Zobrazeno 1 - 8
of 8
pro vyhledávání: '"İlker Ercanlı"'
Autor:
İlker Ercanlı
Publikováno v:
Forest Ecosystems, Vol 7, Iss 1, Pp 1-18 (2020)
Abstract Background Deep Learning Algorithms (DLA) have become prominent as an application of Artificial Intelligence (AI) Techniques since 2010. This paper introduces the DLA to predict the relationships between individual tree height (ITH) and the
Externí odkaz:
https://doaj.org/article/be975e05c5d94488af4bb0e73bb633ce
Publikováno v:
Forest Ecosystems, Vol 5, Iss 1, Pp 1-12 (2018)
Abstract Background Leaf Area Index (LAI) is an important parameter used in monitoring and modeling of forest ecosystems. The aim of this study was to evaluate performance of the artificial neural network (ANN) models to predict the LAI by comparing
Externí odkaz:
https://doaj.org/article/939a8610490f4ac1995c62c772141853
Autor:
Abdurrahman SAHIN, Ilker ERCANLI
Publikováno v:
Forest Systems, Vol 32, Iss 3 (2023)
Aim of study: To assess the capabilities of some infrequently used probability density functions (PDFs) in modeling stand diameter distributions and compare their performance to that of typical PDFs. Area of study: The research was conducted in pu
Externí odkaz:
https://doaj.org/article/f1732667e4744223a99090c288617bbc
Publikováno v:
Artvin Çoruh Üniversitesi Orman Fakültesi Dergisi, Vol 5, Iss 2, Pp 165-171 (2004)
In this study, classical methods used to estimate biomass of forest stands the base of biological energy resources, and remote sensing methods on which many study have been done recently were explained. Furthermore, these methods were compared. It wa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doajarticles::2206b84bf7af1a0323cf116f57c39dc4
http://ofd.artvin.edu.tr/issue/2254/29699
http://ofd.artvin.edu.tr/issue/2254/29699
Publikováno v:
Forest Systems, Vol 32, Iss 1 (2023)
Aim of study: This paper introduces comparative evaluations of artificial neural network models and regression modeling techniques based on some fitting statistics and desirable characteristics for predicting dominant height. Area of study: The da
Externí odkaz:
https://doaj.org/article/57e869be5b274b74bc2b7370695798ff
Autor:
İlker Ercanli
Publikováno v:
Forest Systems, Vol 29, Iss 2, Pp e013-e013 (2020)
Aim of Study: As an innovative prediction technique, Artificial Intelligence technique based on a Deep Learning Algorithm (DLA) with various numbers of neurons and hidden layer alternatives were trained and evaluated to predict the relationships betw
Externí odkaz:
https://doaj.org/article/dbf808199a794fffa6f7051f5e91f9ce
Publikováno v:
Scientia Agricola, Vol 72, Iss 3, Pp 245-251 (2015)
Diameter at breast height (DBH) is the simplest, most common and most important tree dimension in forest inventory and is closely correlated with wood volume, height and biomass. In this study, a number of linear and nonlinear models predicting diame
Externí odkaz:
https://doaj.org/article/7cfc9cbc1d494a8f867516c62aa775f1
Autor:
Ilker Ercanli
Publikováno v:
Revista Chapingo: Serie Ciencias Forestales y del Ambiente, Vol 21, Iss 2, Pp 185-202 (2015)
Modelos estadísticos no lineales de efectos mixtos se utilizaron para predecir las relaciones entre la altura total y el diámetro a la altura del pecho (DAP) en rodales de árboles de haya oriental (Fagus orientalis Lipsky) en Kestel, Bursa, al nor
Externí odkaz:
https://doaj.org/article/29c889576fce41429dff026cdec3908e