On qualitative uncertainty in modelling assumptions

Reasoning under fuzzy uncertainty arises in many applications including planning and scheduling in fuzzy environments. In many real-world applications, it is necessary to define fuzzy uncertainty over qualitative uncertainty, where fuzzy values are assigned over the possible outcomes of qualitative uncertainty. However, current fuzzy logic programming frameworks support only reasoning under fuzzy uncertainty. Moreover, disjunctive logic programs, although used for reasoning under qualitative uncertainty it cannot be used for reasoning with fuzzy uncertainty. In this paper we combine extended and normal fuzzy logic programs [30, 23], for reasoning under fuzzy uncertainty, with disjunctive logic programs [7, 4], for reasoning under qualitative uncertainty, in a unified logic programming framework, namely extended and normal disjunctive fuzzy logic programs. This is to allow directly and intuitively to represent and reason in the presence of both fuzzy uncertainty and qualitative uncertainty. The syntax and semantics of extended and normal disjunctive fuzzy logic programs naturally extends and subsumes the syntax and semantics of extended and normal fuzzy logic programs [30, 23] and disjunctive logic programs [7, 4]. Moreover, we show that extended and normal disjunctive fuzzy logic programs can be intuitively used for representing and reasoning about scheduling with fuzzy preferences.

Identifying and controlling risk: The problem of uncertainty in the private finance initiative in the UK's National Health Service

Assessment of water quality management with a systematic qualitative uncertainty analysis

Solving sequential collective decision problems under qualitative uncertainty

Group decision making based on acceptable consistency analysis of interval linguistic hesitant fuzzy preference relations

Nowadays turbulent environment exposes global producing companies to many risks caused by uncertain parameters. Therefore, a correct evaluation of investments in factories including uncertainties becomes increasingly important. Existing monetary evaluation methods as the calculation of the Net Present Value (NPV) integrate only static parameters like wages, material costs or overhead costs. Most evaluating methods do not consider the development of those parameters, e.g. future developments of wages. In a correct factory-evaluation method, a multitude of influence parameters including uncertain parameters should be integrated. These uncertainties can be both quantitative and qualitative. In this paper, factors like the development of wage cost, quantities and currency exchange rates are defined as quantitative uncertainties. So-called weak factors like cultural differences, staff motivation or quality awareness are specified as qualitative uncertainties. Qualitative uncertainties are not yet integrated into monetary factory-evaluation methods. Moreover, the dependencies between uncertainties — e.g. the impact of staff motivation to their productivity — have not been considered. This paper therefore presents an approach on how to integrate both qualitative and quantitative uncertainties and their dependencies into a monetary evaluation method for investments in factories through the use of a Fuzzy-Evaluation-Net. This Evaluation-Net is based on Fuzzy-Logic and is similar to the structure of Artificial-Neural-Networks (ANNs).

Commodity money under private information

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In markets with qualitative uncertainty, pricing on the basis of average quality will be unattractive to participants whose products are above average in quality. This note examines the possibility of quality certification as an alternative to exit from the market in such situations. Examples dealing with labor market uncertainties illustrate the economic properties of the quality certification process, which unravels from the top down. The economic motivations and patterns of this form of price discrimination are similar to those encountered in standard lemons models.

In the preceding communication we developed a model for the conversion of neural output to mechanical output. We were left with two qualitative uncertainties, namely, the relation between neural output and isometric pressure, and the behavior of inspiratory muscles during expiratory flow; and two quantitative uncertainties concerning the effect of configurational pathway on pressure output, and the slope of the pressure-flow relation. For each of the above uncertainties we made certain assumptions based on indirect evidence but defined reasonable error limits. In the present communication we describe the method of implementing the model and evaluate the significance, in terms of spirometric output, of possible errors in the assumptions. Volume and flow profiles were generated from different neural output profiles. Analysis was repeated when the different assumptions were systematically altered within the limits set by the previous theoretical analysis. We conclude that the pattern of inspiratory muscle activation during spontaneous breathing and the existence of several mechanical interactions within the respiratory system combine to render spirometric output fairly insensitive to most potential errors in our assumptions.

The Low Density Supersonic Decelerator project performed a wind tunnel experiment on the structural design and geometric porosity of various sub-scale parachutes in order to inform the design of the 110ft nominal diameter flight test canopy. Thirteen different parachute configurations, including disk-gap-band, ring sail, disk sail, and star sail canopies, were tested at the National Full-scale Aerodynamics Complex 80- by 120-foot Wind Tunnel at NASA Ames Research Center. Canopy drag load, dynamic pressure, and canopy position data were recorded in order to quantify there lative drag performance and stability of the various canopies. Desirable designs would yield increased drag above the disk-gap-band with similar, or improved, stability characteristics. Ring sail parachutes were tested at geometric porosities ranging from 10% to 22% with most of the porosity taken from the shoulder region near the canopy skirt. The disk sail canopy replaced the rings lot portion of the ring sail canopy with a flat circular disk and wastested at geometric porosities ranging from 9% to 19%. The star sail canopy replaced several ringsail gores with solid gores and was tested at 13% geometric porosity. Two disk sail configurations exhibited desirable properties such as an increase of 6-14% in the tangential force coefficient above the DGB with essentially equivalent stability. However, these data are presented with caveats including the inherent differences between wind tunnel and flight behavior and qualitative uncertainty in the aerodynamic coefficients.

The strategic decision process between the best way of training and the time of this process is a big challenge, and when it comes to health services, this decision is more tenuous because it involves patient / client safety. The objective was to analyze the alternatives in the decision making of the education managers / training area of a diagnostic medicine service company regarding the training options of the operational team. This research has a theoretical-conceptual approach due to primary and secondary data extracted from an institutional sector of training and development of human resources, a health service specialized in diagnostic medicine and the literature analysis, resulting in a relevant survey points for the planning and conduction of a case study. In the first part of the analysis the following points were raised: decisions, uncertainties and objectives of the case. In this scenario, a diagram for the training of new employees was sketched out. As delimitations of the study were chosen the decisions of the tactical and operational levels and seven alternatives was generated. Possible classifications of strategic institutional domains and practical action were described. This study concludes that the construction of the alternatives to define the training strategy is dependent on quantitative and qualitative uncertainties, which makes the decision of this service difficult. Converging with the revisedliterature it was noticed that the practical part of the training has a direct influence on the quality of the employees who are active in the routine and operational results.

Simulationof the complete earthquake generation process requires assimilation of observational data on long-term behavior of faults over multiple rupture cycles. Paleoseismology, the study of pre-instrumental earthquakes from geological field investigations, provides the only observations of long-term fault behavior. Paleoseismic data present challenges for assimilation into models because data sets are small, sparse, analog, and contain qualitative uncertainties. Observations can be categorized as primary measurements from field data, or non-primary extrapolations or interpretations of primary data. Assimilation of non-primary data could yield biased simulation results. We present a primary data set for the San Andreas and Imperial faults for comparison with non-primary data in existing databases, and propose standard formats and structure for paleoseismic data assimilation into numerical simulation models.

Bargaining between a single seller and a succession of potential buyers of an indivisible object is studied in this paper. The seller bargains with one buyer at a time and switching buyers is costly. The seller does not know the buyers' reservation prices and buyers cannot observe the quality of the object. If the costs of switching buyers are high, there exists a signalling equilibrium in which the seller's price offer reveals the quality of the object. If the costs of switching are low, adverse selection occurs and the high-quality seller drops out of the market.

Bayesian games offer a suitable framework for games where the utility degrees are additive in essence. This approach does nevertheless not apply to ordinal games, where the utility degrees do not capture more than a ranking, nor to situations of decision under qualitative uncertainty. This paper proposes a representation framework for ordinal games under possibilistic incomplete information (π-games) and extends the fundamental notion of Nash equilibrium (NE) to this framework. We show that deciding whether a NE exists is a difficult problem (NP-hard) and propose a Mixed Integer Linear Programming (MILP) encoding. Experiments on variants of the GAMUT problems confirm the feasibility of this approach.