采用人工免疫算法的加速寿命试验分析方法

极大似然估计是加速寿命试验统计分析中常用的分析方法,但似然函数的优化问题是该方法广泛运用的主要障碍,常用的似然函数优化算法对初值要求高,而且容易陷入局部最优解.为了有效地解决上述问题,在似然函数的优化中引入了人工免疫算法,提出了一种采用人工免疫算法的步降应力加速寿命试验分析方法.利用人工免疫算法在解决多维复杂函数优化问题时强大的全局寻优能力,有效地解决了似然函数的优化问题.最后通过实例验证表明,采用人工免疫算法的步降应力加速寿命试验分析方法是有效的,而且在统计分析中避免了查统计用表,能够很方便的实现计算机编程计算,有较大的工程应用价值.     

人工神经网络在激光涂层多冲碰撞疲劳寿命预测中的应用

运用人工神经网络技术,采用激光涂层多冲碰撞寿命试验数据和专家数据相结合,以涂层材料、基体材料、涂层厚度和应力水平为输入因子建立疲劳寿命的预测模型,该模型精度较高,可为今后激光涂层多冲碰撞疲劳试验结果的预测提供理论根据。     

春草连天绿,花开四月红--第四届中国信息安全发展趋势与战略高层研讨会素描

又到了绿草天涯的时节,又到了信息安全各界朋友相聚的时刻.借着中办27号文件和全国信息安全保障工作会议的强劲东风,4月20日,由<信息安全与通信保密>杂志和中国信息安全产品测评认证中心共同主办的"第四届中国信息安全发展趋势与战略高层研讨会"在北京中国科技会堂再次涌动起催花促雨的春潮.     

Uncertainty in the output of artificial neural networks

Analysis of the performance of artificial neural networks (ANNs) is usually based on aggregate results on a population of cases. In this paper, we analyze ANN output corresponding to the individual case. We show variability in the outputs of multiple ANNs that are trained and "optimized" from a common set of training cases. We predict this variability from a theoretical standpoint on the basis that multiple ANNs can be optimized to achieve similar overall performance on a population of cases, but produce different outputs for the same individual case because the ANNs use different weights. We use simulations to show that the average standard deviation in the ANN output can be two orders of magnitude higher than the standard deviation in the ANN overall performance measured by the Az value. We further show this variability using an example in mammography where the ANNs are used to classify clustered microcalcifications as malignant or benign based on image features extracted from mammograms. This variability in the ANN output is generally not recognized because a trained individual ANN becomes a deterministic model. Recognition of this variability and the deterministic view of the ANN present a fundamental contradiction. The implication of this variability to the classification task warrants additional study.     

Cycle life estimation of lithium-ion polymer batteries using artificial neural network and support vector machine with time-resolved thermography

A battery cycle life forecast method without requirements of contact measurement devices and long testing time would be beneficial for industrial applications. The combination of infrared thermography and supervised learning techniques provided the potential solution to this problem. This research investigates the application of machine learning techniques—artificial neural networks (ANNs) and support vector machines (SVMs)—in combination with thermography for cycle life estimation of lithium-ion polymer batteries. Infrared images were captured at 1 frame/min during 70 min of charging followed by 60 min of discharging for 410 cycles. The surface temperature profiles during either charging or discharging were used as the input nodes for ANN and SVM models. The results demonstrated that with thermal profiles as the input, ANN could estimate the current cycle life of studied cell with the error of < 10% under 10 min of testing time. While when compared to ANN, the accuracy of SVM-based forecast models was similar but generally required a longer amount of testing time.     

未知源信号峭度正负性的盲分离

大多数的盲分离算法假设源信号峭度的正负性是己知的，并据此选择相应的非线性函数近似评价函数(score function)。针对源信号峭度的正负性未知的情况，本文提出了一个评价函数的参数估计方法，本算法能有效地分离混合在一起的超高斯信号和亚高斯信号，仿真结果验证了算法的有效性。     

Paris公式在起重机疲劳断裂中的研究与应用

起重机部件的疲劳断裂对安全生产具有严重的破坏,运用了Paris公式,研究提出了起重机的疲劳裂纹扩展试验,用于预测起重机部件的工作寿命。通过在疲劳试验机上进行疲劳裂纹扩展试验,采用AFGROW软件进行模拟疲劳裂纹的发展,对起重设备部件进行了疲劳仿真,对设备的工作寿命进行了预测,有效的预防生产事故的产生。     

2010年4月黑龙江省电信行业运行情况

截至2010年4月底,黑龙江省电信行业累计完成投资6亿元,其中,3G投资1.29亿元.全省电信业务总量达到236.2亿元,同比增长19.8%;全省电信业务收入67.9亿元,同比增长7.8%.全省电话用户(含固定和移动电话用户)总数达到2 940.5万户,环比增加18.7万户,环比上升0.64%.     

自然环境下交通标志牌的检测与识别

在社会经济飞速发展背景下,汽车的应用得到普及,已进入千家万户,汽车为人们出行带来了便利性,不过频发的交通事故也值得深思。而引起交通事故的原因之一即未及时检测到交通标志牌,故而探索出可快捷进行交通标志牌检测与识别的技术非常重要,该检测结合智能交通技术进行交通标志识别系统的设计,设计的识别方法即经提取标准图片与待识别图片的垂直、水平方位的灰度分布,完成Pearson相关系数计算工作,并通过一定阈值的设定,于待识别图片和所有标准图片里均作Pearson相关系数计算后,相关系数的值为最大,同时比阈值更大则认定成匹配成功来达到提醒与警示驾驶员的作用,将交通事故发生率控制到最低。     

Application of artificial intelligence in mobile communication:challenge and practice

The research and application progress in mobile communication,and points out its obstacle for improving the performance of mobile communication system were summarized.A new approach for reducing the gap between the practical and the ideal network performance was put forward creatively,which included the artificial intelligence reconstruction for performance outer loop part,the traditional adaptation or optimization for performance inner loop part,and the optimal cooperation between the two parts.The effectiveness of this approach was proved by the several successful applications.Finally,it pointed out that in order to meet the severe demands of mobile communication system for the “stable” “accurate” and “fast” artificial intelligence solution,and make the mobile network automatic,intelligent and wise,in addition to the excellent performance of the artificial intelligence reconstruction scheme itself,there must also be a feedback closed-loop system architecture based on the big data analysis and analog system,which is the key path to achieve this target.     

缅甸：湄公河畔的信息化沃土

从中国青海省唐古拉山发源，流经西藏自治区，由云南省南部西双版纳傣族自治州出境，于越南胡志明市附近注入南中国海；这条全长4880公里，在中国境内段被称为澜沧江，境外段称为湄公河的国际河流所流经的地区，也许是由于历史和地理的原因，竞都是清一色的发展中国家。例如缅甸、老挝、泰国、柬埔寨、越南。     

2009年4月黑龙江省电信行业运行情况

截至2009年4月底,黑龙江省电信行业累计完成投资10.4亿元,全省电信业务总量达到197.2亿元,同比增长9.2%;全省电信业务收入63.2亿元,同比增长0.5%.全省电话用户(含固定和移动电话用户)总数达到2 877.7万户,环比增加25.1万户,增长0.88%.目前,全省电话普及率达到75.2部/百人,固定电话普及率达到26.7部/百人,移动电话普及率达到48.4部/百人.     

Low-loss propagation in the dipole-mode along a coaxial waveguide

A theoretical investigation has been made as a step towards defining more precisely the operating conditions of a fully screened dipole-mode waveguide, comprising a coaxial structure whose inner consists of a cylindrical grid of parallel longitudinal wires separated by air and whose outer is represented by a concentric tube of continuous metal.     

Testability of artificial neural networks: A behavioral approach

Testability analysis of neural architectures can be performed at a very high abstraction level on the computational paradigm. In this paper, we consider the case of feed-forward multi-layered neural networks. We introduce a behavioral error model which allows good mapping of the physical faults in widely different implementations. Conditions for error controllability, observability and global testability are analytically derived; their purpose is that of verifying whether it is possible to excite all modeled errors and to propagate the error's effects to the primary outputs (actual test vectors being then technological-dependent). Mapping of physical faults onto behavioral errors is performed for some representative, architectures.     

浅谈人工智能在计算机中的应用

随着社会经济的不断发展与进步,科学技术的不断改革与创新,人工智能技术发展得到了质的飞跃,社会各界人士开始高度关注和重视到人工智能的应用。人工智能作为计算机运行过程的重中之重,是一个必不可缺的关键环节,它能够有效提高计算机的工作质量和效率,最大化满足现代社会对于智能化和人性化的服务需求,推动社会和谐稳定的发展,文章将进一步对人工智能在计算机中的应用展开分析与探讨。