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Computing with words (CWW) techniques have been shown to be useful in the management of imperfect information. From the programmer's standpoint, new tools are necessary to ease the use of these techniques within current programming platforms. This paper presents a step in this direction by describing a general framework that supports the implementation of applications dealing with fuzzy objects. We pay special attention to the study of the object comparison problem by offering both a theoretical analysis and a simple and transparent way to use our theoretical results in practice.

The paper presents wind tunnel investigations of the influence of wind direction on the natural ventilation of buildings. Tests were carried out on models of an apartment building complex, made to 1:100 scale, consisting of six adjacent buildings, and on a natural-scale isolated roof ventilation shaft outlet. Walls and roof pressure distribution were obtained and difference in pressure values between windows and the ventilation shaft outlets on the roof have been calculated. It was found that some wind directions decrease chimney draught. Aerodynamic interference of neighbouring buildings also decreases chimney draught. The influence of the location of an adjacent building on the ventilation of the building under consideration was tested.

This paper presents wind tunnel investigations of the aerodynamic interference effects on the pressure distribution on a building adjacent to another one. Tests were carried out at the Aviation Institute in Warsaw. Models, made to 1:100 scale, were set up behind a turbulent flow development system. It has been found that for some wind directions local values of the external pressure coefficient on the leeward wall, close to the gap between buildings, may be 2.5 times higher than on an isolated building. This may also lead to a reverse draught in the natural ventilation system of the apartment buildings.

Continuous utility functions for nontotal preorders: a review of recent results.- Risk Assessment of SLAs in Grid Computing with Predictive Probabilistic and Possibilistic Models.- From Benchmarks to Generalised Expectations.- Memory property in heterogeneously populated markets.- From comparative degrees of belief to conditional measures.- Delay and Interval Effects with Subadditive Discounting functions.- Pairwise comparison matrices: some issue on consistency and a new consistency index.- On a decision model for a life insurance company rating.- Qualitative Bipolar Decision Rules: Toward More Expressive Settings.- The dynamics of consensus in group decision making: investigating the pairwise interactions between fuzzy preferences.- Fuzzy Preference Relations Based on Differences.- Indices of Collusion among Judges and an Anti-collusion Average.- Scoring Rules and Consensus.- Dominance-based Rough Set Approach to Interactive Evolutionary Multiobjective Optimization.- Supporting Consensus Reaching Processes under Fuzzy Preferences and a Fuzzy Majority via Linguistic Summaries.- Decision Making in Social Actions.- Coherence for Fuzzy Measures and Applications to Decision Making.- Measures for Firms Value in Random Scenarios.- Thin Rationality and Representation of Preferences with Implications to Spatial Voting Models.- Quantum Dynamics of Non Commutative Algebras: The SU(2) Case.- Benefits of Full-Reinforcement Operators for Spacecraft Target Landing.- Neural Networks for Non-independent Lotteries.- Weak Implication and Fuzzy Inclusion.- The TOPSIS Method and its Application to Linguistic Vartiables.- Information Fusion with the Power Average Operator.

Summary form only given. First, we briefly advocate a need of natural language based methods in data mining, notably whew domain experts have a limited knowledge of modern tools of information technology. We present some approaches to linguistic summarization of sets of (numeric and/or textual) data, and show that a fuzzy logic based approach by Yager (1982), notably in its extended and implementable version of Kacprzyk and Yager (2001), and Kacprzyk, Yager and Zadrozny (2000), offers a simplicity and intuitive appeal, in particular in its new setting by Kacprzyk and Zadrozny (2005) based on Zadeh's computing with words and protoforms.

Summary form only given. First, we briefly present the essence of some new computing paradigms that try to attain a synergy, and bridge the gap between the human user and computer systems, notably the so-called: human centric computing, human centered computing, human computing, etc. We present a brief account of modern approaches to real world decision making, emphasize the concept of a decision making process that involves more factors and aspects like: the use of explicit and tacit knowledge, intuition, individual habitual domains, non-trivial rationality, different paradigms, etc. We advocate the need for computer based decision support systems. After a short presentation of their history and classification, we indicate that decision support systems should incorporate some sort of "intelligence", and we first briefly mention some views of intelligence in an individual and collective perspective. We indicate possible advantages of using those new human-centered computing paradigms in the decision making and support context, and advocate soft computing, notably Zadeh's computing with words (and perceptions) as a tools that makes it possible to merge the ideas presented like: human centric computing, decision making processes, intelligent decision support, etc. Finally, we show an example of our own implementation of a data/document driven decision support system in which, first, Zadeh's computing with words and perceptions paradigm is employed via linguistic database summaries, elements of business intelligence and Web intelligence.

Summary form only given. We present first some general remarks on challenges faced by modern information technology, notably when a human being is a relevant factor. These challenges are mainly related to inherent difficulties in solving some "meta-problems", in particular broadly perceived decision making. We assume, on the one hand, business intelligence related perspective, augmented with elements of Web intelligence, to fully use all available tools and resources. On the other hand, we assume a human centric computing perspective in the spirit of, for instance, Dertouzos's ideas. First, we present a brief account of modem approaches to real world decision making, emphasize the concept of a decision making process that involves more factors and aspects like: the use of own and external knowledge, involvement of various ,actors, aspects, etc., individual habitual domains, non-trivial rationality, different paradigms. As an example we mention Checkland's deliberative decision making (which is an important elements of his soft approach to systems analysis). After an analysis of specifics and difficulties encountered in many real world decision-making situations, we strongly advocate the use of computer based decision support systems. First, we briefly review the history of decision support systems, and then present a popular classification, starting from data driven to Web based and inter-organizational. We indicate that decision support systems should incorporate some sort of "intelligence", and we first briefly mention some views of what intelligence may mean in this concept, and then assume some more pragmatic, though limited, view of intelligent decision support systems. We indicate possible advantages of using elements of fuzzy logic and soft computing, notably, Zadeh's computing with words to be able to somehow merge the ideas presented like: human centric computing, decision making processes, intelligent decision support, etc. Finally, we present an example of implementation in which the above-mentioned ideas have been to some extent implemented. This concern a data and document driven decision support system for a small to medium company in which, first, Zadeh's computing with words and perceptions paradigm is employed via linguistic database summaries, elements of Web intelligence are used to derive additional information, and the ideas of an intelligent decision support and human centric computing are shown to be synergistically combined. We finish with some general remarks emphasizing that fuzzy logic and soft computing, notably as exemplified by Zadeh's computing with words and perceptions may be viewed as providing just the right tools to solve the problems considered

We consider multistage control of a fuzzy dynamic system under fuzzy constraints on controls and fuzzy goals on states. First, we present the standard solution by dynamic programming, indicate its limitations related to its inherent curse of dimensionality. We propose to use a granulation of the space of states and controls, and replace the source problem by its auxiliary counterpart with a small number of reference fuzzy states and reference fuzzy controls. After its solution by dynamic programming, we "adjust" the solution obtained by using Koczy and Hirota's interpolative reasoning technique.

Publisher Summary Radioactive elements common in nature are responsible for the exposure of the whole population to ionizing radiation that originates among others from radon. In Poland there are over thirty underground tourist routes, but radon concentrations are measured only in few of them. Among other routes, the following should be singled out: the drift of the former Kowary uranium mine and Niedzwiedzia Cave located near Kletno (the Sudetes). The results presented here should be analyzed from two perspectives – the tourist service personnel and tourists themselves. Persons employed in the tourist service should be regarded as those occupationally exposed to ionizing radiation and as such their exposure has to be controlled. The exposure of employees working in the “Kowary Drift” amounts to about 5% of the recommended annual limit (20 mSv), whereas in Niedzwiedzia Cave this value increases to 15% of the limit. In none of these routes is there a potential to exceed the limit of annual dose.

We briefly present, first, a simple approach to derive linguistic data summaries of a set of data exemplified by "most sales are with a low commission". The approach is based on fuzzy logic with linguistic quantifiers. Then, we implement such linguistic summaries via a fuzzy querying interface to a database. We use a genetic algorithm for searching the database. We present an application for deriving relevant relations concerning sales data at a computer retailer.

I: General Issues.- Modeling Knowledge: Model-based Decision Support and Soft Computations.- Benefits of Decision Support Using Soft Computing.- Evolving Connectionist-based Decision Support Systems.- An Agent-based Soft Computing Society with Application Applications in Financial Investment Planning.- A Rough Sets/Neoral Networks Approach to Knowledge Discovery for the Development of Decision Support Systems.- II: Applications and Implementations.- Decision Support Systems in Healthcare: Emerging Trends and Success Factors.- A View of Public and Private Sectors for Taiwan's BOT Project Financing Using Fuzzy Multi-Criteria Methods.- Relational Structures for the Analysis of Decision Information in an Electronic Market.- A Fuzzy Evaluation Model: A Case for Intermodal Terminals in Europe.- Application of Kemeny's Median for Group Decision Support.- An Internet-based Group Decision and Consensus Reaching Support System.- Limpio: A DSS for the Urban Waste Collection Problem.- A Decision Support System for Air Quality Control Based on Soft Computing Methods.- Multicriteria Genetic Tuning for the Optimization and Control of HVAC Systems.- Intelligent Information Systems for Crime Analysis.- Application of Fuzzy Decision Trees to Reservoir Recognition.- Introducing SACRA: A Decision Support System for the Construction of Cattle Diets.- Prediction of Parthenium Weed Dispersal Using Fuzzy Logic on GIS Spatial Image.

We extend the basic Bellman and Zadeh's (1970) model of multistage control (decision making) in a fuzzy environment to include both objective and subjective fuzzy constraints on controls and fuzzy goals on states at the consecutive control stages. Moreover, we consider some aggregation operators to reflect different attitudes towards the satisfaction and substitutability of the fuzzy constraints and fuzzy goals. We present an extended fuzzy dynamic programming model covering those aspects. The extension is motivated by a socio-economic regional planning problem discussed in Kacprzyk and Straszak (1982, 1984), which is outlined in this paper.

We briefly survey main developments and issues related to the use of (broadly perceived) fuzzy logic in database management systems (DBMSs), in particular in database querying. We show how this can help make DBMSs and their usage easier and more human-consistent.

The paper describes the calibration procedure for and data obtained from routine X-ray dosimetry service in Poland. In 1998 the number of readouts amounted to 152,000. The dosimetry concerned 31,281 workers in 3,113 enterprises. The annual collective dose was assessed to be 16.7 man.Sv. The analysis of the calibration quality is discussed as well. Only 2.9% of all points lay outside the quality curve while the number of the acceptable outliers was 5%.

We propose the use of linguistic data summaries, exemplified by the proposition “most employees are young and well paid” (with a degree of validity), to grasp relevant relations in data data. We employ Yager’s (1982, 1991) concept of a linguistic data summary based on a calculus of linguistically quantified propositions. We advocate an interactive approach in that the user formulates the class of summaries of interest. We show how this is related to fuzzy database queries, and how to employ here Kacprzyk, Zadrozny—s (1994a-1997b) fuzzy querying addon, FQUERY for Access. We present an implementation for a sales database of a computer retailer.

The determination of company’s investment policy in “soft” setting is considered. Softness is due to many nonquantifiable, intangible and subjective factors conditioning the operation and performance assessment. Hence a general lack of precise knowledge on data and relations. A considerable nonquantifiable experience existing is introduced in linguistic form and handled via the calculus of linguistic variables which equates the meaning of linguistic terms (statements) with fuzzy sets (relations). A multistage fuzzy decision-making model is constructed using that linguistic information. Fuzzy constraints on investments and fuzzy goals on outcomes are imposed. An optimal investment policy over a planning horizon is sought. The model forms a basis of a decision-support system. It may be implemented on a small computer and is simple to operate because the linguistic information is used.

The design of socioeconomic development policies is discussed. The development is in terms of life quality indicators covering social, economic, environmental, etc. aspects. It is evaluated with respect to effectiveness and stability. The effectiveness is how well the constraints on investments, and the goals on life quality indicators and the resulting social satisfactions are fulfilled. The stability is how smooth the basic development indicators evolve. The optimal investments are sought to attain the best effectiveness and stability. Due to an inherent “softness” of the problem, a fuzzy model is used for solution. Next step is the determination of the optimal policy meant as values and softness of constraints and goals, investment partitioning rules, and general attitudes(e.g., safety-first, balanced growth). An optimal policy is sought among some scenarios.

The paper is an extension of the authors previous work [5] in which an approximate discrete technique is proposed to solve the Weber problem with the Euclidean distance. Now, it is assumed that the cost of connection (the cost associated with two points in the plane) depends upon the distance stronger than linearly. A model is formulated and an approximate discrete technique analogous to that in [5] is proposed. Its validity is proved. Both the numerical complexity and the practical efficiency of the algorithm are considered. An example is given

Multistage decision-making(control) under fuzziness consists basically in finding an optimal sequence of controls which maximizes the membership function of the fuzzy decision. The fuzzy decision is mainly the intersection of fuzzy constraints imposed on the successive controls applied and fuzzy goals imposed on the successive states attained. This is equivalent to determining an optimal sequence of controls which “best satisfies the fuzzy constraints and fuzzy goals at all the control stages”. The purpose of this Daper is to propose a model in which the strict “” may be replaced by a milder requirement, e.g., “most”, “much more than 50%”, etc. A calculus of linguistically quantified statements is used.

In this paper, the problem of determining a maximizing decision in the multistage control of a fuzzy system in a fuzzy environment is considered. In the fuzzy system under control, the state is assumed to be fuzzy, while the control, not fuzzy. The fuzzy environment is given by fuzzy constraints and fuzzy goals imposed on particular control stages. The number of control stages, i.e. the termination time, is assumed to be fixed and specified; the same applies to the initial state. The fuzzy decision is defined as the intersection of fuzzy goals and fuzzy constraints. For solving the above problem, a branch‐and‐bound algorithm is proposed. The algorithm is simple and relatively efficient. Two examples are given.

To enhance human acceptance and hence implementability of guideline solutions provided by a decision support system, we propose some means to make decision making models to be used by the system more “human-consistent”. Basically, we try to introduce commonsense knowledge into some multicriteria and multistage (control) models. Commonsense knowledge is represented and manipulated in terms of Zadeh's fuzzy-logic-based approach, i.e. as a collection of dispositions (propositions with implicit fuzzy linguistic quantifiers).

We consider the determination of a maximizing decision in a fuzzy environment, i.e. a sequence of controls u0 m ,u1 m ,..., uN-1 m such that $$ m{{u}_{D}}\left( {\mu \begin{array}{*{20}{c}} m \\ 0 \\ \end{array} ,...,\mu \begin{array}{*{20}{c}} m \\ {N - 1} \\ \end{array} } \right) = \max \left[ {\min {{\mu }_{C}}0({{\mu }_{0}}),...,{{\mu }_{C}}N - 1({{\mu }_{{N - 1}}}),{\mkern 1mu} {{\mu }_{G}}N({{x}_{N}})} \right] $$

We consider the control of a deterministic system in a fuzzy environment when the termination time is a fuzzy set T in the space of control stages T. Such a case may be adequate for some socioeconomic systems. The approach proposed is based on the idea that the grade of membership of particular t in T is regarded as a preference of that termination time (μT(t) = 1—the best one, =0—impossible) and modifies the fuzzy goal μT(r).G. Hence, one must find the best termination time t* and the maximizing decision u p ,..., ut- 1.

We propose the use of Yager's (1988) ordered weighted averaging (OWA) operators as a means for fuzzy linguistic quantifier based aggregation in inductive learning (from examples) under errors, misclassifications, etc. To somehow neglect those errors, we formulate the problem so as to find a concept description covering, say, almost all of the positive examples and almost none of the negative examples. Thus, by neglecting some examples, those errors are somehow "masked".

An idea of a new model of a Web-based system to support a group of decision makers in reaching consensus is proposed. The core of the system is a flexible human consistent representation of preferences. However many means, notably Web-based, are conceived to help a group member to form and express his or her preferences. Moreover the model integrates the mechanisms for the discussion guidance so as to smoothly and effectively run the session.

We consider the problem of group decisions, in which decision-makers have different opinions or interests. This study proposes various metric spaces for representing the movements of decision-makers for reaching consensus. We also introduce the concept of fuzzy coalition for developing an algorithm for building a feasible fuzzy coalition, which is defined as the union of winning maximum coalitions which solve the issue of consensus among decision-makers.

The aim of this chapter is the development of three approaches for obtaining the value of an n-payment annuity, with payments of 1 unit each, when the interest rate is random. To calculate the value of these annuities, we are going to assume that only some non-central moments of the capitalization factor are known. The first technique consists in using a tetraparametric function which depends on the arctangent function. The second expression is derived from the so-called quadratic discounting whereas the third approach is based on the approximation of the mathematical expectation of the ratio of two random variables by Mood et al. (1974). A comparison of these methodologies through an application, using the R statistical software, shows that all of them lead to different results.

Among the countless papers written by Ronald R. Yager, those on Entropies and measures of information are considered, keeping in mind the notion of view of a set, in order to point out a similarity between the quantities introduced in various frameworks to evaluate a kind of entropy. We define the concept of entropy measure and we show that its main characteristic is a form of monotonicity, satisfied by quantities scrutinised by R.R. Yager.

In this chapter, a clear difference is made between the parallel design aspect and the parallel implementation aspect of evolutionary algorithms (EAs). From the algorithmic design point of view, the main parallel models for EAs are presented. A unifying view of parallel models for EAs is outlined. This chapter is organized as follows. In Sect. 55.2, the main parallel models for designing EAs are presented. Section 55.3 deals with the implementation issues of parallel EAs. In this section, the main concepts of parallel architectures and parallel programming paradigms, which interfere with the design and implementation of parallel EAs, are outlined. The main performance indicators that can be used to evaluate a parallel EAs in terms of efficiency are detailed. Finally, Sect. 55.4 deals with the design and implementation of different parallel models for EAs based on the software framework ParadisEO.

The “Solvency II” directive will be enforced starting from 2016. The insurance and reassurance companies have asked to reflect upon ways of adapting to the new rules and to consider value creation strategies under the new constraints. An Observatory was started for understanding how open Italian insurance companies are to change and how the announced rules influence the current operations. In order to monitor the behaviour of the companies over the years and evaluate the responsiveness to the new regulatory requirements of the Italian insurance Companies, a Fuzzy Expert System (FES) was developed. The objective of this work is to show the evaluation / monitoring tool created for the observatory. The special feature of the FES is to be created exclusively on judgments and not on objective data

International audience; This chapter is devoted to autonomous cognitive machines by mean of the design of an artificial curiosity based cognitive system for autonomous high-level knowledge acquisition from visual information. Playing a chief role as well in visual attention as in interactive high-level knowledge construction, the artificial curiosity is realized through combining visual saliency detection and Machine-Learning based approaches. Experimental results validating the deployment of the investigated system have been obtained using as well simulation facilities as a real humanoid robot acquiring visually knowledge about its surrounding environment interacting with a human tutor. As show the reported results and experiments, the proposed cognitive system allows the machine to discover autonomously the surrounding world in which it may evolve, to learn new knowledge about it and to describe it using human-like natural utterances.

The process of intertemporal choice is intimately linked with the concept of discounting function. Usually the benchmark in this important financial tool is the instant 0. This is an actual constraint for economic agent decision-making; indeed, in many situations, individuals have to decide at instants different from 0. Obviously, this introduces a multicriteria decision making framework in which a group of agents can (or cannot) cooperate in order to obtain greater profitabilities in function of the time variable. In this financial context, it is necessary to choose between transitive and non-transitive choice, giving rise to additive and non-additive (which includes subadditive and superadditive) discounting, respectively. Finally, another classification distinguishes between discounting with increasing or decreasing impatience.

The building process is configured as an arranged sequence of steps, from the needs detection of clients/users for their satisfaction, to design, realization and management of human made capital. The level of performance of the object to the requirements defines the degree of quality that distinguishes it. Assessing, through the Protocol ITACA, the building performance during different phases of production and utilization, means to have a tool directing the design solutions to the environmental friendly behavior approach, and valuating weaknesses and potentiality, without losing the global effect of choices. This contribute illustrates the potentiality of the Protocol ITACA that must be not only an assessment tool finalized to control ex-post the energy-environmental performance of buildings, but also a method for designing innovative and efficient architecture and making appropriate decisions. Only when this happens, will it be really possible to change the design way.