Ivan Vrana

Fuzzy aggregation and averaging for group decision making: A generalization and survey

This article presents some systematic sorting and ordering of approaches dealing with fuzzy aggregation and fuzzy averaging from different authors. The aggregation of fuzzy information from a group of experts for developing collective opinion or verdict is the important question in the expert systems theory and practice. This is to obtain a more comprehensive and realistic solution to the given decision problem. This note tries to outline an overall formal umbrella to various methods to aggregate several fuzzy sets, which describe the individual points of view of experts, or results of judgements from the various characteristics.

Assessing candidate industrial technologies utilising hierarchical fuzzy decision making systems

The adoption of new industrial technology is a type of critical decisions. Important characteristics of such significant decision problem are ill-structuredness, subjectivity and vagueness of input and output factors and their relationships. Most of past researches have considered only the quantitative view, and little or even no researches have treated inherent ambiguity in determining exact values of quantitative inputs and in quantifying subjective ones. In this paper, a hierarchical fuzzy decision making model is proposed for handling vagueness and subjectivity associated with the problems inputs (i.e. technology performance factors), and for structuring the relationships between them at one side and a technology evaluation score at the other side. The inputs to the model are groups of technical, economical and transferability-related measures. The output of the model is a crisp score for comparing merits of candidate technologies. Finally, a hypothetical illustrative example is provided.

Detection of Resource Overload in Conditions of Project Ambiguity

The planning of project resource allocation is an important part of project management, but it often suffers from uncertainty and ambiguity. Ambiguity conditions can be described and simulated by the theory of fuzzy sets and fuzzy quantities. The fuzzy approach to project planning is usually applied in critical path setting and project duration monitoring. In this article, we show a new application of the fuzzy set theory that involves planning project resource allocation and monitoring resource workloads. We derive the theoretical relations for the membership functions of the corresponding fuzzy quantities and demonstrate their application by taking a simple project as an example. The derived methods were used in planning a real project whose purpose was to analyze the possible resource workload. As a result, it was possible to recognize the serious risk of resource overload, which is not possible with the deterministic approach. They contributed to the success of the project.

Stakeholder group consensus based on multi-aspect hydrology decision making / Skupinový konsensus zainteresovaných subjektů založený na multikriteriální metodě rozhodování. j. hydrol. hydromech., 60, 2012, 4; 22 lit, 6 obr., 8 tab.

Catastrophic impact of floods is the result of an interaction between extreme hydrologic events and environmental, social and economic processes. Therefore, an integrated approach to flood management plays an important role in sustainable development. Such an approach requires a team comprising experts from the fields of hydrology and water resources, nature protection, risk management, human security, municipalities, economics and land use. The estimations of experts can serve for finding a solution to specific YES/NO problems and for estimating the value of specific attributes or parameters. In order to measure and evaluate the level of agreement between experts, a newly developed method for assessing the level of agreement and the value of τ-agreement, based on the Shannon theory of entropy, was applied. The use of such fuzzy-group-agreement decision making procedure, involving a broad range of stakeholders, is illustrated by the Flood Control Case Study, Zarosice, Czech Republic. In the case study of the Zdrava Voda catchment, where a part of the urbanised territory of the Zarosice village suffered from periodical flooding, a group of experts analysed the catchment data, focusing particularly on designed rainfall data. The KINFIL model was subsequently applied. Katastrofální dopad povodní je výsledkem vzájemné interakce extrémních hydrologických událostí a environmentálních, sociálních a ekonomických procesů. Z tohoto důvodu je integrovaný přístup k řešení protipovodňové ochrany důležitou součástí trvale udržitelného rozvoje. Tento přístup vyžaduje tým odborníků z oborů hydrologie a vodního hospodářství, ochrany přírody, řízení rizik (risk managementu), bezpečnosti osob, samosprávy, ekonomiky a hospodářského využití půdy. Názory těchto odborníků slouží k nalezení odpovědi na specifické otázky typu ano/ne, případně ke stanovení přesných hodnot parametrů. Pro měření a vyhodnocení konsenzu odborníků je použita nová metoda pro stanovení míry souhlasu a hodnoty τ-agreement vycházející z Shannonovy teorie entropie. Metoda je popsána na případové studii prováděné v části katastru obce Žarošice, která je často zaplavována. Tým expertů, zahrnující široké spektrum zainteresovaných subjektů, se zaměřil na dostupné informace o povodí, zejména na návrhové srážky, které byly následně vstupem do matematického srážko-odtokového modelu KINFIL.

Modeling Heterogeneous Experts’ Preference Ratings for Environmental Impact Assessment through a Fuzzy Decision Making System

Currently, there is an increasing demand for more efficient and practical environmental impact assessment (EIA) tools due to the emerging climate change challenges and need to better evaluate and control impacts of industrial technologies and activities. However, due to the inherent uncertainties, vagueness’s of assessment data, traditional EIA methods are unable to handle efficiently and properly such decision making process, and consequently more efficient method resorts to the opinions of group of relevant experts in order to enhance the reliability of the assessment decision. However, experts’ assessments are usually in heterogeneous forms, multi-metric or multi-criterion and usually conflicting. This article presents a fuzzy decision making systems (FDMS) that enables heterogeneous experts’ preference ratings assessment and provides for aggregation of those opinions over multi-metric scales. Experts can provide their opinion in form of crisp, linguistic or fuzzy values.

Correction to “Detection of Resource Overload in Conditions of Project Ambiguity”

The planning of project resource allocation is an important part of project management, but it often suffers from uncertainty and ambiguity. Ambiguity conditions can be described and simulated by the theory of fuzzy sets and fuzzy quantities. The fuzzy approach to project planning is usually applied in critical path setting and project duration monitoring. In this article, we show a new application of the fuzzy set theory that involves planning project resource allocation and monitoring resource workloads. We derive the theoretical relations for the membership functions of the corresponding fuzzy quantities and demonstrate their application by taking a simple project as an example. The derived methods were used in planning a real project whose purpose was to analyze the possible resource workload. As a result, it was possible to recognize the serious risk of resource overload, which is not possible with the deterministic approach. They contributed to the success of the project.

EM-OLAP Framework

Econometrics is currently one of the most popular approaches to economic analysis. To better support advances in these areas as much as possible, it is necessary to apply econometric problems to econometric intelligent systems. The article describes an econometric OLAP framework that supports the design of a multidimensional database to secure econometric analyses to increase the effectiveness of the development of econometric intelligent systems. The first part of the article consists of the creation of formal rules for the new transformation of the econometric model (TEM) method for the econometric model transformation of multidimensional schema through the use of mathematical notation. In the proposed TEM method, the authors pay attention to the measurement of quality and understandability of the multidimensional schema, and compare the proposed method with the original TEM-CM method. In the second part of the article, the authors create a multidimensional database prototype according to the new TEM method and design an OLAP application for econometric analysis.

Concept of Econometric Intelligence System: OLAP Applications in the Ambient Intelligence Environment

Econometric analysis is a non-trivial discipline applied to different areas of an enterprise or economy, in order to express economic reality and anticipate economic phenomena. This requires a great deal of econometric knowledge using a number of sophisticated methods and their good capabilities for correct and high quality interpretation of results. Currently, the intelligent system is a solution that is capable of performing highly complex tasks in the same way as people approach these tasks. In the context of ambient intelligence, it is possible to use personalized, contextual awareness and adaptive attributes for the design of an intelligent econometric system. In our work, we focused on the concept of an intelligent econometric system together with the application of OLAP technology for the creation of interactive analytical outputs. This new concept of the system is presented in an example of a data analysis to derive the forecast from the econometric model by designing a multidimensional view of the data.

Multidimensional Design of OLAP System for Context-Aware Analysis in the Ambient Intelligence Environment

Ambient Intelligence (AmI) is currently a perspective area of development intelligent systems that react on human presence, their behavior and AmI adapts to requirements based on contextual knowledge. The important issue in the study of AmI is thinking about context-aware preference. In the context of ubiquitous computing technologies there is not any access for users to the system at one point, but in different contexts. This creates need for context-sensitive preferences. The aim of context reasoning is getting new knowledge, so that systems or services were more intelligent. This process is not a trivial problem, so that we propose multidimensional view on context-aware knowledge for support of contextual reasoning. In this paper we introduce a new TCAP procedure for transformation context-aware preference through OLAP in the AmI. The OLAP technology enables us better analyzing contextual dependence on preferences and choosing relevant content for users in the AmI environment.

A Feasible Approximation to Optimum Decision Support System for Multidimensional Cases through a Modular Decomposition

The today’s decision making tasks in globalized business and manufacturing become more complex, and ill-defined, and typically multiaspect or multi-discipline due to many influencing factors. The requirement of obtaining fast and reliable decision solutions further complicates the task. Intelligent decision support system (DSS) currently exhibit wide spread applications in business and manufacturing because of its ability to treat ill-structuredness and vagueness associated with complex decision making problems. For multi-dimensional decision problems, generally an optimum single DSS can be developed. However, with an increasing number of influencing dimensions, increasing number of their factors and relationships, complexity of such a system exponentially grows. As a result, software development and maintenance of an optimum DSS becomes cumbersome and is often practically unfeasible for real situations. This paper presents a technically feasible approximation of an optimum DSS through decreasing its complexity by a modular structure. It consists of multiple DSSs, each of which contains the homogenous knowledge’s, decision making tools and possibly expertise’s pertaining to a certain decision making dimension. Simple, efficient and practical integration mechanism is introduced for integrating the individual DSSs within the proposed overall DSS architecture.