耕地利用多功能权衡关系测度与分区优化 ——以河南省为例

研究目的:分析河南省耕地利用多功能空间分布特征、多功能权衡关系区域差异,提出分区优化管控措施。研究方法:耦合协调度方法、权衡强度方法。研究结果:(1)河南省各县(区)耕地利用多功能呈现明显的空间异质性,中原城市群生产功能和社会保障功能优势明显,黄淮平原生产—生态功能强;(2)多功能协调度、权衡强度空间差异明显,中原城市群和豫北地区协调程度高、权衡强度低;(3)全省可耕地划分为多功能高协调区、多功能低协调区、单功能主导区、生产—生态协调区、生产—社会保障协调区、生态—社会保障协调区6大区域。研究结论:研究结果与河南省区域发展战略定位相符,揭示河南省耕地利用多功能分布和权衡关系,划分不同类型区并提出优化建议,为河南省农业空间管控提供决策支持。     

The evolving 5G case study in United States unilateral spectrum planning and policy

This paper tracks increasingly aggressive initiatives by the United States government to reallocate spectrum on an expedited and unilateral basis well before conclusion of inter-governmental coordination. Rather than embrace the customary commitment to achieve consensus on global spectrum allocations at the International Telecommunication Union (“ITU”), the Federal Communications Commission (“FCC”) has auctioned off large blocks of frequencies for the next generation (“5G”) of wireless services.The FCC might have framed its first 5G auction, reassigning Ultra High Frequency (“UHF”) spectrum, as a one-time deviation from compliance with long standing, intergovernmental coordination procedures. These frequencies have ideal signal propagation characteristics and the Commission could use financial incentives—unavailable in most nations—to expedite “repacking” by incumbent broadcasters willing to move, share or abandon spectrum in exchange for ample financial compensation. However, the FCC has continued to auction off 5G spectrum on grounds that it must find ways to abate an acute shortage of wireless bandwidth and doing so will regain or maintain global leadership in wireless technologies. This paper offers a critical rebuke to unilateral spectrum management, because the short-term benefits expected by the U. S. government likely will be offset by countervailing harms to 5G manufacturers, carriers and consumers. The paper tracks fractious preparation for the ITU's 2019 World Radio Conference by the U.S. delegation and the mixed record achieved there. Additionally, the paper explains how injecting trade, industrial policy and national security issues at the ITU can trigger more delays and disputes, including possible retaliation by nations displeased with U.S. efforts to subvert traditional technology optimization goals.A worst case scenario has the ITU deadlocked and unable to reach closure on “mission critical” spectrum planning issues at World Radio Conferences, convened every four years. The paper concludes that costs and likely challenges to the efficacy and legitimacy of the ITU will reduce the benefits accruing from the FCC's unilateral, spectrum planning campaign.     

基于两阶段法的多车型卷烟配送路径优化研究

在烟草商业企业中,物流是其重要的环节,是连接客户与烟草企业间的纽带,其卷烟配送线路设计的合理与否直接影响到卷烟的配送效率和配送成本,就如何合理的规划线路成为卷烟配送的关键问题。文章以Q烟草公司为例,运用先分组后路线的两阶段法对问题进行求解,先利用K-means聚类算法对区域进行划分,再考虑工作量均衡的条件下引入遗传算法对区域进一步调整,最后利用混合遗传算法对各配送区域进行线路优化,通过实例从线路数、车辆数、空载率、配送里程及总成本等指标上可以看出两阶段法的配送效果更优。     

基于粒子群算法下的交叉口信号配时优化

为了合理地优化交叉口信号配时,通过分析交叉口的评价指标,建立了以车辆的平均延误、停车次数最小、交叉口整体通行能力最大、各相位有效绿灯时间和交叉口周期时长作为约束条件的数学模型。并通过改进前人研究基础上的动态加权系数,将多目标的非线性优化问题转化为单一目标的非线性规划问题,为了得出更科学稳定的解,提出了改善粒子群算法系统稳定性的2种方法,并将其与粒子群算法结合起来。然后以Matlab为求解工具,结合临邑市某一交叉口实例进行求解分析。最后的结果表明,在使用改进后的粒子群算法进行优化后交叉口通行能力较之现状提升了9%,延误下降了28%,停车次数下降了9%,且各项优化结果均优于Webster,改进后的算法在程序中运行300代,到216代才开始收敛,而未改进的算法稳定性较差,优化结果和收敛曲线则随着实验次数的变化而变化,最后的结论证明了该算法和模型的可靠性。     

基于PSO-SAS的联合侦察任务规划

针对联合侦察筹划中任务规划阶段机动侦察平台阵位与路线确定困难的问题，提出了一种基于粒子群优化-稀疏A星(Particle Swarm Optimization—Sparse A-star,PSO-SAS)算法的规划方法。该方法综合考虑侦察装备机动性能以及敌火力威胁、地形等因素，在侦察阵位规划上，建立了阵位综合评估模型，并利用粒子群算法进行阵位寻优；在路线规划上，采用稀疏A*算法进行航迹规划，通过将机动性能、安全距离、路程等约束引入搜索过程，缩短最优路线的计算时间。仿真试验验证了所提方法生成的侦察阵位和路线能够满足侦察任务要求。     

利用双正交小波变换优化G3-PLC系统性能

为了提高G3-PLC(G3-Power Line Communication)在复杂信道环境下通信的可靠性，提出了基于双正交小波变换的正交频分复用（Discrete Wavelet Transform-Orthogonal Frequency Division Multiplexing,DWT-OFDM）。通过双正交小波变换减小复杂信道环境下G3-PLC通信系统中OFDM载波间干扰，并通过合理减少循环前缀，优化传输效率，降低峰均比。在DWT-OFDM的G3-PLC系统中，通过不同小波基性能分析与对比，利用bior6.8双正交小波基进行系统性能优化。将DWT-OFDM的G3-PLC系统在实际电力线噪声库环境下进行实验分析，仿真结果表明，在平均误码率为10-3量级时，性能有5 dB左右提升，通信效率由40%提高至54%；结合限幅法，峰均比由11 dB降低至8 dB，通信性能极大优于基于FFT-OFDM的G3-PLC系统。     

基于减缓热岛效应的公园绿地布局 优化研究

城市化进程加快导致城市热岛效应问题日益突出， 公园绿地在降温方面具有重要作用，如何通过公园绿地布局以 减缓热岛效应是当前值得思考的问题。以福州市主城区为研究 区，利用辐射传输方程和泰森多边形分析城市热岛情况及公园 绿地布局现状，采用P-中值模型结合城市用地规划确定公园 绿地布局优化方案，结果表明：1)福州市主城区的整体温度偏 高，其热岛范围达城市总面积的11.78%；2)共提取福州市主 城区公园绿地47个，总面积为11.11km2，占主城区总面积 的4.47%，公园绿地布局总体不能满足人们的需要；3)利用 P-中值模型对公园绿地供需情况进行分析，得出18个公园绿 地需要优化，其中包括福州动物园、环南公园等12个一级优化 公园绿地，以及屏山公园、琴亭湖公园等6个二级优化公园绿 地；4)结合福州市中心城区用地规划，得到50个潜在公园绿 地建设点，主要集中于城门镇、盖山镇及新店镇。     

Optimizing a portfolio of mean-reverting assets with transaction costs via a feedforward neural network

Optimizing a portfolio of mean-reverting assets under transaction costs and a finite horizon is severely constrained by the curse of high dimensionality. To overcome the exponential barrier, we develop an efficient, scalable algorithm by employing a feedforward neural network. A novel concept is to apply HJB equations as an advanced start for the neural network. Empirical tests with several practical examples, including a portfolio of 48 correlated pair trades over 50 time steps, show the advantages of the approach in a high-dimensional setting. We conjecture that other financial optimization problems are amenable to similar approaches.     

Research on a stock-matching trading strategy based on bi-objective optimization

In recent years, with strict domestic financial supervision and other policy-oriented factors, some products are becoming increasingly restricted, including nonstandard products, bank-guaranteed wealth management products, and other products that can provide investors with a more stable income. Pairs trading, a type of stable strategy that has proved efficient in many financial markets worldwide, has become the focus of investors. Based on the traditional Gatev–Goetzmann–Rouwenhorst (GGR, Gatev et al., 2006) strategy, this paper proposes a stock-matching strategy based on bi-objective quadratic programming with quadratic constraints (BQQ) model. Under the condition of ensuring a long-term equilibrium between pairedstock prices, the volatility of stock spreads is increased as much as possible, improving the profitability of the strategy. To verify the effectiveness of the strategy, we use the natural logs of the daily stock market indices in Shanghai. The GGR model and the BQQ model proposed in this paper are back-tested and compared. The results show that the BQQ model can achieve a higher rate of returns.     

A Novel Compact Cat Swarm Optimization Based on Differential Method

ABSTRACT

A compact cat swarm optimization scheme (cCSO) is proposed in this paper, which is designed to solve application domains plagued with limited memory and less-computation power, as a member of cat swarm optimization algorithms (CSO), it composes of two sub-modes, i.e., tracing and seeking modes, so it keeps the same search logic of CSO. On the other hand, cCSO inherits the main feature of compact algorithms, a normal probabilistic model is used to represent the population of solutions instead of processing an actual population, which ensures the cCSO to have the modest memory requirement. The updating vector for the probabilistic model provides a clear moving direction for cats in next step. A cat without historical position and velocity is applied in the algorithm. When the cat is in seeking mode, it employs a differential operator to update the cat’s position, which makes it possible for the cat to have multiple searching directions. Experimental results show that cCSO has pretty performance compared with respect to some population-based testing benchmarks. And it also shows superior performance in convergence rate to some compact optimization algorithms. The case study of gray image segmentation proves that it suits for solving the optimization problem by limited hardware.