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排序方式: 共有10000条查询结果,搜索用时 15 毫秒
1.
Multimedia Tools and Applications - Remote Sensing categorical signature classification has gained significant implications on spatial resolution image analysis due to differences in the... 相似文献
2.
Journal of Materials Science - 相似文献
3.
Xiao Zhu Chen Yanxun Jiang Hongbo Hu Zhenzhen Lui John C. S. Min Geyong Dustdar Schahram 《Wireless Networks》2022,28(7):3305-3322
Wireless Networks - Unmanned aerial vehicles (UAV) have been widely used in various fields because of their high mobility and portability. At the same time, due to the rapid development of... 相似文献
4.
5.
Chumakov Yu. A. Knyazeva A. G. Pribytkov G. A. 《Theoretical Foundations of Chemical Engineering》2021,55(3):490-503
Theoretical Foundations of Chemical Engineering - On the basis of the classic concepts of the theory of solid-phase combustion, for the first time, a model with a detailed scheme of chemical... 相似文献
6.
Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (Tg) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (nd) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high nd (1.7 or more) and low Tg (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses. 相似文献
7.
Journal of Chemical Ecology - Biocontrol agents such as parasitic wasps use long-range volatiles and host-associated cues from lower trophic levels to find their hosts. However, this chemical... 相似文献
8.
Journal of Communications Technology and Electronics - A statistical study of the effectiveness of the non-threshold search procedure for a noise-like phase-shift keyed signal by the delay time is... 相似文献
9.
Ahmed Fathy Mohammad Ali Abdelkareem A.G. Olabi Hegazy Rezk 《International Journal of Hydrogen Energy》2021,46(8):6087-6099
Cell temperature and water content of the membrane have a significant effect on the performance of fuel cells. The current-power curve of the fuel cell has a maximum power point (MPP) that is needed to be tracked. This study presents a novel strategy based on a salp swarm algorithm (SSA) for extracting the maximum power of proton-exchange membrane fuel cell (PEMFC). At first, a new formula is derived to estimate the optimal voltage of PEMFC corresponding to MPP. Then the error between the estimated voltage at MPP and the actual terminal voltage of the fuel cell is fed to a proportional-integral-derivative controller (PID). The output of the PID controller tunes the duty cycle of a boost converter to maximize the harvested power from the PEMFC. SSA determines the optimal gains of PID. Sensitivity analysis is performed with the operating fuel cell at different cell temperature and water content of the membrane. The obtained results through the proposed strategy are compared with other programmed approaches of incremental resistance method, Fuzzy-Logic, grey antlion optimizer, wolf optimizer, and mine-blast algorithm. The obtained results demonstrated high reliability and efficiency of the proposed strategy in extracting the maximum power of the PEMFC. 相似文献
10.
John D. Rodney S. Deepapriya M. Cyril Robinson C. Justin Raj Suresh Perumal Byung Chul Kim S. Krishnan S. Jerome Das 《International Journal of Hydrogen Energy》2021,46(54):27585-27596
The production of hydrogen, a favourable alternative to an unsustainable fossil fuel remains as a significant hurdle with the pertaining challenge in the design of proficient, highly productive and sustainable electrocatalyst for both oxygen evolution reaction (OER) and hydrogen evolution reaction (HER). Herein, the dysprosium (Dy) doped copper oxide (Cu1-xDyxO) nanoparticles were synthesized via solution combustion technique and utilized as a non-noble metal based bi-functional electrocatalyst for overall water splitting. Due to the improved surface to volume ratio and conductivity, the optimized Cu1-xDyxO (x = 0.01, 0.02) electrocatalysts exhibited impressive HER and OER performance respectively in 1 M KOH delivering a current density of 10 mAcm?2 at a potential of ?0.18 V vs RHE for HER and 1.53 V vs RHE for OER. Moreover, the Dy doped CuO electrocatalyst used as a bi-functional catalyst for overall water splitting achieved a potential of 1.56 V at a current density 10 mAcm?2 and relatively high current density of 66 mAcm?2 at a peak potential of 2 V. A long term stability of 24 h was achieved for a cell voltage of 2.2 V at a constant current density of 30 mAcm?2 with only 10% of the initial current loss. This showcases the accumulative opportunity of dysprosium as a dopant in CuO nanoparticles for fabricating a highly effective and low-cost bi-functional electrocatalyst for overall water splitting. 相似文献