高砷烟尘酸性氧化浸出砷和锌的试验研究

采用酸性氧化浸出工艺对某冶炼厂高砷烟尘进行湿法浸出砷、锌的试验研究。通过单因素试验确定最佳浸出工艺条件。结果表明,采用pH值为2的稀硫酸溶液,在浸出温度80℃、浸出时间105min、液固体积质量比10∶1、H2O2添加量1.75mL/g(烟灰)、搅拌速度705r/min的条件下,砷、锌浸出率分别达到78.25%和85.42%。     

矿用钢丝绳寿命分布及可靠性

研究了矿用钢丝绳的使用寿命问题。用柯尔莫哥洛夫检验法检验寿命数据是否服从正态分布及对数正态分布,用最小二乘法(MIS)检验是否服从Weibull分布,并对Weibull分布的三参数进行估计,给出了三参数的置信区间及钢丝绳使用过程的可靠度。     

Moving beyond Volatility Index (VIX): HARnessing the term structure of implied volatility

This paper considers how information from the implied volatility (IV) term structure can be harnessed to improve stock return volatility forecasting within the state-of-the-art HAR model. Factors are extracted from the IV term structure and included as exogenous variables in the HAR framework. We found that including slope and curvature factors leads to significant forecast improvements over the HAR benchmark at a range of forecast horizons, compared with the standard HAR model and HAR model with VIX as IV information set.     

基于准时制的主生产计划方法

在当今的市场竞争中,能否及时供货和满足客户的要求关系到企业的信誉。为了提高企业的竞争能力,制造业都致力于采用日本的准时生产的策略。在前人研究的基础上,建立了适合于单件小批的主生产计划模型,这一模型有３个特点：（１）保证产品及时交货,也就是提前和滞后于交货期都要受到惩罚;（２）模型考虑了带有小批与单件并存的生产情况;（３）产品对能力的需求数据,考虑了分时段分布特点,并采用聚合算法从工艺路线和产品结构数据聚合而成。在对这一模型构造启发式算法的基础上,实现了主生产计划系统。该系统具有方便的人机界面,能够对由启发式算法产生的解进行修改。     

导弹子母弹抛撒的均匀性指标的确定及评定方法

本文以导弹侵彻子母弹抛撒为背景,提出了一种适合于有限子弹抛撒的均匀性指标,并且运用现代统计方法——ＢａｙｅｓＢｏｏｔｓｔｒａｐ法模拟了均匀性指标统计量的分布;另外,从火力运用的观点出发,根据子母弹抛撒的均匀性指标的大小对战斗部毁伤效率的影响,确定了均匀性指标的容许下限;应用统计检验方法给出了子母弹抛撒的均匀性的评定方法,为导弹侵彻子母弹抛撒的鉴定及同类武器该项目的鉴定提供可信且便于操作的方法。     

Cost and Service-Level-Based Model for a Seru Production System Formation Problem with Uncertain Demand

With increasing demand diversification and short product lifecycles, industries now encounter challenges of demand uncertainty. The Japanese seru production system has received increased attention owing to its high efficiency and flexibility. In this paper, the problem of seru production system formation under uncertain demand is researched. A multi-objective optimization model for a seru production system formation problem is developed to minimize the cost and maximize the service level of the system. The purpose of this paper is to formulate a robust production system that can respond efficiently to the stochastic demand. Sample average approximation (SAA) is used to approximate the expected objective of the stochastic programming. The non-dominated sorting genetic algorithm II (NSGA-II) is improved to solve the multi-objective optimization model. Numerical experiments are conducted to test the tradeoff between cost and service level, and how the performance of the seru production system varies with the number of product types, mean and deviation of product volume, and skill-level-based cost.     

C~3CM(C~2W)系统效能评价技术

通过分析研究建立Ｃ３ＣＭ系统效能评价准则,探索了Ｃ３ＣＭ效能评估技术和方法     

System deployment optimization in architecture design

Optimization of architecture design has recently drawn research interest. System deployment optimization （SDO） refers to the process of optimizing systems that are being deployed to activi- ties. This paper first formulates a mathematical model to theorize and operationalize the SDO problem and then identifies optimal so- lutions to solve the SDO problem. In the solutions, the success rate of the combat task is maximized, whereas the execution time of the task and the cost of changes in the system structure are mini- mized. The presented optimized algorithm generates an optimal solution without the need to check the entire search space. A novel method is finally proposed based on the combination of heuristic method and genetic algorithm （HGA）, as well as the combination of heuristic method and particle swarm optimization （HPSO）. Experi- ment results show that the HPSO method generates solutions faster than particle swarm optimization （PSO） and genetic algo- rithm （GA） in terms of execution time and performs more efficiently than the heuristic method in terms of determining the best solution.     

A Novel Cross-Project Software Defect Prediction Algorithm Based on Transfer Learning

Software Defect Prediction(SDP) technology is an effective tool for improving software system quality that has attracted much attention in recent years. However, the prediction of cross-project data remains a challenge for the traditional SDP method due to the different distributions of the training and testing datasets. Another major difficulty is the class imbalance issue that must be addressed in Cross-Project Defect Prediction(CPDP). In this work,we propose a transfer-leaning algorithm(TSboo...