Results 1  10
of
113
Uncertainty of Data, Fuzzy Membership Functions, and MultiLayer Perceptrons
, 2004
"... Probability that a crisp logical rule applied to imprecise input data is true may be computed using fuzzy membership function. All reasonable assumptions about input uncertainty distributions lead to membership functions of sigmoidal shape. Convolution of several inputs with uniform uncertainty lead ..."
Abstract

Cited by 15 (6 self)
 Add to MetaCart
Probability that a crisp logical rule applied to imprecise input data is true may be computed using fuzzy membership function. All reasonable assumptions about input uncertainty distributions lead to membership functions of sigmoidal shape. Convolution of several inputs with uniform uncertainty leads to bellshaped Gaussianlike uncertainty functions. Relations between input uncertainties and fuzzy rules are systematically explored and several new types of membership functions discovered. Multilayered perceptron (MLP) networks are shown to be a particular implementation of hierarchical sets of fuzzy threshold logic rules based on sigmoidal membership functions. They are equivalent to crisp logical networks applied to input data with uncertainty. Leaving fuzziness on the input side makes the networks or the rule systems easier to understand. Practical applications of these ideas are presented for analysis of questionnaire data and gene expression data.
Automorphisms of the algebra of fuzzy truth values II
 INT J. OF UNCERTAINTY, FUZZINESS AND KNOWLEDGEBASED SYSTEMS
, 2008
"... ..."
Investigating Adaptation in Type2 Fuzzy Logic Systems Applied to Umbilical AcidBase Assessment
 in European Symposium on Intelligent Technologies, Hybrid Systems and Their Implementation on Smart Adaptive Systems
, 2003
"... In this paper, we describe the development of a type2 Fuzzy Logic System (FLS) based expert system for Umbilical AcidBase (UAB) assessment. The aim of this work is to develop an expert system which can adapt to an individual experts decision making mechanism by determining the parameters that de ..."
Abstract

Cited by 11 (6 self)
 Add to MetaCart
In this paper, we describe the development of a type2 Fuzzy Logic System (FLS) based expert system for Umbilical AcidBase (UAB) assessment. The aim of this work is to develop an expert system which can adapt to an individual experts decision making mechanism by determining the parameters that define the uncertainties of the terms used. Umbilical acidbase assessment of a newborn infant can provide vital information on the infants health and guide requirements for neonatal care. However, there are problems with the technique. Blood samples used for UAB assessment frequently contain errors in one or more of the important parameters, preventing accurate interpretation and many clinical staff lack the expert knowledge required to interpret errorfree results. A type1 FLSbased expert system was previously developed and implemented to overcome these difficulties [1]. However, it was observed that the type1 fuzzy expert system was not capable of fully capturing the linguistic uncertainties in the terms used and the inconsistency of the experts decision making. Type2 FLSs offer better capabilities to handle linguistic uncertainties by modelling the uncertainties using type2 membership functions and provide diagnosticians with decisionmaking flexibilities. The development of a type2 FLS for UAB assessment will provide the capability to handle linguistic uncertainties better and will lead to the creation of mechanisms to allow the system to adapt to individual experts decisionmaking. Such a system would truely be a smart adaptive fuzzy expert system. KEYWORDS: Type2 fuzzy logic systems; Umbilical acidbase assessment
Cognitive Situation and Threat Assessments of Ground Battlespaces
, 2003
"... We develop an integrated multiphase approach to middle and high level data fusion with an application to situation and threat assessments. The method first builds a feature vector for each detected ground target that includes time, position and target class in a particular rectangular geographical ..."
Abstract

Cited by 10 (1 self)
 Add to MetaCart
We develop an integrated multiphase approach to middle and high level data fusion with an application to situation and threat assessments. The method first builds a feature vector for each detected ground target that includes time, position and target class in a particular rectangular geographical area of the battlespace. It then clusters the feature vectors by position using a new robust clustering algorithm and makes an inventory of each cluster as to target classes, counts and posture parameters. Situation assessment is done next via a threetiered cascaded process of casebased reasoning on cluster attribute records to infer the unit types, sizes, and purposes. These are then fed into our fuzzy belief network that performs inferencing via heuristic belief propagation for threat assessment, that is, it infers the actions and intentions of the enemy. A simple synthetic example demonstrates the process.
Uncertainty in Risk Analysis: Towards a General SecondOrder Approach Combining Interval, Probabilistic, and Fuzzy Techniques
, 2002
"... Uncertainty is very important in risk analysis. A natural way to describe this uncertainty is to describe a set of possible values of each unknown quantity (this set is usually an interval) , plus any additional information that we may have about the probability of different values within this set. ..."
Abstract

Cited by 9 (4 self)
 Add to MetaCart
Uncertainty is very important in risk analysis. A natural way to describe this uncertainty is to describe a set of possible values of each unknown quantity (this set is usually an interval) , plus any additional information that we may have about the probability of different values within this set. Traditional statistical techniques deal with the situations in which we have a complete information about the probabilities; in real life, however, we often have only partial information about them. We therefore need to describe methods of handling such partial information in risk analysis. Several such techniques have been presented, often on a heuristic basis. The main goal of this paper is to provide a justification for a general secondorder formalism for handling different types of uncertainty.
Simulating flocks on the wing: The fuzzy approach
, 2005
"... Traditionally the systematic study of animal behaviour using simulations requires the construction of a suitable mathematical model. The construction of such models in most cases requires advanced mathematical skills and exact knowledge of the studied animal's behaviour. Exact knowledge is rarely av ..."
Abstract

Cited by 8 (1 self)
 Add to MetaCart
Traditionally the systematic study of animal behaviour using simulations requires the construction of a suitable mathematical model. The construction of such models in most cases requires advanced mathematical skills and exact knowledge of the studied animal's behaviour. Exact knowledge is rarely available. Usually it is available in the form of the observer's linguistic explanations and descriptions of the perceived behaviour. Mathematical models thus require a transition from the linguistic description to a mathematical formula that is seldom straightforward. The substantial increase of the processing power of personal computers has had as a result a notable progress in the field of fuzzy logic. In this paper we present a novel approach to the construction of artificial animals (animats) that is based on fuzzy logic. Our leading hypothesis is, that by omitting the transition from linguistic descriptions to mathematical formulas, ethologists would gain a tool for testing the existing or forming new hypotheses about `why' and `how' animals behave the way they do.
Effect of Type2 Fuzzy Membership Function Shape on Modelling Variation in Human Decision Making
, 2004
"... This paper explains how the shape of type2 fuzzy membership functions can be used to model the variation in human decision making. An interval type2 fuzzy logic system (FLS) is developed for umbilical acidbase assessment. The influence of the shape of the membership functions on the variation in ..."
Abstract

Cited by 8 (5 self)
 Add to MetaCart
This paper explains how the shape of type2 fuzzy membership functions can be used to model the variation in human decision making. An interval type2 fuzzy logic system (FLS) is developed for umbilical acidbase assessment. The influence of the shape of the membership functions on the variation in decision making of the fuzzy logic system is studied using the interval outputs. Three different methods are used to create interval type2 membership functions. The centre points of the primary membership functions are shifted, the widths are shifted, and a uniform band is introduced around the original type1 membership functions. It is shown that there is a direct relationship between the variation in decision making and the uncertainty introduced to the membership functions.
E.: The variety generated by the truth value algebra of type2 fuzzy sets. Fuzzy Sets and Systems
, 2010
"... This paper addresses some questions about the variety generated by the algebra of truth values of type2 fuzzy sets. Its principal result is that this variety is generated by a nite algebra, and in particular is locally nite. This provides an algorithm for determining when an equation holds in this ..."
Abstract

Cited by 7 (7 self)
 Add to MetaCart
This paper addresses some questions about the variety generated by the algebra of truth values of type2 fuzzy sets. Its principal result is that this variety is generated by a nite algebra, and in particular is locally nite. This provides an algorithm for determining when an equation holds in this variety. It also sheds light on the question of determining an equational axiomatization of this variety, although this problem remains open.
Preliminary Investigations into Modelling the Variation in Human Decision Making
 in Information Processing and Management of Uncertainty in Knowledge Based Systems
, 2004
"... This paper presents preliminary investigations into modelling the variation in human decision making. The relationship between the uncertainty introduced to the membership functions (mfs) of a Fuzzy Logic System (FLS) and the variation in decision making is explored using two separate methods ..."
Abstract

Cited by 7 (6 self)
 Add to MetaCart
This paper presents preliminary investigations into modelling the variation in human decision making. The relationship between the uncertainty introduced to the membership functions (mfs) of a Fuzzy Logic System (FLS) and the variation in decision making is explored using two separate methods.