分布式实时系统的通信中间件设计与实现

面向汽车电子的分布式实时系统通信中间件,须处理大量周期通信或非周期通信事件,并对时间有着严格的限制,不能有效进行通信时刻控制。为此,参考AUTOSAR规范,从实时性保证与柔性配置管理角度出发,提出一种分布式实时应用的通信中间件。该通信中间件具有可重用性、可裁减性和可配置性,可应用于多种操作系统及硬件平台。通过通信中间件的运行示例分析,验证了该通信中间件的可行性。     

交易中间件的研究与实现

文章设计了一个交易中间件模型，该模型主要由通信进程、交易进程和服务进程组成，同时介绍了应用层接口和数据库接口，重点描述了交易处理方式及完整性保护机制。为了有效地控制交易风险，提出了一种锁与自动确认／冲正相结合的处理方式。     

高速公路通信中间件的设计和实现

提出一种基于动态路由算法的通信中间件设计思路,并给出实现该中间件所使用的具体技术手段和实现方法。该中间件实现了多协议适配、自动路由、消息转发、对等网络等功能,尤其在复杂拓扑网络条件下具有良好的网络自适应能力。相比传统的通信中间件的静态路由管理,该中间件的动态路由能力具有更大的灵活性和适应性,在某些网络体系复杂以及软件系统庞大的行业和领域,该中间件有着良好的应用前景和巨大的市场价值。     

Tcn中间件系统的设计与实现

主要介绍了一款基于消息通信的中间件软件——The Cocklebur Network,即Tcn中间件的设计与实现。该系统具有以下特点:多进程模型、预先创建子进程机制,提高系统响应速度;编程API简单易用,都是围绕Tcn软件中专有的协议——Tcn协议展开,可运用标准的C语言库函数与头文件进行各种应用服务的开发;Tcn设计并实现了通过动态库与静态链接两种方式加载用户服务;同时此款软件还支持文件传输、负载均衡等功能。经过LoadRunner测试,该软件有较好的性能,可以满足大多数企业需要。     

基于线程的MPI通信加速器技术研究

为了针对多核系统构建更高效的MPI支撑环境,文中提出了一种基于线程的MPI加速器,称作MPIActor.MPIActor是一种用于协助传统MPI库的透明中间件,用户可以在编译期选择是否在单线程MPI程序中采用该中间件.加入MPIActor后,每个节点内的MPI进程都被映射成同一进程中的多个线程,从而节点内的通信可通过轻...     

连接CNC系统和套料软件的中间件设计与实现

针对目前工业自动化用户的个性化需求,设计了一种连接CNC系统和套料软件的中间件系统。首先设计了一种适合普通工程师理解与使用的人机界面,并基于过程控制系统的PVI通信方式,实现CNC系统数据的实时显示与跟踪;通过FTP协议,将标准套料软件生成的G代码传输到CNC系统,并采用消息机制的进程通信方式,实时回传CNC系统自动解析并执行G代码时的运行参数,保证CNC系统执行路径与套料软件规划路径的一致性。最后,以某公司套料软件与B&R激光切割机CNC系统为对象,设计并实现了该中间件。经过工业现场测试表明,该中间件能够连接到B&R公司目前所有的硬件系统上,稳定性良好,并能满足用户个性化的开发,具有一定推广价值。     

面向商品电子交易的一种层次结构通信中间件系统

针对大规模商品电子交易中交易引擎集中式竞价交易的应用要求，结合基于消息传递机制通信中间件的工作特点，提出了面向交易通信中间件系统的一种树状层次结构模型。分析并讨论了基于该模型的通信中间件系统的通信机制和工作特点。     

通信中间件的随机Petri网模型及性能分析

通信中间件由于其在屏蔽网络通信复杂性和提高系统性能等方面所起到的重要作用而被越来越广泛地应用。文章运用随机Petri网对通信中间件系统进行了描述,建立了一个实时通信中间件的同步及消息队列的模型。并对该模型的系统吞吐量、请求的平均延时等性能进行了评价,为系统的进一步设计和配置提供了理论依据。     

JCG：单点访问的通信中间件研究

提出了一个基于Java的通信中间件,该中间件提供了一个灵活的模块间通信方式,采用了通信设计模式Acceptor模式,并使用了多种设计模式来增加系统的可重用性和降低耦合性,使之具有良好的可用性。该中间件适合于中等以上规模的Java分布式应用程序的设计,具有接口简单,资源占用低的特点。实践表明,该系统具有良好的可用性。     

基于CORBA和XML的中间件设计与实现

目前,中间件（Middleware）在解决异构平台的通信问题上应用越来越为广泛,但由于其功能繁琐,使用复杂,价格昂贵,很难适用于小型企业异构数据集成通信。针对此问题,提出了一种中间件框架实现――基于CORBA和xml的中间件。该中间件通过xml定义统一的访问请求格式,运用corba原理和JDBC来进行对远程异构数据库的访问操作.框架设计实现了该中间件可移植,性价比高,可扩展性,易操作性的特点,适合于小型企业应用。     

System for foreign exchange trading using genetic algorithms and reinforcement learning

Foreign exchange trading has emerged recently as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system that effectively emulates the trading process will be very helpful. A major issue for traders in the deregulated Foreign Exchange Market is when to sell and when to buy a particular currency in order to maximize profit. This paper presents novel trading strategies based on the machine learning methods of genetic algorithms and reinforcement learning.     

基于区块链的电力交易模型及博弈定价方法

为解决传统能源中心化交易模式缺少灵活性、透明性和可监督性等问题,满足新型电力系统中电网各主体间电力交易市场化、定价灵活化等新要求,提出一种基于区块链的电力交易模型及博弈定价方法。该电力交易模型具有分布式、去中心化、不可篡改和加密安全等优势。首先,建立基于区块链的电力交易模型,协调发、供、用等主体间的生产和消费行为,形成统一的市场机制;其次,提出了基于博弈的多时间尺度电力交易竞价机制,利用蚁群优化(ACO)算法求解可得每小时的最佳竞拍价格。最后,通过仿真验证了交易模型及博弈定价方法,在激励政策下各交易方收益最优化。结果表明,交易模型及定价方法在新能源参与交易背景下能有效地平衡市场各主体的效益;基于区块链的智能合约可实现电力交易过程的智能化、透明化和可追溯性。     

在线金融交易确认框架协议研究

为了解决网上金融交易实时清算的快速确认问题,分析了典型的交易过程及安全特性,并基于椭圆曲线签名原理,提出了一种基于双线性映射的清算确认框架协议,使得对交易结果的确认可以递进进行,并在最终清算时一次完成,有效地实现了不可否认性和证据留存,避免了复杂的PKI体系和两两确认的繁琐过程,使真正的直通式处理和在线清算成为可能.     

Developing a rule change trading system for the futures market using rough set analysis

Many technical indicators have been selected as input variables in order to develop an automated trading system that determines buying and selling trading decision using optimal trading rules within the futures market. However, optimal technical trading rules alone may not be sufficient for real-world application given the endlessly changing futures market. In this study, a rule change trading system (RCTS) that consists of numerous trading rules generated using rough set analysis is developed in order to cover diverse market conditions. To change the trading rules, a rule change mechanism based on previous trading results is proposed. Simultaneously, a genetic algorithm is employed with the objective function of maximizing the payoff ratio to determine the thresholds of market timing for both buying and selling in the futures market. An empirical study of the proposed system was conducted in the Korea Composite Stock Price Index 200 (KOSPI 200) futures market. The proposed trading system yields profitable results as compared to both the buy-and-hold strategy, and a system not utilizing a genetic algorithm for maximizing the payoff ratio.     

Computational Intelligence for Evolving Trading Rules

This paper describes an adaptive computational intelligence system for learning trading rules. The trading rules are represented using a fuzzy logic rule base, and using an artificial evolutionary process the system learns to form rules that can perform well in dynamic market conditions. A comprehensive analysis of the results of applying the system for portfolio construction using portfolio evaluation tools widely accepted by both the financial industry and academia is provided.      

基于MAS 协调的CDM GDP 时隙动态交易

针对CDM GDP 时隙交换问题,提出一种基于MAS 协调的动态交易方法,以增加交换的灵活性和自 主性,提高机场资源利用率．采用基于市场机制的协商策略,在SCS 基础上建立了有条件的时隙拍卖交易机制,并 给出了MAS 协调交易模型,该模型可以使航空公司灵活、自主地选择交易对象;应用基于BDI 的协调推理机制, 给出了基于效用的航空公司运控中心（AOC）Agent 内部推理策略,以及效用计算过程．最后,采用Microsoft.NET 平台开发了所提方法的仿真系统,通过一些典型的CDM GDP 算例对所提方法进行仿真验证和对比分析,结果表明 了其有效性．     

An event based approach for quantifying the effects of securities fraud in the IT industry

Detecting the incidence and impact of illegal insider trading is a difficult process since access to the actual trading records of insiders that overlap precisely with fraudulent events is difficult. This paper provides a case study of a specific IT stock in Canada that was successfully prosecuted in the Canadian court system for market manipulation and illegal insider trading violations. The study provides a quantification of the impact of insider trading activities by the President directly through his own account or through accounts under his control, and illustrates the impact of some off-exchange transactions by the impugned parties. Overall, the costs of the insider trading violations are quite high, given the significant wealth effects produced by the events surrounding this case.     

多主体撮合交易系统的设计与实现

研究了电子商务交易模型的实现机制,设计了基于Multi-Agent的电子商务交易市场的组织结构,在基于Multi-Agent的撮合交易系统中,把整个交易过程看成一个动态的交互过程,体现了MultiAgent系统的动态特性,同时引入强化学习算法对竞标策略进行动态修正,使多主体撮合交易系统具有一定的自均衡和自学习能力。试验表明,基于多主体的撮合交易模型和动态竞标机制具有较好的交易性能。     

Profitability Edge by Dynamic Back Testing Optimal Period Selection for Technical Parameters Optimization,in Trading Systems with Forecasting

Back testing process is widely used today in forecasting experiments tests. This method is to calculate the profitability of a trading system, applied to specific past period. The data which are used, correspond to that specific past period and are called “historical data” or “training data”. There is a plethora of trading systems, which include technical indicators, trend following indicators, oscillators, control indicators of price level, etc. It is common nowadays for calculations of technical indicator values to be used along with the prices of securities or shares, as training data in fuzzy, hybrid and support vector machine/regression (SVM/SVR) systems. Whether the data are used in fuzzy systems, or for SVM and SVR systems training, the historical data period selection on most occasions is devoid of validation (In this research we designate historical data as training data). We substantiate that such an expert trading system, has a profitability edge—with regard to future transactions—over currently applied trading strategies that merely implement parameters’ optimization. Thus not profitable trading systems can be turned into profitable. To that end, first and foremost, an optimal historical data period must be determined, secondarily a parameters optimization computation must be completed and finally the right conditions of parameters must be applied for optimal parameters’ selection. In this new approach, we develop an integrated dynamic computation algorithm, called the “d-BackTest PS Method”, for selection of optimal historical data period, periodically. In addition, we test conditions of parameters and values via back-testing, using multi agent technology, integrated in an automated trading expert system based on Moving Average Convergence Divergence (MACD) technical indicator. This dynamic computation algorithm can be used in Technical indicators, Fuzzy, SVR and SVM and hybrid forecasting systems. The outcome crystalizes in an autonomous intelligent trading system.     

An Investigation into the Use of Intelligent Systems for Currency Trading

Investors use a number of technical trading tools to help them in their decision-making. This article aims to enhance this decision making process through the application of Genetic Algorithms (GAs) and Artificial Neural Networks (ANNs). The signals generated by technical trading tools are optimised for maximum profit through the use of GAs. The optimised signals are fed into a variety of fully connected feed forward ANNs, which combine these signals and output a single set of signals of whether to buy, hold or sell in the current market state. The different solutions produced are compared and contrasted, to determine the best ANN architecture for this type of signal amalgamation problem, and the optimal population size and mutation function for the GA. The result is an autonomous trading system with intelligence. This system, as described in this article, has proven to be profitable based on data presented to it—which spans ten currencies over a five year period. The profit margins are statistically significant when compared to un-optimised trading rules as suggested by literature. Further, the margins are statistically significantly more profitable than other no-risk investment strategies.