Cutting off or controlling the enemy’s power supply at critical moments or strategic locations may result in a cascade failure,thus gaining an advantage in a war.However,the exist-ing cascading failure modeling analy...Cutting off or controlling the enemy’s power supply at critical moments or strategic locations may result in a cascade failure,thus gaining an advantage in a war.However,the exist-ing cascading failure modeling analysis of interdependent net-works is insufficient for describing the load characteristics and dependencies of subnetworks,and it is difficult to use for model-ing and failure analysis of power-combat(P-C)coupling net-works.This paper considers the physical characteristics of the two subnetworks and studies the mechanism of fault propaga-tion between subnetworks and across systems.Then the surviv-ability of the coupled network is evaluated.Firstly,an integrated modeling approach for the combat system and power system is predicted based on interdependent network theory.A heteroge-neous one-way interdependent network model based on proba-bility dependence is constructed.Secondly,using the operation loop theory,a load-capacity model based on combat-loop betweenness is proposed,and the cascade failure model of the P-C coupling system is investigated from three perspectives:ini-tial capacity,allocation strategy,and failure mechanism.Thirdly,survivability indexes based on load loss rate and network sur-vival rate are proposed.Finally,the P-C coupling system is con-structed based on the IEEE 118-bus system to demonstrate the proposed method.展开更多
Transmission network planning (TNP) is a large-scale, complex, with more non-linear discrete variables and the multi-objective constrained optimization problem. In the optimization process, the line investment, networ...Transmission network planning (TNP) is a large-scale, complex, with more non-linear discrete variables and the multi-objective constrained optimization problem. In the optimization process, the line investment, network reliability and the network loss are the main objective of transmission network planning. Combined with set pair analysis (SPA), particle swarm optimization (PSO), neural network (NN), a hybrid particle swarm optimization model was established with neural network and set pair analysis for transmission network planning (HPNS). Firstly, the contact degree of set pair analysis was introduced, the traditional goal set was converted into the collection of the three indicators including the identity degree, difference agree and contrary degree. On this bases, using shi(H), the three objective optimization problem was converted into single objective optimization problem. Secondly, using the fast and efficient search capabilities of PSO, the transmission network planning model based on set pair analysis was optimized. In the process of optimization, by improving the BP neural network constantly training so that the value of the fitness function of PSO becomes smaller in order to obtain the optimization program fitting the three objectives better. Finally, compared HPNS with PSO algorithm and the classic genetic algorithm, HPNS increased about 23% efficiency than THA, raised about 3.7% than PSO and improved about 2.96% than GA.展开更多
As for the factors affecting the heat transfer performance of complex and nonlinear oscillating heat pipe (OHP),grey relational analysis (GRA) was used to deal with the relationship between heat transfer rate of a loo...As for the factors affecting the heat transfer performance of complex and nonlinear oscillating heat pipe (OHP),grey relational analysis (GRA) was used to deal with the relationship between heat transfer rate of a looped copper-water OHP and charging ratio,inner diameter,inclination angel,heat input,number of turns,and the main influencing factors were defined.Then,forecasting model was obtained by using main influencing factors (such as charging ratio,interior diameter,and inclination angel) as the inputs of function chain neural network.The results show that the relative average error between the predicted and actual value is 4%,which illustrates that the function chain neural network can be applied to predict the performance of OHP accurately.展开更多
A new method was proposed to cope with the earth slope reliability problem under seismic loadings. The algorithm integrates the concepts of artificial neural network, the first order second moment reliability method a...A new method was proposed to cope with the earth slope reliability problem under seismic loadings. The algorithm integrates the concepts of artificial neural network, the first order second moment reliability method and the deterministic stability analysis method of earth slope. The performance function and its derivatives in slope stability analysis under seismic loadings were approximated by a trained multi-layer feed-forward neural network with differentiable transfer functions. The statistical moments calculated from the performance function values and the corresponding gradients using neural network were then used in the first order second moment method for the calculation of the reliability index in slope safety analysis. Two earth slope examples were presented for illustrating the applicability of the proposed approach. The new method is effective in slope reliability analysis. And it has potential application to other reliability problems of complicated engineering structure with a considerably large number of random variables.展开更多
The turn-key construction project is implemented in Taiwan not by a single company but by a make-shift group of several companies. Hence,problems to coordinate the professional construction management (PCM) and the su...The turn-key construction project is implemented in Taiwan not by a single company but by a make-shift group of several companies. Hence,problems to coordinate the professional construction management (PCM) and the supervising architectural company often occur for the lack of long-term experience to work together. The various factors that affect the implementation of turn-key projects currently practiced in Taiwan are analyzed using the analytic network process (ANP). The objective is to study how the twelve key factors in the four layers of "Role assignment","Signing contract","Operational procedures" and "Losing capital investment" affect the progress of implementing the turn-key project in Taiwan. The results reveal that "Delay in payment" has the most negative influence with 15.62% weighing factor; "Latent risk" comes next with 11.14% weighing factor,and "Responsibility of construction company for project quality" is the third with 10.79% weighing factor.展开更多
A method of system structural analysis based on decision making trial and evaluation laboratory together with interpretative structural modeling(DEMATEL-ISM) and entropy is proposed to clarify system structure of comm...A method of system structural analysis based on decision making trial and evaluation laboratory together with interpretative structural modeling(DEMATEL-ISM) and entropy is proposed to clarify system structure of communication networks and analyze mutual influencing degree between different networks.Mutual influencing degree and importance degree of elements are both considered to determine weights of elements,and the entropy of expert judgment results is used to omit unimportant influence relation and simplify system structure.Structural analysis on communication networks system shows that the proposed method can quantificationally present weights and mutual influencing degree of elements,and reasonably simplify system structure.The results indicate the rationality and feasibility of the method.展开更多
Fault diagnostics is an important research area including different techniques.Principal component analysis(PCA)is a linear technique which has been widely used.For nonlinear processes,however,the nonlinear principal ...Fault diagnostics is an important research area including different techniques.Principal component analysis(PCA)is a linear technique which has been widely used.For nonlinear processes,however,the nonlinear principal component analysis(NLPCA)should be applied.In this work,NLPCA based on auto-associative neural network(AANN)was applied to model a chemical process using historical data.First,the residuals generated by the AANN were used for fault detection and then a reconstruction based approach called enhanced AANN(E-AANN)was presented to isolate and reconstruct the faulty sensor simultaneously.The proposed method was implemented on a continuous stirred tank heater(CSTH)and used to detect and isolate two types of faults(drift and offset)for a sensor.The results show that the proposed method can detect,isolate and reconstruct the occurred fault properly.展开更多
A combined model based on principal components analysis (PCA) and generalized regression neural network (GRNN) was adopted to forecast electricity price in day-ahead electricity market. PCA was applied to mine the mai...A combined model based on principal components analysis (PCA) and generalized regression neural network (GRNN) was adopted to forecast electricity price in day-ahead electricity market. PCA was applied to mine the main influence on day-ahead price, avoiding the strong correlation between the input factors that might influence electricity price, such as the load of the forecasting hour, other history loads and prices, weather and temperature; then GRNN was employed to forecast electricity price according to the main information extracted by PCA. To prove the efficiency of the combined model, a case from PJM (Pennsylvania-New Jersey-Maryland) day-ahead electricity market was evaluated. Compared to back-propagation (BP) neural network and standard GRNN, the combined method reduces the mean absolute percentage error about 3%.展开更多
The interception probability of a single missile is the basis for combat plan design and weapon performance evaluation,while its influencing factors are complex and mutually coupled.Existing calculation methods have v...The interception probability of a single missile is the basis for combat plan design and weapon performance evaluation,while its influencing factors are complex and mutually coupled.Existing calculation methods have very limited analysis of the influence mechanism of influencing factors,and none of them has analyzed the influence of the guidance law.This paper considers the influencing factors of both the interceptor and the target more comprehensively.Interceptor parameters include speed,guidance law,guidance error,fuze error,and fragment killing ability,while target performance includes speed,maneuverability,and vulnerability.In this paper,an interception model is established,Monte Carlo simulation is carried out,and the influence mechanism of each factor is analyzed based on the model and simulation results.Finally,this paper proposes a classification-regression neural network to quickly estimate the interception probability based on the value of influencing factors.The proposed method reduces the interference of invalid interception data to valid data,so its prediction accuracy is significantly better than that of pure regression neural networks.展开更多
Accurate 3-D fracture network model for rock mass in dam foundation is of vital importance for stability,grouting and seepage analysis of dam foundation.With the aim of reducing deviation between fracture network mode...Accurate 3-D fracture network model for rock mass in dam foundation is of vital importance for stability,grouting and seepage analysis of dam foundation.With the aim of reducing deviation between fracture network model and measured data,a 3-D fracture network dynamic modeling method based on error analysis was proposed.Firstly,errors of four fracture volume density estimation methods(proposed by ODA,KULATILAKE,MAULDON,and SONG)and that of four fracture size estimation methods(proposed by EINSTEIN,SONG and TONON)were respectively compared,and the optimal methods were determined.Additionally,error index representing the deviation between fracture network model and measured data was established with integrated use of fractal dimension and relative absolute error(RAE).On this basis,the downhill simplex method was used to build the dynamic modeling method,which takes the minimum of error index as objective function and dynamically adjusts the fracture density and size parameters to correct the error index.Finally,the 3-D fracture network model could be obtained which meets the requirements.The proposed method was applied for 3-D fractures simulation in Miao Wei hydropower project in China for feasibility verification and the error index reduced from 2.618 to 0.337.展开更多
The stability analysis and stabilization problems of the wireless networked control systems(WNCSs) with signal transmission deadbands were considered. The deadbands were respectively set up at the sensor to the contro...The stability analysis and stabilization problems of the wireless networked control systems(WNCSs) with signal transmission deadbands were considered. The deadbands were respectively set up at the sensor to the controller and the controller to the actor sides in the WNCS, which were used to reduce data transmission, furthermore, to decrease the network collision and node energy consumption. Under the consideration of time-varying delays and signal transmission deadbands, the model for the WNCS was presented. A novel Lyapunov functional which took full advantages of the network factors was exploited. Meanwhile, new stability analysis and stabilization conditions for the WNCS were proposed, which described the relationship of the delay bounds, the transmission deadband bounds and the system stability. Two examples were used to demonstrate the effectiveness of the proposed methods. The results show that the proposed approach can guarantee asymptotical stability of the system and reduce the data transmission effectively.展开更多
In district heating(DH) system with gas-fired peak load regulating boiler in the secondary network,by prolonging run time of base load plants under rated condition,the mean energy efficiency could be increased. The fu...In district heating(DH) system with gas-fired peak load regulating boiler in the secondary network,by prolonging run time of base load plants under rated condition,the mean energy efficiency could be increased. The fuels of the system,including coal and gas,would cause different environmental impacts. Meanwhile,the reliability of the heating networks would be changed because the peak load regulating boiler could work as a standby heat source. A model for assessment of heating system was established by value analysis to optimize this kind of system. Energy consumption,greenhouse gas emission,pollution emission and system reliability were selected as functional assessment indexes in the model. Weights of each function were determined by analytical hierarchy process (AHP) and experts consultation. Life cycle cost was used as the cost in the model. A real case as an example was discussed to obtain the optimal base load ratio. The result shows that the optimal base load ratio of the case is 0.77.展开更多
A general classification algorithm of neural networks is unable to obtain satisfied results because of the uncertain problems existing among the features in moot classification programs, such as interaction. With new ...A general classification algorithm of neural networks is unable to obtain satisfied results because of the uncertain problems existing among the features in moot classification programs, such as interaction. With new features constructed by optimizing decision trees of examples, the input of neural networks is improved and an optimized classification algorithm based on neural networks is presented. A concept of dispersion of a classification program is also introduced too in this paper. At the end of the paper, an analysis is made with an example.展开更多
A new combinational technology is proposed,which is feasible to apply physical-layer network coding（PNC） to wireless fading channels by employing the harmful interference strategically.The key step of PNC is that so...A new combinational technology is proposed,which is feasible to apply physical-layer network coding（PNC） to wireless fading channels by employing the harmful interference strategically.The key step of PNC is that sources broadcast signals simultaneously without orthogonal scheduling.Naturally,the signals overlap in the free space at the receivers.Since the signals from different sources are mutual independent,rooted on this rational assumption,an enhanced joint diagonalization separation named altering row diagonalization（ARD） algorithm is exploited to separate these signals by maximizing the cost function measuring independence among them.This ARD PNC（APNC） methodology provides an innovative way to implement signal-level network coding at the presence of interference and without any priori information about channels in fading environments.In conclusions,the proposed APNC performs well with higher bandwidth utility and lower error rate.展开更多
The probability model is used to analyze the fault tolerance of mesh. To simplify its analysis, it is as-sumed that the failure probability of each node is independent. A 3-D mesh is partitioned into smaller submeshes...The probability model is used to analyze the fault tolerance of mesh. To simplify its analysis, it is as-sumed that the failure probability of each node is independent. A 3-D mesh is partitioned into smaller submeshes,and then the probability with which each submesh satisfies the defined condition is computed. If each submesh satis-fies the condition, then the whole mesh is connected. Consequently, the probability that a 3-D mesh is connected iscomputed assuming each node has a failure probability. Mathematical methods are used to derive a relationship be-tween network node failure probability and network connectivity probability. The calculated results show that the 3-D mesh networks can remain connected with very high probability in practice. It is formally proved that when thenetwork node failure probability is boutded by 0.45 %, the 3-D mesh networks of more than three hundred thousandnodes remain connected with probability larger than 99 %. The theoretical results show that the method is a power-ful technique to calculate the lower bound of the connectivity probability of mesh networks.展开更多
OBJECTIVE To construct the neuroendocrine immunomodulation(NIM) sub-network regulated by Liuwei Dihuang decoction(LW) and analyze its characteristics.METHODS We took the GSE57273 in GEO database and screened the diffe...OBJECTIVE To construct the neuroendocrine immunomodulation(NIM) sub-network regulated by Liuwei Dihuang decoction(LW) and analyze its characteristics.METHODS We took the GSE57273 in GEO database and screened the differentially expressed genes(DEGs)(P<0.01) by the GEO2 R tool as gene expression signature of LW.The global PPI network was constructed in the context of whole PPI network through direct interaction algorithm and forest algorithm respectively.Then the enrichment and the topological characteristics of NIM signaling molecules were evaluated by permutation test.Finally,we abstracted the NIM sub-network by NIMNT,which combined the NIM molecular network and forest algorithm,and analyzed the topological characteristics of it by the Network Analyzer(release 2.7) plugin in Cytoscape v3.5.1.RESULTS We got 2468 DEGs in the gene expression signature of LW.After analyzing the global PPI network of LW got by two kinds of algorithms,we found that the NIM signaling molecules significantly enriched and located in important positions in the global PPI network.The NIM sub-network regulated by LW contained 1099 nodes and 1056 edges.We screened out 22 hub nodes(Degree>10).Among them,there were 19 NIM signaling molecules in which only ESR1 changed significantly and 3 non-DEGs(NFATC2,RARA,TP53).However,the down.stream of the hub nodes were significantly changes.CONCLUSION The results suggested that LW might mainly regulate the non-hub nodes to recovery of the network imbalance of the body in the state of disease.展开更多
In order to solve the problem that the ripple-effect analy- sis for the operational architecture of air defense systems （OAADS） is hardly described in quantity with previous modeling approaches, a supernetwork model...In order to solve the problem that the ripple-effect analy- sis for the operational architecture of air defense systems （OAADS） is hardly described in quantity with previous modeling approaches, a supernetwork modeling approach for the OAADS is put for- ward by extending granular computing. Based on that operational units and links are equal to different information granularities, the supernetwork framework of the OAADS is constructed as a “four- network within two-layer” structure by forming dynamic operating coalitions, and measuring indexes of the ripple-effect analysis for the OAADS are given combining with Laplace spectral radius. In this framework, via analyzing multidimensional attributes which inherit relations between operational units in different granular scales, an extended granular computing is put forward integrating with a topological structure. Then the operation process within the supernetwork framework, including transformation relations be- tween two layers in the vertical view and mapping relations among functional networks in the horizontal view, is studied in quantity. As the application case shows, comparing with previous modeling approaches, the supernetwork model can validate and analyze the operation mechanism in the air defense architecture, and the ripple-effect analysis can be used to confirm the key operational unit with micro and macro viewpoints.展开更多
This paper proposes a reliability evaluation model for a multi-dimensional network system,which has potential to be applied to the internet of things or other practical networks.A multi-dimensional network system with...This paper proposes a reliability evaluation model for a multi-dimensional network system,which has potential to be applied to the internet of things or other practical networks.A multi-dimensional network system with one source element and multiple sink elements is considered first.Each element can con-nect with other elements within a stochastic connection ranges.The system is regarded as successful as long as the source ele-ment remains connected with all sink elements.An importance measure is proposed to evaluate the performance of non-source elements.Furthermore,to calculate the system reliability and the element importance measure,a multi-valued decision diagram based approach is structured and its complexity is analyzed.Finally,a numerical example about the signal transfer station system is illustrated to analyze the system reliability and the ele-ment importance measure.展开更多
基金supported by the National Natural Science Foundation of China(72271242)Hunan Provincial Natural Science Foundation of China for Excellent Young Scholars(2022JJ20046).
文摘Cutting off or controlling the enemy’s power supply at critical moments or strategic locations may result in a cascade failure,thus gaining an advantage in a war.However,the exist-ing cascading failure modeling analysis of interdependent net-works is insufficient for describing the load characteristics and dependencies of subnetworks,and it is difficult to use for model-ing and failure analysis of power-combat(P-C)coupling net-works.This paper considers the physical characteristics of the two subnetworks and studies the mechanism of fault propaga-tion between subnetworks and across systems.Then the surviv-ability of the coupled network is evaluated.Firstly,an integrated modeling approach for the combat system and power system is predicted based on interdependent network theory.A heteroge-neous one-way interdependent network model based on proba-bility dependence is constructed.Secondly,using the operation loop theory,a load-capacity model based on combat-loop betweenness is proposed,and the cascade failure model of the P-C coupling system is investigated from three perspectives:ini-tial capacity,allocation strategy,and failure mechanism.Thirdly,survivability indexes based on load loss rate and network sur-vival rate are proposed.Finally,the P-C coupling system is con-structed based on the IEEE 118-bus system to demonstrate the proposed method.
基金Projects(70373017 70572090) supported by the National Natural Science Foundation of China
文摘Transmission network planning (TNP) is a large-scale, complex, with more non-linear discrete variables and the multi-objective constrained optimization problem. In the optimization process, the line investment, network reliability and the network loss are the main objective of transmission network planning. Combined with set pair analysis (SPA), particle swarm optimization (PSO), neural network (NN), a hybrid particle swarm optimization model was established with neural network and set pair analysis for transmission network planning (HPNS). Firstly, the contact degree of set pair analysis was introduced, the traditional goal set was converted into the collection of the three indicators including the identity degree, difference agree and contrary degree. On this bases, using shi(H), the three objective optimization problem was converted into single objective optimization problem. Secondly, using the fast and efficient search capabilities of PSO, the transmission network planning model based on set pair analysis was optimized. In the process of optimization, by improving the BP neural network constantly training so that the value of the fitness function of PSO becomes smaller in order to obtain the optimization program fitting the three objectives better. Finally, compared HPNS with PSO algorithm and the classic genetic algorithm, HPNS increased about 23% efficiency than THA, raised about 3.7% than PSO and improved about 2.96% than GA.
基金Project(531107040300) supported by the Fundamental Research Funds for the Central Universities in ChinaProject(2006BAJ04B04) supported by the National Science and Technology Pillar Program during the Eleventh Five-year Plan Period of China
文摘As for the factors affecting the heat transfer performance of complex and nonlinear oscillating heat pipe (OHP),grey relational analysis (GRA) was used to deal with the relationship between heat transfer rate of a looped copper-water OHP and charging ratio,inner diameter,inclination angel,heat input,number of turns,and the main influencing factors were defined.Then,forecasting model was obtained by using main influencing factors (such as charging ratio,interior diameter,and inclination angel) as the inputs of function chain neural network.The results show that the relative average error between the predicted and actual value is 4%,which illustrates that the function chain neural network can be applied to predict the performance of OHP accurately.
文摘A new method was proposed to cope with the earth slope reliability problem under seismic loadings. The algorithm integrates the concepts of artificial neural network, the first order second moment reliability method and the deterministic stability analysis method of earth slope. The performance function and its derivatives in slope stability analysis under seismic loadings were approximated by a trained multi-layer feed-forward neural network with differentiable transfer functions. The statistical moments calculated from the performance function values and the corresponding gradients using neural network were then used in the first order second moment method for the calculation of the reliability index in slope safety analysis. Two earth slope examples were presented for illustrating the applicability of the proposed approach. The new method is effective in slope reliability analysis. And it has potential application to other reliability problems of complicated engineering structure with a considerably large number of random variables.
文摘The turn-key construction project is implemented in Taiwan not by a single company but by a make-shift group of several companies. Hence,problems to coordinate the professional construction management (PCM) and the supervising architectural company often occur for the lack of long-term experience to work together. The various factors that affect the implementation of turn-key projects currently practiced in Taiwan are analyzed using the analytic network process (ANP). The objective is to study how the twelve key factors in the four layers of "Role assignment","Signing contract","Operational procedures" and "Losing capital investment" affect the progress of implementing the turn-key project in Taiwan. The results reveal that "Delay in payment" has the most negative influence with 15.62% weighing factor; "Latent risk" comes next with 11.14% weighing factor,and "Responsibility of construction company for project quality" is the third with 10.79% weighing factor.
基金Project(20141996018)supported by Aerospace Science Foundation of ChinaProject(2012JZ8005)supported by the Natural Science Fundamental Research Planned Project of Shanxi Province,China
文摘A method of system structural analysis based on decision making trial and evaluation laboratory together with interpretative structural modeling(DEMATEL-ISM) and entropy is proposed to clarify system structure of communication networks and analyze mutual influencing degree between different networks.Mutual influencing degree and importance degree of elements are both considered to determine weights of elements,and the entropy of expert judgment results is used to omit unimportant influence relation and simplify system structure.Structural analysis on communication networks system shows that the proposed method can quantificationally present weights and mutual influencing degree of elements,and reasonably simplify system structure.The results indicate the rationality and feasibility of the method.
基金Project(1390/2)supported by Khuzestan Gas Company,Iran
文摘Fault diagnostics is an important research area including different techniques.Principal component analysis(PCA)is a linear technique which has been widely used.For nonlinear processes,however,the nonlinear principal component analysis(NLPCA)should be applied.In this work,NLPCA based on auto-associative neural network(AANN)was applied to model a chemical process using historical data.First,the residuals generated by the AANN were used for fault detection and then a reconstruction based approach called enhanced AANN(E-AANN)was presented to isolate and reconstruct the faulty sensor simultaneously.The proposed method was implemented on a continuous stirred tank heater(CSTH)and used to detect and isolate two types of faults(drift and offset)for a sensor.The results show that the proposed method can detect,isolate and reconstruct the occurred fault properly.
基金Project(70671039) supported by the National Natural Science Foundation of China
文摘A combined model based on principal components analysis (PCA) and generalized regression neural network (GRNN) was adopted to forecast electricity price in day-ahead electricity market. PCA was applied to mine the main influence on day-ahead price, avoiding the strong correlation between the input factors that might influence electricity price, such as the load of the forecasting hour, other history loads and prices, weather and temperature; then GRNN was employed to forecast electricity price according to the main information extracted by PCA. To prove the efficiency of the combined model, a case from PJM (Pennsylvania-New Jersey-Maryland) day-ahead electricity market was evaluated. Compared to back-propagation (BP) neural network and standard GRNN, the combined method reduces the mean absolute percentage error about 3%.
基金supported by the Foundation Strengthening Program Technology Field Foundation(2020-JCJQ-JJ-132)。
文摘The interception probability of a single missile is the basis for combat plan design and weapon performance evaluation,while its influencing factors are complex and mutually coupled.Existing calculation methods have very limited analysis of the influence mechanism of influencing factors,and none of them has analyzed the influence of the guidance law.This paper considers the influencing factors of both the interceptor and the target more comprehensively.Interceptor parameters include speed,guidance law,guidance error,fuze error,and fragment killing ability,while target performance includes speed,maneuverability,and vulnerability.In this paper,an interception model is established,Monte Carlo simulation is carried out,and the influence mechanism of each factor is analyzed based on the model and simulation results.Finally,this paper proposes a classification-regression neural network to quickly estimate the interception probability based on the value of influencing factors.The proposed method reduces the interference of invalid interception data to valid data,so its prediction accuracy is significantly better than that of pure regression neural networks.
基金Project(51321065)supported by the Innovative Research Groups of the National Natural Science Foundation of ChinaProject(2013CB035904)supported by the National Basic Research Program of China(973 Program)Project(51439005)supported by the National Natural Science Foundation of China
文摘Accurate 3-D fracture network model for rock mass in dam foundation is of vital importance for stability,grouting and seepage analysis of dam foundation.With the aim of reducing deviation between fracture network model and measured data,a 3-D fracture network dynamic modeling method based on error analysis was proposed.Firstly,errors of four fracture volume density estimation methods(proposed by ODA,KULATILAKE,MAULDON,and SONG)and that of four fracture size estimation methods(proposed by EINSTEIN,SONG and TONON)were respectively compared,and the optimal methods were determined.Additionally,error index representing the deviation between fracture network model and measured data was established with integrated use of fractal dimension and relative absolute error(RAE).On this basis,the downhill simplex method was used to build the dynamic modeling method,which takes the minimum of error index as objective function and dynamically adjusts the fracture density and size parameters to correct the error index.Finally,the 3-D fracture network model could be obtained which meets the requirements.The proposed method was applied for 3-D fractures simulation in Miao Wei hydropower project in China for feasibility verification and the error index reduced from 2.618 to 0.337.
基金Project(61104106)supported by the National Natural Science Foundation of ChinaProject(201202156)supported by the Natural Science Foundation of Liaoning Province,ChinaProject(LJQ2012100)supported by the Program for Liaoning Excellent Talents in University(LNET),China
文摘The stability analysis and stabilization problems of the wireless networked control systems(WNCSs) with signal transmission deadbands were considered. The deadbands were respectively set up at the sensor to the controller and the controller to the actor sides in the WNCS, which were used to reduce data transmission, furthermore, to decrease the network collision and node energy consumption. Under the consideration of time-varying delays and signal transmission deadbands, the model for the WNCS was presented. A novel Lyapunov functional which took full advantages of the network factors was exploited. Meanwhile, new stability analysis and stabilization conditions for the WNCS were proposed, which described the relationship of the delay bounds, the transmission deadband bounds and the system stability. Two examples were used to demonstrate the effectiveness of the proposed methods. The results show that the proposed approach can guarantee asymptotical stability of the system and reduce the data transmission effectively.
基金Supported by National Naturai Science Foundation of China （61273104, 61021002, 61104097）, and Projects of Major Interna-tional （Regional） Joint Research Program National Natural Science Foundation of China （61120106010）
文摘In district heating(DH) system with gas-fired peak load regulating boiler in the secondary network,by prolonging run time of base load plants under rated condition,the mean energy efficiency could be increased. The fuels of the system,including coal and gas,would cause different environmental impacts. Meanwhile,the reliability of the heating networks would be changed because the peak load regulating boiler could work as a standby heat source. A model for assessment of heating system was established by value analysis to optimize this kind of system. Energy consumption,greenhouse gas emission,pollution emission and system reliability were selected as functional assessment indexes in the model. Weights of each function were determined by analytical hierarchy process (AHP) and experts consultation. Life cycle cost was used as the cost in the model. A real case as an example was discussed to obtain the optimal base load ratio. The result shows that the optimal base load ratio of the case is 0.77.
文摘A general classification algorithm of neural networks is unable to obtain satisfied results because of the uncertain problems existing among the features in moot classification programs, such as interaction. With new features constructed by optimizing decision trees of examples, the input of neural networks is improved and an optimized classification algorithm based on neural networks is presented. A concept of dispersion of a classification program is also introduced too in this paper. At the end of the paper, an analysis is made with an example.
基金supported by the National Natural Science Foundation of China(6120118361132002)
文摘A new combinational technology is proposed,which is feasible to apply physical-layer network coding（PNC） to wireless fading channels by employing the harmful interference strategically.The key step of PNC is that sources broadcast signals simultaneously without orthogonal scheduling.Naturally,the signals overlap in the free space at the receivers.Since the signals from different sources are mutual independent,rooted on this rational assumption,an enhanced joint diagonalization separation named altering row diagonalization（ARD） algorithm is exploited to separate these signals by maximizing the cost function measuring independence among them.This ARD PNC（APNC） methodology provides an innovative way to implement signal-level network coding at the presence of interference and without any priori information about channels in fading environments.In conclusions,the proposed APNC performs well with higher bandwidth utility and lower error rate.
基金Project (69928201) supported by the National Science Fund for Distinguished Young Scholars+1 种基金project (90104028) by the National Natural Science Foundation of China Project by Changjiang Scholar Re-ward Project
文摘The probability model is used to analyze the fault tolerance of mesh. To simplify its analysis, it is as-sumed that the failure probability of each node is independent. A 3-D mesh is partitioned into smaller submeshes,and then the probability with which each submesh satisfies the defined condition is computed. If each submesh satis-fies the condition, then the whole mesh is connected. Consequently, the probability that a 3-D mesh is connected iscomputed assuming each node has a failure probability. Mathematical methods are used to derive a relationship be-tween network node failure probability and network connectivity probability. The calculated results show that the 3-D mesh networks can remain connected with very high probability in practice. It is formally proved that when thenetwork node failure probability is boutded by 0.45 %, the 3-D mesh networks of more than three hundred thousandnodes remain connected with probability larger than 99 %. The theoretical results show that the method is a power-ful technique to calculate the lower bound of the connectivity probability of mesh networks.
基金supported by National Natural Science Foundation of China(81473191) and the National key Research and Development Program(2016YFC1306300)
文摘OBJECTIVE To construct the neuroendocrine immunomodulation(NIM) sub-network regulated by Liuwei Dihuang decoction(LW) and analyze its characteristics.METHODS We took the GSE57273 in GEO database and screened the differentially expressed genes(DEGs)(P<0.01) by the GEO2 R tool as gene expression signature of LW.The global PPI network was constructed in the context of whole PPI network through direct interaction algorithm and forest algorithm respectively.Then the enrichment and the topological characteristics of NIM signaling molecules were evaluated by permutation test.Finally,we abstracted the NIM sub-network by NIMNT,which combined the NIM molecular network and forest algorithm,and analyzed the topological characteristics of it by the Network Analyzer(release 2.7) plugin in Cytoscape v3.5.1.RESULTS We got 2468 DEGs in the gene expression signature of LW.After analyzing the global PPI network of LW got by two kinds of algorithms,we found that the NIM signaling molecules significantly enriched and located in important positions in the global PPI network.The NIM sub-network regulated by LW contained 1099 nodes and 1056 edges.We screened out 22 hub nodes(Degree>10).Among them,there were 19 NIM signaling molecules in which only ESR1 changed significantly and 3 non-DEGs(NFATC2,RARA,TP53).However,the down.stream of the hub nodes were significantly changes.CONCLUSION The results suggested that LW might mainly regulate the non-hub nodes to recovery of the network imbalance of the body in the state of disease.
基金supported by the National Natural Science Foundation of China(61272011)
文摘In order to solve the problem that the ripple-effect analy- sis for the operational architecture of air defense systems （OAADS） is hardly described in quantity with previous modeling approaches, a supernetwork modeling approach for the OAADS is put for- ward by extending granular computing. Based on that operational units and links are equal to different information granularities, the supernetwork framework of the OAADS is constructed as a “four- network within two-layer” structure by forming dynamic operating coalitions, and measuring indexes of the ripple-effect analysis for the OAADS are given combining with Laplace spectral radius. In this framework, via analyzing multidimensional attributes which inherit relations between operational units in different granular scales, an extended granular computing is put forward integrating with a topological structure. Then the operation process within the supernetwork framework, including transformation relations be- tween two layers in the vertical view and mapping relations among functional networks in the horizontal view, is studied in quantity. As the application case shows, comparing with previous modeling approaches, the supernetwork model can validate and analyze the operation mechanism in the air defense architecture, and the ripple-effect analysis can be used to confirm the key operational unit with micro and macro viewpoints.
基金supported by the National Natural Science Foundation of China(72101025,72271049),the Interdisciplinary Research Project for Young Teachers of USTB(Fundamental Research Funds for the Central Universities,FRF-IDRY-24-024)the Hebei Natural Science Foundation(F2023501011)+1 种基金the Fundamental Research Funds for the Central Universities(FRF-TP-20-073A1)the R&D Program of Beijing Municipal Education Commission(KM202411232015).
文摘This paper proposes a reliability evaluation model for a multi-dimensional network system,which has potential to be applied to the internet of things or other practical networks.A multi-dimensional network system with one source element and multiple sink elements is considered first.Each element can con-nect with other elements within a stochastic connection ranges.The system is regarded as successful as long as the source ele-ment remains connected with all sink elements.An importance measure is proposed to evaluate the performance of non-source elements.Furthermore,to calculate the system reliability and the element importance measure,a multi-valued decision diagram based approach is structured and its complexity is analyzed.Finally,a numerical example about the signal transfer station system is illustrated to analyze the system reliability and the ele-ment importance measure.
