PHYSICS INFORMED NEURAL NETWORK ON DIFFERENTIAL EQUATIONS

PHYSICS INFORMED NEURAL NETWORK ON DIFFERENTIAL EQUATIONS

This final project aims to search for an approximate numerical solution of a differential equation using the Physics Informed Neural Network (PINN) method. This method uses a deep learning approach, namely, an artificial neural network. In the process of building a model, it takes information on...

Saved in:

書目詳細資料
主要作者:	Almira Suheri, Fidya
格式:	Final Project
語言:	Indonesia
在線閱讀:	https://digilib.itb.ac.id/gdl/view/74524
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!
機構:	Institut Teknologi Bandung
語言:	Indonesia

相似書籍

MITIGATING SHOCK PHENOMENON OF HYPERBOLIC PARTIAL DIFFERENTIAL EQUATIONS WITH PHYSICS INFORMED NEURAL NETWORKS
由: LIU ZHENGYANG
出版: (2024)

DETERMINATING APPROXIMATION SOLUTION OF PARTIAL DIFFERENTIAL EQUATION USING PHYSICS-INFORMED NEURAL NETWORK (PINN)
由: Agnes Priscilla, Cyntia

Physics-informed neural networks with non-differentiable loss
由: Yang, Junyan
出版: (2022)

IMPLEMENTATION OF PHYSICS-INFORMED NEURAL NETWORKS USING SPIRAL OPTIMIZATION IN DETERMINING SOLUTION FOR BLACK-SCHOLES EQUATION
由: Cahyohartoto, Fairuz

Graph neural differential equation networks for improved representation learning and robustness
由: Zhao, Kai
出版: (2025)

Learning strategies for physics-informed neural networks
由: Wong, Jian Cheng
出版: (2025)

Quantifying uncertainty in physics-informed neural networks
由: Yip, Jun Kai
出版: (2025)

CAN-PINN: a fast physics-informed neural network based on coupled-automatic-numerical differentiation method
由: Chiu, Pao-Hsiung, et al.
出版: (2022)

PEMANFAATAN PHYSICS INFORMED NEURAL NETWORK MENGGUNAKAN NEURAL NETWORK ALGORITHM UNTUK MENYELESAIKAN PERSAMAAN DIFERENSIAL
由: Maisaroh, Siti

PHYSICS-INFORMED NEURAL NETWORK (PINN) AND ITS APPLICATION TO HEAT DISTRIBUTION
由: Alfarino B. P., Michael

PHYSICS-INFORMED NEURAL NETWORK (PINN) AND ITS APPLICATION TO POLLUTANT TRANSPORT
由: Yuki Sutanto, Christopher

Physics informed neural network for heat transfer problem in concrete structure
由: Powa, Anderson Justin
出版: (2024)

Finding optimal hyperparameters of feedforward neural networks for solving differential equations using a genetic algorithm
由: C. Boonthanawat, et al.
出版: (2022)

Analyses of internal structures and defects in materials using physics-informed neural networks
由: Zhang, Enrui, et al.
出版: (2023)

Physics-informed neural networks for low Reynolds number flows over cylinder
由: Ang, Elijah Hao Wei, et al.
出版: (2023)

Physics informed neural network-based high-frequency modeling of induction motors
由: Zhao, Zhenyu, et al.
出版: (2023)

Three-dimensional physics-informed neural network simulation in coronary artery trees
由: Alzhanov, Nursultan, et al.
出版: (2024)

PHYSICS-INFORMED NEURAL NETWORK (PINN) DALAM MENYELESAIKAN KASUS ALIRAN FLUIDA VISKOS
由: Amalinadhi Putra, Cahya

CONSTRUCTING EQUILIBRIUM OF PLASMA MAGNETIC CONFINEMENT THROUGH THE APPLICATION OF PHYSICS-INFORMED NEURAL NETWORKS
由: Harry Yudha Pratama, Muchamad

Using neural networks for approximating functions and equations
由: Li, Yongming
出版: (2019)

A physics-informed neural network approach to augmented dynamics visual servoing of multirotors
由: Kamath, Archit Krishna, et al.
出版: (2025)

USING PHYSICS-INFORMED NEURAL NETWORK (PINN) FOR SOLVING DIRECT AND INVERSE HEAT CONDUCTION PROBLEMS
由: Abdul Aziz, Muhamad

Neural network model for differential GPS
由: Low, Kwong Hwee.
出版: (2008)

High-frequency modelling of variable-frequency drive systems based on physics-informed neural network
由: Raymond, Sammuel
出版: (2024)

INVESTIGATION OF APPLYING PHYSICS INFORMED NEURAL NETWORKS (PINN) AND VARIANTS ON 2D AERODYNAMICS PROBLEMS
由: TAY WEE BENG, et al.
出版: (2020)

Rectified deep neural networks overcome the curse of dimensionality when approximating solutions of McKean–Vlasov stochastic differential equations
由: Neufeld, Ariel, et al.
出版: (2024)

DESIGN AND IMPLEMENTATION OF NON LINEAR CONTROLLER WITH PHYSICS INFORMED NEURAL NETWORK APPROACH FOR GANTRY CRANE PROTOTYPE
由: Ash Shiddieqy, Shabri

Analogous View Between Residual Networks and Partial Differential Equations
由: Vichayuth Imchitr
出版: (2020)

Ensemble learning of soil–water characteristic curve for unsaturated seepage using physics-informed neural networks
由: Yang, Haoqing, et al.
出版: (2025)

A primal neural network for solving nonlinear equations and inequalities
由: Zhang, Y., et al.
出版: (2014)

DEVELOPMENT OF PRESSURE ESTIMATOR AND VELOCITY FIELD CORRECTIONS FOR PARTICLE IMAGE VELOCIMETRY USING PHYSICS-INFORMED NEURAL NETWORK
由: Christian Chandra, Calvin

THE APPLICATION OF PHYSICS-INFORMED NEURAL NETWORKS FOR GEOTHERMAL NATURAL STATE MODELING AND POST-DRILLING WELL HEATING UP
由: Piere Canilandi, Mesias

Partial Differential Equations
出版: (2017)

On hypergeodesic differential equations
由: Roongsiri Masarat
出版: (2014)

Differential equations in business
由: Badillo, Rustica D.
出版: (1984)

PARTIAL DIFFERENTIAL EQUATIONS
由: QIN YUHUA
出版: (2021)

TOPICS IN DIFFERENTIAL EQUATIONS
由: HO WEI LUN DESMOND
出版: (2021)

STOCHASTIC DIFFERENTIAL EQUATIONS
由: LAU PUI MAN
出版: (2021)

PARTIAL DIFFERENTIAL EQUATIONS
由: TIMOTHY GOENADIBRATA
出版: (2021)

PARTIAL DIFFERENTIAL EQUATIONS
由: TAN ZHIPENG DARYL
出版: (2021)