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1.
Machine learning algorithms have been widely used in mine fault diagnosis. The correct selection of the suitable algorithms is the key factor that affects the fault diagnosis. However, the impact of machine learning algorithms on the prediction performance of mine fault diagnosis models has not been fully evaluated. In this study, the windage alteration faults (WAFs) diagnosis models, which are based on K-nearest neighbor algorithm (KNN), multi-layer perceptron (MLP), support vector machine (SVM), and decision tree (DT), are constructed. Furthermore, the applicability of these four algorithms in the WAFs diagnosis is explored by a T-type ventilation network simulation experiment and the field empirical application research of Jinchuan No. 2 mine. The accuracy of the fault location diagnosis for the four models in both networks was 100%. In the simulation experiment, the mean absolute percentage error (MAPE) between the predicted values and the real values of the fault volume of the four models was 0.59%, 97.26%, 123.61%, and 8.78%, respectively. The MAPE for the field empirical application was 3.94%, 52.40%, 25.25%, and 7.15%, respectively. The results of the comprehensive evaluation of the fault location and fault volume diagnosis tests showed that the KNN model is the most suitable algorithm for the WAFs diagnosis, whereas the prediction performance of the DT model was the second-best. This study realizes the intelligent diagnosis of WAFs, and provides technical support for the realization of intelligent ventilation. 相似文献
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针对某金矿,在回收金银的基础上,对金银浮选尾矿进行云母和长石浮选,以及提纯石英试验,最终获得SiO2品位99.91%的石英产品。提纯石英产品与比利时矽比科矿业有限公司石英产品进行对比试验,通过化学成分、粒度组成、熔制、粘度和热膨胀系数测试对比试验,得出金矿提纯石英达到甚至超过矽比科进口石英产品的各项技术指标。 相似文献
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随着社会的不断发展,矿产资源为我国带来了巨大的经济效益,并在社会经济发展中占有重要的地位。但在矿山资源开发的过程中,威胁人身安全的事故经常发生。因此,本文对探矿工程安全措施进行了研究和分析。 相似文献
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A mathematical model for open pit mine production scheduling with Grade Engineering® and stockpiling
《矿业科学技术学报(英文版)》2021,31(4):717-728
This paper presents the development and implementation of an innovative mixed integer programming based mathematical model for an open pit mining operation with Grade Engineering framework. Grade Engineering comprises a range of coarse-separation based pre-processing techniques that separate the desirable (i.e. high-grade) and undesirable (i.e. low-grade or uneconomic) materials and ensure the delivery of only selected quantity of high quality (or high-grade) material to energy, water, and cost-intensive processing plant. The model maximizes the net present value under a range of operational and processing constraints. Given that the proposed model is computationally complex, the authors employ a data pre-processing procedure and then evaluate the performance of the model at several practical instances using computation time, optimality gap, and the net present value as valid measures. In addition, a comparison of the proposed and traditional (without Grade Engineering) models reflects that the proposed model outperforms the traditional formulation. 相似文献
6.
The World robot summit disaster robotics category – achievements of the 2018 preliminary competition
Satoshi Tadokoro Tetsuya Kimura Masayuki Okugawa Katsuji Oogane Hiroki Igarashi Yoshikazu Ohtsubo 《Advanced Robotics》2019,33(17):854-875
The World Robot Summit is a robot Olympics and aims to be held in a different country every four years from 2020. The concept of the Plant Disaster Prevention challenge is daily inspections, checks, and emergency response in industrial plants, and in this competition, robots must carry out these types of missions in a mock-up plant. The concept of the Tunnel Disaster Response and Recovery challenge is emergency response to tunnel disasters, and is a simulation competition whereby teams compete to show their ability to deal with disasters, by collecting information and removing debris. The Standard Disaster Robotics challenge assesses, in the form of a contest, the standard performance levels of a robot that are necessary for disaster prevention and emergency response. The World Robot Summit Preliminary Competition was held at Tokyo Big Sight in October 2018, and 36 teams participated in the Disaster Robotics Category. UGVs and UAVs contended the merits of new technology for solving complex problems, using core technologies such as mobility, sensing, recognition, performing operations, human interface, autonomous intelligence etc., as well as system integration and implementation of strategies for completing missions, gaining high-level results. 相似文献
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流域泥沙灾害与泥沙资源性的研究 总被引:5,自引:0,他引:5
泥沙灾害与泥沙资源性是流域泥沙的重要属性,二者在一定条件下可以相互转化。本文论述了泥沙淤积、泥沙冲刷、岸滩崩塌、山地崩塌与泥石流、粗沙淤积的土地沙化等泥沙灾害,指出泥沙灾害具有时空分布的不均匀性、渐变性或突发性、群发性、转化性及危害严重性等;流域泥沙资源化的主要途径包括填海造陆及造地、引洪淤灌、堤防淤临淤背、建筑材料、湿地形成(河流、湖泊与河口海岸)等,指出流域泥沙资源化及其优化配置既要解决思想观念、基本理论、目标效益等方面的问题,还要考虑与水资源联合配置问题。 相似文献
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容灾系统中存储方案选择的研究 总被引:1,自引:0,他引:1
论文首先阐述了在容灾系统中存储方案的重要性,讨论了存储方案需要考虑的衡量指标,然后介绍了主要的存储方式,根据衡量指标划分了存储方式的特性范围,最后着重研究了容灾系统中存储方案的选择流程,并使用一个实例说明容灾系统中存储方案的选择流程。 相似文献