Decomposing InSAR LOS displacement into co-seismic dislocation with a linear interpolation model: A case study of the Kunlun Mountain M S=8.1 earthquake

2006 ◽  
Vol 19 (1) ◽  
pp. 100-107 ◽  
Author(s):  
Chao Ma ◽  
Xi-jian Shan
Keyword(s):  
Linear Interpolation ◽  
Interpolation Model ◽  
Seismic Dislocation ◽  
Kunlun Mountain

Study on Lidar Data Interpolation Method Based on GA-BP

2012 ◽  
Vol 588-589 ◽  
pp. 1312-1315
Author(s):  
Yi Kun Zhang ◽  
Ming Hui Zhang ◽  
Xin Hong Hei ◽  
Deng Xin Hua ◽  
Hao Chen
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Interpolation Method ◽  
Linear Interpolation ◽  
Lidar Data ◽  
Data Interpolation ◽  
Interpolation Model ◽  
Genetic Method ◽  
Interpolation Accuracy ◽  
Linear Interpolation Method

Aiming at building a Lidar data interpolation model, this paper designs and implements a GA-BP interpolation method. The proposed method uses genetic method to optimize BP neural network, which greatly improves the calculation accuracy and convergence rate of BP neural network. Experimental results show that the proposed method has a higher interpolation accuracy compared with BP neural network as well as linear interpolation method.

Helicopter rotor blade multiple-section optimization with performance

2021 ◽  
Author(s):  
Luke Allen ◽  
Joon Lim ◽  
Robert Haehnel ◽  
Ian Dettwiller
Keyword(s):  
Rotor Blade ◽  
Degrees Of Freedom ◽  
Linear Interpolation ◽  
Blade Design ◽  
Objective Functions ◽  
Forward Flight ◽  
Optimization Framework ◽  
Multi Objective Genetic Algorithm ◽  
Helicopter Rotor Blade

This paper presents advancements in a surrogate-based, rotor blade design optimization framework for improved helicopter performance. The framework builds on previous successes by allowing multiple airfoil sections to designed simultaneously to minimize required rotor power in multiple flight conditions. Rotor power in hover and forward flight, at advance ratio 𝜇 = 0.3, are used as objective functions in a multi-objective genetic algorithm. The framework is constructed using Galaxy Simulation Builder with optimization provided through integration with Dakota. Three independent airfoil sections are morphed using ParFoil and aerodynamic coefficients for the updated airfoil shapes (i.e., lift, drag, moment) are calculated using linear interpolation from a database generated using C81Gen/ARC2D. Final rotor performance is then calculated using RCAS. Several demonstrative optimization case studies were conducted using the UH-60A main rotor. The degrees of freedom for this case are limited to the airfoil camber, camber crest position, thickness, and thickness crest position for each of the sections. The results of the three-segment case study show improvements in rotor power of 4.3% and 0.8% in forward flight and hover, respectively. This configuration also yields greater reductions in rotor power for high advance ratios, e.g., 6.0% reduction at 𝜇 = 0.35, and 8.8% reduction at 𝜇 = 0.4.

Application of monotonic adaptive kernel for optimization: A case study

2017 ◽  
Vol 232 (2) ◽  
pp. 256-264 ◽  
Author(s):  
Muhammad Abid ◽  
Masroor Hussain ◽  
Ayesha Khan ◽  
Hafiz A Wajid
Keyword(s):  
Linear Interpolation ◽  
Optimization Techniques ◽  
Interpolation Function ◽  
Target Values ◽  
Wide Range ◽  
Adaptive Kernel ◽  
Pipe Joints ◽  
Bolted Flange ◽  
Pipe Joint

Optimization is considered to be the integral part of designing a wide range of engineering solutions. Manual optimization is a hectic job to obtain desired optimized results using hit and trial method. Monotonic adaptive kernel algorithm optimizes the solution to the target stress by using linear interpolation function and checking current values on every iterative step and computing differential load. Using monotonic adaptive kernel algorithm, numerical simulations are conducted on gasketed bolted flange pipe joints to achieve required preload in the bolts as per industrial guidelines for their optimized performance. It is observed that the monotonic adaptive kernel algorithm produces more accurate and fast results conforming to the desired target values as compared to the manual and semiautomatic optimization techniques implemented for the gasketed bolted flange pipe joint.

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 The Combination Forecasting of Electricity Price Based on Price Spikes Processing: A Case Study in South Australia

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Jianzhou Wang ◽  
Ling Xiao ◽  
Jun Shi
Keyword(s):  
Electricity Market ◽  
Spatial Clustering ◽  
South Australia ◽  
Linear Interpolation ◽  
Electricity Price ◽  
Price Forecasting ◽  
Combined Model ◽  
Electricity Price Forecasting ◽  
Combination Forecasting

Electricity price forecasting holds very important position in the electricity market. Inaccurate price forecasting may cause energy waste and management chaos in the electricity market. However, electricity price forecasting has always been regarded as one of the largest challenges in the electricity market because it shows high volatility, which makes electricity price forecasting difficult. This paper proposes the use of artificial intelligence optimization combination forecasting models based on preprocessing data, called “chaos particles optimization (CPSO) weight-determined combination models.” These models allow for the weight of the combined model to take values of[-1,1]. In the proposed models, the density-based spatial clustering of applications with noise (DBSCAN) algorithm is used to identify outliers, and the outliers are replaced by a new data-produced linear interpolation function. The proposed CPSO weight-determined combination models are then used to forecast the projected future electricity price. In this case study, the electricity price data of South Australia are simulated. The results indicate that, while the weight of the combined model takes values of[-1,1], the proposed combination model can always provide adaptive, reliable, and comparatively accurate forecast results in comparison to traditional combination models.

Analysis and Research of Extrapolation Accuracy with Interpolation Model Based on Network RTK

2013 ◽  
Vol 411-414 ◽  
pp. 1732-1737
Author(s):  
Ji An Deng ◽  
Xiao Bing Cheng
Keyword(s):  
Linear Interpolation ◽  
Estimation Accuracy ◽  
Validity And Reliability ◽  
Interpolation Model ◽  
Spatial Error ◽  
Network Rtk ◽  
Interpolation Coefficient ◽  
Relationship Of ◽  
The Relationship ◽  
Better Than

In network RTK the models extrapolation accuracy of spatial error is directly related to RTK position validity and reliability. So the extrapolation accuracy of coordinate linear interpolation model and distance linear interpolation model are studied in this paper. Firstly, according to the root mean square of interpolation coefficient of model and the law of errors propagation, two models stability and the factors which affected the extrapolation accuracy are analyzed from the relationship of the models linear function. Secondly, in different areas out of net the change regularity of extrapolation error is further discussed with types of data in different length baselines. The result shows that extrapolation accuracy of the above model are related to the net shape of network RTK, the estimation precision of the comprehensive error that exists between reference stations, and the distance that rover is away from the net. The extrapolation accuracy of the coordinate linear interpolation model is better than the distance linear interpolation model. In the areas that not more than 40km to the net external it can be reached within 5cm estimation accuracy of the extrapolation comprehensive error. It is helpful to rapid high-precision position out of the network.

The Genesis and Internal Dynamics of El Salvador's People's Revolutionary Army, 1970–1976

2014 ◽  
Vol 38 (01) ◽  
pp. 102-129
Author(s):  
ALBERTO MARTÍN ÁLVAREZ ◽  
EUDALD CORTINA ORERO
Keyword(s):  
Latin America ◽  
El Salvador ◽  
Early Years ◽  
Left Wing ◽  
Internal Dynamics ◽  
Internal Coherence ◽  
The 1960S

AbstractUsing interviews with former militants and previously unpublished documents, this article traces the genesis and internal dynamics of the Ejército Revolucionario del Pueblo (People's Revolutionary Army, ERP) in El Salvador during the early years of its existence (1970–6). This period was marked by the inability of the ERP to maintain internal coherence or any consensus on revolutionary strategy, which led to a series of splits and internal fights over control of the organisation. The evidence marshalled in this case study sheds new light on the origins of the armed Salvadorean Left and thus contributes to a wider understanding of the processes of formation and internal dynamics of armed left-wing groups that emerged from the 1960s onwards in Latin America.

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