Akademisyen
AMIN GHAREHBAGHI
DOÇENT
HASAN KALYONCU ÜNİVERSİTESİ MÜHENDİSLİK FAKÜLTESİ İNŞAAT MÜHENDİSLİĞİ BÖLÜMÜ
- Ana Dal Mühendislik Temel Alanı
- Yan Dal İnşaat Mühendisliği
Kayıtlı çıktılara kısa bakış — ayrıntılar aşağıda.
- Makale 64
- Proje 0
- Kitap 1
- Bildiri 5
- Patent 0
- Sanatsal 0
Scopus (SJR)
Q1
31
Q2
21
Q3
5
Q4
0
WoS (JCR)
Q1
29
Q2
11
Q3
13
Q4
4
TR Index
4
makale
Alan+yıl+tür normalize OpenAlex yüzdelik — Clarivate ESI / SciVal değildir.
Üst %1 makale
0
Üst %10 makale
0
Ort. yüzdelik
88.4%
Üst %1 payı
0.0%
Üst %10 payı
0.0%
Makaleler
YÖKSİS ve OpenAlex kaynak ayrımıyla makaleler; quartile ve TR Index ile daraltabilirsiniz.
Makale listesi
- 2026 Advancement in forecasting rainfall-runoff process: application of a novel hybrid FMD-SVR-ABC modeling technique YÖKSİS SJR Q2 JCR Q2
- 2026 Next-generation intelligent framework for pan evaporation prediction: introducing Chebyshev polynomial-based Kolmogorov-Arnold networks YÖKSİS SJR Q1 JCR Q1
- 2026 Monthly and fixed coefficient calibration of empirical reference evapotranspiration equations: A case study for a Mediterranean climate (Izmir Province) YÖKSİS SJR Q1 JCR Q3
- 2026 Application of Hybrid Meta-Heuristic-Based Data‑Driven Models to Forecast Streamflow Drought Index YÖKSİS SJR Q1 JCR Q1 OpenAlex 90.0%
- 2026 Advancing river streamflow prediction with convolutional Kolmogorov-Arnold network: a comprehensive comparison against machine learning and deep learning models YÖKSİS SJR Q1 JCR Q1
- 2026 Application of Novel Hybrid SVMD-NARX-ACO Model for Precise Predicting Monthly Pan Evaporation YÖKSİS SJR Q1 JCR Q2
- 2026 A Comparative Evaluation of Deep Learning and Machine Learning Models for River Suspended Sediment Concentration Forecasting YÖKSİS SJR Q1 JCR Q1
- 2026 An advanced complex hybrid machine learning model for forecasting reference evapotranspiration YÖKSİS SJR Q1 JCR Q1
- 2025 Correction: Developing a novel hybrid model based on GRU deep neural network and Whale optimization algorithm for precise forecasting of river’s streamflow YÖKSİS SJR Q1 JCR Q1
- 2025 Development of interpretable intelligent frameworks for estimating river water turbidity YÖKSİS SJR Q1 JCR Q1
- 2025 A Comparative Study on Novel Hybrid Approaches Based on CEEMDAN, Random Forest, Deep Learning Methods for Predicting Daily Wind Speed YÖKSİS SJR Q1 JCR Q1
- 2025 Developing a novel hybrid model based on GRU deep neural network and Whale optimization algorithm for precise forecasting of river’s streamflow YÖKSİS SJR Q1 JCR Q1
- 2025 Developing a novel layer network structure for a LSTM model to predict mean monthly river streamflow YÖKSİS SJR Q1 JCR Q1
- 2025 A Comparative Study on Novel Hybrid Approaches Based on CEEMDAN, Random Forest, Deep Learning Methods for Predicting Daily Wind Speed YÖKSİS SJR Q1 JCR Q1
- 2025 Development of interpretable intelligent frameworks for estimating river water turbidity YÖKSİS SJR Q1 JCR Q1
- 2025 Developing a novel hybrid model based on GRU deep neural network and Whale optimization algorithm for precise forecasting of river's streamflow YÖKSİS SJR Q1 JCR Q1 OpenAlex 89.1%
- 2025 A Comparative Assessment of Machine Learning and Deep Learning Models for the Daily River Streamflow Forecasting YÖKSİS SJR Q1 JCR Q1
- 2025 Development of deep learning approaches for drought forecasting: a comparative study in a cold and semi-arid region YÖKSİS SJR Q1 JCR Q1
- 2025 Developing a novel layer network structure for a LSTM model to predict mean monthly river streamflow YÖKSİS SJR Q1 JCR Q1
- 2025 Development of explainable hybrid quantum-inspired recurrent neural networks for predicting groundwater quality: A case study at West Azerbaijan, Iran YÖKSİS SJR Q1 JCR Q1