Wireless sensor networks （WSN） provide an approachto collecting distributed monitoring data and transmiting them tothe sink node. This paper proposes a WSN-based multi-hop networkinfrastructure, to increase network ...Wireless sensor networks （WSN） provide an approachto collecting distributed monitoring data and transmiting them tothe sink node. This paper proposes a WSN-based multi-hop networkinfrastructure, to increase network lifetime by optimizing therouting strategy. First, a network model is established, an operatingcontrol strategy is devised, and energy consumption characteristicsare analyzed. Second, a fast route-planning algorithm isproposed to obtain the original path that takes into account the remainingenergy of communicating nodes and the amount of energyconsumed in data transmission. Next, considering the amount ofenergy consumed by an individual node and the entire network,a criterion function is established to describe node performanceand to evaluate data transmission ability. Finally, a route optimizingalgorithm is proposed to increase network lifetime by adjusting thetransmission route in protection of the weak node （the node withlow transmission ability）. Simulation and comparison experimentalresults demonstrate the good performance of the proposed algorithmsto increase network lifetime.展开更多
Objective Repetitive transcranial magnetic stimulation(rTMS)has demonstrated efficacy in enhancing neurocognitive performance in Alzheimer’s disease(AD),but the neurobiological mechanisms linking synaptic pathology,n...Objective Repetitive transcranial magnetic stimulation(rTMS)has demonstrated efficacy in enhancing neurocognitive performance in Alzheimer’s disease(AD),but the neurobiological mechanisms linking synaptic pathology,neural oscillatory dynamics,and brain network reorganization remain unclear.This investigation seeks to systematically evaluate the therapeutic potential of rTMS as a non-invasive neuromodulatory intervention through a multimodal framework integrating clinical assessments,molecular profiling,and neurophysiological monitoring.Methods In this prospective double-blind trial,12 AD patients underwent a 14-day protocol of 20 Hz rTMS,with comprehensive multimodal assessments performed pre-and postintervention.Cognitive functioning was quantified using the mini-mental state examination(MMSE)and Montreal cognitive assessment(MOCA),while daily living capacities and neuropsychiatric profiles were respectively evaluated through the activities of daily living(ADL)scale and combined neuropsychiatric inventory(NPI)-Hamilton depression rating scale(HAMD).Peripheral blood biomarkers,specifically Aβ1-40 and phosphorylated tau(p-tau181),were analyzed to investigate the effects of rTMS on molecular metabolism.Spectral power analysis was employed to investigate rTMS-induced modulations of neural rhythms in AD patients,while brain network analyses incorporating topological properties were conducted to examine stimulus-driven network reorganization.Furthermore,systematic assessment of correlations between cognitive scale scores,blood biomarkers,and network characteristics was performed to elucidate cross-modal therapeutic associations.Results Clinically,MMSE and MOCA scores improved significantly(P<0.05).Biomarker showed that Aβ1-40 level increased(P<0.05),contrasting with p-tau181 reduction.Moreover,the levels of Aβ1-40 were positively correlated with MMSE and MOCA scores.Post-intervention analyses revealed significant modulations in oscillatory power,characterized by pronounced reductions in delta(P<0.05)and theta bands(P<0.05),while concurrent enhancements were observed in alpha,beta,and gamma band activities(all P<0.05).Network analysis revealed frequency-specific reorganization:clustering coefficients were significantly decreased in delta,theta,and alpha bands(P<0.05),while global efficiency improvement was exclusively detected in the delta band(P<0.05).The alpha band demonstrated concurrent increases in average nodal degree(P<0.05)and characteristic path length reduction(P<0.05).Further research findings indicate that the changes in the clinical scale HAMD scores before and after rTMS stimulation are negatively correlated with the changes in the blood biomarkers Aβ1-40 and p-tau181.Additionally,the changes in the clinical scales MMSE and MoCA scores were negatively correlated with the changes in the node degree of the alpha frequency band and negatively correlated with the clustering coefficient of the delta frequency band.However,the changes in MMSE scores are positively correlated with the changes in global efficiency of both the delta and alpha frequency bands.Conclusion 20 Hz rTMS targeting dorsolateral prefrontal cortex(DLPFC)significantly improves cognitive function and enhances the metabolic clearance ofβ-amyloid and tau proteins in AD patients.This neurotherapeutic effect is mechanistically associated with rTMS-mediated frequency-selective neuromodulation,which enhances the connectivity of oscillatory networks through improved neuronal synchronization and optimized topological organization of functional brain networks.These findings not only support the efficacy of rTMS as an adjunctive therapy for AD but also underscore the importance of employing multiple assessment methods—including clinical scales,blood biomarkers,and EEG——in understanding and monitoring the progression of AD.This research provides a significant theoretical foundation and empirical evidence for further exploration of rTMS applications in AD treatment.展开更多
The optimization of network performance in a movement-assisted data gathering scheme was studied by analyzing the energy consumption of wireless sensor network with node uniform distribution. A theoretically analytica...The optimization of network performance in a movement-assisted data gathering scheme was studied by analyzing the energy consumption of wireless sensor network with node uniform distribution. A theoretically analytical method for avoiding energy hole was proposed. It is proved that if the densities of sensor nodes working at the same time are alternate between dormancy and work with non-uniform node distribution. The efficiency of network can increase by several times and the residual energy of network is nearly zero when the network lifetime ends.展开更多
In the application of periodic data-gathering in sensor networks,sensor nodes located near the sink have to forward the data received from all other nodes to the sink,which depletes their energy very quickly.A moving ...In the application of periodic data-gathering in sensor networks,sensor nodes located near the sink have to forward the data received from all other nodes to the sink,which depletes their energy very quickly.A moving scheme for the sink based on local residual energy was proposed.In the scheme,the sink periodically moves to a new location with the highest stay-value defined by the average residual energy and the number of neighbors.The scheme can balance energy consumption and prevent nodes around sink from draining their energy very quickly in the networks.The simulation results show that the scheme can prolong the network lifetime by 26%-65%compared with the earlier schemes where the sink is static or moves randomly.展开更多
The method of determining the structures and parameters of radial basis function neural networks(RBFNNs) using improved genetic algorithms is proposed. Akaike′s information criterion (AIC) with generalization error t...The method of determining the structures and parameters of radial basis function neural networks(RBFNNs) using improved genetic algorithms is proposed. Akaike′s information criterion (AIC) with generalization error term is used as the best criterion of optimizing the structures and parameters of networks. It is shown from the simulation results that the method not only improves the approximation and generalization capability of RBFNNs ,but also obtain the optimal or suboptimal structures of networks.展开更多
OBJECTIVE To explore the new indications and key mechanism of Bazi Bushen capsule(BZBS)by network pharmacology and in vitro experiment.METHODS The potential tar⁃get profiles of the components of BZBS were pre⁃dicted.S...OBJECTIVE To explore the new indications and key mechanism of Bazi Bushen capsule(BZBS)by network pharmacology and in vitro experiment.METHODS The potential tar⁃get profiles of the components of BZBS were pre⁃dicted.Subsequently,new indications for BZBS were predicted by disease ontology(DO)enrich⁃ment analysis and initially validated by GO and KEGG pathway enrichment analysis.Further⁃more,the therapeutic target of BZBS acting on AD signaling pathway were identified by intersec⁃tion analysis.Two Alzheimer′s disease(AD)cell models,BV-2 and SH-SY5Y,were used to pre⁃liminarily verify the anti-AD efficacy and mecha⁃nism of BZBS in vitro.RESULTS In total,1499 non-repeated ingredients were obtained from 16 herbs in BZBS formula,and 1320 BZBS targets with high confidence were predicted.Disease enrichment results strongly suggested that BZBS formula has the potential to be used in the treat⁃ment of AD.In vitro experiments showed that BZ⁃BS could significantly reduce the release of TNF-αand IL-6 and the expression of COX-2 and PSEN1 in Aβ25-35-induced BV-2 cells.BZBS reduced the apoptosis rate of Aβ25-35 induced SH-SY5Y cells,significantly increased mitochon⁃drial membrane potential,reduced the expres⁃sion of Caspase3 active fragment and PSEN1,and increased the expression of IDE.CONCLU⁃SIONS BZBS formula has a potential use in the treatment of AD,which is achieved through regu⁃lation of ERK1/2,NF-κB signaling pathways,and GSK-3β/β-catenin signaling pathway.Further⁃more,the network pharmacology technology is a feasible drug repurposing strategy to reposition new clinical use of approved TCM and explore the mechanism of action.The study lays a foun⁃dation for the subsequent in-depth study of BZBS in the treatment of AD and provides a basis for its application in the clinical treatment of AD.展开更多
A distributed local adaptive transmit power assignment (LA-TPA) strategy was proposed to construct a topology with better performance according to the environment and application scenario and prolong the network lifet...A distributed local adaptive transmit power assignment (LA-TPA) strategy was proposed to construct a topology with better performance according to the environment and application scenario and prolong the network lifetime.It takes the path loss exponent and the energy control coefficient into consideration with the aim to accentuate the minimum covering district of each node more accurately and precisely according to various network application scenarios.Besides,a self-healing scheme that enhances the robustness of the network was provided.It makes the topology tolerate more dead nodes than existing algorithms.Simulation was done under OMNeT++ platform and the results show that the LA-TPA strategy is more effective in constructing a well-performance network topology based on various application scenarios and can prolong the network lifetime significantly.展开更多
Newton＇s learning algorithm of NN is presented and realized. In theory, the convergence rate of learning algorithm of NN based on Newton＇s method must be faster than BP＇s and other learning algorithms, because the ...Newton＇s learning algorithm of NN is presented and realized. In theory, the convergence rate of learning algorithm of NN based on Newton＇s method must be faster than BP＇s and other learning algorithms, because the gradient method is linearly convergent while Newton＇s method has second order convergence rate. The fast computing algorithm of Hesse matrix of the cost function of NN is proposed and it is the theory basis of the improvement of Newton＇s learning algorithm. Simulation results show that the convergence rate of Newton＇s learning algorithm is high and apparently faster than the traditional BP method＇s, and the robustness of Newton＇s learning algorithm is also better than BP method＇ s.展开更多
Security and reliability must be focused on control sys- tems firstly, and fault detection and diagnosis （FDD） is the main theory and technology. Now, there are many positive results in FDD for linear networked cont...Security and reliability must be focused on control sys- tems firstly, and fault detection and diagnosis （FDD） is the main theory and technology. Now, there are many positive results in FDD for linear networked control systems （LNCSs）, but nonlinear networked control systems （NNCSs） are less involved. Based on the T-S fuzzy-modeling theory, NNCSs are modeled and network random time-delays are changed into the unknown bounded uncertain part without changing its structure. Then a fuzzy state observer is designed and an observer-based fault detection approach for an NNCS is presented. The main results are given and the relative theories are proved in detail. Finally, some simulation results are given and demonstrate the proposed method is effective.展开更多
Identifying influential nodes in complex networks is still an open issue. In this paper, a new comprehensive centrality mea- sure is proposed based on the Dempster-Shafer evidence theory. The existing measures of degr...Identifying influential nodes in complex networks is still an open issue. In this paper, a new comprehensive centrality mea- sure is proposed based on the Dempster-Shafer evidence theory. The existing measures of degree centrality, betweenness centra- lity and closeness centrality are taken into consideration in the proposed method. Numerical examples are used to illustrate the effectiveness of the proposed method.展开更多
Based on the T-S fuzzy model,this paper presents a new model of non-linear network control system with stochastic transfer delay.Sufficient criterion is proposed to guarantee globally asymptotically stability of this ...Based on the T-S fuzzy model,this paper presents a new model of non-linear network control system with stochastic transfer delay.Sufficient criterion is proposed to guarantee globally asymptotically stability of this two-levels T-S fuzzy model.Also a T-S fuzzy observer of NCS is designed base on this two-levels T-S fuzzy model.All these results present a new approach for networked control system analysis and design.展开更多
The accuracy of present flatness predictive method is limited and it just belongs to software simulation. In order to improve it, a novel flatness predictive model via T-S cloud reasoning network implemented by digita...The accuracy of present flatness predictive method is limited and it just belongs to software simulation. In order to improve it, a novel flatness predictive model via T-S cloud reasoning network implemented by digital signal processor(DSP) is proposed. First, the combination of genetic algorithm(GA) and simulated annealing algorithm(SAA) is put forward, called GA-SA algorithm, which can make full use of the global search ability of GA and local search ability of SA. Later, based on T-S cloud reasoning neural network, flatness predictive model is designed in DSP. And it is applied to 900 HC reversible cold rolling mill. Experimental results demonstrate that the flatness predictive model via T-S cloud reasoning network can run on the hardware DSP TMS320 F2812 with high accuracy and robustness by using GA-SA algorithm to optimize the model parameter.展开更多
为更好地对S/X波段天气雷达组网融合在广西区域的应用能力进行评估,利用雷达观测资料,依次进行基数据解析、Z_(H)-K_(DP)综合法衰减订正、单站雷达网格化及多部雷达组网拼图,最终利用组合反射率、等高平面反射率对广西现有雷达组网覆盖...为更好地对S/X波段天气雷达组网融合在广西区域的应用能力进行评估,利用雷达观测资料,依次进行基数据解析、Z_(H)-K_(DP)综合法衰减订正、单站雷达网格化及多部雷达组网拼图,最终利用组合反射率、等高平面反射率对广西现有雷达组网覆盖能力在2023年第4号台风“泰利”影响过程进行初步应用分析。结果显示:结合径向廓线对比、网格化对比及多个连续体扫得到的反射率对比分析,经过Z_(H)-K_(DP)综合法订正后的X波段天气雷达反射率在一定范围内具有较高的可靠性;将组网拼图结果应用于台风“泰利”暴雨过程分析,对比S波段和S/X波段天气雷达组网后的0.5 km、0.75 km、1.0 km和2.0 km CAPPI(Constant Altitude Plan Position Indicator)组网反射率因子覆盖区域,结果显示X波段加入雷达组网后,得到了空间结构连续、覆盖更广的资料,有效补充了广西新一代天气雷达的低层盲区、阻挡空缺区等。展开更多
基金supported by the National Natural Science Foundation of China(61571068)the Innovative Research Projects of Colleges and Universities in Chongqing(12A19369)
文摘Wireless sensor networks （WSN） provide an approachto collecting distributed monitoring data and transmiting them tothe sink node. This paper proposes a WSN-based multi-hop networkinfrastructure, to increase network lifetime by optimizing therouting strategy. First, a network model is established, an operatingcontrol strategy is devised, and energy consumption characteristicsare analyzed. Second, a fast route-planning algorithm isproposed to obtain the original path that takes into account the remainingenergy of communicating nodes and the amount of energyconsumed in data transmission. Next, considering the amount ofenergy consumed by an individual node and the entire network,a criterion function is established to describe node performanceand to evaluate data transmission ability. Finally, a route optimizingalgorithm is proposed to increase network lifetime by adjusting thetransmission route in protection of the weak node （the node withlow transmission ability）. Simulation and comparison experimentalresults demonstrate the good performance of the proposed algorithmsto increase network lifetime.
文摘Objective Repetitive transcranial magnetic stimulation(rTMS)has demonstrated efficacy in enhancing neurocognitive performance in Alzheimer’s disease(AD),but the neurobiological mechanisms linking synaptic pathology,neural oscillatory dynamics,and brain network reorganization remain unclear.This investigation seeks to systematically evaluate the therapeutic potential of rTMS as a non-invasive neuromodulatory intervention through a multimodal framework integrating clinical assessments,molecular profiling,and neurophysiological monitoring.Methods In this prospective double-blind trial,12 AD patients underwent a 14-day protocol of 20 Hz rTMS,with comprehensive multimodal assessments performed pre-and postintervention.Cognitive functioning was quantified using the mini-mental state examination(MMSE)and Montreal cognitive assessment(MOCA),while daily living capacities and neuropsychiatric profiles were respectively evaluated through the activities of daily living(ADL)scale and combined neuropsychiatric inventory(NPI)-Hamilton depression rating scale(HAMD).Peripheral blood biomarkers,specifically Aβ1-40 and phosphorylated tau(p-tau181),were analyzed to investigate the effects of rTMS on molecular metabolism.Spectral power analysis was employed to investigate rTMS-induced modulations of neural rhythms in AD patients,while brain network analyses incorporating topological properties were conducted to examine stimulus-driven network reorganization.Furthermore,systematic assessment of correlations between cognitive scale scores,blood biomarkers,and network characteristics was performed to elucidate cross-modal therapeutic associations.Results Clinically,MMSE and MOCA scores improved significantly(P<0.05).Biomarker showed that Aβ1-40 level increased(P<0.05),contrasting with p-tau181 reduction.Moreover,the levels of Aβ1-40 were positively correlated with MMSE and MOCA scores.Post-intervention analyses revealed significant modulations in oscillatory power,characterized by pronounced reductions in delta(P<0.05)and theta bands(P<0.05),while concurrent enhancements were observed in alpha,beta,and gamma band activities(all P<0.05).Network analysis revealed frequency-specific reorganization:clustering coefficients were significantly decreased in delta,theta,and alpha bands(P<0.05),while global efficiency improvement was exclusively detected in the delta band(P<0.05).The alpha band demonstrated concurrent increases in average nodal degree(P<0.05)and characteristic path length reduction(P<0.05).Further research findings indicate that the changes in the clinical scale HAMD scores before and after rTMS stimulation are negatively correlated with the changes in the blood biomarkers Aβ1-40 and p-tau181.Additionally,the changes in the clinical scales MMSE and MoCA scores were negatively correlated with the changes in the node degree of the alpha frequency band and negatively correlated with the clustering coefficient of the delta frequency band.However,the changes in MMSE scores are positively correlated with the changes in global efficiency of both the delta and alpha frequency bands.Conclusion 20 Hz rTMS targeting dorsolateral prefrontal cortex(DLPFC)significantly improves cognitive function and enhances the metabolic clearance ofβ-amyloid and tau proteins in AD patients.This neurotherapeutic effect is mechanistically associated with rTMS-mediated frequency-selective neuromodulation,which enhances the connectivity of oscillatory networks through improved neuronal synchronization and optimized topological organization of functional brain networks.These findings not only support the efficacy of rTMS as an adjunctive therapy for AD but also underscore the importance of employing multiple assessment methods—including clinical scales,blood biomarkers,and EEG——in understanding and monitoring the progression of AD.This research provides a significant theoretical foundation and empirical evidence for further exploration of rTMS applications in AD treatment.
基金Project(60873081)supported by the National Natural Science Foundation of ChinaProject(NCET-10-0787)supported by Program for New Century Excellent Talents in UniversityProject(11JJ1012)supported by the Natural Science Foundation of Hunan Province,China
文摘The optimization of network performance in a movement-assisted data gathering scheme was studied by analyzing the energy consumption of wireless sensor network with node uniform distribution. A theoretically analytical method for avoiding energy hole was proposed. It is proved that if the densities of sensor nodes working at the same time are alternate between dormancy and work with non-uniform node distribution. The efficiency of network can increase by several times and the residual energy of network is nearly zero when the network lifetime ends.
基金Project(60673164)supported by the National Natural Science Foundation of ChinaProject(20060533057)supported by the Specialized Research Foundation for the Doctoral Program of Higher Education of China
文摘In the application of periodic data-gathering in sensor networks,sensor nodes located near the sink have to forward the data received from all other nodes to the sink,which depletes their energy very quickly.A moving scheme for the sink based on local residual energy was proposed.In the scheme,the sink periodically moves to a new location with the highest stay-value defined by the average residual energy and the number of neighbors.The scheme can balance energy consumption and prevent nodes around sink from draining their energy very quickly in the networks.The simulation results show that the scheme can prolong the network lifetime by 26%-65%compared with the earlier schemes where the sink is static or moves randomly.
文摘The method of determining the structures and parameters of radial basis function neural networks(RBFNNs) using improved genetic algorithms is proposed. Akaike′s information criterion (AIC) with generalization error term is used as the best criterion of optimizing the structures and parameters of networks. It is shown from the simulation results that the method not only improves the approximation and generalization capability of RBFNNs ,but also obtain the optimal or suboptimal structures of networks.
基金Chinese Academy of Engi⁃neering Strategic Consulting Project(2022-XY-45)S&T Program of Hebei(22372502D)+1 种基金Scien⁃tific Research Project of Hebei Provincial Admin⁃istration of Traditional Chinese Medicine(023172)and Scientific Research Project of Hebei Provincial Administration of Traditional Chinese Medicine(2021273)。
文摘OBJECTIVE To explore the new indications and key mechanism of Bazi Bushen capsule(BZBS)by network pharmacology and in vitro experiment.METHODS The potential tar⁃get profiles of the components of BZBS were pre⁃dicted.Subsequently,new indications for BZBS were predicted by disease ontology(DO)enrich⁃ment analysis and initially validated by GO and KEGG pathway enrichment analysis.Further⁃more,the therapeutic target of BZBS acting on AD signaling pathway were identified by intersec⁃tion analysis.Two Alzheimer′s disease(AD)cell models,BV-2 and SH-SY5Y,were used to pre⁃liminarily verify the anti-AD efficacy and mecha⁃nism of BZBS in vitro.RESULTS In total,1499 non-repeated ingredients were obtained from 16 herbs in BZBS formula,and 1320 BZBS targets with high confidence were predicted.Disease enrichment results strongly suggested that BZBS formula has the potential to be used in the treat⁃ment of AD.In vitro experiments showed that BZ⁃BS could significantly reduce the release of TNF-αand IL-6 and the expression of COX-2 and PSEN1 in Aβ25-35-induced BV-2 cells.BZBS reduced the apoptosis rate of Aβ25-35 induced SH-SY5Y cells,significantly increased mitochon⁃drial membrane potential,reduced the expres⁃sion of Caspase3 active fragment and PSEN1,and increased the expression of IDE.CONCLU⁃SIONS BZBS formula has a potential use in the treatment of AD,which is achieved through regu⁃lation of ERK1/2,NF-κB signaling pathways,and GSK-3β/β-catenin signaling pathway.Further⁃more,the network pharmacology technology is a feasible drug repurposing strategy to reposition new clinical use of approved TCM and explore the mechanism of action.The study lays a foun⁃dation for the subsequent in-depth study of BZBS in the treatment of AD and provides a basis for its application in the clinical treatment of AD.
基金Projects(61101104,61100213) supported by the National Natural Science Foundation of ChinaProject(NY211050) supported by Fund of Nanjing University of Posts and Telecommunications,China
文摘A distributed local adaptive transmit power assignment (LA-TPA) strategy was proposed to construct a topology with better performance according to the environment and application scenario and prolong the network lifetime.It takes the path loss exponent and the energy control coefficient into consideration with the aim to accentuate the minimum covering district of each node more accurately and precisely according to various network application scenarios.Besides,a self-healing scheme that enhances the robustness of the network was provided.It makes the topology tolerate more dead nodes than existing algorithms.Simulation was done under OMNeT++ platform and the results show that the LA-TPA strategy is more effective in constructing a well-performance network topology based on various application scenarios and can prolong the network lifetime significantly.
文摘Newton＇s learning algorithm of NN is presented and realized. In theory, the convergence rate of learning algorithm of NN based on Newton＇s method must be faster than BP＇s and other learning algorithms, because the gradient method is linearly convergent while Newton＇s method has second order convergence rate. The fast computing algorithm of Hesse matrix of the cost function of NN is proposed and it is the theory basis of the improvement of Newton＇s learning algorithm. Simulation results show that the convergence rate of Newton＇s learning algorithm is high and apparently faster than the traditional BP method＇s, and the robustness of Newton＇s learning algorithm is also better than BP method＇ s.
基金Supported by National Natural Science Foundation of China （61034005, 60974071）, Program for New Century Excellent Talents in University （NCET-08-0101）, and Fundamental Research Funds for the Central Universities （N100104102, Nl10604007）
文摘Security and reliability must be focused on control sys- tems firstly, and fault detection and diagnosis （FDD） is the main theory and technology. Now, there are many positive results in FDD for linear networked control systems （LNCSs）, but nonlinear networked control systems （NNCSs） are less involved. Based on the T-S fuzzy-modeling theory, NNCSs are modeled and network random time-delays are changed into the unknown bounded uncertain part without changing its structure. Then a fuzzy state observer is designed and an observer-based fault detection approach for an NNCS is presented. The main results are given and the relative theories are proved in detail. Finally, some simulation results are given and demonstrate the proposed method is effective.
基金supported by the National Natural Science Foundation of China(61174022)the National High Technology Research and Development Program of China(863 Program)(2013AA013801)+2 种基金the Open Funding Project of State Key Laboratory of Virtual Reality Technology and Systems,Beihang University(BUAA-VR-14KF-02)the General Research Program of the Science Supported by Sichuan Provincial Department of Education(14ZB0322)the Fundamental Research Funds for the Central Universities(XDJK2014D008)
文摘Identifying influential nodes in complex networks is still an open issue. In this paper, a new comprehensive centrality mea- sure is proposed based on the Dempster-Shafer evidence theory. The existing measures of degree centrality, betweenness centra- lity and closeness centrality are taken into consideration in the proposed method. Numerical examples are used to illustrate the effectiveness of the proposed method.
基金National Natural Science Foundation of china(60274014,60574088)
文摘Based on the T-S fuzzy model,this paper presents a new model of non-linear network control system with stochastic transfer delay.Sufficient criterion is proposed to guarantee globally asymptotically stability of this two-levels T-S fuzzy model.Also a T-S fuzzy observer of NCS is designed base on this two-levels T-S fuzzy model.All these results present a new approach for networked control system analysis and design.
基金Project(E2015203354)supported by Natural Science Foundation of Steel United Research Fund of Hebei Province,ChinaProject(ZD2016100)supported by the Science and the Technology Research Key Project of High School of Hebei Province,China+1 种基金Project(LJRC013)supported by the University Innovation Team of Hebei Province Leading Talent Cultivation,ChinaProject(16LGY015)supported by the Basic Research Special Breeding of Yanshan University,China
文摘The accuracy of present flatness predictive method is limited and it just belongs to software simulation. In order to improve it, a novel flatness predictive model via T-S cloud reasoning network implemented by digital signal processor(DSP) is proposed. First, the combination of genetic algorithm(GA) and simulated annealing algorithm(SAA) is put forward, called GA-SA algorithm, which can make full use of the global search ability of GA and local search ability of SA. Later, based on T-S cloud reasoning neural network, flatness predictive model is designed in DSP. And it is applied to 900 HC reversible cold rolling mill. Experimental results demonstrate that the flatness predictive model via T-S cloud reasoning network can run on the hardware DSP TMS320 F2812 with high accuracy and robustness by using GA-SA algorithm to optimize the model parameter.
文摘为更好地对S/X波段天气雷达组网融合在广西区域的应用能力进行评估,利用雷达观测资料,依次进行基数据解析、Z_(H)-K_(DP)综合法衰减订正、单站雷达网格化及多部雷达组网拼图,最终利用组合反射率、等高平面反射率对广西现有雷达组网覆盖能力在2023年第4号台风“泰利”影响过程进行初步应用分析。结果显示:结合径向廓线对比、网格化对比及多个连续体扫得到的反射率对比分析,经过Z_(H)-K_(DP)综合法订正后的X波段天气雷达反射率在一定范围内具有较高的可靠性;将组网拼图结果应用于台风“泰利”暴雨过程分析,对比S波段和S/X波段天气雷达组网后的0.5 km、0.75 km、1.0 km和2.0 km CAPPI(Constant Altitude Plan Position Indicator)组网反射率因子覆盖区域,结果显示X波段加入雷达组网后,得到了空间结构连续、覆盖更广的资料,有效补充了广西新一代天气雷达的低层盲区、阻挡空缺区等。
