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1.
The operational optimisation of coal-fired power units is important for saving energy and reducing losses in the electric power industry. One of the key issues is how to determine the benchmark values of the energy efficiency indexes of the units. Therefore, a new framework for determining these benchmark values is proposed, based on data mining methods. First, the energy efficiency key performance indicators (KPIs) associated with the net coal consumption rate (NCCR) were selected based on the domain knowledge. Second, the decision-making samples with minimal NCCR were acquired with the fuzzy C-means (FCM) clustering algorithm, and the corresponding clustering centres were employed as the benchmark values. Finally, based on the support vector regression (SVR) algorithm, the target values of the NCCR were obtained with the KPIs as input, and the energy saving potential was evaluated by comparing the target values with the historical values of the NCCR. An actual on-duty 1000 MW unit was taken as study unit, and the results show that the energy saving potential is remarkable when the operators adjust the KPIs based on the calculated benchmark values. 相似文献
2.
Assembly line balancing is important for the efficiency of the assembly process, however, a wide range of disruptions can break the current workload balance. Some researchers explored the task assignment plan for the assembly line balancing problem with the assumption that the assembly process is smooth with no disruption. Other researchers considered the impacts of disruptions, but they only explored the task re-assignment solutions for the assembly line re-balancing problem with the assumption that the re-balancing decision has been made already. There is limited literature exploring on-line adjustment solutions (layout adjustment and production rate adjustment) for an assembly line in a dynamic environment. This is because real-time monitoring of an assembly process was impossible in the past, and it is difficult to incorporate uncertainty factors into the balancing process because of the randomness and non-linearity of these factors. However, Industry 4.0 breaks the information barriers between different parts of an assembly line, since smart, connected products, which are enabled by advanced information and communication technology, can intelligently interact and communicate with each other and collect, process and produce information. Smart control of an assembly line becomes possible with the large amounts of real-time production data in the era of Industry 4.0, but there is little literature considering this new context. In this study, a fuzzy control system is developed to analyze the real-time information of an assembly line, with two types of fuzzy controllers in the fuzzy system. Type 1 fuzzy controller is used to determine whether the assembly line should be re-balanced to satisfy the demand, and type 2 fuzzy controller is used to adjust the production rate of each workstation in time to eliminate blockage and starvation, and increase the utilization of machines. Compared with three assembly lines without the proposed fuzzy control system, the assembly line with the fuzzy control system performs better, in terms of blockage ratio, starvation ratio and buffer level. Additionally, with the improvement of information transparency, the performance of an assembly line will be better. The research findings shed light on the smart control of the assembly process, and provide insights into the impacts of Industry 4.0 on assembly line balancing. 相似文献
3.
针对星载合成孔径雷达(SAR)天线要求在超低转速下平稳转动,同时满足小型化轻量化的要求,本文提出一种基于微步距模式的天线转动控制技术,该技术使用两个带PWM电路的全桥驱动器通过微步距方式驱动步进电机。在给出系统架构、微步距控制原理后,进一步提出可靠性设计的具体措施。经测试和环境试验验证,该技术对同类应用具有一定的参考价值。 相似文献
4.
计算机技术、控制技术及信息技术的发展,电力系统自动化面临着空前的变革,多媒体技术、智能控制技术将迅速进入电力系统自动化领域。 相似文献
5.
A Takagi-Sugeno adaptive neuro-fuzzy inference system (TSFIS) model is developed and applied to a dataset of wellhead flow-test data for the Resalat oil field located offshore southern Iran, the objective is to assist in the prediction and control of multi-phase flow rates of oil and gas through the wellhead chokes. For this purpose, 182 test data points (Appendix 1) related to the Resalat field are evaluated. In order to predict production flow rate (QL) expressed as stock-tank barrels per day (STB/D), this dataset includes four selected input variables: upstream pressure (Pwh); wellhead choke sizes (D64); gas to liquid ratio (GLR); and, base solids and water including some water-soluble oil emulsion (BS&W). The test data points evaluated include a wide range of oil flow rate conditions and values for the four input variables recorded. The TSFIS algorithm applied involves five data processing steps: a) pre-processing, b) fuzzification, c) rules base and adaptive neuro-fuzzy inference engine, d) defuzzification, and e) post-processing of the fuzzy model. The developed TSFIS model for the Resalat oil field database predicted oil flow rate to a high degree of accuracy (root mean square error = 247 STB/D, correlation coefficient = 0.9987), which improves substantially on the commonly used empirical algorithms used for such predictions. TSFIS can potentially be applied in wellhead choke fuzzy controllers to stabilize flow in specific wells based on real-time input data records. 相似文献
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In this paper, a robust controller for a Six Degrees of Freedom (6 DOF) coaxial octorotor helicopter control is proposed in presence of actuator faults. Radial Base Function Neural Network (RBFNN), Fuzzy Logic Control approach (FLC) and Sliding Mode Control (SMC) technique are used to design a controller, named Fault Tolerant Control (FTC), for each subsystem of the octorotor helicopter. The proposed FTC scheme allows avoiding difficult modeling, attenuating the chattering effect of the SMC, reducing the rules number of the fuzzy controller, and guaranteeing the stability and the robustness of the system. The simulation results show that the proposed FTC can greatly alleviate the chattering effect, good tracking in presence of actuator faults. 相似文献
9.
以鄂尔多斯盆地靖边气田A井区为例,采用单因素相关分析和数值模拟方法,对比研究了井网控制程度、储层物性及地层废弃压力对气藏采收率影响及其主次关系。结果表明,井网控制程度是影响采收率的首要因素,井网控制程度每增加10%,采收率提高8.5%;渗透率是影响采收率的重要因素,渗透率每增加10%,采收率平均增加6%;废弃压力对采收率亦有较大影响,废弃压力每降低10%,采收率可提高1.6%。三者对采收率影响综合排序为:井网控制程度>储层物性>废弃压力。分析认为,渗透率是储层固有属性,很难从根本改变;而废弃压力受井口外输压力和增压开采成本制约,降低幅度有限。因此,优化井网及增加井网控制程度是提高气藏采收率的有效途径。研究成果具有实践意义,可为改进气田开发方式和提高气藏采收率提供参考。 相似文献
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