A5015773594- Geochemistry and Geologic Mapping
- Mineral Processing and Grinding
- Remote-Sensing Image Classification
- Hydrocarbon exploration and reservoir analysis
- Geological and Geochemical Analysis
- Natural Language Processing Techniques
- Language and cultural evolution
- Marine Ecology and Invasive Species
- Environmental DNA in Biodiversity Studies
- Soil Geostatistics and Mapping
- Heavy metals in environment
- Underwater Acoustics Research
- Target Tracking and Data Fusion in Sensor Networks
- Advanced SAR Imaging Techniques
- Dynamics and Control of Mechanical Systems
- Engineering Structural Analysis Methods
- Syntax, Semantics, Linguistic Variation
- Inertial Sensor and Navigation
- Fault Detection and Control Systems
- Mechanical Engineering and Vibrations Research
- Maritime Navigation and Safety
- Advanced Computational Techniques and Applications
- Advanced X-ray and CT Imaging
- Geoscience and Mining Technology
- Industrial Technology and Control Systems
Chengdu University of Technology
2014-2024
China Academy of Launch Vehicle Technology
2021
Huaqiao University
2017-2019
Anhui Jianzhu University
2019
Institute of Geochemistry
2014-2016
Neusoft (China)
2012
Heilongjiang University of Science and Technology
2010
Chengdu University of Information Technology
2007
Mineral Prospectivity Mapping (MPM) plays a pivotal role in identifying geo-anomalies that are indicative of potential mineralization, drawing upon various geological, geophysical, geochemical, and remote sensing data. With the increasing availability such data recent years, data-driven MPM methods have proven effective discovering new mineral deposits, especially when utilizing machine learning techniques to unveil complex relationships between exploration occurrences. Deep learning,...
This study comprehensively analyzed air pollution in Chengdu (CD), a megacity southwest China, evaluated the Variation Characteristics of quality during 2015–2018, and conducted Random Forest classification data 2017. The results showed three periods: severe (December, January February), ozone (May‒August), slight (March November). These features were combined with potential source contribution function (PSCF), concentration weighted trajectory (CWT) backward model (HYSPLIT) for simulating...
The effective integration of geochemical data with multisource geoscience is a necessary condition for mapping mineral prospects. In the present study, based on maximum entropy principle, model (MaxEnt model) was established to predict potential distribution copper deposits by integrating 43 ore-controlling factors from geological, and geophysical data. MaxEnt used screen factors, eight (i.e., stratigraphic combination entropy, structural iso-density, Cu, Hg, Li, La, U, Na2O) were selected...
This paper focuses on researching the scientific problem of deep extraction and inference favorable geological geochemical information about mineralization at depth, based which a mineral resources prediction model is established machine learning approaches are used to carry out quantitative prediction. The main contents include: (i) discussing method 3D anomaly under multi-fractal content-volume (C-V) models, extracting 12 element anomalies constructing data volume for laying foundation...
This paper focuses on the scientific problem of quantitative mineralization prediction at large depth in Zaozigou gold deposit, west Qinling, China. Five geological and geochemical indicators are used to establish model. Machine learning Deep algorithms employed for 3D Mineral Prospectivity Mapping (MPM). Especially, Student Teacher Ore-induced Anomaly Detection (STOAD) model is proposed based knowledge distillation (KD) idea combined with Auto-encoder (DAE) network Compared DAE, STOAD uses...
To address the issue of low interpretability in deep learning-based methods for mining multi-layer features from synthetic aperture radar (SAR) target samples, non-negative matrix factorization (DNMF) technique is proposed. However, DNMF needs to face trade-off between high-precision recognition and efficient feature extraction as number SAR samples increases. In this letter, we propose <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</i>...
Deep-seated mineralization prediction is an important scientific problem in the area of mineral resources exploration. The 3D metallogenic information extraction geology and geochemistry can be great help. This study uses modeling technology to intuitively depict spatial distribution orebodies, fractures, intrusive rocks. In particular, geochemical models 12 elements are established for extraction. Subsequently, front halo element association As-Sb-Hg, near-ore Au-Ag-Cu-Pb-Zn, tail W-Mo-Bi...
The smoothing effect of data interpolation could cause useful information loss in geochemical mapping, and the uncertainty assessment anomaly help to extract reasonable anomalies. In this paper, multiple-point geostatistical simulation local singularity analysis (LSA) are proposed identify regional anomalies potential mineral resources areas. Taking Cu Mila Mountain Region, southern Tibet, as an example, several conclusions were obtained: (1) mapping based on direct sampling (DS) algorithm...
Geochemical data processing plays an important role in the process of geochemical prospecting. According to nonlinear characteristics data, wavelet adaptive multi-threshold based on generalized cross-validation (GCV) criterion was adopted towards preprocessing and good results are also achieved by validation practical work area.
A geological anomaly is the basis of mineral deposit prediction. Through study knowledge and characteristics anomalies, category extreme value theory (EVT) to which a belongs can be determined. Associating principle EVT ensuring methods shape parameter scale for generalized Pareto distribution (GPD), select threshold GPD studied. This paper designs new algorithm called model anomaly. These data on Cu Au originate from 26 exploration lines Jiguanzui Cu-Au mining area in Hubei, China. The...