大数据分析是当代矿产资源评价方法体系面临的新挑战，绝大多数矿产资源评价方法的大数据处理效率偏低。因此，项目组拟将大数据分析处理功能强大的压缩感知理论引入矿产资源评价领域，用稀疏表示、稀疏采样和稀疏重构三种压缩感知核心技术分析处理多源地学大数据，创建大数据矿产资源评价的压缩感知模型体系。内容包括：①借鉴压缩感知在人脸识别和手写数字识别等方面的研究成果，研制基于压缩感知的“相似类比”矿产资源评价模型体系；②借鉴压缩感知在无线网络异常事件检测和未知信号非重构压缩检测等方面的研究成果，研制基于压缩感知的“求异”矿产资源评价模型体系；③在稀疏表示和极限学习机基础上，研制矿产资源评价稀疏优化极限学习机系列模型。把三种矿产资源评价模型体系应用于实验区，创建大数据矿产资源评价的压缩感知模型体系应用范例。研究工作能够推动压缩感知地学应用研究，促进当代矿产资源评价方法体系的发展，具有重要的理论和实际意义。

Big-data analyzing is the new challenge faced by the modern methodology of mineral resources assessment. Most methods of mineral resources assessment are low efficient for processing big-data. Thus, our research team plans to introduce compressive sensing, which is powerful for analyzing and processing big-data, to the field of mineral resources assessment. We plan to use sparse representation, sparse sampling, and sparse reconstruction, which are the three core techniques for compressive sensing to analyze and process multi-sourced geologic big-data and establish a model system for compressive sensing based mineral resources assessment on big-data. The research content includes: (a) Develop a similar analogy model system for compressive sensing based mineral resources assessment by referring to the research results of compressive sensing based face and handwriting digits recognition and etc.; (b) Develop a dissimilation model system for compressive sensing based mineral resources assessment by referring to the research results of compressive sensing based anomaly event detection in wireless networks and unreconstructed compressive detection of unknown-parameters signals and etc.; and (c)Develop sparse maximum learning machines for mineral resources assessment based on sparse representation and maximum learning machines. We plan to use these three model systems to the mineral resources assessment in the experimental area and set up a typical example of applying compressive sensing to mineral resources assessment on multi-sourced geologic big-data. The research can promote both application of compressive sensing in geosciences and development of the methodology of modern mineral resources assessment. Therefore, it has an important theoretical and practical significance.