南京红山森林动物园场馆的建筑结构

南京红山森林动物园有三大展区,39个设计新颖的动物场馆,是南京的著名旅游景点之一。该课题对南京红山森林动物园场馆的建筑构造、设计、创意等进行了详细的论述。     

北京八达岭国家森林公园景观评价

近年来,旅游业成为促进城乡融合、推动居民就业的重要举措.许多内陆城市将投资的重心转向了辖区内有着独特地理优势的大面积林区,因此对森林公园景观进行评价对推动旅游业具有重要意义.本文以北京八达岭国家森林公园为研究对象,依据《中国森林公园风景资源质量等级评定》,基于层次分析法对森林公园风景资源建立评价体系,并提出相应意见.主...     

Measuring financial soundness around the world: A machine learning approach

We use a fully data-driven approach and information provided by the IMF’s financial soundness indicators to measure the condition of a country’s financial system around the world. Given the nature of the measurement problem, we apply different versions of principal component analysis (PCA) to deal with the presence of strong cross-sectional and time dependence in the data due to unobserved common factors. Using this comprehensive sample and various statistical methods, we produce an alternative data-driven measure of financial soundness that provides policy makers and financial institutions with a monitoring and policy tool that is easy to implement and update. We validate our index by using alternative macroeconomic factors, confirming its predictive power. Our index captures important aspects of financial intermediation around the world.     

A random forest-based model for crypto asset forecasts in futures markets with out-of-sample prediction

In this study, a price prediction model for futures markets of crypto assets is presented. Random Forest was used to study three scenarios as a function of input variables: technical indicators, candlestick patterns and both simultaneously. In turn, the model parameters, the time intervals, and the most suitable investment horizons were studied. In addition to showing the results from the model, a one-year out-of-sample prediction was simulated. The entire year of 2020 was chosen because the three possible stock market scenarios occurred in this year: a sideways market, a bear market resulting from the global pandemic and an end-of-year bull market. Last, this out-of-sample simulation was analyzed as a real operation, that is, by retraining the model after each new collection of data, so that the model had the maximum information at all times. In conclusion, using candlestick patterns instead of technical indicators, improves the efficiency of the results.     

“互联网+”背景下林业电商发展策略探究

“互联网+”背景下,电子商务已经成为许多传统产业转型的重要手段,同时催生了众多热门的第三方购物平台,现代信息技术与电商的融合也为许多传统产业注入了新的活力,让传统产业变得“信息化、智慧化”,实现了质的飞跃。林业作为我国传统的基础产业,正处于向电商转型的初级阶段。以林业电商为探讨对象,分析了我国林产品销售过程中存在的共性问题,并结合实际与经验从人才引进、物流运输、品牌打造、信息获取等方面提出了相关建议。     

专利转化特征精准识别与预测——以人工智能芯片为例

探讨前沿科技领域专利转化特征并对其进行精准识别与预测，对于我国破解“卡脖子”技术难题及实现科技自立自强具有重要意义。选取人工智能芯片专利领域，采用机器学习算法测度最优转化预测方案，分析全球范围内主要国家或地区专利成功转化影响因素，从企业/高校、国内/国际等不同层面总结专利成功转化的主要特征。结果发现：随机森林算法预测效果较好，人工智能芯片领域专利转化概率服从对数曲线分布，影响高校/企业、国内/国外专利转化特征的因素有所不同。最后，提出高校/科研机构应注重高价值专利维持和团队合作、企业应提升专利技术质量和撰写质量等政策建议。