基于Logistic回归模型的人口预测分析

Logistic函数在人口、资源、环境和生态诸多系统的预测中是一个非常重要的模型．然而,Logistic模型中参数的确定又是一件较困难的事情．本文基于数值微分和最小二乘曲线拟合对Logistic回归模型进行参数估计,据此计算了我国1980年到2005年总人口数的误差,并预测了2015年我国的人口总数。     

基于BP神经网络的校园用水预测模型

校园人口密集,用水量大,对某一栋教学楼或某一区域的定量用水预测,对于发现用水异常、合理下达用水指标有实际意义.本文利用BP神经网络,结合校园用水的特点,建立校园用水预测模型,并以实际数据进行验证,证明其有效性.     

基于灰色系统理论的交通事故预测模型

交通事故的发生是一个典型的灰色系统,利用灰色理论的GM(1,1)模型建立了交通事故起数、死亡人数、受伤人数及直接经济损失预测模型,并利用某市31个月的交通状况数据验证了模型有较好的精确度。     

回归分析与学生进步程度的评价

本文讨论一元回归分析方法在成绩评价中的应用.给出了学生进步程度的定义、成绩预测和综合成绩评价的公式,将自变量取值中心化后简化了学生进步程度的计算公式.     

郑州市机动车新车入户量预测研究

对郑州市2009～2012年机动车新车入户量的数据进行一阶弱化算子处理,然后建立新车入户量的灰色模型GM(1,1),并预测了未来5年郑州市机动车新车入户量.     

《市场调查和预测》中直线方程的系数求解方法探讨

《市场调查和预测》是市场营销专业和工商管理专业的一门必修课程,市场预测的时间序列法和因果分析法中经常会提到直线方程,关于直线方程的系数求解,不同情况下可以用不同的方法解决,为了帮助学生理解记忆、提高教学效果,现专门针对直线方程的系数求解及应用范围进行例题讲解并归纳总结．     

灰色多变量模型在运动员竞技能力发展预测中的应用研究

从探讨运动员竞技能力系统发展的一般特征出发,结合实例介绍灰色多变量预测模型在运动员竞技能力系统发展中的建模、预测方法,并通过与单因素模型的实际对比,阐述灰色多变量预测模型的实用价值和应用前提,为运动训练及其他体育领域的灰色预测提供了一种方法与思路。     

关于"计算机未来学"学科理论的思索

计算机未来学是关于计算机科学、技术及其产品的未来发展趋势的学科.开展"计算机未来学"新学科研究,对计算机科学的发展进行宏观研究,从整体上、宏观上把握计算机科学的发展趋势,这对制定正确的计算机科学发展策略,调整研究起点和开发方向,有着指导性的意义.     

Methods to account for citation inflation in research evaluation

Quantitative research evaluation requires measures that are transparent, relatively simple, and free of disciplinary and temporal bias. We document and provide a solution to a hitherto unaddressed temporal bias – citation inflation – which arises from the basic fact that scientific publication is steadily growing at roughly 4% per year. Moreover, because the total production of citations grows by a factor of 2 every 12 years, this means that the real value of a citation depends on when it was produced. Consequently, failing to convert nominal citation values into real citation values produces significant mis-measurement of scientific impact. To address this problem, we develop a citation deflator method, outline the steps to generalize and implement it using the Web of Science portal, and analyze a large set of researchers from biology and physics to demonstrate how two common evaluation metrics – total citations and h-index – can differ by a remarkable amount depending on whether the underlying citation counts are deflated or not. In particular, our results show that the scientific impact of prior generations is likely to be significantly underestimated when citations are not deflated, often by 100% or more of the nominal value. Thus, our study points to the need for a systemic overhaul of the counting methods used evaluating citation impact – especially in the case of researchers, journals, and institutions – which can span several decades and thus several doubling periods.     

A study on forecasting electricity production and consumption in smart cities and factories

The electrical power sector must undergo a thorough metamorphosis to achieve the ambitious targets in greenhouse gas reduction set forth in the Paris Agreement of 2015. Reducing uncertainty about demand and, in case of renewable electricity generation, supply is important for the determination of spot electricity prices. In this work we propose and evaluate a context-based technique to anticipate the electricity production and consumption in buildings. We focus on a household with photovoltaics and energy storage system. We analyze the efficiency of Markov chains, stride predictors and also their combination into a hybrid predictor in modelling the evolution of electricity production and consumption. All these methods anticipate electric power based on previous values. The main goal is to determine the best method and its optimal configuration which can be integrated into a (possibly hardware-based) intelligent energy management system. The role of such a system is to adjust and synchronize through prediction the electricity consumption and production in order to increase self-consumption, reducing thus the pressure over the power grid. The experiments performed on datasets collected from a real system show that the best evaluated predictor is the Markov chain configured with an electric power history of 100 values, a context of one electric power value and the interval size of 1.