Discussion of “Generalized regression neural networks for evapotranspiration modelling”

Hafzullah Aksoy; Aytac Guven; Ali Aytek; M. Ishak Yuce; N. Erdem Unal

doi:10.1623/hysj.52.4.825

Discussion of “Generalized regression neural networks for evapotranspiration modelling”

Hydrological Sciences Journal ◽

10.1623/hysj.52.4.825 ◽

2007 ◽

Vol 52 (4) ◽

pp. 825-831 ◽

Cited By ~ 26

Author(s):

Hafzullah Aksoy ◽

Aytac Guven ◽

Ali Aytek ◽

M. Ishak Yuce ◽

N. Erdem Unal

Keyword(s):

Neural Networks ◽

Generalized Regression Neural Networks ◽

Generalized Regression

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Adaptive Trajectory Tracking Control for Quadrotors with Disturbances by Using Generalized Regression Neural Networks

Neurocomputing ◽

10.1016/j.neucom.2021.06.079 ◽

2021 ◽

Author(s):

Ivan Lopez-Sanchez ◽

Francisco Rossomando ◽

Ricardo Pérez-Alcocer ◽

Carlos Soria ◽

Ricardo Carelli ◽

...

Keyword(s):

Neural Networks ◽

Trajectory Tracking ◽

Tracking Control ◽

Trajectory Tracking Control ◽

Generalized Regression Neural Networks ◽

Generalized Regression

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Knowledge discovery in data streams with the orthogonal series-based generalized regression neural networks

Information Sciences ◽

10.1016/j.ins.2017.07.013 ◽

2018 ◽

Vol 460-461 ◽

pp. 497-518 ◽

Cited By ~ 15

Author(s):

Piotr Duda ◽

Maciej Jaworski ◽

Leszek Rutkowski

Keyword(s):

Neural Networks ◽

Knowledge Discovery ◽

Data Streams ◽

Orthogonal Series ◽

Generalized Regression Neural Networks ◽

Generalized Regression

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A Simulation Study for Performance Comparison between Generalized Linear Mixed Modeling (GLMM) and Generalized Regression Neural Networks (GRNN) in Joint Modeling of Mixed Responses

Tropical Agricultural Research ◽

10.4038/tar.v32i1.8441 ◽

2021 ◽

Vol 32 (1) ◽

pp. 49

Author(s):

J. C. Hapugoda ◽

M. R. Sooriyarachchi

Keyword(s):

Neural Networks ◽

Simulation Study ◽

Joint Modeling ◽

Performance Comparison ◽

Generalized Regression Neural Networks ◽

Mixed Responses ◽

Generalized Regression

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On the Global Convergence of the Parzen-Based Generalized Regression Neural Networks Applied to Streaming Data

Artificial Intelligence and Soft Computing - Lecture Notes in Computer Science ◽

10.1007/978-3-319-91253-0_3 ◽

2018 ◽

pp. 25-34

Author(s):

Jinde Cao ◽

Leszek Rutkowski

Keyword(s):

Neural Networks ◽

Global Convergence ◽

Streaming Data ◽

Generalized Regression Neural Networks ◽

Generalized Regression

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Generalized Regression Neural Networks with K-Fold Cross-Validation for Displacement of Landslide Forecasting

Advances in Neural Networks – ISNN 2014 - Lecture Notes in Computer Science ◽

10.1007/978-3-319-12436-0_59 ◽

2014 ◽

pp. 533-541 ◽

Cited By ~ 8

Author(s):

Ping Jiang ◽

Zhigang Zeng ◽

Jiejie Chen ◽

Tingwen Huang

Keyword(s):

Neural Networks ◽

Cross Validation ◽

Generalized Regression Neural Networks ◽

Landslide Forecasting ◽

Generalized Regression ◽

Fold Cross Validation

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Public transportation trip flow modeling with generalized regression neural networks

Advances in Engineering Software ◽

10.1016/j.advengsoft.2006.08.003 ◽

2007 ◽

Vol 38 (2) ◽

pp. 71-79 ◽

Cited By ~ 50

Author(s):

Hilmi Berk Celikoglu ◽

Hikmet Kerem Cigizoglu

Keyword(s):

Neural Networks ◽

Public Transportation ◽

Flow Modeling ◽

Generalized Regression Neural Networks ◽

Generalized Regression

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Generalized Regression Neural Networks Based HVDC Transmission Line Fault Localization

2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics ◽

10.1109/ihmsc.2015.103 ◽

2015 ◽

Cited By ~ 6

Author(s):

Hang Cui ◽

Niannian Tu

Keyword(s):

Neural Networks ◽

Transmission Line ◽

Fault Localization ◽

Hvdc Transmission ◽

Generalized Regression Neural Networks ◽

Generalized Regression

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Corporate reputation and market value: Evidence with generalized regression neural networks

Expert Systems with Applications ◽

10.1016/j.eswa.2015.10.028 ◽

2016 ◽

Vol 46 ◽

pp. 69-76 ◽

Cited By ~ 18

Author(s):

Manuel A. Fernández-Gámez ◽

Antonio M. Gil-Corral ◽

Federico Galán-Valdivieso

Keyword(s):

Neural Networks ◽

Corporate Reputation ◽

Market Value ◽

Generalized Regression Neural Networks ◽

Generalized Regression

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COMPARING THE PERFORMANCE OF PREDICTIVE MODELS CONSTRUCTED USING THE TECHNIQUES OF FEED - FORWORD AND GENERALIZED REGRESSION NEURAL NETWORKS

International Journal of Computer Systems & Software Engineering ◽

10.15282/ijsecs.2.2016.3.0017 ◽

2016 ◽

Vol 2 ◽

pp. 66-73

Author(s):

Adeleke Raheem Ajiboye ◽

◽

Ruzaini Abdullah Arshah ◽

Hongwu Qin ◽

Jamila Abdul Hadi ◽

...

Keyword(s):

Neural Networks ◽

Predictive Models ◽

Generalized Regression Neural Networks ◽

Generalized Regression

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Penerapan Generalized Regression Neural Networks untuk Memprediksi Produksi Padi Terhadap Perubahan Iklim

Jurnal Teknologi Rekayasa ◽

10.31544/jtera.v2.i2.2017.117-124 ◽

2017 ◽

Vol 2 (2) ◽

pp. 117 ◽

Cited By ~ 1

Author(s):

Muhammad Alkaff ◽

Yuslena Sari

Keyword(s):

Neural Networks ◽

Root Mean Square Error ◽

Mean Square Error ◽

Root Mean Square ◽

Input Data ◽

Mean Square ◽

Generalized Regression Neural Networks ◽

Data Output ◽

Generalized Regression

Padi sebagai bahan makanan pokok utama bagi masyarakat Indonesia merupakan tanaman pangan yang rentan terhadap perubahan iklim. Pendataan dan perhitungan ramalan hasil produksi padi sangat diperlukan untuk mendukung kebijakan yang berkaitan dengan ketahanan pangan. Penelitian ini bertujuan untuk melakukan peramalan terhadap produksi padi di Kabupaten Barito Kuala sebagai kabupaten penghasil padi terbesar di Kalimantan Selatan dengan menggunakan data iklim sebagai input. Data iklim yang digunakan berasal dari Stasiun Meteorologi Syamsudin Noor, sedangkan sebagai data output adalah data produksi padi dari Badan Pusat Statistika (BPS) Provinsi Kalimantan Selatan. Metode yang digunakan untuk melakukan peramalan produksi padi adalah Generalized Regression Neural Networks (GRNN). Dari hasil pengujian didapatkan nilai Root Mean Square Error (RMSE) sebesar 0,296 dengan menggunakan parameter smoothness bernilai 1.Kata kunci: padi, iklim, Barito Kuala, GRNN, RMSE

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