New method of acoustic control in choice of optimal parameters of laser transscleral cyclocoagulation in patients with open ungle pseudoexfolia-tive glaucoma

This paper presents development of an optimal PID and PD controllers for controlling the nonlinear Gantry Crane System (GCS). A new method of Binary Particle Swarm Optimization (BPSO) algorithm that uses Priority-based Fitness Scheme is developed to obtain optimal PID and PD parameters. The optimal parameters are tested on the control structure to examine system responses including trolley displacement and payload oscillation. The dynamic model of GCS is derived using Lagrange equation. Simulation is conducted within Matlab environment to verify the performance of the system in terms of settling time, steady state error and overshoot. The result not only confirmed the successes of using new method for GCS, but also shows the new method performs more efficiently compared to the continuous PSO. This proposed technique demonstrates that implementation of Priority-based Fitness Scheme in BPSO is effective and able to move the trolley as fast as possible to the desired position with low payload oscillation.

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NEW METHOD FOR CONSTRUCTION OF OPTIMAL SCALAR QUANTIZERS FOR LAPLACIAN SOURCE

International Journal of Computing ◽

10.47839/ijc.5.2.396 ◽

2014 ◽

pp. 50-54

Author(s):

Zoran Peric ◽

Jelena Nikolic ◽

Dragoljub Pokrajac

Keyword(s):

Approximation Method ◽

New Method ◽

Optimal Parameters ◽

Optimal Values ◽

Transcendental Equations ◽

Scalar Quantizers

In this paper we consider methods for computing the necessary parameters when constructing the optimal scalar quantizers for Laplacian source. We investigate two approaches to the problem of finding the sets of optimal parameters. The first approach requires solving the transcendental equations, but provides nearly optimal values of the scalar quantizers’ parameters on successive manner. The proposed approach is an approximation method that linearizes transcendental equations providing simple and fast computing of scalar quantizers’ parameters. We demonstrate that the proposed technique provides parameters values that are very close to the optimal ones.

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The new method of 1,2-epoxy-3-butanol production over titanium silicalite catalysts

Polish Journal of Chemical Technology ◽

10.2478/v10026-007-0025-8 ◽

2007 ◽

Vol 9 (2) ◽

pp. 49-52

Author(s):

Joanna Wajzberg ◽

Agnieszka Wróblewska

Keyword(s):

Hydrogen Peroxide ◽

Organic Compounds ◽

Main Product ◽

Chemical Compounds ◽

New Method ◽

Titanium Silicalite ◽

Butanol Production ◽

Optimal Parameters ◽

The Individual ◽

Mcm 41

The new method of 1,2-epoxy-3-butanol production over titanium silicalite catalysts The results of 1-butene-3-ol (1B3O) epoxidation over the titanium silicalite catalysts: TS-1, Ti-Beta, Ti-MCM-41 has been presented. The optimal parameters obtained for the individual catalyst were compared. The main functions describing the process were: the selectivity of transformation to 1,2-epoxy-3-butanol (1,2E3B) in relation to 1B3O consumed, the conversions of 1B3O and hydrogen peroxide and the selectivity of the transformation to organic compounds in relation to the H2O2 consumed. The main product of the epoxidation process was 1,2-epoksy-3-butanol, the chemical compounds having a lot of applications.

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A Novel Ensemble Model - The Random Granular Reflections

Fundamenta Informaticae ◽

10.3233/fi-2021-2020 ◽

2021 ◽

Vol 179 (2) ◽

pp. 183-203

Author(s):

Piotr Artiemjew ◽

Krzysztof Ropiak

Keyword(s):

Random Forests ◽

Learning Process ◽

Ensemble Methods ◽

Training System ◽

New Method ◽

Ensemble Model ◽

Optimal Parameters ◽

New Approach ◽

Decision Systems

One of the most popular families of techniques to boost classification are Ensemble methods. Random Forests, Bagging and Boosting are the most popular and widely used ones. This article presents a novel Ensemble Model, named Random Granular Reflections. The algorithm used in this new approach creates an ensemble of homogeneous granular decision systems. The first step of the learning process is to take the training system and cover it with random homogeneous granules (groups of objects from the same decision class that are as little indiscernible from each other as possible). Next, granular reflection is created, which is finally used in the classification process. Results obtained by our initial experiments show that this approach is promising and comparable with other tested methods. The main advantage of our new method is that it is not necessary to search for optimal parameters while looking for granular reflections in the subsequent iterations of our ensemble model.

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Adhered cantilevers: A new method to measure dispersion forces between rough surfaces at short distances

Modern Physics Letters A ◽

10.1142/s0217732320400143 ◽

2020 ◽

Vol 35 (03) ◽

pp. 2040014

Author(s):

Vitaly B. Svetovoy ◽

George Palasantzas

Keyword(s):

Crucial Role ◽

Short Distance ◽

Measurement Method ◽

Microelectromechanical Systems ◽

Rough Surfaces ◽

Adhesion Energy ◽

New Method ◽

Dispersion Forces ◽

Optimal Parameters ◽

Interacting Surfaces

Dispersion forces start to play an important role when the bodies are separated by the distances smaller than 100 nm. Such small gaps characterize modern nano- or microelectromechanical systems. Although the forces were reliably measured and compared to the theory in the range of 30–100 nm, severe problems appear at distances shorter than 30[Formula: see text]nm due to jump-to-contact instability. In this paper we propose a new measurement method, which does not suffer the short-distance instability. The method is based on the shape of an adhered cantilever that is sensitive to the forces acting near the adhered end. Two values are measured simultaneously: the dispersion pressure at minimal separation (close to contact) and the adhesion energy. Roughness of interacting surfaces plays a crucial role. We discuss possible realization of this experiment and propose the choice of optimal parameters.

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DNA Optimization Threshold Autoregressive Prediction Model and Its Application in Ice Condition Time Series

Mathematical Problems in Engineering ◽

10.1155/2012/191902 ◽

2012 ◽

Vol 2012 ◽

pp. 1-10 ◽

Cited By ~ 2

Author(s):

Xiao-Hua Yang ◽

Yu-Qi Li

Keyword(s):

Genetic Algorithm ◽

Time Series ◽

Prediction Model ◽

Threshold Value ◽

Optimization Method ◽

New Method ◽

Optimal Parameters ◽

Improved Genetic Algorithm ◽

Threshold Autoregressive

There are many parameters which are very difficult to calibrate in the threshold autoregressive prediction model for nonlinear time series. The threshold value, autoregressive coefficients, and the delay time are key parameters in the threshold autoregressive prediction model. To improve prediction precision and reduce the uncertainties in the determination of the above parameters, a new DNA (deoxyribonucleic acid) optimization threshold autoregressive prediction model (DNAOTARPM) is proposed by combining threshold autoregressive method and DNA optimization method. The above optimal parameters are selected by minimizing objective function. Real ice condition time series at Bohai are taken to validate the new method. The prediction results indicate that the new method can choose the above optimal parameters in prediction process. Compared with improved genetic algorithm threshold autoregressive prediction model (IGATARPM) and standard genetic algorithm threshold autoregressive prediction model (SGATARPM), DNAOTARPM has higher precision and faster convergence speed for predicting nonlinear ice condition time series.

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An Improved Design for PID Controller Based on Viere Theorem

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.303-306.1167 ◽

2013 ◽

Vol 303-306 ◽

pp. 1167-1170

Author(s):

Zhi Yi Xu ◽

Xiang Jun Zhang ◽

Zhen Liu

Keyword(s):

Pid Controller ◽

Closed Loop ◽

Controller Design ◽

New Method ◽

Optimal Parameters ◽

Closed Loop System ◽

Pid Controller Design ◽

Search Speed ◽

Improved Design ◽

The Stability

The paper proposes a new method based on the Viere theorem to decide the range containing the optimal parameters. The method can accelerate the parameters search speed on the computer and avoid some unnecessary job for PID controller design. It can be acted as a criterion to judge the stability of the closed loop system.

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A New Adaptive Local Linear Prediction Method and Its Application in Hydrological Time Series

Mathematical Problems in Engineering ◽

10.1155/2010/205438 ◽

2010 ◽

Vol 2010 ◽

pp. 1-15 ◽

Cited By ~ 18

Author(s):

Dunxian She ◽

Xiaohua Yang

Keyword(s):

Time Series ◽

Linear Prediction ◽

Nearest Neighbor ◽

Prediction Method ◽

Nearest Neighbors ◽

New Method ◽

Embedding Dimension ◽

Optimal Parameters ◽

Local Linear ◽

Two Parameters

The embedding dimension and the number of nearest neighbors are very important parameters in the prediction of a chaotic time series. In order to reduce the uncertainties in the determination of the forgoing two parameters, a new adaptive local linear prediction method is proposed in this study. In the new method, the embedding dimension and the number of nearest neighbors are combined as a parameter set and change adaptively in the process of prediction. The generalized degree of freedom is used to help select the optimal parameters. Real hydrological time series are taken to examine the performance of the new method. The prediction results indicate that the new method can choose the optimal parameters of embedding dimension and the nearest neighbor number adaptively in the prediction process. And the nonlinear hydrological time series perhaps could be modeled better by the new method.

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A New Method Seeking Optimal Parameters and Locations for Bearings of Rotating Machinery Systems

Volume 5: 19th Biennial Conference on Mechanical Vibration and Noise, Parts A, B, and C ◽

10.1115/detc2003/vib-48549 ◽

2003 ◽

Author(s):

Zhichu Fang ◽

Miao Wang

Keyword(s):

Objective Function ◽

Rotating Machinery ◽

The Other ◽

New Method ◽

System Stability ◽

Control Technique ◽

Modal Control ◽

Optimal Parameters ◽

Control Forces ◽

Modal Space

A new method to optimize oil-film bearing parameters and choose the best bearing locations was presented here for rotor-bearing systems. Through applying the independent modal space control technique, optimized modal control forces and bearing forces guaranteeing system stability were deduced. The objective function minimizing the square difference between real bearing forces and optimized bearing forces was employed to optimize the bearing parameters. And then the other objective function was established to seek the best bearing locations among several possible choices. An interesting numerical example proved that the proposed approach is correct and efficient.

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