황형주 교수
Hyoung-Joo Hwang
포항공과대학교 컴퓨터공학과 · 수학
연구실 소개
황형주 교수의 연구실은 주로 비선형 편미분방정식과 입자 운동론을 기반으로 한 수학적 모델링을 중심으로 활동하고 있습니다. 특히, Vlasov-Poisson 시스템의 정규성 해와 경계 효과에 관한 고전적 해의 존재성, 그리고 생물학적 이동 현상인 화학성향운동(chemotaxis)의 운동 기반 모델링에 깊이 관여해 왔습니다. 이와 더불어, 신종 코로나바이러스 감염증(코로나19)의 전파를 기반으로 한 SIR 모델을 활용한 역문제 해법 연구를 통해 실제 데이터 기반의 수학적 예측 모델 개발에도 기여하고 있습니다. 이러한 연구들은 수학적 이론과 실제 응용을 연결하는 데 초점을 맞추고 있습니다.
연구 현황
연구 성과 추이
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
주요 논문
15As the amount of data increases, it is more likely that the assumptions in the existing economic analysis model are unsatisfied or make it difficult to establish a new analysis model. Therefore, there has been increased demand for applying the machine learning methodology to bankruptcy prediction due to its high performance. By contrast, machine learning models usually operate as black-boxes but credit rating regulatory systems require the provisioning of appropriate information regarding credit
A widespread phenomenon in moving microorganisms and cells is their ability to reorient themselves depending on changes of concentrations of certain chemical signals. In this paper we discuss kinetic models for chemosensitive movement, which also takes into account evaluations of gradient fields of chemical stimuli which subsequently influence the motion of the respective microbiological species. The basic type of model was discussed by Alt [J. Math. Biol., 9 (1980), pp. 147--177], [J. Reine Ang
Abstract Mathematical modeling is a process aimed at finding a mathematical description of a system and translating it into a relational expression. When a system is continuously changing over time (e.g., infectious diseases) differential equations, which may include parameters, are used for modeling the system. The process of finding those parameters that best fit the given data from the system is called an inverse problem. This study aims at analyzing the novel coronavirus infection (COVID-19)
In this paper we prove the existence of a large class of periodic solutions of the Vlasov-Poisson in one space dimension that decay exponentially as t -> infinity. The exponential decay is well known for the linearized version of the Landau damping problem and it has been proved in [4] for a class Of solutions of the Vlasov-Poisson system that behaves asymptotically as free streaming solutions and are sufficiently flat in the space of velocities. The results in this paper enlarge the class of
We study a kinetic model for chemotaxis introduced by Othmer, Dunbar, and Alt [23], which was motivated by earlier results of Alt, presented in [1], [2]. In two papers by Chalub, Markowich, Perthame and Schmeiser, it was rigorously shown that, in three dimensions, this kinetic model leads to the classical Keller-Segel model as its drift-diffusion limit when the equation of the chemo-attractant is of elliptic type [4], [5]. As an extension of these works we prove that such kinetic models have a m
We consider the initial-boundary value problem in a convex domain for the Vlasov--Poisson system. Boundary effects play an important role in such physical problems that are modeled by the Vlasov--Poisson system. We establish the global existence of classical solutions with regular initial boundary data under the absorbing boundary condition. We also prove that regular symmetric initial data lead to unique classical solutions for all time in the specular reflection case.
We establish the exponential time decay rate of smooth solutions of smallamplitude to the Vlasov-Poisson-Fokker-Planck equations to the Maxwellian bothin the whole space and in the periodic box via the uniform-in-time energyestimates and also the macroscopic equations.
BACKGROUND: The COVID-19 pandemic has caused major disruptions worldwide since March 2020. The experience of the 1918 influenza pandemic demonstrated that decreases in the infection rates of COVID-19 do not guarantee continuity of the trend. OBJECTIVE: The aim of this study was to develop a precise spread model of COVID-19 with time-dependent parameters via deep learning to respond promptly to the dynamic situation of the outbreak and proactively minimize damage. METHODS: In this study, we inves
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