Extrapolation of fuzzy values from incomplete data bases

This paper presents different approaches which enable a data base management system to obtain a plausible fuzzy estimate for an attribute value of an item for which the information is not explicitly stored in the data base. This can be made either by a kind of analogical reasoning from information about particular items or by means of expert rules which specify the (fuzzy) sets of possible values of the attribute under consideration, for various classes of items. Another kind of expert rules enables the system to compute an estimate from the attribute value of another item provided that, in other respects, this latter item sufficiently resembles the item, the value of which we are interested in; then these expert rules are used either for controlling the analogical reasoning process or for enlarging the scope of application of the first kind of expert rules. The different approaches are discussed in the framework of possibility theory.     

Time and cost securing in complex large-scale projects

Meeting time and cost objectives in complex projects involves specific problems and risks. An attempt is made to analyse the components of total cost increase of a project caused by time delay. An outline is given as to how these considerations can be used to estimate cost increases in investors' decision situations as well as to ascertain fair contractual penalties and claims for compensation and for the evaluation of justified project acceleration costs.     

Data mining of resilience indicators

In recent years, the Asia-Pacific region has experienced several financial setbacks, including speculative attacks in 1998 and the SARS outbreak in 2003. Financial stresses of this nature are unanticipated, and not all of the dangers can be predicted by the examination of market information and macroeconomic indicators. The Early Warning System (EWS) that has been adopted by the International Monetary Fund may not be able to predict future financial crises for all possible scenarios, because shocks come in many different forms. To supplement the EWS, this paper proposes a data mining framework to measure the resilience of an economy. The resilience framework does not predict a crisis, but rather assesses the current state of health of an economy and its ability to withstand a financial shock should one occur. The framework is based on a feedback system consisting of two stages. The first stage assigns a resilience score to each economy based on a fuzzy logic scoring scheme that is built on the ambiguous reasoning of experts. The second stage uses the classification tree approach to estimate thresholds for each economic indicator, and examines the quality of the fuzzy score. The result from the second stage is then passed back to the first stage as feedback. The final result is obtained when the feedback system reaches its equilibrium state. The proposed resilience framework is applied to the external-sector and the public-sector economies of several countries to illustrate its applicability.     

Immobilized α-amylase from Bacillus licheniformis: a potential enzymic time—temperature integrator for thermal processing

Biphasic and nth-order models were tested as to their usefulness to fit experimental inactivation data of Bacillus licheniformis α-amylase, immobilized on glass beads, and were discussed with respect to their suitability to characterize the considered enzymic system as a time—temperature integrator (TTI) to evaluate heat processes. Both isothermal and non-isothermal inactivation experiments were carried out. Model (kinetic) parameters (rate constant k, activation energy E_A and reaction order n) were estimated using a non-linear regression procedure. The results obtained, especially the activation energy of about 293 kJ mole^–1, indicated a potential use of this system as a TTI for heating processes in the temperature range of 96–108°C.     

Modified CIELAB formula tested using a textile pass/fail data set

The proposed new color-difference formula of CIE TC 129, which is a modified version of CIELAB, was tested with a recently published data set of textile pass/fail judgments. Goodness of fit is improved, if the parameter of lightness is set near 2, and if, additionally, a weight function for lightness is defined that reduces the weight of a lightness difference with lightness level in relation to chroma or hue scaling. © 1994 John Wiley & Sons, Inc.     

A new voltage control equipment using fuzzy inference

Power system control equipment needs higher sensitivity and operational reliability. Advanced voltage control equipment is needed for reducing the frequency of tap changes and improving the characteristics (the relationship between the actual voltage and reference voltage) of the voltage to meet today's power system requirements. However, these objectives are in a trade-off relationship. Studies of voltage control derived from a knowledge base suitable for electric power systems can satisfy these objectives using fuzzy inference. Compared with corresponding conventional equipment, the new equipment improved the deviation of 30 min average voltage of 30 percent. This paper describes the design concept of new voltage control equipment using fuzzy inference. In addition, field test results are described along with rules of fuzzy inference, membership functions, and the deviation of 30 min average voltage through detailed simulation.     

利用计算机进行油气资源评价和勘探决策

本文着重介绍了构成《现代勘探决策理论系统》的5个主要计算机模块,即:生油岩热演化处理、求任意曲边形面积、数学模拟预测资源量、勘探经济评价分析及决策、辅助处理等模块。该系统曾在塔里木盆地和准噶尔盆地的油气资源评价和勘探决策中发挥了作用,受到了专家和用户的好评。     

A comparative study of color measurement lntstrumentation

A multiplant Quality Improvement Team [QIT] was firmed to develop and implement an evaluation program for various color measurement .systems as potential replacements for the then-current aging systems. The emphasis qf this article is the analytical methodology utilized to evaluate the various color systems. The evaluation program consisted cf two phases. Phase I was a general overview/review of several systems, while Phase II was an extensive internal comparative evaluation measurement systems. These were Milton-Roy's ColorMate HDS, HunterLab's Ultrascan, Datacolor's CS-5, and BYK-Gardner's The Color Sphere [TCS]. The main comparison criteria were interinstrument agreement [agreement between two instruments ofthe same system], user-friendly software and computer interface capability, vendor amenability to a long-term logistical and maintenance relationship, and price. All systems were evaluated by duplicate measurements on various color tiles, yarns, and polymer flakes-over 1600 measurements on each system. The systems were compared with an instrument matrix, a decision matrix, and a product matrix. The instrument matrix was a comparison qfinstrument parameters, software/math treatments, and economics. The decision matrix was a forced ranking of each system by each criteria category [1–4 scale, with 1 representing the best and 4 representing the worst]. The product matrix accentuated the relative importance ofone criterion category over another by multiplying the forced ranking by the criticality of the category. The criticality of a given category wus determined by consensus within the QIT. Thr combination qf the three matrices allowed the evaluator[.s] t o select the color rneasuremmt system that best satixfied the color measurement needs and requirements of their facility and their products. For this evaluation, all ofthe evaluated systems were superior to the then-current agingsystems. As a result of this methodology, one instrument emerged as clearly superior. © 1994 John Wrley & Sons, Inc.     

EXTENSION OF THE RELATIONAL DATABASE AND ITS ALGEBRA WITH ROUGH SET TECHNIQUES

This paper describes a database model based on the original rough sets theory. Its rough relations permit the representation of a rough set of tuples not definable in terms of the elementary classes, except through use of lower and upper approximations. The rough relational database model also incorporates indiscernibility in the representation and in all the operators of the rough relational algebra. This indiscernibility is based strictly on equivalence classes which must be defined for every attribute domain. There are several obvious applications for which the rough relational database model can more accurately model an enterprise than does the standard relational model. These include systems involving ambiguous, imprecise, or uncertain data. Retrieval over mismatched domains caused by the merging of one or more applications can be facilitated by the use of indiscernibility, and naive system users can achieve greater recall with the rough relational database. In addition, applications inherently “rough” could be more easily implemented and maintained in the rough relational database.