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31.
In most countries, the main step in the process of power system restoration, following a complete/partial blackout, is energization of primary restorative transmission lines. Artificial neural network (ANN) is employed for performing a nonlinear input–output mapping in this work, in order to estimate the temporary overvoltages (TOVs) due to transmission lines energization. In the proposed methodology, Levenberg–Marquardt second order method is used to train the multilayer perceptron. Proposed ANN is trained with equivalent circuit parameters of the network as input parameters, trained ANN has therefore satisfactory generalization capability. Both single and three-phase line energizations are analyzed. The simulated results for 39-bus New England test system, indicate that the proposed technique can estimate the peak values and duration of switching overvoltages with acceptable accuracy. 相似文献
32.
One of the most important assumptions in production scheduling is that the machines are permanently available without any breakdown. In the real world of scheduling, machines can be made unavailable due to various reasons such as preventive maintenance and unpredicted breakdown. In this paper, we explore flowshop configuration under the assumption of condition-based maintenance to minimize expected makespan. Furthermore, we consider a condition-based maintenance (CBM) strategy which could be used in most industrial settings. The proposed algorithm is designed for non-resumable flowshop state where the processing of jobs after preventive maintenance is restarted from the beginning. We propose a hybrid algorithm based on genetic algorithm and simulated annealing. Additionally, we conduct an extensive parameter calibration with the utilization of Taguchi method and select the optimal levels of the algorithm’s performance influential factors. The preliminary results indicate that the proposed method provides significantly better results compared with other high performing algorithms in the literature. 相似文献
33.
Sayed Yousef Monir Vaghefi Sayed Mahmoud Monir Vaghefi 《Neural computing & applications》2011,20(7):1055-1060
A multilayer feedforward neural network with two hidden layers was designed and developed for prediction of the phosphorus
content of electroless Ni–P coatings. The input parameters of the network were the pH, metal turnover, and loading of an electroless
bath. The output parameter was the phosphorus content of the electroless Ni–P coatings. The temperature and molar rate of
the bath were constant (
91° \textC, 0.4 \textNi\text + + /\textH2 \textPO2 - - 91^\circ {\text{C}},\:0.4\,{\text{Ni}}^{{{\text{ + + }}}} /{\text{H}}_{2} {\text{PO}}_{2}^{{ - - }} ). The network was trained and tested using the data gathered from our own experiments. The goal of the study was to estimate
the accuracy of this type of neural network in prediction of the phosphorus content. The study result shows that this type
of network has high accuracy even when the number of hidden neurons is very low. Some comparison between the network’s predictions
and own experimental data are given. 相似文献
34.
A resource investment problem with discounted cash flows (RIPDCF) is a project-scheduling problem in which (a) the availability levels of the resources are considered decision variables and (b) the goal is to find a schedule such that the net present value of the project cash flows optimizes. In this paper, the RIPDCF in which the activities are subject to generalized precedence relations is first modeled. Then, a genetic algorithm (GA) is proposed to solve this model. In addition, design of experiments and response surface methodology are employed to both tune the GA parameters and to evaluate the performance of the proposed method in 240 test problems. The results of the performance analysis show that the efficiency of the proposed GA method is relatively well. 相似文献
35.
Seyedali Mirjalili Seyed Mohammad Mirjalili Abdolreza Hatamlou 《Neural computing & applications》2016,27(2):495-513
This paper proposes a novel nature-inspired algorithm called Multi-Verse Optimizer (MVO). The main inspirations of this algorithm are based on three concepts in cosmology: white hole, black hole, and wormhole. The mathematical models of these three concepts are developed to perform exploration, exploitation, and local search, respectively. The MVO algorithm is first benchmarked on 19 challenging test problems. It is then applied to five real engineering problems to further confirm its performance. To validate the results, MVO is compared with four well-known algorithms: Grey Wolf Optimizer, Particle Swarm Optimization, Genetic Algorithm, and Gravitational Search Algorithm. The results prove that the proposed algorithm is able to provide very competitive results and outperforms the best algorithms in the literature on the majority of the test beds. The results of the real case studies also demonstrate the potential of MVO in solving real problems with unknown search spaces. Note that the source codes of the proposed MVO algorithm are publicly available at http://www.alimirjalili.com/MVO.html. 相似文献
36.
Seyed Ali Modarres Najafabadi József Kövecses Jorge Angeles 《Multibody System Dynamics》2008,20(2):163-176
This paper outlines a novel approach to the modeling and analysis of impact involving multibody systems. This approach is
based on an analysis of energy absorption and restitution during impact, using a decomposition of the kinetic energy, which
decouples the parts associated with the spaces of admissible and constrained motions of the underlying unilateral constraints.
Such a decomposition turns out to be useful in the analysis of energy dissipation during impact, and leads to a generalized
definition of the energetic coefficient of restitution, which targets particularly collisions in multibody systems. The applicability
of the approach reported is investigated by conducting an experimental study on a robotic testbed. It is shown that impact
between multibody systems is considerably affected not only by the local dynamics characteristics of the interacting bodies,
but also the configuration of the whole multibody system. The results reported here show that our decomposition can offer
a sound characterization of impact in several problems of multibody systems. 相似文献
37.
Determining the Main Factors in Declining the Urmia Lake Level by Using System Dynamics Modeling 总被引:6,自引:2,他引:4
Urmia Lake in Iran is the second largest saline lake in the world. This ecosystem is the home for different species. Due to
various socio-economical and ecological criteria, Urmia Lake has important role in the Northwestern part of the country but
it has faced many problems in recent years. Because of droughts, overuse of surface water resources and dam constructions,
water level has decreased in such a way that one quarter of the lake has changed to saline area in the last 10 years. The
purpose of this research is to determine the main factors which reduce the lake’s water level. To this end, a simulation model,
based on system dynamics method, is developed for the Urmia Lake basin to estimate the lake’s level. After successful verification
of the model, results show that (among the proposed factors) changes in inflows due to the climate change and overuse of surface
water resources is the main factor for 65% of the effect, constructing four dams is responsible for 25% of the problem, and
less precipitation on lake has 10% effect on decreasing the lake’s level in the recent years. In the future, the model also
can be used by managers as a decision support system to find the effects of building new dams or other infrastructures. 相似文献
38.
Ata Allah Taleizadeh Seyed Taghi Akhavan Niaki Seyed Mohammad Haji Seyedjavadi 《Journal of Manufacturing Systems》2012
In this paper, a multiproduct inventory control problem is considered in which the periods between two replenishments of the products are assumed independent random variables, and increasing and decreasing functions are assumed to model the dynamic demands of each product. Furthermore, the quantities of the orders are assumed integer-type, space and budget are constraints, the service-level is a chance-constraint, and that the partial back-ordering policy is taken into account for the shortages. The costs of the problem are holding, purchasing, and shortage. We show the model of this problem is an integer nonlinear programming type and to solve it, a harmony search approach is used. At the end, three numerical examples of different sizes are given to demonstrate the applicability of the proposed methodology in real world inventory control problems, to validate the results obtained, and to compare its performances with the ones of both a genetic and a particle swarm optimization algorithms. 相似文献
39.
Seyed Jafar Sadjadi Seyed Ahmad Yazdian Kamran Shahanaghi 《Computers & Industrial Engineering》2012,62(1):349-358
In the classical economic production quantity (EPQ) problem demand is considered to be known in advance. However, in the real-world, demand of a product is a function of factors such as product’s price, its quality, and marketing expenditures for promoting the product. Quality level of the product and specifications of the adopted manufacturing process also affect the unit product’s cost. Therefore, in this paper we consider a profit maximizing firm who wants to jointly determine the optimal lot-sizing, pricing, and marketing decisions along with manufacturing requirements in terms of flexibility and reliability of the process. Geometric programming (GP) technique is proposed to address the resulting nonlinear optimization problem. Using recent advances in optimization techniques we are able to optimally solve the developed, highly nonlinear, mathematical model. Finally, using numerical examples, we illustrate the solution approach and analyze the solution under different conditions. 相似文献
40.