Optimization of parameters in mathematical models of biological systems

추상목,김영희 한국전산응용수학회 2008 Journal of applied mathematics & informatics Vol.26 No.1

Under pathological stress stimuli, dynamics of a biological system can be changed by alteration of several components such as functional proteins, ultimately leading to disease state. These dynamics in disease state can be modeled using differential equations in which kinetic or system parameters can be obtained from experimental data. One of the most effective ways to restore a particular disease state of biology system (i.e., cell, organ and organism) into the normal state makes optimization of the altered components usually represented by system parameters in the differential equations. There has been no such approach as far as we know. Here we show this approach with a cardiac hypertrophy model in which we obtain the existence of the optimal parameters and construct an optimal system which can be used to find the optimal parameters. Under pathological stress stimuli, dynamics of a biological system can be changed by alteration of several components such as functional proteins, ultimately leading to disease state. These dynamics in disease state can be modeled using differential equations in which kinetic or system parameters can be obtained from experimental data. One of the most effective ways to restore a particular disease state of biology system (i.e., cell, organ and organism) into the normal state makes optimization of the altered components usually represented by system parameters in the differential equations. There has been no such approach as far as we know. Here we show this approach with a cardiac hypertrophy model in which we obtain the existence of the optimal parameters and construct an optimal system which can be used to find the optimal parameters.

Parameters Tuning via Simplex-Search based Model-Free Optimization for the Steam Generator Level Control

Guan Jiansheng,Kong Xiansong 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.4

Control performance is critical to a control system. To improve the performance of the steam generator level control system, the control system parameters need to be optimized. Traditional parameters tuning methods, such as trial and error and Design of Experiments etc., are usually experience-based, cumbersome and time-consuming. To address the above inefficiencies, in this paper, the simplex-search based Model-Free Optimization (MFO) has been proposed to search for the optimal control system parameters. The optimized parameters will be gained to maximize the system’s control performance. Rather than traditional controller parameter tuning method, this method optimizes the control system by directly using measurements of control performance. An example of the PID parameters tuning for the steam generator level control was illustrated. The efficiency and the effectiveness of the Simplex-search based Model-Free Optimization – based control parameters tuning methodology has been verified through simulation experiments.

Optimal Procedure for Determining Constitutive Parameters of Giuffrè–Menegotto–Pinto Model for Steel Based on Experimental Results

Van Tu Nguyen,Xuan Dai Nguyen 한국강구조학회 2022 International Journal of Steel Structures Vol.22 No.3

Describing the nonlinear behaviour of constitutive materials plays an important role in structural analysis. The Giuff rè– Menegotto–Pinto (GMP) model is widely used in the nonlinear modelling of steel structures, with its constituent parameters often calibrated from tests. However, the experimental results obtained require intermediate identifi cation procedures before being used directly, meanwhile, the calibration of model parameters based on experimental data is complicated due to the many interrelated constituent variables. This paper aims to propose a method that calibrates the GMP model parameters optimally based on the experimental data. An available set of test results of high-strength steels subjected to cyclic strain is employed to perform an optimal analysis. The obtained results are then compared to numerical and experimental results to evaluate the eff ectiveness of the proposed method. An extensive study was carried out to evaluate the applicability of the optimal parameters obtained and those suggested by OpenSees. The fi ndings reveal that the proposed procedure is highly effi cient, making it a useful option for developing OpenSees applications that automatically calibrate model parameters. A typical 3D steel frame structure subjected to an earthquake is analyzed to evaluate the applicability of the results obtained.

OPTIMIZATION OF PARAMETERS IN MATHEMATICAL MODELS OF BIOLOGICAL SYSTEMS

Choo, S.M.,Kim, Y.H. Korean Society of Computational and Applied Mathem 2008 Journal of applied mathematics & informatics Vol.26 No.1

Under pathological stress stimuli, dynamics of a biological system can be changed by alteration of several components such as functional proteins, ultimately leading to disease state. These dynamics in disease state can be modeled using differential equations in which kinetic or system parameters can be obtained from experimental data. One of the most effective ways to restore a particular disease state of biology system (i.e., cell, organ and organism) into the normal state makes optimization of the altered components usually represented by system parameters in the differential equations. There has been no such approach as far as we know. Here we show this approach with a cardiac hypertrophy model in which we obtain the existence of the optimal parameters and construct an optimal system which can be used to find the optimal parameters.

Structural shape optimization of free-form surface shell and property of solution search using firefly algorithm

Natsuki Tanaka,Toshio Honma,Yohei Yokosuka 대한기계학회 2015 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.29 No.4

The computation procedure for structural shape optimization is based on the heuristic optimization procedures, such as swarm intelligence(SI), that use patterns found in self-organizing phenomena observed in nature. Most SI techniques including particle swarm optimization(PSO) and artificial bee colony (ABC), attain a global optimal solution. The firefly algorithm (FA) can attain both a global optimaland local optimal solutions by setting suitable computational parameters. However, the method for setting these parameters is comparativelydifficult. In order to simplify the setting of these parameters, we implement a computational scheme where the distance betweentwo fireflies in the design variable space is dimensionless. The effectiveness and the validity of this FA are clarified by showingthe diversified solution for a global optimal solution and local optimal solutions using a local search in the structural shape optimizationof a free-form surface shell.

Model and Optimize the Magnetic Composite Fluid (MCF) Polishing Process with Machine Learning Modeling and Intelligent Optimization Algorithm

Jinwei Fan,Xingfei Ren,Ri Pan,Peitong Wang,Haohao Tao 한국정밀공학회 2022 International Journal of Precision Engineering and Vol.23 No.9

In the magnetic composite fluid (MCF) polishing process, appropriate polishing parameters are the basis of achieving high-quality polishing without damage. Appropriate polishing parameters are mainly based on an accurate polishing model and an excellent polishing parameters optimization algorithm. However, due to the complicated principle of MCF polishing and various influencing elements, traditional modeling methods have the limitations of low accuracy, poor application, and difficulty in correcting. Therefore, it is challenging to obtain the optimal polishing quality by optimizing the polishing parameters based on the traditional model. This study proposed an online modeling approach considering data cleaning based on machine learning modeling, and the particle swarm optimization (PSO) algorithm was used to optimize polishing parameters. Then, copper polishing experiments were carried out to validate the modeling and optimization methods. The results demonstrate that the proposed machine learning online modeling method can establish an accurate MCF polishing model, and the nano-scale fine polishing of copper can be achieved by the optimized polishing parameters of PSO, and the surface roughness of the copper sample was reduced by 85% to 0.031 μm.

1,000km의 비 영 분산 천이 광섬유로 구성된 WDM 시스템에서 최적 파라미터를 갖는 MSSI를 이용한 NRZ 형식의 16×40 Gbps WDM 신호의 비트 에러율 개선

이영교 (사)디지털산업정보학회 2010 디지털산업정보학회논문지 Vol.6 No.3

In this paper the numerical methods of finding out the optimal position of optical phase conjugator (OPC) and the optimal fiber dispersion are proposed, which are able to effectively compensate overall channels in 16×40 Gbps WDM system. And the compensation characteristics in the system with two induced optimal parameters are compared with those in the system with the currently used mid-span spectral inversion (MSSI) in order to confirm the availability of the proposed methods. It is confirmed that the reception performances are largely improved in the system with the induced optimal parameters than in the system with MSSI through the analyzing the eye opening penalty (EOP) and bit error rate (BER) characteristics. It is also confirmed that two optimal parameters depend on each other, but are less related with the procedural problem about the first optimal value among these parameters.

Parameters optimization design for LCL-type STATCOMs under complex power grid

Wang, Xiangyu,Wang, Minglei,Wang, Liguo,Fu, Guangjie,Qiao, Jinxin The Korean Institute of Power Electronics 2020 JOURNAL OF POWER ELECTRONICS Vol.20 No.2

LCL filter parameters and control parameters are interdependent and inter-restricted. They can all affect the stability of a static synchronous compensator (STATCOM) under the effects of a complex power grid such as harmonic grid voltage and grid impedance variation. An advanced parameters optimization method integrated with LCL filter and control strategy is proposed. At first, the ABC-Pareto algorithm (Pareto multi-objective optimization of an artificial bee colony algorithm) is used to reasonably choose the LCL filter parameters. Under the premise of using capacitor current feedback active damping control and grid voltage feedforward control, the mathematical models of the STATCOM are derived. The constraints of control performances on the control parameters are obtained. According to these constraints, it is possible to construct a satisfactory 3D space. The control parameters can be chosen reasonably by finding the optimized space when the power grid is changed. Simulation and experimental results show the effectiveness and superiority of the proposed method.

Development of Parameter Optimization System using Iterative Experiment and Optimization for Injection Foam Molding

Kyung-min Lee(이경민) 제어로봇시스템학회 2017 제어·로봇·시스템학회 논문지 Vol.23 No.12

Injection molding (IM) is one of the most important processes for mass-producing plastic products. There are several significant challenges in using IM. The IM process requires many input parameters, but the relationships between the desired material properties and parameter settings (e.g. gas content and pressure drop) are not well understood collectively. We propose an optimization-based computational framework that will provide computer-based decision support for setting parameters in the IM process. The decision support will enable dramatic time and cost efficiencies in that the settings for parameters. It can discover optimized parameters much more rapidly than conventional methods that require extensive experimentation. Key elements in the framework involve approximating the governing equations using analysis of variance (ANOVA) techniques and normative optimization modeling to achieve optimal parameter settings. We illustrate the computational framework on HDPE materials in which parameter settings such as gate geometry, N2 content, void fraction, and injection speed are considered. The proposed framework will provide an improved understanding of the relationships between material properties and parameter settings in general IM process environments.

Optimal Design of a Planar-Type Antenna with a Reduced Number of Design Parameters Using Taguchi Method and Adaptive Particle Swarm Optimization

Lee, Jeong-Hyeok,Jang, Dong-Hyeok,Kim, Hyeong-Seok The Korean Institute of Electrical Engineers 2014 Journal of Electrical Engineering & Technology Vol.9 No.6

This paper presents a method to optimize the design of a planar-type antenna and reduce the number of design parameters for rapid computation. The electromagnetic characteristics of the structure are analyzed, and Taguchi method is used to identify critical design parameters. Adaptive particle swarm optimization, which has a faster convergence rate than particle swarm optimization, is used to achieve the design goal effectively. A compact dual-band USB dongle antenna is tested to verify the advantage of the proposed method. In this case, we can use only five selected geometrical parameters instead of eighteen to accelerate the optimization of the antenna design. The 10 dB bandwidth for return loss ranges from 2.3 GHz to 2.7 GHz and from 5.1 GHz to 5.9 GHz, covering all the WiBro, Bluetooth, WiMAX, and 802.11 b/g/n WLAN bands in both simulation and measurement. The optimization process enables the antenna design to achieve the required performance with fewer design parameters.