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1.
2.
活性焦的热解析参数对再生活性焦的脱硫脱硝性能和机械强度至关重要。为了明确解析参数对活性焦再生过程和再生效果的影响规律,通过热解析试验探究活性焦硫残余比例、CO2和CO生成量及再生活性焦脱硫脱硝性能随解析温度和解析时间的变化规律,继而明确适宜的活性焦热解析参数。结果表明,活性焦升温解析过程中,脱硫产物在317 ℃左右迅速分解,随后分解速率下降;在进入恒温解析阶段后脱硫产物分解速率先快速下降,而后进入缓慢解析状态。硫残余比例随恒温解析温度的升高而下降,在530 ℃下解析3 h可使脱硫产物完全解析;解析温度高于430 ℃后,活性焦表面的酚基、醌基、内酯基等含氧官能团分解量明显增加,并随恒温解析温度的升高而持续增加,分解所生成的CO和CO2也随之大幅增加,这将使活性焦的孔隙结构进一步发展,继而不利于活性焦机械强度的保持;解析温度低于530 ℃时,硫残余比例随解析温度的升高而持续降低,使再生活性焦的脱硫脱硝性能持续提高;解析温度高于530 ℃后,含氧官能团分解量随解析温度的升高而持续增加,这将有利于提高活性焦表面SO2氧化反应速率,继而使再生活性焦的脱硫性能持续升高,但酚基、内酯基等酸性含氧官能团的分解使再生活性焦对NH3的吸附性能降低,进而使其脱硝性能降低。在兼顾再生活性焦脱硫脱硝性能、机械强度和生产效率等多方面因素时,430 ℃恒温解析3 h是相对较优的解析参数。在此解析条件下,再生活性焦的硫残余比例仅为1.8%,含氧官能团尚未发生大量分解,脱硫脱硝性能相对较为优良。 相似文献
3.
The most common form of cancer for women is breast cancer. Recent advances in medical imaging technologies increase the use of digital mammograms to diagnose breast cancer. Thus, an automated computerized system with high accuracy is needed. In this study, an efficient Deep Learning Architecture (DLA) with a Support Vector Machine (SVM) is designed for breast cancer diagnosis. It combines the ideas from DLA with SVM. The state-of-the-art Visual Geometric Group (VGG) architecture with 16 layers is employed in this study as it uses the small size of 3 × 3 convolution filters that reduces system complexity. The softmax layer in VGG assumes that the training samples belong to exactly only one class, which is not valid in a real situation, such as in medical image diagnosis. To overcome this situation, SVM is employed instead of the softmax layer in VGG. Data augmentation is also employed as DLA usually requires a large number of samples. VGG model with different SVM kernels is built to classify the mammograms. Results show that the VGG-SVM model has good potential for the classification of Mammographic Image Analysis Society (MIAS) database images with an accuracy of 98.67%, sensitivity of 99.32%, and specificity of 98.34%. 相似文献
4.
利用推荐系统进行群组推荐时,群组成员之间的交互关系对推荐结果有很大影响,但传统的群组推荐算法较少考虑用户信任度的重要性,致使社交关系信息不能得到充分利用。在群组融合时考虑群组内用户间的交互关系,提出一种基于用户信任度和概率矩阵的群组推荐算法。在获取用户信任度数据后,使用概率矩阵分解(PMF)算法补全信任度矩阵并进行归一化处理,得到相似度矩阵,同时在后验概率计算过程中加入用户间的信任度因素,通过极大化后验概率获得预测评分。在此基础上,对群组中用户的权重进行归一化处理,使用基于用户交互关系的权重策略融合群组成员偏好,得到最终的推荐结果。在Epinions和FilmTrust数据集上的实验结果表明,该算法可使融合结果更具群组特性,同时提高推荐结果的可靠性和可解释性,且均方根误差和命中率均优于PMF、NeuMF、RippleNet等对比算法。 相似文献
5.
从铂族金属二次资源中回收铂族金属,对于解决我国铂族金属的供需矛盾及可持续发展具有重要意义。火法工艺回收在工业生产上应用多、技术较成熟。本文详细总结了火法回收铂族金属工艺研究进展,其中以铅、铜、铁、锍等金属捕集法在工业上应用较多、技术较成熟,其中铁捕集法、铜捕集法回收率高、发展前景广阔;高温氯化挥发法对设备要求高、产生有毒气体;焚烧法仅适用于处理炭质载体催化剂;未来需针对火法回收工艺中存在的相关问题进行深入基础研究,同时开发高效清洁回收新方法,实现我国铂族金属二次资源的高效清洁循环利用。 相似文献
6.
The outsourced storage mode of cloud computing leads to the separation of data ownership and management rights of data owners, which changes the data storage network model and security model. To effectively deal with the software and hardware failures of the cloud server and the potential dishonest service provider and also ensure the availability of the data owners’ data, the design of secure and efficient data availability and recoverability auditing scheme has both theoretical and practical importance in solving the concern of users and ensuring the security of cloud data. However, most of the existing studies were designed for the security and efficiency of data integrity or recoverability schemes, without considering the fast identification and reliable recovery of damaged data under dynamic group users. Thus, to quickly identify and recover damaged data, a publicly verifiable proof of storage scheme was proposed for dynamic group cloud users. The designed scheme enabled a trusted third-party auditor to efficiently identify the damaged files through a challenge-response protocol and allowed the cloud storage server to effectively recover them when the degree of data damage is less than an error correction ability threshold. The scheme combined association calculation and accumulation calculation, which effectively reduced the number of calculations for the identification of damaged data. By combining erasure coding and shared coding technology, the scheme achieved effective recovery of damaged data of dynamic group users. At the same time, the scheme also supported dynamic user revocation, which ensured the integrity audit and reliable recovery of the collective data after user revocation. The network model and threat model of the designed scheme were defined and the security of the scheme under the corresponding security model was proved. Through the prototype implementation of the scheme in the real environment and the modular performance analysis, it is proved that the proposed scheme can effectively identify the damaged data and reliably recover the cloud data when the data is damaged. Besides, compared with other schemes, it is also proved that the proposed scheme has less computational overhead in identifying and recovering damaged data. © 2022, Beijing Xintong Media Co., Ltd.. All rights reserved. 相似文献
7.
Large-scale group decision-making problems based on social network analysis and minimum cost consensus models (MCCMs) have recently attracted considerable attention. However, few studies have combined them to form a complete decision-making system. Accordingly, we define the satisfaction index to optimize the classical MCCM by considering the effect of the group on individuals. Similarly, we define the consistency index to optimize the consensus reaching process (CRP). Regarding the evolution of the consensus network, the Louvain algorithm is used to divide the entire group into several subgroups to ensure that each subgroup is independent but has strong cohesion. By constructing the MCCM based on the satisfaction index and the optimized consensus-reaching process, the group opinions in each subgroup are ranked to obtain the final ranking of alternatives. Finally, to verify the validity of CRP and the practical value of the proposed model, we conduct consensus network evolution and decision-making analysis in the case of a negotiation between the government and polluting companies to achieve uniform pollution emissions. Sensitivity analysis is performed to demonstrate the stability of the subgroup weights. Furthermore, a comparative analysis using existing models verifies the effectiveness of the proposed model. 相似文献
8.
为了安全开采含有较多采空区的矿体,制定了2种卸压方案,并采用FLAC3D软件对矿体进行建模,模拟并分析了其卸压效果。结果表明,采用方案1(卸压巷道与凿岩巷道呈“非”字形、相邻卸压巷道间隔10 m)时,最小主应力在凿岩巷道两边及顶板附近分别从8 MPa和9 MPa降至5 MPa和8 MPa,最大主应力变化不大; 采用方案2(交错式开挖卸压巷道、相邻卸压巷道间隔20 m)时,最小主应力在凿岩巷道与卸压巷道的交汇处从8 MPa降至4 MPa,最大主应力在下层凿岩巷道顶板附近由24 MPa降至20 MPa。模拟结果表明,方案2的卸压效果优于方案1。小厂坝矿区按方案2进行卸压巷道施工,安全地完成了60万吨矿体开采。研究成果对巷道卸压的工程实践具有一定参考价值。 相似文献
9.
水库群供水规则中蓄供水次序与调度图彼此影响,如何实现二者联合优化是供水调度的难点。为此,提出了供水水库群蓄供水次序与调度图双层优化方法。首先合理拟定不同蓄供水次序,其次求解各次序对应最优调度图,最后通过模拟调度比选最佳蓄供水次序与调度图组合。应用该方法对宝鸡峡灌区六库混联供水系统开展了实例研究。结果表明,若上游水库先蓄水且先供水或下游水库先蓄水且先供水均会增大灌区缺水率、降低供水空间公平性,最优蓄供水次序为上游水库先蓄水、下游水库先供水。较现状调度方案,采用最优蓄供水次序及对应调度图组合可有效缓解灌区缺水状况,缩小分区供水效益的差异。本方法为水库群蓄供水次序与调度图联合优化提供了可行途径。 相似文献
10.
南水北调中线总干渠无在线调蓄水库,对藻类生态调度过程中出现的问题开展生态调度实现策略和实施方式研究。主要实现策略包括:划定自身的调蓄区,隔离生态调度对下游的影响;采用高效的渠池运行方式,减少生态调度时蓄量的反复调整;综合考虑安全、快速、平稳等需求,设定生态调度实施进程和方式。具体实施方式包括:将总干渠划分为流速调控区、调蓄区和正常运行区,分别实施等体积、控制蓄量和闸前常水位方式运行;将生态调度过程划分为充水阶段和泄水阶段,基于流速调控目标值、持续时长和水位降幅约束条件,确定各阶段时长和各分区的闸门群调控方案等。基于2018年3月输水工况,采用明渠一维非恒定流模型,仿真总干渠上游15个渠池的藻类生态调度过程。结果表明,生态调度可在3.5 d内完成,各渠池的平均流速由0.48 m/s增至0.93 m/s,持续时间超过2 h。在整个生态调度过程中,水位变化平稳,水位变幅符合安全阈值要求,下游渠道的正常运行未受生态调度明显影响。 相似文献