314 research outputs found
Fuzzy expert systems in civil engineering
Imperial Users onl
Foundations of Fuzzy Logic and Semantic Web Languages
This book is the first to combine coverage of fuzzy logic and Semantic Web languages. It provides in-depth insight into fuzzy Semantic Web languages for non-fuzzy set theory and fuzzy logic experts. It also helps researchers of non-Semantic Web languages get a better understanding of the theoretical fundamentals of Semantic Web languages. The first part of the book covers all the theoretical and logical aspects of classical (two-valued) Semantic Web languages. The second part explains how to generalize these languages to cope with fuzzy set theory and fuzzy logic
AUTOMATED INTERPRETATION OF THE BACKGROUND EEG USING FUZZY LOGIC
A new framework is described for managing uncertainty and for deahng with artefact
corruption to introduce objectivity in the interpretation of the electroencephalogram
(EEG).
Conventionally, EEG interpretation is time consuming and subjective, and is known to
show significant inter- and intra-personnel variation. A need thus exists to automate the
interpretation of the EEG to provide a more consistent and efficient assessment.
However, automated analysis of EEGs by computers is complicated by two major
factors. The difficulty of adequately capturing in machine form, the skills and subjective
expertise of the experienced electroencephalbgrapher, and the lack of a reliable means of
dealing with the range of EEG artefacts (signal contamination). In this thesis, a new
framework is described which introduces objectivity in two important outcomes of
clinical evaluation of the EEG, namely, the clinical factual report and the clinical
'conclusion', by capturing the subjective expertise of the electroencephalographer and
dealing with the problem of artefact corruption.
The framework is separated into two stages .to assist piecewise optimisation and to cater
for different requirements. The first stage, 'quantitative analysis', relies on novel digital
signal processing algorithms and cluster analysis techniques to reduce data and identify
and describe background activities in the EEG. To deal with artefact corruption, an
artefact removal strategy, based on new reUable techniques for artefact identification is
used to ensure that artefact-free activities only are used in the analysis. The outcome is a
quantitative analysis, which efficiently describes the background activity in the record,
and can support future clinical investigations in neurophysiology. In clinical practice,
many of the EEG features are described by the clinicians in natural language terms, such
as very high, extremely irregular, somewhat abnormal etc. The second stage of the
framework, 'qualitative analysis', captures the subjectivity and linguistic uncertainty
expressed.by the clinical experts, using novel, intelligent models, based on fuzzy logic, to
provide an analysis closely comparable to the clinical interpretation made in practice.
The outcome of this stage is an EEG report with qualitative descriptions to complement
the quantitative analysis.
The system was evaluated using EEG records from 1 patient with Alzheimer's disease
and 2 age-matched normal controls for the factual report, and 3 patients with Alzheimer's
disease and 7 age-matched nonnal controls for the 'conclusion'. Good agreement was
found between factual reports produced by the system and factual reports produced by
qualified clinicians. Further, the 'conclusion' produced by the system achieved 100%
discrimination between the two subject groups. After a thorough evaluation, the system
should significantly aid the process of EEG interpretation and diagnosis
Foundations of Fuzzy Logic and Semantic Web Languages
This book is the first to combine coverage of fuzzy logic and Semantic Web languages. It provides in-depth insight into fuzzy Semantic Web languages for non-fuzzy set theory and fuzzy logic experts. It also helps researchers of non-Semantic Web languages get a better understanding of the theoretical fundamentals of Semantic Web languages. The first part of the book covers all the theoretical and logical aspects of classical (two-valued) Semantic Web languages. The second part explains how to generalize these languages to cope with fuzzy set theory and fuzzy logic
Optimization and inference under fuzzy numerical constraints
Εκτεταμένη έρευνα έχει γίνει στους τομείς της Ικανοποίησης Περιορισμών με
διακριτά (ακέραια) ή πραγματικά πεδία τιμών. Αυτή η έρευνα έχει οδηγήσει σε
πολλαπλές σημασιολογικές περιγραφές, πλατφόρμες και
συστήματα για την περιγραφή σχετικών προβλημάτων με επαρκείς βελτιστοποιήσεις.
Παρά ταύτα, λόγω της ασαφούς φύσης
πραγματικών προβλημάτων ή ελλιπούς μας γνώσης για αυτά, η σαφής μοντελοποίηση
ενός προβλήματος ικανοποίησης περιορισμών δεν είναι πάντα ένα εύκολο ζήτημα ή
ακόμα και η καλύτερη προσέγγιση. Επιπλέον, το πρόβλημα της μοντελοποίησης και
επίλυσης ελλιπούς γνώσης είναι ακόμη δυσκολότερο. Επιπροσθέτως, πρακτικές
απαιτήσεις μοντελοποίησης και μέθοδοι βελτιστοποίησης του χρόνου αναζήτησης
απαιτούν συνήθως ειδικές πληροφορίες για το πεδίο εφαρμογής,
καθιστώντας τη δημιουργία ενός γενικότερου πλαισίου βελτιστοποίησης ένα
ιδιαίτερα δύσκολο πρόβλημα. Στα πλαίσια αυτής της εργασίας θα μελετήσουμε το
πρόβλημα της μοντελοποίησης και αξιοποίησης σαφών, ελλιπών ή ασαφών
περιορισμών, καθώς και πιθανές στρατηγικές βελτιστοποίησης. Καθώς τα
παραδοσιακά προβλήματα ικανοποίησης περιορισμών λειτουργούν βάσει συγκεκριμένων
και προκαθορισμένων κανόνων και σχέσεων, παρουσιάζει ενδιαφέρον η διερεύνηση
στρατηγικών και βελτιστοποιήσεων που θα επιτρέπουν το συμπερασμό νέων ή/και
αποδοτικότερων περιορισμών. Τέτοιοι επιπρόσθετοι κανόνες θα μπορούσαν να
βελτιώσουν τη διαδικασία αναζήτησης μέσω της εφαρμογής αυστηρότερων περιορισμών
και περιορισμού του χώρου αναζήτησης ή να προσφέρουν χρήσιμες πληροφορίες στον
αναλυτή για τη φύση του προβλήματος που
μοντελοποιεί.Extensive research has been done in the areas of Constraint Satisfaction with
discrete/integer
and real domain ranges. Multiple platforms and systems to deal with these kinds
of domains have been developed and appropriately optimized. Nevertheless, due
to the incomplete and possibly vague nature of real-life problems, modeling a
crisp and adequately strict satisfaction problem may not always be easy or even
appropriate. The problem of modeling incomplete
knowledge or solving an incomplete/relaxed representation of a problem is a
much harder issue to tackle. Additionally, practical modeling requirements and
search optimizations require specific domain knowledge in order to be
implemented, making the creation of a more generic optimization framework an
even harder problem.In this thesis, we will study the problem of modeling and
utilizing incomplete and fuzzy constraints, as well as possible optimization
strategies. As constraint satisfaction problems usually contain hard-coded
constraints based on specific problem and domain knowledge, we will investigate
whether strategies and generic heuristics exist for inferring new constraint
rules. Additional rules could optimize the search process by implementing
stricter constraints and thus pruning the search space or even provide useful
insight to the researcher concerning the nature of the investigated problem
OWL and Rules
The relationship between the Web Ontology Language OWL and rule-based formalisms has been the subject of many discussions and research investigations, some of them controversial. From the many attempts to reconcile the two paradigms, we present some of the newest developments. More precisely, we show which kind of rules can be modeled in the current version of OWL, and we show how OWL can be extended to incorporate rules. We finally give references to a large body of work on rules and OWL
An Empirical Evaluation of the Inferential Capacity of Defeasible Argumentation, Non-monotonic Fuzzy Reasoning and Expert Systems
Several non-monotonic formalisms exist in the field of Artificial Intelligence for reasoning under uncertainty. Many of these are deductive and knowledge-driven, and also employ procedural and semi-declarative techniques for inferential purposes. Nonetheless, limited work exist for the comparison across distinct techniques and in particular the examination of their inferential capacity. Thus, this paper focuses on a comparison of three knowledge-driven approaches employed for non-monotonic reasoning, namely expert systems, fuzzy reasoning and defeasible argumentation. A knowledge-representation and reasoning problem has been selected: modelling and assessing mental workload. This is an ill-defined construct, and its formalisation can be seen as a reasoning activity under uncertainty. An experimental work was performed by exploiting three deductive knowledge bases produced with the aid of experts in the field. These were coded into models by employing the selected techniques and were subsequently elicited with data gathered from humans. The inferences produced by these models were in turn analysed according to common metrics of evaluation in the field of mental workload, in specific validity and sensitivity. Findings suggest that the variance of the inferences of expert systems and fuzzy reasoning models was higher, highlighting poor stability. Contrarily, that of argument-based models was lower, showing a superior stability of its inferences across knowledge bases and under different system configurations. The originality of this research lies in the quantification of the impact of defeasible argumentation. It contributes to the field of logic and non-monotonic reasoning by situating defeasible argumentation among similar approaches of non-monotonic reasoning under uncertainty through a novel empirical comparison
On the mechanisation of the logic of partial functions
PhD ThesisIt is well known that partial functions arise frequently in formal reasoning
about programs. A partial function may not yield a value for every member
of its domain. Terms that apply partial functions thus may not denote, and
coping with such terms is problematic in two-valued classical logic. A question
is raised: how can reasoning about logical formulae that can contain references
to terms that may fail to denote (partial terms) be conducted formally? Over
the years a number of approaches to coping with partial terms have been
documented. Some of these approaches attempt to stay within the realm
of two-valued classical logic, while others are based on non-classical logics.
However, as yet there is no consensus on which approach is the best one to
use. A comparison of numerous approaches to coping with partial terms is
presented based upon formal semantic definitions.
One approach to coping with partial terms that has received attention over
the years is the Logic of Partial Functions (LPF), which is the logic underlying
the Vienna Development Method. LPF is a non-classical three-valued logic
designed to cope with partial terms, where both terms and propositions may
fail to denote. As opposed to using concrete undfined values, undefinedness
is treated as a \gap", that is, the absence of a defined value. LPF is based
upon Strong Kleene logic, where the interpretations of the logical operators
are extended to cope with truth value \gaps".
Over the years a large body of research and engineering has gone into the
development of proof based tool support for two-valued classical logic. This
has created a major obstacle that affects the adoption of LPF, since such proof
support cannot be carried over directly to LPF. Presently, there is a lack of
direct proof support for LPF.
An aim of this work is to investigate the applicability of mechanised (automated)
proof support for reasoning about logical formulae that can contain
references to partial terms in LPF. The focus of the investigation is on the basic
but fundamental two-valued classical logic proof procedure: resolution and
the associated technique proof by contradiction. Advanced proof techniques
are built on the foundation that is provided by these basic fundamental proof
techniques. Looking at the impact of these basic fundamental proof techniques
in LPF is thus the essential and obvious starting point for investigating proof
support for LPF. The work highlights the issues that arise when applying
these basic techniques in LPF, and investigates the extent of the modifications needed to carry them over to LPF. This work provides the essential foundation
on which to facilitate research into the modification of advanced proof
techniques for LPF.EPSR
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