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排序方式: 共有207条查询结果,搜索用时 15 毫秒
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Neural Processing Letters - Political optimizer (PO) is a recently proposed human-behavior inspired meta-heuristic, which has shown tremendous performance on complex multimodal functions as well as... 相似文献
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Muhammad Waseem Rizwan Ahmed Muhammad Irfan Shahid Qamar 《Quantum Information Processing》2013,12(12):3649-3664
We present a scheme for the implementation of three-qubit Grover’s algorithm using four-level superconducting quantum interference devices (SQUIDs) coupled to a superconducting resonator. The scheme is based on resonant, off-resonant interaction of the cavity field with SQUIDs and application of classical microwave pulses. We show that adjustment of SQUID level spacings during the gate operations, adiabatic passage, and second-order detuning are not required that leads to faster implementation. We also show that the marked state can be searched with high fidelity even in the presence of unwanted off-resonant interactions, level decay, and cavity dissipation. 相似文献
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Hassan Md Rafiul Ismail Walaa N Chowdhury Ahmad Hossain Sharara Huda Shamsul Hassan Mohammad Mehedi 《The Journal of supercomputing》2022,78(7):10250-10274
The Journal of Supercomputing - This paper designs and develops a computational intelligence-based framework using convolutional neural network (CNN) and genetic algorithm (GA) to detect COVID-19... 相似文献
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A kinetic flux-vector splitting (KFVS) scheme for the shallow water magnetohydrodynamic (SWMHD) equations in one- and two-space dimensions is formulated and applied. These equations model the dynamics of a thin layer of nearly incompressible and electrically conducting fluids for which the evolution is nearly two-dimensional with magnetic equilibrium in the third direction. The proposed numerical scheme is based on the direct splitting of macroscopic flux functions of the SWMHD equations. In two-space dimensions the scheme is derived in a usual dimensionally split manner; that is, the formulae for the fluxes can be used along each coordinate direction. The high-order resolution of the scheme is achieved by using a MUSCL-type initial reconstruction and Runge-Kutta time stepping method. Both one- and two-dimensional test computations are presented. For validation, the results of KFVS scheme are compared with those obtained from the space-time conservation element and solution element (CE/SE) method. The accuracy, efficiency and simplicity of the KFVS scheme demonstrate its potential in modeling SWMHD equations. 相似文献
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Senti‐CS: Building a lexical resource for sentiment analysis using subjective feature selection and normalized Chi‐Square‐based feature weight generation
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Sentiment analysis involves the detection of sentiment content of text using natural language processing. Natural language processing is a very challenging task due to syntactic ambiguities, named entity recognition, use of slangs, jargons, sarcasm, abbreviations and contextual sensitivity. Sentiment analysis can be performed using supervised as well as unsupervised approaches. As the amount of data grows, unsupervised approaches become vital as they cut down on the learning time and the requirements for availability of a labelled dataset. Sentiment lexicons provide an easy application of unsupervised algorithms for text classification. SentiWordNet is a lexical resource widely employed by many researchers for sentiment analysis and polarity classification. However, the reported performance levels need improvement. The proposed research is focused on raising the performance of SentiWordNet3.0 by using it as a labelled corpus to build another sentiment lexicon, named Senti‐CS. The part of speech information, usage based ranks and sentiment scores are used to calculate Chi‐Square‐based feature weight for each unique subjective term/part‐of‐speech pair extracted from SentiWordNet3.0. This weight is then normalized in a range of ?1 to +1 using min–max normalization. Senti‐CS based sentiment analysis framework is presented and applied on a large dataset of 50000 movie reviews. These results are then compared with baseline SentiWordNet, Mutual Information and Information Gain techniques. State of the art comparison is performed for the Cornell movie review dataset. The analyses of results indicate that the proposed approach outperforms state‐of‐the‐art classifiers. 相似文献
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Yazeed Alaskar Shamsul Arafin Darshana Wickramaratne Mark A. Zurbuchen Liang He Jeff McKay Qiyin Lin Mark S. Goorsky Roger K. Lake Kang L. Wang 《Advanced functional materials》2014,24(42):6629-6638
Van der Waals growth of GaAs on silicon using a two‐dimensional layered material, graphene, as a lattice mismatch/thermal expansion coefficient mismatch relieving buffer layer is presented. Two‐dimensional growth of GaAs thin films on graphene is a potential route towards heteroepitaxial integration of GaAs on silicon in the developing field of silicon photonics. Hetero‐layered GaAs is deposited by molecular beam epitaxy on graphene/silicon at growth temperatures ranging from 350 °C to 600 °C under a constant arsenic flux. Samples are characterized by plan‐view scanning electron microscopy, atomic force microscopy, Raman microscopy, and X‐ray diffraction. The low energy of the graphene surface and the GaAs/graphene interface is overcome through an optimized growth technique to obtain an atomically smooth low temperature GaAs nucleation layer. However, the low adsorption and migration energies of gallium and arsenic atoms on graphene result in cluster‐growth mode during crystallization of GaAs films at an elevated temperature. In this paper, we present the first example of an ultrasmooth morphology for GaAs films with a strong (111) oriented fiber‐texture on graphene/silicon using quasi van der Waals epitaxy, making it a remarkable step towards an eventual demonstration of the epitaxial growth of GaAs by this approach for heterogeneous integration. 相似文献
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Babani Vikas Charulata Pragya Prateek Arya Rajeev Qamar Shamimul 《Wireless Personal Communications》2022,124(3):2699-2722
Wireless Personal Communications - Water Cycle Algorithm (WCA) is a nature-inspired metaheuristic algorithm. There is a lack of literature surrounding the use of WCA in modern cellular mobile... 相似文献
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A rule-based expert system for earthquake prediction 总被引:2,自引:0,他引:2
Earthquake is a natural disaster which causes extensive damage as well as the death of thousands of people. Earthquake professionals for many decades have recognized the benefits to society from reliable earthquake predictions. Techniques like: mathematical modelling, hydrology analysis, ionosphere analysis and even animal responses have been used to forecast a quake. Most of these techniques rely on certain precursors like, stress or seismic activity. Data mining techniques can also be used for prediction of this natural hazard. Data mining consists of evolving set of techniques such as association rule mining that can be used to extract valuable information and knowledge from massive volumes of data. The aim of this study is to predict a subsequent earthquake from the data of the previous earthquake. This is achieved by applying association rule mining on earthquake data from 1979 to 2012. These associations are polished using predicate-logic techniques to draw stimulating production-rules to be used with a rule-based expert system. Prediction process is done by an expert system, which takes only current earthquake attributes to predict a subsequent earthquake. The rules generated for predicting the earthquake are mathematically validated as well as tested on real life earthquake data. Results from our study show that the proposed rule-based expert system is able to detect 100 % of earthquakes which actually occurred within 15 hours at-most within a defined range, depth and location. This work solely relies on previous earthquake data for predicting the next. 相似文献