A Technique for Developing a Precise Thermal Compact Model

Okamoto, Keishi; Koyamada, K.; Kuzuno, Masanori; Nishio, Toshihiko; Kotera, Hidetoshi

doi:10.1115/pvp2002-1597

Cited by 2 publications

(1 citation statement)

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“…To cope with these problems, we employ the Response Surface Methodology (RSM) [1] as the optimization technique. In general, the RSM is used for optimization of the process of a product design etc, and thermal simulation [5,6,7].…”

Section: Introductionmentioning

confidence: 99%

Parameter optimization technique using the response surface methodology

Koyamada

Saki

Itoch³

The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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We propose a parameter optimization technique using the response surface methodology (RSM) for the accurate biological cell simulation which calculates cell behavior by numerically integrating the differential equation and generates action potentials, intracellular Ca transient, contraction, and intracellular ATP consumption by using parameter values of major ion permeability and amplitude of Ko dependency. Since most of these parameters cannot be directly measured by experiment, these are searched for by applying an optimization technique, that is, by minimizing an objective function defined as a difference between a measured and a calculated waveform of action potentials in a cardiac myocyte. We employ the RSM as the optimization technique. In the RSM, a quadratic polynomial is used in general, and a mathematical technique is used to calculate the extreme points. Because our parameter space cannot be approximated by a single quadratic polynomial surface, we adopt a recursive subdivision technique and use the coefficient of multiple determination to representing a response surface in each subspace for a criteria of the subdivision. We confirmed the effectiveness of the proposed technique by searching for parameters which are determined in advance.

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Section: Introductionmentioning

confidence: 99%

Parameter optimization technique using the response surface methodology

Koyamada

Saki

Itoch³

The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Improved Hierarchical Parameter Optimization Technique - Application for a cardiac myocyte model

Yamashita

Sakai²,

Sakamoto³

et al. 2006

2006 International Conference of the IEEE Engineering in Medicine and Biology Society

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We propose a hierarchical parameter optimization technique which further enhances our original technique for an accurate biological cell simulation. Our original technique generates a k-d tree and uses the coefficient of multiple determination (R2) for tree-branching, however it requires a huge computation time since it processes the response surface at every leaf node of the k-d tree, including those that do not have optimum parameters. In our parameter optimization problem, the objective function is defined as the difference between the measured and calculated waveform of action potentials in a cardiac myocyte. The function value is always non-negative, and is equal to zero if and only if the best optimized parameter is included in the leaf node. To minimize the computational cost problem, our proposed technique takes advantage of the aforementioned conditions and only processes a leaf node if the corresponding Hessian matrix of the objective function is found to be a positive definite matrix. We confirmed the effectiveness of the proposed parameter optimization technique by searching for some pre-determined parameters.

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A Technique for Developing a Precise Thermal Compact Model

Cited by 2 publications

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Parameter optimization technique using the response surface methodology

Parameter optimization technique using the response surface methodology

Improved Hierarchical Parameter Optimization Technique - Application for a cardiac myocyte model

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