基于改进指纹聚类的WLAN定位优化方法

将K-means聚类算法应用到无线局域网（WLAN）位置指纹定位中，虽然可以缩短定位时间，但是容易降低定位精度。为了解决此问题，提出了基于改进指纹聚类的WLAN定位优化方法。首先根据接收信号强度标准差来优化初始聚类中心的选取,然后对指纹数据进行聚类处理,最后进行在线定位。实验结果表明，与传统的WLAN位置指纹定位方法和K-means聚类定位方法相比，基于改进指纹聚类的定位优化方法不仅缩短了定位时间，还能有效提高定位精度。     

基于PSO的信息熵数据融合非均匀分簇路由算法

针对无线传感器网络分簇算法中能量分布不均衡导致的"热区"和簇头负载过重问题,提出了一种基于PSO算法优化簇头选举的非均匀分簇算法。在候选簇头选举和竞争半径计算过程中综合考虑节点动态能量、节点密度和节点距基站距离,将网络进行非均匀分簇,并引入PSO算法进行最终簇头选举。根据节点能量、节点密度和距基站距离确定簇间单跳多跳结合的路由规则,选取代价函数小的节点作为下一跳节点。基于节点信息熵确定融合阈值,进行簇内数据融合剔除冗余数据。仿真结果表明,改进算法的数据传输量比EEUC算法和UCRA算法分别提高了20%和10%,提升了数据的融合效率,有效延长了网络生命周期,簇头能量消耗得到均衡,减少了网络能量消耗,网络的整体性能显著优于其他对比算法。     

Payments for agrobiodiversity conservation services: An overview of Latin American experiences,lessons learned and upscaling challenges

Many developing countries face a major challenge today: how to safeguard the biodiversity maintained in the fields of the rural poor - which constitute a national and global public good - whilst meeting those same people's development needs and rights? A solution to this dilemma has thus been sought in adapting the design and implementation of Payments for Ecosystem Services (PES) concepts to the conservation of agrobiodiversity.Here we review the application of nine such Payments for Agrobiodiversity Conservation (PACS) schemes that have been applied to date in four Latin American countries over the period 2010–2018. These covered 130 threatened varieties across a number of major food crops, and involved over 100 farming communities and 1,100 farmers (45 % of which were women). Conservation service offers were received through a competitive tender mechanism. Average bid offers revealed high heterogeneity, varying between US$675/ha. to ten times as much.In relation to issues identified as key to PES, such as spatial targeting, differentiated payments and conditionality, the underlying design of the PACS schemes may be considered solid. PACS-related prioritisation processes allow for the a priori identification of sites with high ecosystem service densities and high threat levels. The use of competitive tenders permits accounting for cost heterogeneity in the provision of conservation services and for payments to be differentiated. Conditionality is strong.In terms of implementation, a “back of the envelope” calculation based on the results of the competitive tenders suggests that conservation costs are modest. For a priority conservation portfolio of 100 varieties (which may be from different crops) each with a target area of five hectares, costs would amount to just under US$860,000 over twenty years or US$70,000 p.a. at a 5 % discount rate. The small-scale and one-off nature of the interventions realised to date, along with threatened crop variety seed availability constraints, have however meant that environmental effectiveness has been incomplete in the short-term (area cultivated with specific threatened varieties increased, but still below the “not at risk” threshold). The establishment of systematic monitoring systems is required to determine longer-term impacts and inform more regular PACS interventions within a dynamically evolving systems context.     

The role of text-extracted investor sentiment in Chinese stock price prediction with the enhancement of deep learning

Whether investor sentiment affects stock prices is an issue of long-standing interest for economists. We conduct a comprehensive study of the predictability of investor sentiment, which is measured directly by extracting expectations from online user-generated content (UGC) on the stock message board of Eastmoney.com in the Chinese stock market. We consider the influential factors in prediction, including the selections of different text classification algorithms, price forecasting models, time horizons, and information update schemes. Using comparisons of the long short-term memory (LSTM) model, logistic regression, support vector machine, and Naïve Bayes model, the results show that daily investor sentiment contains predictive information only for open prices, while the hourly sentiment has two hours of leading predictability for closing prices. Investors do update their expectations during trading hours. Moreover, our results reveal that advanced models, such as LSTM, can provide more predictive power with investor sentiment only if the inputs of a model contain predictive information.     

Optimal capacity and operation design of a robot logistics system for the hotel industry

This study introduces an optimal capacity and operation design of a robot logistics system that can reduce human workload in the hotel industry. In hotels, there are several duties that can be replaced by robots such as accompanying guests to the certain areas, delivering specific items to the guest rooms, and transporting some items that guests want to be removed from the guest rooms. To apply the robot logistics system in the hotel industry, the capacity and operation design should be prepared adequately. For that, a mathematical model-based optimization technique is used to decide the number of robots with the concept of minimizing total investment cost and to derive the optimal job assigning with the purpose of maximizing total covered jobs. In addition, a numerical example is performed to validate the proposed mathematical model and the sensitivity tests are examined to reflect the random features.     

基于改进Dijkstra算法的最短路算法

Dijkstra算法是求解最短路径问题的经典算法。在现如今的城市交通网络中,经常需要寻求两个地点之间的最短距离,减少运输时间。本文将Dijkstra算法与C语言相结合,对Dijkstra算法进行改进,根据实际网络图的情况,建立了相应的数学模型,运用C语言编程,在给定的网络图中,实现了只需确定起始点和终点,就可以直接输出最短路径和最短距离的功能。在有多个相同最短路径的情况下,会将多个最短路径一起输出,在搜索到终点时,立即跳出,结束循环。在一般情况下,无需对所有点进行迭代,提高了效率。这种方法可以应用到现在的物流运输中,以此来节约时间,降低成本。     

南太行綦村岩体中辉石的成因矿物学研究

通过对不同岩石中的辉石进行了详细的成因矿物学研究,结果表明綦村岩体不同岩性中的辉石可以分为两类:一类是岩浆系统中早期结晶形成的晶体,被后期的岩浆携带至地壳浅部,另一类是岩浆定位以后结晶的自生晶。在辉石的分类中大部分辉石属于透辉石,有少量是普通辉石。尽管在不同岩性中辉石的成分存在一定差异,但是所有辉石成分都指示綦村岩体的母岩浆属于亚碱性系列,其在演化过程中经历了辉石和角闪石的结晶分离过程,这一过程导致岩浆中的镁元素在早期形成的辉石和角闪石中富集,铁元素在残余熔体中富集,并在岩浆定位后随流体出熔成矿。     

基于SBO-PP模型的水资源可持续发展能力评价模型及应用

为利用投影寻踪(PP)技术科学,客观评价区域水资源可持续发展能力,基于生态环境、水资源和经济社会因素选取20个指标构建区域水资源可持续发展能力评价指标体系。利用新型仿生群体智能算法——凉亭鸟优化(SBO)算法优化PP技术最佳投影方向,提出SBO-PP水资源可持续发展能力评价模型,并构建灰狼优化(GWO)算法-PP模型、人工蜂群(ABC)算法-PP模型、差分进化(DE)算法-PP模型、地理生物学优化(BBO)算法-PP模型、粒子群优化(PSO)算法-PP模型作对比,以云南省2006—2015年及2020年水资源可持续发展能力评价为例进行实例研究。结果表明:SBO算法优化PP技术获得的适应度值优于GWO、ABC、DE、BBO和PSO算法,具有较好的求解精度、稳健性能和极值寻优能力。SBO-PP模型对云南省2006—2007年水资源可持续发展能力评价为"较差",2008—2015年评价为"中等",2020年评价为"较强"。     

A genetic algorithm based approach to transactional and QoS-aware service selection

As there are various risks of failure when Web services are deployed in unreliable environment, the execution of a composite Web service (CWS) requires the transaction mechanism to guarantee its reliable execution. However, the existing service selection approaches consider QoS and transaction separately and have not considered that transactional properties may affect the QoS such as the execution time of a CWS. This work addresses the importance of considering transactional properties and how the transactional properties affect the QoS simultaneously in the process of service selection by a QoS-aware and transactional-aware selection approach. First, a performance evaluation method is proposed to calculate the execution time of a transactional CWS. Then, a genetic algorithm based approach, which takes into account the execution time, price, transactional property and successful execution rate of CWS, is presented to achieve global optimisation service selection. Finally, experimental results show the efficiency and effectiveness of the approach.     

Structured deplaning via simulation and optimization

Deplaning naturally occurs row by row down the length of an aircraft. Using simulation and optimization, we design deplaning strategies (e.g., deplane by group and/or column) that significantly reduce the overall unstructured deplaning time. The evaluations derived from a combination of optimization and simulation were tested across several equipment types using data gathered through field observations for calibration.