optimization parameters improved

optimization parameters improved

Optimization of Acquisition and Data-Processing Parameters . - NCBIJ Proteome Res. 2017 Feb 3;16(2):738-747. doi: 10.1021/acs.jproteome.6b00767. Epub 2017 Jan 3. Optimization of Acquisition and Data-Processing Parameters for Improved Proteomic Quantification by Sequential Window Acquisition of All Theoretical Fragment Ion Mass Spectrometry. Li S(1), Cao Q(2), Xiao W(3), Guo.optimization parameters improved,Optimization of Acquisition and Data-Processing Parameters for .Dec 20, 2016 . Fine tuning these interdependent parameters can further improve the throughput and accuracy of SWATH quantification compared to the original setting adopted in most SWATH proteomic studies. Furthermore, we compared the effectiveness of two widely used peak extraction software PeakView and.

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optimization parameters improved,

Parameters optimization of classifier and feature selection based on .

Parameters optimization of classifier and feature selection based on improved artificial bee colony algorithm. Abstract: The feature subset selection, along with the parameters of classifier significantly influences the classification accuracy. In order to ensure the optimal classification performance, the artificial bee colony.

An Improved Ant Lion Optimization Algorithm and Its . - MDPI

Jan 2, 2018 . Abstract: In this paper, an improved ant lion optimization (IALO) algorithm for parameter identification of hydraulic turbine governing system (HTGS) is proposed. In the proposed algorithm, the search space is explored by the ant lion optimization first, and then the domain is searched by the particle swarm.

An Improved Swarm Optimization for Parameter Estimation and .

Apr 11, 2013 . The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model.

Parameters optimization of the novel probabilistic algorithm for .

A probabilistic method for improving the spatial resolution of multispectral space images using a reference image is proposed. The developed method calculates the mathematical expectation of pixel.

Optimization of Acquisition and Data-Processing Parameters . - NCBI

J Proteome Res. 2017 Feb 3;16(2):738-747. doi: 10.1021/acs.jproteome.6b00767. Epub 2017 Jan 3. Optimization of Acquisition and Data-Processing Parameters for Improved Proteomic Quantification by Sequential Window Acquisition of All Theoretical Fragment Ion Mass Spectrometry. Li S(1), Cao Q(2), Xiao W(3), Guo.

Parameters optimization of classifier and feature selection based on .

Parameters optimization of classifier and feature selection based on improved artificial bee colony algorithm. Abstract: The feature subset selection, along with the parameters of classifier significantly influences the classification accuracy. In order to ensure the optimal classification performance, the artificial bee colony.

optimization parameters improved,

On Convergence and Parameter Selection of an Improved Particle .

Abstract: This paper proposes an improved particle swarm optimization named PSO with. Controllable Random Exploration Velocity (PSO-CREV) behaving an additional exploration behavior. Different from other improvements on PSO, the updating principle of PSO-CREV is constructed in terms of stochastic approximation.

An Improved Ant Lion Optimization Algorithm and Its . - MDPI

Jan 2, 2018 . Abstract: In this paper, an improved ant lion optimization (IALO) algorithm for parameter identification of hydraulic turbine governing system (HTGS) is proposed. In the proposed algorithm, the search space is explored by the ant lion optimization first, and then the domain is searched by the particle swarm.

An Improved Swarm Optimization for Parameter Estimation and .

Apr 11, 2013 . The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model.

Parameters optimization of the novel probabilistic algorithm for .

A probabilistic method for improving the spatial resolution of multispectral space images using a reference image is proposed. The developed method calculates the mathematical expectation of pixel.

Improved parameter optimization method for complex assembly .

Show all authors. Single Sentence Summary: This paper improves the process parameter optimization method for complex robotic assembly process in robotic manufacturing showing that the proposed method is very promising in reducing the cycle time in assembly processes. Abstract:.

A Parameter Estimation Method for Nonlinear Systems Based on .

Nov 20, 2016 . As a novel swarm intelligence algorithm, chicken swarm optimization (CSO) has attracted much attention owing to its good global convergence and robustness. In this paper, a method based on improved boundary chicken swarm optimization (IBCSO) is proposed for parameter estimation of nonlinear.

Optimization of Machining Parameters for improved Surface . - Hal

Mar 18, 2013 . Abstract: The surface integrity plays a very important rule in this functional performance, being dependent of a large number of machining parameters. The major concern of the industry is to know which combination of machining parameters provides a better surface integrity of the machined components.

Application Of Taguchi Method For Optimization Of Process - irjes

ABSTRACT: Taguchi Method is a statistical approach to optimize the process parameters and improve the quality of components that are manufactured. The objective of this study is to illustrate the procedure adopted in using Taguchi Method to a lathe facing operation. The orthogonal array, signal-to-noise ratio, and the.

An optimal autonomous microgrid cluster based on distributed .

An optimal autonomous microgrid cluster based on distributed generation droop parameter optimization and renewable energy sources using an improved grey wolf optimizer.

Physico-Chemical Condition Optimization during Biosynthesis lead .

Jun 8, 2016 . Each physical and biological parameter plays a different role while governing the rules for dimension and geometry of nanoparticles. Cell free extract being source of reducing and stabilizing agent can affect the nucleation and growth of nanoparticles. High concentration of cell free extract can enhance.

Parameter estimation for chaotic systems based on improved .

Title: Parameter estimation for chaotic systems based on improved boundary chicken swarm optimization. Authors: Chen, Shaolong; Yan, Renhuan. Affiliation: AA(Jinan Univ. (China)), AB(Jinan Univ. (China)). Publication: Proceedings of the SPIE, Volume 10157, id. 101571K 6 pp. (2016). Publication Date: 10/2016. Origin:

Optimization of Wet Multi-disk Clutch Based on Improved Genetic .

Abstract—For the wet multi-disk clutch plate parameters optimization process of multi-objective, multi-parameter and multi-constraint features, an optimization method based on improved genetic algorithm was put forward. The combination coefficient was applied to the genetic algorithm to improve the evolution efficienc; As.

SVM Parameter Optimization using Grid Search and Genetic .

Support Vector Machine (SVM) has been proven to perform much better when dealing with high dimensional datasets and numerical features. Although SVM works well with default value, the performance of SVM can be improved significantly using parameter optimization. We applied two methods which are Grid Search.

Parameter optimization of improved fuzzy c-means clustering .

Mar 1, 2010 . A traditional approach to segmentation of magnetic resonance (MR) images is the fuzzy c-means (FCM) clustering algorithm. The efficacy of FCM algorithm considerably reduces in the case of noisy data. In order to improve the performance of FCM algorithm, researchers have introduced a neighborhood.

optimization parameters improved,

Parameters Optimization for Extended-range Electric . - SERSC

vehicle. The optimal operation curve control strategy was proposed for a 12 meter-long range extended electric bus. With exponential function inertia weight adjustment and local chaos substitution, an improved chaotic particle swarm optimization algorithm was applied to optimize the key parameters of energy management.

This tutorial will consist of performing additional optimization on a .

Optimization is the process by which the performance of a lens system is improved by changing the values of some of the lens data (variables) such that a measure of lens performance is improved. .. a variable during optimization (system parameters such as a surface curvature cannot have a solve applied at the.

Bayesian Optimization for Hyperparameter Tuning - Arimo

Apr 18, 2016 . Bayesian Optimization helped us find a hyperparameter configuration that is better than the one found by Random Search for a neural network on the San . so hyperparameters are tuned by adjusting parameters and taking another step of training the model – essentially an optimization procedure by itself.

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