1,521 research outputs found
Fuzzy expert systems in civil engineering
Imperial Users onl
Fuzzy Inference Systems for Risk Appraisal in Military Operational Planning
Advances in computing and mathematical techniques have given rise to increasingly complex models employed in the management of risk across numerous disciplines. While current military doctrine embraces sound practices for identifying, communicating, and mitigating risk, the complex nature of modern operational environments prevents the enumeration of risk factors and consequences necessary to leverage anything beyond rudimentary risk models. Efforts to model military operational risk in quantitative terms are stymied by the interaction of incomplete, inadequate, and unreliable knowledge. Specifically, it is evident that joint and inter-Service literature on risk are inconsistent, ill-defined, and prescribe imprecise approaches to codifying risk. Notably, the near-ubiquitous use of risk matrices (along with other qualitative methods), are demonstrably problematic at best, and downright harmful at worst, due to misunderstanding and misapplication of their quantitative implications. The use of fuzzy set theory is proposed to overcome the pervasive ambiguity of risk modeling encountered by today’s operational planners. Fuzzy logic is adept at addressing the problems caused by imperfect and imprecise knowledge, entangled causal relationships, and the linguistic input of expert opinion. To this end, a fuzzy inference system is constructed for the purpose of risk appraisal in military operational planning
Quantification of uncertainty of geometallurgical variables for mine planning optimisation
Interest in geometallurgy has increased significantly over the past 15 years or
so because of the benefits it brings to mine planning and operation. Its use
and integration into design, planning and operation is becoming increasingly
critical especially in the context of declining ore grades and increasing mining
and processing costs.
This thesis, comprising four papers, offers methodologies and methods to
quantify geometallurgical uncertainty and enrich the block model with geometallurgical
variables, which contribute to improved optimisation of mining
operations. This enhanced block model is termed a geometallurgical block
model.
Bootstrapped non-linear regression models by projection pursuit were built
to predict grindability indices and recovery, and quantify model uncertainty.
These models are useful for populating the geometallurgical block model with
response attributes. New multi-objective optimisation formulations for block
caving mining were formulated and solved by a meta-heuristics solver focussing
on maximising the project revenue and, at the same time, minimising
several risk measures. A novel clustering method, which is able to use
both continuous and categorical attributes and incorporate expert knowledge,
was also developed for geometallurgical domaining which characterises the
deposit according to its metallurgical response. The concept of geometallurgical
dilution was formulated and used for optimising production scheduling in
an open-pit case study.Thesis (Ph.D.) (Research by Publication) -- University of Adelaide, School of Civil, Environmental and Mining Engineering, 201
Predictive long-term asset maintenance strategy: development of a fuzzy logic condition-based control system
Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceTechnology has accelerated the growth of the Facility Management industry and its roles are
broadening to encompass more responsibilities and skill sets. FM budgets and teams are becoming
larger and more impactful as new technological trends are incorporated into data-driven strategies.
This new scenario has motivated institutions such as the European Central Bank to initiate projects
aimed at optimising the use of data to improve the monitoring, control and preservation of the assets
that enable the continuity of the Bank's activities. Such projects make it possible to reduce costs, plan,
manage and allocate resources, reinforce the control, and efficiency of safety and operational systems.
To support the long-term maintenance strategy being developed by the Technical Facility
Management section of the ECB, this thesis proposes a model to calculate the Left wear margin of the
equipment. This is accomplished through the development of an algorithm based on a fuzzy logic
system that uses Python language and presents the system's structure, its reliability, feasibility,
potential, and limitations. For Facility Management, this project constitutes a cornerstone of the
ongoing digital transformation program
Handling a large number of preferences in a multi-level decision-making process
The complexity of a decision is related to the number of persons that are involved, as well as to the diversity of their preferences based on their knowledge, experience or area of expertise. Consequently, it is a challenge to adequately handle a large number of heterogeneous preferences considering that all the participants are considered to be an important source of information to make better motivated decisions. Addressing this challenge constitutes the main motivation in this dissertation because these days decision makers seem to be increasingly interested in the opinions (or preferences) given by persons around a community (and sometimes around the world) through different sources including social media channels.
This PhD study provides a set of tools that helps a decision maker to make better motivated decisions by a proper handling of a large number of preferences, identifying and evaluating relevant preferences and handling multiple perspectives. Herein, by 'preference' is meant a greater interest expressed by an individual for a particular alternative over others; by 'relevant' is meant a variety of preferences which are significant (or important) to a particular person acting as a decision maker; and by 'perspective' is understood a position (e.g., social, technical, financial or environmental) adopted by a decision maker when expressing his/ her preferences or constraints
An evaluation methodology for the level of service at the airport landside system
A methodology is proposed for evaluating the level of service within an airport
landside system from the passenger's point of view using linguistic service
criteria. The new concept of level of service for a transport system, particularly
within the airports indicates that there must be strong stimulation in order to
proceed with the current stereotyped service standards which are being
criticised due to their being based on, either physical capacity/volume or
temporal/spatial standards that directly incorporates the perception of
passengers, the dominant users. Most service evaluation methodologies have
been concentrated on the factors of the time spent and the space provided.
These quantitative factors are reasonably simple to measure but represent a
narrow approach. Qualitative service level attributes are definitely important
factors when evaluating the level of service from a user's point of view. This
study has adopted three main evaluation factors: temporal or spatial factors as
quantitative measurements and comfort factors and reasonable service factors
as qualitative measurements. The service level evaluation involves the
passenger's subjective judgement as a perception for service provision. To
evaluate the level of service in the airport landside system from the user's
perception, this research proposes to apply a multi-decision model using fuzzy
set theory, in particular fuzzy approximate reasoning. Fuzzy set theory provides a
strict mathematical framework for vague conceptual phenomena and a
modelling language for real situations. The multi-decision model was applied to
a case study at Kimpo International Airport in Seoul, Korea. Results are
presented in terms of passenger satisfaction and dissatisfaction with a variety of
different values
Fuzzy Logic
Fuzzy Logic is becoming an essential method of solving problems in all domains. It gives tremendous impact on the design of autonomous intelligent systems. The purpose of this book is to introduce Hybrid Algorithms, Techniques, and Implementations of Fuzzy Logic. The book consists of thirteen chapters highlighting models and principles of fuzzy logic and issues on its techniques and implementations. The intended readers of this book are engineers, researchers, and graduate students interested in fuzzy logic systems
Proceedings of the Third International Workshop on Neural Networks and Fuzzy Logic, volume 1
Documented here are papers presented at the Neural Networks and Fuzzy Logic Workshop sponsored by the National Aeronautics and Space Administration and cosponsored by the University of Houston, Clear Lake. The workshop was held June 1-3, 1992 at the Lyndon B. Johnson Space Center in Houston, Texas. During the three days approximately 50 papers were presented. Technical topics addressed included adaptive systems; learning algorithms; network architectures; vision; robotics; neurobiological connections; speech recognition and synthesis; fuzzy set theory and application, control, and dynamics processing; space applications; fuzzy logic and neural network computers; approximate reasoning; and multiobject decision making
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