基于VB.NET MapObjects的人口统计GIS研究

组件技术是当前GIS软件业的潮流。系统以安徽县域人口统计GIS为案例,基于.NET环境,将数据库技术、数学模型与GIS技术应用到人口统计信息管理当中,开发了重心模块、洛伦茨模块、人口金字塔模块与GM(1.1)人口预测等模块,完成了人口统计信息与地理空间信息的集成,实现了地图浏览、统计查询、专题制图、模型分析等功能。其强大的空间分析和可视化功能增强了人口统计信息的表现力,将进一步拓展人口统计GIS在相关领域的应用。     

文化算法研究

文中介绍一种新的进化计算构架——文化算法。文化算法分别从微观（种群空间）和宏观（信念空间）两个层面上模拟文化的双重进化继承过程。从进化角度看,任何一种符合文化算法要求的计算构架或符号表达都能被用来描述文化算法框架中的种群空间和信念空间。文中叙述了文化算法的发展背景,阐述了文化算法的特点、适用范围及基本原理,回顾了其发展历程以及应用,给出了结论和进一步的研究方向。     

基于IGD+指标的两阶段选择高维多目标进化算法

针对在高维空间下多目标进化算法难以维持种群收敛性和多样性平衡的问题, 本文提出一个基于IGD+指标的两阶段选择高维多目标进化算法(MaOEA–ITS). 在第1阶段, 算法基于IGD+指标选择收敛性良好的精英个体, 其所需的参考点通过引入切割平面截距法构建. 在第2阶段, MaOEA–ITS使用模糊c均值算法对参考向量进行聚类, 聚类后的参考向量引导种群分解策略对剩余个体进行环境选择, 从而维持种群的多样性. 另外, 为了保护能够提高种群多样性的极值解, 本文提出一个参考点分布自适应策略. 最后, 通过仿真实验来验证MaOEA–ITS的有效性和优越性.     

德国老年人药物管理系统设计研究

目的针对德国老年人用药问题进行分析,运用智能药物管理系统,提出解决方案。方法重点分析了德国人口老龄化产生的健康问题,阐述了老年用药方面的问题,提出了用药过程中针对患者、医生、药店有机结合的智能药物管理系统的设计原则和案例。结论人口的老龄化和老年人的健康是全球面临的问题,在"互联网+"健康的基础上,设计人性化的智能药物管理系统,可以为老年人健康生活带来更多的便利。     

Fractional Order Nonlinear Bone Remodeling Dynamics Using the Supervised Neural Network

This study aims to solve the nonlinear fractional-order mathematical model (FOMM) by using the normal and dysregulated bone remodeling of the myeloma bone disease (MBD). For the more precise performance of the model, fractional-order derivatives have been used to solve the disease model numerically. The FOMM is preliminarily designed to focus on the critical interactions between bone resorption or osteoclasts (OC) and bone formation or osteoblasts (OB). The connections of OC and OB are represented by a nonlinear differential system based on the cellular components, which depict stable fluctuation in the usual bone case and unstable fluctuation through the MBD. Untreated myeloma causes by increasing the OC and reducing the osteoblasts, resulting in net bone waste the tumor growth. The solutions of the FOMM will be provided by using the stochastic framework based on the Levenberg-Marquardt backpropagation (LVMBP) neural networks (NN), i.e., LVMBPNN. The mathematical performances of three variations of the fractional-order derivative based on the nonlinear disease model using the LVMPNN. The static structural performances are 82% for investigation and 9% for both learning and certification. The performances of the LVMBPNN are authenticated by using the results of the Adams-Bashforth-Moulton mechanism. To accomplish the capability, steadiness, accuracy, and ability of the LVMBPNN, the performances of the error histograms (EHs), mean square error (MSE), recurrence, and state transitions (STs) will be provided.     

设计引导合理健康的生活方式

设计,虽然不是生产力,它不能决定社会、经济、甚至生态环境的发展,但是它的本质特征所表现出的那种协调性,却起到了很大的引导作用,在人类共同的大课题面前,只有设计能担负起"创造更合理,更健康的生活方式"的历史使命。     

基于强化学习的多策略选择遗传算法

为解决传统遗传算法早熟收敛和收敛速度慢的问题,提出一种基于强化学习的多策略选择遗传算法MPSGA。通过使用不同的选择策略将整个种群划分为3个子种群并分别进化,能提高种群的多样性,有效避免遗传算法的早熟收敛问题。将种群的多样性和算法的运行机制相结合,根据种群多样性的变化运用强化学习算法动态地优化各子种群间的比例参数,从而将种群多样性保持在合适的范围,一定程度上解决了收敛速度和全局收敛性之间的矛盾。实验结果表明,该算法在收敛精度和搜索效率上都表现出较好的性能。     

Low-complexity joint transmit and receive antenna selection for MIMO systems

In this paper, we present a low-complexity algorithm for real-time joint transmit and receive antenna selection in MIMO systems. The computational complexity of exhaustive search in this problem grows exponentially with the number of transmit and receive antennas. We apply Binary Particle Swarm Optimization (BPSO) to the joint transmit and receive antenna selection problem. In addition, applying the general BPSO to joint antenna selection, we also present a specific improvement to this population-based heuristic algorithm, namely, we feed cyclically shifted initial population so that the average convergence time (the number of iterations until reaching an acceptable solution) is reduced. The proposed BPSO for joint antenna selection problem has a low computational complexity, and its effectiveness is verified through simulation results.     

Random linear-quadratic mathematical models: Computing explicit solutions and applications

This paper deals with the study of linear random population models and with a random logistic model (where parameters are random variables). Assuming appropriate conditions, the stochastic processes solutions are obtained under closed form using mean square calculus. Expectation and variance expressions for the stochastic processes solutions are given and illustrative examples are included.     

Replica Exchange Light Transport

We solve the light transport problem by introducing a novel unbiased Monte Carlo algorithm called replica exchange light transport, inspired by the replica exchange Monte Carlo method in the fields of computational physics and statistical information processing. The replica exchange Monte Carlo method is a sampling technique whose operation resembles simulated annealing in optimization algorithms using a set of sampling distributions. We apply it to the solution of light transport integration by extending the probability density function of an integrand of the integration to a set of distributions. That set of distributions is composed of combinations of the path densities of different path generation types: uniform distributions in the integral domain, explicit and implicit paths in light (particle/photon) tracing, indirect paths in bidirectional path tracing, explicit and implicit paths in path tracing, and implicit caustics paths seen through specular surfaces including the delta function in path tracing. The replica‐exchange light transport algorithm generates a sequence of path samples from each distribution and samples the simultaneous distribution of those distributions as a stationary distribution by using the Markov chain Monte Carlo method. Then the algorithm combines the obtained path samples from each distribution using multiple importance sampling. We compare the images generated with our algorithm to those generated with bidirectional path tracing and Metropolis light transport based on the primary sample space. Our proposing algorithm has better convergence property than bidirectional path tracing and the Metropolis light transport, and it is easy to implement by extending the Metropolis light transport.