Discrete Dynamics in Nature and Society
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Open Access journal
ISSN (Print) 1026-0226 - ISSN (Online) 1607-887X
Published by Hindawi [333 journals]
- Multiobjective Location Routing Problem considering Uncertain Data after
Abstract: The relief distributions after large disasters play an important role for rescue works. After disasters there is a high degree of uncertainty, such as the demands of disaster points and the damage of paths. The demands of affected points and the velocities between two points on the paths are uncertain in this article, and the robust optimization method is applied to deal with the uncertain parameters. This paper proposes a nonlinear location routing problem with half-time windows and with three objectives. The affected points can be visited more than one time. The goals are the total costs of the transportation, the satisfaction rates of disaster nodes, and the path transport capacities which are denoted by vehicle velocities. Finally, the genetic algorithm is applied to solve a number of numerical examples, and the results show that the genetic algorithm is very stable and effective for this problem.
PubDate: Thu, 23 Mar 2017 00:00:00 +000
- A New Method for Solving Multiobjective Bilevel Programs
Abstract: We study a class of multiobjective bilevel programs with the weights of objectives being uncertain and assumed to belong to convex and compact set. To the best of our knowledge, there is no study about this class of problems. We use a worst-case weighted approach to solve this class of problems. Our “worst-case weighted multiobjective bilevel programs” model supposes that each player (leader or follower) has a set of weights to their objectives and wishes to minimize their maximum weighted sum objective where the maximization is with respect to the set of weights. This new model gives rise to a new Pareto optimum concept, which we call “robust-weighted Pareto optimum”; for the worst-case weighted multiobjective optimization with the weight set of each player given as a polytope, we show that a robust-weighted Pareto optimum can be obtained by solving mathematical programing with equilibrium constraints (MPEC). For an application, we illustrate the usefulness of the worst-case weighted multiobjective optimization to a supply chain risk management under demand uncertainty. By the comparison with the existing weighted approach, we show that our method is more robust and can be more efficiently applied to real-world problems.
PubDate: Thu, 23 Mar 2017 00:00:00 +000
- Bifurcations and Synchronization of the Fractional-Order Bloch System
Abstract: In this paper, bifurcations and synchronization of a fractional-order Bloch system are studied. Firstly, the bifurcations with the variation of every order and the system parameter for the system are discussed. The rich dynamics in the fractional-order Bloch system including chaos, period, limit cycles, period-doubling, and tangent bifurcations are found. Furthermore, based on the stability theory of fractional-order systems, the adaptive synchronization for the system with unknown parameters is realized by designing appropriate controllers. Numerical simulations are carried out to demonstrate the effectiveness and flexibility of the controllers.
PubDate: Wed, 22 Mar 2017 00:00:00 +000
- A Modified Total Crossing Time Model of Bidirectional Pedestrians at
Abstract: Since crosswalk width and pedestrian green time directly affect the safety of signalized crosswalks, modeling an exact total crossing time model to estimate those two variables is imperative. The total crossing time needed by a group of pedestrians to cross a signalized crosswalk contains the discharge time and the crossing time. The discharge time depends primarily on the maximum queue length, which is determined by pedestrian arrival rate, red interval, waiting position distribution, and the crosswalk width. Crossing time increases when interactions between bidirectional pedestrian flows become more serious. Thus, quantifying the impacts of the start-up process on the discharge time and the effects of the interactions on the crossing time is a prerequisite for optimizing the design of signalized crosswalks. This paper establishes a modified total crossing time model consisting of modified pedestrian discharge and crossing time. Discharge time is modeled by applying traffic wave theory, and crossing time is modeled based on drag force theory. The proposed models provide guidance for the design of crosswalk width and pedestrian green intervals.
PubDate: Wed, 22 Mar 2017 00:00:00 +000
- The Dynamics of Structural and Energy Intensity Change
Abstract: In this study, an extended structural change model is adopted to explore the mechanisms of how structural adjustments influence the changes of energy intensity. Through adding an energy production sector to the standard model, we find that the change of sectoral energy intensity is determined by the differences of sectoral and energy production technologies. Moreover, the change of economy-wide energy intensity is shaped by both structural and sectoral energy intensity changes. According to theoretical findings and simulation exercises, structural change, initiated by technological growth rate and substitution elasticity, affects the growth rate of economy-wide energy intensity. (1) If the energy threshold technological growth rates are high or low enough, the overall energy intensity will develop monotonically. (2) If the energy threshold technological growth rate is moderate, and (i) substitution elasticity and initial final production technological growth rate meet some requirements, the economy-wide energy intensity will grow monotonically; otherwise, (ii) with the suitable combination of substitution elasticity and initial final production technological growth rate, the overall energy intensity can develop nonmonotonically, like U or inverted-U curves.
PubDate: Wed, 22 Mar 2017 00:00:00 +000
- A Singular Sturm-Liouville Problem with Limit Circle Endpoints and
Eigenparameter Dependent Boundary Conditions
Abstract: In this paper, we investigate a class of discontinuous singular Sturm-Liouville problems with limit circle endpoints and eigenparameter dependent boundary conditions. Operator formulation is constructed and asymptotic formulas for eigenvalues and fundamental solutions are given. Moreover, the completeness of eigenfunctions is discussed.
PubDate: Tue, 21 Mar 2017 09:29:20 +000
- A New Method to Extract CSP Gather of Topography for Scattered Wave
Abstract: The seismic method is one of the major geophysical tools to study the structure of the earth. The extraction of the common scatter point (CSP) gather is a critical step to accomplish the seismic imaging with a scattered wave. Conventionally, the CSP gather is obtained with the assumption that the earth surface is horizontal. However, errors are introduced to the final imaging result if the seismic traces obtained at the rugged surface are processed using the conventional method. Hence, we propose the method of the extraction of the CSP gather for the seismic data collected at the rugged surface. The proposed method is validated by two numerical examples and expected to reduce the effect of the topography on the scattered wave imaging.
PubDate: Tue, 21 Mar 2017 00:00:00 +000
- A Combined Weighting Method Based on Hybrid of Interval Evidence Fusion
and Random Sampling
Abstract: Due to the complexity of system and lack of expertise, epistemic uncertainties may present in the experts’ judgment on the importance of certain indices during group decision-making. A novel combination weighting method is proposed to solve the index weighting problem when various uncertainties are present in expert comments. Based on the idea of evidence theory, various types of uncertain evaluation information are uniformly expressed through interval evidence structures. Similarity matrix between interval evidences is constructed, and expert’s information is fused. Comment grades are quantified using the interval number, and cumulative probability function for evaluating the importance of indices is constructed based on the fused information. Finally, index weights are obtained by Monte Carlo random sampling. The method can process expert’s information with varying degrees of uncertainties, which possesses good compatibility. Difficulty in effectively fusing high-conflict group decision-making information and large information loss after fusion is avertible. Original expert judgments are retained rather objectively throughout the processing procedure. Cumulative probability function constructing and random sampling processes do not require any human intervention or judgment. It can be implemented by computer programs easily, thus having an apparent advantage in evaluation practices of fairly huge index systems.
PubDate: Mon, 20 Mar 2017 09:01:56 +000
- Stability and Hopf Bifurcation Analysis for a Computer Virus Propagation
Model with Two Delays and Vaccination
Abstract: A further generalization of an SEIQRS-V (susceptible-exposed-infectious-quarantined-recovered-susceptible with vaccination) computer virus propagation model is the main topic of the present paper. This paper specifically analyzes effects on the asymptotic dynamics of the computer virus propagation model when two time delays are introduced. Sufficient conditions for the asymptotic stability and existence of the Hopf bifurcation are established by regarding different combination of the two delays as the bifurcation parameter. Moreover, explicit formulas that determine the stability, direction, and period of the bifurcating periodic solutions are obtained with the help of the normal form theory and center manifold theorem. Finally, numerical simulations are employed for supporting the obtained analytical results.
PubDate: Mon, 20 Mar 2017 00:00:00 +000
- On the Optimal Dynamic Control Strategy of Disruptive Computer Virus
Abstract: Disruptive computer viruses have inflicted huge economic losses. This paper addresses the development of a cost-effective dynamic control strategy of disruptive viruses. First, the development problem is modeled as an optimal control problem. Second, a criterion for the existence of an optimal control is given. Third, the optimality system is derived. Next, some examples of the optimal dynamic control strategy are presented. Finally, the performance of actual dynamic control strategies is evaluated.
PubDate: Sun, 19 Mar 2017 10:18:05 +000
- A Viral Product Diffusion Model to Forecast the Market Performance of
Abstract: To investigate the diffusion of products in the market, this paper proposes a viral product diffusion model using an epidemiological approach. This model presents the process of product diffusion through the dynamics of human behaviors. Based on the stability theory of Ordinary Differential Equations, we demonstrate the conditions under which a product in the market persists or dies out eventually. Next, we use Google data to validate the model. Fitting results illustrate that the viral product diffusion model not only depicts the steady growth process of products, but also describes the whole diffusion process during which the products increase at the initial stage and then gradually decrease and sometimes even exhibit multiple peaks. This shows that the viral product diffusion model can be used to forecast the developing tendency of products in the market through early behavior of these products. Moreover, our model also provides useful insights on how to design effective marketing strategies via social contagions.
PubDate: Wed, 15 Mar 2017 06:20:38 +000
- Spatial Interpolation of Annual Runoff in Ungauged Basins Based on the
Improved Information Diffusion Model Using a Genetic Algorithm
Abstract: Prediction in Ungauged Basins (PUB) is an important task for water resources planning and management and remains a fundamental challenge for the hydrological community. In recent years, geostatistical methods have proven valuable for estimating hydrological variables in ungauged catchments. However, four major problems restrict the development of geostatistical methods. We established a new information diffusion model based on genetic algorithm (GIDM) for spatial interpolating of runoff in the ungauged basins. Genetic algorithms (GA) are used to generate high-quality solutions to optimization and search problems. So, using GA, the parameter of optimal window width can be obtained. To test our new method, seven experiments for the annual runoff interpolation based on GIDM at 17 stations on the mainstream and tributaries of the Yellow River are carried out and compared with the inverse distance weighting (IDW) method, Cokriging (COK) method, and conventional IDMs using the same sparse observed data. The seven experiments all show that the GIDM method can solve four problems of the previous geostatistical methods to some extent and obtains best accuracy among four different models. The key problems of the PUB research are the lack of observation data and the difficulties in information extraction. So the GIDM is a new and useful tool to solve the Prediction in Ungauged Basins (PUB) problem and to improve the water management.
PubDate: Tue, 14 Mar 2017 10:10:25 +000
- Research on the Method of Traffic Organization and Optimization Based on
Dynamic Traffic Flow Model
Abstract: The modern transportation system is becoming sluggish by traffic jams, so much so that it can harm the economic and society in our country. One of the reasons is the surging vehicles day by day. Another reason is the shortage of the traffic supply seriously. But the most important reason is that the traffic organization and optimization hardly met the conditions of modern transport development. In this paper, the practical method of the traffic organization and optimization used in regional area is explored by the dynamic traffic network analysis method. Firstly, the operational states of the regional traffic network are obtained by simulation method based on the self-developed traffic simulation software DynaCHINA, in which the improved traffic flow simulation model was proposed in order to be more suitable for actual domestic urban transport situation. Then the appropriated optimization model and algorithm were proposed according to different optimized content and organization goals, and the traffic simulation processes more suitable to regional optimization were designed exactly. Finally, a regional network in Tai’an city was selected as an example. The simulation results show that the proposed method is effective and feasible. It can provide strong scientific and technological support for the traffic management department.
PubDate: Tue, 14 Mar 2017 07:26:40 +000
- Spatiotemporal Video Denoising Based on Adaptive Thresholding and
Abstract: In this paper we propose a novel video denoising method based on adaptive thresholding and -means clustering. In the proposed method the adaptive thresholding is applied rather than the conventional hard-thresholding of the VBM3D method. The adaptive thresholding has a high ability to adapt and change according to the amount of noise. More specifically, hard-thresholding is applied on the higher noise areas while soft-thresholding is applied on the lower noise areas. Consequently, we can successfully remove the noise effectively and at the same time preserve the edges of the image, because the clustering approach saves more computation time and is more capable of finding relevant patches than the block-matching approach. So, the -means clustering method in the final estimate in this paper is adopted instead of the block-matching method in the VBM3D method in order to restrict the search of the candidate patches within the region of the reference patch and therefore improve the grouping. Experimental results emphasize the superiority of the new method over the reference methods in terms of visual quality, Peak Signal-to-Noise Ratio (PSNR), and Image Enhancement Factor (IEF). Execution time of the proposed algorithm consumes less time in denoising than that in the VBM3D algorithm.
PubDate: Tue, 14 Mar 2017 00:00:00 +000
- Staged Venture Capital Investment considering Unexpected Major Events
Abstract: This paper presents a dynamic model of capital financing, taking into consideration unexpected major events occurring within continuous time model. We are considering a special jump-diffusion model first described by Samuelson (1973) while using traditional geometric Brownian motion. This paper seeks to accurately show the innovative project valuation when unexpected major events occur and get the analytical results of the project option value. Furthermore, we analyzed the impact of multistaged financing; results indicated that both sources of uncertainty positively impact the project option value; particularly, the option price when considering unexpected major events occurrence is larger than the option price without unexpected major events. Based on a comparative-static analysis, new propositions for optimal amount of investment and optimal level of project are derived from simulations.
PubDate: Sun, 12 Mar 2017 10:16:58 +000
- A Traffic Restriction Scheme for Enhancing Carpooling
Abstract: For the purpose of alleviating traffic congestion, this paper proposes a scheme to encourage travelers to carpool by traffic restriction. By a variational inequity we describe travelers’ mode (solo driving and carpooling) and route choice under user equilibrium principle in the context of fixed demand and detect the performance of a simple network with various restriction links, restriction proportions, and carpooling costs. Then the optimal traffic restriction scheme aiming at minimal total travel cost is designed through a bilevel program and applied to a Sioux Fall network example with genetic algorithm. According to various requirements, optimal restriction regions and proportions for restricted automobiles are captured. From the results it is found that traffic restriction scheme is possible to enhance carpooling and alleviate congestion. However, higher carpooling demand is not always helpful to the whole network. The topology of network, OD demand, and carpooling cost are included in the factors influencing the performance of the traffic system.
PubDate: Sun, 12 Mar 2017 09:26:55 +000
- Optimized Distribution of Beijing Population Based on CA-MAS
Abstract: In recent years rapid expansion of populations, disruption of ecological environments, and power shortages to areas of high population density in undeveloped areas have appeared in major cities in China. Well-planned population distribution in a city has become one of the key development strategies of urbanization in the country. Taking Beijing as a case-study and using 2010 as the base period, this study simulates city population size and distribution during 2011–2030 using the CA-MAS model. The results showed that (1) the unplanned layout of Beijing’s population is inefficient and will result in the slow agglomeration of populations into surrounding small towns, (2) the suburbanization of the population (while employment opportunities remain centralized) increases the stress of the city commuters, (3) the current policy guiding the distribution of residential and commercial areas is effective, accelerating the formation of small town clusters, which play a role in the city’s radiation and diffusion, contributing to reducing urban commuter stress, and (4) promoting the homogenization of public resources, planning the development of a multicenter urban area, and promoting mixed use (commercial and residential) zoning are the main measures recommended to strengthen the sustainability of Beijing’s urban development and to optimize spatial layout.
PubDate: Sun, 12 Mar 2017 00:00:00 +000
- An Efficient Series Solution for Nonlinear Multiterm Fractional
Abstract: In this paper, we introduce an efficient series solution for a class of nonlinear multiterm fractional differential equations of Caputo type. The approach is a generalization to our recent work for single fractional differential equations. We extend the idea of the Taylor series expansion method to multiterm fractional differential equations, where we overcome the difficulty of computing iterated fractional derivatives, which are difficult to be computed in general. The terms of the series are obtained sequentially using a closed formula, where only integer derivatives have to be computed. Several examples are presented to illustrate the efficiency of the new approach and comparison with the Adomian decomposition method is performed.
PubDate: Wed, 08 Mar 2017 07:11:15 +000
- Finite-Time Passivity and Passification Design for Markovian Jumping
Systems with Mode-Dependent Time-Varying Delays
Abstract: This paper investigates the finite-time passivity and passification design problem for a class of Markovian jumping systems with mode-dependent time-varying delays. By employing the Lyapunov-Krasovskii functional method, delay-dependent sufficient criteria are derived to ensure the mean-square stochastically finite-time passivity. Based on the established results, mode-dependent passification controller is further designed in terms of linear matrix inequalities, such that the prescribed passive performance index of the resulting closed-loop system can be satisfied. Finally, two illustrative examples are given to show the effectiveness of the obtained theoretical results.
PubDate: Tue, 07 Mar 2017 06:55:07 +000
- Estimation of Container Traffic at Seaports by Using Several Soft
Computing Methods: A Case of Turkish Seaports
Abstract: Container traffic forecasting is important for the operations and the design steps of a seaport facility. In this study, performances of the novel soft computing models were compared for the container traffic forecasting of principal Turkish seaports (Istanbul, Izmir, and Mersin seaports) with excessive container traffic. Four forecasting models were implemented based on Artificial Neural Network with Artificial Bee Colony and Levenberg-Marquardt Algorithms (ANN-ABC and ANN-LM), Multiple Nonlinear Regression with Genetic Algorithm (MNR-GA), and Least Square Support Vector Machine (LSSVM). Forecasts were carried out by using the past records of the gross domestic product, exports, and population of the Turkey as indicators of socioeconomic and demographic status. Performances of the forecasting models were evaluated with several performance metrics. Considering the testing period, the LSSVM, ANN-ABC, and ANN-LM models performed better than the MNR-GA model considering overall fitting and prediction performances of the extreme values in the testing data. The LSSVM model was found to be more reliable compared to the ANN models. Forecasting part of the study suggested that container traffic of the seaports will be increased up to 60%, 67%, and 95% at the 2023 for the Izmir, Mersin, and Istanbul seaports considering official growth scenarios of Turkey.
PubDate: Tue, 07 Mar 2017 00:00:00 +000
- A Study on the Generalized Approximation Modeling Method Based on Fitting
Sensitivity for Prediction of Engine Performance
Abstract: Prediction technology for aeroengine performance is significantly important in operational maintenance and safety engineering. In the prediction of engine performance, to address overfitting and underfitting problems with the approximation modeling technique, we derived a generalized approximation model that could be used to adjust fitting precision. Approximation precision was combined with fitting sensitivity to allow the model to obtain excellent fitting accuracy and generalization performance. Taking the Grey model (GM) as an example, we discussed the modeling approach of the novel GM based on fitting sensitivity, analyzed the setting methods and optimization range of model parameters, and solved the model by using a genetic algorithm. By investigating the effect of every model parameter on the prediction precision in experiments, we summarized the change regularities of the root-mean-square errors (RMSEs) varying with the model parameters in novel GM. Also, by analyzing the novel ANN and ANN with Bayesian regularization, it is concluded that the generalized approximation model based on fitting sensitivity can achieve a reasonable fitting degree and generalization ability.
PubDate: Mon, 06 Mar 2017 08:37:35 +000
- Mathematical Model and Algorithm for the Reefer Mechanic Scheduling
Problem at Seaports
Abstract: With the development of seaborne logistics, the international trade of goods transported in refrigerated containers is growing fast. Refrigerated containers, also known as reefers, are used in transportation of temperature sensitive cargo, such as perishable fruits. This trend brings new challenges to terminal managers, that is, how to efficiently arrange mechanics to plug and unplug power for the reefers (i.e., tasks) at yards. This work investigates the reefer mechanics scheduling problem at container ports. To minimize the sum of the total tardiness of all tasks and the total working distance of all mechanics, we formulate a mathematical model. For the resolution of this problem, we propose a DE algorithm which is combined with efficient heuristics, local search strategies, and parameter adaption scheme. The proposed algorithm is tested and validated through numerical experiments. Computational results demonstrate the effectiveness and efficiency of the proposed algorithm.
PubDate: Mon, 06 Mar 2017 06:33:34 +000
- Structure Characteristics of the International Stock Market Complex
Network in the Perspective of Whole and Part
Abstract: International stock market forms an abstract complex network through the fluctuation correlation of stock price index. Past studies of complex network almost focus on single country’s stock market. Here we investigate the whole and partial characteristics of international stock market network (ISMN) (hereinafter referred to as ISMN). For the analysis on the whole network, we firstly determine the reasonable threshold as the basic of the following study. Robustness is applied to analyze the stability of the network and the result shows that ISMN has robustness against random attack but intentional attack breaks the connection integrity of ISMN rapidly. In the partial network, the sliding window method is used to analyze the dynamic evolution of the relationship between the Chinese (Shanghai) stock market and the international stock market. The connection between the Chinese stock market and foreign stock markets becomes increasingly closer, and the links between them show a significant enhancement especially after China joined the WTO. In general, we suggest that transnational investors pay more attention to some significant event of the stock market with large degree for better risk-circumvention.
PubDate: Mon, 06 Mar 2017 00:00:00 +000
- Data-Driven Networked Optimal Iterative Learning Control for Discrete
Linear Time-Varying Systems with One-Operation Bernoulli-Type
Abstract: This paper develops a type of data-driven networked optimal iterative learning control strategy for a class of discrete linear time-varying systems with one-operation Bernoulli-type communication delays. In terms of the stochastic Bernoulli-type one-operation communication delayed inputs and outputs, the previous-iteration synchronous compensations are adopted. By means of deriving gradients of two types of objective functions that express the optimal approximation of the system matrix and the minimal tracking error, the strategy approximates the system matrix and upgrades the control inputs in an interact mode as the iteration evolves. By taking advantage of matrix theory and statistical technique, it is derived that the approximation discrepancy of the system matrix is bounded and the mathematical expectation of the tracking error vanishes as the iteration goes on. Numerical simulations manifest the validity and effectiveness.
PubDate: Mon, 06 Mar 2017 00:00:00 +000
- On Consensus of Star-Composed Networks with an Application of Laplacian
Abstract: In this paper, we mainly study the performance of star-composed networks which can achieve consensus. Specifically, we investigate the convergence speed and robustness of the consensus of the networks, which can be measured by the smallest nonzero eigenvalue of the Laplacian matrix and the norm of the graph, respectively. In particular, we introduce the notion of the corona of two graphs to construct star-composed networks and apply the Laplacian spectrum to discuss the convergence speed and robustness for the communication network. Finally, the performances of the star-composed networks have been compared, and we find that the network in which the centers construct a balanced complete bipartite graph has the most advantages of performance. Our research would provide a new insight into the combination between the field of consensus study and the theory of graph spectra.
PubDate: Sun, 05 Mar 2017 09:02:56 +000
- Corrigendum to “A Fractional Trust Region Method for Linear Equality
PubDate: Sun, 05 Mar 2017 00:00:00 +000
- Generalized Characteristic Polynomials of Join Graphs and Their
Abstract: The Kirchhoff index of is the sum of resistance distances between all pairs of vertices of in electrical networks. is the Laplacian-Energy-Like Invariant of in chemistry. In this paper, we define two classes of join graphs: the subdivision-vertex-vertex join and the subdivision-edge-edge join . We determine the generalized characteristic polynomial of them. We deduce the adjacency (Laplacian and signless Laplacian, resp.) characteristic polynomials of and when is -regular graph and is -regular graph. As applications, the Laplacian spectra enable us to get the formulas of the number of spanning trees, Kirchhoff index, and of and in terms of the Laplacian spectra of and .
PubDate: Thu, 02 Mar 2017 07:46:53 +000
- The Threshold of a Stochastic SIRS Model with Vertical Transmission and
Abstract: The threshold of a stochastic SIRS model with vertical transmission and saturated incidence is investigated. If the noise is small, it is shown that the threshold of the stochastic system determines the extinction and persistence of the epidemic. In addition, we find that if the noise is large, the epidemic still prevails. Finally, numerical simulations are given to illustrate the results.
PubDate: Tue, 28 Feb 2017 14:46:32 +000
- The Optimal Strategies of Risk-Averse Newsvendor Model for a Dyadic Supply
Chain with Financing Service
Abstract: This paper studies the budget-constrained newsvendor problem under risk aversion with financing service and builds a two-stage supply chain decision model on the order quantity and wholesale price. The budget-constrained retailer as a newsvendor faces a nonnegative random demand and the financial institution provides the loan service for the retailer who is risk-averse. This paper first explores the impact of risk aversion on the decisions in financial supply chain. Different from the existing research, we analyze how the financing service of bank loan impacts the risk-averse newsvendor’s decision and how the risk-averse behavior of the retailer influences the optimal strategies in supply chain with CVaR risk measure criterion. It is found that the order quantity decreases in the degree of risk aversion. The optimal order quantity is decreasing in initial budget, wholesale price, and interest rate. It is worth noting that the financing service can improve the profit of the supply chain system when the retailer has a low initial wealth. Finally, to compare with the existing results the theoretical analysis and numerical examples are also illustrated.
PubDate: Tue, 28 Feb 2017 00:00:00 +000
- Some Differential Inequalities on Time Scales and Their Applications to
Feedback Control Systems
Abstract: This paper deals with feedback control systems on time scales. Firstly, we generalize the semicycle concept to time scales and then establish some differential inequalities on time scales. Secondly, as applications of these inequalities, we study the uniform ultimate boundedness of solutions of these systems. We give a new method to investigate the permanence of ecosystem on time scales. And some known results have been generalized. Finally, an example is given to support the result.
PubDate: Tue, 28 Feb 2017 00:00:00 +000