A bat-neural network multi-agent system (BNNMAS) for stock price prediction: Case study of DAX stock price

Creating an intelligent system that can accurately predict stock price in a robust way has always been a subject of great interest for many investors and financial analysts. Predicting future trends of financial markets is more remarkable these days especially after the recent global financial crisis. So traders who access to a powerful engine for extracting helpful information throw raw data can meet the success. In this paper we propose a new intelligent model in a multi-agent framework called bat-neural network multi-agent system (BNNMAS) to predict stock price. The model performs in a four layer multi-agent framework to predict eight years of DAX stock price in quarterly periods. The capability of BNNMAS is evaluated by applying both on fundamental and technical DAX stock price data and comparing the outcomes with the results of other methods such as genetic algorithm neural network (GANN) and some standard models like generalized regression neural network (GRNN), etc. The model tested for predicting DAX stock price a period of time that global financial crisis was faced to economics. The results show that BNNMAS significantly performs accurate and reliable, so it can be considered as a suitable tool for predicting stock price specially in a long term periods.     

Quantitative risk assessment using a Japanese hydrogen refueling station model

Although hydrogen refueling stations (HRSs) are becoming widespread across Japan and are essential for the operation of fuel cell vehicles, they present potential hazards. A large number of accidents such as explosions or fires have been reported, rendering it necessary to conduct a number of qualitative and quantitative risk assessments for HRSs. Current safety codes and technical standards related to Japanese HRSs have been established based on the results of a qualitative risk assessment and quantitative effectiveness validation of safety measures over ten years ago. In the last decade, there has been much development in the technologies of the components or facilities used in domestic HRSs and much operational experience as well as knowledge to use hydrogen in HRSs safely have been gained through years of commercial operation. The purpose of the present study is to conduct a quantitative risk assessment (QRA) of the latest HRS model representing Japanese HRSs with the most current information and to identify the most significant scenarios that pose the greatest risks to the physical surroundings in the HRS model. The results of the QRA show that the risk contours of 10^?3 and 10^?4 per year were confined within the HRS boundaries, whereas the risk contours of 10^?5 and 10^?6 per year are still present outside the HRS. Comparing the breakdown of the individual risks (IRs) at the risk ranking points, we conclude that the risk of jet fire demonstrates the highest contribution to the risks at all of the risk ranking points and outside the station. To reduce these risks and confine the risk contour of 10^?6 per year within the HRS boundaries, it is necessary to consider risk mitigation measures for jet fires.     

无失效数据机载多余度EWIS可靠性研究

针对高可靠度机载多余度EWIS各组成部分寿命服从指数分布但参数未知的情况，提出采用无失效数据可靠度分析方法评估EWIS的可靠度水平。通过Monte-Carlo仿真方法对连接形式为“先并联、后串联”EWIS各组成部分寿命进行抽样，利用“最小最大值”方法获得系统寿命的抽样值，用概率纸检验法初步判断EWIS寿命是否服从威布尔分布，再用Pearson拟合优度检验法判断EWIS寿命是否服从威布尔分布。结合无故障飞行时间的样本值与EWIS寿命服从威布尔分布的假设，采用无失效数据分析方法评估EWIS的可靠度水平。研究方法对机载多余度EWIS无失效数据可靠度分析有一定的贡献。     

Systematic optimization of corrosion,bioactivity, and biocompatibility behaviors of calcium-phosphate plasma electrolytic oxidation (PEO) coatings on titanium substrates

To optimize the corrosion, bioactivity, and biocompatibility behaviors of plasma electrolytic oxidation (PEO) coatings on titanium substrates, the effects of five process variables including frequency, current density, duty cycle, treatment time, and electrolyte Ca/P ratio were evaluated. In our systematic study, a Taguchi design of experimental based on an L16 orthogonal array was used. For this, the coatings characteristics such as the surface roughness, wettability, rutile to anatase and Ca/P ratios, and corrosion polarization resistance were investigated. After determining the optimum process variables for each response, the apatite forming ability in SBF (bioactivity behavior) and MG63 cell attachment and flattening (biocompatibility behavior) for two groups of coatings were examined. The first group was optimized based on the maximum corrosion polarization resistance and the variables were set as the frequency of 2000 Hz, the current density of 5 A/dm², the duty cycle of 30%, the treatment time of 5 min, and the Ca/P ratio of 0.65 at. % in the electrolyte. For the second group, the maximum surface roughness, greatest Ca/P ratio, and highest wettability as well as the minimum rutile to anatase ratio in coatings, could be obtained when the variables were set as the frequency of 10 Hz, the current density of 12.5 A/dm², the duty cycle of 50%, the treatment time of 12.5 min, and the Ca/P ratio of 1.70 at. % in the electrolyte. The results showed that while both groups of coatings indicated a significant apatite forming ability and can serve as bioactive coatings, a proper attachment and flattening of cells and consequently, the favorable biocompatibility properties were seen only in the first group.     

马尔可夫跳变线性系统最优控制的研究现状与进展

马尔可夫跳变线性系统（MJLS）是一种具有多个模态的随机系统，系统在各个模态之间的跳变转移由一组马尔可夫链来决定。MJLS模型因其在表示过程中可以产生突变而更能精确的描述实际工程应用中的系统。近年来，MJLS的最优控制问题成为了研究的热点，动态规划、极大值原理以及线性矩阵不等式等成为了解决此类问题的主流方法。本文对MJLS最优控制领域的研究现状进行了综述。分别对一般情况下、带有噪声的情况下、带有时滞的情况下以及某些特定情况下的MLJS最优控制问题的国内外研究现状进行论述。最后进行了总结并提出MJLS最优控制领域未来值得关注的研究方向。     

Catalytic supercritical water oxidation of tri-n-butyl phosphate: Process optimization by response surface methodology and cytotoxicity assessment

Catalytic supercritical water oxidation (SCWO) of an organophosphate flame retardant, namely tri-n-butyl phosphate (TNBP) was studied. Firstly, copper oxide nanoparticles (NPs) were synthesized in SCW and their properties were characterized by various analyses. Afterwards, their catalytic performance was investigated under different conditions including reaction temperature (400–500 °C), TNBP volume percentage in the feed (1–4%), oxidant ratio (0–2) and reaction time (50–150 min) based on response surface methodology (RSM). The synthesized CuO NPs had an average particle size of 30 nm with a narrow distribution. According to RSM analysis, the reaction temperature and time are the most significant factors; whereas, the impact of the other factors, especially TNBP volume percentage in the feed, was found to be negligible. Overall, excellent performance was achieved under optimal conditions found by the RSM, which was reaction temperature of 500 °C, TNBP volume percentage of 4%, oxidant ratio of 1.5, and reaction time of 90 min. The TOC removal efficiency as an indicator of TNBP degradation was about 99%. Finally, in vitro cell viability assays for the cytotoxicity evaluation of fresh and SCW-treated solution were applied. The results of MTT showed that SCWO converts TNBP into by-product that did not induce any cytotoxicity.     

A gradient boosting decision tree approach for insider trading identification: An empirical model evaluation of China stock market

Insider trading is a kind of criminal behavior in stock market by using nonpublic information. In recent years, it has become the major illegal activity in China’s stock market. In this study, a combination approach of GBDT (Gradient Boosting Decision Tree) and DE (Differential Evolution) is proposed to identify insider trading activities by using data of relevant indicators. First, insider trading samples occurred from year 2007 to 2017 and corresponding non-insider trading samples are collected. Next, the proposed method is trained by the GBDT, and initial parameters of the GBDT are optimized by the DE. Finally, out-of-samples are classified by the trained GBDT–DE model and its performances are evaluated. The experiment results show that our proposed method performed the best for insider trading identification under time window length of ninety days, indicating the relevant indicators under 90-days time window length are relatively more useful. Additionally, under all three time window lengths, relative importance result shows that several indicators are consistently crucial for insider trading identification. Furthermore, the proposed approach significantly outperforms other benchmark methods, demonstrating that it could be applied as an intelligent system to improve identification accuracy and efficiency for insider trading regulation in China stock market.     

Simulation studies on a rotating ring disk electrode: Effects of ionic migration with kinetic complication-disk results

In continuation to my previous work (Guha S. AIChE J. 2013;59(4):1390-1399), in this work, effects of ionic migration are evaluated for disk region of a rotating ring disk electrode system by numerically solving complex differential equations, developed for mass transfer along with kinetic complication in presence of ionic migration under limiting current condition. The system for simulation is 0.01 M Fe₂(SO₄)₃ solution with H₂SO₄ as supporting electrolyte. Simulation cases are presence and absence of ionic migration with kinetic complication (oxidation of Fe²⁺ to Fe³⁺ under O₂ pressure). Results show that concentration boundary layer thickness of reactant Fe³⁺ reduces appreciably and steady-state disk current reduces substantially in presence of migration. Simulated steady-state disk current in absence of migration case agrees well with published data. Results indicate higher Fe²⁺ concentration in presence of migration and thereby higher rate of oxidation of Fe²⁺ to Fe³⁺ at all rate constant values.     

澳大利亚“基于能力本位的评估”模式及对我国高职教育 质量评估的启 示

澳大利亚职业教育在全球享有较高的声誉,这与其坚持严格的"基于能力本位的评估"(competency based assessment, CBA)密不可分。介绍了澳大利亚CBA的内涵特征,并详细描述"准备评估、开发评估工具、开展评估、对评估结果进行评估"的CBA运作过程,关注评估工具的开发和后续常规系统性检查及完善,以期对我国的高等职业教育质量评估起到启示和借鉴作用。     

A three-dimensional surface measurement system implemented with Gaussian process based adaptive sampling

Self-adaptive surface measurements that can reduce data redundancy and improve time efficiency are in high demand in many fields of science and technology. For this purpose, a system implemented with Gaussian process (GP) adaptive sampling is developed. The non-parametric GP model is applied to reconstruct the topography and guide the subsequent sampling position, which is determined from the inference uncertainty estimation. A criterion is proposed to terminate the GP adaptive measurement automatically without any prior model or data of the topography. Experiments on typical surfaces validate the intelligence, adaptability, and high accuracy of the GP method along with the stabilization of the automatic iteration termination. Compared with traditional raster sampling, data redundancy is reduced and the time efficiency is improved without sacrificing the surface reconstruction accuracy. The proposed method can be implemented in other systems with similar measurement principles, thus benefitting surface characterizations.