油气勘探目标的经济评价

勘探目标经济评价要坚持常规经济评价和风险评价相结合，在用多种方法合理预测经济评价参数，充分考虑各种风险因素的基础上，认真做好风险评价研究，提高勘探目标经济评价的可靠性。     

商业银行信用风险评估的生存分析模型及实证研究

企业发生财务危机，不能归还到期贷款是商业银行信贷资产的主要风险来源，商业银行如何构建恰当的信用风险评估模型来预测企业的财务危机，从而避免这类信用风险的出现就显得尤为重要。本文以我国上市公司为研究对象，结合杜邦分析法建立了基于生存分析的信用风险评估模型，模型对于随机选取的预测样本，其提前1年、2年和3年的预测准确率分别达到86％、72％和68％。通过与Ahman模型、Ohlson模型预测结果的比较和鲁棒性检验的结果发现，该模型同时具有可以使用时间序列、无需样本配对、中远期预测能力强和高鲁棒性的特点．这些特点特别对于商业银行中长期信贷风险管理具有较高的应用价值．     

国际国内甲醇市场分析及预测

介绍了近年来国际国内甲醇市场供需、生产、贸易、价格等变化特点，并对未来市场走向进行了分析预测。     

An explainable machine learning approach to improve take-off time predictions

Accurate aircraft trajectory predictions are necessary to compute exact traffic demand figures, which are crucial for an efficient and effective air traffic flow and capacity management. At present, the uncertainty of the take-off time is one of the major contributions to the loss of trajectory predictability. In the EUROCONTROL Maastricht Upper Area Control Centre, the predicted take-off time for each individual flight relies on the information received from the Enhanced Traffic Flow Management System. However, aircraft do not always take-off at the times reported by this system due to several factors, which effects and interactions are too complex to be expressed with hard-coded rules. Previous work proposed a machine learning model that, based on historical data, was able to predict the take-off time of individual flights from a set of input features that effectively captures some of these elements. The model demonstrated to reduce by 30% the take-off time prediction errors of the current system one hour before the time that flight is scheduled to depart from the parking position. This paper presents an extension of the model, which overcomes this look-ahead time constraint and allows to improve take-off time predictions as early as the initial flight plan is received. In addition, a subset of the original set of input features has been meticulously selected to facilitate the implementation of the solution in an operational air traffic flow and capacity management system, while minimising the loss of predictive power. Finally, the importance and interactions of the input features are thoroughly analysed with additive feature attribution methods.     

The burden of road traffic injuries in Kermanshah Province,Iran, in 2010–2011: GBD 2010 method

Deaths, injuries and disabilities resulting from road traffic injuries (RTIs) are a public health major concern. This study aims to calculate the burden of RTIs in Kermanshah Province in Iran. In this study to determine the years of life lost (YLL) related to RTIs, the National Death Registration and Forensics Medicine census data were employed. We use forensic medicine data to calculate the incidence of non-fatal injuries and years lost due to disability (YLD). The cause of death and non-fatal injuries was classified using ICD-10 codes and 23 groupes of global burden of diseases (GBD) 2010. The disability-adjusted life year (DALY) estimated on the guidelines of the GBD 2010 and age and sex structure was taken from the National Statistic Center for the year 2010. Overall, 70.8% of the subjects were males. The fatal and non-fatal injury rates of RTI were 51.3 and 283.6 per 100,000 persons, respectively. YLLs and YLDs were 46613 (24.5 per 1000) and 3405 (1.8 per 1000) in both sexes, respectively. The disability adjusted life years were 40711 in males, 9306 in females and 50018 in both sexes (42.5, 9.8 and 26.3 per 1000, respectively). More than 93% of DALY was from YLL (24.5 per 1000), with a small proportion for YLD (1.8 per 1000). Accounting for more than 50,000 DALY attributed to RTIs, traffic injuries is a major public health and socioeconomic problem in Kermanshah. Designing cost-effective interventions based on comprehensive and multi-sectoral programmes at the national and provincial levels can save many lives and resources that are lost every year. Undoubtedly, establishing a surveillance system at the sub-national level and measuring the burden of injuries, as in this study, can help policy-makers and planners in lessening the burden of RTIs.     

Performance assessment of ensemble learning systems in financial data classification

Financial data classification plays an important role in investment and banking industry with the purpose to control default risk, improve cash and select the best customers. Ensemble learning and classification systems are becoming gradually more applied to classify financial data where outputs from different classification systems are combined. The objective of this research is to assess the relative performance of existing state‐of‐the‐art ensemble learning and classification systems with applications to corporate bankruptcy prediction and credit scoring. The considered ensemble systems include AdaBoost, LogitBoost, RUSBoost, subspace, and bagging ensemble system. The experimental results from three datasets: one is composed of quantitative attributes, one encompasses qualitative data, and another one combines both quantitative and qualitative attributes. By using ten‐fold cross‐validation method, the experimental results show that AdaBoost is effective in terms of low classification error, limited complexity, and short time processing of the data. In addition, the experimental results show that ensemble classification systems outperform existing models that were recently validated on the same databases. Therefore, ensemble classification system can be employed to increase the reliability and consistency of financial data classification task.     

基于SVM的房地产财务决策风险预测及敏感性分析

本文以房地产上市公司的财务数据为参考依据,结合相关性分析,筛选并建立影响财务风险的指标体系;利用支持向量机建立财务风险分析预测模型;并使用灰色关联理论对指标进行敏感性分析,从而得到影响财务风险最敏感的指标。     

对江苏省电力负荷进行回归预测

本文主要根据2001-2011年江苏省用电量样本数据,建立了江苏省电力负荷与人均GDP、工业化以及人口数之间的多元回归预测方程,并预测了江苏省2014-2020年总用电量数据,在此基础上提出了相应的建议。     

模糊层次分析法优化BP神经网络的交通冲突预测模型

本文通过全面剖析影响交通冲突的原因,以交通流量、道路几何设计和道路环境三方面的因素建立指标层次结构体系。提出基于模糊层次分析(FAHP)法优化BP神经网络(BPNN)的预测模型,应用于交通冲突预测。     

白音查干矿井涌水量预计

矿井涌水量计算是矿床水文地质勘查中一项重要而复杂的工作,也是矿床水文地质勘查中的根本任务之一。运用大井法和廊道法对首采区、首采工作面和开切眼涌水量进行了预计,认为大井法计算的涌水量成果较为可靠,矿井最大涌水量为296.80m3/h,为今后的矿井安全生产提供了理论依据。