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Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
机构
地理科学与资源研究... [10]
沈阳应用生态研究所 [1]
沈阳自动化研究所 [1]
烟台海岸带研究所 [1]
采集方式
OAI收割 [13]
内容类型
期刊论文 [10]
SCI/SSCI论文 [3]
发表日期
2025 [1]
2024 [2]
2023 [1]
2022 [1]
2021 [4]
2015 [2]
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A feature selection-based hybrid model for accurate spatial prediction of potentially toxic elements in sediments: Application to Poyang Lake, China
期刊论文
OAI收割
JOURNAL OF HAZARDOUS MATERIALS, 2025, 卷号: 498, 页码: 140008
作者:
Guo, Guanghui
;
Anjiang, Meiduo
;
Zhang, Ruiqing
;
Wei, Chaoyang
;
Lei, Mei
  |  
收藏
  |  
浏览/下载:1/0
  |  
提交时间:2025/11/17
Machine learning
Spatial distribution prediction
Environmental predictors
Sediments
Potentially toxic elements
Effect of ocean dynamic processes on the temporal-spatial pattern of persistent organic pollutants (PCB-153 and BDE-47) in the shelf seas
期刊论文
OAI收割
JOURNAL OF HAZARDOUS MATERIALS, 2024, 卷号: 480, 页码: 11
作者:
Wang, Aobo
;
Guo, Xinyu
;
Ding, Xiaokun
;
Shi, Jie
;
Tang, Jianhui
  |  
收藏
  |  
浏览/下载:58/0
  |  
提交时间:2025/01/10
Coupled model
Bottom cold water mass
Spatial distribution
Persistent organic pollutants
Prediction function
Coking exhaust contributes to airborne particulate matter in the Beijing-Tianjin-Hebei region
期刊论文
OAI收割
HELIYON, 2024, 卷号: 10, 期号: 10, 页码: e31359
作者:
Wan, Xiaoming
;
Zeng, Weibin
;
Gu, Gaoquan
  |  
收藏
  |  
浏览/下载:54/0
  |  
提交时间:2024/09/19
Air quality
Land use
Model validation
Prediction
Spatial distribution
Spatial prediction of soil contamination based on machine learning: a review
期刊论文
OAI收割
FRONTIERS OF ENVIRONMENTAL SCIENCE & ENGINEERING, 2023, 卷号: 17, 期号: 8
作者:
Zhang, Yang
;
Lei, Mei
;
Li, Kai
;
Ju, Tienan
  |  
收藏
  |  
浏览/下载:73/0
  |  
提交时间:2023/04/06
Soil contamination
Machine learning
Prediction
Spatial distribution
Ocean Temperature Prediction Based on Stereo Spatial and Temporal 4-D Convolution Model
期刊论文
OAI收割
IEEE Geoscience and Remote Sensing Letters, 2022, 卷号: 19, 页码: 1-5
作者:
Zuo XY(左心怡)
;
Zhou XF(周晓锋)
;
Guo DQ(郭大权)
;
Li S(李帅)
;
Liu SR(刘舒锐)
  |  
收藏
  |  
浏览/下载:92/0
  |  
提交时间:2021/08/28
Convolution
Dual characteristics
Ocean temperature
ocean temperature prediction
Predictive models
Robots
Sea surface
Solid modeling
stereo spatial and temporal 4-D convolution model (SST-4D-CNN).
Temperature distribution
The karst NDVI correlation with climate and its BAS-BP prediction based on multiple factors
期刊论文
OAI收割
ECOLOGICAL INDICATORS, 2021, 卷号: 132, 页码: 12
作者:
Ma, Yuju
;
Zuo, Liyuan
;
Gao, Jiangbo
;
Liu, Qiang
;
Liu, Lulu
  |  
收藏
  |  
浏览/下载:56/0
  |  
提交时间:2022/09/21
Karst NDVI
Climate impact
BAS-BP prediction
Spatial distribution
Dynamic variation
The karst NDVI correlation with climate and its BAS-BP prediction based on multiple factors
期刊论文
OAI收割
ECOLOGICAL INDICATORS, 2021, 卷号: 132, 页码: 12
作者:
Ma, Yuju
;
Zuo, Liyuan
;
Gao, Jiangbo
;
Liu, Qiang
;
Liu, Lulu
  |  
收藏
  |  
浏览/下载:40/0
  |  
提交时间:2022/09/21
Karst NDVI
Climate impact
BAS-BP prediction
Spatial distribution
Dynamic variation
Mapping Rice Paddy Distribution Using Remote Sensing by Coupling Deep Learning with Phenological Characteristics
期刊论文
OAI收割
REMOTE SENSING, 2021, 卷号: 13, 期号: 7, 页码: 16
作者:
Zhu, A-Xing
;
Zhao, Fang-He
;
Pan, Hao-Bo
;
Liu, Jun-Zhi
  |  
收藏
  |  
浏览/下载:66/0
  |  
提交时间:2021/06/10
rice paddy distribution
remote sensing
phenological characteristics
deep learning
machine learning
spatial prediction
Mapping Rice Paddy Distribution Using Remote Sensing by Coupling Deep Learning with Phenological Characteristics
期刊论文
OAI收割
REMOTE SENSING, 2021, 卷号: 13, 期号: 7, 页码: 16
作者:
Zhu, A-Xing
;
Zhao, Fang-He
;
Pan, Hao-Bo
;
Liu, Jun-Zhi
  |  
收藏
  |  
浏览/下载:29/0
  |  
提交时间:2021/06/10
rice paddy distribution
remote sensing
phenological characteristics
deep learning
machine learning
spatial prediction
Maxent modeling for predicting the potential distribution of Sanghuang, an important group of medicinal fungi in China
期刊论文
OAI收割
FUNGAL ECOLOGY, 2015, 卷号: 17, 页码: 140-145
作者:
Wei, Yu-Lian
;
Wang, Xu-Gao
;
Yuan, Hai-Sheng
  |  
收藏
  |  
浏览/下载:53/0
  |  
提交时间:2019/06/04
Biogeographic Distribution
Fungal Fruiting Bodies
Maxent
Spatial Prediction Modeling