Comparing multivariate regression and artificial neural network to predict barley production from soil characteristics in northern Iran

Multivariate Regression ◽

Soil Characteristics ◽

Northern Iran ◽

Detection of common citrus pests in northern Iran using an artificial neural network

Food Science and Technology ◽

10.52547/fsct.17.109.143 ◽

2021 ◽

Vol 17 (109) ◽

pp. 143-152

Author(s):

Morteza Khanramaki ◽

Ezzatollah Askari Asli‐Ardeh ◽

Ehsan Kozegar ◽

reihaneh loni ◽

◽

...

Keyword(s):

Neural Network ◽

Northern Iran ◽

Artificial Neural ◽

Citrus Pests

A comparative study of the performance of artificial neural network and multivariate regression in simulating springs discharge in the Caspian Southern Watersheds, Iran

Applied Water Science ◽

10.1007/s13201-018-0886-4 ◽

2018 ◽

Vol 9 (1) ◽

Author(s):

V. Gholami ◽

M. R. Khaleghi

Keyword(s):

Neural Network ◽

Comparative Study ◽

Multivariate Regression ◽

Hourly predictive artificial neural network and multivariate regression tree models of Alternaria and Cladosporium spore concentrations in Szczecin (Poland)

International Journal of Biometeorology ◽

10.1007/s00484-009-0243-2 ◽

2009 ◽

Vol 53 (6) ◽

pp. 555-562 ◽

Cited By ~ 12

Author(s):

Agnieszka Grinn-Gofroń ◽

Agnieszka Strzelczak

Keyword(s):

Neural Network ◽

Multivariate Regression ◽

Regression Tree ◽

Multivariate Regression Tree ◽

Tree Models ◽

Modelling and estimation of Wide Wheel abrasion values of building stones by multivariate regression and artificial neural network analyses

Journal of Building Engineering ◽

10.1016/j.jobe.2021.103443 ◽

2022 ◽

Vol 45 ◽

pp. 103443

Author(s):

Sefer Beran Çelik ◽

İbrahim Çobanoğlu

Keyword(s):

Neural Network ◽

Multivariate Regression ◽

Building Stones ◽

Network Analyses ◽

Earthquake-induced landslide prediction using back-propagation type artificial neural network: case study in northern Iran

Natural Hazards ◽

10.1007/s11069-021-04963-8 ◽

2021 ◽

Author(s):

Ali M. Rajabi ◽

Mahdi Khodaparast ◽

Mostafa Mohammadi

Keyword(s):

Neural Network ◽

Back Propagation ◽

Landslide Prediction ◽

Northern Iran ◽

Predicting rainfed wheat quality and quantity by artificial neural network using terrain and soil characteristics

Acta Agriculturae Scandinavica Section B - Soil & Plant Science ◽

10.1080/09064710903005682 ◽

2010 ◽

Vol 60 (4) ◽

pp. 341-352 ◽

Cited By ~ 3

Author(s):

M. Norouzi ◽

S. Ayoubi ◽

A. Jalalian ◽

H. Khademi ◽

A.A. Dehghani

Keyword(s):

Neural Network ◽

Soil Characteristics ◽

Wheat Quality ◽

Artificial Neural ◽

Rainfed Wheat

Prediction of the shear strength parameters from easily-available soil properties by means of multivariate regression and artificial neural network methods

Geomechanics and Geoengineering ◽

10.1080/17486025.2020.1778194 ◽

2020 ◽

pp. 1-13

Author(s):

Mojtaba Mohammadi ◽

Seyed Mahmoud Fatemi Aghda ◽

Mehdi Talkhablou ◽

Akbar Cheshomi

Keyword(s):

Neural Network ◽

Shear Strength ◽

Soil Properties ◽

Multivariate Regression ◽

Shear Strength Parameters ◽

Strength Parameters ◽

Network Methods ◽

Predicting Cation Exchange Capacity by Artificial Neural Network and Multiple Linear Regression Using Terrain and Soil Characteristics

Indian Journal of Science and Technology ◽

10.17485/ijst/2015/v8i28/83328 ◽

2015 ◽

Vol 8 (28) ◽

Cited By ~ 3

Author(s):

Asma Shabani ◽

Mojtaba Norouzi

Keyword(s):

Neural Network ◽

Linear Regression ◽

Multiple Linear Regression ◽

Cation Exchange ◽

Cation Exchange Capacity ◽

Soil Characteristics ◽

Exchange Capacity ◽

Comparison of artificial neural network and multivariate regression models for prediction of Azotobacteria population in soil under different land uses

Computers and Electronics in Agriculture ◽

10.1016/j.compag.2017.06.019 ◽

2017 ◽

Vol 140 ◽

pp. 409-421 ◽

Cited By ~ 16

Author(s):

Mitra Ebrahimi ◽

Ali Akbar Safari Sinegani ◽

Mohammad Reza Sarikhani ◽

Seyed Abolghasem Mohammadi

Keyword(s):

Neural Network ◽

Multivariate Regression ◽

Regression Models ◽

Land Uses ◽

Prediction of standard particleboard mechanical properties utilizing an artificial neural network and subsequent comparison with a multivariate regression model

Investigación Agraria Sistemas y Recursos Forestales ◽

10.5424/srf/2008172-01033 ◽

2008 ◽

Vol 17 (2) ◽

pp. 178 ◽

Cited By ~ 18

Author(s):

F. García Fernández ◽

L. García Esteban ◽

P. De Palacios ◽

M. Navarro ◽

M. Conde

Keyword(s):

Neural Network ◽

Mechanical Properties ◽

Regression Model ◽

Multivariate Regression ◽

Multivariate Regression Model ◽

Artificial Neural ◽

Subsequent Comparison