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931.
一种基于朴素贝叶斯分类的性能预测方法 总被引:1,自引:0,他引:1
基于朴素贝叶斯分类提出了一种复杂应用系统的性能预测方法.利用应用系统性能测试的结果作为训练集,引入朴素贝叶斯分类方法训练分类器,再将该分类器包装成预测模块嵌入应用系统,对响应时间等多种性能属性进行预测.与传统方法相比,该方法具有准确度高、构造简单、效率高、鲁棒性强、松耦合等优势.在针对金融报表系统的对比实验中准确率达到... 相似文献
932.
马宏兴 《计算机应用与软件》2011,28(8)
通过对H.264/AVC帧间预测模式选择的实验观测,发现最近采用的SKIP/DIRECT模式或者16×16宏块模式,和当前块的选择模式有着空间和时间上的关联。依据这一现象,提出了一种快速的帧间自适应宏块模式选择算法。从验证模型JM7.6上的实验结果来看,在保持图像编码质量,视频编码比特没有太大增加的情况下,该算法对变化不是很剧烈的视频序列,可节省近50%的编码时间,对变化较为剧烈的视频序列,亦可节省近10%的编码时间,降低了原标准在进行帧间预测时的复杂度,提高了编码器的工作效率。 相似文献
933.
准确的蓄电池荷电状态(SOC)决定了电动汽车剩余的行驶里程数.为准确评估电动车用Ni/MH电池组荷电状态(SOC)值,本文提出了一种非线性自回归滑动平均(NARMAX)模型的系统辨识方法.文中使用联邦城市行驶工况(FUDS)的试验数据,采用NARMAX模型线性简化逼近的辨识方法,对蓄电池SOC建立了多输入变量的模型,并使用这个模型进行实时预测;预测结果与试验结果进行了比较.结果表明,该方法是简单、有效的.预测的最大相对误差为1%. 相似文献
934.
935.
José Luis Crespo Marta Zorrilla Pilar Bernardos Eduardo Mora 《The Visual computer》2009,25(4):309-323
The objective of this paper is to present an overall approach to forecasting the future position of the moving objects of
an image sequence after processing the images previous to it. The proposed method makes use of classical techniques such as
optical flow to extract objects’ trajectories and velocities, and autoregressive algorithms to build the predictive model.
Our method can be used in a variety of applications, where videos with stationary cameras are used, moving objects are not
deformed and change their position with time. One of these applications is traffic control, which is used in this paper as
a case study with different meteorological conditions to compare with.
相似文献
Marta Zorrilla (Corresponding author)Email: |
936.
Multiresolution-based bilinear recurrent neural network 总被引:1,自引:1,他引:0
Dong-Chul Park 《Knowledge and Information Systems》2009,19(2):235-248
A multiresolution-based bilinear recurrent neural network (MBLRNN) is proposed in this paper. The proposed MBLRNN is based
on the BLRNN that has robust abilities in modeling and predicting time series. The learning process is further improved by
using a multiresolution-based learning algorithm for training the BLRNN so as to make it more robust for the prediction of
time series data. The proposed MBLRNN is applied to the problems of network traffic prediction and electric load forecasting.
Experiments and results on both practical problems show that the proposed MBLRNN outperforms both the traditional multilayer
perceptron type neural network (MLPNN) and the BLRNN in the prediction accuracy.
相似文献
Dong-Chul ParkEmail: Email: |
937.
938.
It has been recently shown that calibration with an error less than Δ>0 is almost surely guaranteed with a randomized forecasting algorithm, where forecasts are obtained by random rounding the deterministic forecasts up to Δ. We show that this error cannot be improved for a vast majority of sequences: we prove that, using a probabilistic algorithm, we can effectively generate with probability close to one a sequence “resistant” to any randomized rounding forecasting with an error much smaller than Δ. We also reformulate this result by means of a probabilistic game. 相似文献
939.
Ioanna Lykourentzou Ioannis Giannoukos Vassilis Nikolopoulos George Mpardis Vassili Loumos 《Computers & Education》2009,53(3):950-965
In this paper, a dropout prediction method for e-learning courses, based on three popular machine learning techniques and detailed student data, is proposed. The machine learning techniques used are feed-forward neural networks, support vector machines and probabilistic ensemble simplified fuzzy ARTMAP. Since a single technique may fail to accurately classify some e-learning students, whereas another may succeed, three decision schemes, which combine in different ways the results of the three machine learning techniques, were also tested. The method was examined in terms of overall accuracy, sensitivity and precision and its results were found to be significantly better than those reported in relevant literature. 相似文献
940.
Estimating Siberian timber volume using MODIS and ICESat/GLAS 总被引:4,自引:0,他引:4
Geosciences Laser Altimeter System (GLAS) space LiDAR data are used to attribute a MODerate resolution Imaging Spectrometer (MODIS) 500 m land cover classification of a 10° latitude by 12° longitude study area in south-central Siberia. Timber volume estimates are generated for 16 forest classes, i.e., four forest cover types × four canopy density classes, across this 811,414 km2 area and compared with a ground-based regional volume estimate. Two regional GLAS/MODIS timber volume products, one considering only those pulses falling on slopes ≤ 10° and one utilizing all GLAS pulses regardless of slope, are generated. Using a two-phase(GLAS-ground plot) sampling design, GLAS/MODIS volumes average 163.4 ± 11.8 m3/ha across all 16 forest classes based on GLAS pulses on slopes ≤ 10° and 171.9 ± 12.4 m3/ha considering GLAS shots on all slopes. The increase in regional GLAS volume per-hectare estimates as a function of increasing slope most likely illustrate the effects of vertical waveform expansion due to the convolution of topography with the forest canopy response. A comparable, independent, ground-based estimate is 146 m3/ha [Shepashenko, D., Shvidenko, A., and Nilsson, S. (1998). Phytomass (live biomass) and carbon of Siberian forests. Biomass and Bioenergy, 14, 21-31], a difference of 11.9% and 17.7% for GLAS shots on slopes ≤ 10° and all GLAS shots regardless of slope, respectively. A ground-based estimate of total volume for the entire study area, 7.46 × 109 m3, is derived using Shepashenko et al.'s per-hectare volume estimate in conjunction with forest area derived from a 1990 forest map [Grasia, M.G. (ed.). (1990). Forest Map of USSR. Soyuzgiproleskhoz, Moscow, RU. Scale: 1:2,500,000]. The comparable GLAS/MODIS estimate is 7.38 × 109 m3, a difference of less than 1.1%. Results indicate that GLAS data can be used to attribute digital land cover maps to estimate forest resources over subcontinental areas encompassing hundreds of thousands of square kilometers. 相似文献