Data driven modelling and simulation of wetland dynamics

Anupam, Angesh; Wilton, David J.; Kadirkamanathan, Visakan

doi:10.1080/02286203.2021.1930402

Cited by 5 publications

(2 citation statements)

References 36 publications

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“…In system identification, observed input and output data of an underlying system are used for deriving an appropriate mathematical model of the system, where analytical methods of modelling do not yield very satisfactory results. In the last few decades, system identification methodology has been applied in different disciplines, for example, electroencephalography (Zhao et al, 2012), space weather modelling (Balikhin et al, 2011), synthetic biology (Krishnanathan et al, 2012), power generation (Basso et al, 2005), econometrics (Soofi & Cao, 2012), biomedical engineering (Anderson et al, 2010), environmental systems (Anupam et al, 2021), mechanical systems (Aboelela et al, 2018; Haddouche et al, 2019), and supply chain management (Trapero et al, 2011). Following the success of system identification in these application domains, we explore its application in predicting Norwegian air passenger traffic.…”

Section: Methodsmentioning

confidence: 99%

Forecasting air passenger travel: A case study of Norwegian aviation industry

Anupam,

Lawal

2023

Journal of Forecasting

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Accurate forecasting of airline passenger traffic is important for facilitating the effective management and planning of aviation resources. In this study, we explore the air passenger traffic in the Norwegian aviation industry by collecting the passenger flow data and the corresponding measurements of the weather conditions affecting the flow from the different airports in Norway. We then proposed nonlinear autoregressive with exogenous input (NARX) forecasting models to predict air passenger traffic in advance. The NARX models account for the nonlinearity and nonstationarity in the passenger flow and allow the accurate forecasting of air passenger traffic. We perform experiments to demonstrate the effectiveness of two variants of the NARX model and compare their performances against long short‐term memory (LSTM), a deep learning method. We show that the proposed NARX model achieves the best prediction accuracy compared to LSTM, which is considered as a state‐of‐the‐art approach for fitting sequential data.

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Section: Methodsmentioning

confidence: 99%

Forecasting air passenger travel: A case study of Norwegian aviation industry

Anupam,

Lawal

2023

Journal of Forecasting

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“…Apart from these studies, the authors in [5] adopted a data-driven approach, especially based on system identifcation, to develop nonlinear autoregressive exogenous input model structures corresponding to tropical wetland dynamics as an alternative to classical terrain modeling methods. Te work presented in this study provided many lessons for data-driven environmental research, but needs to be further enhanced in practicality.…”

Section: Related Workmentioning

confidence: 99%

Challenges and Solutions of the Application of Data-Driven Technology in Network 3D Game Design

Wang

2023

Mobile Information Systems

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The development of online games is in full swing in recent years, and it is developing in the direction of 3D, exquisite, and has attained significant popularity. However, there are many challenges faced while designing 3D games that are targeted to specific user groups and can run stably. Data-driven technology can collect game preferences and identify common technical defects and other issues in game design for effective completion of frameworks. To solve the problem and difficulty of obtaining the data for 3D games and the possibility of flaws in the framework design, this paper adopts data-driven technology to descriptively analyze the obtained data through website log files, web beacons, and JS page tags and constructs a network after experimenting with the mathematical model of 3D modeling for gaming. For this purpose, a 3D game framework was successfully designed. After testing the data of the server for three cases while there are 4000, 8000, and 12000 players online at a given time, where each of which ran for 3 consecutive days, and it was concluded that the average CPU occupancy rate of these three cases was below 50%, especially in the range of about 30% for the majority of these players. Moreover, it can stably support about 10000 simultaneous online players for a relatively long period of time. For game servers and character servers, the results are excellent and have the potential to be adopted in future for 3D gaming industry.

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Deep deconstruction and future development of process-based models for subsurface flow constructed wetlands

Li,

Yuan

2023

Journal of Water Process Engineering

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Data driven modelling and simulation of wetland dynamics

Cited by 5 publications

References 36 publications

Forecasting air passenger travel: A case study of Norwegian aviation industry

Forecasting air passenger travel: A case study of Norwegian aviation industry

Challenges and Solutions of the Application of Data-Driven Technology in Network 3D Game Design

Deep deconstruction and future development of process-based models for subsurface flow constructed wetlands

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