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11.
Unsupervised Multiway Data Analysis: A Literature Survey 总被引:1,自引:0,他引:1
Two-way arrays or matrices are often not enough to represent all the information in the data and standard two-way analysis techniques commonly applied on matrices may fail to find the underlying structures in multi-modal datasets. Multiway data analysis has recently become popular as an exploratory analysis tool in discovering the structures in higher-order datasets, where data have more than two modes. We provide a review of significant contributions in the literature on multiway models, algorithms as well as their applications in diverse disciplines including chemometrics, neuroscience, social network analysis, text mining and computer vision. 相似文献
12.
Sunil Kumar Richard J. Pippy Erdem Acar Nam H. Kim Raphael T. Haftka 《Structural and Multidisciplinary Optimization》2009,38(6):613-626
Probabilistic structural design deals with uncertainties in response (e.g. stresses) and capacity (e.g. failure stresses).
The calculation of the structural response is typically expensive (e.g., finite element simulations), while the capacity is
usually available from tests. Furthermore, the random variables that influence response and capacity are often disjoint. In
previous work we have shown that this disjoint property can be used to reduce the cost of obtaining the probability of failure
via Monte Carlo simulations. In this paper we propose to use this property for an approximate probabilistic optimization based
on exact capacity and approximate response distributions (ECARD). In Approximate Probabilistic Optimization Using ECARD, the
change in response distribution is approximated as the structure is re-designed while the capacity distribution is kept exact,
thus significantly reducing the number of expensive response simulations. ECARD may be viewed as an extension of SORA (Sequential
Optimization and Reliability Assessment), which proceeds with deterministic optimization iterations. In contrast, ECARD has
probabilistic optimization iterations, but in each iteration, the response distribution is approximated so as not to require
additional response calculations. The use of inexpensive probabilistic optimization allows easy incorporation of system reliability
constraints and optimal allocation of risk between failure modes. The method is demonstrated using a beam problem and a ten-bar
truss problem. The former allocates risk between two different failure modes, while the latter allocates risk between members.
It is shown that ECARD provides most of the improvement from risk re-allocation that can be obtained from full probabilistic
optimization. 相似文献
13.
In the design of hearing aids (HA), the real-time speech-enhancement is done. The digital hearing aids should provide high signal-to-noise ratio, gain improvement and should eliminate feedback. In generic hearing aids the performance towards different frequencies varies and non uniform. Existing noise cancellation and speech separation methods drops the voice magnitude under the noise environment. The performance of the HA for frequency response is non uniform. Existing noise suppression methods reduce the required signal strength also. So, the performance of uniform sub band analysis is poor when hearing aid is concern. In this paper, a speech separation method using Non-negative Matrix Factorization (NMF) algorithm is proposed for wavelet decomposition. The Proposed non-uniform filter-bank was validated by parameters like band power, Signal-to-noise ratio (SNR), Mean Square Error (MSE), Signal to Noise and Distortion Ratio (SINAD), Spurious-free dynamic range (SFDR), error and time. The speech recordings before and after separation was evaluated for quality using objective speech quality measures International Telecommunication Union -Telecommunication standard ITU-T P.862. 相似文献
14.
Yakup Kara Melek Acar Boyacioglu Ömer Kaan Baykan 《Expert systems with applications》2011,38(5):5311-5319
Prediction of stock price index movement is regarded as a challenging task of financial time series prediction. An accurate prediction of stock price movement may yield profits for investors. Due to the complexity of stock market data, development of efficient models for predicting is very difficult. This study attempted to develop two efficient models and compared their performances in predicting the direction of movement in the daily Istanbul Stock Exchange (ISE) National 100 Index. The models are based on two classification techniques, artificial neural networks (ANN) and support vector machines (SVM). Ten technical indicators were selected as inputs of the proposed models. Two comprehensive parameter setting experiments for both models were performed to improve their prediction performances. Experimental results showed that average performance of ANN model (75.74%) was found significantly better than that of SVM model (71.52%). 相似文献
15.
16.
Despite the importance of knowledge transfer for firms involved in foreign direct investment activities, this area has not
received appropriate attention from the perspectives of both the knowledge transferor (i.e., MNC parent) and the knowledge
recipient. To fill in the gap in the current literature we propose a model to understand the links between criteria complicating
the transfer of knowledge and preferences that the company has to focus. This model is based on both the existing literature
as well as views of company representatives and provides a useful methodology for identifying decision making problems on
the transfer of knowledge. In this paper, we investigate the fuzzy linear programming technique (FLP) to analyze these links
and for multiple attribute group decision making (MAGDM) problems with preference information on criteria. To reflect the
decision maker’s subjective preference information and to determine the weight vector of attributes, the technique for order
preference by similarity to ideal solution (TOPSIS) developed by Hwang and Yoon (1995) and the linear programming technique
for multidimensional analysis of preference (LINMAP) developed by Sirinivasan and Shocker (Psychometrica 38:337–369, 1973)
are used. 相似文献
17.
Acar Esra Hopfgartner Frank Albayrak Sahin 《Multimedia Tools and Applications》2017,76(9):11809-11837
Multimedia Tools and Applications - In today’s society where audio-visual content such as professionally edited and user-generated videos is ubiquitous, automatic analysis of this content is... 相似文献
18.
19.
M. Erdal ?zbek Nalan ?zkurt F. Acar Savac? 《Journal of Intelligent Information Systems》2012,38(1):241-256
The time-varying frequency structure of musical signals have been analyzed using wavelets by either extracting the instantaneous
frequency of signals or building features from the energies of sub-band coefficients. We propose to benefit from a combination
of these two approaches and use the time-frequency domain energy localization curves, called as wavelet ridges, in order to
build features for classification of musical instrument sounds. We evaluated the representative capability of our feature
in different musical instrument classification problems using support vector machine classifiers. The comparison with the
features based on parameterizing the wavelet sub-band energies confirmed the effectiveness of the proposed feature. 相似文献
20.
Phylogenetic tree construction has received much attention recently due to the availability of vast biological data. In this study, we provide a three step method to build phylogenetic trees. Firstly, a density-based clustering algorithm is used to provide clusters of the population at hand using the distance matrix which shows the distances of the species. Secondly, a phylogenetic tree for each cluster is constructed by using the neighbor-joining (NJ) algorithm and finally, the roots of the small phylogenetic trees are connected again by the NJ algorithm to form one large phylogenetic tree. To our knowledge, this is the first method for building phylogenetic trees that uses clustering prior to forming the tree. As such, it provides independent phylogenetic tree formation within each cluster as the second step, hence is suitable for parallel/distributed processing, enabling fast processing of very large biological data sets.The proposed method, clustered neighbor-joining (CNJ) is applied to 145 samples from the Y-DNA Haplogroup G. Distances between male samples are the variation in their set of Y-chromosomal short tandem repeat (STR) values. We show that the clustering method we use is superior to other clustering methods as applied to Y-DNA data and also independent, fast distributed construction of phylogenetic trees is possible with this method. 相似文献