DECISION MAKING UNDER LINGUISTIC UNCERTAINTY CONDITIONS ON BASE OF GENERALIZED FUZZY NUMBERS

This article is devoted to the problem of decision making under linguistic uncertainty. The effective method for modelling linguistic uncertainty is the fuzzy set theory. There are several types of fuzzy number types proposed by L. Zadeh: fuzzy type-1, fuzzy type-2, Z-numbers. Chen proposed concept of generalized fuzzy numbers. Generalized trapezoidal fuzzy numbers (GTFN) one of effective approach which can be used for modeling linguistic uncertainty. GFTN very convenient model which allow take in account second order uncertainty. GFTN are formalized and major operations are described as practical problem is considered group decision making for supplier selection. In this case the criteria assessments are expressed by experts in linguistic form. Group decision making model is presented as 2 step aggregation procedure, in first step is aggregated value of alternative by expert, in second step by criteria. Numerical example with four criteria and three alternatives are presented and solved.This article is devoted to the problem of decision making under linguistic uncertainty. The effective method for modelling linguistic uncertainty is the fuzzy set theory. There are several types of fuzzy number types proposed by L. Zadeh: fuzzy type-1, fuzzy type-2, Z-numbers. Chen proposed concept of generalized fuzzy numbers. Generalized trapezoidal fuzzy numbers (GTFN) one of effective approach which can be used for modeling linguistic uncertainty. GFTN very convenient model which allow take in account second order uncertainty. GFTN are formalized and major operations are described as practical problem is considered group decision making for supplier selection. In this case the criteria assessments are expressed by experts in linguistic form. Group decision making model is presented as 2 step aggregation procedure, in first step is aggregated value of alternative by expert, in second step by criteria. Numerical example with four criteria and three alternatives are presented and solved

SERVER SELECTION ON BASE OF Z-NUMBERS

The paper is devoted to the problem of multi criteria decision making under linguistic uncertainty. Information of different approaches for modeling linguistic uncertainty have been analyzed. The concept of z-numbers proposed by L. Zadeh have been presented. Z-number is presented as cortege of two fuzzy number A and B, where A is analyzed factor, B is reliability of A assessment. The method of conversion z-numbers into generalized fuzzy numbers have been applied. As test have been used server selection problem. As decision making model have been used weighted average method. All calculations and results are presented.The paper is devoted to the problem of multi criteria decision making under linguistic uncertainty. Information of different approaches for modeling linguistic uncertainty have been analyzed. The concept of z-numbers proposed by L. Zadeh have been presented. Z-number is presented as cortege of two fuzzy number A and B, where A is analyzed factor, B is reliability of A assessment. The method of conversion z-numbers into generalized fuzzy numbers have been applied. As test have been used server selection problem. As decision making model have been used weighted average method. All calculations and results are presented

PRIMJENA NAPREDNIH RAČUNALNIH TEHNOLOGIJA U MODELIRANJU I UPRAVLJANJU POMORSKIH SUSTAVA

The paper deals with some application possibilities of advanced computing technologies in marine systems modelling and control. New computing technologies and techniques like fuzzy logic (FL), expert systems (ES), artificial neural networks (ANN), genetic algorithms (GA), object oriented programming (OOP) offer new, extended possibilities to identification, modelling and control of dynamic systems. This paper presents some possibilities of practical use of advanced computing technologies applied to the modelling and control of marine diesel engines. The emphasis is put on two well recognised techniques, fuzzy logic and expert systems. Some application examples are illustrated in the paper to show effectivness of using such methods and techniques in marine diesel engine modelling and control.U radu se daju neke mogućnosti primjena novih računalnih tehnologija u modeliranju i upravljanju sustava u pomorstvu. Nove računalne tehnologije i tehnike kao: neizrazita logika (FL), ekspertni sustavi (ES), umjetne neuronske mreže (ANN), genetički algoritmi (GA), objektno orjentirano programiranje (OOP) pružaju nove proširene mogućnosti za identifikaciju, modeliranje i upravljanje dinamičkih sustava. U ovom radu prezentiraju se neke od mogućnosti praktičnog iskorištenja naprednih računalnih tehnologija s primjenom u svrhe modeliranja i upravljanja drodskih dizelskih strojeva. Naglasak se u radu daje na dvije priznate i dobro prihvaćene tehnike, neizrazite logike i ekspertnih sustava. U radu se daje nekoliko primjera primjene ovih tehnika i metoda, te pokazuje njihova učinkovitost

A Perception Based, Domain Specific Expert System for Question-Answering Support

The current search engine technologies mostly use a keyword based searching mechanism, which does not have any deductive abilities. There is an urgent need for a more intelligent question-answering system that will provide a more intuitive, natural language interface, and more accurate and direct search results. The introduction of Computing with Words (CwW) provides a new theoretical base for developing frameworks with support for dealing with information in natural language. This paper proposes a domain specific question-answering system based on Fuzzy Expert Systems using CwW. In order to perform the translation of natural language based information into a standard format for use with CwW, Probabilistic Context-Free Grammar is used

Модель оценки уровня эффективности корпоративного управления

The majority of Russian enterprises have problems with updating their production assets and therefore are in dire need of  investments. A huge role in the investment attractiveness of  enterprises is provided by its corporate governance system. The lack of a well-developed stock market in Russia is not the last problem  pushing investors away. The purpose of this work is to develop a  mathematical model for assessing the effectiveness of corporate  governance of the enterprise to make a decision on foreign  investment in the oil industry corporation. In the sources available  for analysis, insufficient attention is paid to the analysis and  development of methods for assessing the effectiveness of corporate governance when deciding on the external investment of the  corporation. In order to make a decision of a potential investor to  invest in a company, the investor must have an idea of the activities  of the company and its economic and financial indicators. The  system of performance indicators of the corporation’s personnel, which affect its value, has a poorly structured structure.  To solve the problems of weakly structured systems it is necessary  to use fuzzy logic methods. These methods allow making qualitative  assessment of activity of the enterprise and its administrative  personnel, giving the chance to define level of management of the  enterprise and quality of performers of work. Existing models of  corporate governance performance assessment borrowed from  abroad are not effective in Russia. The level of corporate governance in the company is determined using ratings from the major rating  agencies such as S&P, RBC, EXPERT RA, CORE rating. But for this  method of measurement, there is one important condition: the estimated company must be included in the lists of these  agencies in order to monitor and analyze its corporate governance.  However, often in Russia, not all companies are included in the list of rating agencies, especially if these companies belong to medium- sized businesses. In the paper the model of corporate governance  efficiency evaluation is presented in the form of a system of  components, each of which is formed from economic indicators,  taking into account both the economic characteristics of the  enterprise and the qualitative composition of its personnel and not  tied to the quotes of the company’s shares in the stock markets. This model is built with the help of the method of fuzzy logic, which  allows combining quantitative and qualitative indicators. Using the  theory of fuzzy sets, the difference in the values of the initial  indicators is eliminated when assessing the level of efficiency of  corporate governance, and through operations on linguistic variables, the core component of the corporate governance level is combined. With the help of productive rules of fuzzy logic, the  numerical components of the level of efficiency of corporate  governance are given to fuzzy form. The developed model of  decision-making of a potential investor about investing in an  enterprise, based on the calculation of the assessment of the level of efficiency of its corporate governance, shows the potential investor  the level of economic and financial management of the enterprise,  the quality of management and working staff of the enterprise,  promotes the decision on the feasibility of investing in corporations.Большинство российских предприятий имеют проблемы с обновлением производственных  фондов и по этой причине остро нуждаются в инвестициях. Огромную роль на инвестиционную привлекательность предприятий оказывает его система корпоративного  управления. Далеко не последней проблемой, отталкивающей инвесторов является  отсутствие развитого фондового рынка в России. Целью настоящей работы является разработка математической модели оценки эффективности корпоративного  управления предприятия для принятия решения о внешнем инвестировании в корпорации  нефтяной промышленности. В доступных для анализа источниках в недостаточной мере уделяется внимание анализу и развитию методов оценки эффективности  корпоративного управления при принятии решения о внешнем инвестировании корпорации.  Для принятия решения потенциального инвестора об инвестировании в какую-либо компанию, инвестор должен иметь представление о деятельности данной компании и  ее экономических и финансовых показателей. Система показателей работы персонала  корпорации, которые влияют на ее стоимость, имеет слабоструктурированную структуру.  Для решения задач слабоструктурированных систем и необходимо применение методов  нечеткой логики. Данные методы позволяют произвести качественную оценку деятельности  предприятия и его управленческого персонала, дают возможность определить уровень  управления предприятием и качество исполнителей работы. Существующие модели оценки  эффективности корпоративного управления, заимствованные за рубежом, оказываются не  эффективными в России. Уровень корпоративного управления в компании сегодня  определяется с помощью рейтингов от крупных рейтинговых агентств, таких как S&P, РБК, ЭКСПЕРТ РА, CORE-рейтинг. Но для такого способа измерения существует одно важное  условие: оцениваемая компания должна быть включена в списки этих агентств для того,  чтобы отслеживать и анализировать ее корпоративное управление. Но зачастую в России в  списки рейтинговых агентств попадают не все компании, особенно, если эти компании  принадлежат к среднему бизнесу. В статье модель оценки эффективности корпоративного управления корпорации представлена в виде системы компонент, каждая из которых сформирована из экономических показателей, учитывающая как экономические  характеристики работы предприятия, так и качественный состав его персонала и не привязанный к котировкам акций предприятия на фондовых рынках. Данная модель  построена с помощь метода нечеткой логики, что позволяет объединить количественные и  качественные показатели. Используя теорию нечетких множеств, устраняется разногласие  значений исходных показателей при оценке уровня эффективности корпоративного  управления, а через операции над лингвистическими переменными происходит объединение компонент ядра уровня корпоративного управления. При помощи продуктивных правил  нечеткой логики числовые компоненты уровня эффективности корпоративного управления  приводятся к нечеткому виду. Разработанная модель принятия решений потенциального  инвестора об инвестировании в предприятие, основанная на расчете оценки уровня  эффективности его корпоративного управления, показывает потенциальному инвестору  уровень экономического и финансового управления предприятием, качество управляющего  и рабочего персонала предприятия, способствует принятию решения о целесообразности вложения средств в корпорации

Robotics Vision-based Heuristic Reasoning for Underwater Target Tracking and Navigation

This paper presents a robotics vision-based heuristic reasoning system for underwater target tracking and navigation. This system is introduced to improve the level of automation of underwater Remote Operated Vehicles (ROVs) operations. A prototype which combines computer vision with an underwater robotics system is successfully designed and developed to perform target tracking and intelligent navigation. This study focuses on developing image processing algorithms and fuzzy inference system for the analysis of the terrain. The vision system developed is capable of interpreting underwater scene by extracting subjective uncertainties of the object of interest. Subjective uncertainties are further processed as multiple inputs of a fuzzy inference system that is capable of making crisp decisions concerning where to navigate. The important part of the image analysis is morphological filtering. The applications focus on binary images with the extension of gray-level concepts. An open-loop fuzzy control system is developed for classifying the traverse of terrain. The great achievement is the system's capability to recognize and perform target tracking of the object of interest (pipeline) in perspective view based on perceived condition. The effectiveness of this approach is demonstrated by computer and prototype simulations. This work is originated from the desire to develop robotics vision system with the ability to mimic the human expert's judgement and reasoning when maneuvering ROV in the traverse of the underwater terrain

Soft Computing

Unter dem Begriff Soft Computing werden heute als Kerngebiete Evolutionäre Algorithmen, künstliche Neuronale Netze, die Fuzzy Set Theorie sowie probabilistisches Schließen zusammengefasst. Typisch sind approximative Lösungen ohne analytische Modellierung sowie ein in einem weiten Verständnis naturanaloges Vorgehen