智能高效小型一体化泥浆不落地系统的研究与应用

针对固体矿产勘查钻探工程泥浆性能维护和固控装备自动化的需求,开展小型一体化泥浆不落地循环处理工艺研究和自动化智能化控制装备研制。装备主要由循环系统、净化系统、控制系统及循环管汇组成。系统引入PID控制和物联网技术,实现过渡泵的自反馈控制和远程可视化控制。现场应用结果表明,装备运行安全、可靠、平稳,净化效率高、自动化程度高,在技术、成本和环保等方面都取得了良好的效果,符合绿色勘查需求。通过自动化智能化控制技术,减少现场作业人员,降低工人劳动强度,一定程度上提升了岩心钻探设备自动化智能化水平,为实现岩心钻探设备自动化、智能化目标提供技术支撑。     

一个圈闭评价专家系统的设计与实现

本文详细论述一个圈闭评价专家系统的设计与实现技术,该系统能够接收用户提供的圈闭信息,根据知识库中的专家知识给出圈闭的含油气资源评价;系统采用了基于黑扳的控制结构和基于规则的知识表达以及演绎推理、模糊推理、模糊综合评判等一系列技术在IBM-PC机上用C语言及少量汇编语言实现。系统已通过专家鉴定。     

东莞地区土地利用变化预测的CBR和CA方法对比研究(英文)

Many studies on land use change(LUC),using different approaches and models,have yielded good results.Applications of these methods have revealed both advantages and limitations.However,LUC is a complex problem due to influences of many factors,and variations in policy and natural conditions.Hence,the characteristics and regional suitability of different methods require further research,and comparison of typical approaches is re-quired.Since the late 1980s,CA has been used to simulate urban growth,urban sprawl and land use evolution successfully.Nowadays it is very popular in resolving the LUC estimating problem.Case-based reasoning(CBR),as an artificial intelligence technology,has also been employed to study LUC by some researchers since the 2000s.More and more researchers used the CBR method in the study of LUC.The CA approach is a mathematical system con-structed from many typical simple components,which together are capable of simulating complex behavior,while CBR is a problem-oriented analysis method to solve geographic problems,particularly when the driving mechanisms of geographic processes are not yet understood fully.These two methods were completely different in the LUC research.Thus,in this paper,based on the enhanced CBR model,which is proposed in our previous research(Du et al.2009),a comparison between the CBR and CA approaches to assessing LUC is presented.LUC in Dongguan coastal region,China is investigated.Applications of the im-proved CBR and the cellular automata(CA) to the study area,produce results demonstrating a similarity estimation accuracy of 89% from the improved CBR,and 70.7% accuracy from the CA.From the results,we can see that the accuracies of the CA and CBR approaches are both >70%.Although CA method has the distinct advantage in predicting the urban type,CBR method has the obvious tendency in predicting non-urban type.Considering the entire ana-lytical process,the preprocessing workload in CBR is less than that of the CA approach.As such,it could be concluded that the CBR approach is more flexible and practically useful than the CA approach for estimating land use change.     

Artificial intelligence-based hull structural plate corrosion damage detection and recognition using convolutional neural network

With the support of big data and GPU acceleration training, the artificial intelligence technology with deep learning as its core is developing rapidly and has been widely used in many fields. At the same time, feature extraction operations are required by the current image-based corrosion damage detection method in the field of ships, with little effect but consuming the large amount of manpower and financial resources. Therefore, a new method for hull structural plate corrosion damage detection and recognition based on artificial intelligence using convolutional neural network is proposed. The convolutional neural network (CNN) model is trained through a large number of classified corrosion damage images to obtain a classifier model. Then the classifier model is used with overlap-scanning sliding window algorithm to recognize and position the location of corrosion damage. Finally, the damage detection pattern for hull structural plate corrosion damage as well as other types of superficial structural damage using convolutional neural network is proposed, which can accelerate the application of artificial intelligence technology into the field of naval architecture & ocean engineering.     

中国无人机遥感技术突破与产业发展综述

无人机是未来网络环境下一种数据驱动的空中移动智能体,而无人机遥感则是无人机应用最重要的引领性产业。本文首先以国内外无人机遥感发展现状为背景,重点概述了中国无人机遥感21世纪以来“十五”到“十三五”所获得的具有代表性的国家支持与推动的发展历程,阐述了无人机遥感定标场,航空航天定标场的建立以及应用验证,包括无人机遥感系统的载荷与系统技术发展;然后,进一步阐述了以遥感定标场、地物参量引导载荷性能、系统模型为代表的中国无人机遥感的相关技术跨越;接着,概略介绍了无人机遥感在国防反恐安全以及跨国应急救援,国土测绘与海洋岛礁测绘应用,地质灾害应用以及国家应急救援等领域的产业应用;最后,介绍了中国在无人航空遥感领域展开的跨越性的工作,包括组网智能控制、精度和实时性度量基础、载荷平台自组织冗余容错、遥感大数据云处理技术和无人机遥感组网实用化等内容。未来无人机遥感发展的总体目标是建立起具备迅捷信息获取能力的无人航空器组网观测系统,实现无人航空器组网技术由项目层面跨越到遥感领域,同时也为中国成为世界遥感强国的国家战略跨越奠定基础。     

为社会进步服务的测绘高新技术

当今正值国民经济快速发展,科技创新不断涌现。测绘地理信息技术在人类生活中发挥了越来越大的作用,渐渐地形成了跨界发展,越来越多的行业与测绘地理信息技术建立联系。现如今,社会各行各业的发展已经离不开测绘地理信息行业的服务保障,与此同时,随着互联网时代的深度变革,云计算、大数据、人工智能、虚实融合等智能化技术的发展在测绘行业不断渗透,并与测绘地理信息技术相互融合,取得了很多创新性成果。     

基于改进InceptionV3模型的常见矿物智能识别

以常见的16类矿物作为研究对象,收集每一类矿物约1000张图像,按比例划分为训练集、验证集和测试集,通过图像随机选取增加数据的多样性,建立矿物识别InceptionV3模型,训练7万次在测试集上获得81%的识别正确率。通过对损失函数的改进,引入Center Loss损失函数,训练40万次识别准确率提高到86%。对分类的混淆矩阵分析发现,孔雀石等外观特征明显的矿物识别正确率很高,而闪锌矿等与其他矿物容易混淆导致正确率较低。从特征图分析看出,模型很好地提取了孔雀石的放射状特征,矿物图像特征向量聚集程度很高,也说明了模型的可靠性。     

数据仓库技术在生物信息学中的应用研究

对目前国际互联网中的异地异构生物信息数据源进行研究,分析了生物信息数据的特性,利用数据挖掘技术,设计了一种基于Web的生物信息数据仓库系统的实现方案。采用该方案,可以增强异地生物信息数据库之间的数据交互能力,提高数据库的使用效率;并为解决基于异构数据源的复杂信息数据库的设计提供参考。     

The exemplar‐aided constructor of hyper‐rectangles learning algorithm for stream flow estimation

The exemplar‐aided constructor of hyper‐rectangles (EACH) model which simulates human intelligence by learning from experience and adjusting in time, proposed by Salzberb (1991), is presented and modified to strengthen its performance in variable stream flow extension. The modification is intended to resolve the contradiction between building hyper‐rectangles and predictive accuracy in which the number of hyper‐rectangles becomes too large if higher accuracy is required. To explore the feasibility of the modified EACH, a mathematical function is simulated by the model. It is then applied to extend the 10‐day stream flow records according to the nearby rainfall and/or stream flow gauges. The results show that the modified EACH achieves the goal of saving memory space and promoting predictive accuracy, and its performance is better than those of the original EACH and traditional methods. This research suggests that the modified EACH shows considerable promise in stream flow estimation. Copyright © 2000 John Wiley & Sons, Ltd.     

三峡库区岩性智能分类研究

三峡库区岩体上方覆盖着厚实的土壤和茂密的植被,是高植被覆盖区,岩性信息弱,因此岩性识别和分类困难,没有成熟的方法可循。针对三峡库区进行岩性分析,选择三峡库区巴东城区作为研究区域,采用2000年5月成像的ETM+遥感影像,构造纹理、光谱、植被覆盖等17个分类因子,将遥感影像与地质图叠加,选取1 101个样本点,采用决策树C4.5算法,挖掘出三峡库区巴东县处岩性的解译规则和知识,决策树的学习精度为96.6%,剪枝后精度为95.9%,规则提取的精度为93.1%,提取的规则置信度很高,并基于知识驱动和规则匹配实现了岩性的智能分类,分类精度较高为90.11%;将分类结果与IsoData方法、K-Means方法、马氏距离法、最大似然法、最小距离法、平行六面体方法等6种方法的分类结果进行比较,试验结果证明,决策树方法的分类结果最好,精度明显高于其他6种方法。