四川退耕农户自我发展模式及启示

四川退耕还林工程自1999年启动以来,取得了显著的生态效益和社会经济效益。文章通过对四川退耕还林典型地区的调查,总结出两类主要的退耕农户自我发展模式,并对其优点和存在的问题进行了分析,最后从寻找适合农户自我发展模式,保障农户长远发展和巩固退耕还林成果的角度,总结了许多有益的经验和启示。     

A safe speed guidance model for highways

ABSTRACT

This paper presents a fuzzy logic model to support decisions for the suggested speed limit for sections of highways as they become affected by adverse road conditions, environmental factors and differing traffic levels. The definition of the main factors, and their weight, that reduce safety on highways was conducted by the Delphi method, consulting traffic engineering experts. The survey served as a basis for structuring indicators and indexes in a soft decision tree, structured by a fuzzy logic system. The system can be used to support the decisions of those that manage the roads, indicating to drivers’ speeds, by visual, audible or combined systems.     

Olive oil production and soil conservation in southern Spain, in relation to EU subsidy policies

The European Union spent about two billion ECU per year on subsidies for the olive oil sector, of which Spain received about 35%. For the rainfed areas in southern Spain the olive oil sector is crucial, and so are these subsidies. The European Commission has formulated two options to change the subsidy system, but these do not take the production systems and environmental aspects into account. Many olive plantations are affected by soil erosion. This paper analyses the olive tree production systems in southern Spain, the subsidy systems and the soil erosion problems. It then raises the question whether the subsidies could not be provided in a different way, in order to make olive tree cultivation more sustainable by reducing soil erosion and flood hazard.     

基于台风危害的厦门地区园林树木受损原因研究

基于2016年9月16日1614号台风对厦门绿地的严重影响,通过为期2个月对台风现场实地调研以及相关部门抢险的数据统计,第一时间了解此次台风中厦门重要园林树种的受害状况,分析树木在台风中的受损原因。台风灾害发生后给厦门市的园林树木以及景观带来巨大的损害,因此对于厦门地区园林树木受损原因的研究非常有必要。研究了受损原因后,才可以在灾前以及灾后对重要的园林树木种进行栽培养护管理,增加厦门绿化的抗灾能力以及灾后的及时恢复工作。     

Machine learning for pricing American options in high-dimensional Markovian and non-Markovian models

In this paper we propose two efficient techniques which allow one to compute the price of American basket options. In particular, we consider a basket of assets that follow a multi-dimensional Black–Scholes dynamics. The proposed techniques, called GPR Tree (GRP-Tree) and GPR Exact Integration (GPR-EI), are both based on Machine Learning, exploited together with binomial trees or with a closed form formula for integration. Moreover, these two methods solve the backward dynamic programing problem considering a Bermudan approximation of the American option. On the exercise dates, the value of the option is first computed as the maximum between the exercise value and the continuation value and then approximated by means of Gaussian Process Regression. The two methods mainly differ in the approach used to compute the continuation value: a single step of the binomial tree or integration according to the probability density of the process. Numerical results show that these two methods are accurate and reliable in handling American options on very large baskets of assets. Moreover we also consider the rough Bergomi model, which provides stochastic volatility with memory. Despite that this model is only bidimensional, the whole history of the process impacts on the price, and how to handle all this information is not obvious at all. To this aim, we present how to adapt the GPR-Tree and GPR-EI methods and we focus on pricing American options in this non-Markovian framework.     

太原市古树资源空间分布特征及历史文化价值

太原市古树名木共计3866株,隶属于30科52属62种,以枣树Zizyphus jujuba、国槐Sophora japonica、侧柏Platycladus orientalis、油松Pinus tabulaeformis等乡土树种为主。通过核密度分析发现太原市古树名木在太原市中东部地区形成了9个核密度估计值较高的地区。古树名木数量最多的枣树、国槐、侧柏、和油松的主要聚集区分别位于太原市中部、东部和南部、南部地区、以及中部和东北部地区。并依据历史文献资料,从民间习俗,宗教信仰,古城历史等角度阐述这四种主要树种蕴含的历史文化价值。