首页 | 本学科首页   官方微博 | 高级检索  
文章检索
  按 检索   检索词:      
出版年份:   被引次数:   他引次数: 提示:输入*表示无穷大
  收费全文   650篇
  完全免费   27篇
  自动化技术   677篇
  2018年   24篇
  2017年   27篇
  2016年   26篇
  2015年   20篇
  2014年   30篇
  2013年   28篇
  2012年   30篇
  2011年   49篇
  2010年   32篇
  2009年   55篇
  2008年   32篇
  2007年   29篇
  2006年   35篇
  2005年   22篇
  2004年   8篇
  2003年   12篇
  2002年   20篇
  2001年   9篇
  2000年   17篇
  1999年   20篇
  1998年   16篇
  1997年   12篇
  1996年   9篇
  1995年   12篇
  1994年   7篇
  1993年   5篇
  1992年   5篇
  1991年   10篇
  1990年   11篇
  1989年   11篇
  1988年   13篇
  1987年   6篇
  1986年   7篇
  1985年   8篇
  1984年   1篇
  1983年   6篇
  1982年   2篇
  1979年   1篇
  1976年   1篇
  1975年   1篇
  1974年   1篇
  1973年   1篇
  1971年   2篇
  1969年   1篇
  1968年   2篇
  1964年   1篇
排序方式: 共有677条查询结果,搜索用时 62 毫秒
1.
The k-means algorithm is well known for its efficiency in clustering large data sets. However, working only on numeric values prohibits it from being used to cluster real world data containing categorical values. In this paper we present two algorithms which extend the k-means algorithm to categorical domains and domains with mixed numeric and categorical values. The k-modes algorithm uses a simple matching dissimilarity measure to deal with categorical objects, replaces the means of clusters with modes, and uses a frequency-based method to update modes in the clustering process to minimise the clustering cost function. With these extensions the k-modes algorithm enables the clustering of categorical data in a fashion similar to k-means. The k-prototypes algorithm, through the definition of a combined dissimilarity measure, further integrates the k-means and k-modes algorithms to allow for clustering objects described by mixed numeric and categorical attributes. We use the well known soybean disease and credit approval data sets to demonstrate the clustering performance of the two algorithms. Our experiments on two real world data sets with half a million objects each show that the two algorithms are efficient when clustering large data sets, which is critical to data mining applications.  相似文献
2.
A new evolutionary system for evolving artificial neural networks   总被引:32,自引:0,他引:32  
This paper presents a new evolutionary system, i.e., EPNet, for evolving artificial neural networks (ANNs). The evolutionary algorithm used in EPNet is based on Fogel's evolutionary programming (EP). Unlike most previous studies on evolving ANN's, this paper puts its emphasis on evolving ANN's behaviors. Five mutation operators proposed in EPNet reflect such an emphasis on evolving behaviors. Close behavioral links between parents and their offspring are maintained by various mutations, such as partial training and node splitting. EPNet evolves ANN's architectures and connection weights (including biases) simultaneously in order to reduce the noise in fitness evaluation. The parsimony of evolved ANN's is encouraged by preferring node/connection deletion to addition. EPNet has been tested on a number of benchmark problems in machine learning and ANNs, such as the parity problem, the medical diagnosis problems, the Australian credit card assessment problem, and the Mackey-Glass time series prediction problem. The experimental results show that EPNet can produce very compact ANNs with good generalization ability in comparison with other algorithms.  相似文献
3.
Evolutionary programming made faster   总被引:11,自引:0,他引:11  
Evolutionary programming (EP) has been applied with success to many numerical and combinatorial optimization problems in recent years. EP has rather slow convergence rates, however, on some function optimization problems. In the paper, a “fast EP” (FEP) is proposed which uses a Cauchy instead of Gaussian mutation as the primary search operator. The relationship between FEP and classical EP (CEP) is similar to that between fast simulated annealing and the classical version. Both analytical and empirical studies have been carried out to evaluate the performance of FEP and CEP for different function optimization problems. The paper shows that FEP is very good at search in a large neighborhood while CEP is better at search in a small local neighborhood. For a suite of 23 benchmark problems, FEP performs much better than CEP for multimodal functions with many local minima while being comparable to CEP in performance for unimodal and multimodal functions with only a few local minima. The paper also shows the relationship between the search step size and the probability of finding a global optimum and thus explains why FEP performs better than CEP on some functions but not on others. In addition, the importance of the neighborhood size and its relationship to the probability of finding a near-optimum is investigated. Based on these analyses, an improved FEP (IFEP) is proposed and tested empirically. This technique mixes different search operators (mutations). The experimental results show that IFEP performs better than or as well as the better of FEP and CEP for most benchmark problems tested  相似文献
4.
A perspective on range finding techniques for computer vision   总被引:9,自引:0,他引:9  
In recent times a great deal of interest has been shown, amongst the computer vision and robotics research community, in the acquisition of range data for supporting scene analysis leading to remote (noncontact) determination of configurations and space filling extents of three-dimensional object assemblages. This paper surveys a variety of approaches to generalized range finding and presents a perspective on their applicability and shortcomings in the context of computer vision studies.  相似文献
5.
An optimal batch size for a JIT manufacturing system   总被引:8,自引:0,他引:8  
This paper addresses the problem of a manufacturing system that procures raw materials from suppliers in a lot and processes them to convert to finished products. It proposes an ordering policy for raw materials to meet the requirements of a production facility. In turn, this facility must deliver finished products demanded by outside buyers at fixed interval points in time. In this paper, first we estimate production batch sizes for a JIT delivery system and then we incorporate a JIT raw material supply system. A simple algorithm is developed to compute the batch sizes for both manufacturing and raw material purchasing policies. Computational experiences of the problem are also briefly discussed.  相似文献
6.
This paper proposes an alternative solution to the global stabilization of nonholonomic multi-input chained form systems investigated in recent contributions [13, 18]. A systematic design, which is reminiscent of integrator backstepping methods, is presented to generate a new class of smooth time-varying dynamic stabilizers. The proof of stability is straightforward and the algorithm finds its application in adaptive control of nonholonomic systems and tracking control of mobile robot.  相似文献
7.
Multiple criteria decision making (MCDM) tools have been used in recent years to solve a wide variety of problems. In this paper we consider a nation-wide crop-planning problem and show how an MCDM tool can be used efficiently and effectively for these types of problems. A crop-planning problem is usually formulated as a single objective linear programming model. The objective is either the maximization of return from cultivated land or the minimization of cost of cultivation. This type of problem, however, normally involves more than one goal. We thus formulate a crop-planning problem as a goal program (an MCDM tool) and discuss the importance of three different goals for a case problem. We solve the goal program with a real world data set, and compare the solution with that of linear program. We argue that the goal program provides better insights to the problem and thus allows better decision support.  相似文献
8.
确定学习与基于数据的建模及控制   总被引:4,自引:1,他引:3       下载免费PDF全文
确定学习运用自适应控制和动力学系统的概念与方法, 研究未知动态环境下的知识获取、表达、存储和利用等问题. 针对产生周期或回归轨迹的连续 非线性动态系统, 确定学习可以对其未知系统动态进行局部准确建模, 其基本要 素包括: 1)使用径向基函数(Radial basis function, RBF)神经网络; 2)对于周期(或回归)状态轨迹 满足部分持续激励条件; 3)在周期(或回归)轨迹的邻域内实现对非线性系统动态的局部准确神经网络逼近(局部准确建模); 4)所学的知识以时不变且空间分布的方式表达、以常值神经网络权值的方式存储, 并可在动态环境下用于动态模式的快速识别或者闭环神经网络控制. 本文针对离散动态系统, 扩展了确定学习理论, 提出一个根据时态数据序列对离散动态系统进行建模与控制的框架. 首先, 运用确定学习原理和离散系统的自适应辨识方法, 实现对产生时态数据的离散非线性系统的未知动态进行局部准确的神经网络建模, 并利用此建模结果对时态数据序列进行时不变表达. 其次, 提出时态数据序列的基于动力学的相似性定义, 以及对离散动态系统产生的时态数据序列(亦可称为动态模式)进行快速识别方法. 最后, 针对离散非线性控制系统, 实现了基于时态数据序列对控制系统动态的闭环辨识(局部准确建模). 所学关于闭环动态的知识可用于基于模式的智能控制. 本文表明确定学习可以为时态数据挖掘的研究提供新的途径, 并为基于数据的建模与控制等问题提供新的研究思路.  相似文献
9.
This paper presents a concept of passivity for switched systems using multiple storage functions. This passivity property is invariant under compatible feedback interconnection. Branicky's stability theorem of multiple Lyapunov functions is generalized by relaxing the non-increasing condition on values of Lyapunov-like functions. Using this result we show that a passive switched system is stable in the sense of Lyapunov. Moreover, asymptotic stability is reached if all subsystems are asymptotically detectable.  相似文献
10.
A ground-based, upward-scanning, near-infrared lidar, the Echidna® validation instrument (EVI), built by CSIRO Australia, retrieves forest stand structural parameters, including mean diameter at breast height (DBH), stem count density (stems/area), basal area, and above-ground woody biomass with very good accuracy in six New England hardwood and conifer forest stands. Comparing forest structural parameters retrieved using EVI data with extensive ground measurements, we found excellent agreement at the site level using five EVI scans (plots) per site (R2 = 0.94-0.99); very good agreement at the plot level for stem count density and biomass (R2 = 0.90-0.85); and good agreement at the plot level for mean DBH and basal area (R2 = 0.48-0.66). The observed variance at site and plot levels suggest that a sample area of at least 1 ha (104 m2) is required to estimate these parameters accurately at the stand level using either lidar-based or conventional methods. The algorithms and procedures used to retrieve these structural parameters are dependent on the unique ability of the Echidna® lidar to digitize the full waveform of the scattered lidar pulse as it returns to the instrument, which allows consistent separation of scattering by trunks and large branches from scattering by leaves. This successful application of ground-based lidar technology opens the door to rapid and accurate measurement of biomass and timber volume in areal sampling scenarios and as a calibration and validation tool for mapping biomass using airborne or spaceborne remotely sensed data.  相似文献
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号