我国MIS的开发现状及发展趋势

为适应体制转换和市场经济的要求 ,建立管理信息系统 (MIS)对我国企业极具重要性和紧迫感 ,本文分析了我国MIS的开发现状及存在的问题 ,提出了相应的措施 ,并尝试性地指出管理信息系统的发展趋势是知识信息系统 (KIS) ,并随着知识经济向更高阶段———智能经济的发展进化 ,知识信息系统也将向智能信息系统 (IIS)进化。     

简论民事诉讼处分原则之立法模式

处分原则是最能反映民事诉讼特色的基本原则。由于诉讼传统、理论以及观念的差异,各国关于处分原则的立法并不一致,主要有三种模式：大陆法系的＂处分权主义＂、英美法系对抗制下的处分原则、苏联的＂职权干预式＂处分原则。其中,大陆法系的立法模式为中国进一步改革与完善处分原则提供了一个好的范例。     

基于智能代理的电子商务信息服务评价研究

随着计算机技术和信息技术的发展开始应用到诸多领域,现在最为热门的是智能代理技术在电子商务信息服务中的应用。本文首先从理论上阐述了智能代理技术的定义、特点、应用结构以及应用领域,归纳了其在电子商务信息服务中的应用层面和应用架构,然后重点对两个应用智能代理技术来提供信息服务的电子商务网站进行详尽的比较分析和研究,最后评价了电子商务信息服务中引入智能代理技术后出现的相关问题,并提出了部分改进意见。     

美国证据开示程序改革的启示与借鉴

该文以美国的证据开示制度为参考依据,对我国的证据交换制度进行了定位,提出借鉴证据开示制度的可取之处,吸取证据开示滥用造成负面效果的教训,重构证据交换制度的改革建议。     

以热流率作为补偿的智能PID控制

本文以电加热流动热力系统为例，提出了一种以静态模型为基础．以热流率作为补偿的智能ＰＩＤ控制处理动态模型的方法．较好地解决了由于热流率的变化而引起的温度波动，在应用中得到了满意的结果．     

Stimulating effects of intelligent policy on the performance of listed manufacturing companies in China

Based on the pilot projects of intelligent manufacturing of the Ministry of Industry and Information Technology of the People’s Republic of China and the annual data reported by listed companies, this paper studies the effect of China's intelligent policy on the performance of listed manufacturing companies by using the panel data of relevant enterprises from 2011 to 2017, as well as the mechanism of impact. Our empirical tests, using the difference-in-difference method, shows that intelligent policy can significantly improve the economic performance of manufacturing enterprises by guiding enterprises to optimize their intelligent management, strengthening investment in intelligent equipment and promoting collaborative manufacturing. Further empirical tests show that the impact of intelligent policy on economic performance is different in time. In the later selected pilot enterprises, the impact of intelligent policy on their economic performance is more significant; there is regional heterogeneity in the effects of intelligent policy: in regions with low intelligence, the positive impact of intelligent policy on the economic performance of manufacturing industry is more significant. Based on these conclusions, relevant intelligent policy suggestions are put forward.     

刑事侦查模式与审判模式的机制冲突

修改后的《刑事诉讼法》第一次出现了'公正审判'一词,在刑事审判阶段大量吸收英美法系当事人主义的审判模式内容,使校辩双方地位趋于平等化。但侦查阶段,我国始终奉行的是职权主义模式,几千年义务本位的法文化背景直接或间接地使犯罪嫌疑人和被告人地位的实际客体化,从而使犯罪嫌疑人和辩护人与国家侦查机关的地位不平等,没有达到'公正侦查',以至于形成'控'、'辩'前提条件不完备的诉讼结构失衡,我们所期待的公正审判将只能是一座空中楼阁。因此笔者试图在我国侦查阶段引入以'弹劾制'侦查现为支撑的当事人主义侦查摸式,使其与当事人主义趋向的庭审相适应、并且适当做好侦查与庭审之间的衔接工作,以完善我国刑事诉讼运行体制。     

Evaluation of Embedded Intelligent Real‐time Systems*

Over the past two decades, questions have surfaced about the effectiveness and contribution of intelligent systems to decision makers in a variety of settings. This paper focuses on the evaluation challenges associated with intelligent real‐time software systems that are embedded in larger host systems. With the proliferation of such systems in operational settings such as aerospace, medical, manufacturing, and transportation systems, increased attention to evaluations of such systems, and to resulting software safety, is warranted. This paper describes one such evaluation and proposes a set of evaluation criteria for embedded intelligent real‐time systems (EIRTS). Implications of the evaluation and the evaluation criteria are discussed.     

Learning by Objectives for Adaptive Shop-Floor Scheduling*

Effective production scheduling requires consideration of the dynamics and unpredictability of the manufacturing environment. An automated learning scheme, utilizing genetic search, is proposed for adaptive control in typical decentralized factory-floor decision making. A high-level knowledge representation for modeling production environments is developed, with facilities for genetic learning within this scheme. A multiagent framework is used, with individual agents being responsible for the dispatch decision making at different workstations. Learning is with respect to stated objectives, and given the diversity of scheduling goals, the efficacy of the designed learning scheme is judged through its response under different objectives. The behavior of the genetic learning scheme is analyzed and simulation studies help compare how learning under different objectives impacts certain aggregate measures of system performance.     

AOD精炼铁合金终点预测模型的建立

智能控制技术在冶金终点检测和终点控制中得到广泛应用,特别是神经网络技术,采用径向基函数神经网络(RBF)构成的神经网络控制方案可以有效地提高系统的精度、自适应性和鲁棒性。选用RBF神经网络建立冶炼终点温度和碳含量的预测模型,可以为后续的控制模型提供有价值的控制信息,通过终点控制模型计算所要补吹的氧气量以及补加的冷却剂量,以达到冶炼终点温度和碳含量的精确命中。仿真分析表明,RBF神经网络应用于冶炼终点温度和碳含量预测模型的建立,具有一定的预测精度。