İlker Ercanlı

Akademik Profiller

1. 1
   Deep learning algorithms for addressing overfitting and biological realism in tree taper and volume predictionsCanadian Journal of Forest Research
   2024
2. 2
   ÇAKÜ Araştırma Ormanı Karaçam meşcereleri için tek ve çift girişli toprak üstü ağaç biyokütle denklemlerinin geliştirilmesiAnadolu Orman Araştırmaları Dergisi
   2024
3. 3
   An evaluation of various probability density functions for predicting diameter distributions in pure and mixed-species stands in TürkiyeForest Systems
   2023
4. 4
   Karışık etkili modelleme yaklaşımıyla karaçam hacim denklemlerinin geliştirilmesiOrmancılık Araştırma Dergisi
   2023
5. 5
   A comparison of artificial neural networks and regression modeling techniques for predicting dominant heights of Oriental spruce in a mixed standForest Systems
   2023
6. 6
   Artificial intelligence with deep learning algorithms to model relationships between total tree height and diameter at breast heightForest Systems
   2020
7. 7
   Artificial neural network models by ALOS PALSAR data for aboveground stand carbon predictions of pure beech stands: a case study from northern of TurkeyGeocarto International
   2018
8. 8
   Positive effect of forest structural diversity on aboveground stand carbon stocks for even-aged Scots pine (Pinus sylvestris L.) stands in the Sarıçiçek Forest, Northern TurkeyScandinavian Journal of Forest Research
   2018
9. 9
   Estimation of leaf area index using WorldView-2 and Aster satellite image: a case study from TurkeyEnvironmental Monitoring and Assessment
   2017
10. 10
    Taper equations based on nonlinear mixed effect modeling approach for Pinus nigra in Çankırı forests,Ecuaciones de ahusamiento basadas en un enfoque de modelado no lineal de efectos mixtos para Pinus nigra en bosques de ÇankırıBosque
    2017

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