Motohide Umano

Fuzzy relational algebra for possibility-distribution-fuzzy-relational model of fuzzy data

In the real world, there exist a lot of fuzzy data which cannot or need not be precisely defined. We distinguish two types of fuzziness: one in an attribute value itself and the other in an association of them. For such fuzzy data, we propose a possibility-distribution-fuzzy-relational model, in which fuzzy data are represented by fuzzy relations whose grades of membership and attribute values are possibility distributions. In this model, the former fuzziness is represented by a possibility distribution and the latter by a grade of membership. Relational algebra for the ordinary relational database as defined by Codd includes the traditional set operations and the special relational operations. These operations are classified into the primitive operations, namely, union, difference, extended Cartesian product, selection and projection, and the additional operations, namely, intersection, join, and division. We define the relational algebra for the possibility-distribution-fuzzy-relational model of fuzzy databases.

fstds System: A fuzzy-set manipulation system

This paper describes an implementation of a system for fuzzy sets manipulation which is based on fstds (Fuzzy-Set-Theoretic Data Structure), an extended version of Childss stds (Set-Theoretic Data Structure). The fstds language is considered as a fuzzy-set-theoretically oriented language which can deal, for example, with ordinary sets, ordinary relations, fuzzy sets, fuzzy relations, L-fuzzy sets, level-m fuzzy sets and type-n fuzzy sets. The system consists of an interpreter, a collection of fuzzy-set operations and the data structure, fstds, for representing fuzzy sets. fstds is made up of eight areas, namely, the fuzzy-set area, fuzzy-set representation area, grade area, grade-tuple area, element area, element-tuple area, fuzzy-set name area and fuzzy-set operator name area. The fstds system, in which 52 fuzzy-set operations are available, is implemented in fortran, and is currently running on a FACOM 230-45S computer.

Knowledge-based expert system for damage assessment based on fuzzy reasoning

Abstract This paper attempts to develop a knowledge-based expert system for assessing damage states of bridge structure, where the focus is put on reinforced concrete bridge deck, because its failures have been occasionally reported. Similar to the usual expert systems, this system consists of a rule-base, working memory and interpreter. However, this system has such a remarkable feature that it includes a fuzzy set manipulation system which can treat fuzzy sets in the process of data handling, rule representation and inference procedure. Using this system, it is possible to deal with various kinds of uncertainties and ambiguities involved inherently in the data, rules and inference process in a unified and simple manner. An illustrative example is presented to demonstrate the applicability of the system developed herein.

Non-Numeric Method for Pairwise Fuzzy Group-Decision Analysis

In this article, we propose a non-numeric method for pairwise group-decision analysis based on fuzzy preference relations. The proposed method expresses and processes the preference relations non-nwnerically. The computation processes are relatively simple and fast. We apply our method for selecting the most prospective new agro-industries to be implemented by a multi-corporate company. Moreover, in the application we develop a procedure consisting of 4 stages: 1 a brain-storming process for alternatives and criteria identifications, 2 a pre-selection of the prospective alternatives using a modification of fuzzy Delphi method, 3 a pre-selection of the significant criteria using a non-nwneric independent evaluation method, and 4 a final alternatives selection based on all significant criteria by using the non-numeric pairwise fuzzy group-decision analysis. The final results are compared with results obtained by a semi-numeric method. The proposed method is suitable for group-decision making cases in which a full consensus is the most important role in selecting the alternatives.

A fuzzy expert system for durability assessment of bridge decks

An attempt is made to develop a knowledge-based expert system for assessing the durability of bridge decks. The present expert system has a feature that includes a fuzzy set manipulation system which can treat fuzzy sets in the process of data handling, rule representation and inference procedure. Using this system, it is possible to deal with various kinds of uncertainties and ambiguities involved inherently in the data, rules and inference processes in a unified and simple manner. Moreover, it is intended to introduce the concept of neural network for the automatic generation of fuzzy production rules. Several illustrative examples are presented to demonstrate the applicability of the system.<<ETX>>

An expert system for damage assessment of a reinforced concrete bridge deck

Abstract This paper attempts to develop an expert system for assessing damage states of bridge structures, where the focus is put on the reinforced concrete bridge deck, because its failures have occasionally been reported. The expert system consists of an interpreter, data-base and rule-base. All the rules involved are described through production rules with certainty factors. An example is presented to demonstrate the expert developed.

On a Behavioral Model of Analytic Hierarchy Process for Modeling the Legitimacy of Rank Reversal

This paper deals with a behavioral extension of a conventional Analytic Hierarchy Process (AHP), called behavioral AHP, such that rank reversal phenomena are legitimately observed and explanatory. In AHP, the main causes of rank reversal are either inconsistency in pairwise comparison or change in hierarchical structure, or both. Without these causes AHP should not lead to rank reversal. But if we use inappropriate normalization procedure such that entries sum to 1, the method will lead to rank reversal even when the rank should be preserved. Behavioral AHP proposed in this paper will preserve rank when it should be preserved, and will lead to rank reversal when the rank reversal is legitimate. Some numerical examples obtained by the behavioral AHP are included which could explain the legitimacy of the rank reversal.

LIFE fuzzy expert system shell

LIFE fuzzy expert system shell (LIFE FEShell) is designed for building expert systems using fuzzy knowledge. This shell consists of four parts: a fuzzy production system (FPS), an FPS object editor (FPOE), a fuzzy frame system (FFS) and an FFS editor (FFE), FPS and FFS can exchange information with each other and work together for building a more complex expert system and each editor helps to create and edit knowledge base with interactive window.<<ETX>>

Fuzzy database systems

We demonstrate a fuzzy object-oriented database system based on the possibility-distribution fuzzy-relational model proposed by us. And we present two data manipulation languages based on the fuzzy relational algebra and SQL (structured query language), which are standard in ordinary database systems for theoretical issue and practical use.<<ETX>>

Management of uncertainty in LIFE FEShell fuzzy frame system

Abstract LIFE FEShell is a fuzzy expert system shell that handles several kinds of uncertainty. LIFE FEShell is based on fuzzy logic, possibility theory, fuzzy measures and the fuzzy integral and is constructed in four parts: Fuzzy Production System (FPS), Fuzzy Frame System (FFS), FPS Object Editor (FPOE), and Fuzzy Frame Editor (FFE). We are now developing a few expert systems on LIFE FEShell to study and solve problems that are likely to arise during the implementation of these systems. In this paper, we present an analysis of uncertainty in the frame system and show details of the LIFE FEShell Fuzzy Frame System and its handling of uncertainty. LIFE FEShell FFS allows linguistic representations in data and evaluation functions and handles its hierarchical definitions to accommodate their linguistic polysemy. Data may be set not only with crisp values, but also using possibility distributions as slot values, data grades, and link grades.