A5100656735- Geophysical and Geoelectrical Methods
- Seismic Waves and Analysis
- Remote Sensing and Land Use
- Earthquake Detection and Analysis
- Geophysical Methods and Applications
- Underwater Acoustics Research
- Seismic Imaging and Inversion Techniques
- Advanced Computational Techniques and Applications
- Nanomaterials for catalytic reactions
- Environmental Changes in China
- Geophysics and Sensor Technology
- Geochemistry and Geologic Mapping
- Catalytic Processes in Materials Science
- Seismology and Earthquake Studies
- Catalysis and Hydrodesulfurization Studies
- Nuclear Materials and Properties
- Advanced Algorithms and Applications
- Computational Physics and Python Applications
- stochastic dynamics and bifurcation
- Metal-Organic Frameworks: Synthesis and Applications
- Geoscience and Mining Technology
- E-commerce and Technology Innovations
- Covalent Organic Framework Applications
- Blind Source Separation Techniques
- Radar Systems and Signal Processing
Guangzhou Automobile Group (China)
2024
Chinese Academy of Geological Sciences
2016-2023
Ministry of Natural Resources
2020-2022
China University of Petroleum, Beijing
2020-2021
China University of Mining and Technology
2020-2021
China University of Petroleum, East China
2017-2020
National University of Defense Technology
2018
Central South University
2015
University of Southern California
2014
Shaanxi Normal University
2009
In this letter, two machine learning algorithms are improved, including a sample-compressed neural network algorithm for magnetotelluric (MT) inversion and an adaptive-clustering analysis boundary demarcation. MT is widely used in deep geological structure exploration; however, data processing interpretation still need to be further improved. Inverting the underground electrical model from surface electromagnetic response highly nonlinear optimization problem. Common quasi-linear rely on...
While they are an effective tool for studying landscape patterns and describing land-use change, metrics sensitive to variation in spatial grain sizes.It is therefore crucially important select optimal size characterizing urban patterns.Due accelerated urbanization, Shanghai, the economic capital of China, has seen drastic changes recent decades it would be interesting take Shanghai as example examining effect patterns.In this study, from Shanghai's land use maps derived Landsat images 1998,...
Induced polarization (IP) is a widely used geophysical exploration technique. Continuous random noise one of the most prevalent interferences that can seriously contaminate IP signal and distort apparent electrical characteristics. We develop separation algorithm based on deep learning to overcome this issue. The standard signals are first produced by combining Cole-Cole model Fourier series decomposition, then mathematical simulation generate various types interferences, which subsequently...
In audio magnetotelluric (AMT) sounding data processing, the absence of sferic signals in some time ranges results a lack energy AMT dead band, causing unreliable resistivity estimations. To address this issue, we develop deep convolutional neural network (CNN) to automatically recognize from redundantly recorded over long range and use these accurately estimate resistivity. The CNN is trained using field time-series with different signal-to-noise ratios (S/Ns) acquired regions mainland...
Volcanic activity remains highly detrimental to populations, property and activities in the range of its products. In order reduce impact volcanic processes products, it is critically important conduct comprehensive risk assessments on volcanically active areas. This study tests a assessment methodology based numerical simulations hazards quantitative analysis social vulnerability Spanish island Tenerife, well-known tourist destination. We first simulated most likely two eruptive scenarios...
In near surface electrical exploration, it is often necessary to estimate the Cole-Cole model parameters according measured multi-frequency complex resistivity spectrum of ore and rock samples in advance. Parameter estimation a nonlinear optimization problem, common method least square fitting. The disadvantage this that relies on initial value result unstable when data confronted with noise interference. To further improve accuracy parameter estimation, paper applied artificial neural...
Controlled-source audio-frequency magnetotellurics (CSAMT) has been seriously affected by strong electromagnetic interferences including large-scale drift, durative outbreak interference, and impulsive outliers. To improve the efficiency of noise reduction, a deep learning strategy was proposed to identify type so as select appropriate reduction method. First, CSAMT time series simulation algorithm developed based on current decomposition one-dimensional (1D) forward modeling. Three kinds...
In this paper, a new method for bridge disease image segmentation is introduced, in which the data set includes exp_rebar, breakage, patch and joint. The proposed uses YOLOv8 model to partition region of interest, serves as cue input Segment Anything Model (SAM) high-quality HQ-SAM pre-trained large model, performs automatic accurate based on this. study, three evaluation indexes including accuracy, recall rate F1 score were used quantify accuracy results YOLOv8, YOLOv8+SAM YOLOv8+HQ-SAM...
Abstract Induced polarization (IP) is a near-surface geophysical exploration method. Inverting the electrical properties of underground medium from surface apparent IP parameters highly nonlinear problem. To further improve accuracy, artificial neural network (ANN) algorithm applied to two-dimensional (2D) data inversion for first time. We firstly produced smooth geo-electric models based on stochastic theory, and obtained corresponding theoretical responses through forward modelling. Then,...
Induced polarization (IP) is an effective geophysical method for characterizing near-surface complex resistivity structures. To improve the precision and efficiency of massive-scale exploration, a large-scale distributed full-waveform IP system developed intelligent signal processing technology proposed first time. The testing practical data show that quality can be extremely improved by acquisition anti-interference processing.
PreviousNext You have accessSymposium on the Application of Geophysics to Engineering and Environmental Problems 2015Airborne Geophysics, Remote Sensing, UAV (Drone)-based Surveys Mining GeophysicsAuthors: Andi PfaffhuberHelgard AnschuetzHamed RafeziAlexandre NovoFerri P. HassaniK. I. SorensenWeiqiang LiuRujun ChenHong WuJieting QiuHongchun YaoRuijie ShenQiang RenFuguo ChangPei ZengWeibin LuoGreg HodgesDouglas GarrieAndi PfaffhuberCraig ChristensenHelgard AnschuetzJean M. LegaultDavid...
We focuses on the problem that noise will affect calculation of fractal dimension feature parameters, using method superimposing original nonlinear signal, designing a specific experimental procedure, and studying ability resisting interference. Experimental results show signal has certain degree immunity, but when SNR (signal to ratio) is reduced extent, influence gradually increases until characteristics cannot be manifested. Therefore, can resist interference it also reflect by noise. It...
The 27th IEEE Symposium on Computer Arithmetic, ARITH-2020, was initially planned to be held in Portland, Oregon, USA Jun 7-10, 2020. Due the Covid-19 crisis all around world 2020, face-to-face meeting has been canceled. paper selection process completed, and accepted papers have included ARITH-2020 proceedings. For 73 anonymous submissions submitted at beginning of February. Following peer-review practice this symposium, each blind-reviewed by least three, up five, Program Committee...