煤与瓦斯突出预测综合指标F临界值研究

为了更加准确的预测掘进工作面煤与瓦斯突出,防止灾害事故的发生,针对“三率”各评价指标与掘进工作面煤与瓦斯突出预测综合指标具有区间型属性特性,运用灰靶决策理论,提出了基于熵值加权法与多指标加权灰靶相耦合的决策模型。该模型引入“奖优罚劣”变换算子,对样本矩阵进行无量纲初始化处理,结合改进的熵值法确定指标权重,构建了综合指标F临界值的决策模型,将综合指标F值在200~400内以10为步长形成了21个评价方案,对综合指标F的临界值进行研究。最后,通过在章村煤矿的现场实际应用,证实了该模型的有效性与实用性。     

造纸污泥太阳能干化处理工艺设计

太阳能作为一种清洁能源,将其应用在造纸污泥干化中,与传统干化工艺相比具有能耗低、无污染、运行费用低廉、操作简单、运行安全稳定、干化后的污泥仍保留原有的价值等特点。以某造纸污泥的干化为例,介绍了该工艺的工作原理及流程、工艺单元设计等。     

INTERACTIVE MULTIOBJECTIVE ANALYSIS EMBEDDING THE DECISION MAKER'S IMPLICIT PREFERENCE FUNCTION1

ABSTRACT: Two simple interactive techniques are developed and illustrated by means of two different real-life examples in Thailand. The first technique, Evolutionary Sequential Multiobjective Problem Solving (ESEMOPS), is an open-ended algorithm designed for planning problems with discrete alternatives. ESEMOPS helps the decision making group (DMG) develop progressively a preference function over the alternatives. The algorithm follows an evolutionary “breeding” strategy to generate a small set of good alternative solutions. This heuristic search, which does not guarantee that the adopted ‘satisfactum’ is an efficient solution leads to plausible results when applied to the planning of the Mae Khlong-Chao Phraya interbasin water transfer and irrigation system. The second algorithm, Search Beam Method (SBM) is essentially a series of one-dimensional searches for an efficient point along a “beam” passing through a goal point. Repeated search towards displayed goal points is leading to a set of quasi non-dominated solutions. SBM is illustrated by the Ubol Ratana reservoir control problem with the two conflicting objectives of energy generation and irrigation water supply. Neither ESEMOPS nor SBM require that weights, utilities, or pairwise tradeoffs be assessed. These features have been very much appreciated by a real DMG presented with the two techniques.     

A Hierarchical Fuzzy Decision Support System for the Environmental Rehabilitation of Lake Koronia,Greece

This article presents the design of a fuzzy decision support system (DSS) for the assessment of alternative strategies proposed for the restoration of Lake Koronia, Greece. Fuzzy estimates for the critical characteristics of the possible strategies, such as feasibility, environmental impact, implementation time, and costs are evaluated and supplied to the fuzzy DSS. Different weighting factors are assigned to the critical characteristics and the proposed strategies are ordered with respect to the system responses. The best strategies are selected and their expected impact on the ecosystem is evaluated with the aid of a fuzzy model of the lake. Sensitivity analysis and simulation results have shown that the proposed fuzzy DSS can serve as a valuable tool for the selection and evaluation of appropriate management actions. Note: This version was published online in June 2005 with the cover date of August 2004.     

Evaluating the management strategies of a forestland estate--the S-O-S approach

Connecting Multiple Criteria Decision Support (MCDS) methods with SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis yields analytical priorities for the factors included in SWOT analysis and makes them commensurable. In addition, decision alternatives can be evaluated with respect to each SWOT factor. In this way, SWOT analysis provides the basic frame within which to perform analyses of decision situations. MCDS methods, in turn, assist in carrying out SWOT more analytically and in elaborating the results of the analyses so that alternative strategic decisions can be prioritized also with respect to the entire SWOT. The A'WOT analysis is an example of such hybrid methods. It makes combined use of the Analytic Hierarchy Process (AHP) and SWOT. In this study, a hybrid method of the Stochastic Multicriteria Acceptability Analysis with Ordinal criteria (SMAA-O) and SWOT is developed as an elaboration of the basic ideas of A'WOT. The method is called S-O-S (SMAA-O in SWOT). SMAA-O enables the handling of ordinal preference information as well as mixed data consisting of both ordinal and cardinal information. Using SMAA-O is enough to just rank decision elements instead of giving them cardinal preference or priority ratios as required by the most commonly used MCDS methods. Using SMAA-O, in addition to analyzing what the recommended action is under certain priorities of the criteria, enables one to analyze what kind of preferences would support each action. The S-O-S approach is illustrated by a case study, where the shareholders of a forest holding owned by a private partnership prepared the SWOT analysis. Six alternative strategies for the management of their forest holding and of old cottage located on the holding were formed. After S-O-S analyses were carried out, one alternative was found to be the most recommendable. However, different importance orders of the SWOT groups would lead to different recommendations, since three of the six alternatives were efficient according to S-O-S analyses.     

DomPrevPlanning: User-friendly software for planning domino effects prevention

Chains of accidents, in literature generally referred to as domino effects, knock-on effects, cascade effects or escalation effects occur very infrequently but with disastrous consequences. There exist very few software packages to study such domino accidents in complex industrial areas and to forecast potential catastrophes caused by secondary order (involving a sequence of three installations submitted to two consecutive accidents), tertiary order or even higher order accidents. Moreover, available domino software focuses on risk assessment and on consequence assessment. None of these toolkits specifically addresses the prioritization of installation sequences in an industrial area in order to facilitate objective prevention decisions about domino effects. This paper describes the application of a new computer-automated tool designed to support decision-making on preventive and protective measures to alleviate domino effects in a complex surrounding of chemical installations. Using a holistic approach and thus looking at the entire industrial area as a whole, all sequences of three installations in the area are ranked according to their danger contribution to domino effects. An example of a cluster of chemical plants demonstrates the level of qualitative and quantitative input data required. The example is also used to explain the toolkit results, as well as the surplus value and the benefits for company safety managers and regulators.     

Integration of accident scenario generation and multiobjective optimization for safety-cost decision making in chemical processes

Investment in Chemical Process Industries for improving their safety requires considering risk level, environmental effect, cost and many other aspects simultaneously. This paper focuses on a new systematic method of finding the most cost–risk–effective investment scenario set. The method uses the automatic accident scenario generation technique first to find a set of the most dangerous scenarios. Then it uses the multiobjective optimization method to decide the priority of the investment. These computations includes considering many constraints such as limited budget, environmental requirements and social demands. The Styrene Monomer plant case study proves the practical use of this integration method of accident scenario generation and multiobjective optimization.     

EFFICIENCY OF HYDROLOGIC DATA COLLECTION SYSTEMS ROLE OF TYPE I AND II ERRORS1

ABSTRACT The efficiency of hydrologic data collection systems is relevant to solution of environmental problems, scientific understanding of hydrologic processes, model-building and management of water resources. Because these goals may be overlapping and non-commensurate, design of data networks is not simple. Identified are four elements of error or risk in such networks: (a) choice of variables and mathematical model for the same process, (b) accuracy of model parameter estimates, (c) acceptance of wrong hypothesis or rejection of correct hypothesis and (d) economic losses associated with error. Of these four, the classical hypothesis testing problem is specifically evaluated in terms of costs of type I and II errors for simple and composite hypotheses; mathematical models for these economic analyses also include costs of sample data and costs of waiting while new data is obtained. An illustrative computational example focuses on the hypothesis that natural recharge might be augmented by a system of pumping wells along an ephemeral channel. The relationship of the hypothesis testing problem to Bayesian decision theory is discussed; it is felt that the latter theory offers a more comprehensive framework for design and use of hydrologic data networks.     

Why not in your backyard? scientific data and nonrational decisions about risk

The siting of hazardous waste facilities constitutes a special case of the many no win environmental decisions we face. They share common features: (a) we must decide something; (b) the decision affects some people more than others; (c) as scientists we are not 100% confident of our research results; (d) elements of the decision remain unquantifiable; and (e) decisions combine both scientific and political elements. In this paper we attempt to illustrate and analyze several examples that combine all of these elements and to suggest methods which would lead toward a scientific valid and politically useful resolution. Using well-known examples such as the public's fear of death from nuclear power, snakebite, and smoking, we attempt to integrate public perception of risks into a decision-making model. Finally, the conclusions deal with the role of policy making, public perception, and science in resolving environmental controversies. We do not, however, solve this perplexing problem.