全文获取类型
收费全文 | 462篇 |
免费 | 178篇 |
国内免费 | 139篇 |
专业分类
电工技术 | 44篇 |
综合类 | 66篇 |
化学工业 | 33篇 |
金属工艺 | 2篇 |
机械仪表 | 15篇 |
建筑科学 | 8篇 |
矿业工程 | 2篇 |
能源动力 | 5篇 |
轻工业 | 4篇 |
水利工程 | 5篇 |
石油天然气 | 7篇 |
武器工业 | 11篇 |
无线电 | 71篇 |
一般工业技术 | 43篇 |
冶金工业 | 5篇 |
自动化技术 | 458篇 |
出版年
2024年 | 1篇 |
2023年 | 16篇 |
2022年 | 39篇 |
2021年 | 31篇 |
2020年 | 42篇 |
2019年 | 30篇 |
2018年 | 24篇 |
2017年 | 30篇 |
2016年 | 33篇 |
2015年 | 36篇 |
2014年 | 36篇 |
2013年 | 47篇 |
2012年 | 51篇 |
2011年 | 52篇 |
2010年 | 49篇 |
2009年 | 43篇 |
2008年 | 45篇 |
2007年 | 49篇 |
2006年 | 28篇 |
2005年 | 30篇 |
2004年 | 21篇 |
2003年 | 12篇 |
2002年 | 8篇 |
2001年 | 4篇 |
2000年 | 1篇 |
1999年 | 2篇 |
1997年 | 2篇 |
1996年 | 1篇 |
1995年 | 2篇 |
1994年 | 2篇 |
1993年 | 3篇 |
1991年 | 4篇 |
1990年 | 3篇 |
1989年 | 1篇 |
1980年 | 1篇 |
排序方式: 共有779条查询结果,搜索用时 15 毫秒
1.
Farzaneh Khorasani Morteza Mohammadi Zanjireh Mahdi Bahaghighat Qin Xin 《计算机系统科学与工程》2022,40(3):1085-1098
With a sharp increase in the information volume, analyzing and retrieving this vast data volume is much more essential than ever. One of the main techniques that would be beneficial in this regard is called the Clustering method. Clustering aims to classify objects so that all objects within a cluster have similar features while other objects in different clusters are as distinct as possible. One of the most widely used clustering algorithms with the well and approved performance in different applications is the k-means algorithm. The main problem of the k-means algorithm is its performance which can be directly affected by the selection in the primary clusters. Lack of attention to this crucial issue has consequences such as creating empty clusters and decreasing the convergence time. Besides, the selection of appropriate initial seeds can reduce the cluster’s inconsistency. In this paper, we present a new method to determine the initial seeds of the k-mean algorithm to improve the accuracy and decrease the number of iterations of the algorithm. For this purpose, a new method is proposed considering the average distance between objects to determine the initial seeds. Our method attempts to provide a proper tradeoff between the accuracy and speed of the clustering algorithm. The experimental results showed that our proposed approach outperforms the Chithra with 1.7% and 2.1% in terms of clustering accuracy for Wine and Abalone detection data, respectively. Furthermore, achieved results indicate that comparing with the Reverse Nearest Neighbor (RNN) search approach, the proposed method has a higher convergence speed. 相似文献
2.
离群点检测任务通常缺少可用的标注数据,且离群数据只占整个数据集的很小一部分,相较于其他的数据挖掘任务,离群点检测的难度较大,尚没有单一的算法适合于所有的场景。因此,结合多样性模型集成和主动学习思想,提出了一种基于主动学习的离群点集成检测方法OMAL(Outlier Mining based on Active Learning)。在主动学习框架指导下,根据各种基学习器的对比分析,选择了基于统计的、基于相似性的、基于子空间划分的三个无监督模型作为基学习器。将各基学习器评判的处于离群和正常边界的数据整合后呈现给人类专家进行标注,以最大化人类专家反馈的信息量;从标注的数据集和各基学习器投票产生的数据集中抽样,基于GBM(Gradient BoostingMachine)训练一个有监督二元分类模型,并将该模型应用于全数据集,得出最终的挖掘结果。实验表明,提出方法的AUC有了较为明显的提升,且具有良好的运行效率,具备较好的实用价值。 相似文献
3.
Elahe Aghapour Jay A. Farrell 《International Journal of Adaptive Control and Signal Processing》2020,34(6):777-795
This paper presents a novel state estimation approach for linear dynamic systems when measurements are corrupted by outliers. Since outliers can degrade the performance of state estimation, outlier accommodation is critical. The standard approach combines outlier detection utilizing Neyman-Pearson (NP) type tests with a Kalman filter (KF). This approach ignores all residuals greater than a designer-specified threshold. When measurements with outliers are used (ie, missed detections), both the state estimate and the error covariance matrix become corrupted. This corrupted state and covariance estimate are then the basis for all subsequent outlier decisions. When valid measurements are rejected (ie, false alarms), potentially using the corrupted state estimate and error covariance, measurement information is lost. Either using invalid information or discarding too much valid information can result in divergence of the KF. An alternative approach is moving-horizon (MH) state estimation, which maintains all recent measurement data within a moving window with a time horizon of length L. In MH approaches, the number of measurements available for state estimation is affected by both the number of measurements per time step and the number of time steps L over which measurements are retained. Risk-averse performance-specified (RAPS) state estimation works within an optimization setting to choose a set of measurements that achieves a performance specification with minimum risk of outlier inclusion. This paper derives and formulates the MH-RAPS solution for outlier accommodation. The paper also presents implementation results. The MH-RAPS application uses Global Navigation Satellite Systems measurements to estimate the state of a moving platform using a position, velocity, and acceleration model. In this application, MH-RAPS performance is compared with MH-NP state estimation. 相似文献
4.
5.
为提升雷达探测精度评估中雷达探测导弹目标数据的质量,提出基于滑窗的均值和中值剔除法,并将其
与基于滑窗的多项式拟合法和模板卷积法进行对比分析。通过以3 倍的均方误差作为门限,设置合适的窗口长度,
选取基于窗口滑动的均值或中值剔除法。测试结果表明:2 种方法均可更有效地剔除雷达探测导弹目标数据中的野
值,为后续弹道还原和数据评估提供了有效支撑。 相似文献
6.
通过对管理样的采集、制备、测试、数据处理与分析、定值等几个步骤得到某主要测量Au、Ag、Pb、Zn四个元素的某金矿样品分析用管理样相应Au、Ag、Pb、Zn的准确值。用于含量与成分相似的金矿样品分析过程的质量控制,通过管理样的分析情况以检查整个分析过程的质量。 相似文献
7.
由于人为因素以及现场干扰的影响,变压器油色谱在线监测数据在测量和传输中会不可避免地出现偏误,导致异常数据值,使得经典统计方法的结果出现偏差甚至错误。为了解决上述问题,基于稳健统计理论,根据油色谱监测数据异常值的特点,提出了油色谱H2、CO和总烃3类特征气体异常值的最小协方差行列式MCD稳健多元检测方法。利用迭代和Mahalanobis距离的思想构造一个稳健的协方差估计量,并进行异常值检测,然后再将异常数据和正常数据分类处理。针对H2、CO和总烃这3类特征气体的实例统计分析表明,异常值剔除后可有效减少这3种气体的测量值对经典统计方法的干扰,使得油色谱数据的统计规律更加明显。通过对异常值区间的跟踪评估,还可更加明显地反映变压器运行状态的变化。 相似文献
8.
《Journal of Building Performance Simulation》2013,6(1):53-62
Black-box models such as linear regression have proven to be helpful in ongoing building commissioning in many ways. The aim of this work is to improve linear models with change point for fault detection in buildings. Building simulations revealed poor performance of them (R 2 < 0.7) for some low energy buildings. The regression models (RMs) can be considerably improved by introducing the rate of change of the indoor air temperature (ΔT ind) as an independent variable. Thus, R 2 values were raised by up to 0.5 (e.g. from 0.2 to 0.7, example with the lowest R 2). A new training and application process for the RMs revealed further improvements by using a hierarchical agglomerative clustering algorithm to determine different day-types as additional (categorical) variables in the RM. The application of these improved RMs for outlier detection is demonstrated in three buildings. 相似文献
9.
10.