECTOR REGRESSION WITH PARTICLE SWARM OPTIMIZATION

Displacements induced by earthquake can be very large and result in severe damage to earth and earth supported structures including embankment dams, road embankments, excavations and retaining walls. It is important, therefore, to be able to predict such displacements. In this paper, a new approach to prediction of earthquake induced displacements of slopes (EIDS) using hybrid support vector re...

متن کامل

Inverse / Forward modeling and solution ( 5 ) 7 - 19 : An enhanced particle filter for estimating neural currents from magnetoencephalographic data

We present a dynamical Bayesian method to estimate source currents from MEG data. We assume that the sources can be modeled by a small set of current dipoles whose number, position, orientation, and amplitude may vary over time. A particle filter tracks the probability densities of these parameters by a two-step procedure comprising a filtering step in which the particles best fitting the data ...

متن کامل

S3PSO: Students’ Performance Prediction Based on Particle Swarm Optimization

Nowadays, new methods are required to take advantage of the rich and extensive gold mine of data given the vast content of data particularly created by educational systems. Data mining algorithms have been used in educational systems especially e-learning systems due to the broad usage of these systems. Providing a model to predict final student results in educational course is a reason for usi...

متن کامل

Prediction of shear and Compressional Wave Velocities from petrophysical data utilizing genetic algorithms technique: A case study in Hendijan and Abuzar fields located in Persian Gulf

Shear and Compressional Wave Velocities along with other Petrophysical Logs, are considered as upmost important data for Hydrocarbon reservoirs characterization. Shear Wave Velocity (Vs) in Well Logging is commonly measured by some sort of Dipole Logging Tools, which are able to acquire Shear Waves as well as Compressional Waves such as Sonic Scanner, DSI (Dipole Shear Sonic imager) by Schlumbe...

متن کامل

Traffic Signal Prediction Using Elman Neural Network and Particle Swarm Optimization

Prediction of traffic is very crucial for its management. Because of human involvement in the generation of this phenomenon, traffic signal is normally accompanied by noise and high levels of non-stationarity. Therefore, traffic signal prediction as one of the important subjects of study has attracted researchers’ interests. In this study, a combinatorial approach is proposed for traffic signal...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • CoRR

دوره abs/1107.1545  شماره 

صفحات  -

تاریخ انتشار 2008