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Yin L, Guo Y, Wang L, Yuan S, Fang Z, Zhang B. 2026. A Dual-Transformer Network for Spatiotemporal Modeling of Carbon Dioxide Column Concentration (XCO2) on the Basis of Dynamic Heterogeneous Graphs[J]. Transactions in GIS,  30(3): e70275. DOI: 10.1111/tgis.70275.

Ma K, Zhan Q, Zhang T, Shi Y, Fang Z, Shah SYA, Kablan OABK, Zhang B. 2026. Geo-MAG: A Knowledge Graph (KG)-enhanced Multimodal Retrieval-Augmented Generation (RAG) Framework for Geological Map Understanding[J]. Transactions in GIS,  30(2): e70226. DOI: 10.1111/tgis.70226.

Fang Z, Zhang T, Cai W, Shi Y, Shah SYA, Kablan OABK, Zhang B. 2026. Three-dimensional geological modeling based on dual-task stratigraphy-aware attention networks (Geo-SAN v1.0)[J]. Geosci. Model Dev.,  19(17): 8407-8426. DOI: 10.5194/gmd-19-8407-2026.

Du L, Du J, Fang Z, Shah SYA, Kablan OABK, Zhang B, Tan J. 2026. A Recurrent Neural Network Surrogate Model with Few-Shot Strategy for CO2 Storage in Deep Subsurface Saline Aquifer with Limited Direct Numerical Simulation Samples[J]. Lithosphere,  2026(2). DOI: 10.2113/lithosphere_2025_139.

Dong Z, Su Y, Zhang Y, Wang L, Yuan S, Zhang B. 2025. Locating and profiling city street trees using Baidu street view images for carbon storage evaluation[J]. Ecological Informatics,  91: 103394. DOI: 10.1016/j.ecoinf.2025.103394.

Zhang B, Xu Z, Wei X, Song L, Shah SYA, Khan U, Du L, Li X. 2024. Deep Subsurface Pseudo-Lithostratigraphic Modeling Based on Three-Dimensional Convolutional Neural Network (3D CNN) Using Inversed Geophysical Properties and Shallow Subsurface Geological Model[J]. Lithosphere,  2024(1). DOI: 10.2113/2024/lithosphere_2023_273.

Zhang B, Tang J, Huan Y, Song L, Shah SYA, Wang L. 2024. Multi-scale convolutional neural networks (CNNs) for landslide inventory mapping from remote sensing imagery and landslide susceptibility mapping (LSM)[J]. Geomatics, Natural Hazards and Risk,  15(1): 2383309. DOI: 10.1080/19475705.2024.2383309.

Wang L, Jiang Z, Song L, Yu X, Yuan S, Zhang B. 2024. A groundwater level spatiotemporal prediction model based on graph convolutional networks with a long short-term memory[J]. Journal of Hydroinformatics,  26(11): 2962-2979. DOI: 10.2166/hydro.2024.226.

Zhang B, Xu K, Khan U, Li X, Du L, Xu Z. 2023. A lightweight convolutional neural network with end-to-end learning for three-dimensional mineral prospectivity modeling: A case study of the Sanhetun Area, Heilongjiang Province, Northeastern China[J]. Ore Geology Reviews,  163: 105788. DOI: https://doi.org/10.1016/j.oregeorev.2023.105788.

Zhang B, Li M, Huan Y, Khan U, Wang L, Wang F. 2023. Bedrock mapping based on terrain weighted directed graph convolutional network using stream sediment geochemical samplings[J]. Transactions of Nonferrous Metals Society of China,  33(09): 2799-2814. DOI: 10.1016/S1003-6326(23)66299-5.

Zhang B, Du L, Khan U, Tong Y, Wang L, Deng H. 2023. AdaHRBF v1.0: gradient-adaptive Hermite–Birkhoff radial basis function interpolants for three-dimensional stratigraphic implicit modeling[J]. Geosci. Model Dev.,  16(13): 3651-3674. DOI: 10.5194/gmd-16-3651-2023.

Huan YK, Song L, Khan U, Zhang BY. 2023. Stacking ensemble of machine learning methods for landslide susceptibility mapping in Zhangjiajie City, Hunan Province, China[J]. Environmental Earth Sciences,  82(1): 35. DOI: 10.1007/s12665-022-10723-z.

Zhang B, Li M, Li W, Jiang Z, Khan U, Wang L, Wang F. 2021. Machine learning strategies for lithostratigraphic classification based on geochemical sampling data: A case study in area of Chahanwusu River, Qinghai Province, China[J]. Journal of Central South University,  28(5): 1422-1447. DOI: 10.1007/s11771-021-4707-9.

Wang LF, Wu XB, Zhang BY, Li XF, Huang AS, Meng F, Dai PY. 2019. Recognition of Significant Surface Soil Geochemical Anomalies Via Weighted 3D Shortest-Distance Field of Subsurface Orebodies: A Case Study in the Hongtoushan Copper Mine, NE China[J]. Natural Resources Research,  28(3): 587-607. DOI: 10.1007/s11053-018-9410-7.