全文获取类型
收费全文 | 435篇 |
免费 | 19篇 |
国内免费 | 2篇 |
专业分类
电工技术 | 4篇 |
综合类 | 1篇 |
化学工业 | 117篇 |
金属工艺 | 8篇 |
机械仪表 | 16篇 |
建筑科学 | 17篇 |
矿业工程 | 3篇 |
能源动力 | 30篇 |
轻工业 | 26篇 |
水利工程 | 4篇 |
石油天然气 | 3篇 |
无线电 | 31篇 |
一般工业技术 | 66篇 |
冶金工业 | 25篇 |
原子能技术 | 5篇 |
自动化技术 | 100篇 |
出版年
2024年 | 1篇 |
2023年 | 3篇 |
2022年 | 5篇 |
2021年 | 10篇 |
2020年 | 5篇 |
2019年 | 17篇 |
2018年 | 15篇 |
2017年 | 18篇 |
2016年 | 14篇 |
2015年 | 8篇 |
2014年 | 14篇 |
2013年 | 45篇 |
2012年 | 33篇 |
2011年 | 31篇 |
2010年 | 24篇 |
2009年 | 29篇 |
2008年 | 17篇 |
2007年 | 26篇 |
2006年 | 22篇 |
2005年 | 15篇 |
2004年 | 23篇 |
2003年 | 9篇 |
2002年 | 4篇 |
2001年 | 6篇 |
2000年 | 6篇 |
1999年 | 8篇 |
1998年 | 3篇 |
1997年 | 5篇 |
1996年 | 8篇 |
1995年 | 3篇 |
1994年 | 1篇 |
1993年 | 4篇 |
1992年 | 3篇 |
1990年 | 3篇 |
1989年 | 3篇 |
1988年 | 4篇 |
1987年 | 1篇 |
1986年 | 1篇 |
1985年 | 1篇 |
1983年 | 2篇 |
1982年 | 2篇 |
1979年 | 1篇 |
1978年 | 1篇 |
1976年 | 1篇 |
1973年 | 1篇 |
排序方式: 共有456条查询结果,搜索用时 15 毫秒
1.
A fuzzy logic based-method for prognostic decision making in breast and prostate cancers 总被引:1,自引:0,他引:1
Seker H. Odetayo M.O. Petrovic D. Naguib R.N.G. 《IEEE transactions on information technology in biomedicine》2003,7(2):114-122
Accurate and reliable decision making in oncological prognosis can help in the planning of suitable surgery and therapy, and generally, improve patient management through the different stages of the disease. In recent years, several prognostic markers have been used as indicators of disease progression in oncology. However, the rapid increase in the discovery of novel prognostic markers resulting from the development in medical technology, has dictated the need for developing reliable methods for extracting clinically significant markers where complex and nonlinear interactions between these markers naturally exist. The aim of this paper is to investigate the fuzzy k-nearest neighbor (FK-NN) classifier as a fuzzy logic method that provides a certainty degree for prognostic decision and assessment of the markers, and to compare it with: 1) logistic regression as a statistical method and 2) multilayer feedforward backpropagation neural networks an artificial neural-network tool, the latter two techniques having been widely used for oncological prognosis. In order to achieve this aim, breast and prostate cancer data sets are considered as benchmarks for this analysis. The overall results obtained indicate that the FK-NN-based method yields the highest predictive accuracy, and that it has produced a more reliable prognostic marker model than both the statistical and artificial neural-network-based methods. 相似文献
2.
The problem of operating freeze drying of pharmaceutical products in vials placed in trays of a freeze dryer to remove free water (in frozen state) at a minimum time was formulated as an optimal control problem. Two different types of freeze dryer designs were considered. In type I freeze dryer design, upper and lower plate temperatures were controlled together, while in type II freeze dryer design, upper and lower plate temperatures were controlled independently. The heat input to the material being dried and the drying chamber pressure were considered as control variables. Constraints were placed on the system state variables by the melting and scorch temperatures during primary drying stage. Necessary conditions of optimality for the primary drying stage of freeze drying process in vials are derived and presented. Furthermore, an approach for constructing the optimal control policies that would minimize the drying time for the primary drying stage was given. In order to analyze optimal control policy for the primary drying stage of the freeze-drying process in vials, a rigorous multi-dimensional unsteady state mathematical model was used. The theoretical approach presented in this work was applied in the freeze drying of skim milk. Significant reductions in the drying times of primary drying stage of freeze drying process in vials were obtained, as compared to the drying times obtained from conventional operational policies. 相似文献
3.
Pharmacodynamic Comparison of a Nasal Formulation of Verapamil and Intravenous and Oral Dosage Forms
The nasal route has been shown to be effective for the administration of numerous drugs in order to improve drug bioavailability. A nasal gel of verapamil hydrochloride was formulated and evaluated pharmacodynamically in humans, using electrocardiographic results, with comparison to oral and IV routes. Seven volunteers were involved in the study and the pharmacodynamic parameters were evaluated statistically. Experimental nasal gel showed similar pharmacodynamic results with the intravenous route, which is a hint to the reduction in verapamilinduced first-pass metabolism. However, oral route of administration showed a tendency of less efficacy. No reasonable effect of verapamil could be obtained with the placebo group. 相似文献
4.
5.
Forecasting based on sectoral energy consumption of GHGs in Turkey and mitigation policies 总被引:1,自引:0,他引:1
Recently, global warming and its effects have become one of the most important themes in the world. Under the Kyoto Protocol, the EU has agreed to an 8% reduction in its greenhouse gas (GHG) emissions by 2008–2012. The GHG emissions (total GHG, CO2, CO, SO2, NO2, E (emissions of non-methane volatile organic compounds)) covered by the Protocol are weighted by their global warming potentials (GWPs) and aggregated to give total emissions in CO2 equivalents. The main subject in this study is to obtain equations by the artificial neural network (ANN) approach to predict the GHGs of Turkey using sectoral energy consumption. The equations obtained are used to determine the future level of the GHG and to take measures to control the share of sectors in total emission. According to ANN results, the maximum mean absolute percentage error (MAPE) was found as 0.147151, 0.066716, 0.181901, 0.105146, 0.124684, and 0.158157 for GHG, SO2, NO2, CO, E, and CO2, respectively, for the training data with Levenberg–Marquardt (LM) algorithm by 8 neurons. R2 values are obtained very close to 1. Also, this study proposes mitigation policies for GHGs. 相似文献
6.
We introduce a probability model for populations of cells and viruses that interact in the presence of an anti-viral agent. Cells can be infected by viruses, and their longevity and ability to avoid infection are modified if they survive successive attacks by viruses. Viruses that survive the effect of the anti-viral agent may find that their ability to survive a future encounter with molecules of the anti-viral agent is modified, as is their ability to infect a healthy cell. Additionally, we assume that the anti-viral agents can be a cocktail with different proportions of agents that target different strains of the virus. In this paper, we give the state equations for the model and derive its analytical solution in steady state. The solution then provides insight into the appropriate mix or “cocktail” of anti-viral agents that can be designed to deal with the virus' ability to mutate. In particular, the analysis shows that the concentration of anti-viral agent by itself does not suffice to ultimately control the infection, and that it is important to dose a mix of anti-viral agents so as to target each strain of virus in a specific manner, taking into account the ability of each virus strain to survive in the presence of the anti-viral agents. Models of this kind may eventually lead to the computer aided design of therapeutic protocols or drug design. 相似文献
7.
The Journal of Supercomputing - In recent years, deep artificial neural networks can have better forecasting performance than many other artificial neural networks. The long short-term memory... 相似文献
8.
Cagdas Hakan Aladag Ufuk Yolcu Erol Egrioglu Ali Z. Dalar 《Applied Soft Computing》2012,12(10):3291-3299
In the analysis of time invariant fuzzy time series, fuzzy logic group relationships tables have been generally preferred for determination of fuzzy logic relationships. The reason of this is that it is not need to perform complex matrix operations when these tables are used. On the other hand, when fuzzy logic group relationships tables are exploited, membership values of fuzzy sets are ignored. Thus, in defiance of fuzzy set theory, fuzzy sets’ elements with the highest membership value are only considered. This situation causes information loss and decrease in the explanation power of the model. To deal with these problems, a novel time invariant fuzzy time series forecasting approach is proposed in this study. In the proposed method, membership values in the fuzzy relationship matrix are computed by using particle swarm optimization technique. The method suggested in this study is the first method proposed in the literature in which particle swarm optimization algorithm is used to determine fuzzy relations. In addition, in order to increase forecasting accuracy and make the proposed approach more systematic, the fuzzy c-means clustering method is used for fuzzification of time series in the proposed method. The proposed method is applied to well-known time series to show the forecasting performance of the method. These time series are also analyzed by using some other forecasting methods available in the literature. Then, the results obtained from the proposed method are compared to those produced by the other methods. It is observed that the proposed method gives the most accurate forecasts. 相似文献
9.
Fuzzy time series approaches are used when observations of time series contain uncertainty. Moreover, these approaches do not require the assumptions needed for traditional time series approaches. Generally, fuzzy time series methods consist of three stages, namely, fuzzification, determination of fuzzy relations, and defuzzification. Artificial intelligence algorithms are frequently used in these stages with genetic algorithms being the most popular of these algorithms owing to their rich operators and good performance. However, the mutation operator of a GA may cause some negative results in the solution set. Thus, we propose a modified genetic algorithm to find optimal interval lengths and control the effects of the mutation operator. The results of applying our new approach to real datasets show superior forecasting performance when compared with those obtained by other techniques. 相似文献
10.
Multilayer perceptron has been widely used in time series forecasting for last two decades. However, it is a well-known fact that the forecasting performance of multilayer perceptron is negatively affected when data have outliers and this is an important problem. In recent years, some alternative neuron models such as generalized-mean neuron, geometric mean neuron, and single multiplicative neuron have been also proposed in the literature. However, it is expected that forecasting performance of artificial neural network approaches based on these neuron models can be also negatively affected by outliers since the aggregation function employed in these models is based on mean value. In this study, a new multilayer feed forward neural network, which is called median neuron model multilayer feed forward (MNM-MFF) model, is proposed in order to deal with this problem caused by outliers and to reach high accuracy level. In the proposed model, unlike other models suggested in the literature, MNM which has median-based aggregation function is employed. MNM is also firstly defined in this study. MNM-MFF is a robust neural network method since aggregation functions in MNM-MFF are based on median, which is not affected much by outliers. In addition, to train MNM-MFF model, particle swarm optimization method was utilized. MNM-MFF was applied to two well-known time series in order to evaluate the performance of the proposed approach. As a result of the implementation, it was observed that the proposed MNM-MFF model has high forecasting accuracy and it is not affected by outlier as much as multilayer perceptron model. Proposed method brings improvement in 7 % for data without outlier, in 90 % for data with outlier, in 95 % for data with bigger outlier. 相似文献