施肥模型研究综述

对施肥模型和参数研究的历史、现状和趋势进行了综述,并指出今后定量施肥研究的关键问题。     

An approach to efficient business intelligent system for financial prediction

A concept of business intelligent system for financial prediction is considered in this paper. It provides data needed for fast, precise and good business decision support to all levels of management. The aim of the project is the development of a new online analytical processing oriented on case-based reasoning (CBR) where a previous experience for every new problem is taken into account. Methodological aspects have been tested in practice as a part of the management information system development project of “Novi Sad Fair”. A case study of an improved application of CBR in prediction of future payments is discussed in the paper. This paper is originally presented at The International Conference on Hybrid Information Technology 2006, at the special session on “Intelligent Information Systems for Financial Engineering”, November 2006 in Cheju Island, Korea.     

DSS research and practice in perspective

The aim of this paper is to assess the state-of-the-art in the Decision Support Systems (DSS) field from both a research and a practice perspective. Three main dimensions of DSS research and practice are addressed: 1) supporting human decision-making processes, 2) integrating DSS into the organizational context, and 3) identifying new application domains. The related analysis and discussion provides a better understanding of past developments in the DSS field and insights into future evolution patterns.     

钢铁企业价格预测决策模型体系研究

通过对钢铁企业现行价格管理体系的分析 ,建立了钢铁企业价格预测决策模型体系。充分利用大量的定性、定量信息 ,并把趋势预测和因果预测技术相结合 ,采用组合预测模型对价格进行预测 ,最后对预测出来的多方案进行模糊综合评价 ,给出推荐方案顺序。实际应用表明 ,模型体系是有效的。     

A bidding decision index for construction contractors

Results from applying the model on a sample of contractors, the majority of whom were international and operating in Egypt, reinforces the credibility of the developed methodology, claim the authors.     

An evaluation system of the setting up of predictive maintenance programmes

Predictive Maintenance can provide an increase in safety, quality and availability in industrial plants. However, the setting up of a Predictive Maintenance Programme is a strategic decision that until now has lacked analysis of questions related to its setting up, management and control. In this paper, an evaluation system is proposed that carries out the decision making in relation to the feasibility of the setting up. The evaluation system uses a combination of tools belonging to operational research such as: Analytic Hierarchy Process, decision rules and Bayesian tools. This system is a help tool available to the managers of Predictive Maintenance Programmes which can both increase the number of Predictive Maintenance Programmes set up and avoid the failure of these programmes. The Evaluation System has been tested in a petrochemical plant and in a food industry.     

Maintenance strategy based on a multicriterion classification of equipments

In an industrial plant, the level of maintenance provided to individual equipment is directly related to the availability that is expected from it. Thus, it is hoped that the most critical equipments will not fail or, at least, that any failure will be rapidly detected and corrected in the minimum time possible. Since resources are limited, it is necessary to determine how they should be distributed, so that no important equipment remains neglected while more resources are concentrated on the most critical items. Therefore, it is necessary to classify equipment in an objective way according to its importance. The method of multicriterion classification of critical equipments (MCCE)², which is described in the present work, allows systematic and detailed quantification of the criticality of all equipment, that is to say, it provides an evaluation of the importance that its correct operation has for the plant. To provide this information, the consequences for a company of any failure in the equipment concerned are analysed. Finally, a real case example of an urban wastewater treatment plant is described, in which the MCCE method is applied.     

炼钢工序的变化与挑战——柳钢"十五"期间炼钢的进步与工艺特点

简述了炼钢工序在柳钢"十五"期间工艺和装备的变化及其特点.对工序变化进行了初步分析.     

Applying real options in investment decisions relating to environmental pollution

This study focuses on how to assess the optimal environmental investment decisions under economic and ecological uncertainty, and establishes the continuous time model using the real option approach to optimize environmental pollution policy. Unlike traditional cost benefit analysis, this work extends the model of [Pindyck, R.S., 2002. Optimal timing problems in environmental economics. Journal of Economic Dynamics and Control 26(9–10), 1677–1697], and attempts to identify the storage threshold of pollution stocks and the optimal timing for implementing environmental pollution decisions.     

Industrial energy efficiency: the need for investment decision support from a manager perspective

Global competition, commitment to the Kyoto Protocol and a deregulated, integrated European electricity market will in all probability increase the demand for energy efficiency on the part of companies in Sweden. Investment decisions are an important part of meeting the new demands, because they decide the future efficiency of industrial energy systems. The objective of this study is to investigate, from a managerial perspective, the need to improve decision support in some industries, which can help to facilitate and improve investment decisions concerning energy efficiency. This work has been conducted through in-depth interviews with representatives for a number of energy-intensive companies and non-energy-intensive companies from different sectors. One need that was identified was the improvement of working methods in order to support the decision-making process. Here, external players seem to be playing an increasingly important role. Access to correct information, better follow-up activities, and transparent, understandable calculations are also considered to be important. The study will form the foundation for subsequent work on decision support and energy efficiency in industry.