Sample design optimization for soil mapping using improved artificial neural networks and simulated annealing-Reference-Cited by-同舟云学术

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Sample design optimization for soil mapping using improved artificial neural networks and simulated annealing

Published:2022-05 Issue: Volume:413 Page:115749
ISSN:0016-7061
Container-title:Geoderma
language:en
Short-container-title:Geoderma

Author:

Shao Shuangshuang^ORCID,Su Baowei,Zhang Yalu,Gao Chao,Zhang Ming,Zhang Huan,Yang Lin^ORCID

Publisher

Elsevier BV

Subject

Soil Science

Reference56 articles.

1. Improving response surface methodology by using artificial neural network and simulated annealing;Abbasi;Expert Syst. Appl.,2012

2. Digital soil mapping using artificial neural networks and terrain-related attributes;Bagheri Bodaghabadi;Pedosphere,2015

3. Prediction of pyrite oxidation in a coal washing waste pile using a hybrid method, coupling artificial neural networks and simulated annealing (ANN/SA);Bahrami;J. Cleaner Prod.,2016

4. Soil and agricultural chemistry analysis;Bao,2000

5. Artificial neural networks and decision tree classification for predicting soil drainage classes in Denmark;Beucher;Geoderma,2019

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1. Machine learning aided metaheuristics: A comprehensive review of hybrid local search methods;Expert Systems with Applications;2024-12

2. Sample Size Optimization for Digital Soil Mapping: An Empirical Example;Land;2024-03-14

3. Research on the Optimization of Sample Point Placement for Ground Substrate Survey based on Interpretable Machine Learning;2023 11th International Conference on Agro-Geoinformatics (Agro-Geoinformatics);2023-07-25

4. Improving the Performance of Automated Rooftop Extraction through Geospatial Stratified and Optimized Sampling;Remote Sensing;2022-10-05

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