Estimation of Ground Water Level (GWL) for Tropical Peatland Forest Using Machine Learning-Reference-Cited by-同舟云学术

Estimation of Ground Water Level (GWL) for Tropical Peatland Forest Using Machine Learning

Published:2022 Issue: Volume:10 Page:126180-126187
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Li Lu¹^ORCID,Sali Aduwati¹^ORCID,Liew Jiun Terng¹,Saleh Nur Luqman¹^ORCID,Ahmad Sharifah Mumtazah Syed¹^ORCID,Ali Azizi Mohd¹,Nuruddin Ahmad Ainuddin²,Aziz Nurizana Amir³,Sitanggang Imas Sukaesih⁴,Syaufina Lailan⁵,Nurhayati Ati Dwi⁵,Nishino Hisanori⁶,Asai Nobuyuki⁶

Affiliation:

1. Department of Computer and Communication Systems Engineering, Faculty of Engineering, Wireless and Photonics Networks Research Centre of Excellence (WiPNET), Universiti Putra Malaysia, Serdang, Selangor, Malaysia

2. Institute of Tropical Forestry and Forest Products (INTROP), Universiti Putra Malaysia (UPM), Serdang, Selangor, Malaysia

3. Malaysian Meteorological Department (MET Malaysia), Petaling Jaya, Selangor, Malaysia

4. Department of Computer Science, Faculty of Natural Science and Mathematics, IPB University (Bogor Agricultural University), Bogor, Indonesia

5. Department of Silviculture, Faculty of Forestry, IPB University (Bogor Agricultural University), Bogor, Indonesia

6. National Institute of Information and Communications Technology (NICT), Koganei, Tokyo, Japan

Funder

IGNITE: Interference Modeling for 5G and Fixed Satellite Service (FSS) Coexistence at mmWave With Climate Change Considerations in the Tropical Region

Networked ASEAN Peatland Data (NAPD): Networked Association of Southeast Asian Nations (ASEAN) Peatland Data and Net-Peat: Networked ASEAN Peatland Communities for Transboundary Haze Alert

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09967973.pdf?arnumber=9967973

Reference29 articles.

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