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A application of the theory of underground water net work formation and evolution in the forecast of water inrush from coal floor
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《Global Geology》 1998年第1期70-71,共2页
关键词 net A application of the theory of underground water net work formation and evolution in the forecast of water inrush from coal floor
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用Network Meta分析系统评价GLP-1受体激动剂类降糖药的心血管安全性 被引量:4
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作者 孙凤 郁凯 +4 位作者 武珊珊 张渊 杨智荣 詹思延 史录文 《中国循证心血管医学杂志》 2012年第3期186-193,共8页
目的使用Network Meta分析系统评价胰高血糖素样肽1(GLP-1)受体激动剂类降糖药的心血管安全性。方法系统检索Medline、Embase、Clinical Trials.gov和Cochrane Library数据库(截止2011年10月)中比较GLP-1受体激动剂与其他降糖药物或安... 目的使用Network Meta分析系统评价胰高血糖素样肽1(GLP-1)受体激动剂类降糖药的心血管安全性。方法系统检索Medline、Embase、Clinical Trials.gov和Cochrane Library数据库(截止2011年10月)中比较GLP-1受体激动剂与其他降糖药物或安慰剂的心血管安全性的随机对照研究(RCT),采用传统Meta分析和NetworkMeta分析方法对纳入的RCT的研究结果进行合并。结果共纳入45项研究,15883例糖尿病患者,包括八种干预措施(六种GLP-1类药:艾塞那肽、利拉鲁肽、他司鲁肽、阿必鲁肽、利西拉来和LY2189265,以及安慰剂和传统降糖药),研究总臂数为95。传统Meta分析和Network Meta分析结果相近,均未显示GLP-1受体激动剂与其他降糖药物或安慰剂之间心血管疾病安全性有统计学差异(P均>0.05)。此外,结合直接和间接比较的Network Meta分析显示六种GLP-1类药之间两两比较的心血管安全性也均无统计学差异(P均>0.05)。基于贝叶斯理论的Network Meta分析可对八种干预措施进行排序,显示安慰剂心血管风险最大。结论尽管单个研究报道GLP-1类药有潜在的心血管保护效应,但目前Network Meta分析仍无法定论,仍有待专门设计的大型前瞻性研究加以验证。 展开更多
关键词 GLP-1受体激动剂 2型糖尿病 心血管疾病 network Meta分析 系统评价
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Three-Dimensional Planning of Arrival and Departure Route Network Based on Improved Ant-Colony Algorithm 被引量:3
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作者 王超 贺超男 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2015年第6期654-664,共11页
In order to improve safety,economy efficiency and design automation degree of air route in terminal airspace,Three-dimensional(3D)planning of routes network is investigated.A waypoint probability search method is prop... In order to improve safety,economy efficiency and design automation degree of air route in terminal airspace,Three-dimensional(3D)planning of routes network is investigated.A waypoint probability search method is proposed to optimize individual flight path.Through updating horizontal pheromones by negative feedback factors,an antcolony algorithm of path searching in 3Dterminal airspace is implemented.The principle of optimization sequence of arrival and departure routes is analyzed.Each route is optimized successively,and the overall optimization of the whole route network is finally achieved.A case study shows that it takes about 63 sto optimize 8arrival and departure routes,and the operation efficiency can be significantly improved with desirable safety and economy. 展开更多
关键词 terminal airspace arrival/departure route ant-colony algoritbm path planningl transportation net work design
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Integrative network analysis: bridging the gap between Western medicine and traditional Chinese medicine 被引量:2
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作者 Bing He Ge Zhang Ai-ping Lu 《Journal of Integrative Medicine》 SCIE CAS CSCD 2015年第3期133-135,共3页
There is a global movement calling for the integration of Western medicine(WM)and traditional Chinese medicine(TCM)[1].The World Health Organization suggests that health care would be improved by integrating tradi... There is a global movement calling for the integration of Western medicine(WM)and traditional Chinese medicine(TCM)[1].The World Health Organization suggests that health care would be improved by integrating traditional and complementary medicines into the practices of health care service delivery and self-health care[1].The WM and TCM are commonly integrated in the contemporary practice of medicine in China. 展开更多
关键词 integrated TCM WM traditional Chinese medicine compounds(TCD) health care OMICS net work pharmacology
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Mapping the small-world properties of brain networks in Chinese to English simultaneous interpreting by using functional near-infrared spectroscopy 被引量:1
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作者 Xiaohong Lin Victoria Lai Cheng Lei +3 位作者 Defeng Li Zhishan Hu Yutao Xiang Zhen Yuan 《Journal of Innovative Optical Health Sciences》 SCIE EI CAS 2018年第3期8-19,共12页
The aim of this study is to examine the small-world properties of functional brain networks inChinese to English simultaneous interpreting(SI)using functional near-infrared spectroscopy(INIRS),In particular,the fNIRS ... The aim of this study is to examine the small-world properties of functional brain networks inChinese to English simultaneous interpreting(SI)using functional near-infrared spectroscopy(INIRS),In particular,the fNIRS neuroimaging combined with complex network analysis wasperformed to extract the features of functional brain networks underling three translationstrategies associated with Chinese to English SI:"transcoding"that takes the"shortcut"linkingtranslation equivalents between Chinese and the English,code-mixing"that basically does notinvolve blingual procesing,and"transphrasingn that takes the long route"involving amonolingual processing of meaning in Chinese and then another monolingual processing ofmeaning in English.Our results demonstrated that the small-world net work topology was able todistinguish well bet ween the transcoding,code-mixing and transphrasing strategies related toChinese to English SI. 展开更多
关键词 FNIRS TRANSLATION simultaneous interpreting SMALL-WORLD brain net work
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Interaction Energy Prediction of Organic Molecules using Deep Tensor Neural Network
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作者 Yuan Qi Hong Ren +6 位作者 Hong Li Ding-lin Zhang Hong-qiang Cui Jun-ben Weng Guo-hui Li Gui-yan Wang Yan Li 《Chinese Journal of Chemical Physics》 SCIE CAS CSCD 2021年第1期112-124,I0012,共14页
The interaction energy of two molecules system plays a critical role in analyzing the interacting effect in molecular dynamic simulation.Since the limitation of quantum mechanics calculating resources,the interaction ... The interaction energy of two molecules system plays a critical role in analyzing the interacting effect in molecular dynamic simulation.Since the limitation of quantum mechanics calculating resources,the interaction energy based on quantum mechanics can not be merged into molecular dynamic simulation for a long time scale.A deep learning framework,deep tensor neural network,is applied to predict the interaction energy of three organic related systems within the quantum mechanics level of accuracy.The geometric structure and atomic types of molecular conformation,as the data descriptors,are applied as the network inputs to predict the interaction energy in the system.The neural network is trained with the hierarchically generated conformations data set.The complex tensor hidden layers are simplified and trained in the optimization process.The predicted results of different molecular sys tems indica te that deep t ensor neural net work is capable to predic t the interaction energy with 1 kcal/mol of the mean absolute error in a relatively short time.The prediction highly improves the efficiency of interaction energy calculation.The whole proposed framework provides new insights to introducing deep learning technology into the interaction energy calculation. 展开更多
关键词 Deep tensor neural net work Interac tion energy Organic molecules
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Exploration of the Potential Mechanism of Gancao Yangyin Decoction on Aging Based on Network Pharmacology
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作者 CHEN Yong CHEN Yanjuan +3 位作者 ZHAO Li HE Hui ZHANG Siwei LIU Dongzhou 《Chinese Medicine and Natural Products》 2021年第2期1-10,共10页
Objective:To explore the targels and molecular mechanism of Gancao Yangyin Decoction(甘草养阴汤,GCYYD)based on network pharmacology.Methods:The effective chemical components of 7 kinds of Chinese materia medica in GCY... Objective:To explore the targels and molecular mechanism of Gancao Yangyin Decoction(甘草养阴汤,GCYYD)based on network pharmacology.Methods:The effective chemical components of 7 kinds of Chinese materia medica in GCYYD and their relevant targets were obtai ned through the traditional Chinese medicine systems pharmacology database and analysis platform(TCMSP)and the encyelopedia of traditional Chinese medicine(ETCM).The aging-related targets were obtained through GeneCards database.The targets related to the effective chemical components were mapped with the aging-related targets,and the gene targets of GCY YD for intervening in aging were obtained.The protein interaction network diagram of GCY YD interfering with aging was drawn through String database and Cytoscape 3.7.1 software,and the core target genes were screened.The potential targets obtained were analyzed by gene ontology(GO)biological function enrichment analysis and kyoto encyelopedia of genes and genomes(KEGG)pathway enrichment analysis.Results:Totally 130 effective chemical components of the 7 kinds of Chinese materia medica of GCYYD and 276 related targets were obtained from TCMSP and ETCM databases.Totally 216 aging-related targets were obtained through GeneCards database.There were 63 target genes intervening in aging in GCYYD,with core target genes ALB,AKTI,TNF,L 6,MMP-3,VEGFA,CASP5,etc.Through biological function and signaling pathway enrichment analyses for the target genes with R software,147 KEGG signaling pathways were found,mainly related to age-RAGE signaling pathway in diabetic complications,proteoglycans in cancer,fluid shear stress and atherosclero-sis,HIF-1 signaling pathway,human cytomegalovirus infection,celluar senescence,prostate cancer,bladder cancer,elte.Conclusion:GCYYD can intervene in aging through"multicomponents-mulitargets-multipath-ways",which lays foundation for further experimental research. 展开更多
关键词 Gancao Yangyin Decoction(甘草养阴汤 GCY YD) net work pharmacology AGING action mechanism
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Drogue detection for autonomous aerial refueling based on convolutional neural networks 被引量:11
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作者 Wang Xufeng Dong Xinmin +2 位作者 Kong Xingwei Li Jianmin Zhang Bo 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2017年第1期380-390,共11页
Drogue detection is a fundamental issue during the close docking phase of autonomous aerial refueling(AAR). To cope with this issue, a novel and effective method based on deep learning with convolutional neural netw... Drogue detection is a fundamental issue during the close docking phase of autonomous aerial refueling(AAR). To cope with this issue, a novel and effective method based on deep learning with convolutional neural networks(CNNs) is proposed. In order to ensure its robustness and wide application, a deep learning dataset of images was prepared by utilizing real data of ‘‘Probe and Drogue" aerial refueling, which contains diverse drogues in various environmental conditions without artificial features placed on the drogues. By employing deep learning ideas and graphics processing units(GPUs), a model for drogue detection using a Caffe deep learning framework with CNNs was designed to ensure the method's accuracy and real-time performance. Experiments were conducted to demonstrate the effectiveness of the proposed method, and results based on real AAR data compare its performance to other methods, validating the accuracy, speed, and robustness of its drogue detection ability. 展开更多
关键词 Autonomous aerial refueling Computer vision Convolutional neural net-works Deep learning Drogue detection
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A Combining Call Admission Control and Power Control Scheme for D2D Communications Underlaying Cellular Networks 被引量:7
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作者 Xujie Li Wenna Zhang +1 位作者 Honglang Zhang Wenfeng Li 《China Communications》 SCIE CSCD 2016年第10期137-145,共9页
As device-to-device(D2D) communications usually reuses the resource of cellular networks, call admission control(CAC) and power control are crucial problems. However in most power control schemes, total data rates or ... As device-to-device(D2D) communications usually reuses the resource of cellular networks, call admission control(CAC) and power control are crucial problems. However in most power control schemes, total data rates or throughput are regarded as optimization criterion. In this paper, a combining call admission control(CAC) and power control scheme under guaranteeing QoS of every user equipment(UE) is proposed. First, a simple CAC scheme is introduced. Then based on the CAC scheme, a combining call admission control and power control scheme is proposed. Next, the performance of the proposed scheme is evaluated. Finally, maximum DUE pair number and average transmitting power is calculated. Simulation results show that D2 D communications with the proposed combining call admission control and power control scheme can effectively improve the maximum DUE pair number under the premise of meeting necessary QoS. 展开更多
关键词 device-to-device(D2D) call admission control power control cellular networks
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IUKF neural network modeling for FOG temperature drift 被引量:5
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作者 Feng Zha Jiangning Xu +1 位作者 Jingshu Li Hongyang He 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2013年第5期838-844,共7页
A novel neural network based on iterated unscented Kalman filter (IUKF) algorithm is established to model and com- pensate for the fiber optic gyro (FOG) bias drift caused by temperature. In the network, FOG tempe... A novel neural network based on iterated unscented Kalman filter (IUKF) algorithm is established to model and com- pensate for the fiber optic gyro (FOG) bias drift caused by temperature. In the network, FOG temperature and its gradient are set as input and the FOG bias drift is set as the expected output. A 2-5-1 network trained with IUKF algorithm is established. The IUKF algorithm is developed on the basis of the unscented Kalman filter (UKF). The weight and bias vectors of the hidden layer are set as the state of the UKF and its process and measurement equations are deduced according to the network architecture. To solve the unavoidable estimation deviation of the mean and covariance of the states in the UKF algorithm, iterative computation is introduced into the UKF after the measurement update. While the measure- ment noise R is extended into the state vectors before iteration in order to meet the statistic orthogonality of estimate and mea- surement noise. The IUKF algorithm can provide the optimized estimation for the neural network because of its state expansion and iteration. Temperature rise (-20-20℃) and drop (70-20℃) tests for FOG are carried out in an attemperator. The temperature drift model is built with neural network, and it is trained respectively with BP, UKF and IUKF algorithms. The results prove that the proposed model has higher precision compared with the back- propagation (BP) and UKF network models. 展开更多
关键词 fiber optic gyro (FOG) temperature drift neural net- work iterated unscented Kalman filter (IUKF).
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Synchronization in a fractional-order dynamic network with uncertain parameters using an adaptive control strategy 被引量:2
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作者 Lin DU Yong YANG Youming LEI 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI CSCD 2018年第3期353-364,共12页
This paper studies synchronization of all nodes in a fractional-order complex dynamic network. An adaptive control strategy for synchronizing a dynamic network is proposed. Based on the Lyapunov stability theory, this... This paper studies synchronization of all nodes in a fractional-order complex dynamic network. An adaptive control strategy for synchronizing a dynamic network is proposed. Based on the Lyapunov stability theory, this paper shows that tracking errors of all nodes in a fractional-order complex network converge to zero. This simple yet prac- tical scheme can be used in many networks such as small-world networks and scale-free networks. Unlike the existing methods which assume the coupling configuration among the nodes of the network with diffusivity, symmetry, balance, or irreducibility, in this case, these assumptions are unnecessary, and the proposed adaptive strategy is more feasible. Two examples are presented to illustrate effectiveness of the proposed method. 展开更多
关键词 fractional-order chaotic system SYNCHRONIZATION complex dynamic net-work adaptive control
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Optimization of Laser Ablation Technology for PDPhSM Matrix Nanocomposite Thin Film by Artificial Neural Networks-particle Swarm Algorithm 被引量:3
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作者 唐普洪 宋仁国 《Journal of Wuhan University of Technology(Materials Science)》 SCIE EI CAS 2010年第2期188-193,共6页
A new thermal ring-opening polymerization technique for 1, 1, 3, 3-tetra-ph enyl-1, 3-disilacyclobutane (TPDC) based on the use of metal nanoparticles produced by pulsed laser ablation was investigated. This method ... A new thermal ring-opening polymerization technique for 1, 1, 3, 3-tetra-ph enyl-1, 3-disilacyclobutane (TPDC) based on the use of metal nanoparticles produced by pulsed laser ablation was investigated. This method facilitates the synthesis of polydiphenysilylenemethyle (PDPhSM) thin film, which is difficult to make by conventional methods because of its insolubility and high melting point. TPDC was first evaporated on silicon substrates and then exposed to metal nanoparticles deposition by pulsed laser ablation prior to heat treatment.The TPDC films with metal nanoparticles were heated in an electric furnace in air atmosphere to induce ring-opening polymerization of TPDC. The film thicknesses before and after polymerization were measured by a stylus profilometer. Since the polymerization process competes with re-evaporation of TPDC during the heating, the thickness ratio of the polymer to the monomer was defined as the polymerization efficiency, which depends greatly on the technology conditions. Therefore, a well trained radial base function neural network model was constructed to approach the complex nonlinear relationship. Moreover, a particle swarm algorithm was firstly introduced to search for an optimum technology directly from RBF neural network model. This ensures that the fabrication of thin film with appropriate properties using pulsed laser ablation requires no in-depth understanding of the entire behavior of the technology conditions. 展开更多
关键词 nanocomposite thin film pulsed laser deposition(PLD) artificial neural net- works(ANN) particle swarm optimization (PSO)
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Orchestrating Network Functions in Software-Defined Networks 被引量:2
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作者 Hongchao Hu Lin Pang +1 位作者 Zhenpeng Wang Guozhen Cheng 《China Communications》 SCIE CSCD 2017年第2期104-117,共14页
Software.defined networking(SDN) enables third.part companies to participate in the network function innovations. A number of instances for one network function will inevitably co.exist in the network. Although some o... Software.defined networking(SDN) enables third.part companies to participate in the network function innovations. A number of instances for one network function will inevitably co.exist in the network. Although some orchestration architecture has been proposed to chain network functions, rare works are focused on how to optimize this process. In this paper, we propose an optimized model for network function orchestration, function combination model(FCM). Our main contributions are as following. First, network functions are featured with a new abstraction, and are open to external providers. And FCM identifies network functions using unique type, and organizes their instances distributed over the network with the appropriate way. Second, with the specialized demands, we can combine function instances under the global network views, and formulate it into the problem of Boolean linear program(BLP). A simulated annealing algorithm is designed to approach optimal solution for this BLP. Finally, the numerical experiment demonstrates that our model can create outstanding composite schemas efficiently. 展开更多
关键词 software-defined network network function function orchestrating
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Adaptive coupled synchronization of non-autonomous systems in ring networks 被引量:1
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作者 过榴晓 徐振源 胡满峰 《Chinese Physics B》 SCIE EI CAS CSCD 2008年第3期836-841,共6页
The adaptive coupled synchronization method for non-autonomous systems is proposed. This method can avoid estimating the value of coupling coefficient. Under the uniform Lipschitz assumption, we derive the asymptotica... The adaptive coupled synchronization method for non-autonomous systems is proposed. This method can avoid estimating the value of coupling coefficient. Under the uniform Lipschitz assumption, we derive the asymptotical synchronization for a general coupling ring network with N identical non-autonomous systems~ even when N is large enough. Strict theoretical proofs are given. Numerical simulations illustrate the effectiveness of the present method. 展开更多
关键词 non-autonomous system adaptive synchronization chaotic synchronization ring net-works
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Adaptive H_∞ Synchronization for General Delayed Complex Networks with External Disturbance 被引量:1
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作者 TU Lilan XIONG Aiming 《Wuhan University Journal of Natural Sciences》 CAS 2013年第1期29-36,共8页
The global adaptive H∞ synchronization is intensively investigated for the general delayed complex dynamical networks. The network under consideration contains unknown but bounded nonlinear coupling functions, time-v... The global adaptive H∞ synchronization is intensively investigated for the general delayed complex dynamical networks. The network under consideration contains unknown but bounded nonlinear coupling functions, time-varying delay, and external disturbance. Based on the Lyapunov stability theory, linear matrix inequality (LMI) optimization technique and adaptive control, several global adaptive H∞ synchronization schemes are estab- lished, which guarantee robust asymptotical synchronization of noise-perturbed network as well as a prescribed robust H∞ per- formance level. Finally, numerical simulations have shown the feasibility and effectiveness of the proposed techniques. 展开更多
关键词 H∞ synchronization general delayed complex net-works external disturbance LMI adaptive control
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Mobile user forecast and power-law acceleration invariance of scale-free networks 被引量:1
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作者 郭进利 郭曌华 刘雪娇 《Chinese Physics B》 SCIE EI CAS CSCD 2011年第11期548-555,共8页
This paper studies and predicts the number growth of China's mobile users by using the power-law regression. We find that the number growth of the mobile users follows a power law. Motivated by the data on the evolut... This paper studies and predicts the number growth of China's mobile users by using the power-law regression. We find that the number growth of the mobile users follows a power law. Motivated by the data on the evolution of the mobile users, we consider scenarios of self-organization of accelerating growth networks into scale-free structures and propose a directed network model, in which the nodes grow following a power-law acceleration. The expressions for the transient and the stationary average degree distributions are obtained by using the Poisson process. This result shows that the model generates appropriate power-law connectivity distributions. Therefore, we find a power-law acceleration invariance of the scale-free networks. The numerical simulations of the models agree with the analytical results well. 展开更多
关键词 mobile user forecast power-law accelerating growth complex networks scale-free net-works
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Nonlinear properties of the lattice network-based nonlinear CRLH transmission lines
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作者 王正斌 吴昭质 高超 《Chinese Physics B》 SCIE EI CAS CSCD 2015年第2期480-484,共5页
The nonlinear properties of lattice network-based(LNB) composite right-/left-handed transmission lines(CRLH TLs)with nonlinear capacitors are experimentally investigated.Harmonic generation,subharmonic generation,... The nonlinear properties of lattice network-based(LNB) composite right-/left-handed transmission lines(CRLH TLs)with nonlinear capacitors are experimentally investigated.Harmonic generation,subharmonic generation,and parametric excitation are clearly observed in an unbalanced LNB CRLH TL separately.While the balanced design of the novel nonlinear TL shows that the subharmonic generation and parametric processes can be suppressed,and almost the same power level of the higher harmonics can be achieved over a wide bandwidth range,which are difficult to find in conventional CRLH TLs. 展开更多
关键词 composite right-/left-handed transmission line (CRLH TL) nonlinear metamaterial lattice net-work MICROSTRIP
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Residential Community Open-Up Strategy Based on Prim’s Algorithm and Neural Network Algorithm
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作者 Ximing Lv Ang Li +1 位作者 Shunkai Zhang Jianbao Li 《Journal of Applied Mathematics and Physics》 2017年第2期551-567,共17页
“Open community” has aroused widespread concern and research. This paper focuses on the system analysis research of the problem that based on statistics including the regression equation fitting function and mathema... “Open community” has aroused widespread concern and research. This paper focuses on the system analysis research of the problem that based on statistics including the regression equation fitting function and mathematical theory, combined with the actual effect of camera measurement method, Prim’s algorithm and neural network to “Open community” and the applicable conditions. Research results show that with the increasing number of roads within the district, the benefit time gradually increased, but each type of district capacity is different. 展开更多
关键词 OPEN COMMUNITY Regression Analysis Prim’s ALGORITHM GRAPH Theory NEURAL net-work ALGORITHM
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基于Informer和U-Net的换热器出口温度预测模型设计
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作者 韦威浩 庄伟亮 +1 位作者 宋涵 刘娇 《热能动力工程》 北大核心 2025年第7期144-153,共10页
换热器出口温度的精准预测对工业生产、能源行业及航天等领域机电系统的性能和安全性有重要影响,然而机电部件在不同工况下运行产生的热量差异使换热器出口温度预测难度增大。为解决这一问题,设计了一种基于Informer模型和U-Net模型的... 换热器出口温度的精准预测对工业生产、能源行业及航天等领域机电系统的性能和安全性有重要影响,然而机电部件在不同工况下运行产生的热量差异使换热器出口温度预测难度增大。为解决这一问题,设计了一种基于Informer模型和U-Net模型的换热器出口温度预测模型InfUNet,该模型通过概率稀疏自注意力模块的特征稀疏化机制实现关键特征的全局-局部跨尺度捕捉,并受U-Net模型架构的启发,提出了一种新型的时间序列特征提取模块,增强了局部特征表达能力。为验证模型泛化能力,基于监测周期为1700和1000 s两种工况下的换热器实验平台数据集,将InfUNet模型与Informer、LSTM、RNN和MLP 4种预测模型进行了比较。仿真实验结果表明:与基准模型Informer相比,InfUNet模型在工况突变及微小工况波动下均表现出优异的预测稳定性,其均方根误差(RMSE)、平均绝对误差(MAE)和平均绝对百分比误差(MAPE)分别降低了69.97%、71.06%和70.00%,预测误差稳定在-0.37~0.34℃之间。 展开更多
关键词 时序预测 换热器出口温度 INFORMER U-net 特征提取 不同工况
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基于改进1DCNN-LSTM的防冲钻孔机器人钻进煤岩性状识别
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作者 司垒 刘扬 +5 位作者 王忠宾 顾进恒 魏东 戴剑博 李鑫 赵杨奇 《矿业科学学报》 北大核心 2026年第1期206-217,共12页
防冲钻孔机器人是高地应力矿井卸压作业的关键装备,其对钻进煤岩性状识别准确度直接影响钻孔卸压效率和卸压效果。本文针对当前煤岩钻进状态识别手段多依赖于人工经验,存在识别精度低、响应时间长、无法满足无人化钻孔卸压需求的问题,... 防冲钻孔机器人是高地应力矿井卸压作业的关键装备,其对钻进煤岩性状识别准确度直接影响钻孔卸压效率和卸压效果。本文针对当前煤岩钻进状态识别手段多依赖于人工经验,存在识别精度低、响应时间长、无法满足无人化钻孔卸压需求的问题,基于一维卷积神经网络(1DCNN)和长短时记忆网络(LSTM)并结合模拟实验提出了一种钻进过程煤岩性状识别方法。通过加入卷积块注意力机制(CBAM),提升模型识别准确率,并采用改进蜣螂优化(IDBO)算法对模型中超参数进行寻优,确定最优的网络参数组合。搭建煤岩钻进模拟试验台,制作6种典型煤岩试块,采集回转速度、回转扭矩、推进速度和推进压力等4类传感信号,开展相应的对比测试分析。结果表明:所提方法具有较高的钻进煤岩识别准确率,达到97.00%,明显优于1DCNN和1DCNN-LSTM,以及逻辑回归、支持向量机(SVM)、决策树、随机森林、K聚类、Transformer等方法。 展开更多
关键词 防冲钻孔机器人 钻进煤岩识别 一维卷积神经网络(1DCNN) 长短时记忆神经网络(LSTM) 改进蜣螂优化(IDWO)算法
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