Local models-based regression trees for very short-term wind speed prediction

This paper evaluates the performance of different types of Regression Trees (RTs) in a real problem of very short-term wind speed prediction from measuring data in wind farms. RT is a solidly established methodology that, contrary to other soft-computing approaches, has been under-explored in problems of wind speed prediction in wind farms. In this paper we comparatively evaluate eight different types of RTs algorithms, and we show that they are able obtain excellent results in real problems of very short-term wind speed prediction, improving existing classical and soft-computing approaches such as multi-linear regression approaches, different types of neural networks and support vector regression algorithms in this problem. We also show that RTs have a very small computation time, that allows the retraining of the algorithms whenever new wind speed data are collected from the measuring towers.     

层序地层模式浅析

维尔等人（１９８８，１９８９）提出的层序地层立体模式，可以说是他们的层序地层学新概念立论的基础，也是他们赖于进行地层和岩相解释的依据。然而，这一模式的实质，仍未超越传统地质概念的范畴。除了术语上的差别外，它与经典的海进－海退旋回性层序模式没有根本的差别。     

Statistical Data Analysis in the Era of Big Data

Big data is on everyone's lips and often raises emotions. On the one hand, the notion is a basis for much technological optimism, mostly directed towards new business models, or simplifications and optimizations in professional and private life. On the other hand, it is a basis for dystopic perspectives, which are targeted, e.g., at profiling of the individual and their privacy space, overarching optimization in daily life and intransparency of decision making. In this article, after a short historical prolog, it is discussed what distinguishes big data from traditional data analysis. The underlying mathematical methods are introduced and scientific successes are reported. Additionally, the risks and limits – especially regarding the derivation of causal relationships – of data analysis are discussed.     

A regression model for prediction of pipe conveyor belt contact forces on idler rolls

The paper presents design and verification of regression models for prediction of pipe conveyor belt contact forces on idler rolls. Their advantage is in the fact that they have been created according to the real experimental measurement. The obtained models correspond with real operational conditions. The concept of the experimental rig at the Technical University of Košice is designed so that it represents 8 m long section of pipe conveyor. The conveyor belt is an object with action of tension force and at the same time it takes the initiative in the contact force formation. Several criteria have been used to verify the presented regression models. The tensioning force 9000, 12,000 and 15,000 N have MPE of prediction error less than 5%. About 120,000 measured values have been processed during the evaluations which correspond to approximately 15,000 results from experimental measurements.     

Application of near infrared spectroscopy for the rapid determination of antioxidant activity of bamboo leaf extract

This study was carried out to evaluate the feasibility of using near infrared (NIR) spectroscopy for determining three antioxidant activity indices of the extract of bamboo leaves (EBL), specifically 2,2-diphenyl-1-picrylhydrazyl (DPPH), ferric reducing/antioxidant power (FRAP), and 2,2′-azinobis-(3-ethylbenz-thiazoline-6-sulfonic acid) (ABTS). Four different linear and nonlinear regressions tools (i.e. partial least squares (PLS), multiple linear regression (MLR), back-propagation artificial neural network (BP-ANN), and least squares support vector machine (LS-SVM)) were systemically studied and compared in developing the model. Variable selection was first time considered in applying the NIR spectroscopic technique for the determination of antioxidant activity of food or agricultural products. On the basis of these selected optimum wavelengths, the established MLR calibration models provided the coefficients of correlation with a prediction (r_pre) of 0.863, 0.910, and 0.966 for DPPH, FARP, and ABTS determinations, respectively. The overall results of this study revealed the potential for use of NIR spectroscopy as an objective and non-destructive method to inspect the antioxidant activity of EBL.     

吴旗油田吴410井区长6油层组流动单元研究

本文以吴旗油田吴93井区油藏为例,在吴93井区沉积微相、储层综合分析评价的基础上,选取有效厚度、渗透率、孔隙度、含油饱和度、渗流系数、储能系数、流动层指数和油藏品质指数等八个参数进行流动单元的划分。将长6油藏划分为A,B,C和D四类流动单元。划分结果表明,吴93井区长611和612是该区长6油藏的主力油层,各类流动单元与储层岩性、物性和沉积微相具有很好的对应关系。本次流动单元划分的参数取值,综合评价函数与评价指标,可以客观地反映低渗、低孔、储层物性差、非均质性强等地质特征。     

回归方程在标准加入法测高岭土中铜的应用

用原子吸收光谱法测定高岭土中铜,分别用标准曲线法及标准加入法定量分析铜元素含量,比较了作图法和回归方程法处理标准加入法数据。结果表明,随铜元素变量,标准曲线法及标准加入法均有较好的线性关系,但测定的结果有差异。标准加入法因可消除基体干扰,测得铜结果准确度高。标准加入法适合基体复杂的试样的分析。作图法及回归方程均适用于标准加入法测铜的数据处理,作图法误差大,而回归方程法是快捷,误差小的简便方法。     

Surface Analysis of Chesapeake Bay Water Quality Response to Different Nutrient and Sediment Loads

Based on a set of Chesapeake Bay Estuarine Model (CBEM) scenarios, a three-dimensional response surface of a water quality index, such as chlorophyll concentration, versus a pair of loading constituents, e.g., nitrogen and phosphorus, is constructed. The responses of water quality, such as dissolved oxygen, chlorophyll, and water clarity, to nitrogen, phosphorus, and sediment loads are analyzed. From the response surface, a water quality response is estimated under loading conditions beyond that of a limited set of scenarios. Response surfaces may be used to determine the possible universe of nutrient and sediment load reductions needed to obtain a particular water quality standard and to examine the tradeoffs among nutrient and sediment load reductions that achieve the same water quality objective.     

社会责任与企业绩效的相关性研究--基于中国采矿业数据分析

以采矿业在深沪两市上市的67家 A 股上市公司为样本,对样本公司从2010年到2012年的社会责任与企业绩效进行了实证分析。分析结果表明,采矿业社会责任与企业绩效之间具有线性关系;债权人责任、股东责任、国家责任与企业绩效显著正相关;员工责任、社会责任、环境责任与企业绩效具有相关性。     

我国城镇居民消费与收入关系分析——基于地理加权回归模型（GWR）的实证分析

空间数据一般具有空间非平稳性的特点,究其原因是地理空间上的区域缺乏均质性,存在高消费地区和低消费地区、中心（核心）和外围（边缘）等经济地理结构,从而导致我国城镇居民消费存在较大的空间差异性。对此,本文试图采用地理加权回归模型来分析我国城镇居民消费与收入的关系,从实证分析的结果提出几点建议和对策。