池深深｜安徽理工大学｜学者主页

2026

A High-Precision Monitoring Method for Surface Subsidence in Western Chinese Mining Areas by Fusing InSAR and LiDAR

Dayong Xu, Tao Wei, Lei Wang, Jingyu Li, Shenshen Chi, Xiaohan Liu

Remote Sensing

DOI

2026

LuTan-1 InSAR-Constrained Reconstruction of Concealed Coal-Mining Working-Face Geometry

Shenshen Chi, Bingqian Yang, Lei Wang, Jiajia Yuan, Qingbiao Guo, Xuexiang Yu

Remote Sensing

DOI

2025

基于SBAS-InSAR和CNN-GRU模型的采动村庄地表沉降监测预计

陈月，王磊，池深深，王羽，戚鑫鑫，朱尚军

《金属矿山》

DOI

2025

基于机载LiDAR的山区沉陷监测与预计一体化方法

徐大永，王磊，魏涛，池深深，陈元非

《金属矿山》

DOI

2025

An Intelligent Identification Method for Coal Mining Subsidence Basins Based on Deformable DETR and InSAR

Shenshen Chi, Dexian An, Lei Wang, Sen Du, Jiajia Yuan, Meinan Zheng, Qingbiao Guo

Remote Sensing

DOI

2025

Robust Parameter Inversion and Subsidence Prediction for Probabilistic Integral Methods in Mining Areas

Xinjian Fang, Rui Yang, Mingfei Zhu, Jinling Duan, Shenshen Chi

Applied Sciences

DOI

2024

一种复杂地形场景点云的WOA-CSF自适应性滤波方法

戚鑫鑫，王磊，储栋，池深深

《激光与红外》

2024

Method of Predicting Dynamic Deformation of Mining Areas Based on Synthetic Aperture Radar Interferometry (InSAR) Time Series Boltzmann Function

Shenshen Chi, Xuexiang Yu, Lei Wang

Applied Sciences

DOI

2023

A New Method for Calculating Prediction Parameters of Surface Deformation in the Mining Area

Shenshen Chi, Lei Wang, Xuexiang Yu

Applied Sciences

DOI

2022

Improved mining subsidence prediction model for high water level area using machine learning and chaos theory

Xu Yang, Xingda Chen, Xinjian Fang, Shenshen Chi, Mingfei Zhu

Energy Exploration & Exploitation

DOI

2021

耦合拐点偏移修正的Boltzmann函数预计模型及其参数反演方法

江克贵，王磊，池深深，魏涛，蒋创

《采矿与岩层控制工程学报》

DOI

2021

深井开采地表移动变形响应时空关联模型研究及应用

池深深

《安徽理工大学》

2021

Research on dynamic prediction model of surface subsidence in mining areas with thick unconsolidated layers

Shenshen Chi, Lei Wang, Xuexiang Yu, Weicai Lv, Xinjian Fang

Energy Exploration & Exploitation

DOI

2021

Research on Prediction Model of Mining Subsidence in Thick Unconsolidated Layer Mining Area

Shenshen Chi, Lei Wang, Xuexiang Yu, Xinjian Fang, Chuang Jiang

IEEE Access

DOI

2020

融合混沌残差的BP强预测器的地表下沉预测模型

陈兴达，余学祥，池深深，蒋创，赵祥硕

《大地测量与地球动力学》

DOI

2020

基于多种群遗传算法的概率积分法参数反演

陈兴达，余学祥，池深深，汪涛，陈卫卫

《煤矿安全》

DOI

2020

开采沉陷形变监测云平台的设计与实现

彭小强，池深深，石长伟，陈卫卫，陈佩文

《安徽理工大学学报(自然科学版)》

2020

DPIM-Based InSAR Phase Unwrapping Model and a 3D Mining-Induced Surface Deformation Extracting Method: A Case of Huainan Mining Area

Chuang Jiang, Lei Wang, Xuexiang Yu, Shenshen Chi, Wei Jun Tao, Xuelin Wang

KSCE Journal of Civil Engineering

DOI

2020

Estimation of parameters of probability integral method model based on improved fireworks algorithm

Lei Wang, Kegui Jiang, Tao Wei, Chuang Jiang, Jianfeng Zha, Shenshen Chi

Survey Review

DOI

2019

概率积分预计参数的神经网络优化算法

吕伟才，黄晖，池深深，韩必武

《测绘科学》

DOI

2019

基于PCA-BP神经网络的概率积分法参数算法研究

黄晖，池深深，韩必武，刘可胜

《黑龙江科学》

2019

Robust Estimation of Angular Parameters of the Surface Moving Basin Boundary Induced by Coal Mining: A Case of Huainan Mining Area

Lei Wang, Chuang Jiang, Tao Wei, Nan Li, Shenshen Chi, Jianfeng Zha, Su-yang Fang

KSCE Journal of Civil Engineering

DOI

2018

融合InSAR和GA的开采沉陷预计参数反演模型研究

王磊，张鲜妮，池深深，查剑锋

《武汉大学学报(信息科学版)》

2018

基于模矢法的顾桥矿采空区参数识别

蒋创，王磊，魏涛，池深深，方苏阳，郭庆彪

《金属矿山》

2018

基于ARMA-BP变异系数组合模型的矿山沉陷预计

方苏阳，吕鑫，池深深，郭庆彪，魏涛

《矿山测量》

2018

顾及数据新鲜度函数Knothe的开采沉陷最优组合预测模型及应用

池深深，王磊，李楠，魏涛，韩文权

《煤矿安全》

2018

基于量子遗传算法的概率积分参数反演

魏涛，王磊，李楠，池深深，蒋创

《金属矿山》

2018

基于时间序列的动态神经网络沉降预测

方苏阳，蒋创，魏涛，池深深，李楠

《测绘与空间地理信息》

2018

Research on probability integration parameter inversion of mining-induced surface subsidence based on quantum annealing

Lei Wang, Wei Jun Tao, Nan Li, Shenshen Chi, Chuang Jiang, Su-yang Fang

Environmental Earth Sciences

DOI

2017

矿区地表沉陷的D-InSAR监测方法

李楠，王磊，池深深，魏涛，吕挑

《金属矿山》

2017

融合多源求参结果的开采沉陷稳健预计方法

王磊，魏涛，池深深，陈元非

《煤矿安全》

2017

开采沉陷动态精准预计的时效Knothe函数方法研究

魏涛，王磊，池深深，李楠，吕挑

《金属矿山》

2017

井下等边直伸形方向附合导线优化方法及平差通用模型研究

池深深，王磊，魏涛，李楠，吕挑

《金属矿山》

池深深

精选作品

期刊论文

A High-Precision Monitoring Method for Surface Subsidence in Western Chinese Mining Areas by Fusing InSAR and LiDAR

LuTan-1 InSAR-Constrained Reconstruction of Concealed Coal-Mining Working-Face Geometry

基于SBAS-InSAR和CNN-GRU模型的采动村庄地表沉降监测预计

基于机载LiDAR的山区沉陷监测与预计一体化方法

An Intelligent Identification Method for Coal Mining Subsidence Basins Based on Deformable DETR and InSAR

Robust Parameter Inversion and Subsidence Prediction for Probabilistic Integral Methods in Mining Areas

一种复杂地形场景点云的WOA-CSF自适应性滤波方法

Method of Predicting Dynamic Deformation of Mining Areas Based on Synthetic Aperture Radar Interferometry (InSAR) Time Series Boltzmann Function

A New Method for Calculating Prediction Parameters of Surface Deformation in the Mining Area

Improved mining subsidence prediction model for high water level area using machine learning and chaos theory

耦合拐点偏移修正的Boltzmann函数预计模型及其参数反演方法

深井开采地表移动变形响应时空关联模型研究及应用

Research on dynamic prediction model of surface subsidence in mining areas with thick unconsolidated layers

Research on Prediction Model of Mining Subsidence in Thick Unconsolidated Layer Mining Area

融合混沌残差的BP强预测器的地表下沉预测模型

基于多种群遗传算法的概率积分法参数反演

开采沉陷形变监测云平台的设计与实现

DPIM-Based InSAR Phase Unwrapping Model and a 3D Mining-Induced Surface Deformation Extracting Method: A Case of Huainan Mining Area

Estimation of parameters of probability integral method model based on improved fireworks algorithm

概率积分预计参数的神经网络优化算法

基于PCA-BP神经网络的概率积分法参数算法研究

Robust Estimation of Angular Parameters of the Surface Moving Basin Boundary Induced by Coal Mining: A Case of Huainan Mining Area

融合InSAR和GA的开采沉陷预计参数反演模型研究

基于模矢法的顾桥矿采空区参数识别

基于ARMA-BP变异系数组合模型的矿山沉陷预计

顾及数据新鲜度函数Knothe的开采沉陷最优组合预测模型及应用

基于量子遗传算法的概率积分参数反演

基于时间序列的动态神经网络沉降预测

Research on probability integration parameter inversion of mining-induced surface subsidence based on quantum annealing

矿区地表沉陷的D-InSAR监测方法

融合多源求参结果的开采沉陷稳健预计方法

开采沉陷动态精准预计的时效Knothe函数方法研究

井下等边直伸形方向附合导线优化方法及平差通用模型研究

研究方向