损失规避与公平偏好对房地产征收补偿策略的影响

地方政府对土地财政依赖度高,土地征收与出让仍是市县级政府干预地方经济发展的最主要手段,现行房地产征收补偿制度设计忽略了主体策略互动与信念互动对征收补偿的影响。本文在行为博弈分析框架下,通过构建房地产征收主体的收益理论模型及蕴含损失规避和公平偏好的效用模型,研究损失规避与公平偏好对房地产征收补偿策略的影响。理论推演与数值模拟结果表明：一是征收补偿与被征收人的损失规避和公平偏好正相关,与征收人的损失规避负相关,与征收人的公平偏好正相关;二是被征收人接受征收的意愿越强,征收补偿越高。鉴于此,本文认为在房地产征收补偿制度设计上应充分考虑对人性的尊重,对现行房地产征收补偿价格进行行为偏好系数修正,降低征收人损失规避偏好、强化公平偏好、让被征收人公平共享土地增值收益,提高信息透明度推动被征收人对征收补偿的合理预期。     

基于EMD与DVG的非线性时间序列预测模型及其应用研究

针对具有非线性和不稳定性的时间序列,提出一种结合经验模态分解(EMD)、有向可见图(DVG)网络的动态预测模型。利用经验模态分解将原时间序列分解为多个固有模态函数(IMF),然后对分解后的高频和低频IMF利用快速傅里叶变换得到各自的周期;依据每个周期,从原时间序列的尾部截取长短不一的子序列,然后采用有向可见图算法转换为多个有向网络,利用随机游走在每个有向网络中寻找与时间序列最后一个节点相似的节点;最后,依据平行线法,预测时间序列的下一个数值。原油价格的时间序列是一类典型的具有非线性和不稳定性的序列,利用此模型对WTI原油每日价格进行实证分析。研究结果表明,此模型不但可以有效地预测时间序列的变化趋势,而且具有较高的预测精度。     

基于修剪平均的神经网络集成时序预测方法

由于复杂时序存在结构性断点和异常值等问题,往往导致预测模型训练效果不佳,并可能出现极端预测值的情况。为此,本文提出了基于修剪平均的神经网络集成预测方法。该方法首先从训练数据中生成多组训练集,然后分别训练多个神经网络预测模型,最后将多个神经网络的预测结果使用修剪平均策略进行集成。相较于简单平均策略而言,修剪平均策略不容易受到极值的影响,能够使集成模型获得鲁棒性强的预测效果。在实证研究中,本文构造了两种神经网络集成预测模型,分别为基于修剪平均的自举神经网络集成模型(Trimmed Average based Bootstrap Neural Network Ensemble, TA-BNNE)和基于修剪平均的蒙特卡洛神经网络集成模型(Trimmed Average based Monte Carlo Neural Network Ensemble, TA-MCNNE),并采用这两种模型对NN3竞赛数据集进行预测,结果表明在常规和复杂数据集上,修剪平均策略比简单平均策略具有更好的预测精度。此外,本文将所提出的集成模型与NN3的前十名模型进行比较,发现两种模型在全部数据集上均超过了第6名,在复杂数据集上的表现均超过了第1名,进一步验证本文所提方法的有效性。     

最短时限运输问题及解法

提出了存在于实际中的最短时限运输问题,研究了其解的最优性充分条件,并给出了求解这一问题的具体步骤,最后用实例说明了解法的可操作性,该解法是解决这一类问题的一个好算法。     

Evaluation of Embedded Intelligent Real‐time Systems*

Over the past two decades, questions have surfaced about the effectiveness and contribution of intelligent systems to decision makers in a variety of settings. This paper focuses on the evaluation challenges associated with intelligent real‐time software systems that are embedded in larger host systems. With the proliferation of such systems in operational settings such as aerospace, medical, manufacturing, and transportation systems, increased attention to evaluations of such systems, and to resulting software safety, is warranted. This paper describes one such evaluation and proposes a set of evaluation criteria for embedded intelligent real‐time systems (EIRTS). Implications of the evaluation and the evaluation criteria are discussed.     

Modeling Finite‐Time Failure Probabilities in Risk Analysis Applications

In this article, we introduce a framework for analyzing the risk of systems failure based on estimating the failure probability. The latter is defined as the probability that a certain risk process, characterizing the operations of a system, reaches a possibly time‐dependent critical risk level within a finite‐time interval. Under general assumptions, we define two dually connected models for the risk process and derive explicit expressions for the failure probability and also the joint probability of the time of the occurrence of failure and the excess of the risk process over the risk level. We illustrate how these probabilistic models and results can be successfully applied in several important areas of risk analysis, among which are systems reliability, inventory management, flood control via dam management, infectious disease spread, and financial insolvency. Numerical illustrations are also presented.     

基于时空约束的大规模农产品时间柔性生产计划网络优化研究

随着农村土地有偿流转, 农民专业合作社、农业企业等各农村经济实体拥有大规模的土地, 为实现农产品规模化生产和集约化经营, 各农村经济实体需要根据土地资源、农业信息、生产技术制定农产品生产计划。鉴于此, 本文主要针对农产品生产计划决策问题先后建立网络、线性和非线性模型。首先根据农产品生产的时空特性和农产品生产时间柔性引入网络流规划构建网络模型;通过网络流量平衡分析, 推导网络模型应满足的约束条件, 结合各农产品的定量化控制, 对大规模农产品生产网络模型进行线性优化;再进一步考虑农产品生产率的影响因素, 构建非线性约束和目标函数对线性模型进行扩展;最后通过具体实例诠释大规模农产品生产计划拟订过程。结果表明, 土地满负荷生产农产品将打破市场的供需平衡, 容易造成"丰产不丰收"现象;利用本文模型制定农产品生产计划, 虽土地有闲置, 但在土地闲置期间, 土地肥力能得到恢复, 各种有机质能得到再生, 有利于为农产品持续生产提供良好的生产条件和环境, 有利于提高农产品的质量和产量, 增加经济效益。     

基于分层网络的机动时间研究

现有网络计划技术的研究主要针对单层网络,难以有效地指导大型项目的生产。原因在于大型工程项目生产过程复杂,工序成千上万,给对应的网络图描述带来了极大的困难。然而,通过网络分层技术则能把一个复杂的网络分解成多个简单的子网络,即将大型网络过渡到几个简单的单层网络,继而利用单层网络技术对其进行分析。本文依据大型网络的构建过程提出简化组合模型,将多层次复杂网络转化为多个单层次简单网络,在此基础上给出分层网络机动时间的计算公式。最后通过一个实例验证了此方法的正确性和可行性。     

The Effects of Multitasking on Operations Scheduling

This study considers a typical scheduling environment that is influenced by the behavioral phenomenon of multitasking. Under multitasking, the processing of a selected job suffers from interruption by other jobs that are available but unfinished. This situation arises in a wide variety of applications; for example, administration, manufacturing, and process and project management. Several classical solution methods for scheduling problems no longer apply in the presence of multitasking. The solvability of any scheduling problem under multitasking is no easier than that of the corresponding classical problem. We develop optimal algorithms for some fundamental and practical single machine scheduling problems with multitasking. For other problems, we show that they are computationally intractable, even though in some cases the corresponding problem in classical scheduling is efficiently solvable. We also study the cost increase and value gained due to multitasking. This analysis informs companies about how much it would be worthwhile to invest in measures to reduce or encourage multitasking.     

Poverty and Self‐Control

We argue that poverty can perpetuate itself by undermining the capacity for self‐control. In line with a distinguished psychological literature, we consider modes of self‐control that involve the self‐imposed use of contingent punishments and rewards. We study settings in which consumers with quasi‐hyperbolic preferences confront an otherwise standard intertemporal allocation problem with credit constraints. Our main result demonstrates that low initial assets can limit self‐control, trapping people in poverty, while individuals with high initial assets can accumulate indefinitely. Thus, even temporary policies that initiate accumulation among the poor may be effective. We examine implications concerning the effect of access to credit on saving, the demand for commitment devices, the design of financial accounts to promote accumulation, and the variation of the marginal propensity to consume across income from different sources. We also explore the nature of optimal self‐control, demonstrating that it has a simple and behaviorally plausible structure that is immune to self‐renegotiation.