Fuzzy polynomial regression with fuzzy neural networks

Recently, fuzzy linear regression is considered by Mosleh et al. [1]. In this paper, a novel hybrid method based on fuzzy neural network for approximate fuzzy coefficients (parameters) of fuzzy polynomial regression models with fuzzy output and crisp inputs, is presented. Here a neural network is considered as a part of a large field called neural computing or soft computing. Moreover, in order to find the approximate parameters, a simple algorithm from the cost function of the fuzzy neural network is proposed. Finally, we illustrate our approach by some numerical examples.     

Exploring express delivery networks in China based on complex network theory

Based on the complex network theory, we explore an express delivery system in China, which consists of two delivery networks, namely, the air delivery network (ADN) and the ground delivery network (GDN). Systematic structural analysis indicates that both delivery networks exhibit small‐world phenomenon, disassortative mixing behavior, and rich‐club phenomenon. However, there are significant differences between ADN and GDN in terms of degree distribution property and community structure. On the basis of the Barabási‐Albert model, we have proposed a network model incorporating the structural features of the two delivery networks to reveal their evolutionary mechanisms. Lastly, the parcel strength and the distance strength are analyzed, which, respectively, reflect the number of parcels and the long‐haul delivery distance handled by a node city. The strengths are highly heterogeneous in both delivery networks and have intense correlations with topological structures. These works are beneficial for express enterprises to construct or extend their express delivery networks, and provide some useful insights on improving parcel delivery service. © 2014 Wiley Periodicals, Inc. Complexity 21: 166–179, 2015     

Texture separation via a reference set

Patch-based de-noising algorithms and patch manifold smoothing have emerged as efficient de-noising methods. This paper provides a new insight on these methods. We show how to extend them to separate oscillatory patterns that could be entangled. A collection of particular patches, that we call reference set, is selected by the user. We define a notion of similarity relative to this reference set that is used to extend the Non-Local Means (see Buades et al., 2005) [1] and the graph-based de-noising method (see Szlam et al., 2008) [12].     

复杂网络整合分析方法在乳腺癌疾病机理研究中的应用

将乳腺癌相关基因抽象为节点,利用基因表达谱分别构建正常组织样本(C组)与乳腺癌样本(E组)的pearson、spearman、kendall、mutual information和mic等5种相关性网络,进而分析网络节点度在C组和E组中的差异性,筛选出17个结构性关键基因,其中12个基因已有文献证实与乳腺癌显著相关.它...     

Lower Bounds from State Space Relaxations for Concave Cost Network Flow Problems

In this paper we obtain Lower Bounds (LBs) to concave cost network flow problems. The LBs are derived from state space relaxations of a dynamic programming formulation, which involve the use of non-injective mapping functions guaranteing a reduction on the cardinality of the state space. The general state space relaxation procedure is extended to address problems involving transitions that go across several stages, as is the case of network flow problems. Applications for these LBs include: estimation of the quality of heuristic solutions; local search methods that use information of the LB solution structure to find initial solutions to restart the search (Fontes et al., 2003, Networks, 41, 221–228); and branch-and-bound (BB) methods having as a bounding procedure a modified version of the LB algorithm developed here, (see Fontes et al., 2005a). These LBs are iteratively improved by penalizing, in a Lagrangian fashion, customers not exactly satisfied or by performing state space modifications. Both the penalties and the state space are updated by using the subgradient method. Additional constraints are developed to improve further the LBs by reducing the searchable space. The computational results provided show that very good bounds can be obtained for concave cost network flow problems, particularly for fixed-charge problems.     

Structural balance in fully signed networks

Node attributes play an important role in shaping network structures, but are generally ignored in transformations of structural balance. A fully signed network consisting of signs of edges and nodes expresses both properties of relationship and node attributes. In this article, we generalize the definition of structural balance in fully signed networks. We transform the unbalanced fully signed network by not only changing signs of edges but also changing the signs of nodes. We propose a memetic algorithm to transform unbalanced networks at the lowest cost. Experiments show that our algorithm can solve this problem efficiently, and different node attribute assignments may lead to different optimized structures. © 2016 Wiley Periodicals, Inc. Complexity 21: 497–511, 2016     

Combinatorics on update digraphs in Boolean networks

Boolean networks have been used as models of gene regulation and other biological networks. One key element in these models is the update schedule, which indicates the order in which states have to be updated. In Aracena et al. (2009) [1], the authors define equivalence classes that relate deterministic update schedules that yield the same update digraph and thus the same dynamical behavior of the network. In this paper we study algorithmical and combinatorial aspects of update digraphs. We show a polynomial characterization of these digraphs, which enables us to characterize the corresponding equivalence classes. We prove that the update digraphs are exactly the projections, on the respective subgraphs, of a complete update digraph with the same number of vertices. Finally, the exact number of complete update digraphs is determined, which provides upper and lower bounds on the number of equivalence classes.     

Cyclic subspace codes via subspace polynomials

Subspace codes have been intensely studied in the last decade due to their application in random network coding. In particular, cyclic subspace codes are very useful subspace codes with their efficient encoding and decoding algorithms. In a recent paper, Ben-Sasson et al. gave a systematic construction of subspace codes using subspace polynomials. In this paper, we mainly generalize and improve their result so that we can obtain larger codes for fixed parameters and also we can increase the density of some possible parameters. In addition, we give some relative remarks and explicit examples.     

Curvature invariant and generalized canonical operator models – II

In Douglas et al. (2012) [9], the authors investigated a family of quotient Hilbert modules in the Cowen–Douglas class over the unit disk constructed from classical Hilbert modules such as the Hardy and Bergman modules. In this paper we extend the results to the multivariable case of higher multiplicity. Moreover, similarity as well as isomorphism results are obtained.     

An optimal solution to a three echelon supply chain network with multi-product and multi-period

Recently, Kadadevaramath et al. (2012) [1] presented a mathematical model for optimizing a three echelon supply chain network. Their model is an integer linear programming (ILP) model. In order to solve it, they developed five algorithms; four of them are based on a particle swarm optimization (PSO) method and the other is a genetic algorithm (GA). In this paper, we develop a more general mathematical model that contains the model developed by Kadadevaramath et al. (2012) [1]. Furthermore, we show that all instances proved in Kadadevaramath et al. (2012) [1] can easily be solved optimally by any integer linear programming solver.     

Modeling centrality measures in social network analysis using bi-criteria network flow optimization problems

Centrality measures play an important role in the field of network analysis. In the particular case of social networks, the flow represents the way in which information passes through the network nodes. Freeman et al. (1991) were the first authors to relate centrality measures to network flow optimization problems in terms of betweenness, closeness, and the influence of one node over another one. Such measures are single dimensional and, in general, they amalgamate several heterogeneous dimensions into a single one, which is not suitable for dealing with most real-world problems. In this paper we extend the betweenness centrality measure (or concept) to take into account explicitly several dimensions (criteria). A new closeness centrality measure is defined to deal not only with the maximum flow between every ordered pair of nodes, but also with the cost associated with communications. We shall show how the classical measures can be enhanced when the problem is modeled as a bi-criteria network flow optimization problem.     

Comments on “Interactions among different types of solitary waves in (2 + 1)-dimensional system” by Cheng-lin Bai, Cheng-jie Bai, Hong Zhao [Chaos, Solitons and Fractals 25 (2005) 481]

Starting from a quite universal formula, which is valid for some quite universal (2 + 1)-dimensional physical models, Bai et al. [Bai CL, Bai CJ, Zhao H. Chaos, Solitons & Fractals 2005;25:481] have claimed that the interactions among different types of solitary waves like peakons, dromions, and compactons are investigated both analytically and graphically. We show that all of the claims by Bai et al. are wrong since the adopted q-functions do not satisfy the differential equation. From this point of view, the interactions for peakon–antidromion, compacton–antidromion, and antipeakon–compacton say nothing of completely inelastic or not completely elastic.     

Note on: N.E. Aguilera, M.S. Escalante, G.L. Nasini, “The disjunctive procedure and blocker duality”

Aguilera et al. [Discrete Appl. Math. 121 (2002) 1–13] give a generalization of a theorem of Lehman through an extension of the disjunctive procedure defined by Balas, Ceria and Cornuéjols. This generalization can be formulated as(A) For every clutter , the disjunctive index of its set covering polyhedron coincides with the disjunctive index of the set covering polyhedron of its blocker, .In Aguilera et al. [Discrete Appl. Math. 121 (2002) 1–3], (A) is indeed a corollary of the stronger result(B) .Motivated by the work of Gerards et al. [Math. Oper. Res. 28 (2003) 884–885] we propose a simpler proof of (B) as well as an alternative proof of (A), independent of (B). Both of them are based on the relationship between the “disjunctive relaxations” obtained by and the set covering polyhedra associated with some particular minors of .     

Security of a key agreement protocol based on chaotic maps

Kacorev et al. proposed new public key encryption scheme using chaotic maps. Subsequently, Bergamo et al. has broken Kacorev and Tasev’s encryption scheme and then applied the attack on a key agreement protocol based on Kacorev et al.’s system. In order to address Bergamo et al.’ attack, Xiao et al. proposed a novel key agreement protocol. In this paper, we will present two attacks on Xiao et al.’s key agreement protocol using chaotic maps. Our new attack method is different from the one that Bergamo et al. developed. The proposed attacks work in a way that an adversary can prevent the user and the server from establishing a shared session key even though the adversary cannot get any private information from the user and the server’s communications.     

An Alternative Model for Queueing Systems with Single Arrivals,Batch Services and Customer Coalescence

In this paper we consider a queueing system with single arrivals, batch services and customer coalescence and we use it as a building block for constructing queueing networks that incorporate such characteristics. Chao et al. (1996) considered a similar model and they proved that it possesses a geometric product form stationary distribution, under the assumption that if the number of units present at a service completion epoch is less than the required number of units, then all the units coalesce into an incomplete (defective) batch which leaves the system. We drop this assumption and we study a model without incomplete batches. We prove that the stationary distribution of such a queue has a nearly geometric form. Using quasi-reversibility arguments we construct a network model with such queues which provides relevant bounds and approximations for the behaviour of assembly processes. Several issues about the validity of these bounds and approximations are also discussed.     

Complex dynamics of epidemic models on adaptive networks

There has been a substantial amount of well mixing epidemic models devoted to characterizing the observed complex phenomena (such as bistability, hysteresis, oscillations, etc.) during the transmission of many infectious diseases. A comprehensive explanation of these phenomena by epidemic models on complex networks is still lacking. In this paper we study epidemic dynamics in an adaptive network proposed by Gross et al., where the susceptibles are able to avoid contact with the infectious by rewiring their network connections. Such rewiring of the local connections changes the topology of the network, and inevitably has a profound effect on the transmission of the disease, which in turn influences the rewiring process. We rigorously prove that the adaptive epidemic model investigated in this paper exhibits degenerate Hopf bifurcation, homoclinic bifurcation and Bogdanov–Takens bifurcation. Our study shows that adaptive behaviors during an epidemic may induce complex dynamics of disease transmission, including bistability, transient and sustained oscillations, which contrast sharply to the dynamics of classical network models. Our results yield deeper insights into the interplay between topology of networks and the dynamics of disease transmission on networks.     

Network analysis: Understanding consumers' choice in the film industry and predicting pre‐released weekly box‐office revenue

Predicting weekly box‐office demand is an important yet challenging question. For theater exhibitors, such information will enhance negotiation options with distributers, and assist in planning weekly movie portfolio mix. Existing literature focuses on forecasts of pre‐released total gross revenue or on weekly predictions based on first‐weeks observations. This work adds to the literature in modeling the entire demand structure forecasts by utilizing information on movie similarity network. Specifically, we draw upon the assumption that aggregated consumers' choice in the film industry is the main key in understanding movies' demand. Therefore, similar movies, in terms of audience appeal, should yield similar demand structure. In this work, we propose an automated technique that derives measurements of demand structure. We demonstrate that our technique enables to analyze different aspects of demand structure, namely, decay rate, time of first demand peak, per‐screen gross value at peak time, existence of second demand wave, and time on screens. We deploy ideas from variable selection procedures, to investigate the prediction power of similarity network on demand dynamics. We show that not only our models perform significantly better than models that discard the similarity network but are also robust to new sets of box‐office movies. Copyright © 2016 John Wiley & Sons, Ltd.     

Notes on “stability and chaos control of regularized Prabhakar fractional dynamical systems without and with delay”

This comment is to point out some mistakes made in the paper (Shiva et al in MATH METHOD APPL SCI 42(7):2302‐2323, 2019). The stability of Prabhakar fractional dynamical systems without and with time delay is addressed. Lyapunov stability theorem is extended to these systems. But the proof process is wrong as the memory property of fractional calculus. It is necessary to point out these errors to avoid misleading. Finally, a counterexample is proposed against the proposed theorem.     

A Global Optimization Approach to a Water Distribution Network Design Problem

In this paper, we address a global optimization approach to a waterdistribution network design problem. Traditionally, a variety of localoptimization schemes have been developed for such problems, each new methoddiscovering improved solutions for some standard test problems, with noknown lower bound to test the quality of the solutions obtained. A notableexception is a recent paper by Eiger et al. (1994) who present a firstglobal optimization approach for a loop and path-based formulation of thisproblem, using a semi-infinite linear program to derive lower bounds. Incontrast, we employ an arc-based formulation that is linear except forcertain complicating head-loss constraints and develop a first globaloptimization scheme for this model. Our lower bounds are derived through thedesign of a suitable Reformulation-Linearization Technique (RLT) thatconstructs a tight linear programming relaxation for the given problem, andthis is embedded within a branch-and-bound algorithm. Convergence to anoptimal solution is induced by coordinating this process with an appropriatepartitioning scheme. Some preliminary computational experience is providedon two versions of a particular standard test problem for the literature forwhich an even further improved solution is discovered, but one that isverified for the first time to be an optimum, without any assumed boundson the flows. Two other variants of this problem are also solved exactly forillustrative purposes and to provide researchers with additional test caseshaving known optimal solutions. Suggestions on a more elaborate study involving several algorithmic enhancements are presented for futureresearch.     

An improved Benders decomposition applied to a multi-layer network design problem

Benders decomposition has been widely used for solving network design problems. In this paper, we use a branch-and-cut algorithm to improve the separation procedure of Gabrel et al. and Knippel et al. for capacitated network design. We detail experiments on bi-layer networks, comparing with Knippel’s previous results.