This study proposes innovative methods for determining the starting point and estimating the parameters of the LPPL model for predicting stock market bubbles. These methods address the challenges in determining the st...
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This study proposes innovative methods for determining the starting point and estimating the parameters of the LPPL model for predicting stock market bubbles. These methods address the challenges in determining the starting point of irregularly staged bubbles and the issues of multiple local optima or no solutions in previous prediction algorithms. The proposed LPPL model, incorporating innovative algorithms, is applied to the Chinese A-share market from 2018 to 2021. The starting points of structural bubbles are determined using the difference and grid search methods, and the sequential quadratic programming (sqp) algorithm is used to estimate the parameters of the LPPL model. The study measures and warns about structural bubbles in the A-share market. The results demonstrate that the LPPL model with the innovative algorithm can accurately measure staged and structural bubbles in the A-share market and provide reasonably accurate warnings of bubble bursts, which have been confirmed by the market multiple times.
The aim of this research is to provide a simple, yet realistic, model of the sinonasal tissue as a major requirement for developing more efficient endoscopic neurosurgery simulation systems. Ex-vivo indention tests we...
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The aim of this research is to provide a simple, yet realistic, model of the sinonasal tissue as a major requirement for developing more efficient endoscopic neurosurgery simulation systems. Ex-vivo indention tests were performed on the orbital floor soft tissue of four sheep specimens. The resulting force-displacement data was incorporated into an inverse finite element model to obtain the hyperelastic mechanical properties of the tissue. Material characterization was performed for polynomial, Yeoh, Mooney-Rivlin, and neo-Hookean hyperelastic models using a sequential quadratic programming algorithm. Experimental results indicated relatively large elastic deformation, up to 6 mm, during the indentation test with considerable nonlinearity in the force-displacement response. All hyperelastic models could satisfy the convergence criteria of the optimization procedure, with the highest convergence rate and close fitting accuracy associated with the Yeoh hyperelastic model. The initial guess of the material constants was found to affect the number of iterations before converging, but not the optimization results. The normalized mean square errors of fitting between the model and experimental curves were obtained as 2.39%, 4.26%, and 4.65% for three sheep samples, suggesting that the Yeoh model could adequately describe the typical hyperelastic mechanical behavior of the sino-nasal tissue for surgery simulation. (C) 2020 Sharif University of Technology. All rights reserved.
In this paper, in order to solve semismooth equations with box constraints, we present a class of smoothing sqp algorithms using the regularized-smooth techniques. The main difference of our algorithm from some relate...
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In this paper, in order to solve semismooth equations with box constraints, we present a class of smoothing sqp algorithms using the regularized-smooth techniques. The main difference of our algorithm from some related literature is that the correspondent objective function arising from the equation system is not required to be continuously differentiable. Under the appropriate conditions, we prove the global convergence theorem, in other words, any accumulation point of the iteration point sequence generated by the proposed algorithm is a KKT point of the corresponding optimization problem with box constraints. Particularly, if an accumulation point of the iteration sequence is a vertex of box constraints and additionally, its corresponding KKT multipliers satisfy strictly complementary conditions, the gradient projection of the iteration sequence finitely terminates at this vertex. Furthermore, under local error bound conditions which are weaker than BD-regular conditions, we show that the proposed algorithm converges superlinearly. Finally, the promising numerical results demonstrate that the proposed smoothing sqp algorithm is an effective method.
In present research we propose a nonlinear solving method to obtain the optimum tilt angle for solar panels. For this purpose, solar radiation on tilted panels are estimated by applying anisotropic model in Maple and ...
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ISBN:
(纸本)9783037855645
In present research we propose a nonlinear solving method to obtain the optimum tilt angle for solar panels. For this purpose, solar radiation on tilted panels are estimated by applying anisotropic model in Maple and the maximum is obtained by solving parametric nonlinear equations with Sequential Quadratic Programming (sqp) algorithm. Comparing its results with prevalent calculation proved this method faster and more efficient. The used model is validated by comparing results with measured data on a 45 degrees-tilted surface in Tehran, Iran. Results showed solar radiation on a tilted surface increases 32% by monthly adjustments, in comparison with a fixed horizontal surface.
This paper evaluates the optimum coolant temperature considering the exergy loss in a shell and tube condenser in which vapor is at its saturated temperature. First, exergy loss was formulated mathematically and then ...
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This paper evaluates the optimum coolant temperature considering the exergy loss in a shell and tube condenser in which vapor is at its saturated temperature. First, exergy loss was formulated mathematically and then presented as a function of operating temperatures and optimum coolant and steam mass flow rates. The optimization problem was defined by full condensation of vapor in a condenser and solved by a sequential quadratic programming method. The optimization results were obtained for an industrial condenser for two condensate temperatures of 46 degrees C and 54 degrees C. When the upstream steam mass flow rate increased, the optimum coolant temperature and the exergy efficiency decreased, and the exergy loss also increased simultaneously. The results showed higher values for the higher condensate temperature of 54 degrees C compared with that for 46 degrees C. For instance, if the condensate temperature increases from 46 degrees C to 54 degrees C, the coolant temperature will be increased from 16.76 degrees C to 25.17 degrees C. In addition, by assuming the ambient temperature of 15 degrees C, the exergy loss will be decreased from 172.5 to 164.6 kW. A linear relationship was also shown between the exergy efficiency and the dimensionless temperature, which is presented as a ratio of the temperature difference rate between inlet cooling water and ambient temperatures to the temperature difference rate of condensate and ambient temperatures.
In this work, a detailed study on the modeling, simulation and optimization of the industrial-scale Eluxyl simulated moving bed (SMB) process are presented. Commercial SPX3000 (Ba-faujasite type zeolite) was used as a...
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In this work, a detailed study on the modeling, simulation and optimization of the industrial-scale Eluxyl simulated moving bed (SMB) process are presented. Commercial SPX3000 (Ba-faujasite type zeolite) was used as an adsorbent, and para-diethylbenzene applied as a desorbent for separating para-xylene from other C-8 aromatics isomers. In the first step, the xylenes and para-diethylbenzene adsorption equilibrium on the commercial adsorbent were measured at operating conditions (175 degrees C, 9 bar) experimentally. The density of particle and porosities were determined from commercial plant operation and adsorbent analysis. Furthermore, mass transfer coefficients, including internal (diffusion in the pore) and external (diffusion in the liquid film) resistance, have been investigated in details. A common mathematical model encompassing the SMB strategy, node model, extended Langmuir isotherm, and rate expression were constructed to implement a numerical simulation of the industrial-scale Eluxyl SMB process with and without considering backwash stream. The accuracy of the mathematical model was validated by the industrial data. Besides, a dynamic optimization framework with Sequential Quadratic Programming (sqp) optimization algorithm was used for obtaining optimal conditions. Two separate single objective optimizations by considering minimum desorbent consumption and maximum SMB unit productivity as objectives were firstly designated. By comparing the results, it was concluded that minimizing desorbent consumption was more favorable to be selected as an objective function, which could achieve 6.35% increase in productivity and 7.28% decrease in desorbent consumption. Finally, two-level optimization was planned for reaching maximum feed throughput with minimum desorbent consumption. The results showed that productivity could be increased by 13.75%, and para-diethylbenzene consumption could be reduced by 10.81% at the optimal condition.
This work presents a detailed study for the systematic analysis, simulation and optimization of an industrial-scale simulated moving bed process with Ba/K-exchanged faujasite-type zeolite as adsorbent for separating p...
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This work presents a detailed study for the systematic analysis, simulation and optimization of an industrial-scale simulated moving bed process with Ba/K-exchanged faujasite-type zeolite as adsorbent for separating p-xylene from the C-8 aromatic mixture. The adsorption equilibrium of C-8 aromatic isomers and p-diethylbenzene on the commercial adsorbent were determined experimentally, while the lumped mass transfer coefficients were estimated through pulse experimental results. A generic mathematic model incorporating the fixed model, node model as well as dead volume model was developed to implement a numerical simulation of an industrial-scale p-xylene simulated moving bed process. Moreover, the accuracy of mathematic model was validated by industrial data. Furthermore, a dynamic optimization framework, with state of the art Sequential Quadratic programming optimization algorithm, was firstly proposed to obtain the optimal operating conditions for an existing industrial simulated moving bed unit. Optimization results reflect that the desorbent consumption of p-diethylbenzene was favorable to be selected as objective function to be minimized, which could achieve 3.12% increase in SMB unit productivity and 8.66% decrease in desorbent consumption for seven zone p-xylene simulated moving bed process. Two-level optimization procedure was also constructed to get the maximum feed throughput with a desired minimized desorbent consumption. Under the optimal operating conditions, the productivity increases by 16.63% while the PDEB consumption decreases by 18.85% for seven zone p-xylene simulated moving bed process. Eight zone p-xylene simulated moving bed process as a new operating mode, which was also analyzed, emulated and optimized through numerical calculation. Results show that the eight zone operation could achieve a much higher productivity and the desorbent consumption of p-diethylbenzene was almost the same in comparison with seven zone operation.
Gear mechanism is the most popular transmission mechanism;however, the traditional design method is complex and not accurate. Optimization design is the effective method to solve the above problems, used in gear desig...
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ISBN:
(纸本)9780819490261
Gear mechanism is the most popular transmission mechanism;however, the traditional design method is complex and not accurate. Optimization design is the effective method to solve the above problems, used in gear design method. In many of the optimization software MATLAB, there are obvious advantage projects and numerical calculation. There is a single gear transmission as example, the mathematical model of gear transmission system, based on the analysis of the objective function, and on the basis of design variables and confirmation of choice restrictive conditions. The results show that the algorithm through MATLAB, the optimization designs, efficient, reliable, simple.
This paper introduces the principle of the sqp algorithm and how to realize in MATLAB optimization toolbox. With mega watt wind turbine gear transmission system as the research object, the selection of the appropriate...
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ISBN:
(纸本)9783037853283
This paper introduces the principle of the sqp algorithm and how to realize in MATLAB optimization toolbox. With mega watt wind turbine gear transmission system as the research object, the selection of the appropriate design variables and constraints, as the volume of transmission system is the smallest and part of the gear rotational inertia minimum for target function, and set up the optimization mathematical model. Use the MATLAB optimization toolbox to optimize, and then calculate and analysis the example. The results show that before and after the optimization of the system, the volume and the rotational inertia of the gear are significantly reduced. This paper will supply some references for the wind power gear transmission system design. In order to solve the shortage of conventional energy, wind power is rapid development in world. In the wind turbine, gear growth box is an important component. As the wind turbine is usually installed on the mountains, wilderness and other outdoor outlet [1], and often under the irregular change of wind loads, so its design, manufacture and installation should have a special request. This paper will use the sqp (sequential quadratic programming) algorithm to optimize design parameters of MW-class wind turbine growth box gear transmission system, and apply the MATLAB Optimization Toolbox to achieve. When after the optimization, the transmission system is the smallest, lightest, the cost of manufacture and installation will be reduced, and the maintenance convenience will be improved.
In this paper,a new improved sqp algorithm which can avoid Maratos effect is proposed to solve minimax problems with inequality *** with the existing methods,the computational effort is *** addition,its global and sup...
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In this paper,a new improved sqp algorithm which can avoid Maratos effect is proposed to solve minimax problems with inequality *** with the existing methods,the computational effort is *** addition,its global and superlinear convergence are obtained under some mild ***,some numerical results show that the method is feasible and effective.
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