The Edikan Mine,which consists of Fobinso and Esuajah gold deposits,lies within the Asankrangwa Gold Belt of the Birimian Supergroup in the Kumasi Basin.The metasedimentary rocks in the Basins and the faulted metavolc...The Edikan Mine,which consists of Fobinso and Esuajah gold deposits,lies within the Asankrangwa Gold Belt of the Birimian Supergroup in the Kumasi Basin.The metasedimentary rocks in the Basins and the faulted metavolcanic rocks in the Belts that make up the Birimian Supergroup were intruded by granitoids during the Eburnean Orogeny.This research aims to classify granitoids in the Edikan Mine and ascertain the petrogenetic and geochemical characteristics of some auriferous granitoids in the wider Kumasi Basin,Ghana,to understand the implications for geodynamic settings.A multi-methods approach involving field studies,petrographic studies,and whole-rock geochemical analysis was used to achieve the goal of the study.Petrographic studies revealed a relatively high abundance of plagioclase and a low percentage of K-feldspars(anorthoclase and orthoclase)in the Fobinso samples,suggesting that the samples are granodioritic in nature,while the Esuajah samples showed relatively low plagioclase abundance and a high percentage in K-feldspars,indicating that they are granitic.The granitoids from the study areas are co-magmatic.The granitoids in Esuajah and Fobinso are generally enriched in large ion lithophile elements and light rare earth elements than high field strength elements,middle rare earth elements,and heavy rare earth elements,indicating mixing with crustal sources during the evolution of the granitoids.The granitoids were tectonically formed in a syn-collisional+VAG setting,which implies that they were formed in the subduction zone setting.Fobinso granodiorites showed S-type signatures with evidence of extensive crustal contamination,while the Esuajah granites showed I-type signatures with little or no crustal contamination and are peraluminous.Gold mineralization in the study area is structurally and lithologically controlled with shear zones,faulting,and veining as the principal structures controlling the mineralization.The late-stage vein,V3,in the Edikan Mine is characterized by a low vein angle and is mineralized.展开更多
Owing to process conditions such as uneven clearance of base metal assembly and welding deformation,it is difficult to obtain well-formed structural welds with robot constant specification parameters welding.Determini...Owing to process conditions such as uneven clearance of base metal assembly and welding deformation,it is difficult to obtain well-formed structural welds with robot constant specification parameters welding.Determining how to extract a structured,anti-interference,concise,and dynamic knowledge model from measurable data,and then adjust the welding parameters with corresponding control methods in real time is a central problem to be solved in welding formation control.Hence,this paper proposes a welding penetration control method based on a Neighborhood Rough Set-Adaptive Neuro-Fuzzy Inference System(NRS-ANFIS)to achieve effective penetration control for the GMAW welding process.In orthogonal experiments,the NRS algorithm,which is based on visual sensing to obtain the properties of the weld pool and gap changes,is used to reduce the established frontal weld pool feature information decision table,and the minimum feature set of the weld pool tail width WTand the tail area coefficient CTSis obtained.The minimum feature set of the effective frontal weld pool,real-time line laser distance change,and real-time current information are used as the input for the ANFIS control system.The experimental results for the two groups of time-varying gaps demonstrate that under the condition of no preheating of the base metal,the complete welding penetration rate of the adjusted welding process parameters output by the trained ANFIS model reaches 87%,and the backside melting width is uniform and consistent,which meets the welding specification requirements.展开更多
Dear Editor,This letter deals with the distributed recursive set-membership filtering(DRSMF)issue for state-saturated systems under encryption-decryption mechanism.To guarantee the data security,the encryption-decrypt...Dear Editor,This letter deals with the distributed recursive set-membership filtering(DRSMF)issue for state-saturated systems under encryption-decryption mechanism.To guarantee the data security,the encryption-decryption mechanism is considered in the signal transmission process.Specifically,a novel DRSMF scheme is developed such that,for both state saturation and encryption-decryption mechanism,the filtering error(FE)is limited to the ellipsoid domain.Then,the filtering error constraint matrix(FECM)is computed and a desirable filter gain is derived by minimizing the FECM.Besides,the bound-edness evaluation of the FECM is provided.展开更多
To elucidate the geographical differentiation characteristics and driving mechanisms of Dissolved Organic Matter(DOM)in typical rivers,this study conducted a multi-spectral investigation on three representative river ...To elucidate the geographical differentiation characteristics and driving mechanisms of Dissolved Organic Matter(DOM)in typical rivers,this study conducted a multi-spectral investigation on three representative river types within Shandong Province:The mountainous Dawen River,the plain Tuhai River,and the artificial East Grand Canal.The DOM composition was analyzed using Ultraviolet-Visible(UV-Vis)absorption spectroscopy,Excitation-Emission Matrix(EEM)fluorescence spectroscopy,and parallel factor analysis(PARAFAC),while Principal Component Analysis(PCA)was employed to quantify the synergistic effects of natural processes and anthropogenic activities.Results revealed significant spatial heterogeneity in DOM composition and sources.The plain river exhibited the highest aromaticity(humic-like components:43.3%)due to long-term agricultural non-point source inputs and urban wastewater discharge.The mountain stream,shaped by complex terrain and relatively intact ecosystems,was dominated by autochthonous DOM derived from microbial metabolism,with higher Fluorescence Index(FI=2.12)and biological index(BIX=1.35)than other river types.The artificial canal retained protein-like components(64.2%),largely attributed to winter hydrological stagnation and disturbances from shipping activities.Further analysis demonstrated that geographical settings(e.g.,mountain terrain)and anthropogenic activities(e.g.,agriculture,shipping)jointly regulated DOM composition by altering the balance between input and transformation processes.Integrated fluorescence parameters and PCA results suggested differentiated management strategies:protecting ecological integrity in mountain streams to sustain selfpurification,enhancing non-point source interception in plain rivers,and mitigating shipping pollution in canals.This study systematically reveals the natural-anthropogenic coupling mechanisms driving DOM dynamics in northern China rivers,providing critical insights for precision water environment management at the watershed scale.展开更多
A rough set based corner classification neural network, the Rough-CC4, is presented to solve document classification problems such as document representation of different document sizes, document feature selection and...A rough set based corner classification neural network, the Rough-CC4, is presented to solve document classification problems such as document representation of different document sizes, document feature selection and document feature encoding. In the Rough-CC4, the documents are described by the equivalent classes of the approximate words. By this method, the dimensions representing the documents can be reduced, which can solve the precision problems caused by the different document sizes and also blur the differences caused by the approximate words. In the Rough-CC4, a binary encoding method is introduced, through which the importance of documents relative to each equivalent class is encoded. By this encoding method, the precision of the Rough-CC4 is improved greatly and the space complexity of the Rough-CC4 is reduced. The Rough-CC4 can be used in automatic classification of documents.展开更多
To cope with the constraint problem of power consumption and transmission delay in the virtual backbone of wireless sensor network, a distributed connected dominating set （CDS） algorithm with （α,β）-constraints i...To cope with the constraint problem of power consumption and transmission delay in the virtual backbone of wireless sensor network, a distributed connected dominating set （CDS） algorithm with （α,β）-constraints is proposed. Based on the （α, β）-tree concept, a new connected dominating tree with bounded transmission delay problem（CDTT） is defined and a corresponding algorithm is designed to construct a CDT-tree which can trade off limited total power and bounded transmission delay from source to destination nodes. The CDT algorithm consists of two phases： The first phase constructs a maximum independent set（MIS）in a unit disk graph model. The second phase estimates the distance and calculates the transmission power to construct a spanning tree in an undirected graph with different weights for MST and SPF, respectively. The theoretical analysis and simulation results show that the CDT algorithm gives a correct solution to the CDTF problem and forms a virtual backbone with（ α,β）-constraints balancing the requirements of power consumption and transmission delay.展开更多
A channel allocation algorithm based on the maximum independent set is proposed to decrease network conflict and improve network performance. First, a channel allocation model is formulated and a series of the maximum...A channel allocation algorithm based on the maximum independent set is proposed to decrease network conflict and improve network performance. First, a channel allocation model is formulated and a series of the maximum independent sets （MISs） are obtained from a contention graph by the proposed approximation algorithm with low complexity. Then, a weighted contention graph is obtained using the number of contention vertices between two MISs as a weighted value. Links are allocated to channels by the weighted contention graph to minimize conflicts between independent sets. Finally, after channel allocation, each node allocates network interface cards （NICs） to links that are allocated channels according to the queue lengths of NICs. Simulations are conducted to evaluate the proposed algorithm. The results show that the proposed algorithm significantly improves the network throughput and decreases the end to end delay.展开更多
In data-driven fault diagnosis for turbo-generator sets,the fault samples are usually expensive to obtain,and inevitably with noise,which will both lead to an unsatisfying identification performance of diagnosis model...In data-driven fault diagnosis for turbo-generator sets,the fault samples are usually expensive to obtain,and inevitably with noise,which will both lead to an unsatisfying identification performance of diagnosis models.To address these issues,this paper proposes a fault diagnosis model for turbo-generator sets based on Weighted Extension Neural Network(W-ENN).WENN is a novel neural network which has three types of connection weights and an improved correlation function.The performance of the proposed model is validated against Extension Neural Network(ENN),Support Vector Machine(SVM),Relevance Vector Machine(RVM)and Extreme Learning Machine(ELM)based models.The results indicate that,on noisy small sample sets,the proposed model is superior to the other models in terms of higher identification accuracy with fewer samples and strong noise-tolerant ability.The findings of this study may serve as a powerful fault diagnosis model for turbo-generator sets on noisy small sample sets.展开更多
Abstract Recently, much attention has been paid to the reliability and vulnerability of critical infrastructure. In air traffic systems, the vulnerability analysis for airport networks can be used to guide air traffic...Abstract Recently, much attention has been paid to the reliability and vulnerability of critical infrastructure. In air traffic systems, the vulnerability analysis for airport networks can be used to guide air traffic administrations in their prioritization of the maintenance and repair of airports, as well as to avoid unnecessary disturbances in the planning of flight schedules. In this paper, the evaluation methods of airport importance and network efficiency arc established. Firstly, the evaluation indices of airport importance are proposed from both the topological and functional perspectives. The topological characteristics come from the structure of airport network and the functional features stem from the traffic flow distribution taking place inside the network. Secondly, an integrated evaluation method based on fuzzy soft set theory is proposed to identify the key airports, which can fuse together importance indices over different time intervals. Thirdly, an airport network efficiency method is established for the purpose of assessing the accuracy of the evaluation method. Finally, empirical studies using real traffic data of US and China＇s airport networks show that the evaluation method proposed in this papcr is the most accuratc. Thc vulucrability of US and China＇s airport networks is compared. The similarities and differences between airport geography distribution and airport importance distribution are discussed here and the dynamics of airport importance is studied as well.展开更多
Knowledge reduction is an important issue when dealing with huge amounts of data. And it has been proved that computing the minimal reduct of decision system is NP-complete. By introducing heuristic information into g...Knowledge reduction is an important issue when dealing with huge amounts of data. And it has been proved that computing the minimal reduct of decision system is NP-complete. By introducing heuristic information into genetic algorithm, we proposed a heuristic genetic algorithm. In the genetic algorithm, we constructed a new operator to maintaining the classification ability. The experiment shows that our algorithm is efficient and effective for minimal reduct, even for the special example that the simple heuristic algorithm can’t get the right result.展开更多
Planetary gear set is the critical component in helicopter transmission train, and an important problem in condition monitoring and health management of planetary gear set is quantitative damage detection. In order to...Planetary gear set is the critical component in helicopter transmission train, and an important problem in condition monitoring and health management of planetary gear set is quantitative damage detection. In order to resolve this problem, an approach based on physical models is presented to detect damage quantitatively in planetary gear set. A particular emphasis is put on a feature generation and selection method, which is used for sun gear tooth breakage damage detection quantitatively in planetary gear box of helicopter transmission system. In this feature generation procedure, the pure torsional dynamical models of 2K-H planetary gear set is established for healthy case and sun gear tooth-breakage case. Then, a feature based on the spectrum of simulation signals of the dynamical models is generated. Aiming at selecting the best feature suitable for quantitative damage detection, a two-sample Z-test procedure is used to analyze the performance of features on damage evolution tracing. A feature named SR, which had better performance in tracking damage, is proposed to detect damage in planetary gear set. Meanwhile, the sun gear tooth-chipped seeded experiments with different severity are designed to validate the method above, and then the test vibration signal is picked up and used for damage detection. With the results of several experiments for quantitative damage detection, the feasibility and the effect of this approach are verified. The proposed method can supply an effective tool for degradation state identification in condition monitoring and health management of helicopter transmission system.展开更多
Structural controllability is critical for operating and controlling large-scale complex networks. In real applications, for a given network, it is always desirable to have more selections for driver nodes which make ...Structural controllability is critical for operating and controlling large-scale complex networks. In real applications, for a given network, it is always desirable to have more selections for driver nodes which make the network structurally controllable. Different from the works in complex network field where structural controllability is often used to explore the emergence properties of complex networks at a macro level,in this paper, we investigate it for control design purpose at the application level and focus on describing and obtaining the solution space for all selections of driver nodes to guarantee structural controllability. In accord with practical applications,we define the complete selection rule set as the solution space which is composed of a series of selection rules expressed by intuitive algebraic forms. It explicitly indicates which nodes must be controlled and how many nodes need to be controlled in a node set and thus is particularly helpful for freely selecting driver nodes. Based on two algebraic criteria of structural controllability, we separately develop an input-connectivity algorithm and a relevancy algorithm to deduce selection rules for driver nodes. In order to reduce the computational complexity,we propose a pretreatment algorithm to reduce the scale of network's structural matrix efficiently, and a rearrangement algorithm to partition the matrix into several smaller ones. A general procedure is proposed to get the complete selection rule set for driver nodes which guarantee network's structural controllability. Simulation tests with efficiency analysis of the proposed algorithms are given and the result of applying the proposed procedure to some real networks is also shown, and these all indicate the validity of the proposed procedure.展开更多
Permanent magnet synchronous motors(PMSMs)have been widely employed in the industry. Finite-control-set model predictive control(FCS-MPC), as an advanced control scheme, has been developed and applied to improve the p...Permanent magnet synchronous motors(PMSMs)have been widely employed in the industry. Finite-control-set model predictive control(FCS-MPC), as an advanced control scheme, has been developed and applied to improve the performance and efficiency of the holistic PMSM drive systems. Based on the three elements of model predictive control, this paper provides an overview of the superiority of the FCS-MPC control scheme and its shortcomings in current applications. The problems of parameter mismatch, computational burden, and unfixed switching frequency are summarized. Moreover, other performance improvement schemes, such as the multi-vector application strategy, delay compensation scheme, and weight factor adjustment, are reviewed. Finally, future trends in this field is discussed, and several promising research topics are highlighted.展开更多
In order to increase the efficiency and decrease the cost of machinerydiagnosis, a hybrid system of computational intelligence methods is presented. Firstly, thecontinuous attributes in diagnosis decision system are d...In order to increase the efficiency and decrease the cost of machinerydiagnosis, a hybrid system of computational intelligence methods is presented. Firstly, thecontinuous attributes in diagnosis decision system are discretized with the self-organizing map(SOM) neural network. Then, dynamic reducts are computed based on rough set method, and the keyconditions for diagnosis are found according to the maximum cluster ratio. Lastly, according to theoptimal reduct, the adaptive neuro-fuzzy inference system (ANFIS) is designed for faultidentification. The diagnosis of a diesel verifies the feasibility of engineering applications.展开更多
Set-nets are common alongshore fishing gear used in Haizhou Bay, which rely on flow to catch fish. The catch per unit effort(CPUE) of set-net is affected by spatial-temporal and environmental factors but no research h...Set-nets are common alongshore fishing gear used in Haizhou Bay, which rely on flow to catch fish. The catch per unit effort(CPUE) of set-net is affected by spatial-temporal and environmental factors but no research has been conducted on this subject. In this study, we used generalized additive models(GAMs) to explore the influence of spatial-temporal and environmental factors on CPUEs of species aggregated, small yellow croaker(Larimichthys polyactis), and octopus(Octopus variabilis) based on logbooks investigations conducted at 4 stations in an alongshore area of Haizhou Bay from 2011 to 2012. The results showed that all CPUEs exhibited significant spatial-temporal differences at various scales. Aggregated CPUE was high when the sea surface temperature(SST) was 15-18℃ and 20-23℃, which was mainly determined by life history traits of the octopus and small yellow croaker(optimal SSTs 14-17℃ and 19-24℃, respectively). Chlorophyll-a concentration had significant influences on the aggregated, small yellow croaker and octopus CPUEs at optimal ranges of 3.8-6.2 mg m^(-3), 4.2-4.8 mg m^(-3) and 4.5-5.5 mg m^(-3), respectively. Flow through the net had positive relationships with CPUEs. The approximate logarithmic trends in regression curves had a critical point of 2.5 Mm^3 d^(-1), which was the dividing point that differentiated whether the major factor affecting CPUEs was the flow velocity or the fishery resource. Our results from this study will help guide fishery production and improve catch rate of set-net fishing in Haizhou Bay.展开更多
A fuzzy set-based evaluation approach is demonstrated to assess the security risks for internet-banking System. The Internet-banking system is semi-formally described using Unified Modeling Language （UML） to specify...A fuzzy set-based evaluation approach is demonstrated to assess the security risks for internet-banking System. The Internet-banking system is semi-formally described using Unified Modeling Language （UML） to specify the behavior and state of the system on the base of analyzing the existing qualitative risk assessment methods. And a quantitative method based on fuzzy set is used to measure security risks of the system, A case study was performed on the WEB server of the Internet-banking System using fuzzy-set based assessment algorithm to quantitatively compute the security risk severity. The numeric result also provides a method to decide the most critical component which should amuse the system administrator enough attention to take the appropriate security measure or controls to alleviate the risk severity. The experiments show this method can be used to quantify the security properties for the Internet-banking System in practice.展开更多
文摘The Edikan Mine,which consists of Fobinso and Esuajah gold deposits,lies within the Asankrangwa Gold Belt of the Birimian Supergroup in the Kumasi Basin.The metasedimentary rocks in the Basins and the faulted metavolcanic rocks in the Belts that make up the Birimian Supergroup were intruded by granitoids during the Eburnean Orogeny.This research aims to classify granitoids in the Edikan Mine and ascertain the petrogenetic and geochemical characteristics of some auriferous granitoids in the wider Kumasi Basin,Ghana,to understand the implications for geodynamic settings.A multi-methods approach involving field studies,petrographic studies,and whole-rock geochemical analysis was used to achieve the goal of the study.Petrographic studies revealed a relatively high abundance of plagioclase and a low percentage of K-feldspars(anorthoclase and orthoclase)in the Fobinso samples,suggesting that the samples are granodioritic in nature,while the Esuajah samples showed relatively low plagioclase abundance and a high percentage in K-feldspars,indicating that they are granitic.The granitoids from the study areas are co-magmatic.The granitoids in Esuajah and Fobinso are generally enriched in large ion lithophile elements and light rare earth elements than high field strength elements,middle rare earth elements,and heavy rare earth elements,indicating mixing with crustal sources during the evolution of the granitoids.The granitoids were tectonically formed in a syn-collisional+VAG setting,which implies that they were formed in the subduction zone setting.Fobinso granodiorites showed S-type signatures with evidence of extensive crustal contamination,while the Esuajah granites showed I-type signatures with little or no crustal contamination and are peraluminous.Gold mineralization in the study area is structurally and lithologically controlled with shear zones,faulting,and veining as the principal structures controlling the mineralization.The late-stage vein,V3,in the Edikan Mine is characterized by a low vein angle and is mineralized.
基金Supported by National Natural Science Foundation of China(Grant Nos.52261044,51969001)the Guangxi Provincial Science and Technology Major Project(Grant No.Guike AA23062037)Research Foundation Ability Enhancement Project for Young and Middle Aged Teachers in Guangxi Universities of China(Grant No.2024KY0441)。
文摘Owing to process conditions such as uneven clearance of base metal assembly and welding deformation,it is difficult to obtain well-formed structural welds with robot constant specification parameters welding.Determining how to extract a structured,anti-interference,concise,and dynamic knowledge model from measurable data,and then adjust the welding parameters with corresponding control methods in real time is a central problem to be solved in welding formation control.Hence,this paper proposes a welding penetration control method based on a Neighborhood Rough Set-Adaptive Neuro-Fuzzy Inference System(NRS-ANFIS)to achieve effective penetration control for the GMAW welding process.In orthogonal experiments,the NRS algorithm,which is based on visual sensing to obtain the properties of the weld pool and gap changes,is used to reduce the established frontal weld pool feature information decision table,and the minimum feature set of the weld pool tail width WTand the tail area coefficient CTSis obtained.The minimum feature set of the effective frontal weld pool,real-time line laser distance change,and real-time current information are used as the input for the ANFIS control system.The experimental results for the two groups of time-varying gaps demonstrate that under the condition of no preheating of the base metal,the complete welding penetration rate of the adjusted welding process parameters output by the trained ANFIS model reaches 87%,and the backside melting width is uniform and consistent,which meets the welding specification requirements.
基金supported by the National Natural Science Foundation of China(12471416,12171124,12301567)the Heilongjiang Provincial Natural Science Foundation of China(PL2024F015)+2 种基金the Postdoctoral Science Foundation of Heilongjiang Province of China(LBH-Z22199)the Fundamental Research Foun-dation for Universities of Heilongjiang Province of China(2022-KYYWF-0141)the Alexander von Humboldt Foundation of Germany.
文摘Dear Editor,This letter deals with the distributed recursive set-membership filtering(DRSMF)issue for state-saturated systems under encryption-decryption mechanism.To guarantee the data security,the encryption-decryption mechanism is considered in the signal transmission process.Specifically,a novel DRSMF scheme is developed such that,for both state saturation and encryption-decryption mechanism,the filtering error(FE)is limited to the ellipsoid domain.Then,the filtering error constraint matrix(FECM)is computed and a desirable filter gain is derived by minimizing the FECM.Besides,the bound-edness evaluation of the FECM is provided.
基金supported by the National Natural Science Foundation(42472325)the Fundamental Research Funds of Chinese Academy of Geological Science(SK202103).
文摘To elucidate the geographical differentiation characteristics and driving mechanisms of Dissolved Organic Matter(DOM)in typical rivers,this study conducted a multi-spectral investigation on three representative river types within Shandong Province:The mountainous Dawen River,the plain Tuhai River,and the artificial East Grand Canal.The DOM composition was analyzed using Ultraviolet-Visible(UV-Vis)absorption spectroscopy,Excitation-Emission Matrix(EEM)fluorescence spectroscopy,and parallel factor analysis(PARAFAC),while Principal Component Analysis(PCA)was employed to quantify the synergistic effects of natural processes and anthropogenic activities.Results revealed significant spatial heterogeneity in DOM composition and sources.The plain river exhibited the highest aromaticity(humic-like components:43.3%)due to long-term agricultural non-point source inputs and urban wastewater discharge.The mountain stream,shaped by complex terrain and relatively intact ecosystems,was dominated by autochthonous DOM derived from microbial metabolism,with higher Fluorescence Index(FI=2.12)and biological index(BIX=1.35)than other river types.The artificial canal retained protein-like components(64.2%),largely attributed to winter hydrological stagnation and disturbances from shipping activities.Further analysis demonstrated that geographical settings(e.g.,mountain terrain)and anthropogenic activities(e.g.,agriculture,shipping)jointly regulated DOM composition by altering the balance between input and transformation processes.Integrated fluorescence parameters and PCA results suggested differentiated management strategies:protecting ecological integrity in mountain streams to sustain selfpurification,enhancing non-point source interception in plain rivers,and mitigating shipping pollution in canals.This study systematically reveals the natural-anthropogenic coupling mechanisms driving DOM dynamics in northern China rivers,providing critical insights for precision water environment management at the watershed scale.
基金The National Natural Science Foundation of China(No.60503020,60373066,60403016,60425206),the Natural Science Foundation of Jiangsu Higher Education Institutions ( No.04KJB520096),the Doctoral Foundation of Nanjing University of Posts and Telecommunication (No.0302).
文摘A rough set based corner classification neural network, the Rough-CC4, is presented to solve document classification problems such as document representation of different document sizes, document feature selection and document feature encoding. In the Rough-CC4, the documents are described by the equivalent classes of the approximate words. By this method, the dimensions representing the documents can be reduced, which can solve the precision problems caused by the different document sizes and also blur the differences caused by the approximate words. In the Rough-CC4, a binary encoding method is introduced, through which the importance of documents relative to each equivalent class is encoded. By this encoding method, the precision of the Rough-CC4 is improved greatly and the space complexity of the Rough-CC4 is reduced. The Rough-CC4 can be used in automatic classification of documents.
基金Major Program of the National Natural Science Foundation of China (No.70533050)High Technology Research Program ofJiangsu Province(No.BG2007012)+1 种基金China Postdoctoral Science Foundation(No.20070411065)Science Foundation of China University of Mining andTechnology(No.OC080303)
文摘To cope with the constraint problem of power consumption and transmission delay in the virtual backbone of wireless sensor network, a distributed connected dominating set （CDS） algorithm with （α,β）-constraints is proposed. Based on the （α, β）-tree concept, a new connected dominating tree with bounded transmission delay problem（CDTT） is defined and a corresponding algorithm is designed to construct a CDT-tree which can trade off limited total power and bounded transmission delay from source to destination nodes. The CDT algorithm consists of two phases： The first phase constructs a maximum independent set（MIS）in a unit disk graph model. The second phase estimates the distance and calculates the transmission power to construct a spanning tree in an undirected graph with different weights for MST and SPF, respectively. The theoretical analysis and simulation results show that the CDT algorithm gives a correct solution to the CDTF problem and forms a virtual backbone with（ α,β）-constraints balancing the requirements of power consumption and transmission delay.
基金The National High Technology Research and Development Program of China(863 Program)(No.2013AA013601)Prospective Research Project on Future Netw orks of Jiangsu Future Netw orks Innovation Institute(No.BY2013095-1-18)
文摘A channel allocation algorithm based on the maximum independent set is proposed to decrease network conflict and improve network performance. First, a channel allocation model is formulated and a series of the maximum independent sets （MISs） are obtained from a contention graph by the proposed approximation algorithm with low complexity. Then, a weighted contention graph is obtained using the number of contention vertices between two MISs as a weighted value. Links are allocated to channels by the weighted contention graph to minimize conflicts between independent sets. Finally, after channel allocation, each node allocates network interface cards （NICs） to links that are allocated channels according to the queue lengths of NICs. Simulations are conducted to evaluate the proposed algorithm. The results show that the proposed algorithm significantly improves the network throughput and decreases the end to end delay.
基金the National Natural Science Foundation of China(No.51775272,No.51005114)The Fundamental Research Funds for the Central Universities,China(No.NS2014050)。
文摘In data-driven fault diagnosis for turbo-generator sets,the fault samples are usually expensive to obtain,and inevitably with noise,which will both lead to an unsatisfying identification performance of diagnosis models.To address these issues,this paper proposes a fault diagnosis model for turbo-generator sets based on Weighted Extension Neural Network(W-ENN).WENN is a novel neural network which has three types of connection weights and an improved correlation function.The performance of the proposed model is validated against Extension Neural Network(ENN),Support Vector Machine(SVM),Relevance Vector Machine(RVM)and Extreme Learning Machine(ELM)based models.The results indicate that,on noisy small sample sets,the proposed model is superior to the other models in terms of higher identification accuracy with fewer samples and strong noise-tolerant ability.The findings of this study may serve as a powerful fault diagnosis model for turbo-generator sets on noisy small sample sets.
基金co-supported by the National Natural Science Foundation of China(No.61039001)the Scientific Research Foundation of Civil Aviation University of China(No.2014QD01S)
文摘Abstract Recently, much attention has been paid to the reliability and vulnerability of critical infrastructure. In air traffic systems, the vulnerability analysis for airport networks can be used to guide air traffic administrations in their prioritization of the maintenance and repair of airports, as well as to avoid unnecessary disturbances in the planning of flight schedules. In this paper, the evaluation methods of airport importance and network efficiency arc established. Firstly, the evaluation indices of airport importance are proposed from both the topological and functional perspectives. The topological characteristics come from the structure of airport network and the functional features stem from the traffic flow distribution taking place inside the network. Secondly, an integrated evaluation method based on fuzzy soft set theory is proposed to identify the key airports, which can fuse together importance indices over different time intervals. Thirdly, an airport network efficiency method is established for the purpose of assessing the accuracy of the evaluation method. Finally, empirical studies using real traffic data of US and China＇s airport networks show that the evaluation method proposed in this papcr is the most accuratc. Thc vulucrability of US and China＇s airport networks is compared. The similarities and differences between airport geography distribution and airport importance distribution are discussed here and the dynamics of airport importance is studied as well.
文摘Knowledge reduction is an important issue when dealing with huge amounts of data. And it has been proved that computing the minimal reduct of decision system is NP-complete. By introducing heuristic information into genetic algorithm, we proposed a heuristic genetic algorithm. In the genetic algorithm, we constructed a new operator to maintaining the classification ability. The experiment shows that our algorithm is efficient and effective for minimal reduct, even for the special example that the simple heuristic algorithm can’t get the right result.
基金supported by National Natural Science Foundation of China (Grant No. 50905183)
文摘Planetary gear set is the critical component in helicopter transmission train, and an important problem in condition monitoring and health management of planetary gear set is quantitative damage detection. In order to resolve this problem, an approach based on physical models is presented to detect damage quantitatively in planetary gear set. A particular emphasis is put on a feature generation and selection method, which is used for sun gear tooth breakage damage detection quantitatively in planetary gear box of helicopter transmission system. In this feature generation procedure, the pure torsional dynamical models of 2K-H planetary gear set is established for healthy case and sun gear tooth-breakage case. Then, a feature based on the spectrum of simulation signals of the dynamical models is generated. Aiming at selecting the best feature suitable for quantitative damage detection, a two-sample Z-test procedure is used to analyze the performance of features on damage evolution tracing. A feature named SR, which had better performance in tracking damage, is proposed to detect damage in planetary gear set. Meanwhile, the sun gear tooth-chipped seeded experiments with different severity are designed to validate the method above, and then the test vibration signal is picked up and used for damage detection. With the results of several experiments for quantitative damage detection, the feasibility and the effect of this approach are verified. The proposed method can supply an effective tool for degradation state identification in condition monitoring and health management of helicopter transmission system.
基金supported by the National Science Foundation of China(61333009,61473317,61433002,61521063,61590924,61673366)the National High Technology Research and Development Program of China(2015AA043102)
文摘Structural controllability is critical for operating and controlling large-scale complex networks. In real applications, for a given network, it is always desirable to have more selections for driver nodes which make the network structurally controllable. Different from the works in complex network field where structural controllability is often used to explore the emergence properties of complex networks at a macro level,in this paper, we investigate it for control design purpose at the application level and focus on describing and obtaining the solution space for all selections of driver nodes to guarantee structural controllability. In accord with practical applications,we define the complete selection rule set as the solution space which is composed of a series of selection rules expressed by intuitive algebraic forms. It explicitly indicates which nodes must be controlled and how many nodes need to be controlled in a node set and thus is particularly helpful for freely selecting driver nodes. Based on two algebraic criteria of structural controllability, we separately develop an input-connectivity algorithm and a relevancy algorithm to deduce selection rules for driver nodes. In order to reduce the computational complexity,we propose a pretreatment algorithm to reduce the scale of network's structural matrix efficiently, and a rearrangement algorithm to partition the matrix into several smaller ones. A general procedure is proposed to get the complete selection rule set for driver nodes which guarantee network's structural controllability. Simulation tests with efficiency analysis of the proposed algorithms are given and the result of applying the proposed procedure to some real networks is also shown, and these all indicate the validity of the proposed procedure.
基金supported in part by the National Natural Science Foundation of China(51875261)the Postgraduate Research and Practice Innovation Program of Jiangsu Province(KYCX21_3331)+1 种基金the Faculty of Agricultural Equipment of Jiangsu University(NZXB20210103)。
文摘Permanent magnet synchronous motors(PMSMs)have been widely employed in the industry. Finite-control-set model predictive control(FCS-MPC), as an advanced control scheme, has been developed and applied to improve the performance and efficiency of the holistic PMSM drive systems. Based on the three elements of model predictive control, this paper provides an overview of the superiority of the FCS-MPC control scheme and its shortcomings in current applications. The problems of parameter mismatch, computational burden, and unfixed switching frequency are summarized. Moreover, other performance improvement schemes, such as the multi-vector application strategy, delay compensation scheme, and weight factor adjustment, are reviewed. Finally, future trends in this field is discussed, and several promising research topics are highlighted.
文摘In order to increase the efficiency and decrease the cost of machinerydiagnosis, a hybrid system of computational intelligence methods is presented. Firstly, thecontinuous attributes in diagnosis decision system are discretized with the self-organizing map(SOM) neural network. Then, dynamic reducts are computed based on rough set method, and the keyconditions for diagnosis are found according to the maximum cluster ratio. Lastly, according to theoptimal reduct, the adaptive neuro-fuzzy inference system (ANFIS) is designed for faultidentification. The diagnosis of a diesel verifies the feasibility of engineering applications.
基金funded through the Special Fund for Agro-Scientific Research in the Public Interestthe Special Public Welfare Industry (agriculture) Research-Research and Demonstration of Fisheries Fishing Technology and Fishing Gear (No. 201203018)the National Natural Science Foundation of China (No. 31402350)
文摘Set-nets are common alongshore fishing gear used in Haizhou Bay, which rely on flow to catch fish. The catch per unit effort(CPUE) of set-net is affected by spatial-temporal and environmental factors but no research has been conducted on this subject. In this study, we used generalized additive models(GAMs) to explore the influence of spatial-temporal and environmental factors on CPUEs of species aggregated, small yellow croaker(Larimichthys polyactis), and octopus(Octopus variabilis) based on logbooks investigations conducted at 4 stations in an alongshore area of Haizhou Bay from 2011 to 2012. The results showed that all CPUEs exhibited significant spatial-temporal differences at various scales. Aggregated CPUE was high when the sea surface temperature(SST) was 15-18℃ and 20-23℃, which was mainly determined by life history traits of the octopus and small yellow croaker(optimal SSTs 14-17℃ and 19-24℃, respectively). Chlorophyll-a concentration had significant influences on the aggregated, small yellow croaker and octopus CPUEs at optimal ranges of 3.8-6.2 mg m^(-3), 4.2-4.8 mg m^(-3) and 4.5-5.5 mg m^(-3), respectively. Flow through the net had positive relationships with CPUEs. The approximate logarithmic trends in regression curves had a critical point of 2.5 Mm^3 d^(-1), which was the dividing point that differentiated whether the major factor affecting CPUEs was the flow velocity or the fishery resource. Our results from this study will help guide fishery production and improve catch rate of set-net fishing in Haizhou Bay.
基金Supported by the National Natural Science Foun-dation of China (2002AA142150)
文摘A fuzzy set-based evaluation approach is demonstrated to assess the security risks for internet-banking System. The Internet-banking system is semi-formally described using Unified Modeling Language （UML） to specify the behavior and state of the system on the base of analyzing the existing qualitative risk assessment methods. And a quantitative method based on fuzzy set is used to measure security risks of the system, A case study was performed on the WEB server of the Internet-banking System using fuzzy-set based assessment algorithm to quantitatively compute the security risk severity. The numeric result also provides a method to decide the most critical component which should amuse the system administrator enough attention to take the appropriate security measure or controls to alleviate the risk severity. The experiments show this method can be used to quantify the security properties for the Internet-banking System in practice.
