The performance of traditional imbalanced classification algorithms is degraded when dealing with highly imbalanced data. How to deal with highly imbalanced data is a difficult problem. In this paper, the authors propose an ensemble tree classifier for highly imbalanced data classification. The ensemble tree classifier is constructed with a complete binary tree structure. A mathematical model is established

Meca, et al. (2004) studied a class of inventory games which arise when a group of retailers who observe demand for a common good decide to cooperate and make joint orders. In this paper, the authors extend their model to the situation where the manufacturer provides the retailers with a price discount on purchases in excess of a certain order quantity. The authors define the corresponding inventory

This is an expository paper on algebraic aspects of exponential sums over finite fields. This is a new direction. Various examples, results and open problems are presented along the way, with particular emphasis on Gauss periods, Kloosterman sums and one variable exponential sums. One main tool is the applications of various p-adic methods. For this reason, the author has also included a brief exposition

This paper is concerned with the parameter estimation of deterministic autoregressive moving average (DARMA) systems with quantization data. The estimation algorithms adopted here are the least squares (LS) and the forgetting factor LS, and the signal quantizer is of uniform, that is, with uniform quantization error. The authors analyse the properties of the LS and the forgetting factor LS, and establish

This paper focuses on the leader-following consensus control problem for nonlinear multiagent systems subject to deferred asymmetric time-varying state constraints. A distributed event-triggered adaptive neural control approach is advanced. By virtue of a distributed sliding-mode estimator, the leader-following consensus control problem is converted into multiple simplified tracking control problems

This paper considers series and parallel systems comprising n components drawn from a heterogeneous population consisting of m different subpopulations. The components within each subpopulation are assumed to be dependent, while the subpopulations are independent of each other. The authors also assume that the subpopulations have different Archimedean copulas for their dependence. Under this setup

This paper discusses regression analysis of interval-censored failure time data arising from the accelerated failure time model in the presence of informative censoring. For the problem, a sieve maximum likelihood estimation approach is proposed and in the method, the copula model is employed to describe the relationship between the failure time of interest and the censoring or observation process

This paper studies the continuous-time constrained consensus of heterogeneous multi-agent networks with nonconvex input and velocity constraints, where each agent’s dynamic is modeled by a first-order or second-order integrator, the communication delays are assumed to be time-varying, nonuniform, bounded and the communication graph is changing over time. An improved distributed control algorithm with

In the case of the differential privacy under the Laplace mechanism, the asymptotic properties of parameter estimators have been derived in some special network models with common binary values, but the asymptotic properties in network models with the ordered values are lacking. In this paper, the authors release the degree sequences of the ordered networks under a general noisy mechanism with the

In this paper, the formation control problem is investigated for a team of uncertain underactuated surface vessels (USVs) based on a directed graph. Considering the risk of collision and the limited communication range of USVs, the prescribed performance control (PPC) methodology is employed to ensure collision avoidance and connectivity maintenance. An event-triggered mechanism is designed to reasonably

This paper considers a stochastic chemostat model with degenerate diffusion. Firstly, the Markov semigroup theory is used to establish sufficient criteria for the existence of a unique stable stationary distribution. The authors show that the densities of the distributions of the solutions can converge in L1 to an invariant density. Then, conditions are obtained to guarantee the washout of the microorganism

This paper investigates the state consensus of linear multi-agent systems in a graph where each agent is equipped with two novel event-triggering mechanisms. Each agent utilizes them to avoid continuous information transmissions with its neighbors and to reduce the frequencies of controller updates, respectively. One of the event-triggering mechanisms defines a threshold of state errors by a constant

Most studies of the time-reversibility are limited to a linear or an affine involution. In this paper, the authors consider the case of a quadratic involution. For a polynomial differential system with a linear part in the standard form (−y, x) in ℝ2, by using the method of regular chains in a computer algebraic system, the computational procedure for finding the necessary and sufficient conditions

This paper investigates the exponential stability of traveling wave solutions for nonlinear delayed cellular neural networks. As a continuity of the past work (Wu and Niu, 2016; Yu, et al., 2011) on the existence and uniqueness of the traveling wave solutions, it is very reasonable and interesting to consider the exponential stability of the traveling wave solutions. By the weighted energy method,

The study on how to identify influential spreaders in complex networks is becoming increasingly significant. Previous studies demonstrate that considering the shortest path length can improve the accuracy of identification, but which ignore the influence of the number of shortest paths. In many cases, even though the shortest path length of two nodes is rather larger, their interaction influence is

This paper studies the important problem of how to coordinate the capacity procurement model with asymmetric demand information. Under the model, the supplier has to secure necessary capacity before receiving a firm order from the manufacturer who possesses private demand information for her product. Optimal supply chain performance requires the manufacturer to share her forecast truthfully and the

For high-dimensional nonparametric Behrens-Fisher problem in which the data dimension is larger than the sample size, the authors propose two test statistics in which one is U-statistic Rank-based Test (URT) and another is Cauchy Combination Test (CCT). CCT is analogous to the maximum-type test, while URT takes into account the sum of squares of differences of ranked samples in different dimensions

The ratings in many user-object online rating systems can reflect whether users like or dislike the objects, and in some online rating systems, users can directly choose whether to like an object. So these systems can be represented by signed bipartite networks, but the original unsigned node evaluation algorithm cannot be directly used on the signed networks. This paper proposes the Signed PageRank

The scaled bipartite consensus of second-order multi-agent systems is investigated in this paper. The internal delay and distributed delay are also considered in the dynamic model of each agent, in which the delays can be time-varying and large. The communication topology among agents is assumed to be directed and structurally balanced. On one hand, in order to guarantee scaled bipartite consensus

This paper studies a novel trajectory tracking guidance law for a quadrotor unmanned aerial vehicle (UAV) with obstacle avoidance based on nonlinear model predictive control (NMPC) scheme. By augmenting a reference position trajectory to a reference dynamical system, the authors formulate the tracking problem as a standard NMPC design problem to generate constrained reference velocity commands for

By using Chen, Hou and Mu’s extended Zeilberger algorithm, the authors obtain two recurrence relations for Callan’s generalization of Narayana polynomials. Based on these recurrence relations, the authors further prove the real-rootedness and asymptotic normality of Callan’s Narayana polynomials.

In this paper, for a zero-dimensional polynomial ideal I, the authors prove that k[x1, x2, ⋯, xn]/I is cyclic if and only if the breadth of I is 0 or 1. Furthermore, the authors present a new algorithm to compute polynomial univariate representation (PUR) of such an ideal.

This study is a detailed analysis of Speculation Game, a simple agent-based model of financial markets, in which the round-trip trading and the dynamic wealth evolution with variable trading volumes are implemented. Instead of herding behavior, the authors find that the heterogeneous holding periods in round-trip trades can contribute to the emergence of volatility clustering. In particular, the spontaneous

Lattices in Euclidean spaces are important research objects in geometric number theory, and they have important applications in many areas, such as cryptology. The shortest vector problem (SVP) and the closest vector problem (CVP) are two famous computational problems about lattices. In this paper, we consider p-adic lattices in local fields, and define the p-adic analogues of SVP and CVP in local

This paper solves a mean-field type hierarchical optimal control problem in electricity market. The authors consider n − 1 prosumers and one producer. The ith prosumer, for 1 < i < n, is a leader of the (i − 1)th prosumer and is a follower of the (i + 1)th prosumer. The first player (agent) is the follower at the bottom whereas the nth is the leader at the top. The problem is described by a linear

This paper is concerned with a class of mean-field type stochastic optimal control systems, which are governed by fully coupled mean-field forward-backward stochastic differential equations with Teugels martingales associated to Lévy processes. In these systems, the coefficients contain not only the state processes but also their marginal distribution, and the cost function is of mean-field type as

Option pricing problem is one of the central issue in the theory of modern finance. Uncertain currency model has been put forward under the foundation of uncertainty theory as a tool to portray the foreign exchange rate in uncertain finance market. This paper uses uncertain differential equation involved by Liu process to dispose of the foreign exchange rate. Then an American barrier option of currency

This paper considers the Merton portfolio optimization problem for an investor that aims at maximizing the expected power utility of the terminal wealth and intermediate consumption. Applying the homotopy analysis method, an analytical solution for value function as well as optimal strategy under the 3/2 model is derived, respectively. Compared with the existing explicit solutions for Merton problem

The post-disaster emergency medical rescue (EMR) is critical for people’s lives. This paper presents a stochastic Petri net (SPN) model based on the process of the rescue structure and a Markov chain model (MC), which is applied to the optimization of the EMR process, with the aim of identifying the key activities of EMR. An isomorphic MC model is developed for measuring and evaluating the time performance

The paper focuses on the finite-time stochastic stability (FTSS) problems for positive system with random impulses. Combining Lyapunov functions with the probability property of the impulsive interval, first, the sufficient conditions of FTSS for the positive systems affected by one type of random impulses are given; second, the criteria of FTSS for positive systems suffered from multiple types of

For multi-agent systems with competitive and collaborative relationships, signed graph can more intuitively express the characteristics of their interactive networks. In this paper, the bipartite consensus is investigated for multi-agent systems with structurally balanced signed graph. In order to reduce actuation burden in dynamical network environment, the event-triggering strategy is applied to

This paper proposes an empirical likelihood based diagnostic technique for heteroscedasticity for semiparametric varying-coefficient partially linear models with missing responses. Firstly, the authors complement the missing response variables by regression method. Then, the empirical likelihood method is introduced to study the heteroscedasticity of the semiparametric varying-coefficient partially

Passive control is the most popular methodology for flexible spacecraft while it remains an open problem whether the closed-loop performance can be achieved only with passive control subject to the coupling modes of rigid and flexibility. Also, the closed-loop performance of passive PD control based on the dynamics of the Euler angle parameterization of spacecraft, which has been widely used in practice

The problem of hazard rate estimation under right-censored assumption has been investigated extensively. Integrated square error (ISE) of estimation is one of the most widely accepted measurements of the global performance for nonparametric kernel estimation. But there are no results available for ISE of hazard rate estimation under right-censored model with censoring indicators missing at random (MAR)

The paper presents a numerical method for solving a class of high-dimensional stochastic control systems based on tensor decomposition and parallel computing. The HJB solution provides a globally optimal controller to the associated dynamical system. Variable substitution is used to simplify the nonlinear HJB equation. The curse of dimensionality is avoided by representing the HJB equation using separated

This paper proposes various stages of the hepatitis B virus (HBV) besides its transmissibility and nonlinear incidence rate to develop an epidemic model. The authors plan the model, and then prove some basic results for the well-posedness in term of boundedness and positivity. Moreover, the authors find the threshold parameter R0, called the basic/effective reproductive number and carry out local sensitive

This paper studies the secure and accurate clock synchronization problem for sensor networks with time-varying delays and malicious attacks. A novel clock synchronization scheme based on the attack detection mechanism, attack compensation, and maximum consensus protocol is proposed. The proposed scheme starts with the detection of the malicious attacks and the clock data under attacks is eliminated

In this paper, an approximation-based event-triggered model predictive control (AETMPC) strategy is proposed to implement event-triggered model predictive control for continuous-time constrained nonlinear systems under the digital platform. In the AETMPC strategy, both of the optimal control problem (OCP) and the triggering conditions are defined in a discrete-time manner based on approximate discrete-time

White precious metals have often been regarded as industrial raw materials in the past. With the introduction of the Silver ETF in 2006 and Platinum as well as Palladium ETFs in 2010, their role in asset allocation has become more and more important. This paper selects five countries with rapid economic development (BRICS) as the research scope. The authors select silver, platinum and palladium to

Different from previous viewpoints, multivariate polynomial matrix Diophantine equations are studied from the perspective of modules in this paper, that is, regarding the columns of matrices as elements in modules. A necessary and sufficient condition of the existence for the solution of equations is derived. Using powerful features and theoretical foundation of Gröbner bases for modules, the problem

Up till the present moment, researchers have always featured the single-ring neural network. These investigations, however, disregard the link between rings in neural networks. This paper highlights a high-dimensional double-ring neural network model with multiple time delays. The neural network has two rings of a shared node, where one ring has n neurons and the other has m +1 neurons. By utilizing

This paper studies the estimation of the partially linear panel data models, allowing for cross-sectional dependence through a common factors structure. This semiparametric additive partial linear framework, including both linear and nonlinear additive components, is more flexible compared to linear models, and is preferred to a fully nonparametric regression because of the ‘curse of dimensionality’

In this paper, the concepts of con-numbers and con-matrices are proposed by the introduction of conjugate operators into the field of complex numbers, and some properties of these two concepts are derived. In addition, two potential applications of these two concepts are addressed in details. Specifically, a class of quantum systems is expressed in terms of the proposed con-numbers, and the ℝ-linear

The article proposes a nonlinear optimal (H-infinity) control approach for the model of a tracked robotic vehicle. The kinematic model of such a tracked vehicle takes into account slippage effects due to the contact of the tracks with the ground. To solve the related control problem, the dynamic model of the vehicle undergoes first approximate linearization around a temporary operating point which

Coal is essential to ensure China’s energy security. The sudden or gradual change of coal price reflects the degree of disequilibrium or expected disequilibrium of coal supply and demand, which will not be conducive to energy security. Therefore, it is important to analyze the change points of coal price and explore the reason of the price fluctuation. This paper analyses the coal price from January

This paper mainly studies the strong convergence properties for weighted sums of extended negatively dependent (END, for short) random variables. Some sufficient conditions to prove the strong law of large numbers for weighted sums of END random variables are provided. In particular, the authors obtain the weighted version of Kolmogorov type strong law of large numbers for END random variables as a

Currently, working with partially observed functional data has attracted a greatly increasing attention, since there are many applications in which each functional curve may be observed only on a subset of a common domain, and the incompleteness makes most existing methods for functional data analysis ineffective. In this paper, motivated by the appealing characteristics of conditional quantile regression

This paper extends the notion of μ-bases to arbitrary univariate polynomial matrices and present an efficient algorithm to compute a μ-basis for a univariate polynomial matrix based on polynomial matrix factorization. Particularly, when applied to polynomial vectors, the algorithm computes a μ-basis of a rational space curve in arbitrary dimension. The authors perform theoretical complexity analysis

The problem of designing a passive filter for nonlinear switched singularly perturbed systems with parameter uncertainties is explored in this paper. Firstly, the multiple-time-scale phenomenon is settled effectively by introducing a singular perturbation parameter in the plant. Secondly, the interval type-2 fuzzy set theory is employed where parameter uncertainties are expressed in membership functions

The \({\cal G}\)-SGD algorithm significantly outperforms the conventional SGD algorithm in ReLU neural networks by adopting the basis path set. However, how the inner mechanism of basis paths works remains mysterious, and the \({\cal G}\)-SGD algorithm that helps to find a basis path set is heuristic. This paper employs graph theory to investigate structure properties of basis paths in a more general

Mixed-integer optimal control problems (MIOCPs) usually play important roles in many real-world engineering applications. However, the MIOCP is a typical NP-hard problem with considerable computational complexity, resulting in slow convergence or premature convergence by most current heuristic optimization algorithms. Accordingly, this study proposes a new and effective hybrid algorithm based on quantum

This paper investigates the distributed convex optimization problem over a multi-agent system with Markovian switching communication networks. The objective function is the sum of each agent’s local nonsmooth objective function, which cannot be known by other agents. The communication network is assumed to switch over a set of weight-balanced directed graphs with a Markovian property. The authors propose

This paper presents a Q-learning-based target selection algorithm for spacecraft autonomous navigation using bearing observations of known visible targets. For the considered navigation system, the position and velocity of the spacecraft are estimated using an extended Kalman filter (EKF) with the measurements of inter-satellite line-of-sight (LOS) vectors obtained via an onboard star camera. This

This paper is concerned with the event-triggered L1-gain control of a class of nonlinear positive switched systems. First, an event-triggering condition in the form of 1-norm is presented for the systems. By virtue of the event-triggering strategy, the original system is transformed into an interval uncertain system. An event-triggered L1-gain controller is designed by decomposing the controller gain

This paper is devoted to investigating the dynamic output feedback (DOF) control problem of Markovian jump neutral-type stochastic systems with a guaranteed cost function. Both of the state and measurement equations contain time delays. Mode-dependent DOF controllers are first designed such that the closed-loop system is asymptotically stable in mean-square and an adequate performance level of this

This paper investigates the stabilization issue for a class of sampled-data nonlinear Markov switching system with indistinguishable modes. In order to handle indistinguishable modes, the authors reconstruct the original mode space by mode clustering method, forming a new merged Markov switching system. By specifying the difference between the Euler-Maruyama (EM) approximate discrete-time model of

This paper presents an algorithm to compute the topology of an algebraic space curve. This is a modified version of the previous algorithm. Furthermore, the authors also analyse the bit complexity of the algorithm, which is \(\widetilde{\cal O}\left( {{N^{20}}} \right)\), where N = max{d, τ}, d and τ are the degree bound and the bit size bound of the coefficients of the defining polynomials of the

Biological systems can be modeled and described by biological networks. Biological networks are typical complex networks with widely real-world applications. Many problems arising in biological systems can be boiled down to the identification of important nodes. For example, biomedical researchers frequently need to identify important genes that potentially leaded to disease phenotypes in animal and

Clustered interval-censored failure time data often occur in a wide variety of research and application fields such as cancer and AIDS studies. For such data, the failure times of interest are interval-censored and may be correlated for subjects coming from the same cluster. This paper presents a robust semiparametric transformation mixed effect models to analyze such data and use a U-statistic based

This paper proposes a finite-time consensus control algorithm based on nonlinear integral sliding-mode control for second-order multi-agent systems (MASs) with mismatched and matched disturbances. Firstly, a nonlinear finite-time disturbance observer is established to estimate the states and mismatched disturbances of the agent. Secondly, a dynamic integral sliding-mode (ISM) surface is designed by