scholarly journals Application of Surface Spline Interpolation Method in Parameter Estimation of a PM2.5 Transport Adjoint Model

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Ning Li ◽  
Xianqing Lv ◽  
Jicai Zhang
Keyword(s):  
Initial Conditions ◽  
Interpolation Method ◽  
Spline Interpolation ◽  
Ground Level ◽  
Linear Interpolation ◽  
New Method ◽  
Asia Pacific ◽  
Adjoint Model ◽  
Surface Spline ◽  
Application Fields

A new method for the estimation of initial conditions (ICs) in a PM2.5 transport adjoint model is proposed in this paper. In this method, we construct the field of ICs by interpolating values at independent points using the surface spline interpolation. Compared to the traditionally used linear interpolation, the surface spline interpolation has an advantage for reconstructing continuous smooth surfaces. The method is verified in twin experiments, and the results indicate that this method can produce better inverted ICs and less simulation errors. In practical experiments, simulation results show good agreement with the ground-level observations during the 22nd Asia-Pacific Economic Cooperation summit period, demonstrating that the new method is effective in practical application fields.

scholarly journals Application of Surface Spline Interpolation in Inversion of Bottom Friction Coefficients

2017 ◽  
Vol 34 (9) ◽  
pp. 2021-2028 ◽  
Author(s):  
Zheng Guo ◽  
Haidong Pan ◽  
Wei Fan ◽  
Xianqing Lv
Keyword(s):  
Bohai Sea ◽  
Spline Interpolation ◽  
Linear Interpolation ◽  
Bottom Friction ◽  
New Method ◽  
Practical Application ◽  
Friction Coefficients ◽  
Tidal Model ◽  
Surface Spline ◽  
Nonlinear Distribution

AbstractA new method for the inversion of bottom friction coefficients (BFCs) in a two-dimensional tidal model is proposed in this study. In this method, the field of BFCs is constructed by interpolating values at independent points using a surface spline. The surface spline interpolation has an advantage: that the constructed surface is smoother than the surface constructed by the traditionally used linear interpolation, which has unrealistic extrema. The method is validated in twin experiments where the prescribed nonlinear distribution of BFCs are better inverted with the surface spline interpolation. In practical experiments, the BFCs are inverted and the M2 tide in the Bohai Sea is simulated by assimilating the TOPEX/Poseidon (T/P) data. The small errors between the simulation results and the observations, as well as the accurate cotidal charts, demonstrate the feasibility of the new method in practical application.

scholarly journals Seismic tomography of the Gulf of Corinth: a comparison of methods

1997 ◽  
Vol 40 (1) ◽  
Author(s):  
E. Le Meur ◽  
J. Virieux ◽  
P. Podvin
Keyword(s):  
Linear System ◽  
Travel Time ◽  
Velocity Structure ◽  
Interpolation Method ◽  
Spline Interpolation ◽  
Linear Interpolation ◽  
Regular Grid ◽  
Partial Derivatives ◽  
Simultaneous Inversion ◽  
Gulf Of Corinth

At a local scale, travel-time tomography requires a simultaneous inversion of earthquake positions and velocity structure. We applied a joint iterative inversion scheme where medium parameters and hypocenter parameters were inverted simultaneously. At each step of the inversion, rays between hypocenters and stations were traced, new partial derivatives of travel-time were estimated and scaling between parameters was performed as well. The large sparse linear system modified by the scaling was solved by the LSQR method at each iteration. We compared performances of two different forward techniques. Our first approach was a fast ray tracing based on a paraxial method to solve the two-point boundary value problem. The rays connect sources and stations in a velocity structure described by a 3D B-spline interpolation over a regular grid. The second approach is the finite-difference solution of the eikonal equation with a 3D linear interpolation over a regular grid. The partial derivatives are estimated differently depending on the interpolation method. The reconstructed images are sensitive to the spatial variation of the partial derivatives shown by synthetic examples. We aldo found that a scaling between velocity and hypocenter parameters involved in the linear system to be solved is important in recovering accurate amplitudes of anomalies. This scaling was estimated to be five through synthetic examples with the real configuration of stations and sources. We also found it necessary to scale Pand S velocities in order to recover better amplitudes of S velocity anomaly. The crustal velocity structure of a 50X50X20 km domain near Patras in the Gulf of Corinth (Greece) was recovered using microearthquake data. These data were recorded during a field experiment in 1991 where a dense network of 60 digital stations was deployed. These microearthquakes were widely distributed under the Gulf of Corinth and enabled us to perform a reliable tomography of first arrival P and S travel-times. The obtained images of this seismically active zone show a south/north asymmetry in agreement with the tectonic context. The transition to high velocity lies between 6 km and 9 km indicating a very thin crust related to the active extension regime.At a local scale, travel-time tomography requires a simultaneous inversion of earthquake positions and velocity structure. We applied a joint iterative inversion scheme where medium parameters and hypocenter parameters were inverted simultaneously. At each step of the inversion, rays between hypocenters and stations were traced, new partial derivatives of travel-time were estimated and scaling between parameters was performed as well. The large sparse linear system modified by the scaling was solved by the LSQR method at each iteration. We compared performances of two different forward techniques. Our first approach was a fast ray tracing based on a paraxial method to solve the two-point boundary value problem. The rays connect sources and stations in a velocity structure described by a 3D B-spline interpolation over a regular grid. The second approach is the finite-difference solution of the eikonal equation with a 3D linear interpolation over a regular grid. The partial derivatives are estimated differently depending on the interpolation method. The reconstructed images are sensitive to the spatial variation of the partial derivatives shown by synthetic examples. We aldo found that a scaling between velocity and hypocenter parameters involved in the linear system to be solved is important in recovering accurate amplitudes of anomalies. This scaling was estimated to be five through synthetic examples with the real configuration of stations and sources. We also found it necessary to scale Pand S velocities in order to recover better amplitudes of S velocity anomaly. The crustal velocity structure of a 50X50X20 km domain near Patras in the Gulf of Corinth (Greece) was recovered using microearthquake data. These data were recorded during a field experiment in 1991 where a dense network of 60 digital stations was deployed. These microearthquakes were widely distributed under the Gulf of Corinth and enabled us to perform a reliable tomography of first arrival P and S travel-times. The obtained images of this seismically active zone show a south/north asymmetry in agreement with the tectonic context. The transition to high velocity lies between 6 km and 9 km indicating a very thin crust related to the active extension regime.

scholarly journals Treatment of Outlier Using Interpolation Method in Malaysia Tourist Arrivals

2018 ◽  
Vol 7 (3.7) ◽  
pp. 51
Author(s):  
Maria Elena Nor ◽  
Norsoraya Azurin Wahir ◽  
G P. Khuneswari ◽  
Mohd Saifullah Rusiman
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Performance Indicator ◽  
Interpolation Method ◽  
Spline Interpolation ◽  
Forecast Accuracy ◽  
Linear Interpolation ◽  
Negative Influence ◽  
Series Data ◽  
Missing Value

The presence of outliers is an example of aberrant data that can have huge negative influence on statistical method under the assumption of normality and it affects the estimation. This paper introduces an alternative method as outlier treatment in time series which is interpolation. It compares two interpolation methods using performance indicator. Assuming outlier as a missing value in the data allows the application of the interpolation method to interpolate the missing value, thus comparing the result using the forecast accuracy. The monthly time series data from January 1998 until December 2015 of Malaysia Tourist Arrivals were used to deal with outliers. The results found that the cubic spline interpolation method gave the best result than the linear interpolation and the improved time series data indicated better performance in forecasting rather than the original time series data of Box-Jenkins model. 

Analysis of Ice Response Spectra with Nonlinear Interpolation Method

2011 ◽  
Vol 243-249 ◽  
pp. 93-96
Author(s):  
Ling Ling Jia ◽  
Hang Jing ◽  
Yang Han
Keyword(s):  
Interpolation Method ◽  
Response Spectrum ◽  
Response Spectra ◽  
Linear Interpolation ◽  
New Method ◽  
Amplification Coefficient ◽  
Acceleration Response ◽  
Nonlinear Interpolation ◽  
Linear Interpolation Method ◽  
Ice Resistance

In this paper, the successive computation formulas of ice response spectrum are derived and deduced based on the assumption of nonlinear interpolation method. And with the new way, the ice response spectrum of two true different ice temporal curves are analysized. The results indicate that the ice spectra value obtained by the new method is a litter greater than the values of the called precision method. And the error of the acceleration response spectra amplification coefficient is only 0.53%. therefore, this ice response spectra method presented by this paper can meet the request of precision. As this method is more preciser than linear interpolation method, it can be used in the design of ice resistance.

Surface spline interpolation method for thermal reconstruction with limited sensor data of non-uniform placements

2013 ◽  
Vol 19 (1) ◽  
pp. 65-71 ◽  
Author(s):  
Ruo-lin Wang ◽  
Xin Li ◽  
Wen-jiang Liu ◽  
Tao Liu ◽  
Meng-tian Rong ◽  
...  
Keyword(s):  
Interpolation Method ◽  
Spline Interpolation ◽  
Sensor Data ◽  
Surface Spline

scholarly journals DROUGHT FORECASTING BASED ON MACHINE LEARNING OF REMOTE SENSING AND LONG-RANGE FORECAST DATA

2016 ◽  
Vol XLI-B8 ◽  
pp. 157-158
Author(s):  
J. Rhee ◽  
J. Im ◽  
S. Park
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Long Range ◽  
Initial Conditions ◽  
Interpolation Method ◽  
Spline Interpolation ◽  
Standardized Precipitation Index ◽  
Learning Models ◽  
Drought Forecasting ◽  
Machine Learning Models

The reduction of drought impacts may be achieved through sustainable drought management and proactive measures against drought disaster. Accurate and timely provision of drought information is essential. In this study, drought forecasting models to provide high-resolution drought information based on drought indicators for ungauged areas were developed. The developed models predict drought indices of the 6-month Standardized Precipitation Index (SPI6) and the 6-month Standardized Precipitation Evapotranspiration Index (SPEI6). An interpolation method based on multiquadric spline interpolation method as well as three machine learning models were tested. Three machine learning models of Decision Tree, Random Forest, and Extremely Randomized Trees were tested to enhance the provision of drought initial conditions based on remote sensing data, since initial conditions is one of the most important factors for drought forecasting. Machine learning-based methods performed better than interpolation methods for both classification and regression, and the methods using climatology data outperformed the methods using long-range forecast. The model based on climatological data and the machine learning method outperformed overall.

scholarly journals DROUGHT FORECASTING BASED ON MACHINE LEARNING OF REMOTE SENSING AND LONG-RANGE FORECAST DATA

2016 ◽  
Vol XLI-B8 ◽  
pp. 157-158 ◽  
Author(s):  
J. Rhee ◽  
J. Im ◽  
S. Park
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Long Range ◽  
Initial Conditions ◽  
Interpolation Method ◽  
Spline Interpolation ◽  
Standardized Precipitation Index ◽  
Learning Models ◽  
Drought Forecasting ◽  
Machine Learning Models

The reduction of drought impacts may be achieved through sustainable drought management and proactive measures against drought disaster. Accurate and timely provision of drought information is essential. In this study, drought forecasting models to provide high-resolution drought information based on drought indicators for ungauged areas were developed. The developed models predict drought indices of the 6-month Standardized Precipitation Index (SPI6) and the 6-month Standardized Precipitation Evapotranspiration Index (SPEI6). An interpolation method based on multiquadric spline interpolation method as well as three machine learning models were tested. Three machine learning models of Decision Tree, Random Forest, and Extremely Randomized Trees were tested to enhance the provision of drought initial conditions based on remote sensing data, since initial conditions is one of the most important factors for drought forecasting. Machine learning-based methods performed better than interpolation methods for both classification and regression, and the methods using climatology data outperformed the methods using long-range forecast. The model based on climatological data and the machine learning method outperformed overall.

scholarly journals KOMPARASI METODE INTERPOLASI UNTUK SISTEM PENGENALAN SEL DARAH PUTIH

2020 ◽  
Vol 5 (1) ◽  
pp. 31-36
Author(s):  
Lina Lina ◽  
Kelly Anthony
Keyword(s):  
Blood Cell ◽  
Interpolation Method ◽  
Spline Interpolation ◽  
Cell Types ◽  
Linear Interpolation ◽  
Recognition System ◽  
Medical Field ◽  
Quadratic Spline ◽  
Human Needs ◽  
Characteristic Lines

The over time role of technology becomes very important. That is because the function of technology is to facilitate human work. Because human needs are increasingly complex, technological developments are created in such a way as to meet human needs. The experts in the medical field are currently very dependent on technology to do their jobs, in order to obtain effective and efficient results. Application system designed aims to help experts in the medical field to diagnose diseases through introduction to white blood cell types. The recognition system was developed using the Nearest Feature Line (NFL) method. In this NFL method, characteristic lines are formed using the method of linear interpolation, linear spline, quadratic spline, and cubic spline. Aside from introducing an introduction system, this paper also discusses comparisons between interpolation methods to form characteristic lines. The test was carried out using FTI Untar Pattern Recognition laboratory blood cell data. The test results show that the formation of characteristic lines using the linear interpolation method provides better recognition results compared to the spline interpolation method.

Modeling of Accurate Variable Slope Angles in Open-Pit Mine Design Using Spline Interpolation / Modelowanie Zmiennego Kąta Nachylenia Stoku W Projektowaniu Kopalni Odkrywkowych Za Pomocą Interpolacji Funkcjami Sklejającymi (Metodą Spline’Ów)

2012 ◽  
Vol 57 (4) ◽  
pp. 921-932 ◽  
Author(s):  
Masoud Soleymani Shishvan ◽  
Javad Sattarvand
Keyword(s):  
Interpolation Method ◽  
Spline Interpolation ◽  
Slope Angle ◽  
Linear Interpolation ◽  
Open Pit ◽  
Cubic Form ◽  
The Given ◽  
Numerical Case Study

Abstract In this paper a new method of modeling variable slope angles has been presented based on the spline interpolation method. Slope angle modeling and defining precedency of the blocks are the vital parts of almost any open pit optimization algorithm. Traditionally heuristic patterns such as 1:5 or 1:9 have been used to generate slope angles. Cone template based models were later employed in developing variable slope angles. They normally use a linear interpolation process for determination of slope angles between the given directions which leads to sharp and non-realistic pits. The other elliptical alternatives suffer from having limitations in defining slope angles in non-geographical directions. The method is capable to consider any number of slope angles in any desired direction as well as creating quite accurate and realistic pit shapes. Three major types of the spline interpolation including cubic, quadratic and cardinal are tested, however, the cubic form is preferred due to more realistic outcomes. Main steps of the method are described through a numerical case study.

scholarly journals KOMPARASI METODE INTERPOLASI UNTUK SISTEM PENGENALAN SEL DARAH PUTIH

2020 ◽  
Vol 5 (1) ◽  
pp. 31-36
Author(s):  
Lina Lina ◽  
Kelly Anthony
Keyword(s):  
Pattern Recognition ◽  
Blood Cell ◽  
Interpolation Method ◽  
Spline Interpolation ◽  
Linear Interpolation ◽  
Medical Field ◽  
Quadratic Spline ◽  
Human Needs ◽  
Characteristic Lines ◽  
Feature Line

In English, The over time role of technology becomes very important. That is because the function of technology is to facilitate human work. Because human needs are increasingly complex, technological developments are created in such a way as to meet human needs. The experts in the medical field are currently very dependent on technology to do their jobs, in order to obtain effective and efficient results. Application system designed aims to help experts in the medical field to diagnose diseases through introduction to white blood cell types. The recognition system was developed using the Nearest Feature Line (NFL) method. In this NFL method, characteristic lines are formed using the method of linear interpolation, linear spline, quadratic spline, and cubic spline. Aside from introducing an introduction system, this paper also discusses comparisons between interpolation methods to form characteristic lines. The test was carried out using FTI Untar Pattern Recognition laboratory blood cell data. The test results show that the formation of characteristic lines using the linear interpolation method provides better recognition results compared to the spline interpolation method. Dalam Bahasa Indonesia, Seiring berjalannya waktu peran teknologi menjadi sangat penting. Hal itu disebabkan karena fungsi dari teknologi yaitu mempermudah perkerjaan manusia. Karena kebutuhan manusia semakin kompleks, maka perkembangan teknologi diciptakan sedemikian rupa untuk memenuhi kebutuhan manusia. Para tenaga ahli dalam bidang kedokteran pun saat ini sangat bergantung pada teknologi dalam melakukan pekerjaannya, guna memperoleh hasil yang efektif dan efisien. Sistem aplikasi yang dirancang bertujuan untuk membantu ahli dalam bidang medis untuk mendiagnosis penyakit melalui pengenalan terhadap jenis sel darah putih. Sistem pengenalan yang dikembangkan menggunakan metode Nearest Feature Line (NFL). Dalam metode NFL ini, garis ciri dibentuk menggunakan metode interpolasi linier, spline linier, spline kuadratik, dan spline kubik. Selain melakukan sistem pengenalan, makalah ini juga membahas perbandingan antara metode interpolasi untuk membentuk garis ciri. Pengujian dilakukan dengan menggunakan data sel darah laboratorium Pattern Recognition FTI Untar. Hasil pengujian menunjukkan bahwa pembentukan garis ciri menggunakan metode interpolasi linier memberikan hasil pengenalan yang lebih baik dibandingkan dengan metode interpolasi spline.

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