Search results for "Gate"

A Numerical Method for an Inverse Problem Arising in Two-Phase Fluid Flow Transport Through a Homogeneous Porous Medium

2019

In this paper we study the inverse problem arising in the model describing the transport of two-phase flow in porous media. We consider some physical assumptions so that the mathematical model (direct problem) is an initial boundary value problem for a parabolic degenerate equation. In the inverse problem we want to determine the coefficients (flux and diffusion functions) of the equation from a set of experimental data for the recovery response. We formulate the inverse problem as a minimization of a suitable cost function and we derive its numerical gradient by means of the sensitivity equation method. We start with the discrete formulation and, assuming that the direct problem is discret…

Treed Gaussian Process Regression for Solving Offline Data-Driven Continuous Multiobjective Optimization Problems

2023

Abstract For offline data-driven multiobjective optimization problems (MOPs), no new data is available during the optimization process. Approximation models (or surrogates) are first built using the provided offline data and an optimizer, e.g. a multiobjective evolutionary algorithm, can then be utilized to find Pareto optimal solutions to the problem with surrogates as objective functions. In contrast to online data-driven MOPs, these surrogates cannot be updated with new data and, hence, the approximation accuracy cannot be improved by considering new data during the optimization process. Gaussian process regression (GPR) models are widely used as surrogates because of their ability to pr…

A Surrogate-assisted Reference Vector Guided Evolutionary Algorithm for Computationally Expensive Many-objective Optimization

2018

We propose a surrogate-assisted reference vector guided evolutionary algorithm for computationally expensive optimization problems with more than three objectives. The proposed algorithm is based on a recently developed evolutionary algorithm for many-objective optimization that relies on a set of adaptive reference vectors for selection. The proposed surrogateassisted evolutionary algorithm uses Kriging to approximate each objective function to reduce the computational cost. In managing the Kriging models, the algorithm focuses on the balance of diversity and convergence by making use of the uncertainty information in the approximated objective values given by the Kriging models, the distr…

On Dealing with Uncertainties from Kriging Models in Offline Data-Driven Evolutionary Multiobjective Optimization

2019

Many works on surrogate-assisted evolutionary multiobjective optimization have been devoted to problems where function evaluations are time-consuming (e.g., based on simulations). In many real-life optimization problems, mathematical or simulation models are not always available and, instead, we only have data from experiments, measurements or sensors. In such cases, optimization is to be performed on surrogate models built on the data available. The main challenge there is to fit an accurate surrogate model and to obtain meaningful solutions. We apply Kriging as a surrogate model and utilize corresponding uncertainty information in different ways during the optimization process. We discuss…

Handling expensive multiobjective optimization problems with evolutionary algorithms

2017

Multiobjective optimization problems (MOPs) with a large number of conflicting objectives are often encountered in industry. Moreover, these problem typically involve expensive evaluations (e.g. time consuming simulations or costly experiments), which pose an extra challenge in solving them. In this thesis, we first present a survey of different methods proposed in the literature to handle MOPs with expensive evaluations. We observed that most of the existing methods cannot be easily applied to problems with more than three objectives. Therefore, we propose a Kriging-assisted reference vector guided evolutionary algorithm (K-RVEA) for problems with at least three expensive objectives. The alg…

Approximation through interpolation in nonconvex multiobjective optimization

2011

Probabilistic Selection Approaches in Decomposition-based Evolutionary Algorithms for Offline Data-Driven Multiobjective Optimization

2022

In offline data-driven multiobjective optimization, no new data is available during the optimization process. Approximation models, also known as surrogates, are built using the provided offline data. A multiobjective evolutionary algorithm can be utilized to find solutions by using these surrogates. The accuracy of the approximated solutions depends on the surrogates and approximations typically involve uncertainties. In this paper, we propose probabilistic selection approaches that utilize the uncertainty information of the Kriging models (as surrogates) to improve the solution process in offline data-driven multiobjective optimization. These approaches are designed for decomposition-base…

Approximation method for computationally expensive nonconvex multiobjective optimization problems

2012

Postsynaptic NO/cGMP Increases NMDA Receptor Currents via Hyperpolarization-Activated Cyclic Nucleotide-Gated Channels in the Hippocampus

2013

The nitric oxide (NO)/cyclic guanosine monophosphate (cGMP) signaling cascade participates in the modulation of synaptic transmission. The effects of NO are mediated by the NO-sensitive cGMP-forming guanylyl cyclases (NO-GCs), which exist in 2 isoforms with indistinguishable regulatory properties. The lack of long-term potentiation (LTP) in knock-out (KO) mice deficient in either one of the NO-GC isoforms indicates the contribution of both NO-GCs to LTP. Recently, we showed that the NO-GC1 isoform is located presynaptically in glutamatergic neurons and increases the glutamate release via hyperpolarization-activated cyclic nucleotide (HCN)-gated channels in the hippocampus. Electrophysiologi…

Modulation of voltage-gated K(+) channels Kv11 and Kv1 4 by forskolin.

2002

Forskolin (FSK) affects voltage-gated K + (Kv) currents in different cell types, but it is not known which of the various subunits form FSK-sensitive Kv channels. We compared the effect of the compound at Kv1.1 and Kv1.4 channels ectopically expressed in HEK 293 cells. Low FSK concentrations induced a phosphorylation-dependent potentiation of Kv1.1 currents. At higher concentrations, this effect was superimposed by a fast, cAMP-independent channel block. Kv1.4 currents were inhibited with lower potency by FSK but were not modified by phosphorylation. The variable effect of the compound might help to distinguish between Kv subunits expressed by native cells.  2002 Elsevier Science Ltd. All …