Probability Distribution of Arithmetic Average of China Aviation Network Edge Vertices Nearest Neighbor Average Degree Value and Its Evolutionary Trace Based on Complex Network

In order to reveal the complex network characteristics and evolution principle of China aviation network,the probability distribution and evolution trace of arithmetic average of edge vertices nearest neighbor average degree values of China aviation network were studied based on the statistics data of China civil aviation network in 1988,1994,2001,2008 and 2015.According to the theory and method of complex network,the network system was constructed with the city where the airport was located as the network node and the route between cities as the edge of the network.Based on the statistical data,the arithmetic averages of edge vertices nearest neighbor average degree values of China aviation network in 1988,1994,2001,2008 and 2015 were calculated.Using the probability statistical analysis method,it was found that the arithmetic average of edge vertices nearest neighbor average degree values had the probability distribution of normal function and the position parameters and scale parameters of the probability distribution had linear evolution trace.

Characteristics of Multi-Objective Linear Programming Problem and Multi-Objective Linear Fractional Programming Problem Taking Maximum Value of Multi-Objective Functions

In this paper, a new statistical averaging technique is proposed for finding an optimal solution to a multi-objective linear fractional programming problem (MOLFPP) and multi-objective linear programming problem (MOLPP) by using new arithmetic averaging method and new geometric averaging method. It is significantly noticeable same characteristics among all the technique while taking maximum or minimum among all optimized values for multi-objective functions using simplex algorithm. The characteristics provided from the problems are verified by the numerical examples.

A robust Poisson multi-Bernoulli filter for multi-target tracking based on arithmetic average fusion

The coalescence and missed detection are two key challenges in Multi-Target Tracking(MTT).To balance the tracking accuracy and real-time performance,the existing Random Finite Set(RFS)based filters are generally difficult to handle the above problems simultaneously,such as the Track-Oriented marginal Multi-Bernoulli/Poisson(TOMB/P)and Measurement-Oriented marginal Multi-Bernoulli/Poisson(MOMB/P)filters.Based on the Arithmetic Average(AA)fusion rule,this paper proposes a novel fusion framework for the Poisson Multi-Bernoulli(PMB)filter,which integrates both the advantages of the TOMB/P filter in dealing with missed detection and the advantages of the MOMB/P filter in dealing with coalescence.In order to fuse the different PMB distributions,the Bernoulli components in different Multi-Bernoulli(MB)distributions are associated with each other by Kullback-Leibler Divergence(KLD)minimization.Moreover,an adaptive AA fusion rule is designed on the basis of the exponential fusion weights,which utilizes the TOMB/P and MOMB/P updates to solve these difficulties in MTT.Finally,by comparing with the TOMB/P and MOMB/P filters,the performance of the proposed filter in terms of accuracy and efficiency is demonstrated in three challenging scenarios.

Lanchester equation for cognitive domain using hesitant fuzzy linguistic terms sets

Intelligent wars can take place not only in the physical domain and information domain but also in the cognitive domain.The cognitive domain will become the key domain to win in the future intelligent war.A Lanchester equation considering cognitive domain is proposed to fit the development tendency intelligent wars in this paper.One party is considered to obtain the exponential enhancement advantage on combat forces in combat if it can gain an advantage in the cognitive domain over the other party according to the systemic advantage function.The operational effectiveness of the cognitive domain in war is considered to consist of a series of indicators.Hesitant fuzzy sets and linguistic term sets are powerful tools when evaluating indicators,hence the indicators are scored by experts using hesitant fuzzy linguistic terms sets here.A unique hesitant fuzzy hybrid arithmetical averaging operator is used to aggregate the evaluation.

Group Decision-Making Model of Renal Cancer Surgery Options Using Entropy Fuzzy Element Aczel-Alsina Weighted Aggregation Operators under the Environment of Fuzzy Multi-Sets

Since existing selection methods of surgical treatment schemes of renal cancer patients mainly depend on physicians’clinical experience and judgments,the surgical treatment options of renal cancer patients lack their scientifical and reasonable information expression and group decision-making model for renal cancer patients.Fuzzy multi-sets(FMSs)have a number of properties,which make them suitable for expressing the uncertain information of medical diagnoses and treatments in group decision-making(GDM)problems.To choose the most appropriate surgical treatment scheme for a patient with localized renal cell carcinoma(RCC)(T1 stage kidney tumor),this article needs to develop an effective GDM model based on the fuzzy multivalued evaluation information of the renal cancer patients.First,we propose a conversionmethod of transforming FMSs into entropy fuzzy sets(EFSs)based on the mean and Shannon entropy of a fuzzy sequence in FMS to reasonably simplify the information expression and operations of FMSs and define the score function of an entropy fuzzy element(EFE)for ranking EFEs.Second,we present the Aczel-Alsina t-norm and t-conorm operations of EFEs and the EFE Aczel-Alsina weighted arithmetic averaging(EFEAAWAA)and EFE Aczel-Alsina weighted geometric averaging(EFEAAWGA)operators.Third,we develop a multicriteria GDM model of renal cancer surgery options in the setting of FMSs.Finally,the proposed GDM model is applied to two clinical cases of renal cancer patients to choose the best surgical treatment scheme for a renal cancer patient in the setting of FMSs.The selected results of two clinical cases verify the efficiency and rationality of the proposed GDM model in the setting of FMSs.

HIGH ACCURACY ARITHMETIC AVERAGE TYPE DISCRETIZATION FOR THE SOLUTION OF TWO-SPACE DIMENSIONAL NONLINEAR WAVE EQUATIONS

In this paper,we propose a new high accuracy discretization based on the ideas given by Chawla and Shivakumar for the solution of two-space dimensional nonlinear hyper-bolic partial differential equation of the form utt=A(x,y,t)uxx+B(x,y,t)uyy+g(x,y,t,u,ux,uy,ut),0<x,y<1,t>0 subject to appropriate initial and Dirichlet boundary conditions.We use only five evaluations of the function g and do not require any fictitious points to discretize the differential equation.The proposed method is directly applicable to wave equation in polar coordinates and when applied to a linear telegraphic hyperbolic equation is shown to be unconditionally stable.Numerical results are provided to illustrate the usefulness of the proposed method.

Simple Sequence Repeat Analysis of Genetic Diversity in Primary Core Collection of Peach(Prunus persica)

In this study, the genetic diversity of 51 cultivars in the primary core collection of peach （Prunus persica （L.） Batsch） was evaluated by using simple sequence repeats （SSRs）. The phylogenetic relationships and the evolutionary history among different cultivars were determined on the basis of SSR data. Twenty-two polymorphic SSR primer pairs were selected, and a total of 111 alleles were identified in the 51 cultivars, with an average of 5 alleles per locus. According to traditional Chinese classification of peach cultivars, the 51 cultivars in the peach primary core collection belong to six variety groups. The SSR analysis revealed that the levels of the genetic diversity within each variety group were ranked as Sweet peach 〉 Crisp peach 〉 Flat peach 〉 Nectarine 〉 Honey Peach 〉 Yellow fleshed peach. The genetic diversity among the Chinese cultivars was higher than that among the introduced cultivars. Cluster analysis by the unweighted pair group method with arithmetic averaging （UPGMA） placed the 51 cultivars into five linkage clusters. Cultivar members from the same variety group were distributed in different UPGMA clusters and some members from different variety groups were placed under the same cluster. Different variety groups could not be differentiated in accordance with SSR markers. The SSR analysis revealed rich genetic diversity in the peach primary core collection, representative of genetic resources of peach.

Orthopair indeterminate information expression,aggregations and multiattribute decision making method with indeterminate ranges

A neutrosophic number(NN)(d=μ+vI)can flexibly represent the indeterminate information corresponding to values/ranges of the indeterminacy I.Regarding the hybrid concept of intuitionistic fuzzy set(IFS)and NN,this study presents an orthopair indeterminate set(OIS),an orthopair indeterminate element weighted arithmetic averaging(OIEWAA)operator and an orthopair indeterminate element weighted geometric averaging(OIEWGA)operator to simplify and generalise the existing IFS and interval-valued IFS expressions and aggregation forms.Thus,a multiattribute decision making(DM)approach with indeterminate ranges of decision makers is developed based on the OIEWAA and OIEWGA operators and the score and accuracy functions of orthopair indeterminate elements in OIS setting.Finally,the proposed DM approach is applied to a multi-attribute DM example of manufacturing schemes(alternatives)in OIS setting to demonstrate the applicability and flexibility of the proposed DM approach in OIS setting.

Study on the Weakening Buffer Operators

Studying on the buffer operator, we structure the GAWBO（Geometry Average Weakening Buffer Operator）, WAWBO（Weighed Average Weakening Buffer Operator）, WGAWBO（Weighed Geometry Average Weakening Buffer Operator） and so on, which are easy to apply and be universality. At the same time, we address their characteristics and their internal relations between these buffer operators. All this effectively resolves the questions, which often come forth in modeling forecasting of disturbed data sequence by shock wave and there are some contradictions between the quantity result and the qualitative analysis.