A related degree-based frequent pattern mining algorithm for railway fault data

It is of great significance to improve the efficiency of railway production and operation by realizing the fault knowledge association through the efficient data mining algorithm.However,high utility quantitative frequent pattern mining algorithms in the field of data mining still suffer from the problems of low time-memory performance and are not easy to scale up.In the context of such needs,we propose a related degree-based frequent pattern mining algorithm,named Related High Utility Quantitative Item set Mining(RHUQI-Miner),to enable the effective mining of railway fault data.The algorithm constructs the item-related degree structure of fault data and gives a pruning optimization strategy to find frequent patterns with higher related degrees,reducing redundancy and invalid frequent patterns.Subsequently,it uses the fixed pattern length strategy to modify the utility information of the item in the mining process so that the algorithm can control the length of the output frequent pattern according to the actual data situation and further improve the performance and practicability of the algorithm.The experimental results on the real fault dataset show that RHUQI-Miner can effectively reduce the time and memory consumption in the mining process,thus providing data support for differentiated and precise maintenance strategies.

Influence of relative compaction and degree of saturation on the deformation characteristics of bentonite under freeze-thaw cycles

Bentonite,consisting of clay minerals of the montmorillonite group,has been widely used as an adsorbent and backfill material in nuclear waste disposal and groundwater remediation.It is challenging to use bentonite as a filling material in cold regions since bentonite is highly sensitive to thermal environmental changes,during which its bulk volume and microstructure change significantly.In this study,a series of one-dimensional and three-dimensional freeze-thaw tests were carried out within a closed system to investigate the influencing factors of the deformation of bentonite under freeze-thaw cycles.Results show that the initial soil water content greatly impacts bentonite's deformation during freeze-thaw cycles.For an initial higher degree of saturation(Sr),the expansion caused by the formation of ice lenses has a greater impact than the shrinkage induced by dehydration,ice-cementation,and so on.Conversely,bentonite tends to shrink at a lower degree of saturation during freezing.And the critical degree of saturation that determines bentonite's behavior of frost heave or frost shrinkage seems to be roughly 0.8.As the number of freeze-thaw cycles rises,initially uncompacted bentonite clay becomes more compacted,and initially compacted bentonite clay remains unchanged.

Severity of the metabolic syndrome as a predictor of prediabetes and type 2 diabetes in first degree relatives of type 2 diabetic patients:A 15-year prospective cohort study

BACKGROUND Type 2 diabetes mellitus(T2DM)has high morbidity and mortality worldwide,therefore there is of paramount importance to identify the risk factors in the populations at risk early in the course of illness.A strong correlation between severity of metabolic syndrome(MetS)and HbA1c,fasting insulin and insulin resistance has been reported.Accordingly,the MetS severity score(or MestS Zscore)can potentially be used to predict the risk of T2DM progression over time.AIM To evaluate the association the of MestS Z-score in first degree relatives(FDRs)of T2DM with the risk of prediabetes and type 2 diabetes in future.METHODS A prospective open cohort study was conducted between 2003-2018.At baseline,the sample comprised of 1766 FDRs of patients with T2DM who had a normal glucose tolerance test.Relative risk(RR)and 95%confidence interval were calculated based on logistic regression.The receiver-operator characteristic analysis and area under the curve based on MetS Z-score were used to evaluate the risk of prediabetes and diabetes among the FDR population.RESULTS Baseline MetS Z-scores were associated with the its latest values(P<0.0001).Compared with individuals who were T2DM free at the end of follow up,those who developed T2DM had higher MetS Z-score at baseline(P<0.001).In multivariable logistic regression analyses for every unit elevation in MetS Z-score at the baseline,the RR for developing future T2DM and prediabetes was(RR=1.94,RR=3.84),(RR=1.5,RR=2.17)in total population and female group,respectively(P<0.05).The associations remained significant after adjusting the potential confounding variables.A cut off value of 0.97 and 0.94 was defined in the receiver-operator characteristic curve based on the MetS Z-score for differentiating female patients with diabetes and prediabetes from the normal population,respectively.CONCLUSION The MetS Z-score was associated with an increased risk of future T2DM.Appropriate interventions at earlier stages for preventing and attenuating MetS effects may be considered as an effective strategy for FDR as at-risk population.

Study on Complex System Evaluation Method Based on PCA and Grey Relative Degree

The complexity and limited data samples in evaluation of complex system are obstacles for traditional evaluation method. Based on Grey relative degree theory and principal components analysis (PCA) method, a novel systemic evaluation method is put forward in this paper. Firstly, standardization method is modified for evaluation objective, and the method includes expression (2) and (3). Secondly, for few schemes of complex system, grey relative degree, expression (5), is substituted for relation coefficient. At last, validity of the method is verified by evaluating 3 schemes of a type of UUV.

Multi-attribute decision making model based on optimal membership and relative entropy

To study the problems of multi-attribute decision making in which the attribute values are given in the form of linguistic fuzzy numbers and the information of attribute weights are incomplete, a new multi-attribute decision making model is presented based on the optimal membership and the relative entropy. Firstly, the definitions of the optimal membership and the relative entropy are given. Secondly, for all alternatives, a set of preference weight vectors are obtained by solving a set of linear programming models whose goals axe all to maximize the optimal membership. Thirdly, a relative entropy model is established to aggregate the preference weight vectors, thus an optimal weight vector is determined. Based on this optimal weight vector, the algorithm of deviation degree minimization is proposed to rank all the alternatives. Finally, a decision making example is given to demonstrate the feasibility and rationality of this new model.

Residential Electricity Consumption Behavior Mining Based on System Cluster and Grey Relational Degree

In order to improve the utilization of the residential electricity consumption data which contains the information on the user’s electricity consumption habits, a residential electricity consumption behaviors mining algorithm model is constructed. Firstly, according to the attribute, the collected data can be divided into the global data and the phase data, then the appropriate global variables are selected to mine the user’s electricity consumption patterns in the near future on the system clustering algorithm. Based on the theory of grey relational analysis, combing phase data with the power modes to analyze the potential characteristics of residential electricity consumption behaviors deeply that verify the ability of latest power mode to predict household electricity consumption situation in the coming few days and the effect of dominant phase variables on the peak load shifting. Finally, from the actual data of a certain family, the proposed data mining algorithm is testified that it can effectively explore the electricity consumption behavior habits and characteristics of the family.

Correlative Analysis of Yanbian’s Primary Forestry Industry and Sub-industries

By selecting three indicators(timber cultivating and planting,timber harvesting,forest products),this paper uses grey relational degree to analyze the correlation between Yanbian’s primary forestry industry and sub-industries. Results show that there is a decline in the relational degree of three indicators concerning Yanbian’s primary forestry industry,but the relational degree of timber harvesting is still high and the relational degree of forest products is slightly increased.

Relative Ecological Value of Major Plants in Minqin Desert Area

This paper analyzed relative ecological value of several major plants in Minqin desert grassland using layered projection of plant canopy. The results showed that ecological functions of natural Nitraria tangutorum and Ephedra sinica woods of a unit area were much better than those of artifi cial Haloxylon ammodendron woods, relative ecological value of N. tangutorum, E. sinica and Artemisia desertorum were much higher than that of artifi cial H. ammodendron woods. Layered projection explains clearly the ecological functions and relative ecological value of desert vegetation of the same coverage. It is inaccurate to indicate wind prevention and sand fi xation of desert vegetation in deserts using ecological function service value and ecological niche calculated on the basis of two-dimensional vegetation coverage, but three-dimensional projection degree should be applied to indicate ecological functions and relative ecological value of vegetation. Application of layered projection of plants in calculating ecological functions and relative ecological value of desert plants(vegetation) is the innovation point of this research.

A solution using only electromagnetic coils for relative pose control in satellite docking

This paper proposes an electromagnetic coil topology and its control strategy,which can be incorporated into the electromagnetic docking device to achieve relative pose control in satellite docking.The target satellite has a main coil;the chaser satellite possesses a main coil of the same size accompanied by six and four evenly arranged secondary coils inside and outside the main coil,respectively.The coil on the target satellite is DC energized,while the currents in the coils of the chaser satellite are regulated.To remove the coupling between the pitch/yaw torque and translational force,the internal and external secondary coils of the chaser satellite interact with the main coil of the target satellite to perform the control of relative pitch/yaw and relative translation,respectively,so relative pose control can be achieved.The torque and force vectors exerted by the secondary coils of the chaser satellite are synthesized onto the pitch and yaw axes of the body frame.According to their spatial composition relationship,the formulas are proposed,which obtain the magnetic moment vectors of the coils from the set torques and forces.The controllers regulating pitch/yaw,translation,and distance utilize a three-loop cascaded structure that consists of an outer position loop,a middle velocity loop and an inner current loop.The control strategy is verified by dynamics simulation.

Comprehensive security risk factor identification for small reservoirs with heterogeneous data based on grey relational analysis model

Identification of security risk factors for small reservoirs is the basis for implementation of early warning systems.The manner of identification of the factors for small reservoirs is of practical significance when data are incomplete.The existing grey relational models have some disadvantages in measuring the correlation between categorical data sequences.To this end,this paper introduces a new grey relational model to analyze heterogeneous data.In this study,a set of security risk factors for small reservoirs was first constructed based on theoretical analysis,and heterogeneous data of these factors were recorded as sequences.The sequences were regarded as random variables,and the information entropy and conditional entropy between sequences were measured to analyze the relational degree between risk factors.Then,a new grey relational analysis model for heterogeneous data was constructed,and a comprehensive security risk factor identification method was developed.A case study of small reservoirs in Guangxi Zhuang Autonomous Region in China shows that the model constructed in this study is applicable to security risk factor identification for small reservoirs with heterogeneous and sparse data.

Interactive group decision making procedure based on uncertain multiplicative linguistic preference relations

Group decision making problems are investigated with uncertain multiplicative linguistic preference relations.An unbalanced multiplicative linguistic label set is introduced,which can be used by the experts to express their linguistic preference information over alternatives.The uncertain linguistic weighted geometric mean operator is utilized to aggregate all the individual uncertain multiplicative linguistic preference relations into a collective one,and then a simple approach is developed to determine the experts＇ weights by utilizing the consensus degrees among the individual uncertain multiplicative linguistic preference relations and the collective uncertain multiplicative linguistic preference relations.Furthermore,a practical interactive procedure for group decision making is proposed based on uncertain multiplicative linguistic preference relations,in which a possibility degree formula and a complementary matrix are used to rank the given alternatives.Finally,the proposed procedure is applied to solve the group decision making problem of a manufacturing company searching the best global supplier for one of its most critical parts used in assembling process.

Grey information coverage interaction relational decision making and its application

This study aims to reflect the information coverage grey number and the interaction between attributes in grey relational decision making. Therefore, a multi-attribute decision method based on the grey information coverage interaction relational degree(GIRD) is proposed. Firstly, this paper defines the information coverage grey number, and establishes the GIRD model by using the Choquet fuzzy integral and grey relational principle. It proves that the proposed model not only is the general and unified form of the point relational degree, interval relational degree, mixed relational degree and grey fuzzy integral relational degree, but also can effectively deal with the interaction between attributes. Further,a decision making example of evaluating the industrial operation quality for 14 cities in Hunan province of China is provided to highlight the implementation, availability, and feasibility of the proposed decision model.

The Evaluation on Ecological Agricultural Development in Sichuan Province on the Basis of Grey Relational Analysis

By using the grey relational model,14 indexes of ecological agricultural development in Sichuan Province from 1997 to 2008 are analyzed.According to the relational degree results,the ecological agricultural development in 12 years can be divided into three stages:the first stage is from 1997 to 2000,with the shape of inverted U;the second stage is from 2001 to 2004,belonging to transition stage with slow growth rate;the third stage is from 2005 to 2008,belonging to the stage of rapid growth.It draws conclusion that per capita grain yield is an important element for evaluating ecological agricultural construction.Besides,reducing the energy consumption of per unit production,improving labor productivity and increasing agricultural science and technology application and input on agricultural infrastructure construction are the engine for developing Sichuan ecological agriculture.

Formula for calculating spatial similarity degrees between point clouds on multi-scale maps taking map scale change as the only independent variable

The degree of spatial similarity plays an important role in map generalization, yet there has been no quantitative research into it. To fill this gap, this study first defines map scale change and spatial similarity degree/relation in multi-scale map spaces and then proposes a model for calculating the degree of spatial similarity between a point cloud at one scale and its gener- alized counterpart at another scale. After validation, the new model features 16 points with map scale change as the x coordinate and the degree of spatial similarity as the y coordinate. Finally, using an application for curve fitting, the model achieves an empirical formula that can calculate the degree of spatial similarity using map scale change as the sole independent variable, and vice versa. This formula can be used to automate algorithms for point feature generalization and to determine when to terminate them during the generalization.

Pore Size Distribution and Its Quantitative Relationship with Strength of Corundum Based Castables

A series of corundum based castables with 0,2%,4%,6%,and 8% α-Al2O3 micropowders were prepared using tabular alumina aggregates （6-3,3-1 and ≤1 mm） and fines （≤0.088 and ≤0.045 mm）,calcium aluminate cement,and α-Al2O3 micropowders （d50=1.754 μm） as starting materials. Cold mechanical strength and pore size distribution of the castables specimens after heat treatment at 110,1 100 and 1 500 ℃ were tested,respectively. The quantitative relationship between strength and apparent porosity,and that between strength and median pore diameter were verified by Atzeni equation. The correlation between interval of pore size and mechanical strength of specimens was also studied by means of gray relational theory. The results show that：（1） the pore size distribution of castables is strongly influenced by both micropowders filling and matrix sintering; the addition of micropowders decreases median pore diameter while the sintering process increases it; （2） when adding a constant correction term,Atzeni equation can substantially describe the quantitative relationship between median pore diameter and strength of castables specimens after heat treatment at the same temperature; the significant differences of the gray relational degree between the interval of pore size and castables strength are characterized; it is also found that for the same interval of pore size,the gray relational degree isaffected by the heat treatment temperature; the pore size interval 〈0.5 μm has the highest gray relational degree with the strength at 110-1 500 ℃.

Empirical Analysis on the Relations between Rural Residents' Consumption and Economic Growth——A Case of Liaoning Province

Liaoning is a granary province with a large agricultural population and great market potential. Expanding rural residents' consumption becomes a necessity for enlarging domestic demand, solving three agriculture problems and promoting sustainable and rapid economic development. The research shows that since invigorating old industrial base in Liaoning, the contribution rate of rural residents' consumption to economic motivation is low and unstable, which has become one of the choke points for the development of economy. By using the grey correlation method, the influences of rural residents' consumption in different periods to GDP per capita are analyzed, the results show that the consumption level of rural residents were increasing, but their contribution rate on economic growth showed the descending tend. The residential expenses stay in the major position of consumption expenses; the education and entertainment products and service consumption play an important role; the growth of transportation and telecommunication is slow; the expenses on medical care are low and its contribution rate on economic growth is relatively weak. The countermeasures on developing rural economy, increasing rural residents' income, improving rural consumption environment, accelerating rural infrastructure construction, constructing and perfecting rural social security system and expanding rural consumption credit market are put forward to expand rural residents' consumption demand and realize the sustainable development of economy.

Method to determine α in rough set model based on connection degree

An improvement of tolerance relation is proposed in regard to rough set model based on connection degree by which reflexivity of relation can be assured without loss of information. Then, a method to determine optimal identity degree based on relative positive region is proposed so that the identity degree can be computed in an objective method without any preliminary or additional information about data, which is consistent with the notion of objectivity in rough set theory and data mining theory. Subsequently, an algorithm is proposed, and in two examples, the global optimum identity degree is found out. Finally, in regard to optimum connection degree, the method of rules extraction for connection degree rough set model based on generalization function is presented by which the rules extracted from a decision table are enumerated.

Exploring relations between city regions based on mobile phone data

City regions often have great diversity in form and function. To better understand the role of each region, the relations between city regions need to be carefully studied. In this work, the human mobility relations between regions of Shanghai based on mobile phone data is explored. By formulating the regions as nodes in a network and the commuting between each pair of regions as link weights, the distribution of nodes degree, and spatial structures of communities in this relation network are studied. Statistics show that regions locate in urban centers and traffic hubs have significantly larger degrees. Moreover, two kinds of spatial structures of communities are found. In most communities, nodes are spatially neighboring. However, in the communities that cover traffic hubs, nodes often locate along corridors.

Characterization of the pairwise correlations in different quantum networks consisting of four-wave mixers and beamsplitters

We investigate the performances of the pairwise correlations（PCs） in different quantum networks consisting of fourwave mixers（FWMs） and beamsplitters（BSs）. PCs with quantum correlation in different quantum networks can be verified by calculating the degree of relative intensity squeezing for any pair of all the output fields. More interestingly, the quantum correlation recovery and enhancement are present in the FWM＋BS network and the repulsion effect phenomena（signal（idler）-frequency mode cannot be quantum correlated with the other two idler（signal）-frequency modes simultaneously）between the PCs with quantum correlation are predicted in the FWM ＋ FWM and FWM ＋ FWM ＋ FWM networks. Our results presented here pave the way for the manipulation of the quantum correlation in quantum networks.