A novel methodology is proposed to determine the error propagation of partial least-square (PIS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variab...
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A novel methodology is proposed to determine the error propagation of partial least-square (PIS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type I and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models. (C) 2017 Published by Elsevier B.V.
A detailed parametric sensitivity analysis reveals the effect on the numerically calculated profile factor of ultrasonic flow meters of various modeling parameters such as mesh refinement, boundary conditions, turbule...
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A detailed parametric sensitivity analysis reveals the effect on the numerically calculated profile factor of ultrasonic flow meters of various modeling parameters such as mesh refinement, boundary conditions, turbulence model, wall treatment, interpolation schemes and numerical integration. The flow field is solved using a commercial CFD code and the profile factor is obtained by numerical integration of the three velocity components along the acoustic path. Interesting relations of these numerical parameters concerning the inertia of the flow are observed, suggesting that the higher the Reynolds number, the more precaution is needed in the simulation of pipe flows, especially when the goal is to infer the profile factor of ultrasonic flow measurements, which are related to strict uncertainties. The main finding is that quantitative conclusions may be mistaken or distorted if a proper analysis of how sensitive the simulation results are with respect to its modeling parameters is not carried out.
Petrophysical model is mainly used to combine the matrix, fluid and pore in certain mode. Therefore, many modeling parameters are involved but the simple and effective control methods are insufficient. The matrix of m...
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Petrophysical model is mainly used to combine the matrix, fluid and pore in certain mode. Therefore, many modeling parameters are involved but the simple and effective control methods are insufficient. The matrix of model is simplified to reduce the influence of polymineral parameters on model frame. The velocity of longitudinal wave is introduced. In addition, the common petrophysical model is divided into velocity control model and modulus control model. The accurate modeling parameters can be obtained through mutual relations among different types of model parameters, thus increasing the efficiency of horizontal wave prediction. The length-width ratio of pore varies with well through the ratio classification technology at the effect of compaction to effectively increase the identification capacity of elastic parameters on fluid and lithology.
The non-linear performances of RC beam specimens under flexure are evaluated with constant % of Thermo Mechanically Treated (TMT) reinforcement in confined and unconfined conditions by pushover and cyclic loading. The...
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The non-linear performances of RC beam specimens under flexure are evaluated with constant % of Thermo Mechanically Treated (TMT) reinforcement in confined and unconfined conditions by pushover and cyclic loading. The pushover and cyclic behavior of the beam specimens is plotted in the form of load-deformation for determining the non-linear modeling parameters as per ASCE/SEI 41-06. The beam specimens under cyclic testing have shown large yield strength but low ductility as compared to pushover testing. It may be concluded that the ductility, which is synonymously used without the relevance either of monotonic or cyclic load of a component or a structure, may result to be lethal if appropriation is neglected in behavior factor in seismic design. The confining of transverse reinforcement is another significant parameter on which the post-yield force-deformation relationship and the resulting ductility of an RC component depend. (C) 2015 The Institution of Structural Engineers. Published by Elsevier Ltd. All rights reserved.
Analyzing service behavior is useful activity for monitoring and comparing cloud services. modeling behavior of a cloud service is required by various cloud providers and researchers to analyze the usage pattern of se...
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ISBN:
(纸本)9781479933587
Analyzing service behavior is useful activity for monitoring and comparing cloud services. modeling behavior of a cloud service is required by various cloud providers and researchers to analyze the usage pattern of service. This can be used to identify failure rate, success rate, and shortcomings of a service. It can also be used to formulate new business strategies and overcome the pitfalls. We are analyzing the behavior of a cloud service to determine the various parameters. These parameters are then can be used to provide trust value, in terms of strength of a cloud service. Also a provider can make use of this to identify the improvement areas for the cloud service and application.
Reinforced concrete (RC) shear walls connected by coupling beams form an efficient structural system for tall buildings to resist earthquake loads. Understanding the load-deformation characteristics of coupling beams ...
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Reinforced concrete (RC) shear walls connected by coupling beams form an efficient structural system for tall buildings to resist earthquake loads. Understanding the load-deformation characteristics of coupling beams is essential to modeling the overall system responses of coupled walls to seismic loading. Using new test data presented in a companion paper, modeling studies are performed to evaluate the effectiveness of current modeling approaches with respect to key parameters, including effective elastic stiffness, deformation capacity, and residual strength. modeling approaches commonly employed in engineering practice are investigated and are shown to reasonably capture measured force-versus-deformation behavior. The impact of the test specimen scale factor is reviewed and shown to be potentially significant on the member effective bending stiffness and deformation capacity. The modeling studies are expanded to include beam aspect ratios not considered in the test program to develop modeling parameters for use in seismic rehabilitation and performance-based seismic design.
Aiming at improving localization accuracy in Wireless Sensor Networks (WSN) based on Least Square Support Vector Regression (LSSVR), making LSSVR localization method more practicable, the mechanism of effects of the k...
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ISBN:
(纸本)9783037851555
Aiming at improving localization accuracy in Wireless Sensor Networks (WSN) based on Least Square Support Vector Regression (LSSVR), making LSSVR localization method more practicable, the mechanism of effects of the kernel function for target localization based on LSSVR is discussed based on the mathematical solution process of LSSVR localization method. A novel method of modeling parameters optimization for LSSVR model using particle swarm optimization is proposed. Construction method of fitness function for modeling parameters optimization is researched. In addition, the characteristics of particle swarm parameters optimization are analyzed. The computational complexity of parameters optimization is taken into consideration comprehensively. Experiments of target localization based on CC2430 show that localization accuracy using LSSVR method with modeling parameters optimization increased by 23%similar to 36% in compare with the maximum likelihood method(MLE) and the localization error is close to the minimum with different LSSVR modeling parameters. Experimental results show that adapting a reasonable fitness function for modeling parameters optimization using particle swarm optimization could enhance the anti-noise ability significantly and improve the LSSVR localization performance.
This work proposes a transformer structure with high -coupling, and small chip area characteristics using current silicon-based technology. The proposed device has tight coupling (k = 0.92), and minimum chip area (O.D...
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ISBN:
(纸本)9782960055160
This work proposes a transformer structure with high -coupling, and small chip area characteristics using current silicon-based technology. The proposed device has tight coupling (k = 0.92), and minimum chip area (O.D. = 140 mu m) characteristics. In order to understand this device operation in high frequency, an equivalent circuit is developed to extract the model parameters. Base on the proposed transformer in this work, this device will be helpful in designing RF integrated circuits for system-on-a-chip applications.
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