Effect of time delay on a harvested predator-prey model

The predator-prey systems with harvesting have received a great deal of attentions for last few decades. Incorporating discrete time delays into predator-prey models could induce instability and bifurcation. In this paper we are interested in studying the combined effects of harvesting and discrete time delay on the dynamics of a predator-prey model. A comparative analysis is provided for stability behaviour in absence as well as in presence of time delay. The length of discrete time delay to preserve stability of the model system is obtained. Existence of Hopf-bifurcating small amplitude periodic solutions is derived by taking discrete time delay as a bifurcation parameter.     

短时交通流混沌预测模型的比较研究

短时交通流预测是实现交通流诱导的关键技术之一.针对目前短时交通混沌预测模型预测结果差异较大的问题,归纳了4种基于混沌理论的短时交通流预测模型:RBF神经网络模型、最大Lyapunov指数模型、局域线性模型和Volterra滤波器自适应预测模型,并对这4种预测模型进行了比较研究.应用4种预测模型对几个典型的非线性系统进行预测,验证了算法的准确性.然后用这4种预测模型对微观实测交通流的时间序列进行实证分析.仿真结果表明,4种预测模型对典型混沌时间序列具有很好的预测效果;而对实测交通流预测,其预测精度和稳定性较差,但可以满足实时交通流预测的需要.     

关于双重时序AR-MA模型的相关结构及与ARMA模型的比较

本文在文［４］的基础上讨论了双重时序ＡＲ（１）－ＭＡ（ｑ）模型的相关结构，在不假定白噪声序列为正态的情况下，证明了安鸿志［２］关于模型的相关结构的猜想是正确的，具体地构造了ＡＲ（１）－ＭＡ（３）模型的相关结构，并与ＡＲＭＡ模型进行了初步的比较，给出了一些抛砖引玉的讨论．     

THE QUALITATIVE CONTENT OF RENEWABLE RESOURCE MODELS

This paper analyzes the extent to which standard dynamic renewable resource models possess refutable implications. Both the steady state comparative static and local comparative dynamic properties of the standard model are studied. A unified framework is developed which enables one to analyze the qualitative properties of any standard renewable resource model. This is achieved by explicitly linking the local stability, steady state comparative static, and local comparative dynamic properties of the model.     

Forecasting business cycle with chaotic time series based on neural network with weighted fuzzy membership functions

This study presents a forecasting model of cyclical fluctuations of the economy based on the time delay coordinate embedding method. The model uses a neuro-fuzzy network called neural network with weighted fuzzy membership functions (NEWFM). The preprocessed time series of the leading composite index using the time delay coordinate embedding method are used as input data to the NEWFM to forecast the business cycle. A comparative study is conducted using other methods based on wavelet transform and Principal Component Analysis for the performance comparison. The forecasting results are tested using a linear regression analysis to compare the approximation of the input data against the target class, gross domestic product (GDP). The chaos based model captures nonlinear dynamics and interactions within the system, which other two models ignore. The test results demonstrated that chaos based method significantly improved the prediction capability, thereby demonstrating superior performance to the other methods.     

A deterministic resource scheduling model in epidemic control: A case study

The resources available to tackle an epidemic infection are usually limited, while the time and effort required to control it are increasing functions of the starting time of the containment effort. The problem of scheduling limited available resources, when there are several areas where the population is infected, is considered. A deterministic model, appropriate for large populations, where random interactions can be averaged out, is used for the epidemic’s rate of spread. The problem is tackled using the concept of deteriorating jobs, i.e. the model represents increasing loss rate as more susceptibles become infected, and increasing time and effort needed for the epidemic’s containment. A case study for a proposed application of the model in the case of the mass vaccination against A(H1N1)_v influenza in the Attica region, Greece and a comparative study of the model’s performance vs. the applied random practice are presented.     

An optimal solution technique for the joint replenishment problem with storage and transport capacities and budget constraints

The joint replenishment problem, which is concerned with the problem of coordinating the replenishment of a group of items that may be ordered jointly, has been studied extensively and many heuristic solution procedures have been presented in the literature. To obtain the minimum of the total cost, the main complexity lies in determining the appropriate lower bound of the basic cycle time. Also there is a lack of a global optimal solution technique of the problem. This paper presents its extended model to include some practical issues and develops a simple procedure to calculate the appropriate lower bound of the basic cycle time. By a comparative study of a numerical example, it demonstrates the inabilities of the available lower bound formulae in the literature. It also develops a generalized global optimal solution algorithm of the extended model and illustrates this with a numerical example. Then a comparative study of the results of seven numerical examples is carried out to highlight the global optimality of the solution technique.     

Nonlinear parametric models from volterra kernels measurements

Methods for nonlinear system identification are often classified, based on the employed model form, into parametric (nonlinear differential or difference equations) and nonparametric (functional expansions). These methods exhibit distinct sets of advantages and disadvantages that have motivated comparative studies and point to potential benefits from combined use. Fundamental to these studies are the mathematical relations between nonlinear differential (or difference, in discrete time) equations (NDE) and Volterra functional expansions (VFE) of the class of nonlinear systems for which both model forms exist, in continuous or discrete time. Considerable work has been done in obtaining the VFE's of a broad class of NDE's, which can be used to make the transition from nonparametric models (obtained from experimental input-output data) to more compact parametric models. This paper presents a methodology by which this transition can be made in discrete time. Specifically, a method is proposed for obtaining a parametric NARMAX (Nonlinear Auto-Regressive Moving-Average with exogenous input) model from Volterra kernels estimated by use of input-output data.     

Comparative regional GDP analysis: case study of Croatia

The focus of this paper is the regional GDP analysis of Croatian Counties. It is a part of an extensive on-going scientific research about Croatian economic challenges within the global recession environment. Although, as EU accession country, Croatia is divided into three NUTS 2 regions, twenty one Croatian Counties show significant economic and social disproportions. In multiple regression model it is researched to what extent regional GDP per capita depends on a set of regional variables (employment, gross investment, production of more important agricultural products, GVA per person employed, construction works value, exports, imports, foreign tourists arrivals, foreign tourist nights, ecology...). Subsequently parameters are evaluated by Monte Carlo simulations which are used for the first time in comparative regional analysis. Also Croatian Counties are classified using Cluster analysis to make a comparative analysis with official spacing into three NUTS 2 regions which are geographical and political areas rather than real and homogenous socio-economic areas.     

改进灰导数和时间响应函数的新灰色预测模型

以白化方程为基础,利用梯形公式白化灰导数,同时根据最小二乘法求出时间响应函数中的常数c,得到一种改进的灰色预测模型.应用实例说明改进模型具有较高的预测和拟合精度.     

Optimal inventory policies under decreasing cost functions via geometric programming

In this paper, we establish and analyze two economic order quantity (EOQ) based inventory models under total cost minimization and profit maximization via geometric programming (GP) techniques. Through GP, optimal solutions for both models are found and managerial implications on the optimal policy are determined through bounding and sensitivity analysis. We investigate the effects on the changes in the optimal order quantity and the demand per unit time according to varied parameters by studying optimality conditions. In addition, a comparative analysis between the total cost minimization model and the profit maximization model is conducted. By investigating the error in the optimal order quantity of these two models, several interesting economic implications and managerial insights can be observed.     

NATURAL RESOURCE EXPLOITATION UNDER COMMON PROPERTY RIGHTS

ABSTRACT. Renewable natural resources such as ground‐water, pastures and fisheries are often governed bycommon propertyrights in which members of a group jointlyown the exclusive use of the resource. We develop a formal model of a common propertycontract based on differential game theory and then use the model to examine (i) the incentives of individual users of the common resource; (ii) the resulting harvest and stock time paths; (iii) the local stabilityof the steady state; and (iv) the steadystate comparative statics. Moreover, we compare the qualitative properties of the common propertyregime to those generated under perfectlydefined private rights and open access. We show how common prop‐ertyownership of natural resources can generate rent and be a second‐best solution when private propertyrights are costly to establish.     

THE INTRINSIC QUALITATIVE PROPERTIES OF THE CLASSICAL OPTIMAL STOPPING PROBLEM ARE INVARIANT TO THE FUNCTIONAL FORM OF THE DISCOUNT FUNCTION

Abstract The intrinsic qualitative properties of a generic optimal stopping model are shown to be invariant to the functional form of the discount function. If the discount function is assumed to be a member of particular infinite parametric family—a family that includes the exponential and classical hyperbolic discount functions as special cases—an additional refutable comparative statics result is produced that holds for the entire family. Consequently, if one limits econometric tests of the model to its qualitative properties, one cannot determine the form of the discount function used by the decision maker. It is also shown that the only discount function that yields a time‐consistent stopping rule is the exponential function with a constant rate of discount.     

MIP models for resource-constrained project scheduling with flexible resource profiles

This paper addresses the resource-constrained project scheduling problem with flexible resource profiles (FRCPSP). Such a problem often arises in many real-world applications, in which the resource usage of an activity is not merely constant, but can be adjusted from period to period. The FRCPSP is, therefore, to simultaneously determine the start time, the resource profile, and the duration of each activity in order to minimize the makespan, subject to precedence relationships, limited availability of multiple resources, and restrictions on resource profiles. We propose four discrete-time model formulations and compare their model efficiency in terms of solution quality and computational times. Both preprocessing and priority-based heuristic methods are also applied to compute both upper and lower bounds of the makespan. Our comparative results show significant dominance of one of the models, the so-called “variable-intensity-based” model, in both solution quality and runtimes.     

教学质量评估的定量比较评价模型

依据华南农业大学 2 0 0 2学年第一学期课堂教学质量评估卡的调查数据 ,利用层次分析法建立了学生评价教师教学质量的定量评价模型 P =WR,并应用该模型对担任数学类课程的 1 3位教师的课堂教学质量作了定量比较分析 .分析结果表明 ,近几年来的扩招 ,对教师的教学提出了新的要求 ,在教学内容、教学手段、教学方法等方面 ,应做出相应的调整 ,才能收到好的教学效果 .     

考虑车载容量的多区型仓库拣货路径优化研究

拣货作业是仓库核心作业之一,占据仓库运营大量的时间成本和资金成本.针对多区型仓库拣货路径优化问题,对多区型仓库布局、货位坐标、路径等问题进行了定义,构建了多区型仓库拣货路径优化建模,接着通过大量实验确定了人工鱼群算法在求解拣货路径问题时的最优算法参数组合,通过演示性实验验证了模型与算法的有效性,最后从波次订单对实验结果...     

Optimal control of locusts in subsistence farming areas

Locust swarms hit subsistence-staple-crop-growing households at random and are not privately controllable. An aerial-spraying optimal control model that supports the said households’ livelihood at least expected cost is therefore developed. The qualitative properties of the model are analysed under economically plausible but mild assumptions. The steady state comparative statics reveal that the locust swarm size and the probability of a household’s crop being destroyed by a swarm decrease with the number of households, yield per household, and the staple crop’s replacement price, and increase with the marginal cost of spraying and the planner’s discount rate. A local comparative dynamics analysis is also conducted, as it provides the necessary economic intuition behind other ostensibly anomalous steady-state comparative statics results.     

Numerical simulation for a long-range dispersion of a pollutant using Chernobyl data

A Lagrangian particle model has been developed and applied to a long-range atmospheric dispersion. The developed numerical model has been tested by comparing its predictions with the ¹³⁷Cs air concentrations recorded over European areas during the Chernobyl accident. Sensitivity studies were performed to investigate the numerical accuracy according to a variation of the parameters such as the mixing height and diffusion coefficient in the model. From a comparative study, the calculated concentration distributions were more sensitive to a variation of the mixing height than to the changes of the diffusion coefficient values. Also, the calculated concentrations agreed with the time series of the measured ones at some sampling points.     

Flow auctions

Flow goods (like electricity) are sold through auctions in a dynamic framework. An important design question is the frequency of such auctions. We use a simple dynamic auction model in continuous time to answer this question. We focus on the relationship between the persistency of bidders’ valuations and the optimal choice of frequency. If the seller focuses on the equilibrium in which bidders follow a repeated static Nash strategy, then the frequency of auctions should typically increase when persistency declines. However, accounting for the fact that bidders can follow different equilibria that are collusive in nature, the comparative statics are reversed, forcing the seller to reduce the frequency when bidders’ valuations are less persistent. The argument builds on the fact that high frequency auctions are more conducive to collusion among bidders.     

Far Casting Cross-Validation

Cross-validation has long been used for choosing tuning parameters and other model selection tasks. It generally performs well provided the data are independent, or nearly so. Improvements have been suggested which address ordinary cross-validation’s (OCV) shortcomings in correlated data. Whereas these techniques have merit, they can still lead to poor model selection in correlated data or are not readily generalizable to high-dimensional data.

The proposed solution, far casting cross-validation (FCCV), addresses these problems. FCCV withholds correlated neighbors in every aspect of the cross-validation procedure. The result is a technique that stresses a fitted model’s ability to extrapolate rather than interpolate. This generally leads to better model selection in correlated datasets.

Whereas FCCV is less than optimal in the independence case, our improvement of OCV applies more generally to higher dimensional error processes and to both parametric and nonparametric model selection problems. To facilitate introduction, we consider only one application, namely estimating global bandwidths for curve estimation with local linear regression. We provide theoretical motivation and report some comparative results from a simulation experiment and on a time series of annual global temperature deviations. For such data, FCCV generally has lower average squared error when disturbances are correlated.

Supplementary materials are available online.