Klaim Artikel Anda
Verifikasi kepemilikan artikel akademik
Apakah artikel-artikel ini milik Anda?
Daftarkan diri Anda sebagai author untuk mengklaim artikel dan dapatkan profil akademik terverifikasi dengan fitur lengkap.
Badge Verifikasi
Profil terverifikasi resmi
Statistik Lengkap
H-index, sitasi, dan metrik
Visibilitas Tinggi
Tampil di direktori author
Kelola Publikasi
Dashboard artikel terpadu
Langkah-langkah Klaim Artikel:
- 1. Daftar akun author dengan email akademik Anda
- 2. Verifikasi email dan lengkapi profil
- 3. Login dan buka menu "Klaim Artikel"
- 4. Cari dan klaim artikel Anda
- 5. Tunggu verifikasi dari admin (1-3 hari kerja)
Menampilkan 1–2 dari 2 artikel
Seasonal Variability in Soil Salinity and its Climatic Drivers in Khulna, Bangladesh
Forum Geografi
Vol 39
, No 3
(2025)
Bangladesh is one of the countries in the world most severely affected by soil salinity issues. This research focuses on the seasonal variation in soil salinity and the associated impact of climate change across different sites in the Batiaghata sub-district of Khulna, located in the southwestern coastal belt of Bangladesh. The study encompasses four meteorological seasons: pre-monsoon (March-April-May), monsoon (June-July-August-September), post-monsoon (October-November), and winter (December-...
Sumber Asli
Google Scholar
DOI
Enhanced Air Quality Prediction Using AI: A Comparative Study of GRU, CNN, and XGBoost Models
Kayam Saikumar
; Munugapati Bhavana
; Rayudu Prasanthi
; Singaraju Suguna Mallika
; Deepthi Kamidi
; Naveen Malik
; Kapil Joshi
Advance Sustainable Science, Engineering and Technology
Vol 7
, No 3
(2025)
Weather monitoring is vital due to environmental changes and rising air pollution, which affects health and lifestyles. Accurate air quality prediction models are essential yet challenging due to complex weather-pollution interactions. This study employs explainable deep learning and machine learning techniques—GRU, CNN, and XGBoost—on a custom dataset of 100,000 samples with 15 features, including PM2.5, PM10, humidity, and temperature. Using SHAP for interpretability, the GRU model outperforms...
Sumber Asli
Google Scholar
DOI