Network Science Research Laboratory (NSRL) Discrete Event Toolkit

Science.gov (United States)

2016-01-01

ARL-TR-7579 ● JAN 2016 US Army Research Laboratory Network Science Research Laboratory (NSRL) Discrete Event Toolkit by...Laboratory (NSRL) Discrete Event Toolkit by Theron Trout and Andrew J Toth Computational and Information Sciences Directorate, ARL...Research Laboratory (NSRL) Discrete Event Toolkit 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Theron Trout

Synchronization Of Parallel Discrete Event Simulations

Science.gov (United States)

Steinman, Jeffrey S.

1992-01-01

Adaptive, parallel, discrete-event-simulation-synchronization algorithm, Breathing Time Buckets, developed in Synchronous Parallel Environment for Emulation and Discrete Event Simulation (SPEEDES) operating system. Algorithm allows parallel simulations to process events optimistically in fluctuating time cycles that naturally adapt while simulation in progress. Combines best of optimistic and conservative synchronization strategies while avoiding major disadvantages. Algorithm processes events optimistically in time cycles adapting while simulation in progress. Well suited for modeling communication networks, for large-scale war games, for simulated flights of aircraft, for simulations of computer equipment, for mathematical modeling, for interactive engineering simulations, and for depictions of flows of information.

On the Expected Value of Fuzzy Events

Czech Academy of Sciences Publication Activity Database

Klement, E.P.; Mesiar, Radko

2015-01-01

Roč. 23, Supplement 1 (2015), s. 57-74 ISSN 0218-4885 Institutional support: RVO:67985556 Keywords : expected value * fuzzy event * Choquet integral Subject RIV: BA - General Mathematics Impact factor: 1.000, year: 2015 http://library.utia.cas.cz/separaty/2015/E/mesiar-0452568.pdf

An algebra of discrete event processes

Science.gov (United States)

Heymann, Michael; Meyer, George

1991-01-01

This report deals with an algebraic framework for modeling and control of discrete event processes. The report consists of two parts. The first part is introductory, and consists of a tutorial survey of the theory of concurrency in the spirit of Hoare's CSP, and an examination of the suitability of such an algebraic framework for dealing with various aspects of discrete event control. To this end a new concurrency operator is introduced and it is shown how the resulting framework can be applied. It is further shown that a suitable theory that deals with the new concurrency operator must be developed. In the second part of the report the formal algebra of discrete event control is developed. At the present time the second part of the report is still an incomplete and occasionally tentative working paper.

Use cases of discrete event simulation. Appliance and research

Energy Technology Data Exchange (ETDEWEB)

Bangsow, Steffen (ed.)

2012-11-01

Use Cases of Discrete Event Simulation. Includes case studies from various important industries such as automotive, aerospace, robotics, production industry. Written by leading experts in the field. Over the last decades Discrete Event Simulation has conquered many different application areas. This trend is, on the one hand, driven by an ever wider use of this technology in different fields of science and on the other hand by an incredibly creative use of available software programs through dedicated experts. This book contains articles from scientists and experts from 10 countries. They illuminate the width of application of this technology and the quality of problems solved using Discrete Event Simulation. Practical applications of simulation dominate in the present book. The book is aimed to researchers and students who deal in their work with Discrete Event Simulation and which want to inform them about current applications. By focusing on discrete event simulation, this book can also serve as an inspiration source for practitioners for solving specific problems during their work. Decision makers who deal with the question of the introduction of discrete event simulation for planning support and optimization this book provides a contribution to the orientation, what specific problems could be solved with the help of Discrete Event Simulation within the organization.

Stochastic Optimal Estimation with Fuzzy Random Variables and Fuzzy Kalman Filtering

Institute of Scientific and Technical Information of China (English)

FENG Yu-hu

2005-01-01

By constructing a mean-square performance index in the case of fuzzy random variable, the optimal estimation theorem for unknown fuzzy state using the fuzzy observation data are given. The state and output of linear discrete-time dynamic fuzzy system with Gaussian noise are Gaussian fuzzy random variable sequences. An approach to fuzzy Kalman filtering is discussed. Fuzzy Kalman filtering contains two parts: a real-valued non-random recurrence equation and the standard Kalman filtering.

Use Cases of Discrete Event Simulation Appliance and Research

CERN Document Server

2012-01-01

Over the last decades Discrete Event Simulation has conquered many different application areas. This trend is, on the one hand, driven by an ever wider use of this technology in different fields of science and on the other hand by an incredibly creative use of available software programs through dedicated experts. This book contains articles from scientists and experts from 10 countries. They illuminate the width of application of this technology and the quality of problems solved using Discrete Event Simulation. Practical applications of simulation dominate in the present book.   The book is aimed to researchers and students who deal in their work with Discrete Event Simulation and which want to inform them about current applications. By focusing on discrete event simulation, this book can also serve as an inspiration source for practitioners for solving specific problems during their work. Decision makers who deal with the question of the introduction of discrete event simulation for planning support and o...

? and ? nonquadratic stabilisation of discrete-time Takagi-Sugeno systems based on multi-instant fuzzy Lyapunov functions

Science.gov (United States)

Tognetti, Eduardo S.; Oliveira, Ricardo C. L. F.; Peres, Pedro L. D.

2015-01-01

The problem of state feedback control design for discrete-time Takagi-Sugeno (TS) (T-S) fuzzy systems is investigated in this paper. A Lyapunov function, which is quadratic in the state and presents a multi-polynomial dependence on the fuzzy weighting functions at the current and past instants of time, is proposed.This function contains, as particular cases, other previous Lyapunov functions already used in the literature, being able to provide less conservative conditions of control design for TS fuzzy systems. The structure of the proposed Lyapunov function also motivates the design of a new stabilising compensator for Takagi-Sugeno fuzzy systems. The main novelty of the proposed state feedback control law is that the gain is composed of matrices with multi-polynomial dependence on the fuzzy weighting functions at a set of past instants of time, including the current one. The conditions for the existence of a stabilising state feedback control law that minimises an upper bound to the ? or ? norms are given in terms of linear matrix inequalities. Numerical examples show that the approach can be less conservative and more efficient than other methods available in the literature.

An Intelligent Complex Event Processing with D Numbers under Fuzzy Environment

Directory of Open Access Journals (Sweden)

Fuyuan Xiao

2016-01-01

Full Text Available Efficient matching of incoming mass events to persistent queries is fundamental to complex event processing systems. Event matching based on pattern rule is an important feature of complex event processing engine. However, the intrinsic uncertainty in pattern rules which are predecided by experts increases the difficulties of effective complex event processing. It inevitably involves various types of the intrinsic uncertainty, such as imprecision, fuzziness, and incompleteness, due to the inability of human beings subjective judgment. Nevertheless, D numbers is a new mathematic tool to model uncertainty, since it ignores the condition that elements on the frame must be mutually exclusive. To address the above issues, an intelligent complex event processing method with D numbers under fuzzy environment is proposed based on the Technique for Order Preferences by Similarity to an Ideal Solution (TOPSIS method. The novel method can fully support decision making in complex event processing systems. Finally, a numerical example is provided to evaluate the efficiency of the proposed method.

Generalized Detectability for Discrete Event Systems

Science.gov (United States)

Shu, Shaolong; Lin, Feng

2011-01-01

In our previous work, we investigated detectability of discrete event systems, which is defined as the ability to determine the current and subsequent states of a system based on observation. For different applications, we defined four types of detectabilities: (weak) detectability, strong detectability, (weak) periodic detectability, and strong periodic detectability. In this paper, we extend our results in three aspects. (1) We extend detectability from deterministic systems to nondeterministic systems. Such a generalization is necessary because there are many systems that need to be modeled as nondeterministic discrete event systems. (2) We develop polynomial algorithms to check strong detectability. The previous algorithms are based on observer whose construction is of exponential complexity, while the new algorithms are based on a new automaton called detector. (3) We extend detectability to D-detectability. While detectability requires determining the exact state of a system, D-detectability relaxes this requirement by asking only to distinguish certain pairs of states. With these extensions, the theory on detectability of discrete event systems becomes more applicable in solving many practical problems. PMID:21691432

The fuzzy set theory application to the analysis of accident progression event trees with phenomenological uncertainty issues

International Nuclear Information System (INIS)

Chun, Moon-Hyun; Ahn, Kwang-Il

1991-01-01

Fuzzy set theory provides a formal framework for dealing with the imprecision and vagueness inherent in the expert judgement, and therefore it can be used for more effective analysis of accident progression of PRA where experts opinion is a major means for quantifying some event probabilities and uncertainties. In this paper, an example application of the fuzzy set theory is first made to a simple portion of a given accident progression event tree with typical qualitative fuzzy input data, and thereby computational algorithms suitable for application of the fuzzy set theory to the accident progression event tree analysis are identified and illustrated with example applications. Then the procedure used in the simple example is extended to extremely complex accident progression event trees with a number of phenomenological uncertainty issues, i.e., a typical plant damage state 'SEC' of the Zion Nuclear Power Plant risk assessment. The results show that the fuzzy averages of the fuzzy outcomes are very close to the mean values obtained by current methods. The main purpose of this paper is to provide a formal procedure for application of the fuzzy set theory to accident progression event trees with imprecise and qualitative branch probabilities and/or with a number of phenomenological uncertainty issues. (author)

Discrete event systems diagnosis and diagnosability

CERN Document Server

Sayed-Mouchaweh, Moamar

2014-01-01

Discrete Event Systems: Diagnosis and Diagnosability addresses the problem of fault diagnosis of Discrete Event Systems (DES). This book provides the basic techniques and approaches necessary for the design of an efficient fault diagnosis system for a wide range of modern engineering applications. The different techniques and approaches are classified according to several criteria such as: modeling tools (Automata, Petri nets) that is used to construct the model; the information (qualitative based on events occurrences and/or states outputs, quantitative based on signal processing and data analysis) that is needed to analyze and achieve the diagnosis; the decision structure (centralized, decentralized) that is required to achieve the diagnosis. The goal of this classification is to select the efficient method to achieve the fault diagnosis according to the application constraints. This book focuses on the centralized and decentralized event based diagnosis approaches using formal language and automata as mode...

Control of Discrete-Event Systems Automata and Petri Net Perspectives

CERN Document Server

Silva, Manuel; Schuppen, Jan

2013-01-01

Control of Discrete-event Systems provides a survey of the most important topics in the discrete-event systems theory with particular focus on finite-state automata, Petri nets and max-plus algebra. Coverage ranges from introductory material on the basic notions and definitions of discrete-event systems to more recent results. Special attention is given to results on supervisory control, state estimation and fault diagnosis of both centralized and distributed/decentralized systems developed in the framework of the Distributed Supervisory Control of Large Plants (DISC) project. Later parts of the text are devoted to the study of congested systems though fluidization, an over approximation allowing a much more efficient study of observation and control problems of timed Petri nets. Finally, the max-plus algebraic approach to the analysis and control of choice-free systems is also considered. Control of Discrete-event Systems provides an introduction to discrete-event systems for readers that are not familiar wi...

Modeling and simulation of discrete event systems

CERN Document Server

Choi, Byoung Kyu

2013-01-01

Computer modeling and simulation (M&S) allows engineers to study and analyze complex systems. Discrete-event system (DES)-M&S is used in modern management, industrial engineering, computer science, and the military. As computer speeds and memory capacity increase, so DES-M&S tools become more powerful and more widely used in solving real-life problems. Based on over 20 years of evolution within a classroom environment, as well as on decades-long experience in developing simulation-based solutions for high-tech industries, Modeling and Simulation of Discrete-Event Systems is the only book on

A Review of Fuzzy Logic and Neural Network Based Intelligent Control Design for Discrete-Time Systems

Directory of Open Access Journals (Sweden)

Yiming Jiang

2016-01-01

Full Text Available Over the last few decades, the intelligent control methods such as fuzzy logic control (FLC and neural network (NN control have been successfully used in various applications. The rapid development of digital computer based control systems requires control signals to be calculated in a digital or discrete-time form. In this background, the intelligent control methods developed for discrete-time systems have drawn great attentions. This survey aims to present a summary of the state of the art of the design of FLC and NN-based intelligent control for discrete-time systems. For discrete-time FLC systems, numerous remarkable design approaches are introduced and a series of efficient methods to deal with the robustness, stability, and time delay of FLC discrete-time systems are recommended. Techniques for NN-based intelligent control for discrete-time systems, such as adaptive methods and adaptive dynamic programming approaches, are also reviewed. Overall, this paper is devoted to make a brief summary for recent progresses in FLC and NN-based intelligent control design for discrete-time systems as well as to present our thoughts and considerations of recent trends and potential research directions in this area.

DEVS representation of dynamical systems - Event-based intelligent control. [Discrete Event System Specification

Science.gov (United States)

Zeigler, Bernard P.

1989-01-01

It is shown how systems can be advantageously represented as discrete-event models by using DEVS (discrete-event system specification), a set-theoretic formalism. Such DEVS models provide a basis for the design of event-based logic control. In this control paradigm, the controller expects to receive confirming sensor responses to its control commands within definite time windows determined by its DEVS model of the system under control. The event-based contral paradigm is applied in advanced robotic and intelligent automation, showing how classical process control can be readily interfaced with rule-based symbolic reasoning systems.

Analysis hierarchical model for discrete event systems

Science.gov (United States)

Ciortea, E. M.

2015-11-01

The This paper presents the hierarchical model based on discrete event network for robotic systems. Based on the hierarchical approach, Petri network is analysed as a network of the highest conceptual level and the lowest level of local control. For modelling and control of complex robotic systems using extended Petri nets. Such a system is structured, controlled and analysed in this paper by using Visual Object Net ++ package that is relatively simple and easy to use, and the results are shown as representations easy to interpret. The hierarchical structure of the robotic system is implemented on computers analysed using specialized programs. Implementation of hierarchical model discrete event systems, as a real-time operating system on a computer network connected via a serial bus is possible, where each computer is dedicated to local and Petri model of a subsystem global robotic system. Since Petri models are simplified to apply general computers, analysis, modelling, complex manufacturing systems control can be achieved using Petri nets. Discrete event systems is a pragmatic tool for modelling industrial systems. For system modelling using Petri nets because we have our system where discrete event. To highlight the auxiliary time Petri model using transport stream divided into hierarchical levels and sections are analysed successively. Proposed robotic system simulation using timed Petri, offers the opportunity to view the robotic time. Application of goods or robotic and transmission times obtained by measuring spot is obtained graphics showing the average time for transport activity, using the parameters sets of finished products. individually.

Discretely Integrated Condition Event (DICE) Simulation for Pharmacoeconomics.

Science.gov (United States)

Caro, J Jaime

2016-07-01

Several decision-analytic modeling techniques are in use for pharmacoeconomic analyses. Discretely integrated condition event (DICE) simulation is proposed as a unifying approach that has been deliberately designed to meet the modeling requirements in a straightforward transparent way, without forcing assumptions (e.g., only one transition per cycle) or unnecessary complexity. At the core of DICE are conditions that represent aspects that persist over time. They have levels that can change and many may coexist. Events reflect instantaneous occurrences that may modify some conditions or the timing of other events. The conditions are discretely integrated with events by updating their levels at those times. Profiles of determinant values allow for differences among patients in the predictors of the disease course. Any number of valuations (e.g., utility, cost, willingness-to-pay) of conditions and events can be applied concurrently in a single run. A DICE model is conveniently specified in a series of tables that follow a consistent format and the simulation can be implemented fully in MS Excel, facilitating review and validation. DICE incorporates both state-transition (Markov) models and non-resource-constrained discrete event simulation in a single formulation; it can be executed as a cohort or a microsimulation; and deterministically or stochastically.

Mixed H-Infinity and Passive Filtering for Discrete Fuzzy Neural Networks With Stochastic Jumps and Time Delays.

Science.gov (United States)

Shi, Peng; Zhang, Yingqi; Chadli, Mohammed; Agarwal, Ramesh K

2016-04-01

In this brief, the problems of the mixed H-infinity and passivity performance analysis and design are investigated for discrete time-delay neural networks with Markovian jump parameters represented by Takagi-Sugeno fuzzy model. The main purpose of this brief is to design a filter to guarantee that the augmented Markovian jump fuzzy neural networks are stable in mean-square sense and satisfy a prescribed passivity performance index by employing the Lyapunov method and the stochastic analysis technique. Applying the matrix decomposition techniques, sufficient conditions are provided for the solvability of the problems, which can be formulated in terms of linear matrix inequalities. A numerical example is also presented to illustrate the effectiveness of the proposed techniques.

Control of discrete-event systems with modular or distributed structure

Czech Academy of Sciences Publication Activity Database

Komenda, Jan; van Schuppen, J. H.

2007-01-01

Roč. 388, č. 3 (2007), s. 199-226 ISSN 0304-3975 R&D Projects: GA AV ČR(CZ) KJB100190609 Institutional research plan: CEZ:AV0Z10190503 Keywords : supervisory control * modular discrete-event system * distributed discrete-event system Subject RIV: BA - General Mathematics Impact factor: 0.735, year: 2007

Intuitionistic fuzzy calculus

CERN Document Server

Lei, Qian

2017-01-01

This book offers a comprehensive and systematic review of the latest research findings in the area of intuitionistic fuzzy calculus. After introducing the intuitionistic fuzzy numbers’ operational laws and their geometrical and algebraic properties, the book defines the concept of intuitionistic fuzzy functions and presents the research on the derivative, differential, indefinite integral and definite integral of intuitionistic fuzzy functions. It also discusses some of the methods that have been successfully used to deal with continuous intuitionistic fuzzy information or data, which are different from the previous aggregation operators focusing on discrete information or data. Mainly intended for engineers and researchers in the fields of fuzzy mathematics, operations research, information science and management science, this book is also a valuable textbook for postgraduate and advanced undergraduate students alike.

H∞ Filtering for Discrete Markov Jump Singular Systems with Mode-Dependent Time Delay Based on T-S Fuzzy Model

Directory of Open Access Journals (Sweden)

Cheng Gong

2014-01-01

Full Text Available This paper investigates the H∞ filtering problem of discrete singular Markov jump systems (SMJSs with mode-dependent time delay based on T-S fuzzy model. First, by Lyapunov-Krasovskii functional approach, a delay-dependent sufficient condition on H∞-disturbance attenuation is presented, in which both stability and prescribed H∞ performance are required to be achieved for the filtering-error systems. Then, based on the condition, the delay-dependent H∞ filter design scheme for SMJSs with mode-dependent time delay based on T-S fuzzy model is developed in term of linear matrix inequality (LMI. Finally, an example is given to illustrate the effectiveness of the result.

A Cluster-Based Fuzzy Fusion Algorithm for Event Detection in Heterogeneous Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

ZiQi Hao

2015-01-01

Full Text Available As limited energy is one of the tough challenges in wireless sensor networks (WSN, energy saving becomes important in increasing the lifecycle of the network. Data fusion enables combining information from several sources thus to provide a unified scenario, which can significantly save sensor energy and enhance sensing data accuracy. In this paper, we propose a cluster-based data fusion algorithm for event detection. We use k-means algorithm to form the nodes into clusters, which can significantly reduce the energy consumption of intracluster communication. Distances between cluster heads and event and energy of clusters are fuzzified, thus to use a fuzzy logic to select the clusters that will participate in data uploading and fusion. Fuzzy logic method is also used by cluster heads for local decision, and then the local decision results are sent to the base station. Decision-level fusion for final decision of event is performed by base station according to the uploaded local decisions and fusion support degree of clusters calculated by fuzzy logic method. The effectiveness of this algorithm is demonstrated by simulation results.

Manufacturing plant performance evaluation by discrete event simulation

International Nuclear Information System (INIS)

Rosli Darmawan; Mohd Rasid Osman; Rosnah Mohd Yusuff; Napsiah Ismail; Zulkiflie Leman

2002-01-01

A case study was conducted to evaluate the performance of a manufacturing plant using discrete event simulation technique. The study was carried out on animal feed production plant. Sterifeed plant at Malaysian Institute for Nuclear Technology Research (MINT), Selangor, Malaysia. The plant was modelled base on the actual manufacturing activities recorded by the operators. The simulation was carried out using a discrete event simulation software. The model was validated by comparing the simulation results with the actual operational data of the plant. The simulation results show some weaknesses with the current plant design and proposals were made to improve the plant performance. (Author)

ANALYSIS OF INPATIENT HOSPITAL STAFF MENTAL WORKLOAD BY MEANS OF DISCRETE-EVENT SIMULATION

Science.gov (United States)

2016-03-24

ANALYSIS OF INPATIENT HOSPITAL STAFF MENTAL WORKLOAD BY MEANS OF DISCRETE -EVENT SIMULATION...in the United States. AFIT-ENV-MS-16-M-166 ANALYSIS OF INPATIENT HOSPITAL STAFF MENTAL WORKLOAD BY MEANS OF DISCRETE -EVENT SIMULATION...UNLIMITED. AFIT-ENV-MS-16-M-166 ANALYSIS OF INPATIENT HOSPITAL STAFF MENTAL WORKLOAD BY MEANS OF DISCRETE -EVENT SIMULATION Erich W

Non-Lipschitz Dynamics Approach to Discrete Event Systems

Science.gov (United States)

Zak, M.; Meyers, R.

1995-01-01

This paper presents and discusses a mathematical formalism for simulation of discrete event dynamics (DED) - a special type of 'man- made' system designed to aid specific areas of information processing. A main objective is to demonstrate that the mathematical formalism for DED can be based upon the terminal model of Newtonian dynamics which allows one to relax Lipschitz conditions at some discrete points.

Decentralized fuzzy control of multiple nonholonomic vehicles

Energy Technology Data Exchange (ETDEWEB)

Driessen, B.J.; Feddema, J.T.; Kwok, K.S.

1997-09-01

This work considers the problem of controlling multiple nonholonomic vehicles so that they converge to a scent source without colliding with each other. Since the control is to be implemented on simple 8-bit microcontrollers, fuzzy control rules are used to simplify a linear quadratic regulator control design. The inputs to the fuzzy controllers for each vehicle are the (noisy) direction to the source, the distance to the closest neighbor vehicle, and the direction to the closest vehicle. These directions are discretized into four values: Forward, Behind, Left, and Right, and the distance into three values: Near, Far, Gone. The values of the control at these discrete values are obtained based on the collision-avoidance repulsive forces and the change of variables that reduces the motion control problem of each nonholonomic vehicle to a nonsingular one with two degrees of freedom, instead of three. A fuzzy inference system is used to obtain control values for inputs between the small number of discrete input values. Simulation results are provided which demonstrate that the fuzzy control law performs well compared to the exact controller. In fact, the fuzzy controller demonstrates improved robustness to noise.

Running Parallel Discrete Event Simulators on Sierra

Energy Technology Data Exchange (ETDEWEB)

Barnes, P. D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Jefferson, D. R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2015-12-03

In this proposal we consider porting the ROSS/Charm++ simulator and the discrete event models that run under its control so that they run on the Sierra architecture and make efficient use of the Volta GPUs.

Failure diagnosis using discrete event models

International Nuclear Information System (INIS)

Sampath, M.; Sengupta, R.; Lafortune, S.; Teneketzis, D.; Sinnamohideen, K.

1994-01-01

We propose a Discrete Event Systems (DES) approach to the failure diagnosis problem. We present a methodology for modeling physical systems in a DES framework. We discuss the notion of diagnosability and present the construction procedure of the diagnoser. Finally, we illustrate our approach using a Heating, Ventilation and Air Conditioning (HVAC) system

Reproductive Health Services Discrete-Event Simulation

OpenAIRE

Lee, Sungjoo; Giles, Denise F.; Goldsman, David; Cook, Douglas A.; Mishra, Ninad; McCarthy, Brian

2006-01-01

Low resource healthcare environments are often characteristic of patient flow patterns with varying patient risks, extensive patient waiting times, uneven workload distributions, and inefficient service delivery. Models from industrial and systems engineering allow for a greater examination of processes by applying discrete-event computer simulation techniques to evaluate and optimize hospital performance.

A fuzzy-based reliability approach to evaluate basic events of fault tree analysis for nuclear power plant probabilistic safety assessment

International Nuclear Information System (INIS)

Purba, Julwan Hendry

2014-01-01

Highlights: • We propose a fuzzy-based reliability approach to evaluate basic event reliabilities. • It implements the concepts of failure possibilities and fuzzy sets. • Experts evaluate basic event failure possibilities using qualitative words. • Triangular fuzzy numbers mathematically represent qualitative failure possibilities. • It is a very good alternative for conventional reliability approach. - Abstract: Fault tree analysis has been widely utilized as a tool for nuclear power plant probabilistic safety assessment. This analysis can be completed only if all basic events of the system fault tree have their quantitative failure rates or failure probabilities. However, it is difficult to obtain those failure data due to insufficient data, environment changing or new components. This study proposes a fuzzy-based reliability approach to evaluate basic events of system fault trees whose failure precise probability distributions of their lifetime to failures are not available. It applies the concept of failure possibilities to qualitatively evaluate basic events and the concept of fuzzy sets to quantitatively represent the corresponding failure possibilities. To demonstrate the feasibility and the effectiveness of the proposed approach, the actual basic event failure probabilities collected from the operational experiences of the David–Besse design of the Babcock and Wilcox reactor protection system fault tree are used to benchmark the failure probabilities generated by the proposed approach. The results confirm that the proposed fuzzy-based reliability approach arises as a suitable alternative for the conventional probabilistic reliability approach when basic events do not have the corresponding quantitative historical failure data for determining their reliability characteristics. Hence, it overcomes the limitation of the conventional fault tree analysis for nuclear power plant probabilistic safety assessment

Disaster Response Modeling Through Discrete-Event Simulation

Science.gov (United States)

Wang, Jeffrey; Gilmer, Graham

2012-01-01

Organizations today are required to plan against a rapidly changing, high-cost environment. This is especially true for first responders to disasters and other incidents, where critical decisions must be made in a timely manner to save lives and resources. Discrete-event simulations enable organizations to make better decisions by visualizing complex processes and the impact of proposed changes before they are implemented. A discrete-event simulation using Simio software has been developed to effectively analyze and quantify the imagery capabilities of domestic aviation resources conducting relief missions. This approach has helped synthesize large amounts of data to better visualize process flows, manage resources, and pinpoint capability gaps and shortfalls in disaster response scenarios. Simulation outputs and results have supported decision makers in the understanding of high risk locations, key resource placement, and the effectiveness of proposed improvements.

Quantum black holes: the event horizon as a fuzzy sphere

International Nuclear Information System (INIS)

Dolan, Brian P.

2005-01-01

Modeling the event horizon of a black hole by a fuzzy sphere leads us to modify some suggestions in the literature concerning black hole mass spectra. We derive a formula for the mass spectrum of quantum black holes in terms of four integers which define the area, angular momentum, electric and magnetic charge of the black hole. Although the event horizon becomes a commutative sphere in the classical limit a vestige of the quantum theory still persists in that the event horizon stereographically projects onto the non-commutative plane. We also suggest how the classical bounds on extremal black holes might be modified in the quantum theory. (author)

Discrete Event Simulation of Distributed Team Communication

Science.gov (United States)

2012-03-22

performs, and auditory information that is provided through multiple audio devices with speech response. This paper extends previous discrete event workload...2008, pg. 1) notes that “Architecture modeling furnishes abstrac- tions for use in managing complexities, allowing engineers to visualise the proposed

Synchronization of autonomous objects in discrete event simulation

Science.gov (United States)

Rogers, Ralph V.

1990-01-01

Autonomous objects in event-driven discrete event simulation offer the potential to combine the freedom of unrestricted movement and positional accuracy through Euclidean space of time-driven models with the computational efficiency of event-driven simulation. The principal challenge to autonomous object implementation is object synchronization. The concept of a spatial blackboard is offered as a potential methodology for synchronization. The issues facing implementation of a spatial blackboard are outlined and discussed.

Optimization of Operations Resources via Discrete Event Simulation Modeling

Science.gov (United States)

Joshi, B.; Morris, D.; White, N.; Unal, R.

1996-01-01

The resource levels required for operation and support of reusable launch vehicles are typically defined through discrete event simulation modeling. Minimizing these resources constitutes an optimization problem involving discrete variables and simulation. Conventional approaches to solve such optimization problems involving integer valued decision variables are the pattern search and statistical methods. However, in a simulation environment that is characterized by search spaces of unknown topology and stochastic measures, these optimization approaches often prove inadequate. In this paper, we have explored the applicability of genetic algorithms to the simulation domain. Genetic algorithms provide a robust search strategy that does not require continuity and differentiability of the problem domain. The genetic algorithm successfully minimized the operation and support activities for a space vehicle, through a discrete event simulation model. The practical issues associated with simulation optimization, such as stochastic variables and constraints, were also taken into consideration.

Hierarchical Discrete Event Supervisory Control of Aircraft Propulsion Systems

Science.gov (United States)

Yasar, Murat; Tolani, Devendra; Ray, Asok; Shah, Neerav; Litt, Jonathan S.

2004-01-01

This paper presents a hierarchical application of Discrete Event Supervisory (DES) control theory for intelligent decision and control of a twin-engine aircraft propulsion system. A dual layer hierarchical DES controller is designed to supervise and coordinate the operation of two engines of the propulsion system. The two engines are individually controlled to achieve enhanced performance and reliability, necessary for fulfilling the mission objectives. Each engine is operated under a continuously varying control system that maintains the specified performance and a local discrete-event supervisor for condition monitoring and life extending control. A global upper level DES controller is designed for load balancing and overall health management of the propulsion system.

Discrete Event Simulation Computers can be used to simulate the ...

Indian Academy of Sciences (India)

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people who use computers every moment of their waking lives, others even ... How is discrete event simulation different from other kinds of simulation? ... time, energy consumption .... Schedule the CustomerDeparture event for this customer.

Approximation-Based Discrete-Time Adaptive Position Tracking Control for Interior Permanent Magnet Synchronous Motors.

Science.gov (United States)

Yu, Jinpeng; Shi, Peng; Yu, Haisheng; Chen, Bing; Lin, Chong

2015-07-01

This paper considers the problem of discrete-time adaptive position tracking control for a interior permanent magnet synchronous motor (IPMSM) based on fuzzy-approximation. Fuzzy logic systems are used to approximate the nonlinearities of the discrete-time IPMSM drive system which is derived by direct discretization using Euler method, and a discrete-time fuzzy position tracking controller is designed via backstepping approach. In contrast to existing results, the advantage of the scheme is that the number of the adjustable parameters is reduced to two only and the problem of coupling nonlinearity can be overcome. It is shown that the proposed discrete-time fuzzy controller can guarantee the tracking error converges to a small neighborhood of the origin and all the signals are bounded. Simulation results illustrate the effectiveness and the potentials of the theoretic results obtained.

Probabilistic fuzzy systems as additive fuzzy systems

NARCIS (Netherlands)

Almeida, R.J.; Verbeek, N.; Kaymak, U.; Costa Sousa, da J.M.; Laurent, A.; Strauss, O.; Bouchon-Meunier, B.; Yager, R.

2014-01-01

Probabilistic fuzzy systems combine a linguistic description of the system behaviour with statistical properties of data. It was originally derived based on Zadeh’s concept of probability of a fuzzy event. Two possible and equivalent additive reasoning schemes were proposed, that lead to the

Parallel discrete event simulation using shared memory

Science.gov (United States)

Reed, Daniel A.; Malony, Allen D.; Mccredie, Bradley D.

1988-01-01

With traditional event-list techniques, evaluating a detailed discrete-event simulation-model can often require hours or even days of computation time. By eliminating the event list and maintaining only sufficient synchronization to ensure causality, parallel simulation can potentially provide speedups that are linear in the numbers of processors. A set of shared-memory experiments, using the Chandy-Misra distributed-simulation algorithm, to simulate networks of queues is presented. Parameters of the study include queueing network topology and routing probabilities, number of processors, and assignment of network nodes to processors. These experiments show that Chandy-Misra distributed simulation is a questionable alternative to sequential-simulation of most queueing network models.

Integrating Continuous-Time and Discrete-Event Concepts in Process Modelling, Simulation and Control

NARCIS (Netherlands)

Beek, van D.A.; Gordijn, S.H.F.; Rooda, J.E.; Ertas, A.

1995-01-01

Currently, modelling of systems in the process industry requires the use of different specification languages for the specification of the discrete-event and continuous-time subsystems. In this way, models are restricted to individual subsystems of either a continuous-time or discrete-event nature.

Discrete Events as Units of Perceived Time

Science.gov (United States)

Liverence, Brandon M.; Scholl, Brian J.

2012-01-01

In visual images, we perceive both space (as a continuous visual medium) and objects (that inhabit space). Similarly, in dynamic visual experience, we perceive both continuous time and discrete events. What is the relationship between these units of experience? The most intuitive answer may be similar to the spatial case: time is perceived as an…

Program For Parallel Discrete-Event Simulation

Science.gov (United States)

Beckman, Brian C.; Blume, Leo R.; Geiselman, John S.; Presley, Matthew T.; Wedel, John J., Jr.; Bellenot, Steven F.; Diloreto, Michael; Hontalas, Philip J.; Reiher, Peter L.; Weiland, Frederick P.

1991-01-01

User does not have to add any special logic to aid in synchronization. Time Warp Operating System (TWOS) computer program is special-purpose operating system designed to support parallel discrete-event simulation. Complete implementation of Time Warp mechanism. Supports only simulations and other computations designed for virtual time. Time Warp Simulator (TWSIM) subdirectory contains sequential simulation engine interface-compatible with TWOS. TWOS and TWSIM written in, and support simulations in, C programming language.

Discrete event simulation: Modeling simultaneous complications and outcomes

NARCIS (Netherlands)

Quik, E.H.; Feenstra, T.L.; Krabbe, P.F.M.

2012-01-01

OBJECTIVES: To present an effective and elegant model approach to deal with specific characteristics of complex modeling. METHODS: A discrete event simulation (DES) model with multiple complications and multiple outcomes that each can occur simultaneously was developed. In this DES model parameters,

Hybrid modelling in discrete-event control system design

NARCIS (Netherlands)

Beek, van D.A.; Rooda, J.E.; Gordijn, S.H.F.; Borne, P.

1996-01-01

Simulation-based testing of discrete-event control systems can be advantageous. There is, however, a considerable difference between languages for real-time control and simulation languages. The Chi language, presented in this paper, is suited to specification and simulation of real-time control

Discrete Event Simulation Model of the Polaris 2.1 Gamma Ray Imaging Radiation Detection Device

Science.gov (United States)

2016-06-01

release; distribution is unlimited DISCRETE EVENT SIMULATION MODEL OF THE POLARIS 2.1 GAMMA RAY IMAGING RADIATION DETECTION DEVICE by Andres T...ONLY (Leave blank) 2. REPORT DATE June 2016 3. REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE DISCRETE EVENT SIMULATION MODEL...modeled. The platform, Simkit, was utilized to create a discrete event simulation (DES) model of the Polaris. After carefully constructing the DES

On constructing optimistic simulation algorithms for the discrete event system specification

International Nuclear Information System (INIS)

Nutaro, James J.

2008-01-01

This article describes a Time Warp simulation algorithm for discrete event models that are described in terms of the Discrete Event System Specification (DEVS). The article shows how the total state transition and total output function of a DEVS atomic model can be transformed into an event processing procedure for a logical process. A specific Time Warp algorithm is constructed around this logical process, and it is shown that the algorithm correctly simulates a DEVS coupled model that consists entirely of interacting atomic models. The simulation algorithm is presented abstractly; it is intended to provide a basis for implementing efficient and scalable parallel algorithms that correctly simulate DEVS models

Generating Li–Yorke chaos in a stable continuous-time T–S fuzzy model via time-delay feedback control

International Nuclear Information System (INIS)

Qiu-Ye, Sun; Hua-Guang, Zhang; Yan, Zhao

2010-01-01

This paper investigates the chaotification problem of a stable continuous-time T–S fuzzy system. A simple nonlinear state time-delay feedback controller is designed by parallel distributed compensation technique. Then, the asymptotically approximate relationship between the controlled continuous-time T–S fuzzy system with time-delay and a discrete-time T–S fuzzy system is established. Based on the discrete-time T–S fuzzy system, it proves that the chaos in the discrete-time T–S fuzzy system satisfies the Li–Yorke definition by choosing appropriate controller parameters via the revised Marotto theorem. Finally, the effectiveness of the proposed chaotic anticontrol method is verified by a practical example. (general)

Improving the Teaching of Discrete-Event Control Systems Using a LEGO Manufacturing Prototype

Science.gov (United States)

Sanchez, A.; Bucio, J.

2012-01-01

This paper discusses the usefulness of employing LEGO as a teaching-learning aid in a post-graduate-level first course on the control of discrete-event systems (DESs). The final assignment of the course is presented, which asks students to design and implement a modular hierarchical discrete-event supervisor for the coordination layer of a…

Empirical Bayes Approaches to Multivariate Fuzzy Partitions.

Science.gov (United States)

Woodbury, Max A.; Manton, Kenneth G.

1991-01-01

An empirical Bayes-maximum likelihood estimation procedure is presented for the application of fuzzy partition models in describing high dimensional discrete response data. The model describes individuals in terms of partial membership in multiple latent categories that represent bounded discrete spaces. (SLD)

Discrete event simulation as an ergonomic tool to predict workload exposures during systems design

NARCIS (Netherlands)

Perez, J.; Looze, M.P. de; Bosch, T.; Neumann, W.P.

2014-01-01

This methodological paper presents a novel approach to predict operator's mechanical exposure and fatigue accumulation in discrete event simulations. A biomechanical model of work-cycle loading is combined with a discrete event simulation model which provides work cycle patterns over the shift

Real Time Robot Soccer Game Event Detection Using Finite State Machines with Multiple Fuzzy Logic Probability Evaluators

Directory of Open Access Journals (Sweden)

Elmer P. Dadios

2009-01-01

Full Text Available This paper presents a new algorithm for real time event detection using Finite State Machines with multiple Fuzzy Logic Probability Evaluators (FLPEs. A machine referee for a robot soccer game is developed and is used as the platform to test the proposed algorithm. A novel technique to detect collisions and other events in microrobot soccer game under inaccurate and insufficient information is presented. The robots' collision is used to determine goalkeeper charging and goal score events which are crucial for the machine referee's decisions. The Main State Machine (MSM handles the schedule of event activation. The FLPE calculates the probabilities of the true occurrence of the events. Final decisions about the occurrences of events are evaluated and compared through threshold crisp probability values. The outputs of FLPEs can be combined to calculate the probability of an event composed of subevents. Using multiple fuzzy logic system, the FLPE utilizes minimal number of rules and can be tuned individually. Experimental results show the accuracy and robustness of the proposed algorithm.

Logical Discrete Event Systems in a trace theory based setting

NARCIS (Netherlands)

Smedinga, R.

1993-01-01

Discrete event systems can be modelled using a triple consisting of some alphabet (representing the events that might occur), and two trace sets (sets of possible strings) denoting the possible behaviour and the completed tasks of the system. Using this definition we are able to formulate and solve

Modular Control of Discrete-Event Systems with Coalgebra

Czech Academy of Sciences Publication Activity Database

Komenda, Jan; van Schuppen, J. H.

2008-01-01

Roč. 53, č. 2 (2008), s. 447-460 ISSN 0018-9286 R&D Projects: GA AV ČR(CZ) KJB100190609 Institutional research plan: CEZ:AV0Z10190503 Keywords : discrete-event systems * modular supervisory control * coalgebra Subject RIV: BA - General Mathematics Impact factor: 3.293, year: 2008

Synchronous Parallel Emulation and Discrete Event Simulation System with Self-Contained Simulation Objects and Active Event Objects

Science.gov (United States)

Steinman, Jeffrey S. (Inventor)

1998-01-01

The present invention is embodied in a method of performing object-oriented simulation and a system having inter-connected processor nodes operating in parallel to simulate mutual interactions of a set of discrete simulation objects distributed among the nodes as a sequence of discrete events changing state variables of respective simulation objects so as to generate new event-defining messages addressed to respective ones of the nodes. The object-oriented simulation is performed at each one of the nodes by assigning passive self-contained simulation objects to each one of the nodes, responding to messages received at one node by generating corresponding active event objects having user-defined inherent capabilities and individual time stamps and corresponding to respective events affecting one of the passive self-contained simulation objects of the one node, restricting the respective passive self-contained simulation objects to only providing and receiving information from die respective active event objects, requesting information and changing variables within a passive self-contained simulation object by the active event object, and producing corresponding messages specifying events resulting therefrom by the active event objects.

Adaptive Event-Triggered Control Based on Heuristic Dynamic Programming for Nonlinear Discrete-Time Systems.

Science.gov (United States)

Dong, Lu; Zhong, Xiangnan; Sun, Changyin; He, Haibo

2017-07-01

This paper presents the design of a novel adaptive event-triggered control method based on the heuristic dynamic programming (HDP) technique for nonlinear discrete-time systems with unknown system dynamics. In the proposed method, the control law is only updated when the event-triggered condition is violated. Compared with the periodic updates in the traditional adaptive dynamic programming (ADP) control, the proposed method can reduce the computation and transmission cost. An actor-critic framework is used to learn the optimal event-triggered control law and the value function. Furthermore, a model network is designed to estimate the system state vector. The main contribution of this paper is to design a new trigger threshold for discrete-time systems. A detailed Lyapunov stability analysis shows that our proposed event-triggered controller can asymptotically stabilize the discrete-time systems. Finally, we test our method on two different discrete-time systems, and the simulation results are included.

Powering stochastic reliability models by discrete event simulation

DEFF Research Database (Denmark)

Kozine, Igor; Wang, Xiaoyun

2012-01-01

it difficult to find a solution to the problem. The power of modern computers and recent developments in discrete-event simulation (DES) software enable to diminish some of the drawbacks of stochastic models. In this paper we describe the insights we have gained based on using both Markov and DES models...

Parallel Stochastic discrete event simulation of calcium dynamics in neuron.

Science.gov (United States)

Ishlam Patoary, Mohammad Nazrul; Tropper, Carl; McDougal, Robert A; Zhongwei, Lin; Lytton, William W

2017-09-26

The intra-cellular calcium signaling pathways of a neuron depends on both biochemical reactions and diffusions. Some quasi-isolated compartments (e.g. spines) are so small and calcium concentrations are so low that one extra molecule diffusing in by chance can make a nontrivial difference in its concentration (percentage-wise). These rare events can affect dynamics discretely in such way that they cannot be evaluated by a deterministic simulation. Stochastic models of such a system provide a more detailed understanding of these systems than existing deterministic models because they capture their behavior at a molecular level. Our research focuses on the development of a high performance parallel discrete event simulation environment, Neuron Time Warp (NTW), which is intended for use in the parallel simulation of stochastic reaction-diffusion systems such as intra-calcium signaling. NTW is integrated with NEURON, a simulator which is widely used within the neuroscience community. We simulate two models, a calcium buffer and a calcium wave model. The calcium buffer model is employed in order to verify the correctness and performance of NTW by comparing it to a serial deterministic simulation in NEURON. We also derived a discrete event calcium wave model from a deterministic model using the stochastic IP3R structure.

Modeling Anti-Air Warfare With Discrete Event Simulation and Analyzing Naval Convoy Operations

Science.gov (United States)

2016-06-01

W., & Scheaffer, R. L. (2008). Mathematical statistics with applications . Belmont, CA: Cengage Learning. 118 THIS PAGE INTENTIONALLY LEFT BLANK...WARFARE WITH DISCRETE EVENT SIMULATION AND ANALYZING NAVAL CONVOY OPERATIONS by Ali E. Opcin June 2016 Thesis Advisor: Arnold H. Buss Co...REPORT DATE June 2016 3. REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE MODELING ANTI-AIR WARFARE WITH DISCRETE EVENT

On Event/Time Triggered and Distributed Analysis of a WSN System for Event Detection, Using Fuzzy Logic

Directory of Open Access Journals (Sweden)

Sofia Maria Dima

2016-01-01

Full Text Available Event detection in realistic WSN environments is a critical research domain, while the environmental monitoring comprises one of its most pronounced applications. Although efforts related to the environmental applications have been presented in the current literature, there is a significant lack of investigation on the performance of such systems, when applied in wireless environments. Aiming at addressing this shortage, in this paper an advanced multimodal approach is followed based on fuzzy logic. The proposed fuzzy inference system (FIS is implemented on TelosB motes and evaluates the probability of fire detection while aiming towards power conservation. Additionally to a straightforward centralized approach, a distributed implementation of the above FIS is also proposed, aiming towards network congestion reduction while optimally distributing the energy consumption among network nodes so as to maximize network lifetime. Moreover this work proposes an event based execution of the aforementioned FIS aiming to further reduce the computational as well as the communication cost, compared to a periodical time triggered FIS execution. As a final contribution, performance metrics acquired from all the proposed FIS implementation techniques are thoroughly compared and analyzed with respect to critical network conditions aiming to offer realistic evaluation and thus objective conclusions’ extraction.

Discrete event simulation of the ATLAS second level trigger

International Nuclear Information System (INIS)

Vermeulen, J.C.; Dankers, R.J.; Hunt, S.; Harris, F.; Hortnagl, C.; Erasov, A.; Bogaerts, A.

1998-01-01

Discrete event simulation is applied for determining the computing and networking resources needed for the ATLAS second level trigger. This paper discusses the techniques used and some of the results obtained so far for well defined laboratory configurations and for the full system

Out-of-order parallel discrete event simulation for electronic system-level design

CERN Document Server

Chen, Weiwei

2014-01-01

This book offers readers a set of new approaches and tools a set of tools and techniques for facing challenges in parallelization with design of embedded systems.? It provides an advanced parallel simulation infrastructure for efficient and effective system-level model validation and development so as to build better products in less time.? Since parallel discrete event simulation (PDES) has the potential to exploit the underlying parallel computational capability in today's multi-core simulation hosts, the author begins by reviewing the parallelization of discrete event simulation, identifyin

Application of Discrete Event Simulation in Mine Production Forecast

African Journals Online (AJOL)

Application of Discrete Event Simulation in Mine Production Forecast. Felix Adaania Kaba, Victor Amoako Temeng, Peter Arroja Eshun. Abstract. Mine production forecast is pertinent to mining as it serves production goals for a production period. Perseus Mining Ghana Limited (PMGL), Ayanfuri, deterministically forecasts ...

New concept of direct torque neuro-fuzzy control for induction motor drives. Simulation study

Energy Technology Data Exchange (ETDEWEB)

Grabowski, P.Z. [Institute of Control and Industrial Electronics, Warsaw University of Technology, Warsaw (Poland)

1997-12-31

This paper presents a new control strategy in the discrete Direct Torque Control (DTC) based on neuro-fuzzy structure. Two schemes are proposed: neuro-fuzzy switching times calculator and neuro-fuzzy incremental controller with space vector modulator. These control strategies guarantee very good dynamic and steady-states characteristics, with very low sampling time and constant switching frequency. The proposed techniques are verified by simulation study of the whole drive system and results are compared with conventional discrete Direct Torque Control method. (orig.) 18 refs.

A non-orthogonal decomposition of flows into discrete events

Science.gov (United States)

Boxx, Isaac; Lewalle, Jacques

1998-11-01

This work is based on the formula for the inverse Hermitian wavelet transform. A signal can be interpreted as a (non-unique) superposition of near-singular, partially overlapping events arising from Dirac functions and/or its derivatives combined with diffusion.( No dynamics implied: dimensionless diffusion is related to the definition of the analyzing wavelets.) These events correspond to local maxima of spectral energy density. We successfully fitted model events of various orders on a succession of fields, ranging from elementary signals to one-dimensional hot-wire traces. We document edge effects, event overlap and its implications on the algorithm. The interpretation of the discrete singularities as flow events (such as coherent structures) and the fundamental non-uniqueness of the decomposition are discussed. The dynamics of these events will be examined in the companion paper.

Discrete event systems in dioid algebra and conventional algebra

CERN Document Server

Declerck, Philippe

2013-01-01

This book concerns the use of dioid algebra as (max, +) algebra to treat the synchronization of tasks expressed by the maximum of the ends of the tasks conditioning the beginning of another task - a criterion of linear programming. A classical example is the departure time of a train which should wait for the arrival of other trains in order to allow for the changeover of passengers.The content focuses on the modeling of a class of dynamic systems usually called "discrete event systems" where the timing of the events is crucial. Events are viewed as sudden changes in a process which i

Discrete event simulations for glycolysis pathway and energy balance

NARCIS (Netherlands)

Zwieten, van D.A.J.; Rooda, J.E.; Armbruster, H.D.; Nagy, J.D.

2010-01-01

In this report, the biological network of the glycolysis pathway has been modeled using discrete event models (DEMs). The most important feature of this pathway is that energy is released. To create a stable steady-state system an energy molecule equilibrating enzyme and metabolic reactions have

Complexity of deciding detectability in discrete event systems

Czech Academy of Sciences Publication Activity Database

Masopust, Tomáš

2018-01-01

Roč. 93, July (2018), s. 257-261 ISSN 0005-1098 Institutional support: RVO:67985840 Keywords : discrete event systems * finite automata * detectability Subject RIV: BA - General Mathematics OBOR OECD: Computer science s, information science , bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 5.451, year: 2016 https://www. science direct.com/ science /article/pii/S0005109818301730

Complexity of deciding detectability in discrete event systems

Czech Academy of Sciences Publication Activity Database

Masopust, Tomáš

2018-01-01

Roč. 93, July (2018), s. 257-261 ISSN 0005-1098 Institutional support: RVO:67985840 Keywords : discrete event systems * finite automata * detectability Subject RIV: BA - General Mathematics OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 5.451, year: 2016 https://www.sciencedirect.com/science/article/pii/S0005109818301730

Asynchronous discrete event schemes for PDEs

Science.gov (United States)

Stone, D.; Geiger, S.; Lord, G. J.

2017-08-01

A new class of asynchronous discrete-event simulation schemes for advection-diffusion-reaction equations is introduced, based on the principle of allowing quanta of mass to pass through faces of a (regular, structured) Cartesian finite volume grid. The timescales of these events are linked to the flux on the face. The resulting schemes are self-adaptive, and local in both time and space. Experiments are performed on realistic physical systems related to porous media flow applications, including a large 3D advection diffusion equation and advection diffusion reaction systems. The results are compared to highly accurate reference solutions where the temporal evolution is computed with exponential integrator schemes using the same finite volume discretisation. This allows a reliable estimation of the solution error. Our results indicate a first order convergence of the error as a control parameter is decreased, and we outline a framework for analysis.

Parallel discrete event simulation: A shared memory approach

Science.gov (United States)

Reed, Daniel A.; Malony, Allen D.; Mccredie, Bradley D.

1987-01-01

With traditional event list techniques, evaluating a detailed discrete event simulation model can often require hours or even days of computation time. Parallel simulation mimics the interacting servers and queues of a real system by assigning each simulated entity to a processor. By eliminating the event list and maintaining only sufficient synchronization to insure causality, parallel simulation can potentially provide speedups that are linear in the number of processors. A set of shared memory experiments is presented using the Chandy-Misra distributed simulation algorithm to simulate networks of queues. Parameters include queueing network topology and routing probabilities, number of processors, and assignment of network nodes to processors. These experiments show that Chandy-Misra distributed simulation is a questionable alternative to sequential simulation of most queueing network models.

Fuzzy multi-criteria approach to ordering policy ranking in a supply chain

Directory of Open Access Journals (Sweden)

Tadić Danijela

2005-01-01

Full Text Available In this paper, a new fuzzy multi-criteria mathematical model for the selection of the best among a finite number of ordering policy of raw material in a supply chain is developed. The problem treated is a part of the purchasing plan of a company in an uncertain environment and it is very common in business practice. Optimization criteria selected describe the performance measures of ordering policies and generally their relative importance is different. It is assumed that the values of the optimization criteria are vague and imprecise. They are described by discrete fuzzy numbers and by linguistic expressions. The linguistic expressions are modeled by discrete fuzzy sets. The measures of belief that one ordering policy is better than another are defined by comparing fuzzy numbers. An illustrative example is given.

Adaptive neuro-fuzzy inference systems for semi-automatic discrimination between seismic events: a study in Tehran region

Science.gov (United States)

Vasheghani Farahani, Jamileh; Zare, Mehdi; Lucas, Caro

2012-04-01

Thisarticle presents an adaptive neuro-fuzzy inference system (ANFIS) for classification of low magnitude seismic events reported in Iran by the network of Tehran Disaster Mitigation and Management Organization (TDMMO). ANFIS classifiers were used to detect seismic events using six inputs that defined the seismic events. Neuro-fuzzy coding was applied using the six extracted features as ANFIS inputs. Two types of events were defined: weak earthquakes and mining blasts. The data comprised 748 events (6289 signals) ranging from magnitude 1.1 to 4.6 recorded at 13 seismic stations between 2004 and 2009. We surveyed that there are almost 223 earthquakes with M ≤ 2.2 included in this database. Data sets from the south, east, and southeast of the city of Tehran were used to evaluate the best short period seismic discriminants, and features as inputs such as origin time of event, distance (source to station), latitude of epicenter, longitude of epicenter, magnitude, and spectral analysis (fc of the Pg wave) were used, increasing the rate of correct classification and decreasing the confusion rate between weak earthquakes and quarry blasts. The performance of the ANFIS model was evaluated for training and classification accuracy. The results confirmed that the proposed ANFIS model has good potential for determining seismic events.

New Applications of m-Polar Fuzzy Matroids

Directory of Open Access Journals (Sweden)

Musavarah Sarwar

2017-12-01

Full Text Available Mathematical modelling is an important aspect in apprehending discrete and continuous physical systems. Multipolar uncertainty in data and information incorporates a significant role in various abstract and applied mathematical modelling and decision analysis. Graphical and algebraic models can be studied more precisely when multiple linguistic properties are dealt with, emphasizing the need for a multi-index, multi-object, multi-agent, multi-attribute and multi-polar mathematical approach. An m-polar fuzzy set is introduced to overcome the limitations entailed in single-valued and two-valued uncertainty. Our aim in this research study is to apply the powerful methodology of m-polar fuzzy sets to generalize the theory of matroids. We introduce the notion of m-polar fuzzy matroids and investigate certain properties of various types of m-polar fuzzy matroids. Moreover, we apply the notion of the m-polar fuzzy matroid to graph theory and linear algebra. We present m-polar fuzzy circuits, closures of m-polar fuzzy matroids and put special emphasis on m-polar fuzzy rank functions. Finally, we also describe certain applications of m-polar fuzzy matroids in decision support systems, ordering of machines and network analysis.

Synchronous Parallel System for Emulation and Discrete Event Simulation

Science.gov (United States)

Steinman, Jeffrey S. (Inventor)

2001-01-01

A synchronous parallel system for emulation and discrete event simulation having parallel nodes responds to received messages at each node by generating event objects having individual time stamps, stores only the changes to the state variables of the simulation object attributable to the event object and produces corresponding messages. The system refrains from transmitting the messages and changing the state variables while it determines whether the changes are superseded, and then stores the unchanged state variables in the event object for later restoral to the simulation object if called for. This determination preferably includes sensing the time stamp of each new event object and determining which new event object has the earliest time stamp as the local event horizon, determining the earliest local event horizon of the nodes as the global event horizon, and ignoring events whose time stamps are less than the global event horizon. Host processing between the system and external terminals enables such a terminal to query, monitor, command or participate with a simulation object during the simulation process.

An Advanced Simulation Framework for Parallel Discrete-Event Simulation

Science.gov (United States)

Li, P. P.; Tyrrell, R. Yeung D.; Adhami, N.; Li, T.; Henry, H.

1994-01-01

Discrete-event simulation (DEVS) users have long been faced with a three-way trade-off of balancing execution time, model fidelity, and number of objects simulated. Because of the limits of computer processing power the analyst is often forced to settle for less than desired performances in one or more of these areas.

Discrete event simulation versus conventional system reliability analysis approaches

DEFF Research Database (Denmark)

Kozine, Igor

2010-01-01

Discrete Event Simulation (DES) environments are rapidly developing and appear to be promising tools for building reliability and risk analysis models of safety-critical systems and human operators. If properly developed, they are an alternative to the conventional human reliability analysis models...... and systems analysis methods such as fault and event trees and Bayesian networks. As one part, the paper describes briefly the author’s experience in applying DES models to the analysis of safety-critical systems in different domains. The other part of the paper is devoted to comparing conventional approaches...

Discrete event simulation of Maglev transport considering traffic waves

Directory of Open Access Journals (Sweden)

Moo Hyun Cha

2014-10-01

Full Text Available A magnetically levitated vehicle (Maglev system is under commercialization as a new transportation system in Korea. The Maglev is operated by an unmanned automatic control system. Therefore, the plan of train operation should be carefully established and validated in advance. In general, when making a train operation plan, statistically predicted traffic data is used. However, a traffic wave often occurs in real train service, and demand-driven simulation technology is required to review a train operation plan and service quality considering traffic waves. We propose a method and model to simulate Maglev operation considering continuous demand changes. For this purpose, we employed a discrete event model that is suitable for modeling the behavior of railway passenger transportation. We modeled the system hierarchically using discrete event system specification (DEVS formalism. In addition, through implementation and an experiment using the DEVSim++ simulation environment, we tested the feasibility of the proposed model. Our experimental results also verified that our demand-driven simulation technology can be used for a priori review of train operation plans and strategies.

Fuzzy Arden Syntax: A fuzzy programming language for medicine.

Science.gov (United States)

Vetterlein, Thomas; Mandl, Harald; Adlassnig, Klaus-Peter

2010-05-01

The programming language Arden Syntax has been optimised for use in clinical decision support systems. We describe an extension of this language named Fuzzy Arden Syntax, whose original version was introduced in S. Tiffe's dissertation on "Fuzzy Arden Syntax: Representation and Interpretation of Vague Medical Knowledge by Fuzzified Arden Syntax" (Vienna University of Technology, 2003). The primary aim is to provide an easy means of processing vague or uncertain data, which frequently appears in medicine. For both propositional and number data types, fuzzy equivalents have been added to Arden Syntax. The Boolean data type was generalised to represent any truth degree between the two extremes 0 (falsity) and 1 (truth); fuzzy data types were introduced to represent fuzzy sets. The operations on truth values and real numbers were generalised accordingly. As the conditions to decide whether a certain programme unit is executed or not may be indeterminate, a Fuzzy Arden Syntax programme may split. The data in the different branches may be optionally aggregated subsequently. Fuzzy Arden Syntax offers the possibility to formulate conveniently Medical Logic Modules (MLMs) based on the principle of a continuously graded applicability of statements. Furthermore, ad hoc decisions about sharp value boundaries can be avoided. As an illustrative example shows, an MLM making use of the features of Fuzzy Arden Syntax is not significantly more complex than its Arden Syntax equivalent; in the ideal case, a programme handling crisp data remains practically unchanged when compared to its fuzzified version. In the latter case, the output data, which can be a set of weighted alternatives, typically depends continuously from the input data. In typical applications an Arden Syntax MLM can produce a different output after only slight changes of the input; discontinuities are in fact unavoidable when the input varies continuously but the output is taken from a discrete set of possibilities

Discrete-Event Simulation Unmasks the Quantum Cheshire Cat

Science.gov (United States)

Michielsen, Kristel; Lippert, Thomas; Raedt, Hans De

2017-05-01

It is shown that discrete-event simulation accurately reproduces the experimental data of a single-neutron interferometry experiment [T. Denkmayr {\\sl et al.}, Nat. Commun. 5, 4492 (2014)] and provides a logically consistent, paradox-free, cause-and-effect explanation of the quantum Cheshire cat effect without invoking the notion that the neutron and its magnetic moment separate. Describing the experimental neutron data using weak-measurement theory is shown to be useless for unravelling the quantum Cheshire cat effect.

Optimized Parallel Discrete Event Simulation (PDES) for High Performance Computing (HPC) Clusters

National Research Council Canada - National Science Library

Abu-Ghazaleh, Nael

2005-01-01

The aim of this project was to study the communication subsystem performance of state of the art optimistic simulator Synchronous Parallel Environment for Emulation and Discrete-Event Simulation (SPEEDES...

Choquet Integral of Fuzzy-Number-Valued Functions: The Differentiability of the Primitive with respect to Fuzzy Measures and Choquet Integral Equations

Directory of Open Access Journals (Sweden)

Zengtai Gong

2014-01-01

Full Text Available This paper deals with the Choquet integral of fuzzy-number-valued functions based on the nonnegative real line. We firstly give the definitions and the characterizations of the Choquet integrals of interval-valued functions and fuzzy-number-valued functions based on the nonadditive measure. Furthermore, the operational schemes of above several classes of integrals on a discrete set are investigated which enable us to calculate Choquet integrals in some applications. Secondly, we give a representation of the Choquet integral of a nonnegative, continuous, and increasing fuzzy-number-valued function with respect to a fuzzy measure. In addition, in order to solve Choquet integral equations of fuzzy-number-valued functions, a concept of the Laplace transformation for the fuzzy-number-valued functions in the sense of Choquet integral is introduced. For distorted Lebesgue measures, it is shown that Choquet integral equations of fuzzy-number-valued functions can be solved by the Laplace transformation. Finally, an example is given to illustrate the main results at the end of the paper.

AUTOMOTIVE APPLICATIONS OF EVOLVING TAKAGI-SUGENO-KANG FUZZY MODELS

Directory of Open Access Journals (Sweden)

Radu-Emil Precup

2017-08-01

Full Text Available This paper presents theoretical and application results concerning the development of evolving Takagi-Sugeno-Kang fuzzy models for two dynamic systems, which will be viewed as controlled processes, in the field of automotive applications. The two dynamic systems models are nonlinear dynamics of the longitudinal slip in the Anti-lock Braking Systems (ABS and the vehicle speed in vehicles with the Continuously Variable Transmission (CVT systems. The evolving Takagi-Sugeno-Kang fuzzy models are obtained as discrete-time fuzzy models by incremental online identification algorithms. The fuzzy models are validated against experimental results in the case of the ABS and the first principles simulation results in the case of the vehicle with the CVT.

Nuclear facility safeguards systems modeling using discrete event simulation

International Nuclear Information System (INIS)

Engi, D.

1977-01-01

The threat of theft or dispersal of special nuclear material at a nuclear facility is treated by studying the temporal relationships between adversaries having authorized access to the facility (insiders) and safeguards system events by using a GASP IV discrete event simulation. The safeguards system events--detection, assessment, delay, communications, and neutralization--are modeled for the general insider adversary strategy which includes degradation of the safeguards system elements followed by an attempt to steal or disperse special nuclear material. The performance measure used in the analysis is the estimated probability of safeguards system success in countering the adversary based upon a predetermined set of adversary actions. An exemplary problem which includes generated results is presented for a hypothetical nuclear facility. The results illustrate representative information that could be utilized by safeguards decision-makers

Control of Discrete Event Systems

NARCIS (Netherlands)

Smedinga, Rein

1989-01-01

Systemen met discrete gebeurtenissen spelen in vele gebieden een rol. In dit proefschrift staat de volgorde van gebeurtenissen centraal en worden tijdsaspecten buiten beschouwing gelaten. In dat geval kunnen systemen met discrete gebeurtenissen goed worden gemodelleerd door gebruik te maken van

Fuzzy Uncertainty Evaluation for Fault Tree Analysis

Energy Technology Data Exchange (ETDEWEB)

Kim, Ki Beom; Shim, Hyung Jin [Seoul National University, Seoul (Korea, Republic of); Jae, Moo Sung [Hanyang University, Seoul (Korea, Republic of)

2015-05-15

This traditional probabilistic approach can calculate relatively accurate results. However it requires a long time because of repetitive computation due to the MC method. In addition, when informative data for statistical analysis are not sufficient or some events are mainly caused by human error, the probabilistic approach may not be possible because uncertainties of these events are difficult to be expressed by probabilistic distributions. In order to reduce the computation time and quantify uncertainties of top events when basic events whose uncertainties are difficult to be expressed by probabilistic distributions exist, the fuzzy uncertainty propagation based on fuzzy set theory can be applied. In this paper, we develop a fuzzy uncertainty propagation code and apply the fault tree of the core damage accident after the large loss of coolant accident (LLOCA). The fuzzy uncertainty propagation code is implemented and tested for the fault tree of the radiation release accident. We apply this code to the fault tree of the core damage accident after the LLOCA in three cases and compare the results with those computed by the probabilistic uncertainty propagation using the MC method. The results obtained by the fuzzy uncertainty propagation can be calculated in relatively short time, covering the results obtained by the probabilistic uncertainty propagation.

Desktop Modeling and Simulation: Parsimonious, yet Effective Discrete-Event Simulation Analysis

Science.gov (United States)

Bradley, James R.

2012-01-01

This paper evaluates how quickly students can be trained to construct useful discrete-event simulation models using Excel The typical supply chain used by many large national retailers is described, and an Excel-based simulation model is constructed of it The set of programming and simulation skills required for development of that model are then determined we conclude that six hours of training are required to teach the skills to MBA students . The simulation presented here contains all fundamental functionallty of a simulation model, and so our result holds for any discrete-event simulation model. We argue therefore that Industry workers with the same technical skill set as students having completed one year in an MBA program can be quickly trained to construct simulation models. This result gives credence to the efficacy of Desktop Modeling and Simulation whereby simulation analyses can be quickly developed, run, and analyzed with widely available software, namely Excel.

Advanced Concepts in Fuzzy Logic and Systems with Membership Uncertainty

CERN Document Server

Starczewski, Janusz T

2013-01-01

This book generalizes fuzzy logic systems for different types of uncertainty, including - semantic ambiguity resulting from limited perception or lack of knowledge about exact membership functions - lack of attributes or granularity arising from discretization of real data - imprecise description of membership functions - vagueness perceived as fuzzification of conditional attributes. Consequently, the membership uncertainty can be modeled by combining methods of conventional and type-2 fuzzy logic, rough set theory and possibility theory.            In particular, this book provides a number of formulae for implementing the operation extended on fuzzy-valued fuzzy sets and presents some basic structures of generalized uncertain fuzzy logic systems, as well as introduces several of methods to generate fuzzy membership uncertainty. It is desirable as a reference book for under-graduates in higher education, master and doctor graduates in the courses of computer science, computational intelligence, or...

Discrete event simulation methods applied to advanced importance measures of repairable components in multistate network flow systems

International Nuclear Information System (INIS)

Huseby, Arne B.; Natvig, Bent

2013-01-01

Discrete event models are frequently used in simulation studies to model and analyze pure jump processes. A discrete event model can be viewed as a system consisting of a collection of stochastic processes, where the states of the individual processes change as results of various kinds of events occurring at random points of time. We always assume that each event only affects one of the processes. Between these events the states of the processes are considered to be constant. In the present paper we use discrete event simulation in order to analyze a multistate network flow system of repairable components. In order to study how the different components contribute to the system, it is necessary to describe the often complicated interaction between component processes and processes at the system level. While analytical considerations may throw some light on this, a simulation study often allows the analyst to explore more details. By producing stable curve estimates for the development of the various processes, one gets a much better insight in how such systems develop over time. These methods are particulary useful in the study of advanced importancez measures of repairable components. Such measures can be very complicated, and thus impossible to calculate analytically. By using discrete event simulations, however, this can be done in a very natural and intuitive way. In particular significant differences between the Barlow–Proschan measure and the Natvig measure in multistate network flow systems can be explored

A Recursive Fuzzy System for Efficient Digital Image Stabilization

Directory of Open Access Journals (Sweden)

Nikolaos Kyriakoulis

2008-01-01

Full Text Available A novel digital image stabilization technique is proposed in this paper. It is based on a fuzzy Kalman compensation of the global motion vector (GMV, which is estimated in the log-polar plane. The GMV is extracted using four local motion vectors (LMVs computed on respective subimages in the logpolar plane. The fuzzy Kalman system consists of a fuzzy system with the Kalman filter's discrete time-invariant definition. Due to this inherited recursiveness, the output results into smoothed image sequences. The proposed stabilization system aims to compensate any oscillations of the frame absolute positions, based on the motion estimation in the log-polar domain, filtered by the fuzzy Kalman system, and thus the advantages of both the fuzzy Kalman system and the log-polar transformation are exploited. The described technique produces optimal results in terms of the output quality and the level of compensation.

The dynamics of discrete populations and series of events

CERN Document Server

Hopcraft, Keith Iain; Ridley, Kevin D

2014-01-01

IntroductionReferencesStatistical PreliminariesIntroductionProbability DistributionsMoment-Generating FunctionsDiscrete ProcessesSeries of EventsSummaryFurther ReadingMarkovian Population ProcessesIntroductionBirths and DeathsImmigration and the Poisson ProcessThe Effect of MeasurementCorrelation of CountsSummaryFurther ReadingThe Birth-Death-Immigration ProcessIntroductionRate Equations for the ProcessEquation for the Generating FunctionGeneral Time-Dependent SolutionFluctuation Characteristics of a Birth-Death-Immigration PopulationSampling and Measurement ProcessesCorrelation of CountsSumma

Discrete Event Simulation for the Analysis of Artillery Fired Projectiles from Shore

Science.gov (United States)

2017-06-01

model. 2.1 Discrete Event Simulation with Simkit Simkit is a library of classes and interfaces, written in Java , that support ease of implemen- tation...Simkit allows simulation modelers to break complex systems into components through a framework of Listener Event Graph Objects (LEGOs), described in...Classes A disadvantage to using Java Enum Types is the inability to change the values of Enum Type parameters while conducting a designed experiment

Discrete event simulation of crop operations in sweet pepper in support of work method innovation

NARCIS (Netherlands)

Ooster, van 't Bert; Aantjes, Wiger; Melamed, Z.

2017-01-01

Greenhouse Work Simulation, GWorkS, is a model that simulates crop operations in greenhouses for the purpose of analysing work methods. GWorkS is a discrete event model that approaches reality as a discrete stochastic dynamic system. GWorkS was developed and validated using cut-rose as a case

Discrete event model-based simulation for train movement on a single-line railway

International Nuclear Information System (INIS)

Xu Xiao-Ming; Li Ke-Ping; Yang Li-Xing

2014-01-01

The aim of this paper is to present a discrete event model-based approach to simulate train movement with the considered energy-saving factor. We conduct extensive case studies to show the dynamic characteristics of the traffic flow and demonstrate the effectiveness of the proposed approach. The simulation results indicate that the proposed discrete event model-based simulation approach is suitable for characterizing the movements of a group of trains on a single railway line with less iterations and CPU time. Additionally, some other qualitative and quantitative characteristics are investigated. In particular, because of the cumulative influence from the previous trains, the following trains should be accelerated or braked frequently to control the headway distance, leading to more energy consumption. (general)

Research on a Hierarchical Dynamic Automatic Voltage Control System Based on the Discrete Event-Driven Method

Directory of Open Access Journals (Sweden)

Yong Min

2013-06-01

Full Text Available In this paper, concepts and methods of hybrid control systems are adopted to establish a hierarchical dynamic automatic voltage control (HD-AVC system, realizing the dynamic voltage stability of power grids. An HD-AVC system model consisting of three layers is built based on the hybrid control method and discrete event-driven mechanism. In the Top Layer, discrete events are designed to drive the corresponding control block so as to avoid solving complex multiple objective functions, the power system’s characteristic matrix is formed and the minimum amplitude eigenvalue (MAE is calculated through linearized differential-algebraic equations. MAE is applied to judge the system’s voltage stability and security and construct discrete events. The Middle Layer is responsible for management and operation, which is also driven by discrete events. Control values of the control buses are calculated based on the characteristics of power systems and the sensitivity method. Then control values generate control strategies through the interface block. In the Bottom Layer, various control devices receive and implement the control commands from the Middle Layer. In this way, a closed-loop power system voltage control is achieved. Computer simulations verify the validity and accuracy of the HD-AVC system, and verify that the proposed HD-AVC system is more effective than normal voltage control methods.

Statistical and Probabilistic Extensions to Ground Operations' Discrete Event Simulation Modeling

Science.gov (United States)

Trocine, Linda; Cummings, Nicholas H.; Bazzana, Ashley M.; Rychlik, Nathan; LeCroy, Kenneth L.; Cates, Grant R.

2010-01-01

NASA's human exploration initiatives will invest in technologies, public/private partnerships, and infrastructure, paving the way for the expansion of human civilization into the solar system and beyond. As it is has been for the past half century, the Kennedy Space Center will be the embarkation point for humankind's journey into the cosmos. Functioning as a next generation space launch complex, Kennedy's launch pads, integration facilities, processing areas, launch and recovery ranges will bustle with the activities of the world's space transportation providers. In developing this complex, KSC teams work through the potential operational scenarios: conducting trade studies, planning and budgeting for expensive and limited resources, and simulating alternative operational schemes. Numerous tools, among them discrete event simulation (DES), were matured during the Constellation Program to conduct such analyses with the purpose of optimizing the launch complex for maximum efficiency, safety, and flexibility while minimizing life cycle costs. Discrete event simulation is a computer-based modeling technique for complex and dynamic systems where the state of the system changes at discrete points in time and whose inputs may include random variables. DES is used to assess timelines and throughput, and to support operability studies and contingency analyses. It is applicable to any space launch campaign and informs decision-makers of the effects of varying numbers of expensive resources and the impact of off nominal scenarios on measures of performance. In order to develop representative DES models, methods were adopted, exploited, or created to extend traditional uses of DES. The Delphi method was adopted and utilized for task duration estimation. DES software was exploited for probabilistic event variation. A roll-up process was used, which was developed to reuse models and model elements in other less - detailed models. The DES team continues to innovate and expand

Genetic algorithms and fuzzy multiobjective optimization

CERN Document Server

Sakawa, Masatoshi

2002-01-01

Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together with several significant monographs and books have been published on this methodology. As a result, genetic algorithms have made a major contribution to optimization, adaptation, and learning in a wide variety of unexpected fields. Over the years, many excellent books in genetic algorithm optimization have been published; however, they focus mainly on single-objective discrete or other hard optimization problems under certainty. There appears to be no book that is designed to present genetic algorithms for solving not only single-objective but also fuzzy and multiobjective optimization problems in a unified way. Genetic Algorithms And Fuzzy Multiobjective Optimization introduces the latest advances in the field of genetic algorithm optimization for 0-1 programming, integer programming, nonconvex programming, and job-shop scheduling problems under multiobjectiveness and fuzziness. In addition, the book treats a w...

Discrete event simulation tool for analysis of qualitative models of continuous processing systems

Science.gov (United States)

Malin, Jane T. (Inventor); Basham, Bryan D. (Inventor); Harris, Richard A. (Inventor)

1990-01-01

An artificial intelligence design and qualitative modeling tool is disclosed for creating computer models and simulating continuous activities, functions, and/or behavior using developed discrete event techniques. Conveniently, the tool is organized in four modules: library design module, model construction module, simulation module, and experimentation and analysis. The library design module supports the building of library knowledge including component classes and elements pertinent to a particular domain of continuous activities, functions, and behavior being modeled. The continuous behavior is defined discretely with respect to invocation statements, effect statements, and time delays. The functionality of the components is defined in terms of variable cluster instances, independent processes, and modes, further defined in terms of mode transition processes and mode dependent processes. Model construction utilizes the hierarchy of libraries and connects them with appropriate relations. The simulation executes a specialized initialization routine and executes events in a manner that includes selective inherency of characteristics through a time and event schema until the event queue in the simulator is emptied. The experimentation and analysis module supports analysis through the generation of appropriate log files and graphics developments and includes the ability of log file comparisons.

Stabilization Using a Discrete Fuzzy PDC Control with PID Controllers and Pole Placement: Application to an Experimental Greenhouse

Directory of Open Access Journals (Sweden)

Amine Chouchaine

2011-01-01

Full Text Available This paper proposes a control strategy for complex and nonlinear systems, based on a parallel distributed compensation (PDC controller. A solution is presented to solve a stability problem that arises when dealing with a Takagi-Sugeno discrete system with great numbers of rules. The PDC controller will use a classical controller like a PI, PID, or RST in each rule with a pole placement strategy to avoid causing instability. The fuzzy controller presented combines the multicontrol approach and the performance of the classical controllers to obtain a robust nonlinear control action that can also deal with time-variant systems. The presented method was applied to a small greenhouse to control its inside temperature by variation in ventilation rate inside the process. The results obtained will show the efficiency of the adopted method to control the nonlinear and complex systems.

The cost of conservative synchronization in parallel discrete event simulations

Science.gov (United States)

Nicol, David M.

1990-01-01

The performance of a synchronous conservative parallel discrete-event simulation protocol is analyzed. The class of simulation models considered is oriented around a physical domain and possesses a limited ability to predict future behavior. A stochastic model is used to show that as the volume of simulation activity in the model increases relative to a fixed architecture, the complexity of the average per-event overhead due to synchronization, event list manipulation, lookahead calculations, and processor idle time approach the complexity of the average per-event overhead of a serial simulation. The method is therefore within a constant factor of optimal. The analysis demonstrates that on large problems--those for which parallel processing is ideally suited--there is often enough parallel workload so that processors are not usually idle. The viability of the method is also demonstrated empirically, showing how good performance is achieved on large problems using a thirty-two node Intel iPSC/2 distributed memory multiprocessor.

Simulation of interim spent fuel storage system with discrete event model

International Nuclear Information System (INIS)

Yoon, Wan Ki; Song, Ki Chan; Lee, Jae Sol; Park, Hyun Soo

1989-01-01

This paper describes dynamic simulation of the spent fuel storage system which is described by statistical discrete event models. It visualizes flow and queue of system over time, assesses the operational performance of the system activities and establishes the system components and streams. It gives information on system organization and operation policy with reference to the design. System was tested and analyzed over a number of critical parameters to establish the optimal system. Workforce schedule and resources with long processing time dominate process. A combination of two workforce shifts a day and two cooling pits gives the optimal solution of storage system. Discrete system simulation is an useful tool to get information on optimal design and operation of the storage system. (Author)

Event-Triggered Fault Detection of Nonlinear Networked Systems.

Science.gov (United States)

Li, Hongyi; Chen, Ziran; Wu, Ligang; Lam, Hak-Keung; Du, Haiping

2017-04-01

This paper investigates the problem of fault detection for nonlinear discrete-time networked systems under an event-triggered scheme. A polynomial fuzzy fault detection filter is designed to generate a residual signal and detect faults in the system. A novel polynomial event-triggered scheme is proposed to determine the transmission of the signal. A fault detection filter is designed to guarantee that the residual system is asymptotically stable and satisfies the desired performance. Polynomial approximated membership functions obtained by Taylor series are employed for filtering analysis. Furthermore, sufficient conditions are represented in terms of sum of squares (SOSs) and can be solved by SOS tools in MATLAB environment. A numerical example is provided to demonstrate the effectiveness of the proposed results.

A neuro-fuzzy system to support in the diagnostic of epileptic events and non-epileptic events using different fuzzy arithmetical operations Um sistema neuro-difuso para auxiliar no diagnóstico de eventos epilépticos e eventos não epilépticos utilizando diferentes operações aritméticas difusas

Directory of Open Access Journals (Sweden)

Lucimar M.F. de Carvalho

2008-06-01

Full Text Available OBJECTIVE: To investigate different fuzzy arithmetical operations to support in the diagnostic of epileptic events and non epileptic events. METHOD: A neuro-fuzzy system was developed using the NEFCLASS (NEuro Fuzzy CLASSIfication architecture and an artificial neural network with backpropagation learning algorithm (ANNB. RESULTS: The study was composed by 244 patients with a bigger frequency of the feminine sex. The number of right decisions at the test phase, obtained by the NEFCLASS and ANNB was 83.60% and 90.16%, respectively. The best sensibility result was attained by NEFCLASS (84.90%; the best specificity result were attained by ANNB with 95.65%. CONCLUSION: The proposed neuro-fuzzy system combined the artificial neural network capabilities in the pattern classifications together with the fuzzy logic qualitative approach, leading to a bigger rate of system success.OBJETIVO: Investigar diferentes operações aritméticas difusas para auxíliar no diagnóstico de eventos epilépticos e eventos não-epilépticos. MÉTODO: Um sistema neuro-difuso foi desenvolvido utilizando a arquitetura NEFCLASS (NEuro Fuzzy CLASSIfication e uma rede neural artificial com o algoritmo de aprendizagem backpropagation (RNAB. RESULTADOS: A amostra estudada foi de 244 pacientes com maior freqüência no sexo feminino. O número de decisões corretas na fase de teste, obtidas através do NEFCLASS e RNAB foi de 83,60% e 90,16%, respectivamente. O melhor resultado de sensibilidade foi obtido com o NEFCLASS (84,90%; o melhor resultado de especificidade foi obtido com a RNAB (95,65%. CONCLUSÃO: O sistema neuro-difuso proposto combinou a capacidade das redes neurais artificiais na classificação de padrões juntamente com a abordagem qualitativa da logica difusa, levando a maior taxa de acertos do sistema.

Modelling machine ensembles with discrete event dynamical system theory

Science.gov (United States)

Hunter, Dan

1990-01-01

Discrete Event Dynamical System (DEDS) theory can be utilized as a control strategy for future complex machine ensembles that will be required for in-space construction. The control strategy involves orchestrating a set of interactive submachines to perform a set of tasks for a given set of constraints such as minimum time, minimum energy, or maximum machine utilization. Machine ensembles can be hierarchically modeled as a global model that combines the operations of the individual submachines. These submachines are represented in the global model as local models. Local models, from the perspective of DEDS theory , are described by the following: a set of system and transition states, an event alphabet that portrays actions that takes a submachine from one state to another, an initial system state, a partial function that maps the current state and event alphabet to the next state, and the time required for the event to occur. Each submachine in the machine ensemble is presented by a unique local model. The global model combines the local models such that the local models can operate in parallel under the additional logistic and physical constraints due to submachine interactions. The global model is constructed from the states, events, event functions, and timing requirements of the local models. Supervisory control can be implemented in the global model by various methods such as task scheduling (open-loop control) or implementing a feedback DEDS controller (closed-loop control).

Decomposition of fuzzy continuity and fuzzy ideal continuity via fuzzy idealization

International Nuclear Information System (INIS)

Zahran, A.M.; Abbas, S.E.; Abd El-baki, S.A.; Saber, Y.M.

2009-01-01

Recently, El-Naschie has shown that the notion of fuzzy topology may be relevant to quantum paretical physics in connection with string theory and E-infinity space time theory. In this paper, we study the concepts of r-fuzzy semi-I-open, r-fuzzy pre-I-open, r-fuzzy α-I-open and r-fuzzy β-I-open sets, which is properly placed between r-fuzzy openness and r-fuzzy α-I-openness (r-fuzzy pre-I-openness) sets regardless the fuzzy ideal topological space in Sostak sense. Moreover, we give a decomposition of fuzzy continuity, fuzzy ideal continuity and fuzzy ideal α-continuity, and obtain several characterization and some properties of these functions. Also, we investigate their relationship with other types of function.

Fuzzy probability based fault tree analysis to propagate and quantify epistemic uncertainty

International Nuclear Information System (INIS)

Purba, Julwan Hendry; Sony Tjahyani, D.T.; Ekariansyah, Andi Sofrany; Tjahjono, Hendro

2015-01-01

Highlights: • Fuzzy probability based fault tree analysis is to evaluate epistemic uncertainty in fuzzy fault tree analysis. • Fuzzy probabilities represent likelihood occurrences of all events in a fault tree. • A fuzzy multiplication rule quantifies epistemic uncertainty of minimal cut sets. • A fuzzy complement rule estimate epistemic uncertainty of the top event. • The proposed FPFTA has successfully evaluated the U.S. Combustion Engineering RPS. - Abstract: A number of fuzzy fault tree analysis approaches, which integrate fuzzy concepts into the quantitative phase of conventional fault tree analysis, have been proposed to study reliabilities of engineering systems. Those new approaches apply expert judgments to overcome the limitation of the conventional fault tree analysis when basic events do not have probability distributions. Since expert judgments might come with epistemic uncertainty, it is important to quantify the overall uncertainties of the fuzzy fault tree analysis. Monte Carlo simulation is commonly used to quantify the overall uncertainties of conventional fault tree analysis. However, since Monte Carlo simulation is based on probability distribution, this technique is not appropriate for fuzzy fault tree analysis, which is based on fuzzy probabilities. The objective of this study is to develop a fuzzy probability based fault tree analysis to overcome the limitation of fuzzy fault tree analysis. To demonstrate the applicability of the proposed approach, a case study is performed and its results are then compared to the results analyzed by a conventional fault tree analysis. The results confirm that the proposed fuzzy probability based fault tree analysis is feasible to propagate and quantify epistemic uncertainties in fault tree analysis

Numerical implementation of wavelet and fuzzy transform IFOC for three-phase induction motor

Directory of Open Access Journals (Sweden)

Sanjeevikumar Padmanaban

2016-03-01

Full Text Available This article elaborates the numerical implementation of a novel, indirect field-oriented control (IFOC for induction motor drive by wave-let discrete transform/fuzzy logic interface system unique combination. The feedback (speed error signal is a mixed component of multiple low and high frequencies. Further, these signals are decomposed by the discrete wave-let transform (WT, then fuzzy logic (FL generates the scaled gains for the proportional-integral (P-I controller parameters. This unique combination improves the high precision speed control of induction motor during both transient as well as steady-state conditions. Numerical simulation model is implemented with proposed control scheme using Matlab/Simulink software and obtained results confirm the expectation.

Conditions for extinction events in chemical reaction networks with discrete state spaces.

Science.gov (United States)

Johnston, Matthew D; Anderson, David F; Craciun, Gheorghe; Brijder, Robert

2018-05-01

We study chemical reaction networks with discrete state spaces and present sufficient conditions on the structure of the network that guarantee the system exhibits an extinction event. The conditions we derive involve creating a modified chemical reaction network called a domination-expanded reaction network and then checking properties of this network. Unlike previous results, our analysis allows algorithmic implementation via systems of equalities and inequalities and suggests sequences of reactions which may lead to extinction events. We apply the results to several networks including an EnvZ-OmpR signaling pathway in Escherichia coli.

U.S. Marine Corps Communication-Electronics School Training Process: Discrete-Event Simulation and Lean Options

National Research Council Canada - National Science Library

Neu, Charles R; Davenport, Jon; Smith, William R

2007-01-01

This paper uses discrete-event simulation modeling, inventory-reduction, and process improvement concepts to identify and analyze possibilities for improving the training continuum at the Marine Corps...

Modeling crowd behavior based on the discrete-event multiagent approach

OpenAIRE

Лановой, Алексей Феликсович; Лановой, Артем Алексеевич

2014-01-01

The crowd is a temporary, relatively unorganized group of people, who are in close physical contact with each other. Individual behavior of human outside the crowd is determined by many factors, associated with his intellectual activities, but inside the crowd the man loses his identity and begins to obey more simple laws of behavior.One of approaches to the construction of multi-level model of the crowd using discrete-event multiagent approach was described in the paper.Based on this analysi...

Humans can integrate feedback of discrete events in their sensorimotor control of a robotic hand.

Science.gov (United States)

Cipriani, Christian; Segil, Jacob L; Clemente, Francesco; ff Weir, Richard F; Edin, Benoni

2014-11-01

Providing functionally effective sensory feedback to users of prosthetics is a largely unsolved challenge. Traditional solutions require high band-widths for providing feedback for the control of manipulation and yet have been largely unsuccessful. In this study, we have explored a strategy that relies on temporally discrete sensory feedback that is technically simple to provide. According to the Discrete Event-driven Sensory feedback Control (DESC) policy, motor tasks in humans are organized in phases delimited by means of sensory encoded discrete mechanical events. To explore the applicability of DESC for control, we designed a paradigm in which healthy humans operated an artificial robot hand to lift and replace an instrumented object, a task that can readily be learned and mastered under visual control. Assuming that the central nervous system of humans naturally organizes motor tasks based on a strategy akin to DESC, we delivered short-lasting vibrotactile feedback related to events that are known to forcefully affect progression of the grasp-lift-and-hold task. After training, we determined whether the artificial feedback had been integrated with the sensorimotor control by introducing short delays and we indeed observed that the participants significantly delayed subsequent phases of the task. This study thus gives support to the DESC policy hypothesis. Moreover, it demonstrates that humans can integrate temporally discrete sensory feedback while controlling an artificial hand and invites further studies in which inexpensive, noninvasive technology could be used in clever ways to provide physiologically appropriate sensory feedback in upper limb prosthetics with much lower band-width requirements than with traditional solutions.

Adaptive Functional-Based Neuro-Fuzzy-PID Incremental Controller Structure

Directory of Open Access Journals (Sweden)

Ashraf Ahmed Fahmy

2014-03-01

Full Text Available This paper presents an adaptive functional-based Neuro-fuzzy-PID incremental (NFPID controller structure that can be tuned either offline or online according to required controller performance. First, differential membership functions are used to represent the fuzzy membership functions of the input-output space of the three term controller. Second, controller rules are generated based on the discrete proportional, derivative, and integral function for the fuzzy space. Finally, a fully differentiable fuzzy neural network is constructed to represent the developed controller for either offline or online controller parameter adaptation.  Two different adaptation methods are used for controller tuning, offline method based on controller transient performance cost function optimization using Bees Algorithm, and online method based on tracking error minimization using back-propagation with momentum algorithm. The proposed control system was tested to show the validity of the controller structure over a fixed PID controller gains to control SCARA type robot arm.

Discrete event simulation and the resultant data storage system response in the operational mission environment of Jupiter-Saturn /Voyager/ spacecraft

Science.gov (United States)

Mukhopadhyay, A. K.

1978-01-01

The Data Storage Subsystem Simulator (DSSSIM) simulating (by ground software) occurrence of discrete events in the Voyager mission is described. Functional requirements for Data Storage Subsystems (DSS) simulation are discussed, and discrete event simulation/DSSSIM processing is covered. Four types of outputs associated with a typical DSSSIM run are presented, and DSSSIM limitations and constraints are outlined.

A Novel Finite-Sum Inequality-Based Method for Robust H∞ Control of Uncertain Discrete-Time Takagi-Sugeno Fuzzy Systems With Interval-Like Time-Varying Delays.

Science.gov (United States)

Zhang, Xian-Ming; Han, Qing-Long; Ge, Xiaohua

2017-09-22

This paper is concerned with the problem of robust H∞ control of an uncertain discrete-time Takagi-Sugeno fuzzy system with an interval-like time-varying delay. A novel finite-sum inequality-based method is proposed to provide a tighter estimation on the forward difference of certain Lyapunov functional, leading to a less conservative result. First, an auxiliary vector function is used to establish two finite-sum inequalities, which can produce tighter bounds for the finite-sum terms appearing in the forward difference of the Lyapunov functional. Second, a matrix-based quadratic convex approach is employed to equivalently convert the original matrix inequality including a quadratic polynomial on the time-varying delay into two boundary matrix inequalities, which delivers a less conservative bounded real lemma (BRL) for the resultant closed-loop system. Third, based on the BRL, a novel sufficient condition on the existence of suitable robust H∞ fuzzy controllers is derived. Finally, two numerical examples and a computer-simulated truck-trailer system are provided to show the effectiveness of the obtained results.

Discrete-Event Simulation with Agents for Modeling of Dynamic Asymmetric Threats in Maritime Security

National Research Council Canada - National Science Library

Ng, Chee W

2007-01-01

.... Discrete-event simulation (DES) was used to simulate a typical port-security, local, waterside-threat response model and to test the adaptive response of asymmetric threats in reaction to port-security procedures, while a multi-agent system (MAS...

Dynamic cluster generation for a fuzzy classifier with ellipsoidal regions.

Science.gov (United States)

Abe, S

1998-01-01

In this paper, we discuss a fuzzy classifier with ellipsoidal regions that dynamically generates clusters. First, for the data belonging to a class we define a fuzzy rule with an ellipsoidal region. Namely, using the training data for each class, we calculate the center and the covariance matrix of the ellipsoidal region for the class. Then we tune the fuzzy rules, i.e., the slopes of the membership functions, successively until there is no improvement in the recognition rate of the training data. Then if the number of the data belonging to a class that are misclassified into another class exceeds a prescribed number, we define a new cluster to which those data belong and the associated fuzzy rule. Then we tune the newly defined fuzzy rules in the similar way as stated above, fixing the already obtained fuzzy rules. We iterate generation of clusters and tuning of the newly generated fuzzy rules until the number of the data belonging to a class that are misclassified into another class does not exceed the prescribed number. We evaluate our method using thyroid data, Japanese Hiragana data of vehicle license plates, and blood cell data. By dynamic cluster generation, the generalization ability of the classifier is improved and the recognition rate of the fuzzy classifier for the test data is the best among the neural network classifiers and other fuzzy classifiers if there are no discrete input variables.

Synchronization of generalized Henon map by using adaptive fuzzy controller

Energy Technology Data Exchange (ETDEWEB)

Xue Yueju E-mail: xueyj@mail.tsinghua.edu.cn; Yang Shiyuan E-mail: ysy-dau@tsinghua.edu.cn

2003-08-01

In this paper, an adaptive fuzzy control method is presented to synchronize model-unknown discrete-time generalized Henon map. The proposed method is robust to approximate errors and disturbances, because it integrates the merits of adaptive fuzzy and the variable structure control. Moreover, it can realize the synchronizations of non-identical chaotic systems. The simulation results of synchronization of generalized Henon map show that it not only can synchronize model-unknown generalized Henon map but also is robust against the noise of the systems. These merits are advantageous for engineering realization.

Synchronization of generalized Henon map by using adaptive fuzzy controller

International Nuclear Information System (INIS)

Xue Yueju; Yang Shiyuan

2003-01-01

In this paper, an adaptive fuzzy control method is presented to synchronize model-unknown discrete-time generalized Henon map. The proposed method is robust to approximate errors and disturbances, because it integrates the merits of adaptive fuzzy and the variable structure control. Moreover, it can realize the synchronizations of non-identical chaotic systems. The simulation results of synchronization of generalized Henon map show that it not only can synchronize model-unknown generalized Henon map but also is robust against the noise of the systems. These merits are advantageous for engineering realization

Safety Discrete Event Models for Holonic Cyclic Manufacturing Systems

Science.gov (United States)

Ciufudean, Calin; Filote, Constantin

In this paper the expression “holonic cyclic manufacturing systems” refers to complex assembly/disassembly systems or fork/join systems, kanban systems, and in general, to any discrete event system that transforms raw material and/or components into products. Such a system is said to be cyclic if it provides the same sequence of products indefinitely. This paper considers the scheduling of holonic cyclic manufacturing systems and describes a new approach using Petri nets formalism. We propose an approach to frame the optimum schedule of holonic cyclic manufacturing systems in order to maximize the throughput while minimize the work in process. We also propose an algorithm to verify the optimum schedule.

Control of discrete event systems modeled as hierarchical state machines

Science.gov (United States)

Brave, Y.; Heymann, M.

1991-01-01

The authors examine a class of discrete event systems (DESs) modeled as asynchronous hierarchical state machines (AHSMs). For this class of DESs, they provide an efficient method for testing reachability, which is an essential step in many control synthesis procedures. This method utilizes the asynchronous nature and hierarchical structure of AHSMs, thereby illustrating the advantage of the AHSM representation as compared with its equivalent (flat) state machine representation. An application of the method is presented where an online minimally restrictive solution is proposed for the problem of maintaining a controlled AHSM within prescribed legal bounds.

Discrete-event simulation of nuclear-waste transport in geologic sites subject to disruptive events. Final report

International Nuclear Information System (INIS)

Aggarwal, S.; Ryland, S.; Peck, R.

1980-01-01

This report outlines a methodology to study the effects of disruptive events on nuclear waste material in stable geologic sites. The methodology is based upon developing a discrete events model that can be simulated on the computer. This methodology allows a natural development of simulation models that use computer resources in an efficient manner. Accurate modeling in this area depends in large part upon accurate modeling of ion transport behavior in the storage media. Unfortunately, developments in this area are not at a stage where there is any consensus on proper models for such transport. Consequently, our work is directed primarily towards showing how disruptive events can be properly incorporated in such a model, rather than as a predictive tool at this stage. When and if proper geologic parameters can be determined, then it would be possible to use this as a predictive model. Assumptions and their bases are discussed, and the mathematical and computer model are described

Application of fuzzy fault tree analysis based on modified fuzzy AHP and fuzzy TOPSIS for fire and explosion in the process industry.

Science.gov (United States)

Yazdi, Mohammad; Korhan, Orhan; Daneshvar, Sahand

2018-05-09

This study aimed at establishing fault tree analysis (FTA) using expert opinion to compute the probability of an event. To find the probability of the top event (TE), all probabilities of the basic events (BEs) should be available when the FTA is drawn. In this case, employing expert judgment can be used as an alternative to failure data in an awkward situation. The fuzzy analytical hierarchy process as a standard technique is used to give a specific weight to each expert, and fuzzy set theory is engaged for aggregating expert opinion. In this regard, the probability of BEs will be computed and, consequently, the probability of the TE obtained using Boolean algebra. Additionally, to reduce the probability of the TE in terms of three parameters (safety consequences, cost and benefit), the importance measurement technique and modified TOPSIS was employed. The effectiveness of the proposed approach is demonstrated with a real-life case study.

Spinning the fuzzy sphere

International Nuclear Information System (INIS)

Berenstein, David; Dzienkowski, Eric; Lashof-Regas, Robin

2015-01-01

We construct various exact analytical solutions of the SO(3) BMN matrix model that correspond to rotating fuzzy spheres and rotating fuzzy tori. These are also solutions of Yang Mills theory compactified on a sphere times time and they are also translationally invariant solutions of the N=1"∗ field theory with a non-trivial charge density. The solutions we construct have a ℤ_N symmetry, where N is the rank of the matrices. After an appropriate ansatz, we reduce the problem to solving a set of polynomial equations in 2N real variables. These equations have a discrete set of solutions for each value of the angular momentum. We study the phase structure of the solutions for various values of N. Also the continuum limit where N→∞, where the problem reduces to finding periodic solutions of a set of coupled differential equations. We also study the topology change transition from the sphere to the torus.

Fuzzy time series forecasting model with natural partitioning length approach for predicting the unemployment rate under different degree of confidence

Science.gov (United States)

Ramli, Nazirah; Mutalib, Siti Musleha Ab; Mohamad, Daud

2017-08-01

Fuzzy time series forecasting model has been proposed since 1993 to cater for data in linguistic values. Many improvement and modification have been made to the model such as enhancement on the length of interval and types of fuzzy logical relation. However, most of the improvement models represent the linguistic term in the form of discrete fuzzy sets. In this paper, fuzzy time series model with data in the form of trapezoidal fuzzy numbers and natural partitioning length approach is introduced for predicting the unemployment rate. Two types of fuzzy relations are used in this study which are first order and second order fuzzy relation. This proposed model can produce the forecasted values under different degree of confidence.

Application of discrete event simulation to MRS design

International Nuclear Information System (INIS)

Bali, M.; Standley, W.

1993-01-01

The application of discrete event simulation to the Monitored, Retrievable Storage (MRS) material handling operations supported the MRS conceptual design effort and established a set of tools for use during MRS detail design and license application. The effort to develop a design analysis tool to support the MRS project started in 1991. The MRS simulation has so far identified potential savings and suggested methods of improving operations to enhance throughput. Immediately, simulation aided the MRS conceptual design effort through the investigation of alternative cask handling operations and the sizing and sharing of expensive equipment. The simulation also helped analyze the operability of the current design of MRS under various waste acceptance scenarios. Throughout the simulation effort, the model development and experimentation resulted in early identification and resolution of several design and operational issues

FSILP: fuzzy-stochastic-interval linear programming for supporting municipal solid waste management.

Science.gov (United States)

Li, Pu; Chen, Bing

2011-04-01

Although many studies on municipal solid waste management (MSW management) were conducted under uncertain conditions of fuzzy, stochastic, and interval coexistence, the solution to the conventional linear programming problems of integrating fuzzy method with the other two was inefficient. In this study, a fuzzy-stochastic-interval linear programming (FSILP) method is developed by integrating Nguyen's method with conventional linear programming for supporting municipal solid waste management. The Nguyen's method was used to convert the fuzzy and fuzzy-stochastic linear programming problems into the conventional linear programs, by measuring the attainment values of fuzzy numbers and/or fuzzy random variables, as well as superiority and inferiority between triangular fuzzy numbers/triangular fuzzy-stochastic variables. The developed method can effectively tackle uncertainties described in terms of probability density functions, fuzzy membership functions, and discrete intervals. Moreover, the method can also improve upon the conventional interval fuzzy programming and two-stage stochastic programming approaches, with advantageous capabilities that are easily achieved with fewer constraints and significantly reduces consumption time. The developed model was applied to a case study of municipal solid waste management system in a city. The results indicated that reasonable solutions had been generated. The solution can help quantify the relationship between the change of system cost and the uncertainties, which could support further analysis of tradeoffs between the waste management cost and the system failure risk. Copyright © 2010 Elsevier Ltd. All rights reserved.

LAN attack detection using Discrete Event Systems.

Science.gov (United States)

Hubballi, Neminath; Biswas, Santosh; Roopa, S; Ratti, Ritesh; Nandi, Sukumar

2011-01-01

Address Resolution Protocol (ARP) is used for determining the link layer or Medium Access Control (MAC) address of a network host, given its Internet Layer (IP) or Network Layer address. ARP is a stateless protocol and any IP-MAC pairing sent by a host is accepted without verification. This weakness in the ARP may be exploited by malicious hosts in a Local Area Network (LAN) by spoofing IP-MAC pairs. Several schemes have been proposed in the literature to circumvent these attacks; however, these techniques either make IP-MAC pairing static, modify the existing ARP, patch operating systems of all the hosts etc. In this paper we propose a Discrete Event System (DES) approach for Intrusion Detection System (IDS) for LAN specific attacks which do not require any extra constraint like static IP-MAC, changing the ARP etc. A DES model is built for the LAN under both a normal and compromised (i.e., spoofed request/response) situation based on the sequences of ARP related packets. Sequences of ARP events in normal and spoofed scenarios are similar thereby rendering the same DES models for both the cases. To create different ARP events under normal and spoofed conditions the proposed technique uses active ARP probing. However, this probing adds extra ARP traffic in the LAN. Following that a DES detector is built to determine from observed ARP related events, whether the LAN is operating under a normal or compromised situation. The scheme also minimizes extra ARP traffic by probing the source IP-MAC pair of only those ARP packets which are yet to be determined as genuine/spoofed by the detector. Also, spoofed IP-MAC pairs determined by the detector are stored in tables to detect other LAN attacks triggered by spoofing namely, man-in-the-middle (MiTM), denial of service etc. The scheme is successfully validated in a test bed. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Modeling discrete time-to-event data

CERN Document Server

Tutz, Gerhard

2016-01-01

This book focuses on statistical methods for the analysis of discrete failure times. Failure time analysis is one of the most important fields in statistical research, with applications affecting a wide range of disciplines, in particular, demography, econometrics, epidemiology and clinical research. Although there are a large variety of statistical methods for failure time analysis, many techniques are designed for failure times that are measured on a continuous scale. In empirical studies, however, failure times are often discrete, either because they have been measured in intervals (e.g., quarterly or yearly) or because they have been rounded or grouped. The book covers well-established methods like life-table analysis and discrete hazard regression models, but also introduces state-of-the art techniques for model evaluation, nonparametric estimation and variable selection. Throughout, the methods are illustrated by real life applications, and relationships to survival analysis in continuous time are expla...

Genetic Learning of Fuzzy Parameters in Predictive and Decision Support Modelling

Directory of Open Access Journals (Sweden)

Nebot

2012-04-01

Full Text Available In this research a genetic fuzzy system (GFS is proposed that performs discretization parameter learning in the context of the Fuzzy Inductive Reasoning (FIR methodology and the Linguistic Rule FIR (LR-FIR algorithm. The main goal of the GFS is to take advantage of the potentialities of GAs to learn the fuzzification parameters of the FIR and LR-FIR approaches in order to obtain reliable and useful predictive (FIR models and decision support (LR-FIR models. The GFS is evaluated in an e-learning context.

Supervisory control synthesis of discrete-event systems using a coordination scheme

Czech Academy of Sciences Publication Activity Database

Komenda, Jan; Masopust, Tomáš; van Schuppen, J. H.

2012-01-01

Roč. 48, č. 2 (2012), s. 247-254 ISSN 0005-1098 R&D Projects: GA ČR(CZ) GAP103/11/0517; GA ČR GPP202/11/P028 Grant - others:European Commission(XE) EU.ICT.DISC 224498 Institutional research plan: CEZ:AV0Z10190503 Keywords : discrete-event systems * supervisory control * distributed control * closed-loop systems * controllability Subject RIV: BA - General Mathematics Impact factor: 2.919, year: 2012 http://www.sciencedirect.com/science/article/pii/S0005109811005395

Supervisory control synthesis of discrete-event systems using a coordination scheme

Czech Academy of Sciences Publication Activity Database

Komenda, Jan; Masopust, Tomáš; van Schuppen, J. H.

2012-01-01

Roč. 48, č. 2 (2012), s. 247-254 ISSN 0005-1098 R&D Projects: GA ČR(CZ) GAP103/11/0517; GA ČR GPP202/11/P028 Grant - others:European Commission(XE) EU. ICT .DISC 224498 Institutional research plan: CEZ:AV0Z10190503 Keywords : discrete-event systems * supervisory control * distributed control * closed-loop systems * controllability Subject RIV: BA - General Mathematics Impact factor: 2.919, year: 2012 http://www.sciencedirect.com/science/article/pii/S0005109811005395

Advances in Discrete-Event Simulation for MSL Command Validation

Science.gov (United States)

Patrikalakis, Alexander; O'Reilly, Taifun

2013-01-01

In the last five years, the discrete event simulator, SEQuence GENerator (SEQGEN), developed at the Jet Propulsion Laboratory to plan deep-space missions, has greatly increased uplink operations capacity to deal with increasingly complicated missions. In this paper, we describe how the Mars Science Laboratory (MSL) project makes full use of an interpreted environment to simulate change in more than fifty thousand flight software parameters and conditional command sequences to predict the result of executing a conditional branch in a command sequence, and enable the ability to warn users whenever one or more simulated spacecraft states change in an unexpected manner. Using these new SEQGEN features, operators plan more activities in one sol than ever before.

Modeling energy market dynamics using discrete event system simulation

International Nuclear Information System (INIS)

Gutierrez-Alcaraz, G.; Sheble, G.B.

2009-01-01

This paper proposes the use of Discrete Event System Simulation to study the interactions among fuel and electricity markets and consumers, and the decision-making processes of fuel companies (FUELCOs), generation companies (GENCOs), and consumers in a simple artificial energy market. In reality, since markets can reach a stable equilibrium or fail, it is important to observe how they behave in a dynamic framework. We consider a Nash-Cournot model in which marketers are depicted as Nash-Cournot players that determine supply to meet end-use consumption. Detailed engineering considerations such as transportation network flows are omitted, because the focus is upon the selection and use of appropriate market models to provide answers to policy questions. (author)

A Discrete-Event Simulation Model for Evaluating Air Force Reusable Military Launch Vehicle Post-Landing Operations

National Research Council Canada - National Science Library

Martindale, Michael

2006-01-01

The purpose of this research was to develop a discrete-event computer simulation model of the post-landing vehicle recoveoperations to allow the Air Force Research Laboratory, Air Vehicles Directorate...

Fuzzy stochastic multiobjective programming

CERN Document Server

Sakawa, Masatoshi; Katagiri, Hideki

2011-01-01

With a stress on interactive decision-making, this work breaks new ground by covering both the random nature of events related to environments, and the fuzziness of human judgements. The text runs from mathematical preliminaries to future research directions.

Discrete event simulation in an artificial intelligence environment: Some examples

International Nuclear Information System (INIS)

Roberts, D.J.; Farish, T.

1991-01-01

Several Los Alamos National Laboratory (LANL) object-oriented discrete-event simulation efforts have been completed during the past three years. One of these systems has been put into production and has a growing customer base. Another (started two years earlier than the first project) was completed but has not yet been used. This paper will describe these simulation projects. Factors which were pertinent to the success of the one project, and to the failure of the second project will be discussed (success will be measured as the extent to which the simulation model was used as originally intended). 5 figs

Creating Clinical Fuzzy Automata with Fuzzy Arden Syntax.

Science.gov (United States)

de Bruin, Jeroen S; Steltzer, Heinz; Rappelsberger, Andrea; Adlassnig, Klaus-Peter

2017-01-01

Formal constructs for fuzzy sets and fuzzy logic are incorporated into Arden Syntax version 2.9 (Fuzzy Arden Syntax). With fuzzy sets, the relationships between measured or observed data and linguistic terms are expressed as degrees of compatibility that model the unsharpness of the boundaries of linguistic terms. Propositional uncertainty due to incomplete knowledge of relationships between clinical linguistic concepts is modeled with fuzzy logic. Fuzzy Arden Syntax also supports the construction of fuzzy state monitors. The latter are defined as monitors that employ fuzzy automata to observe gradual transitions between different stages of disease. As a use case, we re-implemented FuzzyARDS, a previously published clinical monitoring system for patients suffering from acute respiratory distress syndrome (ARDS). Using the re-implementation as an example, we show how key concepts of fuzzy automata, i.e., fuzzy states and parallel fuzzy state transitions, can be implemented in Fuzzy Arden Syntax. The results showed that fuzzy state monitors can be implemented in a straightforward manner.

A New Approach to Reducing Search Space and Increasing Efficiency in Simulation Optimization Problems via the Fuzzy-DEA-BCC

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Rafael de Carvalho Miranda

2014-01-01

Full Text Available The development of discrete-event simulation software was one of the most successful interfaces in operational research with computation. As a result, research has been focused on the development of new methods and algorithms with the purpose of increasing simulation optimization efficiency and reliability. This study aims to define optimum variation intervals for each decision variable through a proposed approach which combines the data envelopment analysis with the Fuzzy logic (Fuzzy-DEA-BCC, seeking to improve the decision-making units’ distinction in the face of uncertainty. In this study, Taguchi’s orthogonal arrays were used to generate the necessary quantity of DMUs, and the output variables were generated by the simulation. Two study objects were utilized as examples of mono- and multiobjective problems. Results confirmed the reliability and applicability of the proposed method, as it enabled a significant reduction in search space and computational demand when compared to conventional simulation optimization techniques.

Fuzzy vulnerability matrix

International Nuclear Information System (INIS)

Baron, Jorge H.; Rivera, S.S.

2000-01-01

The so-called vulnerability matrix is used in the evaluation part of the probabilistic safety assessment for a nuclear power plant, during the containment event trees calculations. This matrix is established from what is knows as Numerical Categories for Engineering Judgement. This matrix is usually established with numerical values obtained with traditional arithmetic using the set theory. The representation of this matrix with fuzzy numbers is much more adequate, due to the fact that the Numerical Categories for Engineering Judgement are better represented with linguistic variables, such as 'highly probable', 'probable', 'impossible', etc. In the present paper a methodology to obtain a Fuzzy Vulnerability Matrix is presented, starting from the recommendations on the Numerical Categories for Engineering Judgement. (author)

Cardiovascular Dysautonomias Diagnosis Using Crisp and Fuzzy Decision Tree: A Comparative Study.

Science.gov (United States)

Kadi, Ilham; Idri, Ali

2016-01-01

Decision trees (DTs) are one of the most popular techniques for learning classification systems, especially when it comes to learning from discrete examples. In real world, many data occurred in a fuzzy form. Hence a DT must be able to deal with such fuzzy data. In fact, integrating fuzzy logic when dealing with imprecise and uncertain data allows reducing uncertainty and providing the ability to model fine knowledge details. In this paper, a fuzzy decision tree (FDT) algorithm was applied on a dataset extracted from the ANS (Autonomic Nervous System) unit of the Moroccan university hospital Avicenne. This unit is specialized on performing several dynamic tests to diagnose patients with autonomic disorder and suggest them the appropriate treatment. A set of fuzzy classifiers were generated using FID 3.4. The error rates of the generated FDTs were calculated to measure their performances. Moreover, a comparison between the error rates obtained using crisp and FDTs was carried out and has proved that the results of FDTs were better than those obtained using crisp DTs.

Control Synthesis of Discrete-Time T-S Fuzzy Systems: Reducing the Conservatism Whilst Alleviating the Computational Burden.

Science.gov (United States)

Xie, Xiangpeng; Yue, Dong; Zhang, Huaguang; Peng, Chen

2017-09-01

The augmented multi-indexed matrix approach acts as a powerful tool in reducing the conservatism of control synthesis of discrete-time Takagi-Sugeno fuzzy systems. However, its computational burden is sometimes too heavy as a tradeoff. Nowadays, reducing the conservatism whilst alleviating the computational burden becomes an ideal but very challenging problem. This paper is toward finding an efficient way to achieve one of satisfactory answers. Different from the augmented multi-indexed matrix approach in the literature, we aim to design a more efficient slack variable approach under a general framework of homogenous matrix polynomials. Thanks to the introduction of a new extended representation for homogeneous matrix polynomials, related matrices with the same coefficient are collected together into one sole set and thus those redundant terms of the augmented multi-indexed matrix approach can be removed, i.e., the computational burden can be alleviated in this paper. More importantly, due to the fact that more useful information is involved into control design, the conservatism of the proposed approach as well is less than the counterpart of the augmented multi-indexed matrix approach. Finally, numerical experiments are given to show the effectiveness of the proposed approach.

Electromyography (EMG) signal recognition using combined discrete wavelet transform based adaptive neuro-fuzzy inference systems (ANFIS)

Science.gov (United States)

Arozi, Moh; Putri, Farika T.; Ariyanto, Mochammad; Khusnul Ari, M.; Munadi, Setiawan, Joga D.

2017-01-01

People with disabilities are increasing from year to year either due to congenital factors, sickness, accident factors and war. One form of disability is the case of interruptions of hand function. The condition requires and encourages the search for solutions in the form of creating an artificial hand with the ability as a human hand. The development of science in the field of neuroscience currently allows the use of electromyography (EMG) to control the motion of artificial prosthetic hand into the necessary use of EMG as an input signal to control artificial prosthetic hand. This study is the beginning of a significant research planned in the development of artificial prosthetic hand with EMG signal input. This initial research focused on the study of EMG signal recognition. Preliminary results show that the EMG signal recognition using combined discrete wavelet transform and Adaptive Neuro-Fuzzy Inference System (ANFIS) produces accuracy 98.3 % for training and 98.51% for testing. Thus the results can be used as an input signal for Simulink block diagram of a prosthetic hand that will be developed on next study. The research will proceed with the construction of artificial prosthetic hand along with Simulink program controlling and integrating everything into one system.

Using Metaheuristic and Fuzzy System for the Optimization of Material Pull in a Push-Pull Flow Logistics Network

Directory of Open Access Journals (Sweden)

Afshin Mehrsai

2013-01-01

Full Text Available Alternative material flow strategies in logistics networks have crucial influences on the overall performance of the networks. Material flows can follow push, pull, or hybrid systems. To get the advantages of both push and pull flows in networks, the decoupling-point strategy is used as coordination mean. At this point, material pull has to get optimized concerning customer orders against pushed replenishment-rates. To compensate the ambiguity and uncertainty of both dynamic flows, fuzzy set theory can practically be applied. This paper has conceptual and mathematical parts to explain the performance of the push-pull flow strategy in a supply network and to give a novel solution for optimizing the pull side employing Conwip system. Alternative numbers of pallets and their lot-sizes circulating in the assembly system are getting optimized in accordance with a multi-objective problem; employing a hybrid approach out of meta-heuristics (genetic algorithm and simulated annealing and fuzzy system. Two main fuzzy sets as triangular and trapezoidal are applied in this technique for estimating ill-defined waiting times. The configured technique leads to smoother flows between push and pull sides in complex networks. A discrete-event simulation model is developed to analyze this thesis in an exemplary logistics network with dynamics.

IDENTIFYING ROOF FALL PREDICTORS USING FUZZY CLASSIFICATION

International Nuclear Information System (INIS)

Bertoncini, C. A.; Hinders, M. K.

2010-01-01

Microseismic monitoring involves placing geophones on the rock surfaces of a mine to record seismic activity. Classification of microseismic mine data can be used to predict seismic events in a mine to mitigate mining hazards, such as roof falls, where properly bolting and bracing the roof is often an insufficient method of preventing weak roofs from destabilizing. In this study, six months of recorded acoustic waveforms from microseismic monitoring in a Pennsylvania limestone mine were analyzed using classification techniques to predict roof falls. Fuzzy classification using features selected for computational ease was applied on the mine data. Both large roof fall events could be predicted using a Roof Fall Index (RFI) metric calculated from the results of the fuzzy classification. RFI was successfully used to resolve the two significant roof fall events and predicted both events by at least 15 hours before visual signs of the roof falls were evident.

Evolutionary paths, applications and future development of discrete event simulation systems; Simulazione a eventi discreti: nuove linee di sviluppo e applicazioni

Energy Technology Data Exchange (ETDEWEB)

Garetti, M. [Milan Politecnico, Milan (Italy). Dipt. di Economia e Produzione; Bartolotta, A.

2000-10-01

The state of the art of discrete event simulation tools is presented with special reference to the application to the manufacturing systems area. After presenting the basics of discrete event computer simulation, the different steps to be followed for the successful use of simulation are defined and discussed. The evolution of software packages for discrete event simulation is also presented, highlighting main technological changes. Finally the future development lines of simulation are outlined. [Italian] Viene presentato lo stato dell'arte della simulazione a eventi discreti. Dopo una breve descrizione della tecnica della simulazione e della sua evoluzione, con un particolare riguardo alla simulazione dei sistemi produttivi, sono descritte le fasi della procedura da seguire per condurre unostudio di simulazione e i possibili approcci per la costruzione del modello. Viene infine descritta l'evoluzione dei principali pacchetti software di simulazione esistenti sul mercato.

On Intuitionistic Fuzzy Filters of Intuitionistic Fuzzy Coframes

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Rajesh K. Thumbakara

2013-01-01

Full Text Available Frame theory is the study of topology based on its open set lattice, and it was studied extensively by various authors. In this paper, we study quotients of intuitionistic fuzzy filters of an intuitionistic fuzzy coframe. The quotients of intuitionistic fuzzy filters are shown to be filters of the given intuitionistic fuzzy coframe. It is shown that the collection of all intuitionistic fuzzy filters of a coframe and the collection of all intutionistic fuzzy quotient filters of an intuitionistic fuzzy filter are coframes.

Why fuzzy controllers should be fuzzy

International Nuclear Information System (INIS)

Nowe, A.

1996-01-01

Fuzzy controllers are usually looked at as crisp valued mappings especially when artificial intelligence learning techniques are used to build up the controller. By doing so the semantics of a fuzzy conclusion being a fuzzy restriction on the viable control actions is non-existing. In this paper the authors criticise from an approximation point of view using a fuzzy controller to express a crisp mapping does not seem the right way to go. Secondly it is illustrated that interesting information is contained in a fuzzy conclusion when indeed this conclusion is considered as a fuzzy restriction. This information turns out to be very valuable when viability problems are concerned, i.e. problems where the objective is to keep a system within predefined boundaries

A Framework for the Optimization of Discrete-Event Simulation Models

Science.gov (United States)

Joshi, B. D.; Unal, R.; White, N. H.; Morris, W. D.

1996-01-01

With the growing use of computer modeling and simulation, in all aspects of engineering, the scope of traditional optimization has to be extended to include simulation models. Some unique aspects have to be addressed while optimizing via stochastic simulation models. The optimization procedure has to explicitly account for the randomness inherent in the stochastic measures predicted by the model. This paper outlines a general purpose framework for optimization of terminating discrete-event simulation models. The methodology combines a chance constraint approach for problem formulation, together with standard statistical estimation and analyses techniques. The applicability of the optimization framework is illustrated by minimizing the operation and support resources of a launch vehicle, through a simulation model.

A reduced-form intensity-based model under fuzzy environments

Science.gov (United States)

Wu, Liang; Zhuang, Yaming

2015-05-01

The external shocks and internal contagion are the important sources of default events. However, the external shocks and internal contagion effect on the company is not observed, we cannot get the accurate size of the shocks. The information of investors relative to the default process exhibits a certain fuzziness. Therefore, using randomness and fuzziness to study such problems as derivative pricing or default probability has practical needs. But the idea of fuzzifying credit risk models is little exploited, especially in a reduced-form model. This paper proposes a new default intensity model with fuzziness and presents a fuzzy default probability and default loss rate, and puts them into default debt and credit derivative pricing. Finally, the simulation analysis verifies the rationality of the model. Using fuzzy numbers and random analysis one can consider more uncertain sources in the default process of default and investors' subjective judgment on the financial markets in a variety of fuzzy reliability so as to broaden the scope of possible credit spreads.

Non-fragile ?-? control for discrete-time stochastic nonlinear systems under event-triggered protocols

Science.gov (United States)

Sun, Ying; Ding, Derui; Zhang, Sunjie; Wei, Guoliang; Liu, Hongjian

2018-07-01

In this paper, the non-fragile ?-? control problem is investigated for a class of discrete-time stochastic nonlinear systems under event-triggered communication protocols, which determine whether the measurement output should be transmitted to the controller or not. The main purpose of the addressed problem is to design an event-based output feedback controller subject to gain variations guaranteeing the prescribed disturbance attenuation level described by the ?-? performance index. By utilizing the Lyapunov stability theory combined with S-procedure, a sufficient condition is established to guarantee both the exponential mean-square stability and the ?-? performance for the closed-loop system. In addition, with the help of the orthogonal decomposition, the desired controller parameter is obtained in terms of the solution to certain linear matrix inequalities. Finally, a simulation example is exploited to demonstrate the effectiveness of the proposed event-based controller design scheme.

Analysis of linguistic terms of variables representing the wave of arterial diameter variation in radial arteries using fuzzy entropies

International Nuclear Information System (INIS)

Nuno Almirantearena, F; Introzzi, A; Clara, F; Burillo Lopez, P

2007-01-01

In this work we use 53 Arterial Diameter Variation (ADV) waves extracted from radial artery of normotense males, along with the values of variables that represent the ADV wave, obtained by means of multivariate analysis. Then, we specify the linguistic variables and the linguistic terms. The variables are fuzzified using triangular and trapezoidal fuzzy numbers. We analyze the fuzziness of the linguistic terms by applying discrete and continuous fuzzy entropies. Finally, we infer which variable presents the greatest disorder associated to the loss of arterial elasticity in radial artery

COMPARISON of FUZZY-BASED MODELS in LANDSLIDE HAZARD MAPPING

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N. Mijani

2017-09-01

Full Text Available Landslide is one of the main geomorphic processes which effects on the development of prospect in mountainous areas and causes disastrous accidents. Landslide is an event which has different uncertain criteria such as altitude, slope, aspect, land use, vegetation density, precipitation, distance from the river and distance from the road network. This research aims to compare and evaluate different fuzzy-based models including Fuzzy Analytic Hierarchy Process (Fuzzy-AHP, Fuzzy Gamma and Fuzzy-OR. The main contribution of this paper reveals to the comprehensive criteria causing landslide hazard considering their uncertainties and comparison of different fuzzy-based models. The quantify of evaluation process are calculated by Density Ratio (DR and Quality Sum (QS. The proposed methodology implemented in Sari, one of the city of Iran which has faced multiple landslide accidents in recent years due to the particular environmental conditions. The achieved results of accuracy assessment based on the quantifier strated that Fuzzy-AHP model has higher accuracy compared to other two models in landslide hazard zonation. Accuracy of zoning obtained from Fuzzy-AHP model is respectively 0.92 and 0.45 based on method Precision (P and QS indicators. Based on obtained landslide hazard maps, Fuzzy-AHP, Fuzzy Gamma and Fuzzy-OR respectively cover 13, 26 and 35 percent of the study area with a very high risk level. Based on these findings, fuzzy-AHP model has been selected as the most appropriate method of zoning landslide in the city of Sari and the Fuzzy-gamma method with a minor difference is in the second order.

Numerical implementation of wavelet and fuzzy transform IFOC for three-phase induction motor

DEFF Research Database (Denmark)

Padamanaban, Sanjeevi Kumar; Daya, J.L. Febin; Blaabjerg, Frede

2016-01-01

This article elaborates the numerical implementation of a novel, indirect field-oriented control (IFOC) for induction motor drive by wave-let discrete transform/fuzzy logic interface system unique combination. The feedback (speed) error signal is a mixed component of multiple low and high frequen...

Determination of interrill soil erodibility coefficient based on Fuzzy and Fuzzy-Genetic Systems

Directory of Open Access Journals (Sweden)

Habib Palizvan Zand

2017-02-01

Full Text Available Introduction: Although the fuzzy logic science has been used successfully in various sudies of hydrology and soil erosion, but in literature review no article was found about its performance for estimating of interrill erodibility. On the other hand, studies indicate that genetic algorithm techniques can be used in fuzzy models and finding the appropriate membership functions for linguistic variables and fuzzy rules. So this study was conducted to develop the fuzzy and fuzzy–genetics models and investigation of their performance in the estimation of soil interrill erodibility factor (Ki. Materials and Methods: For this reason 36 soil samples with different physical and chemical properties were collected from west of Azerbaijan province . soilsamples were also taken from the Ap or A horizon of each soil profile. The samples were air-dried , sieved and Some soil characteristics such as soil texture, organic matter (OM, cation exchange capacity (CEC, sodium adsorption ratio (SAR, EC and pH were determined by the standard laboratory methods. Aggregates size distributions (ASD were determined by the wet-sieving method and fractal dimension of soil aggregates (Dn was also calculated. In order to determination of soil interrill erodibility, the flume experiment performed by packing soil a depth of 0.09-m in 0.5 × 1.0 m. soil was saturated from the base and adjusted to 9% slope and was subjected to at least 90 min rainfall . Rainfall intensity treatments were 20, 37 and 47 mm h-1. During each rainfall event, runoff was collected manually in different time intervals, being less than 60 s at the beginning, up to 15 min near the end of the test. At the end of the experiment, the volumes of runoff samples and the mass of sediment load at each time interval were measured. Finally interrill erodibility values were calculated using Kinnell (11 Equation. Then by statistical analyses Dn and sand percent of the soils were selected as input variables and Ki as

Fuzzy spaces topology change and BH thermodynamics

International Nuclear Information System (INIS)

Silva, C A S; Landim, R R

2014-01-01

What is the ultimate fate of something that falls into a black hole? From this question arises one of the most intricate problems of modern theoretical physics: the black hole information loss paradox. Bekenstein and Hawking have been shown that the entropy in a black hole is proportional to the surface area of its event horizon, which should be quantized in a multiple of the Planck area. This led G.'t Hooft and L. Susskind to propose the holographic principle which states that all the information inside the black hole can be stored on its event horizon. From this results, one may think if the solution to the information paradox could lies in the quantum properties of the black hole horizon. One way to quantize the event horizon is to see it as a fuzzy sphere, which posses a closed relation with Hopf algebras. This relation makes possible a topology change process where a fuzzy sphere splits in two others. In this work it will be shown that, if one quantize the black hole event horizon as a fuzzy sphere taking into account its quantum symmetry properties, a topology change process to black holes can be defined without break unitarity or locality, and we can obtain a possible solution to the information paradox. Moreover, we show that this model can explain the origin of the black hole entropy, and why black holes obey a generalized second law of thermodynamics

Discrete event simulation for exploring strategies: an urban water management case.

Science.gov (United States)

Huang, Dong-Bin; Scholz, Roland W; Gujer, Willi; Chitwood, Derek E; Loukopoulos, Peter; Schertenleib, Roland; Siegrist, Hansruedi

2007-02-01

This paper presents a model structure aimed at offering an overview of the various elements of a strategy and exploring their multidimensional effects through time in an efficient way. It treats a strategy as a set of discrete events planned to achieve a certain strategic goal and develops a new form of causal networks as an interfacing component between decision makers and environment models, e.g., life cycle inventory and material flow models. The causal network receives a strategic plan as input in a discrete manner and then outputs the updated parameter sets to the subsequent environmental models. Accordingly, the potential dynamic evolution of environmental systems caused by various strategies can be stepwise simulated. It enables a way to incorporate discontinuous change in models for environmental strategy analysis, and enhances the interpretability and extendibility of a complex model by its cellular constructs. It is exemplified using an urban water management case in Kunming, a major city in Southwest China. By utilizing the presented method, the case study modeled the cross-scale interdependencies of the urban drainage system and regional water balance systems, and evaluated the effectiveness of various strategies for improving the situation of Dianchi Lake.

Discrete event simulation for petroleum transfers involving harbors, refineries and pipelines

Energy Technology Data Exchange (ETDEWEB)

Martins, Marcella S.R.; Lueders, Ricardo; Delgado, Myriam R.B.S. [Universidade Tecnologica Federal do Parana (UTFPR), Curitiba, PR (Brazil)

2009-07-01

Nowadays a great effort has been spent by companies to improve their logistics in terms of programming of events that affect production and distribution of products. In this case, simulation can be a valuable tool for evaluating different behaviors. The objective of this work is to build a discrete event simulation model for scheduling of operational activities in complexes containing one harbor and two refineries interconnected by a pipeline infrastructure. The model was developed in Arena package, based on three sub-models that control pier allocation, loading of tanks, and transfers to refineries through pipelines. Preliminary results obtained for a given control policy, show that profit can be calculated by taking into account many parameters such as oil costs on ships, pier using, over-stay of ships and interface costs. Such problem has already been considered in the literature but using different strategies. All these factors should be considered in a real-world operation where decision making tools are necessary to obtain high returns. (author)

Countable Fuzzy Topological Space and Countable Fuzzy Topological Vector Space

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Apu Kumar Saha

2015-06-01

Full Text Available This paper deals with countable fuzzy topological spaces, a generalization of the notion of fuzzy topological spaces. A collection of fuzzy sets F on a universe X forms a countable fuzzy topology if in the definition of a fuzzy topology, the condition of arbitrary supremum is relaxed to countable supremum. In this generalized fuzzy structure, the continuity of fuzzy functions and some other related properties are studied. Also the class of countable fuzzy topological vector spaces as a generalization of the class of fuzzy topological vector spaces has been introduced and investigated.

Discrete event simulation of the Defense Waste Processing Facility (DWPF) analytical laboratory

International Nuclear Information System (INIS)

Shanahan, K.L.

1992-02-01

A discrete event simulation of the Savannah River Site (SRS) Defense Waste Processing Facility (DWPF) analytical laboratory has been constructed in the GPSS language. It was used to estimate laboratory analysis times at process analytical hold points and to study the effect of sample number on those times. Typical results are presented for three different simultaneous representing increasing levels of complexity, and for different sampling schemes. Example equipment utilization time plots are also included. SRS DWPF laboratory management and chemists found the simulations very useful for resource and schedule planning

Discrete-Event Execution Alternatives on General Purpose Graphical Processing Units

International Nuclear Information System (INIS)

Perumalla, Kalyan S.

2006-01-01

Graphics cards, traditionally designed as accelerators for computer graphics, have evolved to support more general-purpose computation. General Purpose Graphical Processing Units (GPGPUs) are now being used as highly efficient, cost-effective platforms for executing certain simulation applications. While most of these applications belong to the category of time-stepped simulations, little is known about the applicability of GPGPUs to discrete event simulation (DES). Here, we identify some of the issues and challenges that the GPGPU stream-based interface raises for DES, and present some possible approaches to moving DES to GPGPUs. Initial performance results on simulation of a diffusion process show that DES-style execution on GPGPU runs faster than DES on CPU and also significantly faster than time-stepped simulations on either CPU or GPGPU.

DeMO: An Ontology for Discrete-event Modeling and Simulation

Science.gov (United States)

Silver, Gregory A; Miller, John A; Hybinette, Maria; Baramidze, Gregory; York, William S

2011-01-01

Several fields have created ontologies for their subdomains. For example, the biological sciences have developed extensive ontologies such as the Gene Ontology, which is considered a great success. Ontologies could provide similar advantages to the Modeling and Simulation community. They provide a way to establish common vocabularies and capture knowledge about a particular domain with community-wide agreement. Ontologies can support significantly improved (semantic) search and browsing, integration of heterogeneous information sources, and improved knowledge discovery capabilities. This paper discusses the design and development of an ontology for Modeling and Simulation called the Discrete-event Modeling Ontology (DeMO), and it presents prototype applications that demonstrate various uses and benefits that such an ontology may provide to the Modeling and Simulation community. PMID:22919114

Synthesis of controllable and normal sublanguages for discrete-event systems using a coordinator

Czech Academy of Sciences Publication Activity Database

Komenda, Jan; Masopust, Tomáš; van Schuppen, J. H.

2011-01-01

Roč. 60, č. 7 (2011), s. 492-502 ISSN 0167-6911 R&D Projects: GA ČR(CZ) GAP103/11/0517; GA ČR(CZ) GPP202/11/P028 Grant - others:European Commission(XE) EU. ICT .DISC 224498 Institutional research plan: CEZ:AV0Z10190503 Keywords : discrete-event system * coordination control * coordinator Subject RIV: BA - General Mathematics Impact factor: 1.222, year: 2011 http://www.sciencedirect.com/science/article/pii/S0167691111000739

Synthesis of controllable and normal sublanguages for discrete-event systems using a coordinator

Czech Academy of Sciences Publication Activity Database

Komenda, Jan; Masopust, Tomáš; van Schuppen, J. H.

2011-01-01

Roč. 60, č. 7 (2011), s. 492-502 ISSN 0167-6911 R&D Projects: GA ČR(CZ) GAP103/11/0517; GA ČR(CZ) GPP202/11/P028 Grant - others:European Commission(XE) EU.ICT.DISC 224498 Institutional research plan: CEZ:AV0Z10190503 Keywords : discrete-event system * coordination control * coordinator Subject RIV: BA - General Mathematics Impact factor: 1.222, year: 2011 http://www.sciencedirect.com/science/article/pii/S0167691111000739

Optimality Conditions for Fuzzy Number Quadratic Programming with Fuzzy Coefficients

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Xue-Gang Zhou

2014-01-01

Full Text Available The purpose of the present paper is to investigate optimality conditions and duality theory in fuzzy number quadratic programming (FNQP in which the objective function is fuzzy quadratic function with fuzzy number coefficients and the constraint set is fuzzy linear functions with fuzzy number coefficients. Firstly, the equivalent quadratic programming of FNQP is presented by utilizing a linear ranking function and the dual of fuzzy number quadratic programming primal problems is introduced. Secondly, we present optimality conditions for fuzzy number quadratic programming. We then prove several duality results for fuzzy number quadratic programming problems with fuzzy coefficients.

Application of fuzzy consensus for oral pre-cancer and cancer susceptibility assessment

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Satarupa Banerjee

2016-11-01

Full Text Available Health questionnaire data assessment conventionally relies upon statistical analysis in understanding disease susceptibility using discrete numbers and fails to reflect physician’s perspectives and missing narratives in data, which play subtle roles in disease prediction. In addressing such limitations, the present study applies fuzzy consensus in oral health and habit questionnaire data for a selected Indian population in the context of assessing susceptibility to oral pre-cancer and cancer. Methodically collected data were initially divided into age based small subgroups and fuzzy membership function was assigned to each. The methodology further proposed the susceptibility to oral precancers (viz. leukoplakia, oral submucous fibrosis and squamous cell carcinoma in patients considering a fuzzy rulebase through If-Then rules with certain conditions. Incorporation of similarity measures using the Jaccard index was used during conversion into the linguistic output of fuzzy set to predict the disease outcome in a more accurate manner and associated condition of the relevant features. It is also expected that this analytical approach will be effective in devising strategies for policy making through real-life questionnaire data handling.

Fuzzy Itand#244; Integral Driven by a Fuzzy Brownian Motion

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Didier Kumwimba Seya

2015-11-01

Full Text Available In this paper we take into account the fuzzy stochastic integral driven by fuzzy Brownian motion. To define the metric between two fuzzy numbers and to take into account the limit of a sequence of fuzzy numbers, we invoke the Hausdorff metric. First this fuzzy stochastic integral is constructed for fuzzy simple stochastic functions, then the construction is done for fuzzy stochastic integrable functions.

Improvements to Earthquake Location with a Fuzzy Logic Approach

Science.gov (United States)

Gökalp, Hüseyin

2018-01-01

In this study, improvements to the earthquake location method were investigated using a fuzzy logic approach proposed by Lin and Sanford (Bull Seismol Soc Am 91:82-93, 2001). The method has certain advantages compared to the inverse methods in terms of eliminating the uncertainties of arrival times and reading errors. In this study, adopting this approach, epicentral locations were determined based on the results of a fuzzy logic space concerning the uncertainties in the velocity models. To map the uncertainties in arrival times into the fuzzy logic space, a trapezoidal membership function was constructed by directly using the travel time difference between the two stations for the P- and S-arrival times instead of the P- and S-wave models to eliminate the need for obtaining information concerning the velocity structure of the study area. The results showed that this method worked most effectively when earthquakes occurred away from a network or when the arrival time data contained phase reading errors. In this study, to resolve the problems related to determining the epicentral locations of the events, a forward modeling method like the grid search technique was used by applying different logical operations (i.e., intersection, union, and their combination) with a fuzzy logic approach. The locations of the events were depended on results of fuzzy logic outputs in fuzzy logic space by searching in a gridded region. The process of location determination with the defuzzification of only the grid points with the membership value of 1 obtained by normalizing all the maximum fuzzy output values of the highest values resulted in more reliable epicentral locations for the earthquakes than the other approaches. In addition, throughout the process, the center-of-gravity method was used as a defuzzification operation.

Solving fully fuzzy transportation problem using pentagonal fuzzy numbers

Science.gov (United States)

Maheswari, P. Uma; Ganesan, K.

2018-04-01

In this paper, we propose a simple approach for the solution of fuzzy transportation problem under fuzzy environment in which the transportation costs, supplies at sources and demands at destinations are represented by pentagonal fuzzy numbers. The fuzzy transportation problem is solved without converting to its equivalent crisp form using a robust ranking technique and a new fuzzy arithmetic on pentagonal fuzzy numbers. To illustrate the proposed approach a numerical example is provided.

Human Factors Reliability Analysis for Assuring Nuclear Safety Using Fuzzy Fault Tree

International Nuclear Information System (INIS)

Eisawy, E.A.-F. I.; Sallam, H.

2016-01-01

In order to ensure effective prevention of harmful events, the risk assessment process cannot ignore the role of humans in the dynamics of accidental events and thus the seriousness of the consequences that may derive from them. Human reliability analysis (HRA) involves the use of qualitative and quantitative methods to assess the human contribution to risk. HRA techniques have been developed in order to provide human error probability values associated with operators’ tasks to be included within the broader context of system risk assessment, and are aimed at reducing the probability of accidental events. Fault tree analysis (FTA) is a graphical model that displays the various combinations of equipment failures and human errors that can result in the main system failure of interest. FTA is a risk analysis technique to assess likelihood (in a probabilistic context) of an event. The objective data available to estimate the likelihood is often missing, and even if available, is subject to incompleteness and imprecision or vagueness. Without addressing incompleteness and imprecision in the available data, FTA and subsequent risk analysis give a false impression of precision and correctness that undermines the overall credibility of the process. To solve this problem, qualitative justification in the context of failure possibilities can be used as alternative for quantitative justification. In this paper, we introduce the approach of fuzzy reliability as solution for fault tree analysis drawbacks. A new fuzzy fault tree method is proposed for the analysis of human reliability based on fuzzy sets and fuzzy operations t-norms, co-norms, defuzzification, and fuzzy failure probability. (author)

Diamond Fuzzy Number

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T. Pathinathan

2015-01-01

Full Text Available In this paper we define diamond fuzzy number with the help of triangular fuzzy number. We include basic arithmetic operations like addition, subtraction of diamond fuzzy numbers with examples. We define diamond fuzzy matrix with some matrix properties. We have defined Nested diamond fuzzy number and Linked diamond fuzzy number. We have further classified Right Linked Diamond Fuzzy number and Left Linked Diamond Fuzzy number. Finally we have verified the arithmetic operations for the above mentioned types of Diamond Fuzzy Numbers.

The Impact of Inpatient Boarding on ED Efficiency: A Discrete-Event Simulation Study

OpenAIRE

Bair, Aaron E.; Song, Wheyming T.; Chen, Yi-Chun; Morris, Beth A.

2009-01-01

In this study, a discrete-event simulation approach was used to model Emergency Department’s (ED) patient flow to investigate the effect of inpatient boarding on the ED efficiency in terms of the National Emergency Department Crowding Scale (NEDOCS) score and the rate of patients who leave without being seen (LWBS). The decision variable in this model was the boarder-released-ratio defined as the ratio of admitted patients whose boarding time is zero to all admitted patients. Our analysis sho...

SPEEDES - A multiple-synchronization environment for parallel discrete-event simulation

Science.gov (United States)

Steinman, Jeff S.

1992-01-01

Synchronous Parallel Environment for Emulation and Discrete-Event Simulation (SPEEDES) is a unified parallel simulation environment. It supports multiple-synchronization protocols without requiring users to recompile their code. When a SPEEDES simulation runs on one node, all the extra parallel overhead is removed automatically at run time. When the same executable runs in parallel, the user preselects the synchronization algorithm from a list of options. SPEEDES currently runs on UNIX networks and on the California Institute of Technology/Jet Propulsion Laboratory Mark III Hypercube. SPEEDES also supports interactive simulations. Featured in the SPEEDES environment is a new parallel synchronization approach called Breathing Time Buckets. This algorithm uses some of the conservative techniques found in Time Bucket synchronization, along with the optimism that characterizes the Time Warp approach. A mathematical model derived from first principles predicts the performance of Breathing Time Buckets. Along with the Breathing Time Buckets algorithm, this paper discusses the rules for processing events in SPEEDES, describes the implementation of various other synchronization protocols supported by SPEEDES, describes some new ones for the future, discusses interactive simulations, and then gives some performance results.

Fuzzy uncertainty modeling applied to AP1000 nuclear power plant LOCA

International Nuclear Information System (INIS)

Ferreira Guimaraes, Antonio Cesar; Franklin Lapa, Celso Marcelo; Lamego Simoes Filho, Francisco Fernando; Cabral, Denise Cunha

2011-01-01

Research highlights: → This article presents an uncertainty modelling study using a fuzzy approach. → The AP1000 Westinghouse NPP was used and it is provided of passive safety systems. → The use of advanced passive safety systems in NPP has limited operational experience. → Failure rates and basic events probabilities used on the fault tree analysis. → Fuzzy uncertainty approach was employed to reliability of the AP1000 large LOCA. - Abstract: This article presents an uncertainty modeling study using a fuzzy approach applied to the Westinghouse advanced nuclear reactor. The AP1000 Westinghouse Nuclear Power Plant (NPP) is provided of passive safety systems, based on thermo physics phenomenon, that require no operating actions, soon after an incident has been detected. The use of advanced passive safety systems in NPP has limited operational experience. As it occurs in any reliability study, statistically non-significant events report introduces a significant uncertainty level about the failure rates and basic events probabilities used on the fault tree analysis (FTA). In order to model this uncertainty, a fuzzy approach was employed to reliability analysis of the AP1000 large break Loss of Coolant Accident (LOCA). The final results have revealed that the proposed approach may be successfully applied to modeling of uncertainties in safety studies.

Expert Opinion Elicitation Using Fuzzy Set Theory and Distempers-Shaker's Theory

International Nuclear Information System (INIS)

Yu, Donghan

1993-01-01

This study presents a new approach for expert opinion elicitation. The need to work with rare events and limited data is severe accident have led analysts to use expert opinions extensively. Unlike the conventional approaches using point-valued probabilities, the study proposes the concept of fuzzy probability to represent expert opinion. The use of fuzzy probability has an advantage over the conventional approach when an expert's judgment is used under limited data and imprecise knowledge. The study demonstrates a method of combining fuzzy probabilities in a manner consistent with the Distempers-Shaper's Theory (DDT). The propagation of fuzzy probabilities through a system is also introduced

Comparison of discrete event simulation tools in an academic environment

Directory of Open Access Journals (Sweden)

Mario Jadrić

2014-12-01

Full Text Available A new research model for simulation software evaluation is proposed consisting of three main categories of criteria: modeling and simulation capabilities of the explored tools, and tools’ input/output analysis possibilities, all with respective sub-criteria. Using the presented model, two discrete event simulation tools are evaluated in detail using the task-centred scenario. Both tools (Arena and ExtendSim were used for teaching discrete event simulation in preceding academic years. With the aim to inspect their effectiveness and to help us determine which tool is more suitable for students i.e. academic purposes, we used a simple simulation model of entities competing for limited resources. The main goal was to measure subjective (primarily attitude and objective indicators while using the tools when the same simulation scenario is given. The subjects were first year students of Master studies in Information Management at the Faculty of Economics in Split taking a course in Business Process Simulations (BPS. In a controlled environment – in a computer lab, two groups of students were given detailed, step-by-step instructions for building models using both tools - first using ExtendSim then Arena or vice versa. Subjective indicators (students’ attitudes were collected using an online survey completed immediately upon building each model. Subjective indicators primarily include students’ personal estimations of Arena and ExtendSim capabilities/features for model building, model simulation and result analysis. Objective indicators were measured using specialised software that logs information on user's behavior while performing a particular task on their computer such as distance crossed by mouse during model building, the number of mouse clicks, usage of the mouse wheel and speed achieved. The results indicate that ExtendSim is well preferred comparing to Arena with regards to subjective indicators while the objective indicators are

Control of baker’s yeast fermentation : PID and fuzzy algorithms

OpenAIRE

Machado, Carlos; Gomes, Pedro; Soares, Rui; Pereira, Silvia; Soares, Filomena

2001-01-01

A MATLAB/SIMULINK-based simulator was employed for studies concerning the control of baker’s yeast fed-batch fermentation. Four control algorithms were implemented and compared: the classical PID control, two discrete versions- modified velocity and position algorithms, and a fuzzy law. The simulation package was seen to be an efficient tool for the simulation and tests of control strategies of the non-linear process.

Developing Flexible Discrete Event Simulation Models in an Uncertain Policy Environment

Science.gov (United States)

Miranda, David J.; Fayez, Sam; Steele, Martin J.

2011-01-01

On February 1st, 2010 U.S. President Barack Obama submitted to Congress his proposed budget request for Fiscal Year 2011. This budget included significant changes to the National Aeronautics and Space Administration (NASA), including the proposed cancellation of the Constellation Program. This change proved to be controversial and Congressional approval of the program's official cancellation would take many months to complete. During this same period an end-to-end discrete event simulation (DES) model of Constellation operations was being built through the joint efforts of Productivity Apex Inc. (PAl) and Science Applications International Corporation (SAIC) teams under the guidance of NASA. The uncertainty in regards to the Constellation program presented a major challenge to the DES team, as to: continue the development of this program-of-record simulation, while at the same time remain prepared for possible changes to the program. This required the team to rethink how it would develop it's model and make it flexible enough to support possible future vehicles while at the same time be specific enough to support the program-of-record. This challenge was compounded by the fact that this model was being developed through the traditional DES process-orientation which lacked the flexibility of object-oriented approaches. The team met this challenge through significant pre-planning that led to the "modularization" of the model's structure by identifying what was generic, finding natural logic break points, and the standardization of interlogic numbering system. The outcome of this work resulted in a model that not only was ready to be easily modified to support any future rocket programs, but also a model that was extremely structured and organized in a way that facilitated rapid verification. This paper discusses in detail the process the team followed to build this model and the many advantages this method provides builders of traditional process-oriented discrete

Fuzzy logic utilization for the diagnosis of metallic loose part impact in nuclear power plant

International Nuclear Information System (INIS)

Oh, Y.-G.; Hong, H.-P.; Han, S.-J.; Chun, C.S.; Kim, B.-K.

1996-01-01

In consideration of the fuzzy nature of impact signals detected from the complex mechanical structures in a nuclear power plant under operation. Loose Part Monitoring System with a signal processing technique utilizing fuzzy logic is proposed. In the proposed Fuzzy Loose Part Monitoring System design, comprehensive relations among the impact signal features are taken into account in the fuzzy rule bases for the alarm discrimination and impact event diagnosis. Through the performance test with a mock-up facility, the proposed approach for the loose parts monitoring and diagnosis has been revealed to be effective not only in suppressing the false alarm generation but also in characterizing the metallic loose-part impact event, from the points of Possible Impacted-Area and Degree of Impact Magnitude

Modeling a Million-Node Slim Fly Network Using Parallel Discrete-Event Simulation

Energy Technology Data Exchange (ETDEWEB)

Wolfe, Noah; Carothers, Christopher; Mubarak, Misbah; Ross, Robert; Carns, Philip

2016-05-15

As supercomputers close in on exascale performance, the increased number of processors and processing power translates to an increased demand on the underlying network interconnect. The Slim Fly network topology, a new lowdiameter and low-latency interconnection network, is gaining interest as one possible solution for next-generation supercomputing interconnect systems. In this paper, we present a high-fidelity Slim Fly it-level model leveraging the Rensselaer Optimistic Simulation System (ROSS) and Co-Design of Exascale Storage (CODES) frameworks. We validate our Slim Fly model with the Kathareios et al. Slim Fly model results provided at moderately sized network scales. We further scale the model size up to n unprecedented 1 million compute nodes; and through visualization of network simulation metrics such as link bandwidth, packet latency, and port occupancy, we get an insight into the network behavior at the million-node scale. We also show linear strong scaling of the Slim Fly model on an Intel cluster achieving a peak event rate of 36 million events per second using 128 MPI tasks to process 7 billion events. Detailed analysis of the underlying discrete-event simulation performance shows that a million-node Slim Fly model simulation can execute in 198 seconds on the Intel cluster.

Fuzzy forecasting based on fuzzy-trend logical relationship groups.

Science.gov (United States)

Chen, Shyi-Ming; Wang, Nai-Yi

2010-10-01

In this paper, we present a new method to predict the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) based on fuzzy-trend logical relationship groups (FTLRGs). The proposed method divides fuzzy logical relationships into FTLRGs based on the trend of adjacent fuzzy sets appearing in the antecedents of fuzzy logical relationships. First, we apply an automatic clustering algorithm to cluster the historical data into intervals of different lengths. Then, we define fuzzy sets based on these intervals of different lengths. Then, the historical data are fuzzified into fuzzy sets to derive fuzzy logical relationships. Then, we divide the fuzzy logical relationships into FTLRGs for forecasting the TAIEX. Moreover, we also apply the proposed method to forecast the enrollments and the inventory demand, respectively. The experimental results show that the proposed method gets higher average forecasting accuracy rates than the existing methods.

Multiple-event probability in general-relativistic quantum mechanics. II. A discrete model

International Nuclear Information System (INIS)

Mondragon, Mauricio; Perez, Alejandro; Rovelli, Carlo

2007-01-01

We introduce a simple quantum mechanical model in which time and space are discrete and periodic. These features avoid the complications related to continuous-spectrum operators and infinite-norm states. The model provides a tool for discussing the probabilistic interpretation of generally covariant quantum systems, without the confusion generated by spurious infinities. We use the model to illustrate the formalism of general-relativistic quantum mechanics, and to test the definition of multiple-event probability introduced in a companion paper [Phys. Rev. D 75, 084033 (2007)]. We consider a version of the model with unitary time evolution and a version without unitary time evolution

A participative and facilitative conceptual modelling framework for discrete event simulation studies in healthcare

OpenAIRE

Kotiadis, Kathy; Tako, Antuela; Vasilakis, Christos

2014-01-01

Existing approaches to conceptual modelling (CM) in discrete-event simulation do not formally support the participation of a group of stakeholders. Simulation in healthcare can benefit from stakeholder participation as it makes possible to share multiple views and tacit knowledge from different parts of the system. We put forward a framework tailored to healthcare that supports the interaction of simulation modellers with a group of stakeholders to arrive at a common conceptual model. The fra...

Discrete event simulation and virtual reality use in industry: new opportunities and future trends

OpenAIRE

Turner, Christopher; Hutabarat, Windo; Oyekan, John; Tiwari, Ashutosh

2016-01-01

This paper reviews the area of combined discrete event simulation (DES) and virtual reality (VR) use within industry. While establishing a state of the art for progress in this area, this paper makes the case for VR DES as the vehicle of choice for complex data analysis through interactive simulation models, highlighting both its advantages and current limitations. This paper reviews active research topics such as VR and DES real-time integration, communication protocols,...

A Discrete Model for Color Naming

Science.gov (United States)

Menegaz, G.; Le Troter, A.; Sequeira, J.; Boi, J. M.

2006-12-01

The ability to associate labels to colors is very natural for human beings. Though, this apparently simple task hides very complex and still unsolved problems, spreading over many different disciplines ranging from neurophysiology to psychology and imaging. In this paper, we propose a discrete model for computational color categorization and naming. Starting from the 424 color specimens of the OSA-UCS set, we propose a fuzzy partitioning of the color space. Each of the 11 basic color categories identified by Berlin and Kay is modeled as a fuzzy set whose membership function is implicitly defined by fitting the model to the results of an ad hoc psychophysical experiment (Experiment 1). Each OSA-UCS sample is represented by a feature vector whose components are the memberships to the different categories. The discrete model consists of a three-dimensional Delaunay triangulation of the CIELAB color space which associates each OSA-UCS sample to a vertex of a 3D tetrahedron. Linear interpolation is used to estimate the membership values of any other point in the color space. Model validation is performed both directly, through the comparison of the predicted membership values to the subjective counterparts, as evaluated via another psychophysical test (Experiment 2), and indirectly, through the investigation of its exploitability for image segmentation. The model has proved to be successful in both cases, providing an estimation of the membership values in good agreement with the subjective measures as well as a semantically meaningful color-based segmentation map.

Parallel discrete-event simulation of FCFS stochastic queueing networks

Science.gov (United States)

Nicol, David M.

1988-01-01

Physical systems are inherently parallel. Intuition suggests that simulations of these systems may be amenable to parallel execution. The parallel execution of a discrete-event simulation requires careful synchronization of processes in order to ensure the execution's correctness; this synchronization can degrade performance. Largely negative results were recently reported in a study which used a well-known synchronization method on queueing network simulations. Discussed here is a synchronization method (appointments), which has proven itself to be effective on simulations of FCFS queueing networks. The key concept behind appointments is the provision of lookahead. Lookahead is a prediction on a processor's future behavior, based on an analysis of the processor's simulation state. It is shown how lookahead can be computed for FCFS queueing network simulations, give performance data that demonstrates the method's effectiveness under moderate to heavy loads, and discuss performance tradeoffs between the quality of lookahead, and the cost of computing lookahead.

Simulation of land use evolution by discrete events method: Application to “la chaîne des puys” from XV to XVIII Century

OpenAIRE

Y. Michelin; C. Poix

1998-01-01

By using a discrete event method, simulation of land use evolution has been applied to a landscape model of “la ChaÎne des Puys” (French Massif Central) during along period (XV–XVIII centuries). The indications concerning the evolution of land use are in conformity with the observation of actual situations but the dynamic changes are faster than in actual facts. In spite of limitations due to necessary simplifications, it is now established that the discrete event method is efficient to simu...

On the Fuzzy Convergence

Directory of Open Access Journals (Sweden)

Abdul Hameed Q. A. Al-Tai

2011-01-01

Full Text Available The aim of this paper is to introduce and study the fuzzy neighborhood, the limit fuzzy number, the convergent fuzzy sequence, the bounded fuzzy sequence, and the Cauchy fuzzy sequence on the base which is adopted by Abdul Hameed (every real number r is replaced by a fuzzy number r¯ (either triangular fuzzy number or singleton fuzzy set (fuzzy point. And then, we will consider that some results respect effect of the upper sequence on the convergent fuzzy sequence, the bounded fuzzy sequence, and the Cauchy fuzzy sequence.

A paradigm for discrete physics

International Nuclear Information System (INIS)

Noyes, H.P.; McGoveran, D.; Etter, T.; Manthey, M.J.; Gefwert, C.

1987-01-01

An example is outlined for constructing a discrete physics using as a starting point the insight from quantum physics that events are discrete, indivisible and non-local. Initial postulates are finiteness, discreteness, finite computability, absolute nonuniqueness (i.e., homogeneity in the absence of specific cause) and additivity

Stability Analysis of Interconnected Fuzzy Systems Using the Fuzzy Lyapunov Method

Directory of Open Access Journals (Sweden)

Ken Yeh

2010-01-01

Full Text Available The fuzzy Lyapunov method is investigated for use with a class of interconnected fuzzy systems. The interconnected fuzzy systems consist of J interconnected fuzzy subsystems, and the stability analysis is based on Lyapunov functions. Based on traditional Lyapunov stability theory, we further propose a fuzzy Lyapunov method for the stability analysis of interconnected fuzzy systems. The fuzzy Lyapunov function is defined in fuzzy blending quadratic Lyapunov functions. Some stability conditions are derived through the use of fuzzy Lyapunov functions to ensure that the interconnected fuzzy systems are asymptotically stable. Common solutions can be obtained by solving a set of linear matrix inequalities (LMIs that are numerically feasible. Finally, simulations are performed in order to verify the effectiveness of the proposed stability conditions in this paper.

A new hybrid evolutionary algorithm based on new fuzzy adaptive PSO and NM algorithms for Distribution Feeder Reconfiguration

International Nuclear Information System (INIS)

Niknam, Taher; Azadfarsani, Ehsan; Jabbari, Masoud

2012-01-01

Highlights: ► Network reconfiguration is a very important way to save the electrical energy. ► This paper proposes a new algorithm to solve the DFR. ► The algorithm combines NFAPSO with NM. ► The proposed algorithm is tested on two distribution test feeders. - Abstract: Network reconfiguration for loss reduction in distribution system is a very important way to save the electrical energy. This paper proposes a new hybrid evolutionary algorithm to solve the Distribution Feeder Reconfiguration problem (DFR). The algorithm is based on combination of a New Fuzzy Adaptive Particle Swarm Optimization (NFAPSO) and Nelder–Mead simplex search method (NM) called NFAPSO–NM. In the proposed algorithm, a new fuzzy adaptive particle swarm optimization includes two parts. The first part is Fuzzy Adaptive Binary Particle Swarm Optimization (FABPSO) that determines the status of tie switches (open or close) and second part is Fuzzy Adaptive Discrete Particle Swarm Optimization (FADPSO) that determines the sectionalizing switch number. In other side, due to the results of binary PSO(BPSO) and discrete PSO(DPSO) algorithms highly depends on the values of their parameters such as the inertia weight and learning factors, a fuzzy system is employed to adaptively adjust the parameters during the search process. Moreover, the Nelder–Mead simplex search method is combined with the NFAPSO algorithm to improve its performance. Finally, the proposed algorithm is tested on two distribution test feeders. The results of simulation show that the proposed method is very powerful and guarantees to obtain the global optimization.

A neural fuzzy controller learning by fuzzy error propagation

Science.gov (United States)

Nauck, Detlef; Kruse, Rudolf

1992-01-01

In this paper, we describe a procedure to integrate techniques for the adaptation of membership functions in a linguistic variable based fuzzy control environment by using neural network learning principles. This is an extension to our work. We solve this problem by defining a fuzzy error that is propagated back through the architecture of our fuzzy controller. According to this fuzzy error and the strength of its antecedent each fuzzy rule determines its amount of error. Depending on the current state of the controlled system and the control action derived from the conclusion, each rule tunes the membership functions of its antecedent and its conclusion. By this we get an unsupervised learning technique that enables a fuzzy controller to adapt to a control task by knowing just about the global state and the fuzzy error.

A discrete event modelling framework for simulation of long-term outcomes of sequential treatment strategies for ankylosing spondylitis

NARCIS (Netherlands)

A. Tran-Duy (An); A. Boonen (Annelies); M.A.F.J. van de Laar (Mart); A. Franke (Andre); J.L. Severens (Hans)

2011-01-01

textabstractObjective: To develop a modelling framework which can simulate long-term quality of life, societal costs and cost-effectiveness as affected by sequential drug treatment strategies for ankylosing spondylitis (AS). Methods: Discrete event simulation paradigm was selected for model

A discrete event modelling framework for simulation of long-term outcomes of sequential treatment strategies for ankylosing spondylitis

NARCIS (Netherlands)

Tran-Duy, A.; Boonen, A.; Laar, M.A.F.J.; Franke, A.C.; Severens, J.L.

2011-01-01

Objective To develop a modelling framework which can simulate long-term quality of life, societal costs and cost-effectiveness as affected by sequential drug treatment strategies for ankylosing spondylitis (AS). Methods Discrete event simulation paradigm was selected for model development. Drug

An inexact fuzzy-chance-constrained air quality management model.

Science.gov (United States)

Xu, Ye; Huang, Guohe; Qin, Xiaosheng

2010-07-01

Regional air pollution is a major concern for almost every country because it not only directly relates to economic development, but also poses significant threats to environment and public health. In this study, an inexact fuzzy-chance-constrained air quality management model (IFAMM) was developed for regional air quality management under uncertainty. IFAMM was formulated through integrating interval linear programming (ILP) within a fuzzy-chance-constrained programming (FCCP) framework and could deal with uncertainties expressed as not only possibilistic distributions but also discrete intervals in air quality management systems. Moreover, the constraints with fuzzy variables could be satisfied at different confidence levels such that various solutions with different risk and cost considerations could be obtained. The developed model was applied to a hypothetical case of regional air quality management. Six abatement technologies and sulfur dioxide (SO2) emission trading under uncertainty were taken into consideration. The results demonstrated that IFAMM could help decision-makers generate cost-effective air quality management patterns, gain in-depth insights into effects of the uncertainties, and analyze tradeoffs between system economy and reliability. The results also implied that the trading scheme could achieve lower total abatement cost than a nontrading one.

Complex Fuzzy Set-Valued Complex Fuzzy Measures and Their Properties

Science.gov (United States)

Ma, Shengquan; Li, Shenggang

2014-01-01

Let F*(K) be the set of all fuzzy complex numbers. In this paper some classical and measure-theoretical notions are extended to the case of complex fuzzy sets. They are fuzzy complex number-valued distance on F*(K), fuzzy complex number-valued measure on F*(K), and some related notions, such as null-additivity, pseudo-null-additivity, null-subtraction, pseudo-null-subtraction, autocontionuous from above, autocontionuous from below, and autocontinuity of the defined fuzzy complex number-valued measures. Properties of fuzzy complex number-valued measures are studied in detail. PMID:25093202

A mathematical approach for evaluating Markov models in continuous time without discrete-event simulation.

Science.gov (United States)

van Rosmalen, Joost; Toy, Mehlika; O'Mahony, James F

2013-08-01

Markov models are a simple and powerful tool for analyzing the health and economic effects of health care interventions. These models are usually evaluated in discrete time using cohort analysis. The use of discrete time assumes that changes in health states occur only at the end of a cycle period. Discrete-time Markov models only approximate the process of disease progression, as clinical events typically occur in continuous time. The approximation can yield biased cost-effectiveness estimates for Markov models with long cycle periods and if no half-cycle correction is made. The purpose of this article is to present an overview of methods for evaluating Markov models in continuous time. These methods use mathematical results from stochastic process theory and control theory. The methods are illustrated using an applied example on the cost-effectiveness of antiviral therapy for chronic hepatitis B. The main result is a mathematical solution for the expected time spent in each state in a continuous-time Markov model. It is shown how this solution can account for age-dependent transition rates and discounting of costs and health effects, and how the concept of tunnel states can be used to account for transition rates that depend on the time spent in a state. The applied example shows that the continuous-time model yields more accurate results than the discrete-time model but does not require much computation time and is easily implemented. In conclusion, continuous-time Markov models are a feasible alternative to cohort analysis and can offer several theoretical and practical advantages.

Hierarchical type-2 fuzzy aggregation of fuzzy controllers

CERN Document Server

Cervantes, Leticia

2016-01-01

This book focuses on the fields of fuzzy logic, granular computing and also considering the control area. These areas can work together to solve various control problems, the idea is that this combination of areas would enable even more complex problem solving and better results. In this book we test the proposed method using two benchmark problems: the total flight control and the problem of water level control for a 3 tank system. When fuzzy logic is used it make it easy to performed the simulations, these fuzzy systems help to model the behavior of a real systems, using the fuzzy systems fuzzy rules are generated and with this can generate the behavior of any variable depending on the inputs and linguistic value. For this reason this work considers the proposed architecture using fuzzy systems and with this improve the behavior of the complex control problems.

Temperature prediction in a coal fired boiler with a fixed bed by fuzzy logic based on numerical solution

International Nuclear Information System (INIS)

Biyikoglu, A.; Akcayol, M.A.; Oezdemir, V.; Sivrioglu, M.

2005-01-01

In this study, steady state combustion in boilers with a fixed bed has been investigated. Temperature distributions in the combustion chamber of a coal fired boiler with a fixed bed are predicted using fuzzy logic based on data obtained from the numerical solution method for various coal and air feeding rates. The numerical solution method and the discretization of the governing equations of two dimensional turbulent flow in the combustion chamber and one dimensional coal combustion in the fixed bed are explained. Control Volume and Finite Difference Methods are used in the discretization of the equations in the combustion chamber and in the fixed bed, respectively. Results are presented as contours within the solution domain and compared with numerical ones. Comparison of the results shows that the difference between the numerical solution and fuzzy logic prediction throughout the computational domain is less than 1.5%. The statistical coefficient of multiple determinations for the investigated cases is about 0.9993 to 0.9998. This accuracy degree is acceptable in predicting the temperature values. So, it can be concluded that fuzzy logic provides a feasible method for defining the system properties

Compensatory neurofuzzy model for discrete data classification in biomedical

Science.gov (United States)

Ceylan, Rahime

2015-03-01

Biomedical data is separated to two main sections: signals and discrete data. So, studies in this area are about biomedical signal classification or biomedical discrete data classification. There are artificial intelligence models which are relevant to classification of ECG, EMG or EEG signals. In same way, in literature, many models exist for classification of discrete data taken as value of samples which can be results of blood analysis or biopsy in medical process. Each algorithm could not achieve high accuracy rate on classification of signal and discrete data. In this study, compensatory neurofuzzy network model is presented for classification of discrete data in biomedical pattern recognition area. The compensatory neurofuzzy network has a hybrid and binary classifier. In this system, the parameters of fuzzy systems are updated by backpropagation algorithm. The realized classifier model is conducted to two benchmark datasets (Wisconsin Breast Cancer dataset and Pima Indian Diabetes dataset). Experimental studies show that compensatory neurofuzzy network model achieved 96.11% accuracy rate in classification of breast cancer dataset and 69.08% accuracy rate was obtained in experiments made on diabetes dataset with only 10 iterations.

Fuzzy portfolio model with fuzzy-input return rates and fuzzy-output proportions

Science.gov (United States)

Tsaur, Ruey-Chyn

2015-02-01

In the finance market, a short-term investment strategy is usually applied in portfolio selection in order to reduce investment risk; however, the economy is uncertain and the investment period is short. Further, an investor has incomplete information for selecting a portfolio with crisp proportions for each chosen security. In this paper we present a new method of constructing fuzzy portfolio model for the parameters of fuzzy-input return rates and fuzzy-output proportions, based on possibilistic mean-standard deviation models. Furthermore, we consider both excess or shortage of investment in different economic periods by using fuzzy constraint for the sum of the fuzzy proportions, and we also refer to risks of securities investment and vagueness of incomplete information during the period of depression economics for the portfolio selection. Finally, we present a numerical example of a portfolio selection problem to illustrate the proposed model and a sensitivity analysis is realised based on the results.

A Discrete Events Delay Differential System Model for Transmission of Vancomycin-Resistant Enterococcus (VRE) in Hospitals

Science.gov (United States)

2010-09-19

estimated directly form the surveillance data Infection control measures were implemented in the form of health care worker hand - hygiene before and after...hospital infections , is used to motivate possibilities of modeling nosocomial infec- tion dynamics. This is done in the context of hospital monitoring and...model development. Key Words: Delay equations, discrete events, nosocomial infection dynamics, surveil- lance data, inverse problems, parameter

Combining fuzzy mathematics with fuzzy logic to solve business management problems

Science.gov (United States)

Vrba, Joseph A.

1993-12-01

Fuzzy logic technology has been applied to control problems with great success. Because of this, many observers fell that fuzzy logic is applicable only in the control arena. However, business management problems almost never deal with crisp values. Fuzzy systems technology--a combination of fuzzy logic, fuzzy mathematics and a graphical user interface--is a natural fit for developing software to assist in typical business activities such as planning, modeling and estimating. This presentation discusses how fuzzy logic systems can be extended through the application of fuzzy mathematics and the use of a graphical user interface to make the information contained in fuzzy numbers accessible to business managers. As demonstrated through examples from actual deployed systems, this fuzzy systems technology has been employed successfully to provide solutions to the complex real-world problems found in the business environment.

Fuzzy Languages

Science.gov (United States)

Rahonis, George

The theory of fuzzy recognizable languages over bounded distributive lattices is presented as a paradigm of recognizable formal power series. Due to the idempotency properties of bounded distributive lattices, the equality of fuzzy recognizable languages is decidable, the determinization of multi-valued automata is effective, and a pumping lemma exists. Fuzzy recognizable languages over finite and infinite words are expressively equivalent to sentences of the multi-valued monadic second-order logic. Fuzzy recognizability over bounded ℓ-monoids and residuated lattices is briefly reported. The chapter concludes with two applications of fuzzy recognizable languages to real world problems in medicine.

Relational Demonic Fuzzy Refinement

Directory of Open Access Journals (Sweden)

Fairouz Tchier

2014-01-01

Full Text Available We use relational algebra to define a refinement fuzzy order called demonic fuzzy refinement and also the associated fuzzy operators which are fuzzy demonic join (⊔fuz, fuzzy demonic meet (⊓fuz, and fuzzy demonic composition (□fuz. Our definitions and properties are illustrated by some examples using mathematica software (fuzzy logic.

Modelling and real-time simulation of continuous-discrete systems in mechatronics

Energy Technology Data Exchange (ETDEWEB)

Lindow, H. [Rostocker, Magdeburg (Germany)

1996-12-31

This work presents a methodology for simulation and modelling of systems with continuous - discrete dynamics. It derives hybrid discrete event models from Lagrange`s equations of motion. This method combines continuous mechanical, electrical and thermodynamical submodels on one hand with discrete event models an the other hand into a hybrid discrete event model. This straight forward software development avoids numeric overhead.

Performance Analysis of Cloud Computing Architectures Using Discrete Event Simulation

Science.gov (United States)

Stocker, John C.; Golomb, Andrew M.

2011-01-01

Cloud computing offers the economic benefit of on-demand resource allocation to meet changing enterprise computing needs. However, the flexibility of cloud computing is disadvantaged when compared to traditional hosting in providing predictable application and service performance. Cloud computing relies on resource scheduling in a virtualized network-centric server environment, which makes static performance analysis infeasible. We developed a discrete event simulation model to evaluate the overall effectiveness of organizations in executing their workflow in traditional and cloud computing architectures. The two part model framework characterizes both the demand using a probability distribution for each type of service request as well as enterprise computing resource constraints. Our simulations provide quantitative analysis to design and provision computing architectures that maximize overall mission effectiveness. We share our analysis of key resource constraints in cloud computing architectures and findings on the appropriateness of cloud computing in various applications.

Quality Improvement With Discrete Event Simulation: A Primer for Radiologists.

Science.gov (United States)

Booker, Michael T; O'Connell, Ryan J; Desai, Bhushan; Duddalwar, Vinay A

2016-04-01

The application of simulation software in health care has transformed quality and process improvement. Specifically, software based on discrete-event simulation (DES) has shown the ability to improve radiology workflows and systems. Nevertheless, despite the successful application of DES in the medical literature, the power and value of simulation remains underutilized. For this reason, the basics of DES modeling are introduced, with specific attention to medical imaging. In an effort to provide readers with the tools necessary to begin their own DES analyses, the practical steps of choosing a software package and building a basic radiology model are discussed. In addition, three radiology system examples are presented, with accompanying DES models that assist in analysis and decision making. Through these simulations, we provide readers with an understanding of the theory, requirements, and benefits of implementing DES in their own radiology practices. Copyright © 2016 American College of Radiology. All rights reserved.

Using discrete event simulation to change from a functional layout to a cellular layout in an auto parts industry

Directory of Open Access Journals (Sweden)

Thiago Buselato Maurício

2015-07-01

Full Text Available This paper presents a discrete event simulation employed in a Brazilian automotive company. There was a huge waste caused by one family scrap. It was believed one reason was the company functional layout. In this case, changing from current to cellular layout, employee synergy and knowledge about this family would increase. Due to the complexity for dimensioning a new cellular layout, mainly because of batch size and client’s demand variation. In this case, discrete event simulation was used, which made possible to introduce those effects improving accuracy in final results. This accuracy will be shown by comparing results obtained with simulation and without it (as company used to do. To conclude, cellular layout was responsible for increasing 15% of productivity, reducing lead-time in 7 days and scrap in 15% for this family.

A Discrete Model for Color Naming

Directory of Open Access Journals (Sweden)

J. M. Boi

2007-01-01

Full Text Available The ability to associate labels to colors is very natural for human beings. Though, this apparently simple task hides very complex and still unsolved problems, spreading over many different disciplines ranging from neurophysiology to psychology and imaging. In this paper, we propose a discrete model for computational color categorization and naming. Starting from the 424 color specimens of the OSA-UCS set, we propose a fuzzy partitioning of the color space. Each of the 11 basic color categories identified by Berlin and Kay is modeled as a fuzzy set whose membership function is implicitly defined by fitting the model to the results of an ad hoc psychophysical experiment (Experiment 1. Each OSA-UCS sample is represented by a feature vector whose components are the memberships to the different categories. The discrete model consists of a three-dimensional Delaunay triangulation of the CIELAB color space which associates each OSA-UCS sample to a vertex of a 3D tetrahedron. Linear interpolation is used to estimate the membership values of any other point in the color space. Model validation is performed both directly, through the comparison of the predicted membership values to the subjective counterparts, as evaluated via another psychophysical test (Experiment 2, and indirectly, through the investigation of its exploitability for image segmentation. The model has proved to be successful in both cases, providing an estimation of the membership values in good agreement with the subjective measures as well as a semantically meaningful color-based segmentation map.

A unified approach for squeal instability analysis of disc brakes with two types of random-fuzzy uncertainties

Science.gov (United States)

Lü, Hui; Shangguan, Wen-Bin; Yu, Dejie

2017-09-01

Automotive brake systems are always subjected to various types of uncertainties and two types of random-fuzzy uncertainties may exist in the brakes. In this paper, a unified approach is proposed for squeal instability analysis of disc brakes with two types of random-fuzzy uncertainties. In the proposed approach, two uncertainty analysis models with mixed variables are introduced to model the random-fuzzy uncertainties. The first one is the random and fuzzy model, in which random variables and fuzzy variables exist simultaneously and independently. The second one is the fuzzy random model, in which uncertain parameters are all treated as random variables while their distribution parameters are expressed as fuzzy numbers. Firstly, the fuzziness is discretized by using α-cut technique and the two uncertainty analysis models are simplified into random-interval models. Afterwards, by temporarily neglecting interval uncertainties, the random-interval models are degraded into random models, in which the expectations, variances, reliability indexes and reliability probabilities of system stability functions are calculated. And then, by reconsidering the interval uncertainties, the bounds of the expectations, variances, reliability indexes and reliability probabilities are computed based on Taylor series expansion. Finally, by recomposing the analysis results at each α-cut level, the fuzzy reliability indexes and probabilities can be obtained, by which the brake squeal instability can be evaluated. The proposed approach gives a general framework to deal with both types of random-fuzzy uncertainties that may exist in the brakes and its effectiveness is demonstrated by numerical examples. It will be a valuable supplement to the systematic study of brake squeal considering uncertainty.

Examining Passenger Flow Choke Points at Airports Using Discrete Event Simulation

Science.gov (United States)

Brown, Jeremy R.; Madhavan, Poomima

2011-01-01

The movement of passengers through an airport quickly, safely, and efficiently is the main function of the various checkpoints (check-in, security. etc) found in airports. Human error combined with other breakdowns in the complex system of the airport can disrupt passenger flow through the airport leading to lengthy waiting times, missing luggage and missed flights. In this paper we present a model of passenger flow through an airport using discrete event simulation that will provide a closer look into the possible reasons for breakdowns and their implications for passenger flow. The simulation is based on data collected at Norfolk International Airport (ORF). The primary goal of this simulation is to present ways to optimize the work force to keep passenger flow smooth even during peak travel times and for emergency preparedness at ORF in case of adverse events. In this simulation we ran three different scenarios: real world, increased check-in stations, and multiple waiting lines. Increased check-in stations increased waiting time and instantaneous utilization. while the multiple waiting lines decreased both the waiting time and instantaneous utilization. This simulation was able to show how different changes affected the passenger flow through the airport.

Fault diagnosis for discrete event systems: Modelling and verification

International Nuclear Information System (INIS)

Simeu-Abazi, Zineb; Di Mascolo, Maria; Knotek, Michal

2010-01-01

This paper proposes an effective way for diagnosis of discrete-event systems using a timed-automaton. It is based on the model-checking technique, thanks to time analysis of the timed model. The paper proposes a method to construct all the timed models and details the different steps used to obtain the diagnosis path. A dynamic model with temporal transitions is proposed in order to model the system. By 'dynamical model', we mean an extension of timed automata for which the faulty states are identified. The model of the studied system contains the faultless functioning states and all the faulty states. Our method is based on the backward exploitation of the dynamic model, where all possible reverse paths are searched. The reverse path is the connection of the faulty state to the initial state. The diagnosis method is based on the coherence between the faulty occurrence time and the reverse path length. A real-world batch process is used to demonstrate the modelling steps and the proposed backward time analysis method to reach the diagnosis results.

Fuzzy logic

CERN Document Server

Smets, P

1995-01-01

We start by describing the nature of imperfect data, and giving an overview of the various models that have been proposed. Fuzzy sets theory is shown to be an extension of classical set theory, and as such has a proeminent role or modelling imperfect data. The mathematic of fuzzy sets theory is detailled, in particular the role of the triangular norms. The use of fuzzy sets theory in fuzzy logic and possibility theory,the nature of the generalized modus ponens and of the implication operator for approximate reasoning are analysed. The use of fuzzy logic is detailled for application oriented towards process control and database problems.

α-Cut method based importance measure for criticality analysis in fuzzy probability – Based fault tree analysis

International Nuclear Information System (INIS)

Purba, Julwan Hendry; Sony Tjahyani, D.T.; Widodo, Surip; Tjahjono, Hendro

2017-01-01

Highlights: •FPFTA deals with epistemic uncertainty using fuzzy probability. •Criticality analysis is important for reliability improvement. •An α-cut method based importance measure is proposed for criticality analysis in FPFTA. •The α-cut method based importance measure utilises α-cut multiplication, α-cut subtraction, and area defuzzification technique. •Benchmarking confirm that the proposed method is feasible for criticality analysis in FPFTA. -- Abstract: Fuzzy probability – based fault tree analysis (FPFTA) has been recently developed and proposed to deal with the limitations of conventional fault tree analysis. In FPFTA, reliabilities of basic events, intermediate events and top event are characterized by fuzzy probabilities. Furthermore, the quantification of the FPFTA is based on fuzzy multiplication rule and fuzzy complementation rule to propagate uncertainties from basic event to the top event. Since the objective of the fault tree analysis is to improve the reliability of the system being evaluated, it is necessary to find the weakest path in the system. For this purpose, criticality analysis can be implemented. Various importance measures, which are based on conventional probabilities, have been developed and proposed for criticality analysis in fault tree analysis. However, not one of those importance measures can be applied for criticality analysis in FPFTA, which is based on fuzzy probability. To be fully applied in nuclear power plant probabilistic safety assessment, FPFTA needs to have its corresponding importance measure. The objective of this study is to develop an α-cut method based importance measure to evaluate and rank the importance of basic events for criticality analysis in FPFTA. To demonstrate the applicability of the proposed measure, a case study is performed and its results are then benchmarked to the results generated by the four well known importance measures in conventional fault tree analysis. The results

Determining the significance of associations between two series of discrete events : bootstrap methods /

Energy Technology Data Exchange (ETDEWEB)

Niehof, Jonathan T.; Morley, Steven K.

2012-01-01

We review and develop techniques to determine associations between series of discrete events. The bootstrap, a nonparametric statistical method, allows the determination of the significance of associations with minimal assumptions about the underlying processes. We find the key requirement for this method: one of the series must be widely spaced in time to guarantee the theoretical applicability of the bootstrap. If this condition is met, the calculated significance passes a reasonableness test. We conclude with some potential future extensions and caveats on the applicability of these methods. The techniques presented have been implemented in a Python-based software toolkit.

Supervisor Localization: A Top-Down Approach to Distributed Control of Discrete-Event Systems

International Nuclear Information System (INIS)

Cai, K.; Wonham, W. M.

2009-01-01

A purely distributed control paradigm is proposed for discrete-event systems (DES). In contrast to control by one or more external supervisors, distributed control aims to design built-in strategies for individual agents. First a distributed optimal nonblocking control problem is formulated. To solve it, a top-down localization procedure is developed which systematically decomposes an external supervisor into local controllers while preserving optimality and nonblockingness. An efficient localization algorithm is provided to carry out the computation, and an automated guided vehicles (AGV) example presented for illustration. Finally, the 'easiest' and 'hardest' boundary cases of localization are discussed.

Discrete event dynamic system (DES)-based modeling for dynamic material flow in the pyroprocess

International Nuclear Information System (INIS)

Lee, Hyo Jik; Kim, Kiho; Kim, Ho Dong; Lee, Han Soo

2011-01-01

A modeling and simulation methodology was proposed in order to implement the dynamic material flow of the pyroprocess. Since the static mass balance provides the limited information on the material flow, it is hard to predict dynamic behavior according to event. Therefore, a discrete event system (DES)-based model named, PyroFlow, was developed at the Korea Atomic Energy Research Institute (KAERI). PyroFlow is able to calculate dynamic mass balance and also show various dynamic operational results in real time. By using PyroFlow, it is easy to rapidly predict unforeseeable results, such as throughput in unit process, accumulated product in buffer and operation status. As preliminary simulations, bottleneck analyses in the pyroprocess were carried out and consequently it was presented that operation strategy had influence on the productivity of the pyroprocess.

Fuzzy Neuroidal Nets and Recurrent Fuzzy Computations

Czech Academy of Sciences Publication Activity Database

Wiedermann, Jiří

2001-01-01

Roč. 11, č. 6 (2001), s. 675-686 ISSN 1210-0552. [SOFSEM 2001 Workshop on Soft Computing. Piešťany, 29.11.2001-30.11.2001] R&D Projects: GA ČR GA201/00/1489; GA AV ČR KSK1019101 Institutional research plan: AV0Z1030915 Keywords : fuzzy computing * fuzzy neural nets * fuzzy Turing machines * non-uniform computational complexity Subject RIV: BA - General Mathematics

Power consumption analysis of pump station control systems based on fuzzy controllers with discrete terms in iThink software

Science.gov (United States)

Muravyova, E. A.; Bondarev, A. V.; Sharipov, M. I.; Galiaskarova, G. R.; Kubryak, A. I.

2018-03-01

In this article, power consumption of pumping station control systems is discussed. To study the issue, two simulation models of oil level control in the iThink software have been developed, using a frequency converter only and using a frequency converter and a fuzzy controller. A simulation of the oil-level control was carried out in a graphic form, and plots of pumps power consumption were obtained. Based on the initial and obtained data, the efficiency of the considered control systems has been compared, and also the power consumption of the systems was shown graphically using a frequency converter only and using a frequency converter and a fuzzy controller. The models analysis has shown that it is more economical and safe to use a control circuit with a frequency converter and a fuzzy controller.

Can discrete event simulation be of use in modelling major depression?

Science.gov (United States)

Le Lay, Agathe; Despiegel, Nicolas; François, Clément; Duru, Gérard

2006-12-05

Depression is among the major contributors to worldwide disease burden and adequate modelling requires a framework designed to depict real world disease progression as well as its economic implications as closely as possible. In light of the specific characteristics associated with depression (multiple episodes at varying intervals, impact of disease history on course of illness, sociodemographic factors), our aim was to clarify to what extent "Discrete Event Simulation" (DES) models provide methodological benefits in depicting disease evolution. We conducted a comprehensive review of published Markov models in depression and identified potential limits to their methodology. A model based on DES principles was developed to investigate the benefits and drawbacks of this simulation method compared with Markov modelling techniques. The major drawback to Markov models is that they may not be suitable to tracking patients' disease history properly, unless the analyst defines multiple health states, which may lead to intractable situations. They are also too rigid to take into consideration multiple patient-specific sociodemographic characteristics in a single model. To do so would also require defining multiple health states which would render the analysis entirely too complex. We show that DES resolve these weaknesses and that its flexibility allow patients with differing attributes to move from one event to another in sequential order while simultaneously taking into account important risk factors such as age, gender, disease history and patients attitude towards treatment, together with any disease-related events (adverse events, suicide attempt etc.). DES modelling appears to be an accurate, flexible and comprehensive means of depicting disease progression compared with conventional simulation methodologies. Its use in analysing recurrent and chronic diseases appears particularly useful compared with Markov processes.

Continuous and discreet methods in the aggregation and des fuzzy stages of a diffuse controller of neutron power

International Nuclear Information System (INIS)

Najera H, M.C.; Benitez R, J.S.

2003-01-01

The results of a comparative study are presented of: to) A denominated diffuse controller 'exact', designed by means of an innovative method that determines analytically so much the group of exit resultant in the aggregation stage like the de fuzzy process, and b) a diffuse controller denominated 'discreet' based on the discretization of the variable of having left as much for the aggregation as for the de fuzzy. These stages incorporated to the control algorithms whose objective is the ascent and regulation of the neutron power, carrying out an analysis of its performance. (Author)

Neuro-fuzzy system modeling based on automatic fuzzy clustering

Institute of Scientific and Technical Information of China (English)

Yuangang TANG; Fuchun SUN; Zengqi SUN

2005-01-01

A neuro-fuzzy system model based on automatic fuzzy clustering is proposed.A hybrid model identification algorithm is also developed to decide the model structure and model parameters.The algorithm mainly includes three parts:1) Automatic fuzzy C-means (AFCM),which is applied to generate fuzzy rules automatically,and then fix on the size of the neuro-fuzzy network,by which the complexity of system design is reducesd greatly at the price of the fitting capability;2) Recursive least square estimation (RLSE).It is used to update the parameters of Takagi-Sugeno model,which is employed to describe the behavior of the system;3) Gradient descent algorithm is also proposed for the fuzzy values according to the back propagation algorithm of neural network.Finally,modeling the dynamical equation of the two-link manipulator with the proposed approach is illustrated to validate the feasibility of the method.

Combinational Reasoning of Quantitative Fuzzy Topological Relations for Simple Fuzzy Regions

Science.gov (United States)

Liu, Bo; Li, Dajun; Xia, Yuanping; Ruan, Jian; Xu, Lili; Wu, Huanyi

2015-01-01

In recent years, formalization and reasoning of topological relations have become a hot topic as a means to generate knowledge about the relations between spatial objects at the conceptual and geometrical levels. These mechanisms have been widely used in spatial data query, spatial data mining, evaluation of equivalence and similarity in a spatial scene, as well as for consistency assessment of the topological relations of multi-resolution spatial databases. The concept of computational fuzzy topological space is applied to simple fuzzy regions to efficiently and more accurately solve fuzzy topological relations. Thus, extending the existing research and improving upon the previous work, this paper presents a new method to describe fuzzy topological relations between simple spatial regions in Geographic Information Sciences (GIS) and Artificial Intelligence (AI). Firstly, we propose a new definition for simple fuzzy line segments and simple fuzzy regions based on the computational fuzzy topology. And then, based on the new definitions, we also propose a new combinational reasoning method to compute the topological relations between simple fuzzy regions, moreover, this study has discovered that there are (1) 23 different topological relations between a simple crisp region and a simple fuzzy region; (2) 152 different topological relations between two simple fuzzy regions. In the end, we have discussed some examples to demonstrate the validity of the new method, through comparisons with existing fuzzy models, we showed that the proposed method can compute more than the existing models, as it is more expressive than the existing fuzzy models. PMID:25775452

Discrete Event Simulation of Patient Admissions to a Neurovascular Unit

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S. Hahn-Goldberg

2014-01-01

Full Text Available Evidence exists that clinical outcomes improve for stroke patients admitted to specialized Stroke Units. The Toronto Western Hospital created a Neurovascular Unit (NVU using beds from general internal medicine, Neurology and Neurosurgery to care for patients with stroke and acute neurovascular conditions. Using patient-level data for NVU-eligible patients, a discrete event simulation was created to study changes in patient flow and length of stay pre- and post-NVU implementation. Varying patient volumes and resources were tested to determine the ideal number of beds under various conditions. In the first year of operation, the NVU admitted 507 patients, over 66% of NVU-eligible patient volumes. With the introduction of the NVU, length of stay decreased by around 8%. Scenario testing showed that the current level of 20 beds is sufficient for accommodating the current demand and would continue to be sufficient with an increase in demand of up to 20%.

FUZZY RINGS AND ITS PROPERTIES

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Karyati Karyati

2017-01-01

  One of algebraic structure that involves a binary operation is a group that is defined  an un empty set (classical with an associative binary operation, it has identity elements and each element has an inverse. In the structure of the group known as the term subgroup, normal subgroup, subgroup and factor group homomorphism and its properties. Classical algebraic structure is developed to algebraic structure fuzzy by the researchers as an example semi group fuzzy and fuzzy group after fuzzy sets is introduced by L. A. Zadeh at 1965. It is inspired of writing about semi group fuzzy and group of fuzzy, a research on the algebraic structure of the ring is held with reviewing ring fuzzy, ideal ring fuzzy, homomorphism ring fuzzy and quotient ring fuzzy with its properties. The results of this study are obtained fuzzy properties of the ring, ring ideal properties fuzzy, properties of fuzzy ring homomorphism and properties of fuzzy quotient ring by utilizing a subset of a subset level  and strong level  as well as image and pre-image homomorphism fuzzy ring.   Keywords: fuzzy ring, subset level, homomorphism fuzzy ring, fuzzy quotient ring

On fuzzy quasi continuity and an application of fuzzy set theory

CERN Document Server

Mahmoud, R A

2003-01-01

Where as classical topology has been developed closely connected with classical analysis describing topological phenomena in analysis, fuzzy topology with its important application in quantum gravity indicated by Witten and Elnaschie, has only been introduced as an analogue of the classical topology. The development of fuzzy topology without close relations to analytical problems did not give the possibility of testing successfully the applicability of the new notions and results. Till now this situation did not change, essentially. Although, many types of fuzzy sets and fuzzy functions having the quasi-property in both of weak and strong than openness and continuity, respectively, have been studied in detail. Many properties on fuzzy topological spaces such as compactness are discussed via fuzzy notion. While others are far from being completely devoted in its foundation. So, this paper is devoted to present a new class of fuzzy quasi-continuous functions via fuzzy compactness has been defined. Some characte...

Improvement of Fuzzy Image Contrast Enhancement Using Simulated Ergodic Fuzzy Markov Chains

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Behrouz Fathi-Vajargah

2014-01-01

Full Text Available This paper presents a novel fuzzy enhancement technique using simulated ergodic fuzzy Markov chains for low contrast brain magnetic resonance imaging (MRI. The fuzzy image contrast enhancement is proposed by weighted fuzzy expected value. The membership values are then modified to enhance the image using ergodic fuzzy Markov chains. The qualitative performance of the proposed method is compared to another method in which ergodic fuzzy Markov chains are not considered. The proposed method produces better quality image.

Fuzzy control. Fundamentals, stability and design of fuzzy controllers

Energy Technology Data Exchange (ETDEWEB)

Michels, K. [Fichtner GmbH und Co. KG, Stuttgart (Germany); Klawonn, F. [Fachhochschule Braunschweig/Wolfenbuettel (Germany). Fachbereich Informatik; Kruse, R. [Magdeburg Univ. (Germany). Fakultaet Informatik, Abt. Wiss.- und Sprachverarbeitung; Nuernberger, A. (eds.) [California Univ., Berkeley, CA (United States). Computer Science Division

2006-07-01

The book provides a critical discussion of fuzzy controllers from the perspective of classical control theory. Special emphases are placed on topics that are of importance for industrial applications, like (self-) tuning of fuzzy controllers, optimisation and stability analysis. The book is written as a textbook for graduate students as well as a comprehensive reference book about fuzzy control for researchers and application engineers. Starting with a detailed introduction to fuzzy systems and control theory the reader is guided to up-to-date research results. (orig.)

Discrete-event system simulation on small and medium enterprises productivity improvement

Science.gov (United States)

Sulistio, J.; Hidayah, N. A.

2017-12-01

Small and medium industries in Indonesia is currently developing. The problem faced by SMEs is the difficulty of meeting growing demand coming into the company. Therefore, SME need an analysis and evaluation on its production process in order to meet all orders. The purpose of this research is to increase the productivity of SMEs production floor by applying discrete-event system simulation. This method preferred because it can solve complex problems die to the dynamic and stochastic nature of the system. To increase the credibility of the simulation, model validated by cooperating the average of two trials, two trials of variance and chi square test. Afterwards, Benferroni method applied to development several alternatives. The article concludes that, the productivity of SMEs production floor increased up to 50% by adding the capacity of dyeing and drying machines.

Introduction to fuzzy systems

CERN Document Server

Chen, Guanrong

2005-01-01

Introduction to Fuzzy Systems provides students with a self-contained introduction that requires no preliminary knowledge of fuzzy mathematics and fuzzy control systems theory. Simplified and readily accessible, it encourages both classroom and self-directed learners to build a solid foundation in fuzzy systems. After introducing the subject, the authors move directly into presenting real-world applications of fuzzy logic, revealing its practical flavor. This practicality is then followed by basic fuzzy systems theory. The book also offers a tutorial on fuzzy control theory, based mainly on th

Wavelet transform with fuzzy tuning based indirect field oriented speed control of three-phase induction motor drive

DEFF Research Database (Denmark)

Sanjeevikumar, P.; Daya, J.L. Febin; Wheeler, Patrick

2015-01-01

by the proposed controller for an improved transient and steady state performances. The discrete wavelet transform has been used to decompose the error speed into different frequency components and the fuzzy logic is used to generate the scaling gains of the wavelet controller. The complete model of the proposed...

Assessment of Seismic Damage on The Exist Buildings Using Fuzzy Logic

Science.gov (United States)

Pınar, USTA; Nihat, MOROVA; EVCİ, Ahmet; ERGÜN, Serap

2018-01-01

Earthquake as a natural disaster could damage the lives of many people and buildings all over the world. These is micvulnerability of the buildings needs to be evaluated. Accurate evaluation of damage sustained by buildings during natural disaster events is critical to determine the buildings safety and their suitability for future occupancy. The earthquake is one of the disasters that structures face the most. There fore, there is a need to evaluate seismic damage and vulnerability of the buildings to protect them. These days fuzzy systems have been widely used in different fields of science because of its simpli city and efficiency. Fuzzy logic provides a suitable framework for reasoning, deduction, and decision making in fuzzy conditions. In this paper, studies on earthquake hazard evaluation of buildings by fuzzy logic modeling concepts in the literature have been investigated and evaluated, as a whole.

Stability analysis of polynomial fuzzy models via polynomial fuzzy Lyapunov functions

OpenAIRE

Bernal Reza, Miguel Ángel; Sala, Antonio; JAADARI, ABDELHAFIDH; Guerra, Thierry-Marie

2011-01-01

In this paper, the stability of continuous-time polynomial fuzzy models by means of a polynomial generalization of fuzzy Lyapunov functions is studied. Fuzzy Lyapunov functions have been fruitfully used in the literature for local analysis of Takagi-Sugeno models, a particular class of the polynomial fuzzy ones. Based on a recent Taylor-series approach which allows a polynomial fuzzy model to exactly represent a nonlinear model in a compact set of the state space, it is shown that a refinemen...

Fuzzy logic control of water level in advanced boiling water reactor

International Nuclear Information System (INIS)

Lin, Chaung; Lee, Chi-Szu; Raghavan, R.; Fahrner, D.M.

1995-01-01

The feedwater control system in the Advanced Boiling Water Reactor (ABWR) is more challenging to design compared to other control systems in the plant, due to the possible change in level from void collapses and swells during transient events. A basic fuzzy logic controller is developed using a simplified ABWR mathematical model to demonstrate and compare the performance of this controller with a simplified conventional controller. To reduce the design effort, methods are developed to automatically tune the scaling factors and control rules. As a first step in developing the fuzzy controller, a fuzzy controller with a limited number of rules is developed to respond to normal plant transients such as setpoint changes of plant parameters and load demand changes. Various simulations for setpoint and load demand changes of plant performances were conducted to evaluate the modeled fuzzy logic design against the simplified ABWR model control system. The simulation results show that the performance of the fuzzy logic controller is comparable to that of the Proportional-Integral (PI) controller, However, the fuzzy logic controller produced shorter settling time for step setpoint changes compared to the simplified conventional controller

DROpS: an object of learning in computer simulation of discrete events

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Hugo Alves Silva Ribeiro

2015-09-01

Full Text Available This work presents the “Realistic Dynamics Of Simulated Operations” (DROpS, the name given to the dynamics using the “dropper” device as an object of teaching and learning. The objective is to present alternatives for professors teaching content related to simulation of discrete events to graduate students in production engineering. The aim is to enable students to develop skills related to data collection, modeling, statistical analysis, and interpretation of results. This dynamic has been developed and applied to the students by placing them in a situation analogous to a real industry, where various concepts related to computer simulation were discussed, allowing the students to put these concepts into practice in an interactive manner, thus facilitating learning

Can discrete event simulation be of use in modelling major depression?

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François Clément

2006-12-01

Full Text Available Abstract Background Depression is among the major contributors to worldwide disease burden and adequate modelling requires a framework designed to depict real world disease progression as well as its economic implications as closely as possible. Objectives In light of the specific characteristics associated with depression (multiple episodes at varying intervals, impact of disease history on course of illness, sociodemographic factors, our aim was to clarify to what extent "Discrete Event Simulation" (DES models provide methodological benefits in depicting disease evolution. Methods We conducted a comprehensive review of published Markov models in depression and identified potential limits to their methodology. A model based on DES principles was developed to investigate the benefits and drawbacks of this simulation method compared with Markov modelling techniques. Results The major drawback to Markov models is that they may not be suitable to tracking patients' disease history properly, unless the analyst defines multiple health states, which may lead to intractable situations. They are also too rigid to take into consideration multiple patient-specific sociodemographic characteristics in a single model. To do so would also require defining multiple health states which would render the analysis entirely too complex. We show that DES resolve these weaknesses and that its flexibility allow patients with differing attributes to move from one event to another in sequential order while simultaneously taking into account important risk factors such as age, gender, disease history and patients attitude towards treatment, together with any disease-related events (adverse events, suicide attempt etc.. Conclusion DES modelling appears to be an accurate, flexible and comprehensive means of depicting disease progression compared with conventional simulation methodologies. Its use in analysing recurrent and chronic diseases appears particularly useful

Relational Demonic Fuzzy Refinement

OpenAIRE

Tchier, Fairouz

2014-01-01

We use relational algebra to define a refinement fuzzy order called demonic fuzzy refinement and also the associated fuzzy operators which are fuzzy demonic join $({\\bigsqcup }_{\\mathrm{\\text{f}}\\mathrm{\\text{u}}\\mathrm{\\text{z}}})$ , fuzzy demonic meet $({\\sqcap }_{\\mathrm{\\text{f}}\\mathrm{\\text{u}}\\mathrm{\\text{z}}})$ , and fuzzy demonic composition $({\\square }_{\\mathrm{\\text{f}}\\mathrm{\\text{u}}\\mathrm{\\text{z}}})$ . Our definitions and properties are illustrated by some examples using ma...

Core discrete event simulation model for the evaluation of health care technologies in major depressive disorder.

Science.gov (United States)

Vataire, Anne-Lise; Aballéa, Samuel; Antonanzas, Fernando; Roijen, Leona Hakkaart-van; Lam, Raymond W; McCrone, Paul; Persson, Ulf; Toumi, Mondher

2014-03-01

A review of existing economic models in major depressive disorder (MDD) highlighted the need for models with longer time horizons that also account for heterogeneity in treatment pathways between patients. A core discrete event simulation model was developed to estimate health and cost outcomes associated with alternative treatment strategies. This model simulated short- and long-term clinical events (partial response, remission, relapse, recovery, and recurrence), adverse events, and treatment changes (titration, switch, addition, and discontinuation) over up to 5 years. Several treatment pathways were defined on the basis of fictitious antidepressants with three levels of efficacy, tolerability, and price (low, medium, and high) from first line to third line. The model was populated with input data from the literature for the UK setting. Model outputs include time in different health states, quality-adjusted life-years (QALYs), and costs from National Health Service and societal perspectives. The codes are open source. Predicted costs and QALYs from this model are within the range of results from previous economic evaluations. The largest cost components from the payer perspective were physician visits and hospitalizations. Key parameters driving the predicted costs and QALYs were utility values, effectiveness, and frequency of physician visits. Differences in QALYs and costs between two strategies with different effectiveness increased approximately twofold when the time horizon increased from 1 to 5 years. The discrete event simulation model can provide a more comprehensive evaluation of different therapeutic options in MDD, compared with existing Markov models, and can be used to compare a wide range of health care technologies in various groups of patients with MDD. Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Analysis of manufacturing based on object oriented discrete event simulation

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Eirik Borgen

1990-01-01

Full Text Available This paper describes SIMMEK, a computer-based tool for performing analysis of manufacturing systems, developed at the Production Engineering Laboratory, NTH-SINTEF. Its main use will be in analysis of job shop type of manufacturing. But certain facilities make it suitable for FMS as well as a production line manufacturing. This type of simulation is very useful in analysis of any types of changes that occur in a manufacturing system. These changes may be investments in new machines or equipment, a change in layout, a change in product mix, use of late shifts, etc. The effects these changes have on for instance the throughput, the amount of VIP, the costs or the net profit, can be analysed. And this can be done before the changes are made, and without disturbing the real system. Simulation takes into consideration, unlike other tools for analysis of manufacturing systems, uncertainty in arrival rates, process and operation times, and machine availability. It also shows the interaction effects a job which is late in one machine, has on the remaining machines in its route through the layout. It is these effects that cause every production plan not to be fulfilled completely. SIMMEK is based on discrete event simulation, and the modeling environment is object oriented. The object oriented models are transformed by an object linker into data structures executable by the simulation kernel. The processes of the entity objects, i.e. the products, are broken down to events and put into an event list. The user friendly graphical modeling environment makes it possible for end users to build models in a quick and reliable way, using terms from manufacturing. Various tests and a check of model logic are helpful functions when testing validity of the models. Integration with software packages, with business graphics and statistical functions, is convenient in the result presentation phase.

Using Discrete Event Simulation for Programming Model Exploration at Extreme-Scale: Macroscale Components for the Structural Simulation Toolkit (SST).

Energy Technology Data Exchange (ETDEWEB)

Wilke, Jeremiah J [Sandia National Laboratories (SNL-CA), Livermore, CA (United States); Kenny, Joseph P. [Sandia National Laboratories (SNL-CA), Livermore, CA (United States)

2015-02-01

Discrete event simulation provides a powerful mechanism for designing and testing new extreme- scale programming models for high-performance computing. Rather than debug, run, and wait for results on an actual system, design can first iterate through a simulator. This is particularly useful when test beds cannot be used, i.e. to explore hardware or scales that do not yet exist or are inaccessible. Here we detail the macroscale components of the structural simulation toolkit (SST). Instead of depending on trace replay or state machines, the simulator is architected to execute real code on real software stacks. Our particular user-space threading framework allows massive scales to be simulated even on small clusters. The link between the discrete event core and the threading framework allows interesting performance metrics like call graphs to be collected from a simulated run. Performance analysis via simulation can thus become an important phase in extreme-scale programming model and runtime system design via the SST macroscale components.

Intuitionistic supra fuzzy topological spaces

International Nuclear Information System (INIS)

Abbas, S.E.

2004-01-01

In this paper, We introduce an intuitionistic supra fuzzy closure space and investigate the relationship between intuitionistic supra fuzzy topological spaces and intuitionistic supra fuzzy closure spaces. Moreover, we can obtain intuitionistic supra fuzzy topological space induced by an intuitionistic fuzzy bitopological space. We study the relationship between intuitionistic supra fuzzy closure space and the intuitionistic supra fuzzy topological space induced by an intuitionistic fuzzy bitopological space

Intelligent control-I: review of fuzzy logic and fuzzy set theory

International Nuclear Information System (INIS)

Nagrial, M.H.

2004-01-01

In the past decade or so, fuzzy systems have supplanted conventional technologies in many engineering systems, in particular in control systems and pattern recognition. Fuzzy logic has found applications in a variety of consumer products e.g. washing machines, camcorders, digital cameras, air conditioners, subway trains, cement kilns and many others. The fuzzy technology is also being applied in information technology, where it provides decision-support and expert systems with powerful reasoning capabilities. Fuzzy sets, introduced by Zadeh in 1965 as a mathematical way to represent vagueness in linguistics, can be considered a generalisation of classical set theory. Fuzziness is often confused with probability. This lecture will introduce the principal concepts and mathematical notions of fuzzy set theory. (author)

Hesitant fuzzy sets theory

CERN Document Server

Xu, Zeshui

2014-01-01

This book provides the readers with a thorough and systematic introduction to hesitant fuzzy theory. It presents the most recent research results and advanced methods in the field. These includes: hesitant fuzzy aggregation techniques, hesitant fuzzy preference relations, hesitant fuzzy measures, hesitant fuzzy clustering algorithms and hesitant fuzzy multi-attribute decision making methods. Since its introduction by Torra and Narukawa in 2009, hesitant fuzzy sets have become more and more popular and have been used for a wide range of applications, from decision-making problems to cluster analysis, from medical diagnosis to personnel appraisal and information retrieval. This book offers a comprehensive report on the state-of-the-art in hesitant fuzzy sets theory and applications, aiming at becoming a reference guide for both researchers and practitioners in the area of fuzzy mathematics and other applied research fields (e.g. operations research, information science, management science and engineering) chara...

Fuzzy logic in management

CERN Document Server

Carlsson, Christer; Fullér, Robert

2004-01-01

Fuzzy Logic in Management demonstrates that difficult problems and changes in the management environment can be more easily handled by bringing fuzzy logic into the practice of management. This explicit theme is developed through the book as follows: Chapter 1, "Management and Intelligent Support Technologies", is a short survey of management leadership and what can be gained from support technologies. Chapter 2, "Fuzzy Sets and Fuzzy Logic", provides a short introduction to fuzzy sets, fuzzy relations, the extension principle, fuzzy implications and linguistic variables. Chapter 3, "Group Decision Support Systems", deals with group decision making, and discusses methods for supporting the consensus reaching processes. Chapter 4, "Fuzzy Real Options for Strategic Planning", summarizes research where the fuzzy real options theory was implemented as a series of models. These models were thoroughly tested on a number of real life investments, and validated in 2001. Chapter 5, "Soft Computing Methods for Reducing...

Discrete Event Supervisory Control Applied to Propulsion Systems

Science.gov (United States)

Litt, Jonathan S.; Shah, Neerav

2005-01-01

The theory of discrete event supervisory (DES) control was applied to the optimal control of a twin-engine aircraft propulsion system and demonstrated in a simulation. The supervisory control, which is implemented as a finite-state automaton, oversees the behavior of a system and manages it in such a way that it maximizes a performance criterion, similar to a traditional optimal control problem. DES controllers can be nested such that a high-level controller supervises multiple lower level controllers. This structure can be expanded to control huge, complex systems, providing optimal performance and increasing autonomy with each additional level. The DES control strategy for propulsion systems was validated using a distributed testbed consisting of multiple computers--each representing a module of the overall propulsion system--to simulate real-time hardware-in-the-loop testing. In the first experiment, DES control was applied to the operation of a nonlinear simulation of a turbofan engine (running in closed loop using its own feedback controller) to minimize engine structural damage caused by a combination of thermal and structural loads. This enables increased on-wing time for the engine through better management of the engine-component life usage. Thus, the engine-level DES acts as a life-extending controller through its interaction with and manipulation of the engine s operation.

The World of Combinatorial Fuzzy Problems and the Efficiency of Fuzzy Approximation Algorithms

OpenAIRE

Yamakami, Tomoyuki

2015-01-01

We re-examine a practical aspect of combinatorial fuzzy problems of various types, including search, counting, optimization, and decision problems. We are focused only on those fuzzy problems that take series of fuzzy input objects and produce fuzzy values. To solve such problems efficiently, we design fast fuzzy algorithms, which are modeled by polynomial-time deterministic fuzzy Turing machines equipped with read-only auxiliary tapes and write-only output tapes and also modeled by polynomia...

Safety analysis and synthesis using fuzzy sets and evidential reasoning

International Nuclear Information System (INIS)

Wang, J.; Yang, J.B.; Sen, P.

1995-01-01

This paper presents a new methodology for safety analysis and synthesis of a complex engineering system with a structure that is capable of being decomposed into a hierarchy of levels. In this methodology, fuzzy set theory is used to describe each failure event and an evidential reasoning approach is then employed to synthesise the information thus produced to assess the safety of the whole system. Three basic parameters--failure likelihood, consequence severity and failure consequence probability, are used to analyse a failure event. These three parameters are described by linguistic variables which are characterised by a membership function to the defined categories. As safety can also be clearly described by linguistic variables referred to as the safety expressions, the obtained fuzzy safety score can be mapped back to the safety expressions which are characterised by membership functions over the same categories. This mapping results in the identification of the safety of each failure event in terms of the degree to which the fuzzy safety score belongs to each of the safety expressions. Such degrees represent the uncertainty in safety evaluations and can be synthesised using an evidential reasoning approach so that the safety of the whole system can be evaluated in terms of these safety expressions. Finally, a practical engineering example is presented to demonstrate the proposed safety analysis and synthesis methodology

Fuzzy risk matrix

International Nuclear Information System (INIS)

Markowski, Adam S.; Mannan, M. Sam

2008-01-01

A risk matrix is a mechanism to characterize and rank process risks that are typically identified through one or more multifunctional reviews (e.g., process hazard analysis, audits, or incident investigation). This paper describes a procedure for developing a fuzzy risk matrix that may be used for emerging fuzzy logic applications in different safety analyses (e.g., LOPA). The fuzzification of frequency and severity of the consequences of the incident scenario are described which are basic inputs for fuzzy risk matrix. Subsequently using different design of risk matrix, fuzzy rules are established enabling the development of fuzzy risk matrices. Three types of fuzzy risk matrix have been developed (low-cost, standard, and high-cost), and using a distillation column case study, the effect of the design on final defuzzified risk index is demonstrated

Multivariate spatial condition mapping using subtractive fuzzy cluster means.

Science.gov (United States)

Sabit, Hakilo; Al-Anbuky, Adnan

2014-10-13

Wireless sensor networks are usually deployed for monitoring given physical phenomena taking place in a specific space and over a specific duration of time. The spatio-temporal distribution of these phenomena often correlates to certain physical events. To appropriately characterise these events-phenomena relationships over a given space for a given time frame, we require continuous monitoring of the conditions. WSNs are perfectly suited for these tasks, due to their inherent robustness. This paper presents a subtractive fuzzy cluster means algorithm and its application in data stream mining for wireless sensor systems over a cloud-computing-like architecture, which we call sensor cloud data stream mining. Benchmarking on standard mining algorithms, the k-means and the FCM algorithms, we have demonstrated that the subtractive fuzzy cluster means model can perform high quality distributed data stream mining tasks comparable to centralised data stream mining.

Safety analyses of potential exposure in medical irradiation plants by Fuzzy Fault Tree

International Nuclear Information System (INIS)

Casamirra, Maddalena; Castiglia, Francesco; Giardina, Mariarosa; Tomarchio, Elio

2008-01-01

The results of Fuzzy Fault Tree (FFT) analyses of various accidental scenarios, which involve the operators in potential exposures inside an High Dose Rate (HDR) remote after-loading systems for use in brachytherapy, are reported. To carry out fault tree analyses by means of fuzzy probabilities, the TREEZZY2 computer code is used. Moreover, the HEART (Human Error Assessment and Reduction Technique) model, properly modified on the basis of the fuzzy approach, has been employed to assess the impact of performances haping and error-promoting factors in the context of the accidental events. The assessment of potential dose values for some identified accidental scenarios allows to consider, for a particular event, a fuzzy uncertainty range in potential dose estimate. The availability of lower and upper limits allows evaluating the possibility of optimization of the installation from the point of view of radiation protection. The adequacy of the training and information program for staff and patients (and their family members) and the effectiveness of behavioural rules and safety procedures were tested. Some recommendations on procedures and equipment to reduce the risk of radiological exposure are also provided. (author)

Evaluation of a proposed optimization method for discrete-event simulation models

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Alexandre Ferreira de Pinho

2012-12-01

Full Text Available Optimization methods combined with computer-based simulation have been utilized in a wide range of manufacturing applications. However, in terms of current technology, these methods exhibit low performance levels which are only able to manipulate a single decision variable at a time. Thus, the objective of this article is to evaluate a proposed optimization method for discrete-event simulation models based on genetic algorithms which exhibits more efficiency in relation to computational time when compared to software packages on the market. It should be emphasized that the variable's response quality will not be altered; that is, the proposed method will maintain the solutions' effectiveness. Thus, the study draws a comparison between the proposed method and that of a simulation instrument already available on the market and has been examined in academic literature. Conclusions are presented, confirming the proposed optimization method's efficiency.

Global sensitivity analysis for fuzzy inputs based on the decomposition of fuzzy output entropy

Science.gov (United States)

Shi, Yan; Lu, Zhenzhou; Zhou, Yicheng

2018-06-01

To analyse the component of fuzzy output entropy, a decomposition method of fuzzy output entropy is first presented. After the decomposition of fuzzy output entropy, the total fuzzy output entropy can be expressed as the sum of the component fuzzy entropy contributed by fuzzy inputs. Based on the decomposition of fuzzy output entropy, a new global sensitivity analysis model is established for measuring the effects of uncertainties of fuzzy inputs on the output. The global sensitivity analysis model can not only tell the importance of fuzzy inputs but also simultaneously reflect the structural composition of the response function to a certain degree. Several examples illustrate the validity of the proposed global sensitivity analysis, which is a significant reference in engineering design and optimization of structural systems.

Intuitionistic Fuzzy Subbialgebras and Duality

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Wenjuan Chen

2014-01-01

Full Text Available We investigate connections between bialgebras and Atanassov’s intuitionistic fuzzy sets. Firstly we define an intuitionistic fuzzy subbialgebra of a bialgebra with an intuitionistic fuzzy subalgebra structure and also with an intuitionistic fuzzy subcoalgebra structure. Secondly we investigate the related properties of intuitionistic fuzzy subbialgebras. Finally we prove that the dual of an intuitionistic fuzzy strong subbialgebra is an intuitionistic fuzzy strong subbialgebra.

Evolutionary Computation and Its Applications in Neural and Fuzzy Systems

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Biaobiao Zhang

2011-01-01

Full Text Available Neural networks and fuzzy systems are two soft-computing paradigms for system modelling. Adapting a neural or fuzzy system requires to solve two optimization problems: structural optimization and parametric optimization. Structural optimization is a discrete optimization problem which is very hard to solve using conventional optimization techniques. Parametric optimization can be solved using conventional optimization techniques, but the solution may be easily trapped at a bad local optimum. Evolutionary computation is a general-purpose stochastic global optimization approach under the universally accepted neo-Darwinian paradigm, which is a combination of the classical Darwinian evolutionary theory, the selectionism of Weismann, and the genetics of Mendel. Evolutionary algorithms are a major approach to adaptation and optimization. In this paper, we first introduce evolutionary algorithms with emphasis on genetic algorithms and evolutionary strategies. Other evolutionary algorithms such as genetic programming, evolutionary programming, particle swarm optimization, immune algorithm, and ant colony optimization are also described. Some topics pertaining to evolutionary algorithms are also discussed, and a comparison between evolutionary algorithms and simulated annealing is made. Finally, the application of EAs to the learning of neural networks as well as to the structural and parametric adaptations of fuzzy systems is also detailed.

Fuzzy topological digital space and digital fuzzy spline of electroencephalography during epileptic seizures

Science.gov (United States)

Shah, Mazlina Muzafar; Wahab, Abdul Fatah

2017-08-01

Epilepsy disease occurs because of there is a temporary electrical disturbance in a group of brain cells (nurons). The recording of electrical signals come from the human brain which can be collected from the scalp of the head is called Electroencephalography (EEG). EEG then considered in digital format and in fuzzy form makes it a fuzzy digital space data form. The purpose of research is to identify the area (curve and surface) in fuzzy digital space affected by inside epilepsy seizure in epileptic patient's brain. The main focus for this research is to generalize fuzzy topological digital space, definition and basic operation also the properties by using digital fuzzy set and the operations. By using fuzzy digital space, the theory of digital fuzzy spline can be introduced to replace grid data that has been use previously to get better result. As a result, the flat of EEG can be fuzzy topological digital space and this type of data can be use to interpolate the digital fuzzy spline.

Intuitionistic Fuzzy Time Series Forecasting Model Based on Intuitionistic Fuzzy Reasoning

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Ya’nan Wang

2016-01-01

Full Text Available Fuzzy sets theory cannot describe the data comprehensively, which has greatly limited the objectivity of fuzzy time series in uncertain data forecasting. In this regard, an intuitionistic fuzzy time series forecasting model is built. In the new model, a fuzzy clustering algorithm is used to divide the universe of discourse into unequal intervals, and a more objective technique for ascertaining the membership function and nonmembership function of the intuitionistic fuzzy set is proposed. On these bases, forecast rules based on intuitionistic fuzzy approximate reasoning are established. At last, contrast experiments on the enrollments of the University of Alabama and the Taiwan Stock Exchange Capitalization Weighted Stock Index are carried out. The results show that the new model has a clear advantage of improving the forecast accuracy.

Fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and the probabilities of trends of fuzzy logical relationships.

Science.gov (United States)

Chen, Shyi-Ming; Chen, Shen-Wen

2015-03-01

In this paper, we present a new method for fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and the probabilities of trends of fuzzy-trend logical relationships. Firstly, the proposed method fuzzifies the historical training data of the main factor and the secondary factor into fuzzy sets, respectively, to form two-factors second-order fuzzy logical relationships. Then, it groups the obtained two-factors second-order fuzzy logical relationships into two-factors second-order fuzzy-trend logical relationship groups. Then, it calculates the probability of the "down-trend," the probability of the "equal-trend" and the probability of the "up-trend" of the two-factors second-order fuzzy-trend logical relationships in each two-factors second-order fuzzy-trend logical relationship group, respectively. Finally, it performs the forecasting based on the probabilities of the down-trend, the equal-trend, and the up-trend of the two-factors second-order fuzzy-trend logical relationships in each two-factors second-order fuzzy-trend logical relationship group. We also apply the proposed method to forecast the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) and the NTD/USD exchange rates. The experimental results show that the proposed method outperforms the existing methods.

A fuzzy intelligent system for land consolidation - a case study in Shunde, China

Science.gov (United States)

Wang, J.; Ge, A.; Hu, Y.; Li, C.; Wang, L.

2015-04-01

Traditionally, potential evaluation methods for farmland consolidation have depended mainly on the experts' experiences, statistical computations or subjective adjustments. Some biases usually exist in the results. Thus, computer-aided technology has become essential. In this study, an intelligent evaluation system based on a fuzzy decision tree was established, and this system can deal with numerical data, discrete data and symbolic data. When the original land data are input, the level of potential of the agricultural land for development will be output by this new model. The provision of objective proof for decision making by authorities in rural management is helpful. Agricultural land data characteristically comprise large volumes, complex varieties and more indexes. In land consolidation, it is very important to construct an effective index system. We needed to select a group of indexes useful for land consolidation according to the concrete demand. In this paper, a fuzzy measure, which can describe the importance of a single feature or a group of features, is adopted to accomplish the selection of specific features. A fuzzy integral that is based on a fuzzy measure is a type of fusion tool. We obtained the optimal solution for a fuzzy measure by solving a fuzzy integral. The fuzzy integrals can be transformed to a set of linear equations. We applied the L1-norm regularization method to solve the linear equations, and we found a solution with the fewest nonzero elements for the fuzzy measure; this solution shows the contribution of corresponding features or the combinations of decisions. This algorithm provides a quick and optimal way to identify the land index system when preparing to conduct the research, such as we describe herein, on land consolidation. Shunde's "Three Old" consolidation project provides the data for this work. Our estimation system was compared with a conventional evaluation system that is still accepted by the public. Our results prove

The Skateboard Factory: a teaching case on discrete-event simulation

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Marco Aurélio de Mesquita

Full Text Available Abstract Real-life applications during the teaching process are a desirable practice in simulation education. However, access to real cases imposes some difficulty in implement such practice, especially when the classes are large. This paper presents a teaching case for a computer simulation course in a production engineering undergraduate program. The motivation for the teaching case was to provide students with a realistic manufacturing case to stimulate the learning of simulation concepts and methods in the context of industrial engineering. The case considers a virtual factory of skateboards, which operations include parts manufacturing, final assembly and storage of raw materials, work-in-process and finished products. Students should model and simulate the factory, under push and pull production strategies, using any simulation software available in the laboratory. The teaching case, applied in the last two years, contributed to motivate and consolidate the students’ learning of discrete-event simulation. It proved to be a feasible alternative to the previous practice of letting students freely choose a case for their final project, while keeping the essence of project-based learning approach.

Models for cooperative games with fuzzy relations among the agents fuzzy communication, proximity relation and fuzzy permission

CERN Document Server

Jiménez-Losada, Andrés

2017-01-01

This book offers a comprehensive introduction to cooperative game theory and a practice-oriented reference guide to new models and tools for studying bilateral fuzzy relations among several agents or players. It introduces the reader to several fuzzy models, each of which is first analyzed in the context of classical games (crisp games) and subsequently in the context of fuzzy games. Special emphasis is given to the value of Shapley, which is presented for the first time in the context of fuzzy games. Students and researchers will find here a self-contained reference guide to cooperative fuzzy games, characterized by a wealth of examples, descriptions of a wide range of possible situations, step-by-step explanations of the basic mathematical concepts involved, and easy-to-follow information on axioms and properties.

Multicriteria optimization in a fuzzy environment: The fuzzy analytic hierarchy process

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Gardašević-Filipović Milanka

2010-01-01

Full Text Available In the paper the fuzzy extension of the Analytic Hierarchy Process (AHP based on fuzzy numbers, and its application in solving a practical problem, are considered. The paper advocates the use of contradictory test to check the fuzzy user preferences during fuzzy AHP decision-making process. We also propose consistency check and deriving priorities from inconsistent fuzzy judgment matrices to be included in the process, in order to check if the fuzzy approach can be applied in the AHP for the problem considered. An aggregation of local priorities obtained at different levels into composite global priorities for the alternatives based on weighted-sum method is also discussed. The contradictory fuzzy judgment matrix is analyzed. Our theoretical consideration has been verified by an application of commercially available Super Decisions program (developed for solving multi-criteria optimization problems using AHP approach on the problem previously treated in the literature. The obtained results are compared with those from the literature. The conclusions are given and the possibilities for further work in the field are pointed out.

Connes distance function on fuzzy sphere and the connection between geometry and statistics

International Nuclear Information System (INIS)

Devi, Yendrembam Chaoba; Chakraborty, Biswajit; Prajapat, Shivraj; Mukhopadhyay, Aritra K.; Scholtz, Frederik G.

2015-01-01

An algorithm to compute Connes spectral distance, adaptable to the Hilbert-Schmidt operatorial formulation of non-commutative quantum mechanics, was developed earlier by introducing the appropriate spectral triple and used to compute infinitesimal distances in the Moyal plane, revealing a deep connection between geometry and statistics. In this paper, using the same algorithm, the Connes spectral distance has been calculated in the Hilbert-Schmidt operatorial formulation for the fuzzy sphere whose spatial coordinates satisfy the su(2) algebra. This has been computed for both the discrete and the Perelemov’s SU(2) coherent state. Here also, we get a connection between geometry and statistics which is shown by computing the infinitesimal distance between mixed states on the quantum Hilbert space of a particular fuzzy sphere, indexed by n ∈ ℤ/2

Fuzzy weakly preopen (preclosed) function in Kubiak-Sostak fuzzy topological spaces

International Nuclear Information System (INIS)

Zahran, A.M.; Abd-Allah, M. Azab.; Abd El-Rahman, Abd El-Nasser G.

2009-01-01

In this paper, we introduce and characterize fuzzy weakly preopen and fuzzy weakly preclosed functions between L-fuzzy topological spaces in Kubiak-Sostak sense and also study these functions in relation to some other types of already known functions.

On Fuzzy β-I-open sets and Fuzzy β-I-continuous functions

International Nuclear Information System (INIS)

Keskin, Aynur

2009-01-01

In this paper, first of all we obtain some properties and characterizations of fuzzy β-I-open sets. After that, we also define the notion of β-I-closed sets and obtain some properties. Lastly, we introduce the notions of fuzzy β-I-continuity with the help of fuzzy β-I-open sets to obtain decomposition of fuzzy continuity.

On Fuzzy {beta}-I-open sets and Fuzzy {beta}-I-continuous functions

Energy Technology Data Exchange (ETDEWEB)

Keskin, Aynur [Department of Mathematics, Faculty of Science and Arts, Selcuk University, Campus, 42075 Konya (Turkey)], E-mail: akeskin@selcuk.edu.tr

2009-11-15

In this paper, first of all we obtain some properties and characterizations of fuzzy {beta}-I-open sets. After that, we also define the notion of {beta}-I-closed sets and obtain some properties. Lastly, we introduce the notions of fuzzy {beta}-I-continuity with the help of fuzzy {beta}-I-open sets to obtain decomposition of fuzzy continuity.

Fuzzy stochastic damage mechanics (FSDM based on fuzzy auto-adaptive control theory

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Ya-jun Wang

2012-06-01

Full Text Available In order to fully interpret and describe damage mechanics, the origin and development of fuzzy stochastic damage mechanics were introduced based on the analysis of the harmony of damage, probability, and fuzzy membership in the interval of [0,1]. In a complete normed linear space, it was proven that a generalized damage field can be simulated through β probability distribution. Three kinds of fuzzy behaviors of damage variables were formulated and explained through analysis of the generalized uncertainty of damage variables and the establishment of a fuzzy functional expression. Corresponding fuzzy mapping distributions, namely, the half-depressed distribution, swing distribution, and combined swing distribution, which can simulate varying fuzzy evolution in diverse stochastic damage situations, were set up. Furthermore, through demonstration of the generalized probabilistic characteristics of damage variables, the cumulative distribution function and probability density function of fuzzy stochastic damage variables, which show β probability distribution, were modified according to the expansion principle. The three-dimensional fuzzy stochastic damage mechanical behaviors of the Longtan rolled-concrete dam were examined with the self-developed fuzzy stochastic damage finite element program. The statistical correlation and non-normality of random field parameters were considered comprehensively in the fuzzy stochastic damage model described in this paper. The results show that an initial damage field based on the comprehensive statistical evaluation helps to avoid many difficulties in the establishment of experiments and numerical algorithms for damage mechanics analysis.

ANALYSIS OF FUZZY QUEUES: PARAMETRIC PROGRAMMING APPROACH BASED ON RANDOMNESS - FUZZINESS CONSISTENCY PRINCIPLE

OpenAIRE

Dhruba Das; Hemanta K. Baruah

2015-01-01

In this article, based on Zadeh’s extension principle we have apply the parametric programming approach to construct the membership functions of the performance measures when the interarrival time and the service time are fuzzy numbers based on the Baruah’s Randomness- Fuzziness Consistency Principle. The Randomness-Fuzziness Consistency Principle leads to defining a normal law of fuzziness using two different laws of randomness. In this article, two fuzzy queues FM...

Discrete event simulation model of sudden cardiac death predicts high impact of preventive interventions.

Science.gov (United States)

Andreev, Victor P; Head, Trajen; Johnson, Neil; Deo, Sapna K; Daunert, Sylvia; Goldschmidt-Clermont, Pascal J

2013-01-01

Sudden Cardiac Death (SCD) is responsible for at least 180,000 deaths a year and incurs an average cost of $286 billion annually in the United States alone. Herein, we present a novel discrete event simulation model of SCD, which quantifies the chains of events associated with the formation, growth, and rupture of atheroma plaques, and the subsequent formation of clots, thrombosis and on-set of arrhythmias within a population. The predictions generated by the model are in good agreement both with results obtained from pathological examinations on the frequencies of three major types of atheroma, and with epidemiological data on the prevalence and risk of SCD. These model predictions allow for identification of interventions and importantly for the optimal time of intervention leading to high potential impact on SCD risk reduction (up to 8-fold reduction in the number of SCDs in the population) as well as the increase in life expectancy.

ANALYSIS OF FUZZY QUEUES: PARAMETRIC PROGRAMMING APPROACH BASED ON RANDOMNESS - FUZZINESS CONSISTENCY PRINCIPLE

Directory of Open Access Journals (Sweden)

Dhruba Das

2015-04-01

Full Text Available In this article, based on Zadeh’s extension principle we have apply the parametric programming approach to construct the membership functions of the performance measures when the interarrival time and the service time are fuzzy numbers based on the Baruah’s Randomness- Fuzziness Consistency Principle. The Randomness-Fuzziness Consistency Principle leads to defining a normal law of fuzziness using two different laws of randomness. In this article, two fuzzy queues FM/M/1 and M/FM/1 has been studied and constructed their membership functions of the system characteristics based on the aforesaid principle. The former represents a queue with fuzzy exponential arrivals and exponential service rate while the latter represents a queue with exponential arrival rate and fuzzy exponential service rate.

Introduction to Fuzzy Set Theory

Science.gov (United States)

Kosko, Bart

1990-01-01

An introduction to fuzzy set theory is described. Topics covered include: neural networks and fuzzy systems; the dynamical systems approach to machine intelligence; intelligent behavior as adaptive model-free estimation; fuzziness versus probability; fuzzy sets; the entropy-subsethood theorem; adaptive fuzzy systems for backing up a truck-and-trailer; product-space clustering with differential competitive learning; and adaptive fuzzy system for target tracking.

Uncertainty analysis of flexible rotors considering fuzzy parameters and fuzzy-random parameters

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Fabian Andres Lara-Molina

Full Text Available Abstract The components of flexible rotors are subjected to uncertainties. The main sources of uncertainties include the variation of mechanical properties. This contribution aims at analyzing the dynamics of flexible rotors under uncertain parameters modeled as fuzzy and fuzzy random variables. The uncertainty analysis encompasses the modeling of uncertain parameters and the numerical simulation of the corresponding flexible rotor model by using an approach based on fuzzy dynamic analysis. The numerical simulation is accomplished by mapping the fuzzy parameters of the deterministic flexible rotor model. Thereby, the flexible rotor is modeled by using both the Fuzzy Finite Element Method and the Fuzzy Stochastic Finite Element Method. Numerical simulations illustrate the methodology conveyed in terms of orbits and frequency response functions subject to uncertain parameters.

Developing a discrete event simulation model for university student shuttle buses

Science.gov (United States)

Zulkepli, Jafri; Khalid, Ruzelan; Nawawi, Mohd Kamal Mohd; Hamid, Muhammad Hafizan

2017-11-01

Providing shuttle buses for university students to attend their classes is crucial, especially when their number is large and the distances between their classes and residential halls are far. These factors, in addition to the non-optimal current bus services, typically require the students to wait longer which eventually opens a space for them to complain. To considerably reduce the waiting time, providing the optimal number of buses to transport them from location to location and the effective route schedules to fulfil the students' demand at relevant time ranges are thus important. The optimal bus number and schedules are to be determined and tested using a flexible decision platform. This paper thus models the current services of student shuttle buses in a university using a Discrete Event Simulation approach. The model can flexibly simulate whatever changes configured to the current system and report its effects to the performance measures. How the model was conceptualized and formulated for future system configurations are the main interest of this paper.

A computational approach to extinction events in chemical reaction networks with discrete state spaces.

Science.gov (United States)

Johnston, Matthew D

2017-12-01

Recent work of Johnston et al. has produced sufficient conditions on the structure of a chemical reaction network which guarantee that the corresponding discrete state space system exhibits an extinction event. The conditions consist of a series of systems of equalities and inequalities on the edges of a modified reaction network called a domination-expanded reaction network. In this paper, we present a computational implementation of these conditions written in Python and apply the program on examples drawn from the biochemical literature. We also run the program on 458 models from the European Bioinformatics Institute's BioModels Database and report our results. Copyright © 2017 Elsevier Inc. All rights reserved.

Linear matrix inequality approach for synchronization control of fuzzy cellular neural networks with mixed time delays

International Nuclear Information System (INIS)

Balasubramaniam, P.; Kalpana, M.; Rakkiyappan, R.

2012-01-01

Fuzzy cellular neural networks (FCNNs) are special kinds of cellular neural networks (CNNs). Each cell in an FCNN contains fuzzy operating abilities. The entire network is governed by cellular computing laws. The design of FCNNs is based on fuzzy local rules. In this paper, a linear matrix inequality (LMI) approach for synchronization control of FCNNs with mixed delays is investigated. Mixed delays include discrete time-varying delays and unbounded distributed delays. A dynamic control scheme is proposed to achieve the synchronization between a drive network and a response network. By constructing the Lyapunov—Krasovskii functional which contains a triple-integral term and the free-weighting matrices method an improved delay-dependent stability criterion is derived in terms of LMIs. The controller can be easily obtained by solving the derived LMIs. A numerical example and its simulations are presented to illustrate the effectiveness of the proposed method. (interdisciplinary physics and related areas of science and technology)

Statistical Methods for Fuzzy Data

CERN Document Server

Viertl, Reinhard

2011-01-01

Statistical data are not always precise numbers, or vectors, or categories. Real data are frequently what is called fuzzy. Examples where this fuzziness is obvious are quality of life data, environmental, biological, medical, sociological and economics data. Also the results of measurements can be best described by using fuzzy numbers and fuzzy vectors respectively. Statistical analysis methods have to be adapted for the analysis of fuzzy data. In this book, the foundations of the description of fuzzy data are explained, including methods on how to obtain the characterizing function of fuzzy m

Paired fuzzy sets

DEFF Research Database (Denmark)

Rodríguez, J. Tinguaro; Franco de los Ríos, Camilo; Gómez, Daniel

2015-01-01

In this paper we want to stress the relevance of paired fuzzy sets, as already proposed in previous works of the authors, as a family of fuzzy sets that offers a unifying view for different models based upon the opposition of two fuzzy sets, simply allowing the existence of different types...

QUALITY THROUGH INTEGRATION OF PRODUCTION AND SHOP FLOOR MANAGEMENT BY DISCRETE EVENT SIMULATION

Directory of Open Access Journals (Sweden)

Zoran Mirović

2007-06-01

Full Text Available With the intention to integrate strategic and tactical decision making and develop the capability of plans and schedules reconfiguration and synchronization in a very short cycle time many firms have proceeded to the adoption of ERP and Advanced Planning and Scheduling (APS technologies. The final goal is a purposeful scheduling system that guide in the right direction the current, high priority needs of the shop floor while remaining consistent with long-term production plans. The difference, and the power, of Discrete-Event Simulation (DES is its ability to mimic dynamic manufacturing systems, consisting of complex structures, and many heterogeneous interacting components. This paper describes such an integrated system (ERP/APS/DES and draw attention to the essential role of simulation based scheduling within it.

Visual Data-Analytics of Large-Scale Parallel Discrete-Event Simulations

Energy Technology Data Exchange (ETDEWEB)

Ross, Caitlin; Carothers, Christopher D.; Mubarak, Misbah; Carns, Philip; Ross, Robert; Li, Jianping Kelvin; Ma, Kwan-Liu

2016-11-13

Parallel discrete-event simulation (PDES) is an important tool in the codesign of extreme-scale systems because PDES provides a cost-effective way to evaluate designs of highperformance computing systems. Optimistic synchronization algorithms for PDES, such as Time Warp, allow events to be processed without global synchronization among the processing elements. A rollback mechanism is provided when events are processed out of timestamp order. Although optimistic synchronization protocols enable the scalability of large-scale PDES, the performance of the simulations must be tuned to reduce the number of rollbacks and provide an improved simulation runtime. To enable efficient large-scale optimistic simulations, one has to gain insight into the factors that affect the rollback behavior and simulation performance. We developed a tool for ROSS model developers that gives them detailed metrics on the performance of their large-scale optimistic simulations at varying levels of simulation granularity. Model developers can use this information for parameter tuning of optimistic simulations in order to achieve better runtime and fewer rollbacks. In this work, we instrument the ROSS optimistic PDES framework to gather detailed statistics about the simulation engine. We have also developed an interactive visualization interface that uses the data collected by the ROSS instrumentation to understand the underlying behavior of the simulation engine. The interface connects real time to virtual time in the simulation and provides the ability to view simulation data at different granularities. We demonstrate the usefulness of our framework by performing a visual analysis of the dragonfly network topology model provided by the CODES simulation framework built on top of ROSS. The instrumentation needs to minimize overhead in order to accurately collect data about the simulation performance. To ensure that the instrumentation does not introduce unnecessary overhead, we perform a

Simulation of land use evolution by discrete events method: Application to “la chaîne des puys” from XV to XVIII Century

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Y. Michelin

1998-01-01

Full Text Available By using a discrete event method, simulation of land use evolution has been applied to a landscape model of “la ChaÎne des Puys” (French Massif Central during along period (XV–XVIII centuries. The indications concerning the evolution of land use are in conformity with the observation of actual situations but the dynamic changes are faster than in actual facts. In spite of limitations due to necessary simplifications, it is now established that the discrete event method is efficient to simulate land use evolution during a long period. The model is immediately able to describe actual dynamics and to show sensitive variables with their critical values. Although oversimplified, it shows how far factors such as level of crops production and taxation can influence land use and landscape changes with a more or less lengthy period. In the future, the model should be bettered by introducing other determined and/or stochastic events.

Intuitionistic fuzzy logics

CERN Document Server

T Atanassov, Krassimir

2017-01-01

The book offers a comprehensive survey of intuitionistic fuzzy logics. By reporting on both the author’s research and others’ findings, it provides readers with a complete overview of the field and highlights key issues and open problems, thus suggesting new research directions. Starting with an introduction to the basic elements of intuitionistic fuzzy propositional calculus, it then provides a guide to the use of intuitionistic fuzzy operators and quantifiers, and lastly presents state-of-the-art applications of intuitionistic fuzzy sets. The book is a valuable reference resource for graduate students and researchers alike.

Local Model Predictive Control for T-S Fuzzy Systems.

Science.gov (United States)

Lee, Donghwan; Hu, Jianghai

2017-09-01

In this paper, a new linear matrix inequality-based model predictive control (MPC) problem is studied for discrete-time nonlinear systems described as Takagi-Sugeno fuzzy systems. A recent local stability approach is applied to improve the performance of the proposed MPC scheme. At each time k , an optimal state-feedback gain that minimizes an objective function is obtained by solving a semidefinite programming problem. The local stability analysis, the estimation of the domain of attraction, and feasibility of the proposed MPC are proved. Examples are given to demonstrate the advantages of the suggested MPC over existing approaches.

TRStalker: an efficient heuristic for finding fuzzy tandem repeats.

Science.gov (United States)

Pellegrini, Marco; Renda, M Elena; Vecchio, Alessio

2010-06-15

Genomes in higher eukaryotic organisms contain a substantial amount of repeated sequences. Tandem Repeats (TRs) constitute a large class of repetitive sequences that are originated via phenomena such as replication slippage and are characterized by close spatial contiguity. They play an important role in several molecular regulatory mechanisms, and also in several diseases (e.g. in the group of trinucleotide repeat disorders). While for TRs with a low or medium level of divergence the current methods are rather effective, the problem of detecting TRs with higher divergence (fuzzy TRs) is still open. The detection of fuzzy TRs is propaedeutic to enriching our view of their role in regulatory mechanisms and diseases. Fuzzy TRs are also important as tools to shed light on the evolutionary history of the genome, where higher divergence correlates with more remote duplication events. We have developed an algorithm (christened TRStalker) with the aim of detecting efficiently TRs that are hard to detect because of their inherent fuzziness, due to high levels of base substitutions, insertions and deletions. To attain this goal, we developed heuristics to solve a Steiner version of the problem for which the fuzziness is measured with respect to a motif string not necessarily present in the input string. This problem is akin to the 'generalized median string' that is known to be an NP-hard problem. Experiments with both synthetic and biological sequences demonstrate that our method performs better than current state of the art for fuzzy TRs and that the fuzzy TRs of the type we detect are indeed present in important biological sequences. TRStalker will be integrated in the web-based TRs Discovery Service (TReaDS) at bioalgo.iit.cnr.it. Supplementary data are available at Bioinformatics online.

(L,M-Fuzzy σ-Algebras

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Fu-Gui Shi

2010-01-01

Full Text Available The notion of (L,M-fuzzy σ-algebras is introduced in the lattice value fuzzy set theory. It is a generalization of Klement's fuzzy σ-algebras. In our definition of (L,M-fuzzy σ-algebras, each L-fuzzy subset can be regarded as an L-measurable set to some degree.

Recurrent fuzzy ranking methods

Science.gov (United States)

Hajjari, Tayebeh

2012-11-01

With the increasing development of fuzzy set theory in various scientific fields and the need to compare fuzzy numbers in different areas. Therefore, Ranking of fuzzy numbers plays a very important role in linguistic decision-making, engineering, business and some other fuzzy application systems. Several strategies have been proposed for ranking of fuzzy numbers. Each of these techniques has been shown to produce non-intuitive results in certain case. In this paper, we reviewed some recent ranking methods, which will be useful for the researchers who are interested in this area.

Fuzzy production planning models for an unreliable production system with fuzzy production rate and stochastic/fuzzy demand rate

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K. A. Halim

2011-01-01

Full Text Available In this article, we consider a single-unit unreliable production system which produces a single item. During a production run, the production process may shift from the in-control state to the out-of-control state at any random time when it produces some defective items. The defective item production rate is assumed to be imprecise and is characterized by a trapezoidal fuzzy number. The production rate is proportional to the demand rate where the proportionality constant is taken to be a fuzzy number. Two production planning models are developed on the basis of fuzzy and stochastic demand patterns. The expected cost per unit time in the fuzzy sense is derived in each model and defuzzified by using the graded mean integration representation method. Numerical examples are provided to illustrate the optimal results of the proposed fuzzy models.

Genetic algorithm-based fuzzy-PID control methodologies for enhancement of energy efficiency of a dynamic energy system

International Nuclear Information System (INIS)

Jahedi, G.; Ardehali, M.M.

2011-01-01

The simplicity in coding the heuristic judgment of experienced operator by means of fuzzy logic can be exploited for enhancement of energy efficiency. Fuzzy logic has been used as an effective tool for scheduling conventional PID controllers gain coefficients (F-PID). However, to search for the most desirable fuzzy system characteristics that allow for best performance of the energy system with minimum energy input, optimization techniques such as genetic algorithm (GA) could be utilized and the control methodology is identified as GA-based F-PID (GA-F-PID). The objective of this study is to examine the performance of PID, F-PID, and GA-F-PID controllers for enhancement of energy efficiency of a dynamic energy system. The performance evaluation of the controllers is accomplished by means of two cost functions that are based on the quadratic forms of the energy input and deviation from a setpoint temperature, referred to as energy and comfort costs, respectively. The GA-F-PID controller is examined in two different forms, namely, global form and local form. For the global form, all possible combinations of fuzzy system characteristics in the search domain are explored by GA for finding the fittest chromosome for all discrete time intervals during the entire operation period. For the local form, however, GA is used in each discrete time interval to find the fittest chromosome for implementation. The results show that the global form GA-F-PID and local form GA-F-PID control methodologies, in comparison with PID controller, achieve higher energy efficiency by lowering energy costs by 51.2%, and 67.8%, respectively. Similarly, the comfort costs for deviation from setpoint are enhanced by 54.4%, and 62.4%, respectively. It is determined that GA-F-PID performs better in local from than global form.

A study on discrete event dynamic model for nuclear operations of main feed water pump

International Nuclear Information System (INIS)

Bae, J. C.; Choi, J. I.

2000-01-01

A major objective of the study is to propose a supervisory control algorithm based on the discrete event dynamic system (DEDS) model and apply it to the automation of nuclear operations. The study is motivated by the suitability of the DEDS model for simulation of man-made control action and the potential of the DEDS based supervisory control algorithm for enhanced licensibility, when implemented in nuclear plants, through design transparency due to strong analytic backgrounds. The DEDS model can analytically show the robust stability of the proposed supervisory controller providing design transparency for enhanced licensibility when implemented in nuclear operations

Construction of Fuzzy Sets and Applying Aggregation Operators for Fuzzy Queries

DEFF Research Database (Denmark)

Hudec, Miroslav; Sudzina, Frantisek

Flexible query conditions could use linguistic terms described by fuzzy sets. The question is how to properly construct fuzzy sets for each linguistic term and apply an adequate aggregation function. For construction of fuzzy sets, the lowest value, the highest value of attribute...... and the distribution of data inside its domain are used. The logarithmic transformation of domains appears to be suitable. This way leads to a balanced distribution of tuples over fuzzy sets. In addition, users’ opinions about linguistic terms as well as current content in database are merged. The second investigated...

Markov modeling and discrete event simulation in health care: a systematic comparison.

Science.gov (United States)

Standfield, Lachlan; Comans, Tracy; Scuffham, Paul

2014-04-01

The aim of this study was to assess if the use of Markov modeling (MM) or discrete event simulation (DES) for cost-effectiveness analysis (CEA) may alter healthcare resource allocation decisions. A systematic literature search and review of empirical and non-empirical studies comparing MM and DES techniques used in the CEA of healthcare technologies was conducted. Twenty-two pertinent publications were identified. Two publications compared MM and DES models empirically, one presented a conceptual DES and MM, two described a DES consensus guideline, and seventeen drew comparisons between MM and DES through the authors' experience. The primary advantages described for DES over MM were the ability to model queuing for limited resources, capture individual patient histories, accommodate complexity and uncertainty, represent time flexibly, model competing risks, and accommodate multiple events simultaneously. The disadvantages of DES over MM were the potential for model overspecification, increased data requirements, specialized expensive software, and increased model development, validation, and computational time. Where individual patient history is an important driver of future events an individual patient simulation technique like DES may be preferred over MM. Where supply shortages, subsequent queuing, and diversion of patients through other pathways in the healthcare system are likely to be drivers of cost-effectiveness, DES modeling methods may provide decision makers with more accurate information on which to base resource allocation decisions. Where these are not major features of the cost-effectiveness question, MM remains an efficient, easily validated, parsimonious, and accurate method of determining the cost-effectiveness of new healthcare interventions.

Fuzzy social choice theory

CERN Document Server

B Gibilisco, Michael; E Albert, Karen; N Mordeson, John; J Wierman, Mark; D Clark, Terry

2014-01-01

This book offers a comprehensive analysis of the social choice literature and shows, by applying fuzzy sets, how the use of fuzzy preferences, rather than that of strict ones, may affect the social choice theorems. To do this, the book explores the presupposition of rationality within the fuzzy framework and shows that the two conditions for rationality, completeness and transitivity, do exist with fuzzy preferences. Specifically, this book examines: the conditions under which a maximal set exists; the Arrow’s theorem;  the Gibbard-Satterthwaite theorem; and the median voter theorem.  After showing that a non-empty maximal set does exists for fuzzy preference relations, this book goes on to demonstrating the existence of a fuzzy aggregation rule satisfying all five Arrowian conditions, including non-dictatorship. While the Gibbard-Satterthwaite theorem only considers individual fuzzy preferences, this work shows that both individuals and groups can choose alternatives to various degrees, resulting in a so...

Relations Among Some Fuzzy Entropy Formulae

Institute of Scientific and Technical Information of China (English)

卿铭

2004-01-01

Fuzzy entropy has been widely used to analyze and design fuzzy systems, and many fuzzy entropy formulae have been proposed. For further in-deepth analysis of fuzzy entropy, the axioms and some important formulae of fuzzy entropy are introduced. Some equivalence results among these fuzzy entropy formulae are proved, and it is shown that fuzzy entropy is a special distance measurement.

Fuzzy crane control with sensorless payload deflection feedback for vibration reduction

Science.gov (United States)

Smoczek, Jaroslaw

2014-05-01

Different types of cranes are widely used for shifting cargoes in building sites, shipping yards, container terminals and many manufacturing segments where the problem of fast and precise transferring a payload suspended on the ropes with oscillations reduction is frequently important to enhance the productivity, efficiency and safety. The paper presents the fuzzy logic-based robust feedback anti-sway control system which can be applicable either with or without a sensor of sway angle of a payload. The discrete-time control approach is based on the fuzzy interpolation of the controllers and crane dynamic model's parameters with respect to the varying rope length and mass of a payload. The iterative procedure combining a pole placement method and interval analysis of closed-loop characteristic polynomial coefficients is proposed to design the robust control scheme. The sensorless anti-sway control application developed with using PAC system with RX3i controller was verified on the laboratory scaled overhead crane.

New fuzzy EWMA control charts for monitoring phase II fuzzy profiles

Directory of Open Access Journals (Sweden)

Ghazale Moghadam

2016-01-01

Full Text Available In many quality control applications, the quality of a process or product is explained by the relationship between response variable and one or more explanatory variables, called a profile. In this paper, a new fuzzy EWMA control chart for phase II fuzzy profile monitoring is proposed. To this end, we extend EWMA control charts to its equivalent Fuzzy type and then implement fuzzy ranking methods to determine whether the process fuzzy profile is under or out of control. The proposed method is capable of identifying small changes in process under condition of process profile explaining parameters vagueness, roughness and uncertainty. Determining the source of changes, this method provides us with the possibility of recognizing the causes of process transition from stable mode, removing these causes and restoring the process stable mode.

Dynamics and genetic fuzzy neural network vibration control design of a smart flexible four-bar linkage mechanism

International Nuclear Information System (INIS)

Rong Bao; Rui Xiaoting; Tao Ling

2012-01-01

In this paper, a dynamic modeling method and an active vibration control scheme for a smart flexible four-bar linkage mechanism featuring piezoelectric actuators and strain gauge sensors are presented. The dynamics of this smart mechanism is described by the Discrete Time Transfer Matrix Method of Multibody System (MS-DTTMM). Then a nonlinear fuzzy neural network control is employed to suppress the vibration of this smart mechanism. For improving the dynamic performance of the fuzzy neural network, a genetic algorithm based on the MS-DTTMM is designed offline to tune the initial parameters of the fuzzy neural network. The MS-DTTMM avoids the global dynamics equations of the system, which results in the matrices involved are always very small, so the computational efficiency of the dynamic analysis and control system optimization can be greatly improved. Formulations of the method as well as a numerical simulation are given to demonstrate the proposed dynamic method and control scheme.

Use of Fuzzy rainfall-runoff predictions for claypan watersheds with conservation buffers in Northeast Missouri

Science.gov (United States)

Anomaa Senaviratne, G. M. M. M.; Udawatta, Ranjith P.; Anderson, Stephen H.; Baffaut, Claire; Thompson, Allen

2014-09-01

Fuzzy rainfall-runoff models are often used to forecast flood or water supply in large catchments and applications at small/field scale agricultural watersheds are limited. The study objectives were to develop, calibrate, and validate a fuzzy rainfall-runoff model using long-term data of three adjacent field scale row crop watersheds (1.65-4.44 ha) with intermittent discharge in the claypan soils of Northeast Missouri. The watersheds were monitored for a six-year calibration period starting 1991 (pre-buffer period). Thereafter, two of them were treated with upland contour grass and agroforestry (tree + grass) buffers (4.5 m wide, 36.5 m apart) to study water quality benefits. The fuzzy system was based on Mamdani method using MATLAB 7.10.0. The model predicted event-based runoff with model performance coefficients of r2 and Nash-Sutcliffe Coefficient (NSC) values greater than 0.65 for calibration and validation. The pre-buffer fuzzy system predicted event-based runoff for 30-50 times larger corn/soybean watersheds with r2 values of 0.82 and 0.68 and NSC values of 0.77 and 0.53, respectively. The runoff predicted by the fuzzy system closely agreed with values predicted by physically-based Agricultural Policy Environmental eXtender model (APEX) for the pre-buffer watersheds. The fuzzy rainfall-runoff model has the potential for runoff predictions at field-scale watersheds with minimum input. It also could up-scale the predictions for large-scale watersheds to evaluate the benefits of conservation practices.

CONFIG - Adapting qualitative modeling and discrete event simulation for design of fault management systems

Science.gov (United States)

Malin, Jane T.; Basham, Bryan D.

1989-01-01

CONFIG is a modeling and simulation tool prototype for analyzing the normal and faulty qualitative behaviors of engineered systems. Qualitative modeling and discrete-event simulation have been adapted and integrated, to support early development, during system design, of software and procedures for management of failures, especially in diagnostic expert systems. Qualitative component models are defined in terms of normal and faulty modes and processes, which are defined by invocation statements and effect statements with time delays. System models are constructed graphically by using instances of components and relations from object-oriented hierarchical model libraries. Extension and reuse of CONFIG models and analysis capabilities in hybrid rule- and model-based expert fault-management support systems are discussed.

Estimating ICU bed capacity using discrete event simulation.

Science.gov (United States)

Zhu, Zhecheng; Hen, Bee Hoon; Teow, Kiok Liang

2012-01-01

The intensive care unit (ICU) in a hospital caters for critically ill patients. The number of the ICU beds has a direct impact on many aspects of hospital performance. Lack of the ICU beds may cause ambulance diversion and surgery cancellation, while an excess of ICU beds may cause a waste of resources. This paper aims to develop a discrete event simulation (DES) model to help the healthcare service providers determine the proper ICU bed capacity which strikes the balance between service level and cost effectiveness. The DES model is developed to reflect the complex patient flow of the ICU system. Actual operational data, including emergency arrivals, elective arrivals and length of stay, are directly fed into the DES model to capture the variations in the system. The DES model is validated by open box test and black box test. The validated model is used to test two what-if scenarios which the healthcare service providers are interested in: the proper number of the ICU beds in service to meet the target rejection rate and the extra ICU beds in service needed to meet the demand growth. A 12-month period of actual operational data was collected from an ICU department with 13 ICU beds in service. Comparison between the simulation results and the actual situation shows that the DES model accurately captures the variations in the system, and the DES model is flexible to simulate various what-if scenarios. DES helps the healthcare service providers describe the current situation, and simulate the what-if scenarios for future planning.

SOS based robust H(∞) fuzzy dynamic output feedback control of nonlinear networked control systems.

Science.gov (United States)

Chae, Seunghwan; Nguang, Sing Kiong

2014-07-01

In this paper, a methodology for designing a fuzzy dynamic output feedback controller for discrete-time nonlinear networked control systems is presented where the nonlinear plant is modelled by a Takagi-Sugeno fuzzy model and the network-induced delays by a finite state Markov process. The transition probability matrix for the Markov process is allowed to be partially known, providing a more practical consideration of the real world. Furthermore, the fuzzy controller's membership functions and premise variables are not assumed to be the same as the plant's membership functions and premise variables, that is, the proposed approach can handle the case, when the premise of the plant are not measurable or delayed. The membership functions of the plant and the controller are approximated as polynomial functions, then incorporated into the controller design. Sufficient conditions for the existence of the controller are derived in terms of sum of square inequalities, which are then solved by YALMIP. Finally, a numerical example is used to demonstrate the validity of the proposed methodology.

A Discrete Event System Approach to Online Testing of Speed Independent Circuits

Directory of Open Access Journals (Sweden)

P. K. Biswal

2015-01-01

Full Text Available With the increase in soft failures in deep submicron ICs, online testing is becoming an integral part of design for testability. Some techniques for online testing of asynchronous circuits are proposed in the literature, which involves development of a checker that verifies the correctness of the protocol. This checker involves Mutex blocks making its area overhead quite high. In this paper, we have adapted the Theory of Fault Detection and Diagnosis available in the literature on Discrete Event Systems to online testing of speed independent asynchronous circuits. The scheme involves development of a state based model of the circuit, under normal and various stuck-at fault conditions, and finally designing state estimators termed as detectors. The detectors monitor the circuit online and determine whether it is functioning in normal/failure mode. The main advantages are nonintrusiveness and low area overheads compared to similar schemes reported in the literature.

Estimation of the Net Present Value of the Investment Project in the Situation of Fuzzy Initial Data

Directory of Open Access Journals (Sweden)

Kotsyuba Oleksiy S.

2017-03-01

Full Text Available The article investigates the problem of estimating the net present value of the investment project using a methodology based on the theory of fuzzy sets in the situation when the initial data are described by fuzzy estimates. In the general case the fuzzy-multiple estimation of the specified indicator at a discrete-interval representation of the initial parameters is reduced to a set of homogeneous optimization problems. Often, depending on the characteristics of fuzzy estimates of cash flows of the investment project under consideration, the solutions to these problems can be found directly on the basis of relevant analytical expressions, while other problems require using special optimization methods. In the work there made an attempt to develop the analytical component of the fuzzy-multiple modeling of the net present value indicator. First, we examined the general search and optimization approach, which allows providing a predetermined degree of accuracy, as well as the method for approximate determination of the fuzzy estimate of the net present value on the basis of analytical relationships developed by Сhui-Yu Chiu and Chan S. Park. After that, the situation was analyzed, and the corresponding calculation model was proposed, when fuzzy estimates of the cash flows of the investment project can be interpreted from the perspective of the concept of the money-generating operation formulated by O. B. Lozhkin. Among other things, it allowed to develop a general scheme for determining the fuzzy estimate of the net present value, supplementing it with the situation of this concept. As the main direction of the further development of the problems discussed in the publication there determined the formation of a holistic methodology for evaluating the effectiveness of real investments, which would cover different in their nature and structural characteristics types of uncertainty from unified theoretical positions.

Inference of RMR value using fuzzy set theory and neuro-fuzzy techniques

Energy Technology Data Exchange (ETDEWEB)

Bae, Gyu-Jin; Cho, Mahn-Sup [Korea Institute of Construction Technology, Koyang(Korea)

2001-12-31

In the design of tunnel, it contains inaccuracy of data, fuzziness of evaluation, observer error and so on. The face observation during tunnel excavation, therefore, plays an important role to raise stability and to reduce supporting cost. This study is carried out to minimize the subjectiveness of observer and to exactly evaluate the natural properties of ground during the face observation. For these purpose, fuzzy set theory and neuro-fuzzy techniques in artificial intelligent techniques are applied to the inference of the RMR(Rock Mass Rating) value from the observation data. The correlation between original RMR value and inferred RMR{sub {sub F}U} and RMR{sub {sub N}F} values from fuzzy Set theory and neuro-fuzzy techniques is investigated using 46 data. The results show that good correlation between original RMR value and inferred RMR{sub {sub F}U} and RMR{sub {sub N}F} values is observed when the correlation coefficients are |R|=0.96 and |R|=0.95 respectively. >From these results, applicability of fuzzy set theory and neuro-fuzzy techniques to rock mass classification is proved to be sufficiently high enough. (author). 17 refs., 5 tabs., 9 figs.

Outdoor altitude stabilization of QuadRotor based on type-2 fuzzy and fuzzy PID

Science.gov (United States)

Wicaksono, H.; Yusuf, Y. G.; Kristanto, C.; Haryanto, L.

2017-11-01

This paper presents a design of altitude stabilization of QuadRotor based on type-2 fuzzy and fuzzy PID. This practical design is implemented outdoor. Barometric and sonar sensor were used in this experiment as an input for the controller YoHe. The throttle signal as a control input was provided by the controller to leveling QuadRotor in particular altitude and known well as altitude stabilization. The parameter of type-2 fuzzy and fuzzy PID was tuned in several heights to get the best control parameter for any height. Type-2 fuzzy produced better result than fuzzy PID but had a slow response in the beginning.

ps-ro Fuzzy Open(Closed Functions and ps-ro Fuzzy Semi-Homeomorphism

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Pankaj Chettri

2015-11-01

Full Text Available The aim of this paper is to introduce and characterize some new class of functions in a fuzzy topological space termed as ps-ro fuzzy open(closed functions, ps-ro fuzzy pre semiopen functions and ps-ro fuzzy semi-homeomorphism. The interrelation among these concepts and also their relations with the parallel existing concepts are established. It is also shown with the help of examples that these newly introduced concepts are independent of the well known existing allied concepts.

Foundations Of Fuzzy Control

DEFF Research Database (Denmark)

Jantzen, Jan

The objective of this textbook is to acquire an understanding of the behaviour of fuzzy logic controllers. Under certain conditions a fuzzy controller is equivalent to a proportional-integral-derivative (PID) controller. Using that equivalence as a link, the book applies analysis methods from...... linear and nonlinear control theory. In the linear domain, PID tuning methods and stability analyses are transferred to linear fuzzy controllers. The Nyquist plot shows the robustness of different settings of the fuzzy gain parameters. As a result, a fuzzy controller is guaranteed to perform as well...... as any PID controller. In the nonlinear domain, the stability of four standard control surfaces is analysed by means of describing functions and Nyquist plots. The self-organizing controller (SOC) is shown to be a model reference adaptive controller. There is a possibility that a nonlinear fuzzy PID...

Discrete event command and control for networked teams with multiple missions

Science.gov (United States)

Lewis, Frank L.; Hudas, Greg R.; Pang, Chee Khiang; Middleton, Matthew B.; McMurrough, Christopher

2009-05-01

During mission execution in military applications, the TRADOC Pamphlet 525-66 Battle Command and Battle Space Awareness capabilities prescribe expectations that networked teams will perform in a reliable manner under changing mission requirements, varying resource availability and reliability, and resource faults. In this paper, a Command and Control (C2) structure is presented that allows for computer-aided execution of the networked team decision-making process, control of force resources, shared resource dispatching, and adaptability to change based on battlefield conditions. A mathematically justified networked computing environment is provided called the Discrete Event Control (DEC) Framework. DEC has the ability to provide the logical connectivity among all team participants including mission planners, field commanders, war-fighters, and robotic platforms. The proposed data management tools are developed and demonstrated on a simulation study and an implementation on a distributed wireless sensor network. The results show that the tasks of multiple missions are correctly sequenced in real-time, and that shared resources are suitably assigned to competing tasks under dynamically changing conditions without conflicts and bottlenecks.

Algebraic Hyperstructures and Fuzzy Logic in the Treatment of Uncertainty

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Antonio Maturo

2016-09-01

Full Text Available This study presents some fundamental aspects of recent theories  on algebraic Hyperstructures, an important tool for an interdisciplinary vision of Geometry and Algebra. We examine some hypergroupoids of events, useful for a new algebraic-geometry perspective in the study and issues of probability applications. This paper considers some fundamental aspects of fuzzy classifications and their applications to problems of evaluation and decision in Architecture and Economics. Finally, we present hypergroups and join space associated with these classifications.   Iperstrutture algebriche e logica fuzzy nel trattamento dell’incertezza Si presentano alcuni aspetti fondamentali della relativamente recente teoria delle iperstrutture algebriche, importante strumento per una visione interdisciplinare di Geometria e Algebra. Si esaminano alcuni ipergruppoidi di eventi, utili per un nuovo punto di vista algebrico - geometrico nello studio e nelle applicazioni di alcune questioni di probabilità. Si considerano alcuni aspetti fondamentali delle classificazioni fuzzy e le loro applicazioni a problemi di valutazione e decisione in Architettura e in Economia. Si presentano infine ipergruppi e join space associati a tali classificazioni. Parole Chiave: Iperstrutture algebriche. Logica fuzzy. Applicazioni a Architettura e Economia.

Modeling Temporal Processes in Early Spacecraft Design: Application of Discrete-Event Simulations for Darpa's F6 Program

Science.gov (United States)

Dubos, Gregory F.; Cornford, Steven

2012-01-01

While the ability to model the state of a space system over time is essential during spacecraft operations, the use of time-based simulations remains rare in preliminary design. The absence of the time dimension in most traditional early design tools can however become a hurdle when designing complex systems whose development and operations can be disrupted by various events, such as delays or failures. As the value delivered by a space system is highly affected by such events, exploring the trade space for designs that yield the maximum value calls for the explicit modeling of time.This paper discusses the use of discrete-event models to simulate spacecraft development schedule as well as operational scenarios and on-orbit resources in the presence of uncertainty. It illustrates how such simulations can be utilized to support trade studies, through the example of a tool developed for DARPA's F6 program to assist the design of "fractionated spacecraft".

Properties of Bipolar Fuzzy Hypergraphs

OpenAIRE

Akram, M.; Dudek, W. A.; Sarwar, S.

2013-01-01

In this article, we apply the concept of bipolar fuzzy sets to hypergraphs and investigate some properties of bipolar fuzzy hypergraphs. We introduce the notion of $A-$ tempered bipolar fuzzy hypergraphs and present some of their properties. We also present application examples of bipolar fuzzy hypergraphs.

A novel approach for modelling complex maintenance systems using discrete event simulation

International Nuclear Information System (INIS)

Alrabghi, Abdullah; Tiwari, Ashutosh

2016-01-01

Existing approaches for modelling maintenance rely on oversimplified assumptions which prevent them from reflecting the complexity found in industrial systems. In this paper, we propose a novel approach that enables the modelling of non-identical multi-unit systems without restrictive assumptions on the number of units or their maintenance characteristics. Modelling complex interactions between maintenance strategies and their effects on assets in the system is achieved by accessing event queues in Discrete Event Simulation (DES). The approach utilises the wide success DES has achieved in manufacturing by allowing integration with models that are closely related to maintenance such as production and spare parts systems. Additional advantages of using DES include rapid modelling and visual interactive simulation. The proposed approach is demonstrated in a simulation based optimisation study of a published case. The current research is one of the first to optimise maintenance strategies simultaneously with their parameters while considering production dynamics and spare parts management. The findings of this research provide insights for non-conflicting objectives in maintenance systems. In addition, the proposed approach can be used to facilitate the simulation and optimisation of industrial maintenance systems. - Highlights: • This research is one of the first to optimise maintenance strategies simultaneously. • New insights for non-conflicting objectives in maintenance systems. • The approach can be used to optimise industrial maintenance systems.

Discrete-event simulation of coordinated multi-point joint transmission in LTE-Advanced with constrained backhaul

DEFF Research Database (Denmark)

Artuso, Matteo; Christiansen, Henrik Lehrmann

2014-01-01

Inter-cell interference in LTE-Advanced can be mitigated using coordinated multi-point (CoMP) techniques with joint transmission of user data . However, this requires tight coordination of the eNodeBs, usin g the X2 interface. In this paper we use discrete-event simulation to evaluate the latency...... requirements for the X2 interface and investigate the consequences of a constrained ba ckhaul. Our simulation results show a gain of the system throug hput of up to 120% compared to the case without CoMP for low-latency backhaul. With X2 latencies above 5 ms CoMP is no longer a benefit to the network....

Word Similarity from Dictionaries: Inferring Fuzzy Measures from Fuzzy Graphs

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Vicenc Torra

2008-01-01

Full Text Available WORD SIMILARITY FROM DICTIONARIES: INFERRING FUZZY MEASURES FROM FUZZY GRAPHS The computation of similarities between words is a basic element of information retrieval systems, when retrieval is not solely based on word matching. In this work we consider a measure between words based on dictionaries. This is achieved assuming that a dictionary is formalized as a fuzzy graph. We show that the approach permits to compute measures not only for pairs of words but for sets of them.

Comparison of fuzzy AHP and fuzzy TODIM methods for landfill location selection.

Science.gov (United States)

Hanine, Mohamed; Boutkhoum, Omar; Tikniouine, Abdessadek; Agouti, Tarik

2016-01-01

Landfill location selection is a multi-criteria decision problem and has a strategic importance for many regions. The conventional methods for landfill location selection are insufficient in dealing with the vague or imprecise nature of linguistic assessment. To resolve this problem, fuzzy multi-criteria decision-making methods are proposed. The aim of this paper is to use fuzzy TODIM (the acronym for Interactive and Multi-criteria Decision Making in Portuguese) and the fuzzy analytic hierarchy process (AHP) methods for the selection of landfill location. The proposed methods have been applied to a landfill location selection problem in the region of Casablanca, Morocco. After determining the criteria affecting the landfill location decisions, fuzzy TODIM and fuzzy AHP methods are applied to the problem and results are presented. The comparisons of these two methods are also discussed.

(Fuzzy) Ideals of BN-Algebras

Science.gov (United States)

Walendziak, Andrzej

2015-01-01

The notions of an ideal and a fuzzy ideal in BN-algebras are introduced. The properties and characterizations of them are investigated. The concepts of normal ideals and normal congruences of a BN-algebra are also studied, the properties of them are displayed, and a one-to-one correspondence between them is presented. Conditions for a fuzzy set to be a fuzzy ideal are given. The relationships between ideals and fuzzy ideals of a BN-algebra are established. The homomorphic properties of fuzzy ideals of a BN-algebra are provided. Finally, characterizations of Noetherian BN-algebras and Artinian BN-algebras via fuzzy ideals are obtained. PMID:26125050

Design of robust reliable control for T-S fuzzy Markovian jumping delayed neutral type neural networks with probabilistic actuator faults and leakage delays: An event-triggered communication scheme.

Science.gov (United States)

Syed Ali, M; Vadivel, R; Saravanakumar, R

2018-06-01

This study examines the problem of robust reliable control for Takagi-Sugeno (T-S) fuzzy Markovian jumping delayed neural networks with probabilistic actuator faults and leakage terms. An event-triggered communication scheme. First, the randomly occurring actuator faults and their failures rates are governed by two sets of unrelated random variables satisfying certain probabilistic failures of every actuator, new type of distribution based event triggered fault model is proposed, which utilize the effect of transmission delay. Second, Takagi-Sugeno (T-S) fuzzy model is adopted for the neural networks and the randomness of actuators failures is modeled in a Markov jump model framework. Third, to guarantee the considered closed-loop system is exponential mean square stable with a prescribed reliable control performance, a Markov jump event-triggered scheme is designed in this paper, which is the main purpose of our study. Fourth, by constructing appropriate Lyapunov-Krasovskii functional, employing Newton-Leibniz formulation and integral inequalities, several delay-dependent criteria for the solvability of the addressed problem are derived. The obtained stability criteria are stated in terms of linear matrix inequalities (LMIs), which can be checked numerically using the effective LMI toolbox in MATLAB. Finally, numerical examples are given to illustrate the effectiveness and reduced conservatism of the proposed results over the existing ones, among them one example was supported by real-life application of the benchmark problem. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Potential applicability of fuzzy set theory to analyses of containment response and uncertainty for postulated severe accidents

International Nuclear Information System (INIS)

Chun, M.H.; Ahn, K.I.

1991-01-01

An important issue faced by contemporary risk analysts of nuclear power plants is how to deal with uncertainties that arise in each phase of probabilistic risk assessments. The major uncertainty addressed in this paper is the one that arises in the accident-progression event trees (APETs), which treat the physical processes affecting the core after an initiating event occurs. Recent advances in the theory of fuzzy sets make it possible to analyze the uncertainty related to complex physical phenomena that may occur during a severe accident of nuclear power plants by means of fuzzy set or possibility concept. The main purpose of this paper is to prevent the results of assessment of the potential applicability of the fuzzy set theory to the uncertainty analysis of APETs as a possible alternative procedure to that used in the most recent risk assessment

Efficient modeling of vector hysteresis using fuzzy inference systems

International Nuclear Information System (INIS)

Adly, A.A.; Abd-El-Hafiz, S.K.

2008-01-01

Vector hysteresis models have always been regarded as important tools to determine which multi-dimensional magnetic field-media interactions may be predicted. In the past, considerable efforts have been focused on mathematical modeling methodologies of vector hysteresis. This paper presents an efficient approach based upon fuzzy inference systems for modeling vector hysteresis. Computational efficiency of the proposed approach stems from the fact that the basic non-local memory Preisach-type hysteresis model is approximated by a local memory model. The proposed computational low-cost methodology can be easily integrated in field calculation packages involving massive multi-dimensional discretizations. Details of the modeling methodology and its experimental testing are presented

Human visual system automatically encodes sequential regularities of discrete events.

Science.gov (United States)

Kimura, Motohiro; Schröger, Erich; Czigler, István; Ohira, Hideki

2010-06-01

For our adaptive behavior in a dynamically changing environment, an essential task of the brain is to automatically encode sequential regularities inherent in the environment into a memory representation. Recent studies in neuroscience have suggested that sequential regularities embedded in discrete sensory events are automatically encoded into a memory representation at the level of the sensory system. This notion is largely supported by evidence from investigations using auditory mismatch negativity (auditory MMN), an event-related brain potential (ERP) correlate of an automatic memory-mismatch process in the auditory sensory system. However, it is still largely unclear whether or not this notion can be generalized to other sensory modalities. The purpose of the present study was to investigate the contribution of the visual sensory system to the automatic encoding of sequential regularities using visual mismatch negativity (visual MMN), an ERP correlate of an automatic memory-mismatch process in the visual sensory system. To this end, we conducted a sequential analysis of visual MMN in an oddball sequence consisting of infrequent deviant and frequent standard stimuli, and tested whether the underlying memory representation of visual MMN generation contains only a sensory memory trace of standard stimuli (trace-mismatch hypothesis) or whether it also contains sequential regularities extracted from the repetitive standard sequence (regularity-violation hypothesis). The results showed that visual MMN was elicited by first deviant (deviant stimuli following at least one standard stimulus), second deviant (deviant stimuli immediately following first deviant), and first standard (standard stimuli immediately following first deviant), but not by second standard (standard stimuli immediately following first standard). These results are consistent with the regularity-violation hypothesis, suggesting that the visual sensory system automatically encodes sequential

An Application of Fuzzy Inference System by Clustering Subtractive Fuzzy Method for Estimating of Product Requirement

Directory of Open Access Journals (Sweden)

Fajar Ibnu Tufeil

2009-06-01

Full Text Available Model fuzzy memiliki kemampuan untuk menjelaskan secara linguistik suatu sistem yang terlalu kompleks. Aturan-aturan dalam model fuzzy pada umumnya dibangun berdasarkan keahlian manusia dan pengetahuan heuristik dari sistem yang dimodelkan. Teknik ini selanjutnya dikembangkan menjadi teknik yang dapat mengidentifikasi aturan-aturan dari suatu basis data yang telah dikelompokkan berdasarkan persamaan strukturnya. Dalam hal ini metode pengelompokan fuzzy berfungsi untuk mencari kelompok-kelompok data. Informasi yang dihasilkan dari metode pengelompokan ini, yaitu informasi tentang pusat kelompok, digunakan untuk membentuk aturan-aturan dalam sistem penalaran fuzzy. Dalam skripsi ini dibahas mengenai penerapan fuzzy infereance system dengan metode pengelompokan fuzzy subtractive clustering, yaitu untuk membentuk sistem penalaran fuzzy dengan menggunakan model fuzzy Takagi-Sugeno orde satu. Selanjutnya, metode pengelompokan fuzzy subtractive clustering diterapkan dalam memodelkan masalah dibidang pemasaran, yaitu untuk memprediksi permintaan pasar terhadap suatu produk susu. Aplikasi ini dibangun menggunakan Borland Delphi 6.0. Dari hasil pengujian diperoleh tingkat error prediksi terkecil yaitu dengan Error Average 0.08%.

Discrete-event simulation for the design and evaluation of physical protection systems

International Nuclear Information System (INIS)

Jordan, S.E.; Snell, M.K.; Madsen, M.M.; Smith, J.S.; Peters, B.A.

1998-01-01

This paper explores the use of discrete-event simulation for the design and control of physical protection systems for fixed-site facilities housing items of significant value. It begins by discussing several modeling and simulation activities currently performed in designing and analyzing these protection systems and then discusses capabilities that design/analysis tools should have. The remainder of the article then discusses in detail how some of these new capabilities have been implemented in software to achieve a prototype design and analysis tool. The simulation software technology provides a communications mechanism between a running simulation and one or more external programs. In the prototype security analysis tool, these capabilities are used to facilitate human-in-the-loop interaction and to support a real-time connection to a virtual reality (VR) model of the facility being analyzed. This simulation tool can be used for both training (in real-time mode) and facility analysis and design (in fast mode)

A conceptual modeling framework for discrete event simulation using hierarchical control structures

Science.gov (United States)

Furian, N.; O’Sullivan, M.; Walker, C.; Vössner, S.; Neubacher, D.

2015-01-01

Conceptual Modeling (CM) is a fundamental step in a simulation project. Nevertheless, it is only recently that structured approaches towards the definition and formulation of conceptual models have gained importance in the Discrete Event Simulation (DES) community. As a consequence, frameworks and guidelines for applying CM to DES have emerged and discussion of CM for DES is increasing. However, both the organization of model-components and the identification of behavior and system control from standard CM approaches have shortcomings that limit CM’s applicability to DES. Therefore, we discuss the different aspects of previous CM frameworks and identify their limitations. Further, we present the Hierarchical Control Conceptual Modeling framework that pays more attention to the identification of a models’ system behavior, control policies and dispatching routines and their structured representation within a conceptual model. The framework guides the user step-by-step through the modeling process and is illustrated by a worked example. PMID:26778940

A conceptual modeling framework for discrete event simulation using hierarchical control structures.

Science.gov (United States)

Furian, N; O'Sullivan, M; Walker, C; Vössner, S; Neubacher, D

2015-08-01

Conceptual Modeling (CM) is a fundamental step in a simulation project. Nevertheless, it is only recently that structured approaches towards the definition and formulation of conceptual models have gained importance in the Discrete Event Simulation (DES) community. As a consequence, frameworks and guidelines for applying CM to DES have emerged and discussion of CM for DES is increasing. However, both the organization of model-components and the identification of behavior and system control from standard CM approaches have shortcomings that limit CM's applicability to DES. Therefore, we discuss the different aspects of previous CM frameworks and identify their limitations. Further, we present the Hierarchical Control Conceptual Modeling framework that pays more attention to the identification of a models' system behavior, control policies and dispatching routines and their structured representation within a conceptual model. The framework guides the user step-by-step through the modeling process and is illustrated by a worked example.

Supervisor localization a top-down approach to distributed control of discrete-event systems

CERN Document Server

Cai, Kai

2016-01-01

This monograph presents a systematic top-down approach to distributed control synthesis of discrete-event systems (DES). The approach is called supervisor localization; its essence is the allocation of external supervisory control action to individual component agents as their internal control strategies. The procedure is: first synthesize a monolithic supervisor, to achieve globally optimal and nonblocking controlled behavior, then decompose the monolithic supervisor into local controllers, one for each agent. The collective behavior of the resulting local controllers is identical to that achieved by the monolithic supervisor. The basic localization theory is first presented in the Ramadge–Wonham language-based supervisory control framework, then demonstrated with distributed control examples of multi-robot formations, manufacturing systems, and distributed algorithms. An architectural approach is adopted to apply localization to large-scale DES; this yields a heterarchical localization procedure, which is...

Fuzzy control and identification

CERN Document Server

Lilly, John H

2010-01-01

This book gives an introduction to basic fuzzy logic and Mamdani and Takagi-Sugeno fuzzy systems. The text shows how these can be used to control complex nonlinear engineering systems, while also also suggesting several approaches to modeling of complex engineering systems with unknown models. Finally, fuzzy modeling and control methods are combined in the book, to create adaptive fuzzy controllers, ending with an example of an obstacle-avoidance controller for an autonomous vehicle using modus ponendo tollens logic.

Speeding Up Network Simulations Using Discrete Time

OpenAIRE

Lucas, Aaron; Armbruster, Benjamin

2013-01-01

We develop a way of simulating disease spread in networks faster at the cost of some accuracy. Instead of a discrete event simulation (DES) we use a discrete time simulation. This aggregates events into time periods. We prove a bound on the accuracy attained. We also discuss the choice of step size and do an analytical comparison of the computational costs. Our error bound concept comes from the theory of numerical methods for SDEs and the basic proof structure comes from the theory of numeri...

Fuzzy pharmacology: theory and applications.

Science.gov (United States)

Sproule, Beth A; Naranjo, Claudio A; Türksen, I Burhan

2002-09-01

Fuzzy pharmacology is a term coined to represent the application of fuzzy logic and fuzzy set theory to pharmacological problems. Fuzzy logic is the science of reasoning, thinking and inference that recognizes and uses the real world phenomenon that everything is a matter of degree. It is an extension of binary logic that is able to deal with complex systems because it does not require crisp definitions and distinctions for the system components. In pharmacology, fuzzy modeling has been used for the mechanical control of drug delivery in surgical settings, and work has begun evaluating its use in other pharmacokinetic and pharmacodynamic applications. Fuzzy pharmacology is an emerging field that, based on these initial explorations, warrants further investigation.

Fuzzy data analysis

CERN Document Server

Bandemer, Hans

1992-01-01

Fuzzy data such as marks, scores, verbal evaluations, imprecise observations, experts' opinions and grey tone pictures, are quite common. In Fuzzy Data Analysis the authors collect their recent results providing the reader with ideas, approaches and methods for processing such data when looking for sub-structures in knowledge bases for an evaluation of functional relationship, e.g. in order to specify diagnostic or control systems. The modelling presented uses ideas from fuzzy set theory and the suggested methods solve problems usually tackled by data analysis if the data are real numbers. Fuzzy Data Analysis is self-contained and is addressed to mathematicians oriented towards applications and to practitioners in any field of application who have some background in mathematics and statistics.

The remarkable discreteness of being

Indian Academy of Sciences (India)

Life is a discrete, stochastic phenomenon: for a biological organism, the time of the two most important events of its life (reproduction and death) is random and these events change the number of individuals of the species by single units. These facts can have surprising, counterintuitive consequences. I review here three ...

Compound Option Pricing under Fuzzy Environment

Directory of Open Access Journals (Sweden)

Xiandong Wang

2014-01-01

Full Text Available Considering the uncertainty of a financial market includes two aspects: risk and vagueness; in this paper, fuzzy sets theory is applied to model the imprecise input parameters (interest rate and volatility. We present the fuzzy price of compound option by fuzzing the interest and volatility in Geske’s compound option pricing formula. For each α, the α-level set of fuzzy prices is obtained according to the fuzzy arithmetics and the definition of fuzzy-valued function. We apply a defuzzification method based on crisp possibilistic mean values of the fuzzy interest rate and fuzzy volatility to obtain the crisp possibilistic mean value of compound option price. Finally, we present a numerical analysis to illustrate the compound option pricing under fuzzy environment.

Fuzzy measures and integrals

Czech Academy of Sciences Publication Activity Database

Mesiar, Radko

2005-01-01

Roč. 28, č. 156 (2005), s. 365-370 ISSN 0165-0114 R&D Projects: GA ČR(CZ) GA402/04/1026 Institutional research plan: CEZ:AV0Z10750506 Keywords : fuzzy measures * fuzzy integral * regular fuzzy integral Subject RIV: BA - General Mathematics Impact factor: 1.039, year: 2005

Fuzzy Control Tutorial

DEFF Research Database (Denmark)

Dotoli, M.; Jantzen, Jan

1999-01-01

The tutorial concerns automatic control of an inverted pendulum, especially rule based control by means of fuzzy logic. A ball balancer, implemented in a software simulator in Matlab, is used as a practical case study. The objectives of the tutorial are to teach the basics of fuzzy control......, and to show how to apply fuzzy logic in automatic control. The tutorial is distance learning, where students interact one-to-one with the teacher using e-mail....

Pemodelan Sistem Fuzzy Dengan Menggunakan Matlab

Directory of Open Access Journals (Sweden)

Afan Galih Salman

2010-12-01

Full Text Available Fuzzy logic is a method in soft computing category, a method that could process uncertain, inaccurate, and less cost implemented data. Some methods in soft computing category besides fuzzy logic are artificial network nerve, probabilistic reasoning, and evolutionary computing. Fuzzy logic has the ability to develop fuzzy system that is intelligent system in uncertain environment. Some stages in fuzzy system formation process is input and output analysis, determining input and output variable, defining each fuzzy set member function, determining rules based on experience or knowledge of an expert in his field, and implementing fuzzy system. Overall, fuzzy logic uses simple mathematical concept, understandable, detectable uncertain and accurate data. Fuzzy system could create and apply expert experiences directly without exercise process and effort to decode the knowledge into a computer until becoming a modeling system that could be relied on decision making.

Integrating Fuzzy AHP and Fuzzy ARAS for evaluating financial performance

Directory of Open Access Journals (Sweden)

Abdolhamid Safaei Ghadikolaei

2014-09-01

Full Text Available Multi Criteria Decision Making (MCDM is an advanced field of Operation Research; recently MCDM methods are efficient and common tools for performance evaluation in many areas such as finance and economy. The aim of this study is to show one of applications of mathematics in real word. This study with considering value based measures and accounting based measures simultaneously, provided a hybrid approach of MCDM methods in fuzzy environment for financial performance evaluation of automotive and parts manufacturing industry of Tehran stock exchange (TSE.for this purpose Fuzzy analytic hierarchy process (FAHP is applied to determine the relative important of each criterion, then The companies are ranked according their financial performance by using fuzzy additive ratio assessment (Fuzzy ARAS method. The finding of this study showed effective of this approach in evaluating financial performance.

The impact of interoperability of electronic health records on ambulatory physician practices: a discrete-event simulation study

Directory of Open Access Journals (Sweden)

Yuan Zhou

2014-02-01

Full Text Available Background The effect of health information technology (HIT on efficiency and workload among clinical and nonclinical staff has been debated, with conflicting evidence about whether electronic health records (EHRs increase or decrease effort. None of this paper to date, however, examines the effect of interoperability quantitatively using discrete event simulation techniques.Objective To estimate the impact of EHR systems with various levels of interoperability on day-to-day tasks and operations of ambulatory physician offices.Methods Interviews and observations were used to collect workflow data from 12 adult primary and specialty practices. A discrete event simulation model was constructed to represent patient flows and clinical and administrative tasks of physicians and staff members.Results High levels of EHR interoperability were associated with reduced time spent by providers on four tasks: preparing lab reports, requesting lab orders, prescribing medications, and writing referrals. The implementation of an EHR was associated with less time spent by administrators but more time spent by physicians, compared with time spent at paper-based practices. In addition, the presence of EHRs and of interoperability did not significantly affect the time usage of registered nurses or the total visit time and waiting time of patients.Conclusion This paper suggests that the impact of using HIT on clinical and nonclinical staff work efficiency varies, however, overall it appears to improve time efficiency more for administrators than for physicians and nurses.

Fuzzy Graph Language Recognizability

OpenAIRE

Kalampakas , Antonios; Spartalis , Stefanos; Iliadis , Lazaros

2012-01-01

Part 5: Fuzzy Logic; International audience; Fuzzy graph language recognizability is introduced along the lines of the established theory of syntactic graph language recognizability by virtue of the algebraic structure of magmoids. The main closure properties of the corresponding class are investigated and several interesting examples of fuzzy graph languages are examined.

A Decision Tool that Combines Discrete Event Software Process Models with System Dynamics Pieces for Software Development Cost Estimation and Analysis

Science.gov (United States)

Mizell, Carolyn Barrett; Malone, Linda

2007-01-01

The development process for a large software development project is very complex and dependent on many variables that are dynamic and interrelated. Factors such as size, productivity and defect injection rates will have substantial impact on the project in terms of cost and schedule. These factors can be affected by the intricacies of the process itself as well as human behavior because the process is very labor intensive. The complex nature of the development process can be investigated with software development process models that utilize discrete event simulation to analyze the effects of process changes. The organizational environment and its effects on the workforce can be analyzed with system dynamics that utilizes continuous simulation. Each has unique strengths and the benefits of both types can be exploited by combining a system dynamics model and a discrete event process model. This paper will demonstrate how the two types of models can be combined to investigate the impacts of human resource interactions on productivity and ultimately on cost and schedule.

Application of fuzzy decision making to countermeasure strategies after a nuclear accident

International Nuclear Information System (INIS)

Liu, X.; Ruan, D.

1996-01-01

In the event of a nuclear accident, any decision on countermeasures to protect the public should be made based upon the basic principles recommended by the International Commission on Radiological Protection. The application of these principles requires that there is a balance between the cost and the averted radiation dose, taking into account many subjective factors such as social/political acceptability, psychological stress, and the confidence of the population in the authorities etc. In the framework of classical methods, it is difficult to quantify human subjective judgements and the uncertainties of data efficiently. Hence, any attempt to find the optimal solution for countermeasure strategies without deliberative sensitivity analysis can be misleading. However, fuzzy sets, with linguistic terms to describe the human subjective judgement and with fuzzy numbers to model the uncertainties of the parameters, can be introduced to eliminate these difficulties. With fuzzy rating, a fuzzy multiple attribute decision making method can rank the possible countermeasure strategies. This paper will describe the procedure of the method and present an illustrative example

Safety critical application of fuzzy control

International Nuclear Information System (INIS)

Schildt, G.H.

1995-01-01

After an introduction into safety terms a short description of fuzzy logic will be given. Especially, for safety critical applications of fuzzy controllers a possible controller structure will be described. The following items will be discussed: Configuration of fuzzy controllers, design aspects like fuzzfiication, inference strategies, defuzzification and types of membership functions. As an example a typical fuzzy rule set will be presented. Especially, real-time behaviour a fuzzy controllers is mentioned. An example of fuzzy controlling for temperature control purpose within a nuclear reactor together with membership functions and inference strategy of such a fuzzy controller will be presented. (author). 4 refs, 17 figs

Radiation protection and fuzzy set theory

International Nuclear Information System (INIS)

Nishiwaki, Y.

1993-01-01

In radiation protection we encounter a variety of sources of uncertainties which are due to fuzziness in our cognition or perception of objects. For systematic treatment of this type of uncertainty, the concepts of fuzzy sets or fuzzy measures could be applied to construct system models, which may take into consideration both subjective or intrinsic fuzziness and objective or extrinsic fuzziness. The theory of fuzzy sets and fuzzy measures is still in a developing stage, but its concept may be applied to various problems of subjective perception of risk, nuclear safety, radiation protection and also to the problems of man-machine interface and human factor engineering or ergonomic

Fuzziness and fuzzy modelling in Bulgaria's energy policy decision-making dilemma

International Nuclear Information System (INIS)

Wang Xingquan

2006-01-01

The decision complexity resulting from imprecision in decision variables and parameters, a major difficulty for conventional decision analysis methods, can be relevantly analysed and modelled by fuzzy logic. Bulgaria's nuclear policy decision-making process implicates such complexity of imprecise nature: stakeholders, criteria, measurement, etc. Given the suitable applicability of fuzzy logic in this case, this article tries to offer a concrete fuzzy paradigm including delimitation of decision space, quantification of imprecise variables, and, of course, parameterisation. (author)

Operational analysis and improvement of a spent nuclear fuel handling and treatment facility using discrete event simulation

International Nuclear Information System (INIS)

Garcia, H.E.

2000-01-01

Spent nuclear fuel handling and treatment often require facilities with a high level of operational complexity. Simulation models can reveal undesirable characteristics and production problems before they become readily apparent during system operations. The value of this approach is illustrated here through an operational study, using discrete event modeling techniques, to analyze the Fuel Conditioning Facility at Argonne National Laboratory and to identify enhanced nuclear waste treatment configurations. The modeling approach and results of what-if studies are discussed. An example on how to improve productivity is presented.

A Fuzzy Approach of the Competition on the Air Transport Market

Science.gov (United States)

Charfeddine, Souhir; DeColigny, Marc; Camino, Felix Mora; Cosenza, Carlos Alberto Nunes

2003-01-01

The aim of this communication is to study with a new scope the conditions of the equilibrium in an air transport market where two competitive airlines are operating. Each airline is supposed to adopt a strategy maximizing its profit while its estimation of the demand has a fuzzy nature. This leads each company to optimize a program of its proposed services (frequency of the flights and ticket prices) characterized by some fuzzy parameters. The case of monopoly is being taken as a benchmark. Classical convex optimization can be used to solve this decision problem. This approach provides the airline with a new decision tool where uncertainty can be taken into account explicitly. The confrontation of the strategies of the companies, in the ease of duopoly, leads to the definition of a fuzzy equilibrium. This concept of fuzzy equilibrium is more general and can be applied to several other domains. The formulation of the optimization problem and the methodological consideration adopted for its resolution are presented in their general theoretical aspect. In the case of air transportation, where the conditions of management of operations are critical, this approach should offer to the manager elements needed to the consolidation of its decisions depending on the circumstances (ordinary, exceptional events,..) and to be prepared to face all possibilities. Keywords: air transportation, competition equilibrium, convex optimization , fuzzy modeling,

Fuzzy combination of fuzzy and switching state-feedback controllers for nonlinear systems subject to parameter uncertainties.

Science.gov (United States)

Lam, H K; Leung, Frank H F

2005-04-01

This paper presents a fuzzy controller, which involves a fuzzy combination of local fuzzy and global switching state-feedback controllers, for nonlinear systems subject to parameter uncertainties with known bounds. The nonlinear system is represented by a fuzzy combined Takagi-Sugeno-Kang model, which is a fuzzy combination of the global and local fuzzy plant models. By combining the local fuzzy and global switching state-feedback controllers using fuzzy logic techniques, the advantages of both controllers can be retained and the undesirable chattering effect introduced by the global switching state-feedback controller can be eliminated. The steady-state error introduced by the global switching state-feedback controller when a saturation function is used can also be removed. Stability conditions, which are related to the system matrices of the local and global closed-loop systems, are derived to guarantee the closed-loop system stability. An application example will be given to demonstrate the merits of the proposed approach.

Inexact nonlinear improved fuzzy chance-constrained programming model for irrigation water management under uncertainty

Science.gov (United States)

Zhang, Chenglong; Zhang, Fan; Guo, Shanshan; Liu, Xiao; Guo, Ping

2018-01-01

An inexact nonlinear mλ-measure fuzzy chance-constrained programming (INMFCCP) model is developed for irrigation water allocation under uncertainty. Techniques of inexact quadratic programming (IQP), mλ-measure, and fuzzy chance-constrained programming (FCCP) are integrated into a general optimization framework. The INMFCCP model can deal with not only nonlinearities in the objective function, but also uncertainties presented as discrete intervals in the objective function, variables and left-hand side constraints and fuzziness in the right-hand side constraints. Moreover, this model improves upon the conventional fuzzy chance-constrained programming by introducing a linear combination of possibility measure and necessity measure with varying preference parameters. To demonstrate its applicability, the model is then applied to a case study in the middle reaches of Heihe River Basin, northwest China. An interval regression analysis method is used to obtain interval crop water production functions in the whole growth period under uncertainty. Therefore, more flexible solutions can be generated for optimal irrigation water allocation. The variation of results can be examined by giving different confidence levels and preference parameters. Besides, it can reflect interrelationships among system benefits, preference parameters, confidence levels and the corresponding risk levels. Comparison between interval crop water production functions and deterministic ones based on the developed INMFCCP model indicates that the former is capable of reflecting more complexities and uncertainties in practical application. These results can provide more reliable scientific basis for supporting irrigation water management in arid areas.

Fuzzy Pheromone Potential Fields for Virtual Pedestrian Simulation

Directory of Open Access Journals (Sweden)

Meriem Mandar

2016-01-01

Full Text Available The study of collective movement of pedestrians is crucial in various situations, such as evacuation of buildings, stadiums, or external events like concerts or public events. In such situations and under panic conditions, several incidents and disasters may arise, resulting in loss of human lives. Hence, the study and modeling of the pedestrians behavior are imperative in both normal and panic situations. In a previous work, we developed a microscopic model for pedestrian movement based on the algorithm of Ant Colonies and the principles of cellular automata. We took advantage of a fuzzy model to better reflect the uncertainty and vagueness of the perception of space to pedestrians, especially to represent the desirability or blurred visibility of virtual pedestrians. This paper uses the mechanism of artificial potential fields. Said fields provide virtual pedestrians with better visibility of their surroundings and its various components (goals and obstacles. The predictions provided by the first-order traffic flow theory are confirmed by the results of the simulation. The advantage of this model lies in the combination of benefits provided by the model of ants and artificial potential fields in a fuzzy modeling, to better understand the perceptions of pedestrians.

[Predicting Incidence of Hepatitis E in Chinausing Fuzzy Time Series Based on Fuzzy C-Means Clustering Analysis].

Science.gov (United States)

Luo, Yi; Zhang, Tao; Li, Xiao-song

2016-05-01

To explore the application of fuzzy time series model based on fuzzy c-means clustering in forecasting monthly incidence of Hepatitis E in mainland China. Apredictive model (fuzzy time series method based on fuzzy c-means clustering) was developed using Hepatitis E incidence data in mainland China between January 2004 and July 2014. The incidence datafrom August 2014 to November 2014 were used to test the fitness of the predictive model. The forecasting results were compared with those resulted from traditional fuzzy time series models. The fuzzy time series model based on fuzzy c-means clustering had 0.001 1 mean squared error (MSE) of fitting and 6.977 5 x 10⁻⁴ MSE of forecasting, compared with 0.0017 and 0.0014 from the traditional forecasting model. The results indicate that the fuzzy time series model based on fuzzy c-means clustering has a better performance in forecasting incidence of Hepatitis E.

The foundations of fuzzy control

CERN Document Server

Lewis, Harold W

1997-01-01

Harold Lewis applied a cross-disciplinary approach in his highly accessible discussion of fuzzy control concepts. With the aid of fifty-seven illustrations, he thoroughly presents a unique mathematical formalism to explain the workings of the fuzzy inference engine and a novel test plant used in the research. Additionally, the text posits a new viewpoint on why fuzzy control is more popular in some countries than in others. A direct and original view of Japanese thinking on fuzzy control methods, based on the author's personal knowledge of - and association with - Japanese fuzzy research, is also included.

Introduction to fuzzy logic using Matlab

CERN Document Server

Sivanandam, SN; Deepa, S N

2006-01-01

Fuzzy Logic, at present is a hot topic, among academicians as well various programmers. This book is provided to give a broad, in-depth overview of the field of Fuzzy Logic. The basic principles of Fuzzy Logic are discussed in detail with various solved examples. The different approaches and solutions to the problems given in the book are well balanced and pertinent to the Fuzzy Logic research projects. The applications of Fuzzy Logic are also dealt to make the readers understand the concept of Fuzzy Logic. The solutions to the problems are programmed using MATLAB 6.0 and the simulated results are given. The MATLAB Fuzzy Logic toolbox is provided for easy reference.

A Fuzzy Query Mechanism for Human Resource Websites

Science.gov (United States)

Lai, Lien-Fu; Wu, Chao-Chin; Huang, Liang-Tsung; Kuo, Jung-Chih

Users' preferences often contain imprecision and uncertainty that are difficult for traditional human resource websites to deal with. In this paper, we apply the fuzzy logic theory to develop a fuzzy query mechanism for human resource websites. First, a storing mechanism is proposed to store fuzzy data into conventional database management systems without modifying DBMS models. Second, a fuzzy query language is proposed for users to make fuzzy queries on fuzzy databases. User's fuzzy requirement can be expressed by a fuzzy query which consists of a set of fuzzy conditions. Third, each fuzzy condition associates with a fuzzy importance to differentiate between fuzzy conditions according to their degrees of importance. Fourth, the fuzzy weighted average is utilized to aggregate all fuzzy conditions based on their degrees of importance and degrees of matching. Through the mutual compensation of all fuzzy conditions, the ordering of query results can be obtained according to user's preference.

Discrete Event Modeling and Simulation-Driven Engineering for the ATLAS Data Acquisition Network

CERN Document Server

Bonaventura, Matias Alejandro; The ATLAS collaboration; Castro, Rodrigo Daniel

2016-01-01

We present an iterative and incremental development methodology for simulation models in network engineering projects. Driven by the DEVS (Discrete Event Systems Specification) formal framework for modeling and simulation we assist network design, test, analysis and optimization processes. A practical application of the methodology is presented for a case study in the ATLAS particle physics detector, the largest scientific experiment built by man where scientists around the globe search for answers about the origins of the universe. The ATLAS data network convey real-time information produced by physics detectors as beams of particles collide. The produced sub-atomic evidences must be filtered and recorded for further offline scrutiny. Due to the criticality of the transported data, networks and applications undergo careful engineering processes with stringent quality of service requirements. A tight project schedule imposes time pressure on design decisions, while rapid technology evolution widens the palett...

Fault location in underground cables using ANFIS nets and discrete wavelet transform

Directory of Open Access Journals (Sweden)

Shimaa Barakat

2014-12-01

Full Text Available This paper presents an accurate algorithm for locating faults in a medium voltage underground power cable using a combination of Adaptive Network-Based Fuzzy Inference System (ANFIS and discrete wavelet transform (DWT. The proposed method uses five ANFIS networks and consists of 2 stages, including fault type classification and exact fault location. In the first part, an ANFIS is used to determine the fault type, applying four inputs, i.e., the maximum detailed energy of three phase and zero sequence currents. Other four ANFIS networks are utilized to pinpoint the faults (one for each fault type. Four inputs, i.e., the maximum detailed energy of three phase and zero sequence currents, are used to train the neuro-fuzzy inference systems in order to accurately locate the faults on the cable. The proposed method is evaluated under different fault conditions such as different fault locations, different fault inception angles and different fault resistances.

Fuzzy Rough Ring and Its Prop erties

Institute of Scientific and Technical Information of China (English)

REN Bi-jun; FU Yan-ling

2013-01-01

This paper is devoted to the theories of fuzzy rough ring and its properties. The fuzzy approximation space generated by fuzzy ideals and the fuzzy rough approximation operators were proposed in the frame of fuzzy rough set model. The basic properties of fuzzy rough approximation operators were analyzed and the consistency between approximation operators and the binary operation of ring was discussed.

CHARACTERIZATIONS OF FUZZY SOFT PRE SEPARATION AXIOMS

OpenAIRE

El-Latif, Alaa Mohamed Abd

2015-01-01

− The notions of fuzzy pre open soft sets and fuzzy pre closed soft sets were introducedby Abd El-latif et al. [2]. In this paper, we continue the study on fuzzy soft topological spaces andinvestigate the properties of fuzzy pre open soft sets, fuzzy pre closed soft sets and study variousproperties and notions related to these structures. In particular, we study the relationship betweenfuzzy pre soft interior fuzzy pre soft closure. Moreover, we study the properties of fuzzy soft pre regulars...

Fuzzy Constraint-Based Agent Negotiation

Institute of Scientific and Technical Information of China (English)

Menq-Wen Lin; K. Robert Lai; Ting-Jung Yu

2005-01-01

Conflicts between two or more parties arise for various reasons and perspectives. Thus, resolution of conflicts frequently relies on some form of negotiation. This paper presents a general problem-solving framework for modeling multi-issue multilateral negotiation using fuzzy constraints. Agent negotiation is formulated as a distributed fuzzy constraint satisfaction problem (DFCSP). Fuzzy constrains are thus used to naturally represent each agent's desires involving imprecision and human conceptualization, particularly when lexical imprecision and subjective matters are concerned. On the other hand, based on fuzzy constraint-based problem-solving, our approach enables an agent not only to systematically relax fuzzy constraints to generate a proposal, but also to employ fuzzy similarity to select the alternative that is subject to its acceptability by the opponents. This task of problem-solving is to reach an agreement that benefits all agents with a high satisfaction degree of fuzzy constraints, and move towards the deal more quickly since their search focuses only on the feasible solution space. An application to multilateral negotiation of a travel planning is provided to demonstrate the usefulness and effectiveness of our framework.

Fuzzy Commitment

Science.gov (United States)

Juels, Ari

The purpose of this chapter is to introduce fuzzy commitment, one of the earliest and simplest constructions geared toward cryptography over noisy data. The chapter also explores applications of fuzzy commitment to two problems in data security: (1) secure management of biometrics, with a focus on iriscodes, and (2) use of knowledge-based authentication (i.e., personal questions) for password recovery.

Event-by-event simulation of quantum phenomena

NARCIS (Netherlands)

De Raedt, Hans; Michielsen, Kristel

A discrete-event simulation approach is reviewed that does not require the knowledge of the solution of the wave equation of the whole system, yet reproduces the statistical distributions of wave theory by generating detection events one-by-one. The simulation approach is illustrated by applications

Multi-dimensional Fuzzy Euler Approximation

Directory of Open Access Journals (Sweden)

Yangyang Hao

2017-05-01

Full Text Available Multi-dimensional Fuzzy differential equations driven by multi-dimen-sional Liu process, have been intensively applied in many fields. However, we can not obtain the analytic solution of every multi-dimensional fuzzy differential equation. Then, it is necessary for us to discuss the numerical results in most situations. This paper focuses on the numerical method of multi-dimensional fuzzy differential equations. The multi-dimensional fuzzy Taylor expansion is given, based on this expansion, a numerical method which is designed for giving the solution of multi-dimensional fuzzy differential equation via multi-dimensional Euler method will be presented, and its local convergence also will be discussed.

Fuzzy Control Teaching Models

Directory of Open Access Journals (Sweden)

Klaus-Dietrich Kramer

2016-05-01

Full Text Available Many degree courses at technical universities include the subject of control systems engineering. As an addition to conventional approaches Fuzzy Control can be used to easily find control solutions for systems, even if they include nonlinearities. To support further educational training, models which represent a technical system to be controlled are required. These models have to represent the system in a transparent and easy cognizable manner. Furthermore, a programming tool is required that supports an easy Fuzzy Control development process, including the option to verify the results and tune the system behavior. In order to support the development process a graphical user interface is needed to display the fuzzy terms under real time conditions, especially with a debug system and trace functionality. The experiences with such a programming tool, the Fuzzy Control Design Tool (FHFCE Tool, and four fuzzy teaching models will be presented in this paper. The methodical and didactical objective in the utilization of these teaching models is to develop solution strategies using Computational Intelligence (CI applications for Fuzzy Controllers in order to analyze different algorithms of inference or defuzzyfication and to verify and tune those systems efficiently.

Fuzzy statistical decision-making theory and applications

CERN Document Server

Kabak, Özgür

2016-01-01

This book offers a comprehensive reference guide to fuzzy statistics and fuzzy decision-making techniques. It provides readers with all the necessary tools for making statistical inference in the case of incomplete information or insufficient data, where classical statistics cannot be applied. The respective chapters, written by prominent researchers, explain a wealth of both basic and advanced concepts including: fuzzy probability distributions, fuzzy frequency distributions, fuzzy Bayesian inference, fuzzy mean, mode and median, fuzzy dispersion, fuzzy p-value, and many others. To foster a better understanding, all the chapters include relevant numerical examples or case studies. Taken together, they form an excellent reference guide for researchers, lecturers and postgraduate students pursuing research on fuzzy statistics. Moreover, by extending all the main aspects of classical statistical decision-making to its fuzzy counterpart, the book presents a dynamic snapshot of the field that is expected to stimu...

Comparative Effectiveness of Tacrolimus-Based Steroid Sparing versus Steroid Maintenance Regimens in Kidney Transplantation: Results from Discrete Event Simulation.

Science.gov (United States)

Desai, Vibha C A; Ferrand, Yann; Cavanaugh, Teresa M; Kelton, Christina M L; Caro, J Jaime; Goebel, Jens; Heaton, Pamela C

2017-10-01

Corticosteroids used as immunosuppressants to prevent acute rejection (AR) and graft loss (GL) following kidney transplantation are associated with serious cardiovascular and other adverse events. Evidence from short-term randomized controlled trials suggests that many patients on a tacrolimus-based immunosuppressant regimen can withdraw from steroids without increased AR or GL risk. To measure the long-term tradeoff between GL and adverse events for a heterogeneous-risk population and determine the optimal timing of steroid withdrawal. A discrete event simulation was developed including, as events, AR, GL, myocardial infarction (MI), stroke, cytomegalovirus, and new onset diabetes mellitus (NODM), among others. Data from the United States Renal Data System were used to estimate event-specific parametric regressions, which accounted for steroid-sparing regimen (avoidance, early 7-d withdrawal, 6-mo withdrawal, 12-mo withdrawal, and maintenance) as well as patients' demographics, immunologic risks, and comorbidities. Regression-equation results were used to derive individual time-to-event Weibull distributions, used, in turn, to simulate the course of patients over 20 y. Patients on steroid avoidance or an early-withdrawal regimen were more likely to experience AR (45.9% to 55.0% v. 33.6%, P events and other outcomes with no worsening of AR or GL rates compared with steroid maintenance.

Fuzzy Clustering Methods and their Application to Fuzzy Modeling

DEFF Research Database (Denmark)

Kroszynski, Uri; Zhou, Jianjun

1999-01-01

Fuzzy modeling techniques based upon the analysis of measured input/output data sets result in a set of rules that allow to predict system outputs from given inputs. Fuzzy clustering methods for system modeling and identification result in relatively small rule-bases, allowing fast, yet accurate....... An illustrative synthetic example is analyzed, and prediction accuracy measures are compared between the different variants...

An essay on discrete foundations for physics

International Nuclear Information System (INIS)

Noyes, H.P.; McGoveran, D.O.

1988-07-01

We base our theory of physics and cosmology on the five principles of finiteness, discreteness, finite computability, absolute non-uniqueness, and strict construction. Our modeling methodology starts from the current practice of physics, constructs a self-consistent representation based on the ordering operator calculus and provides rules of correspondence that allow us to test the theory by experiment. We use program universe to construct a growing collection of bit strings whose initial portions (labels) provide the quantum numbers that are conserved in the events defined by the construction. The labels are followed by content strings which are used to construct event-based finite and discrete coordinates. On general grounds such a theory has a limiting velocity, and positions and velocities do not commute. We therefore reconcile quantum mechanics with relativity at an appropriately fundamental stage in the construction. We show that events in different coordinate systems are connected by the appropriate finite and discrete version of the Lorentz transformation, that 3-momentum is conserved in events, and that this conservation law is the same as the requirement that different paths can ''interfere'' only when they differ by an integral number of deBroglie wavelengths. 38 refs., 12 figs., 3 tabs

An essay on discrete foundations for physics

International Nuclear Information System (INIS)

Noyes, H.P.; McGoveran, D.O.

1988-01-01

We base our theory of physics and cosmology on the five principles of finiteness, discreteness, finite computability, absolute non- uniqueness, and strict construction. Our modeling methodology starts from the current practice of physics, constructs a self-consistent representation based on the ordering operator calculus and provides rules of correspondence that allow us to test the theory by experiment. We use program universe to construct a growing collection of bit strings whose initial portions (labels) provide the quantum numbers that are conserved in the events defined by the construction. The labels are followed by content strings which are used to construct event-based finite and discrete coordinates. On general grounds such a theory has a limiting velocity, and positions and velocities do not commute. We therefore reconcile quantum mechanics with relativity at an appropriately fundamental stage in the construction. We show that events in different coordinate systems are connected by the appropriate finite and discrete version of the Lorentz transformation, that 3-momentum is conserved in events, and that this conservation law is the same as the requirement that different paths can ''interfere'' only when they differ by an integral number of deBroglie wavelengths. 38 refs., 12 figs., 3 tabs

An essay on discrete foundations for physics

Energy Technology Data Exchange (ETDEWEB)

Noyes, H.P.; McGoveran, D.O.

1988-07-01

We base our theory of physics and cosmology on the five principles of finiteness, discreteness, finite computability, absolute non-uniqueness, and strict construction. Our modeling methodology starts from the current practice of physics, constructs a self-consistent representation based on the ordering operator calculus and provides rules of correspondence that allow us to test the theory by experiment. We use program universe to construct a growing collection of bit strings whose initial portions (labels) provide the quantum numbers that are conserved in the events defined by the construction. The labels are followed by content strings which are used to construct event-based finite and discrete coordinates. On general grounds such a theory has a limiting velocity, and positions and velocities do not commute. We therefore reconcile quantum mechanics with relativity at an appropriately fundamental stage in the construction. We show that events in different coordinate systems are connected by the appropriate finite and discrete version of the Lorentz transformation, that 3-momentum is conserved in events, and that this conservation law is the same as the requirement that different paths can ''interfere'' only when they differ by an integral number of deBroglie wavelengths. 38 refs., 12 figs., 3 tabs.

An essay on discrete foundations for physics

Energy Technology Data Exchange (ETDEWEB)

Noyes, H.P.; McGoveran, D.O.

1988-10-05

We base our theory of physics and cosmology on the five principles of finiteness, discreteness, finite computability, absolute non- uniqueness, and strict construction. Our modeling methodology starts from the current practice of physics, constructs a self-consistent representation based on the ordering operator calculus and provides rules of correspondence that allow us to test the theory by experiment. We use program universe to construct a growing collection of bit strings whose initial portions (labels) provide the quantum numbers that are conserved in the events defined by the construction. The labels are followed by content strings which are used to construct event-based finite and discrete coordinates. On general grounds such a theory has a limiting velocity, and positions and velocities do not commute. We therefore reconcile quantum mechanics with relativity at an appropriately fundamental stage in the construction. We show that events in different coordinate systems are connected by the appropriate finite and discrete version of the Lorentz transformation, that 3-momentum is conserved in events, and that this conservation law is the same as the requirement that different paths can ''interfere'' only when they differ by an integral number of deBroglie wavelengths. 38 refs., 12 figs., 3 tabs.

A computationally efficient fuzzy control s

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Abdel Badie Sharkawy

2013-12-01

Full Text Available This paper develops a decentralized fuzzy control scheme for MIMO nonlinear second order systems with application to robot manipulators via a combination of genetic algorithms (GAs and fuzzy systems. The controller for each degree of freedom (DOF consists of a feedforward fuzzy torque computing system and a feedback fuzzy PD system. The feedforward fuzzy system is trained and optimized off-line using GAs, whereas not only the parameters but also the structure of the fuzzy system is optimized. The feedback fuzzy PD system, on the other hand, is used to keep the closed-loop stable. The rule base consists of only four rules per each DOF. Furthermore, the fuzzy feedback system is decentralized and simplified leading to a computationally efficient control scheme. The proposed control scheme has the following advantages: (1 it needs no exact dynamics of the system and the computation is time-saving because of the simple structure of the fuzzy systems and (2 the controller is robust against various parameters and payload uncertainties. The computational complexity of the proposed control scheme has been analyzed and compared with previous works. Computer simulations show that this controller is effective in achieving the control goals.

Shapley's value for fuzzy games

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Raúl Alvarado Sibaja

2009-02-01

Full Text Available This is the continuation of a previous article titled "Fuzzy Games", where I defined a new type of games based on the Multilinear extensions f, of characteristic functions and most of standard theorems for cooperative games also hold for this new type of games: The fuzzy games. Now we give some other properties and the extension of the definition of Shapley¨s Value for Fuzzy Games Keywords: game theory, fuzzy sets, multiattribute decisions.

Discrete Event Simulation Method as a Tool for Improvement of Manufacturing Systems

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Adrian Kampa

2017-02-01

Full Text Available The problem of production flow in manufacturing systems is analyzed. The machines can be operated by workers or by robots, since breakdowns and human factors destabilize the production processes that robots are preferred to perform. The problem is how to determine the real difference in work efficiency between humans and robots. We present an analysis of the production efficiency and reliability of the press shop lines operated by human operators or industrial robots. This is a problem from the field of Operations Research for which the Discrete Event Simulation (DES method has been used. Three models have been developed, including the manufacturing line before and after robotization, taking into account stochastic parameters of availability and reliability of the machines, operators, and robots. We apply the OEE (Overall Equipment Effectiveness indicator to present how the availability, reliability, and quality parameters influence the performance of the workstations, especially in the short run and in the long run. In addition, the stability of the simulation model was analyzed. This approach enables a better representation of real manufacturing processes.

FFLP problem with symmetric trapezoidal fuzzy numbers

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Reza Daneshrad

2015-04-01

Full Text Available The most popular approach for solving fully fuzzy linear programming (FFLP problems is to convert them into the corresponding deterministic linear programs. Khan et al. (2013 [Khan, I. U., Ahmad, T., & Maan, N. (2013. A simplified novel technique for solving fully fuzzy linear programming problems. Journal of Optimization Theory and Applications, 159(2, 536-546.] claimed that there had been no method in the literature to find the fuzzy optimal solution of a FFLP problem without converting it into crisp linear programming problem, and proposed a technique for the same. Others showed that the fuzzy arithmetic operation used by Khan et al. (2013 had some problems in subtraction and division operations, which could lead to misleading results. Recently, Ezzati et al. (2014 [Ezzati, R., Khorram, E., & Enayati, R. (2014. A particular simplex algorithm to solve fuzzy lexicographic multi-objective linear programming problems and their sensitivity analysis on the priority of the fuzzy objective functions. Journal of Intelligent and Fuzzy Systems, 26(5, 2333-2358.] defined a new operation on symmetric trapezoidal fuzzy numbers and proposed a new algorithm to find directly a lexicographic/preemptive fuzzy optimal solution of a fuzzy lexicographic multi-objective linear programming problem by using new fuzzy arithmetic operations, but their model was not fully fuzzy optimization. In this paper, a new method, by using Ezzati et al. (2014’s fuzzy arithmetic operation and a fuzzy version of simplex algorithm, is proposed for solving FFLP problem whose parameters are represented by symmetric trapezoidal fuzzy number without converting the given problem into crisp equivalent problem. By using the proposed method, the fuzzy optimal solution of FFLP problem can be easily obtained. A numerical example is provided to illustrate the proposed method.

T-S Fuzzy Model Based Control Strategy for the Networked Suspension Control System of Maglev Train

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Guang He

2015-01-01

Full Text Available The control problem for the networked suspension control system of maglev train with random induced time delay and packet dropouts is investigated. First, Takagi-Sugeno (T-S fuzzy models are utilized to represent the discrete-time nonlinear networked suspension control system, and the parameters uncertainties of the nonlinear model have also been taken into account. The controllers take the form of parallel distributed compensation. Then, a sufficient condition for the stability of the networked suspension control system is derived. Based on the criteria, the state feedback fuzzy controllers are obtained, and the controller gains can be computed by using MATLAB LMI Toolbox directly. Finally, both the numerical simulations and physical experiments on the full-scale single bogie of CMS-04 maglev train have been accomplished to demonstrate the effectiveness of this proposed method.

Effectiveness of Securities with Fuzzy Probabilistic Return

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Krzysztof Piasecki

2011-01-01

Full Text Available The generalized fuzzy present value of a security is defined here as fuzzy valued utility of cash flow. The generalized fuzzy present value cannot depend on the value of future cash flow. There exists such a generalized fuzzy present value which is not a fuzzy present value in the sense given by some authors. If the present value is a fuzzy number and the future value is a random one, then the return rate is given as a probabilistic fuzzy subset on a real line. This kind of return rate is called a fuzzy probabilistic return. The main goal of this paper is to derive the family of effective securities with fuzzy probabilistic return. Achieving this goal requires the study of the basic parameters characterizing fuzzy probabilistic return. Therefore, fuzzy expected value and variance are determined for this case of return. These results are a starting point for constructing a three-dimensional image. The set of effective securities is introduced as the Pareto optimal set determined by the maximization of the expected return rate and minimization of the variance. Finally, the set of effective securities is distinguished as a fuzzy set. These results are obtained without the assumption that the distribution of future values is Gaussian. (original abstract

Application of fuzzy logic to social choice theory

CERN Document Server

Mordeson, John N; Clark, Terry D

2015-01-01

Fuzzy social choice theory is useful for modeling the uncertainty and imprecision prevalent in social life yet it has been scarcely applied and studied in the social sciences. Filling this gap, Application of Fuzzy Logic to Social Choice Theory provides a comprehensive study of fuzzy social choice theory.The book explains the concept of a fuzzy maximal subset of a set of alternatives, fuzzy choice functions, the factorization of a fuzzy preference relation into the ""union"" (conorm) of a strict fuzzy relation and an indifference operator, fuzzy non-Arrowian results, fuzzy versions of Arrow's

Implementation of Steiner point of fuzzy set.

Science.gov (United States)

Liang, Jiuzhen; Wang, Dejiang

2014-01-01

This paper deals with the implementation of Steiner point of fuzzy set. Some definitions and properties of Steiner point are investigated and extended to fuzzy set. This paper focuses on establishing efficient methods to compute Steiner point of fuzzy set. Two strategies of computing Steiner point of fuzzy set are proposed. One is called linear combination of Steiner points computed by a series of crisp α-cut sets of the fuzzy set. The other is an approximate method, which is trying to find the optimal α-cut set approaching the fuzzy set. Stability analysis of Steiner point of fuzzy set is also studied. Some experiments on image processing are given, in which the two methods are applied for implementing Steiner point of fuzzy image, and both strategies show their own advantages in computing Steiner point of fuzzy set.

On Modeling the Behavior of Comparators for Complex Fuzzy Objects in a Fuzzy Object-Relational Database Management System

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JuanM. Medina

2012-08-01

Full Text Available This paper proposes a parameterized definition for fuzzy comparators on complex fuzzy datatypes like fuzzy collections with conjunctive semantics and fuzzy objects. This definition and its implementation on a Fuzzy Object-Relational Database Management System (FORDBMS provides the designer with a powerful tool to adapt the behavior of these operators to the semantics of the considered application.

Metamathematics of fuzzy logic

CERN Document Server

Hájek, Petr

1998-01-01

This book presents a systematic treatment of deductive aspects and structures of fuzzy logic understood as many valued logic sui generis. Some important systems of real-valued propositional and predicate calculus are defined and investigated. The aim is to show that fuzzy logic as a logic of imprecise (vague) propositions does have well-developed formal foundations and that most things usually named `fuzzy inference' can be naturally understood as logical deduction.

A New Multidisciplinary Design Optimization Method Accounting for Discrete and Continuous Variables under Aleatory and Epistemic Uncertainties

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Hong-Zhong Huang

2012-02-01

Full Text Available Various uncertainties are inevitable in complex engineered systems and must be carefully treated in design activities. Reliability-Based Multidisciplinary Design Optimization (RBMDO has been receiving increasing attention in the past decades to facilitate designing fully coupled systems but also achieving a desired reliability considering uncertainty. In this paper, a new formulation of multidisciplinary design optimization, namely RFCDV (random/fuzzy/continuous/discrete variables Multidisciplinary Design Optimization (RFCDV-MDO, is developed within the framework of Sequential Optimization and Reliability Assessment (SORA to deal with multidisciplinary design problems in which both aleatory and epistemic uncertainties are present. In addition, a hybrid discrete-continuous algorithm is put forth to efficiently solve problems where both discrete and continuous design variables exist. The effectiveness and computational efficiency of the proposed method are demonstrated via a mathematical problem and a pressure vessel design problem.

Comparison between genetic fuzzy system and neuro fuzzy system to select oil wells for hydraulic fracturing; Comparacao entre genetic fuzzy system e neuro fuzzy system para selecao de pocos de petroleo para fraturamento hidraulico

Energy Technology Data Exchange (ETDEWEB)

Castro, Antonio Orestes de Salvo [PETROBRAS, Rio de Janeiro, RJ (Brazil); Ferreira Filho, Virgilio Jose Martins [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil)

2004-07-01

The hydraulic fracture operation is wide used to increase the oil wells production and to reduce formation damage. Reservoir studies and engineer analysis are made to select the wells for this kind of operation. As the reservoir parameters have some diffuses characteristics, Fuzzy Inference Systems (SIF) have been tested for this selection processes in the last few years. This paper compares the performance of a neuro fuzzy system and a genetic fuzzy system used for hydraulic Fracture well selection, with knowledge acquisition from an operational data base to set the SIF membership functions. The training data and the validation data used were the same for both systems. We concluded that, in despite of the genetic fuzzy system would be a younger process, it got better results than the neuro fuzzy system. Another conclusion was that, as the genetic fuzzy system can work with constraints, the membership functions setting kept the consistency of variables linguistic values. (author)

Construction of fuzzy automata by fuzzy experiments

International Nuclear Information System (INIS)

Mironov, A.

1994-01-01

The solving the problem of canonical realization of partial reaction morphisms (PRM) for automata in toposes and fuzzy automata is addressed. This problem extends the optimal construction problem for finite deterministic automata by experiments. In the present paper the conception of canonical realization of PRM for automata in toposes is introduced and the sufficient conditions for the existence of canonical realizations for PRM in toposes are presented. As a consequence of this result the existence of canonical realizations for PRM in the category of fuzzy sets over arbitrary complete chain is proven

Construction of fuzzy automata by fuzzy experiments

Energy Technology Data Exchange (ETDEWEB)

Mironov, A [Moscow Univ. (Russian Federation). Dept. of Mathematics and Computer Science

1994-12-31

The solving the problem of canonical realization of partial reaction morphisms (PRM) for automata in toposes and fuzzy automata is addressed. This problem extends the optimal construction problem for finite deterministic automata by experiments. In the present paper the conception of canonical realization of PRM for automata in toposes is introduced and the sufficient conditions for the existence of canonical realizations for PRM in toposes are presented. As a consequence of this result the existence of canonical realizations for PRM in the category of fuzzy sets over arbitrary complete chain is proven.

DYNAMIC AUTHORIZATION BASED ON THE HISTORY OF EVENTS

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Maxim V. Baklanovsky

2016-11-01

Full Text Available The new paradigm in the field of access control systems with fuzzy authorization is proposed. Let there is a set of objects in a single data transmissionnetwork. The goal is to develop dynamic authorization protocol based on correctness of presentation of events (news occurred earlier in the network. We propose mathematical method that keeps compactly the history of events, neglects more distant and least-significant events, composes and verifies authorization data. The history of events is represented as vectors of numbers. Each vector is multiplied by several stochastic vectors. The result is known that if vectors of events are sparse, then by solving the problem of -optimization they can be restored with high accuracy. Results of experiments for vectors restoring have shown that the greater the number of stochastic vectors is, the better accuracy of restored vectors is observed. It has been established that the largest absolute components are restored earlier. Access control system with the proposed dynamic authorization method enables to compute fuzzy confidence coefficients in networks with frequently changing set of participants, mesh-networks, multi-agent systems.

Image matching navigation based on fuzzy information

Institute of Scientific and Technical Information of China (English)

田玉龙; 吴伟仁; 田金文; 柳健

2003-01-01

In conventional image matching methods, the image matching process is mostly based on image statistic information. One aspect neglected by all these methods is that there is much fuzzy information contained in these images. A new fuzzy matching algorithm based on fuzzy similarity for navigation is presented in this paper. Because the fuzzy theory is of the ability of making good description of the fuzzy information contained in images, the image matching method based on fuzzy similarity would look forward to producing good performance results. Experimental results using matching algorithm based on fuzzy information also demonstrate its reliability and practicability.

Model predictive control-based scheduler for repetitive discrete event systems with capacity constraints

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Hiroyuki Goto

2013-07-01

Full Text Available A model predictive control-based scheduler for a class of discrete event systems is designed and developed. We focus on repetitive, multiple-input, multiple-output, and directed acyclic graph structured systems on which capacity constraints can be imposed. The target system’s behaviour is described by linear equations in max-plus algebra, referred to as state-space representation. Assuming that the system’s performance can be improved by paying additional cost, we adjust the system parameters and determine control inputs for which the reference output signals can be observed. The main contribution of this research is twofold, 1: For systems with capacity constraints, we derived an output prediction equation as functions of adjustable variables in a recursive form, 2: Regarding the construct for the system’s representation, we improved the structure to accomplish general operations which are essential for adjusting the system parameters. The result of numerical simulation in a later section demonstrates the effectiveness of the developed controller.

Improving Energy Efficiency for the Vehicle Assembly Industry: A Discrete Event Simulation Approach

Science.gov (United States)

Oumer, Abduaziz; Mekbib Atnaw, Samson; Kie Cheng, Jack; Singh, Lakveer

2016-11-01

This paper presented a Discrete Event Simulation (DES) model for investigating and improving energy efficiency in vehicle assembly line. The car manufacturing industry is one of the highest energy consuming industries. Using Rockwell Arena DES package; a detailed model was constructed for an actual vehicle assembly plant. The sources of energy considered in this research are electricity and fuel; which are the two main types of energy sources used in a typical vehicle assembly plant. The model depicts the performance measurement for process- specific energy measures of painting, welding, and assembling processes. Sound energy efficiency model within this industry has two-fold advantage: reducing CO2 emission and cost reduction associated with fuel and electricity consumption. The paper starts with an overview of challenges in energy consumption within the facilities of automotive assembly line and highlights the parameters for energy efficiency. The results of the simulation model indicated improvements for energy saving objectives and reduced costs.

The impact of inpatient boarding on ED efficiency: a discrete-event simulation study.

Science.gov (United States)

Bair, Aaron E; Song, Wheyming T; Chen, Yi-Chun; Morris, Beth A

2010-10-01

In this study, a discrete-event simulation approach was used to model Emergency Department's (ED) patient flow to investigate the effect of inpatient boarding on the ED efficiency in terms of the National Emergency Department Crowding Scale (NEDOCS) score and the rate of patients who leave without being seen (LWBS). The decision variable in this model was the boarder-released-ratio defined as the ratio of admitted patients whose boarding time is zero to all admitted patients. Our analysis shows that the Overcrowded(+) (a NEDOCS score over 100) ratio decreased from 88.4% to 50.4%, and the rate of LWBS patients decreased from 10.8% to 8.4% when the boarder-released-ratio changed from 0% to 100%. These results show that inpatient boarding significantly impacts both the NEDOCS score and the rate of LWBS patient and this analysis provides a quantification of the impact of boarding on emergency department patient crowding.

A Generic Discrete-Event Simulation Model for Outpatient Clinics in a Large Public Hospital

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Waressara Weerawat

2013-01-01

Full Text Available The orthopedic outpatient department (OPD ward in a large Thai public hospital is modeled using Discrete-Event Stochastic (DES simulation. Key Performance Indicators (KPIs are used to measure effects across various clinical operations during different shifts throughout the day. By considering various KPIs such as wait times to see doctors, percentage of patients who can see a doctor within a target time frame, and the time that the last patient completes their doctor consultation, bottlenecks are identified and resource-critical clinics can be prioritized. The simulation model quantifies the chronic, high patient congestion that is prevalent amongst Thai public hospitals with very high patient-to-doctor ratios. Our model can be applied across five different OPD wards by modifying the model parameters. Throughout this work, we show how DES models can be used as decision-support tools for hospital management.

Fuzzy Entropy： Axiomatic Definition and Neural Networks Model

Institute of Scientific and Technical Information of China (English)

QINGMing; CAOYue; HUANGTian-min

2004-01-01

The measure of uncertainty is adopted as a measure of information. The measures of fuzziness are known as fuzzy information measures. The measure of a quantity of fuzzy information gained from a fuzzy set or fuzzy system is known as fuzzy entropy. Fuzzy entropy has been focused and studied by many researchers in various fields. In this paper, firstly, the axiomatic definition of fuzzy entropy is discussed. Then, neural networks model of fuzzy entropy is proposed, based on the computing capability of neural networks. In the end, two examples are discussed to show the efficiency of the model.

On Intuitionistic Fuzzy Context-Free Languages

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Jianhua Jin

2013-01-01

automata theory. Additionally, we introduce the concepts of Chomsky normal form grammar (IFCNF and Greibach normal form grammar (IFGNF based on intuitionistic fuzzy sets. The results of our study indicate that intuitionistic fuzzy context-free languages generated by IFCFGs are equivalent to those generated by IFGNFs and IFCNFs, respectively, and they are also equivalent to intuitionistic fuzzy recognizable step functions. Then some operations on the family of intuitionistic fuzzy context-free languages are discussed. Finally, pumping lemma for intuitionistic fuzzy context-free languages is investigated.

Fuzzy Evidence in Identification, Forecasting and Diagnosis

CERN Document Server

Rotshtein, Alexander P

2012-01-01

The purpose of this book is to present a methodology for designing and tuning fuzzy expert systems in order to identify nonlinear objects; that is, to build input-output models using expert and experimental information. The results of these identifications are used for direct and inverse fuzzy evidence in forecasting and diagnosis problem solving. The book is organised as follows: Chapter 1 presents the basic knowledge about fuzzy sets, genetic algorithms and neural nets necessary for a clear understanding of the rest of this book. Chapter 2 analyzes direct fuzzy inference based on fuzzy if-then rules. Chapter 3 is devoted to the tuning of fuzzy rules for direct inference using genetic algorithms and neural nets. Chapter 4 presents models and algorithms for extracting fuzzy rules from experimental data. Chapter 5 describes a method for solving fuzzy logic equations necessary for the inverse fuzzy inference in diagnostic systems. Chapters 6 and 7 are devoted to inverse fuzzy inference based on fu...

Fuzzy promises

DEFF Research Database (Denmark)

Anker, Thomas Boysen; Kappel, Klemens; Eadie, Douglas

2012-01-01

as narrative material to communicate self-identity. Finally, (c) we propose that brands deliver fuzzy experiential promises through effectively motivating consumers to adopt and play a social role implicitly suggested and facilitated by the brand. A promise is an inherently ethical concept and the article...... concludes with an in-depth discussion of fuzzy brand promises as two-way ethical commitments that put requirements on both brands and consumers....

A Temporal Fuzzy Logic Formalism for Knowledge Based Systems

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Vasile MAZILESCU

2012-11-01

Full Text Available This paper shows that the influence of knowledge on new forms of work organisation can be described as mutual relationships. Different changes in work organisation also have a strong influence on the increasing importance of knowledge of different individual and collective actors in working situations. After that, we characterize a piece of basic formal system, an Extended Fuzzy Logic System (EFLS with temporal attributes, to conceptualize future DKMSs based on human imprecise for distributed just in time decisions. The approximate reasoning is perceived as a derivation of new formulas with the corresponding temporal attributes, within a fuzzy theory defined by the fuzzy set of special axioms. In a management application, the reasoning is evolutionary because of unexpected events which may change the state of the DKMS. In this kind of situations it is necessary to elaborate certain mechanisms in order to maintain the coherence of the obtained conclusions, to figure out their degree of reliability and the time domain for which these are true. These last aspects stand as possible further directions of development at a basic logic level for future technologies that must automate knowledge organizational processes.

On Intuitionistic Fuzzy Sets Theory

CERN Document Server

Atanassov, Krassimir T

2012-01-01

This book aims to be a  comprehensive and accurate survey of state-of-art research on intuitionistic fuzzy sets theory and could be considered a continuation and extension of the author´s previous book on Intuitionistic Fuzzy Sets, published by Springer in 1999 (Atanassov, Krassimir T., Intuitionistic Fuzzy Sets, Studies in Fuzziness and soft computing, ISBN 978-3-7908-1228-2, 1999). Since the aforementioned  book has appeared, the research activity of the author within the area of intuitionistic fuzzy sets has been expanding into many directions. The results of the author´s most recent work covering the past 12 years as well as the newest general ideas and open problems in this field have been therefore collected in this new book.

The first order fuzzy predicate logic (I)

International Nuclear Information System (INIS)

Sheng, Y.M.

1986-01-01

Some analysis tools of fuzzy measures, Sugeno's integrals, etc. are introduced into the semantic of the first order predicate logic to explain the concept of fuzzy quantifiers. The truth value of a fuzzy quantification proposition is represented by Sugeno's integral. With this framework, several important notions of formation rules, fuzzy valutions and fuzzy validity are discussed

Theta-Generalized closed sets in fuzzy topological spaces

International Nuclear Information System (INIS)

El-Shafei, M.E.; Zakari, A.

2006-01-01

In this paper we introduce the concepts of theta-generalized closed fuzzy sets and generalized fuzzy sets in topological spaces. Furthermore, generalized fuzzy sets are extended to theta-generalized fuzzy sets. Also, we introduce the concepts of fuzzy theta-generalized continuous and fuzzy theta-generalized irresolute mappings. (author)

A new fuzzy regression model based on interval-valued fuzzy neural network and its applications to management

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Somaye Yeylaghi

2017-06-01

Full Text Available In this paper, a novel hybrid method based on interval-valued fuzzy neural network for approximate of interval-valued fuzzy regression models, is presented. The work of this paper is an expansion of the research of real fuzzy regression models. In this paper interval-valued fuzzy neural network (IVFNN can be trained with crisp and interval-valued fuzzy data. Here a neural network is considered as a part of a large field called neural computing or soft computing. Moreover, in order to find the approximate parameters, a simple algorithm from the cost function of the fuzzy neural network is proposed. Finally, we illustrate our approach by some numerical examples and compare this method with existing methods.

Fuzzy GML Modeling Based on Vague Soft Sets

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Bo Wei

2017-01-01

Full Text Available The Open Geospatial Consortium (OGC Geography Markup Language (GML explicitly represents geographical spatial knowledge in text mode. All kinds of fuzzy problems will inevitably be encountered in spatial knowledge expression. Especially for those expressions in text mode, this fuzziness will be broader. Describing and representing fuzziness in GML seems necessary. Three kinds of fuzziness in GML can be found: element fuzziness, chain fuzziness, and attribute fuzziness. Both element fuzziness and chain fuzziness belong to the reflection of the fuzziness between GML elements and, then, the representation of chain fuzziness can be replaced by the representation of element fuzziness in GML. On the basis of vague soft set theory, two kinds of modeling, vague soft set GML Document Type Definition (DTD modeling and vague soft set GML schema modeling, are proposed for fuzzy modeling in GML DTD and GML schema, respectively. Five elements or pairs, associated with vague soft sets, are introduced. Then, the DTDs and the schemas of the five elements are correspondingly designed and presented according to their different chains and different fuzzy data types. While the introduction of the five elements or pairs is the basis of vague soft set GML modeling, the corresponding DTD and schema modifications are key for implementation of modeling. The establishment of vague soft set GML enables GML to represent fuzziness and solves the problem of lack of fuzzy information expression in GML.

Event Segmentation Improves Event Memory up to One Month Later

Science.gov (United States)

Flores, Shaney; Bailey, Heather R.; Eisenberg, Michelle L.; Zacks, Jeffrey M.

2017-01-01

When people observe everyday activity, they spontaneously parse it into discrete meaningful events. Individuals who segment activity in a more normative fashion show better subsequent memory for the events. If segmenting events effectively leads to better memory, does asking people to attend to segmentation improve subsequent memory? To answer…

On rarely generalized regular fuzzy continuous functions in fuzzy topological spaces

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Appachi Vadivel

2016-11-01

Full Text Available In this paper, we introduce the concept of rarely generalized regular fuzzy continuous functions in the sense of A.P. Sostak's and Ramadan is introduced. Some interesting properties and characterizations of them are investigated. Also, some applications to fuzzy compact spaces are established.

Logika Fuzzy untuk Audit Sistem Informasi

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Hari Setiabudi Husni

2013-06-01

Full Text Available The aim of this research is to study and introduce fuzzy logic into audit information system. Fuzzy logic is already adopted in other field of study. It helps decision process that incorporates subjective information and transforms it to scientific objective information which is more accepted. This research implements simulation scenario to see how fuzzy logic concept should be used in audit information process. The result shows that there is a possible concept of fuzzy logic that can be used for helping auditor in making objective decision in audit information system process. More researches needed to further explore the fuzzy logic concept such as creating the system of fuzzy logic and build application that can be used for daily information system audit process. 

Beyond fuzzy spheres

International Nuclear Information System (INIS)

Govindarajan, T R; Padmanabhan, Pramod; Shreecharan, T

2010-01-01

We study polynomial deformations of the fuzzy sphere, specifically given by the cubic or the Higgs algebra. We derive the Higgs algebra by quantizing the Poisson structure on a surface in R 3 . We find that several surfaces, differing by constants, are described by the Higgs algebra at the fuzzy level. Some of these surfaces have a singularity and we overcome this by quantizing this manifold using coherent states for this nonlinear algebra. This is seen in the measure constructed from these coherent states. We also find the star product for this non-commutative algebra as a first step in constructing field theories on such fuzzy spaces.

Context-Aware Mobile Sensors for Sensing Discrete Events in Smart Environment

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Awais Ahmad

2016-01-01

Full Text Available Over the last few decades, several advancements in the field of smart environment gained importance, so the experts can analyze ideas for smart building based on embedded systems to minimize the expense and energy conservation. Therefore, propelling the concept of smart home toward smart building, several challenges of power, communication, and sensors’ connectivity can be seen. Such challenges distort the interconnectivity between different technologies, such as Bluetooth and ZigBee, making it possible to provide the continuous connectivity among different objects such as sensors, actuators, home appliances, and cell phones. Therefore, this paper presents the concept of smart building based on embedded systems that enhance low power mobile sensors for sensing discrete events in embedded systems. The proposed scheme comprises system architecture that welcomes all the mobile sensors to communicate with each other using a single platform service. The proposed system enhances the concept of smart building in three stages (i.e., visualization, data analysis, and application. For low power mobile sensors, we propose a communication model, which provides a common medium for communication. Finally, the results show that the proposed system architecture efficiently processes, analyzes, and integrates different datasets efficiently and triggers actions to provide safety measurements for the elderly, patients, and others.

Comparative Study of Aircraft Boarding Strategies Using Cellular Discrete Event Simulation

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Shafagh Jafer

2017-11-01

Full Text Available Time is crucial in the airlines industry. Among all factors contributing to an aircraft turnaround time; passenger boarding delays is the most challenging one. Airlines do not have control over the behavior of passengers; thus, focusing their effort on reducing passenger boarding time through implementing efficient boarding strategies. In this work, we attempt to use cellular Discrete-Event System Specification (Cell-DEVS modeling and simulation to provide a comprehensive evaluation of aircraft boarding strategies. We have developed a simulation benchmark consisting of eight boarding strategies including Back-to-Front; Window Middle Aisle; Random; Zone Rotate; Reverse Pyramid; Optimal; Optimal Practical; and Efficient. Our simulation models are scalable and adaptive; providing a powerful analysis apparatus for investigating any existing or yet to be discovered boarding strategy. We explain the details of our models and present the results both visually and numerically to evaluate the eight implemented boarding strategies. We also compare our results with other studies that have used different modeling techniques; reporting nearly identical performance results. The simulations revealed that Window Middle Aisle provides the least boarding delay; with a small fraction of time difference compared to the optimal strategy. The results of this work could highly benefit the commercial airlines industry by optimizing and reducing passenger boarding delays.

Fuzzy tree automata and syntactic pattern recognition.

Science.gov (United States)

Lee, E T

1982-04-01

An approach of representing patterns by trees and processing these trees by fuzzy tree automata is described. Fuzzy tree automata are defined and investigated. The results include that the class of fuzzy root-to-frontier recognizable ¿-trees is closed under intersection, union, and complementation. Thus, the class of fuzzy root-to-frontier recognizable ¿-trees forms a Boolean algebra. Fuzzy tree automata are applied to processing fuzzy tree representation of patterns based on syntactic pattern recognition. The grade of acceptance is defined and investigated. Quantitative measures of ``approximate isosceles triangle,'' ``approximate elongated isosceles triangle,'' ``approximate rectangle,'' and ``approximate cross'' are defined and used in the illustrative examples of this approach. By using these quantitative measures, a house, a house with high roof, and a church are also presented as illustrative examples. In addition, three fuzzy tree automata are constructed which have the capability of processing the fuzzy tree representations of ``fuzzy houses,'' ``houses with high roofs,'' and ``fuzzy churches,'' respectively. The results may have useful applications in pattern recognition, image processing, artificial intelligence, pattern database design and processing, image science, and pictorial information systems.

MENGUKUR KESUKSESAN PRODUK PADA TAHAP DESAIN: SEBUAH PENDEKATAN FUZZY-MCDM

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Ade Febransyah

2006-01-01

Full Text Available It has always been a great challenge to any product development team to forecast the success of a new product at the design stage. For any product concept, it is of interest to assign an accurate probability to any event or state of the world that reflects the new product success. This probability is then required in decision tree analysis for selecting the best product concept. In practice, the probability is determined solely on intuition or subjective judgment due to impreciseness, lack of information during the design stage, and the cognitive limitation of decision makers. This paper presents an approach integrating fuzzy set theory and multi criteria decision making (MCDM approach in forecasting accurately the success of a new product. The analytic hierarchy process (AHP is used due to its simplicity as a prescriptive approach that will help decision makers select the best decision with respect to a set of criteria. Fuzzy numbers are used to describe any judgment on design criteria and the event probability of a product concept. A numerical example is given to illustrate the use of this approach. Abstract in Bahasa Indonesia : Selalu menjadi tantangan besar bagi setiap tim pengembang produk untuk dapat mengestimasi tingkat kesuksesan suatu produk baru pada tahap desain. Tingkat kesuksesan yang dinyatakan dengan besar probabilitas berbagai state of the world dari suatu konsep produk selanjutnya digunakan dalam analisa keputusan untuk memilih konsep produk terlayak. Selama ini besar probabilitas ditentukan lebih banyak berdasarkan intuisi dan subyektifitas pengambil keputusan. Praktik ini cenderung menghasilkan keputusan yang bias mengingat keterbatasan kapabilitas kognitif manusia dalam mensintesa berbagai keunggulan maupun kekurangan dari sekumpulan konsep produk. Tulisan ini bertujuan untuk menyampaikan satu pendekatan yang mengintegrasikan logika fuzzy dan pendekatan pengambilan keputusan berkriteria jamak (multi criteria decision making

Fuzzy logic controller using different inference methods

International Nuclear Information System (INIS)

Liu, Z.; De Keyser, R.

1994-01-01

In this paper the design of fuzzy controllers by using different inference methods is introduced. Configuration of the fuzzy controllers includes a general rule-base which is a collection of fuzzy PI or PD rules, the triangular fuzzy data model and a centre of gravity defuzzification algorithm. The generalized modus ponens (GMP) is used with the minimum operator of the triangular norm. Under the sup-min inference rule, six fuzzy implication operators are employed to calculate the fuzzy look-up tables for each rule base. The performance is tested in simulated systems with MATLAB/SIMULINK. Results show the effects of using the fuzzy controllers with different inference methods and applied to different test processes

Fuzzy control of small servo motors

Science.gov (United States)

Maor, Ron; Jani, Yashvant

1993-01-01

To explore the benefits of fuzzy logic and understand the differences between the classical control methods and fuzzy control methods, the Togai InfraLogic applications engineering staff developed and implemented a motor control system for small servo motors. The motor assembly for testing the fuzzy and conventional controllers consist of servo motor RA13M and an encoder with a range of 4096 counts. An interface card was designed and fabricated to interface the motor assembly and encoder to an IBM PC. The fuzzy logic based motor controller was developed using the TILShell and Fuzzy C Development System on an IBM PC. A Proportional-Derivative (PD) type conventional controller was also developed and implemented in the IBM PC to compare the performance with the fuzzy controller. Test cases were defined to include step inputs of 90 and 180 degrees rotation, sine and square wave profiles in 5 to 20 hertz frequency range, as well as ramp inputs. In this paper we describe our approach to develop a fuzzy as well as PH controller, provide details of hardware set-up and test cases, and discuss the performance results. In comparison, the fuzzy logic based controller handles the non-linearities of the motor assembly very well and provides excellent control over a broad range of parameters. Fuzzy technology, as indicated by our results, possesses inherent adaptive features.

Distributed mixed-integer fuzzy hierarchical programming for municipal solid waste management. Part I: System identification and methodology development.

Science.gov (United States)

Cheng, Guanhui; Huang, Guohe; Dong, Cong; Xu, Ye; Chen, Xiujuan; Chen, Jiapei

2017-03-01

Due to the existence of complexities of heterogeneities, hierarchy, discreteness, and interactions in municipal solid waste management (MSWM) systems such as Beijing, China, a series of socio-economic and eco-environmental problems may emerge or worsen and result in irredeemable damages in the following decades. Meanwhile, existing studies, especially ones focusing on MSWM in Beijing, could hardly reflect these complexities in system simulations and provide reliable decision support for management practices. Thus, a framework of distributed mixed-integer fuzzy hierarchical programming (DMIFHP) is developed in this study for MSWM under these complexities. Beijing is selected as a representative case. The Beijing MSWM system is comprehensively analyzed in many aspects such as socio-economic conditions, natural conditions, spatial heterogeneities, treatment facilities, and system complexities, building a solid foundation for system simulation and optimization. Correspondingly, the MSWM system in Beijing is discretized as 235 grids to reflect spatial heterogeneity. A DMIFHP model which is a nonlinear programming problem is constructed to parameterize the Beijing MSWM system. To enable scientific solving of it, a solution algorithm is proposed based on coupling of fuzzy programming and mixed-integer linear programming. Innovations and advantages of the DMIFHP framework are discussed. The optimal MSWM schemes and mechanism revelations will be discussed in another companion paper due to length limitation.

Enric Trillas a passion for fuzzy sets : a collection of recent works on fuzzy logic

CERN Document Server

Verdegay, Jose; Esteva, Francesc

2015-01-01

This book presents a comprehensive collection of the latest and most significant research advances and applications in the field of fuzzy logic. It covers fuzzy structures, rules, operations and mathematical formalisms, as well as important applications of fuzzy logic in a number of fields, like decision-making, environmental prediction and prevention, communication, controls and many others. Dedicated to Enric Trillas in recognition of his pioneering research in the field, the book also includes a foreword by Lotfi A. Zadeh and an outlook on the future of fuzzy logic.

Fuzzy Logic in Medicine and Bioinformatics

Directory of Open Access Journals (Sweden)

Angela Torres

2006-01-01

Full Text Available The purpose of this paper is to present a general view of the current applications of fuzzy logic in medicine and bioinformatics. We particularly review the medical literature using fuzzy logic. We then recall the geometrical interpretation of fuzzy sets as points in a fuzzy hypercube and present two concrete illustrations in medicine (drug addictions and in bioinformatics (comparison of genomes.

Model predictive control using fuzzy decision functions

NARCIS (Netherlands)

Kaymak, U.; Costa Sousa, da J.M.

2001-01-01

Fuzzy predictive control integrates conventional model predictive control with techniques from fuzzy multicriteria decision making, translating the goals and the constraints to predictive control in a transparent way. The information regarding the (fuzzy) goals and the (fuzzy) constraints of the

A novel method of fuzzy fault tree analysis combined with VB program to identify and assess the risk of coal dust explosions.

Directory of Open Access Journals (Sweden)

Hetang Wang

Full Text Available Coal dust explosions (CDE are one of the main threats to the occupational safety of coal miners. Aiming to identify and assess the risk of CDE, this paper proposes a novel method of fuzzy fault tree analysis combined with the Visual Basic (VB program. In this methodology, various potential causes of the CDE are identified and a CDE fault tree is constructed. To overcome drawbacks from the lack of exact probability data for the basic events, fuzzy set theory is employed and the probability data of each basic event is treated as intuitionistic trapezoidal fuzzy numbers. In addition, a new approach for calculating the weighting of each expert is also introduced in this paper to reduce the error during the expert elicitation process. Specifically, an in-depth quantitative analysis of the fuzzy fault tree, such as the importance measure of the basic events and the cut sets, and the CDE occurrence probability is given to assess the explosion risk and acquire more details of the CDE. The VB program is applied to simplify the analysis process. A case study and analysis is provided to illustrate the effectiveness of this proposed method, and some suggestions are given to take preventive measures in advance and avoid CDE accidents.

The effects of indoor environmental exposures on pediatric asthma: a discrete event simulation model

Directory of Open Access Journals (Sweden)

Fabian M Patricia

2012-09-01

Full Text Available Abstract Background In the United States, asthma is the most common chronic disease of childhood across all socioeconomic classes and is the most frequent cause of hospitalization among children. Asthma exacerbations have been associated with exposure to residential indoor environmental stressors such as allergens and air pollutants as well as numerous additional factors. Simulation modeling is a valuable tool that can be used to evaluate interventions for complex multifactorial diseases such as asthma but in spite of its flexibility and applicability, modeling applications in either environmental exposures or asthma have been limited to date. Methods We designed a discrete event simulation model to study the effect of environmental factors on asthma exacerbations in school-age children living in low-income multi-family housing. Model outcomes include asthma symptoms, medication use, hospitalizations, and emergency room visits. Environmental factors were linked to percent predicted forced expiratory volume in 1 second (FEV1%, which in turn was linked to risk equations for each outcome. Exposures affecting FEV1% included indoor and outdoor sources of NO2 and PM2.5, cockroach allergen, and dampness as a proxy for mold. Results Model design parameters and equations are described in detail. We evaluated the model by simulating 50,000 children over 10 years and showed that pollutant concentrations and health outcome rates are comparable to values reported in the literature. In an application example, we simulated what would happen if the kitchen and bathroom exhaust fans were improved for the entire cohort, and showed reductions in pollutant concentrations and healthcare utilization rates. Conclusions We describe the design and evaluation of a discrete event simulation model of pediatric asthma for children living in low-income multi-family housing. Our model simulates the effect of environmental factors (combustion pollutants and allergens

A fuzzy genetic approach for network reconfiguration to enhance voltage stability in radial distribution systems

International Nuclear Information System (INIS)

Sahoo, N.C.; Prasad, K.

2006-01-01

This paper presents a fuzzy genetic approach for reconfiguration of radial distribution systems (RDS) so as to maximize the voltage stability of the network for a specific set of loads. The network reconfiguration involves a mechanism for selection of the best set of branches to be opened, one from each loop, such that the reconfigured RDS possesses desired performance characteristics. This discrete solution space is better handled by the proposed scheme, which maximizes a suitable optimizing function (computed using two different approaches). In the first approach, this function is chosen as the average of a voltage stability index of all the buses in the RDS, while in the second approach, the complete RDS is reduced to a two bus equivalent system and the optimizing function is the voltage stability index of this reduced two bus system. The fuzzy genetic algorithm uses a suitable coding and decoding scheme for maintaining the radial nature of the network at every stage of genetic evolution, and it also uses a fuzzy rule based mutation controller for efficient search of the solution space. This method, tested on 69 bus and 33 bus RDSs, shows promising results for the both approaches. It is also observed that the network losses are reduced when the voltage stability is enhanced by the network reconfiguration

Algebraic Aspects of Families of Fuzzy Languages

NARCIS (Netherlands)

Asveld, P.R.J.; Heylen, Dirk K.J.; Nijholt, Antinus; Scollo, Giuseppe

2000-01-01

We study operations on fuzzy languages such as union, concatenation,Kleene $\\star$, intersection with regular fuzzy languages, and several kinds of (iterated) fuzzy substitution. Then we consider families of fuzzy languages, closed under a fixed collection of these operations, which results in the

Discrete events simulation of a route with traffic lights through automated control in real time

Directory of Open Access Journals (Sweden)

Rodrigo César Teixeira Baptista

2013-03-01

Full Text Available This paper presents the integration and communication in real-time of a discrete event simulation model with an automatic control system. The simulation model of an intersection with roads having traffic lights was built in the Arena environment. The integration and communication have been made via network, and the control system was operated by a programmable logic controller. Scenarios were simulated for the free, regular and congested traffic situations. The results showed the average number of vehicles that entered in the system and that were retained and also the total average time of the crossing of the vehicles on the road. In general, the model allowed evaluating the behavior of the traffic in each of the ways and the commands from the controller to activation and deactivation of the traffic lights.

Discrete Event Simulation-Based Resource Modelling in Health Technology Assessment.

Science.gov (United States)

Salleh, Syed; Thokala, Praveen; Brennan, Alan; Hughes, Ruby; Dixon, Simon

2017-10-01

The objective of this article was to conduct a systematic review of published research on the use of discrete event simulation (DES) for resource modelling (RM) in health technology assessment (HTA). RM is broadly defined as incorporating and measuring effects of constraints on physical resources (e.g. beds, doctors, nurses) in HTA models. Systematic literature searches were conducted in academic databases (JSTOR, SAGE, SPRINGER, SCOPUS, IEEE, Science Direct, PubMed, EMBASE) and grey literature (Google Scholar, NHS journal library), enhanced by manual searchers (i.e. reference list checking, citation searching and hand-searching techniques). The search strategy yielded 4117 potentially relevant citations. Following the screening and manual searches, ten articles were included. Reviewing these articles provided insights into the applications of RM: firstly, different types of economic analyses, model settings, RM and cost-effectiveness analysis (CEA) outcomes were identified. Secondly, variation in the characteristics of the constraints such as types and nature of constraints and sources of data for the constraints were identified. Thirdly, it was found that including the effects of constraints caused the CEA results to change in these articles. The review found that DES proved to be an effective technique for RM but there were only a small number of studies applied in HTA. However, these studies showed the important consequences of modelling physical constraints and point to the need for a framework to be developed to guide future applications of this approach.

Approximate Solution of LR Fuzzy Sylvester Matrix Equations

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Xiaobin Guo

2013-01-01

Full Text Available The fuzzy Sylvester matrix equation AX~+X~B=C~ in which A,B are m×m and n×n crisp matrices, respectively, and C~ is an m×n LR fuzzy numbers matrix is investigated. Based on the Kronecker product of matrices, we convert the fuzzy Sylvester matrix equation into an LR fuzzy linear system. Then we extend the fuzzy linear system into two systems of linear equations according to the arithmetic operations of LR fuzzy numbers. The fuzzy approximate solution of the original fuzzy matrix equation is obtained by solving the crisp linear systems. The existence condition of the LR fuzzy solution is also discussed. Some examples are given to illustrate the proposed method.

Fuzzy histogram for internal and external fuzzy directional relations

OpenAIRE

Salamat , Nadeem; Zahzah , El-Hadi

2009-01-01

5 Pages; Spatial relations have key point importance in image analysis and computer vision. Numerous technics have been developed to study these relations especially directional relations. Modern digital computers give rise to quantitative methods and among them fuzzy methods have core importance due to handling imprecise knowledge information and vagueness. In most fuzzy methods external directional relations are considered which are useful for small scale space image analysis but in large s...

Fuzzy relational calculus theory, applications and software

CERN Document Server

Peeva, Ketty

2004-01-01

This book examines fuzzy relational calculus theory with applications in various engineering subjects. The scope of the text covers unified and exact methods with algorithms for direct and inverse problem resolution in fuzzy relational calculus. Extensive engineering applications of fuzzy relation compositions and fuzzy linear systems (linear, relational and intuitionistic) are discussed. Some examples of such applications include solutions of equivalence, reduction and minimization problems in fuzzy machines, pattern recognition in fuzzy languages, optimization and inference engines in textile and chemical engineering, etc. A comprehensive overview of the authors' original work in fuzzy relational calculus is also provided in each chapter. The attached CD-Rom contains a toolbox with many functions for fuzzy calculations, together with an original algorithm for inverse problem resolution in MATLAB. This book is also suitable for use as a textbook in related courses at advanced undergraduate and graduate level...

On the mathematics of fuzziness

Energy Technology Data Exchange (ETDEWEB)

Chulichkov, A.I.; Chulichkova, N.M.; Pyt`ev, Y. P.; Smolnik, L.

1994-12-31

The problem of the minimax linear interpretation of stochastic measurements with fuzzy conditions on values of the object`s parameters is considered. The result of a measurement interpretation is the fuzzy element (u, h, alpha, mu(.,.,.)), where u is the object`s parameter estimation, h is the estimation accuracy and alpha is the reliability of interpretation, mu is the characteristic function of a fuzzy element. Reliability is the characteristic of the agreement between fuzzy a priori information and measuring data. The information on the values of the parameters of an object under investigation is interactively submitted to the computer.

Fuzzy upper bounds and their applications

Energy Technology Data Exchange (ETDEWEB)

Soleimani-damaneh, M. [Department of Mathematics, Faculty of Mathematical Science and Computer Engineering, Teacher Training University, 599 Taleghani Avenue, Tehran 15618 (Iran, Islamic Republic of)], E-mail: soleimani_d@yahoo.com

2008-04-15

This paper considers the concept of fuzzy upper bounds and provides some relevant applications. Considering a fuzzy DEA model, the existence of a fuzzy upper bound for the objective function of the model is shown and an effective approach to solve that model is introduced. Some dual interpretations are provided, which are useful for practical purposes. Applications of the concept of fuzzy upper bounds in two physical problems are pointed out.

DECISION WITH ARTIFICIAL NEURAL NETWORKS IN DISCRETE EVENT SIMULATION MODELS ON A TRAFFIC SYSTEM

Directory of Open Access Journals (Sweden)

Marília Gonçalves Dutra da Silva

2016-04-01

Full Text Available ABSTRACT This work aims to demonstrate the use of a mechanism to be applied in the development of the discrete-event simulation models that perform decision operations through the implementation of an artificial neural network. Actions that involve complex operations performed by a human agent in a process, for example, are often modeled in simplified form with the usual mechanisms of simulation software. Therefore, it was chosen a traffic system controlled by a traffic officer with a flow of vehicles and pedestrians to demonstrate the proposed solution. From a module built in simulation software itself, it was possible to connect the algorithm for intelligent decision to the simulation model. The results showed that the model elaborated responded as expected when it was submitted to actions, which required different decisions to maintain the operation of the system with changes in the flow of people and vehicles.

Fuzzy Clustering

DEFF Research Database (Denmark)

Berks, G.; Keyserlingk, Diedrich Graf von; Jantzen, Jan

2000-01-01

A symptom is a condition indicating the presence of a disease, especially, when regarded as an aid in diagnosis.Symptoms are the smallest units indicating the existence of a disease. A syndrome on the other hand is an aggregate, set or cluster of concurrent symptoms which together indicate...... and clustering are the basic concerns in medicine. Classification depends on definitions of the classes and their required degree of participant of the elements in the cases' symptoms. In medicine imprecise conditions are the rule and therefore fuzzy methods are much more suitable than crisp ones. Fuzzy c......-mean clustering is an easy and well improved tool, which has been applied in many medical fields. We used c-mean fuzzy clustering after feature extraction from an aphasia database. Factor analysis was applied on a correlation matrix of 26 symptoms of language disorders and led to five factors. The factors...

Risk Assessment in Underground Coalmines Using Fuzzy Logic in the Presence of Uncertainty

Science.gov (United States)

Tripathy, Debi Prasad; Ala, Charan Kumar

2018-04-01

Fatal accidents are occurring every year as regular events in Indian coal mining industry. To increase the safety conditions, it has become a prerequisite to performing a risk assessment of various operations in mines. However, due to uncertain accident data, it is hard to conduct a risk assessment in mines. The object of this study is to present a method to assess safety risks in underground coalmines. The assessment of safety risks is based on the fuzzy reasoning approach. Mamdani fuzzy logic model is developed in the fuzzy logic toolbox of MATLAB. A case study is used to demonstrate the applicability of the developed model. The summary of risk evaluation in case study mine indicated that mine fire has the highest risk level among all the hazard factors. This study could help the mine management to prepare safety measures based on the risk rankings obtained.

Application of Bipolar Fuzzy Sets in Graph Structures

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Muhammad Akram

2016-01-01

Full Text Available A graph structure is a useful tool in solving the combinatorial problems in different areas of computer science and computational intelligence systems. In this paper, we apply the concept of bipolar fuzzy sets to graph structures. We introduce certain notions, including bipolar fuzzy graph structure (BFGS, strong bipolar fuzzy graph structure, bipolar fuzzy Ni-cycle, bipolar fuzzy Ni-tree, bipolar fuzzy Ni-cut vertex, and bipolar fuzzy Ni-bridge, and illustrate these notions by several examples. We study ϕ-complement, self-complement, strong self-complement, and totally strong self-complement in bipolar fuzzy graph structures, and we investigate some of their interesting properties.

Influence of fuzzy norms and other heuristics on “Mixed fuzzy rule formation”

OpenAIRE

Gabriel, Thomas R.; Berthold, Michael R.

2004-01-01

In Mixed Fuzzy Rule Formation [Int. J. Approx. Reason. 32 (2003) 67] a method to extract mixed fuzzy rules from data was introduced. The underlying algorithm s performance is influenced by the choice of fuzzy t-norm and t-conorm, and a heuristic to avoid conflicts between patterns and rules of different classes throughout training. In the following addendum to [Int. J. Approx. Reason. 32 (2003) 67], we discuss in more depth how these parameters affect the generalization performance of the res...

Discrete Event Simulation for Decision Modeling in Health Care: Lessons from Abdominal Aortic Aneurysm Screening

Science.gov (United States)

Jones, Edmund; Masconi, Katya L.; Sweeting, Michael J.; Thompson, Simon G.; Powell, Janet T.

2018-01-01

Markov models are often used to evaluate the cost-effectiveness of new healthcare interventions but they are sometimes not flexible enough to allow accurate modeling or investigation of alternative scenarios and policies. A Markov model previously demonstrated that a one-off invitation to screening for abdominal aortic aneurysm (AAA) for men aged 65 y in the UK and subsequent follow-up of identified AAAs was likely to be highly cost-effective at thresholds commonly adopted in the UK (£20,000 to £30,000 per quality adjusted life-year). However, new evidence has emerged and the decision problem has evolved to include exploration of the circumstances under which AAA screening may be cost-effective, which the Markov model is not easily able to address. A new model to handle this more complex decision problem was needed, and the case of AAA screening thus provides an illustration of the relative merits of Markov models and discrete event simulation (DES) models. An individual-level DES model was built using the R programming language to reflect possible events and pathways of individuals invited to screening v. those not invited. The model was validated against key events and cost-effectiveness, as observed in a large, randomized trial. Different screening protocol scenarios were investigated to demonstrate the flexibility of the DES. The case of AAA screening highlights the benefits of DES, particularly in the context of screening studies.

Towards the future of fuzzy logic

CERN Document Server

Trillas, Enric; Kacprzyk, Janusz

2015-01-01

This book provides readers with a snapshot of the state-of-the art in fuzzy logic. Throughout the chapters, key theories developed in the last fifty years as well as important applications to practical problems are presented and discussed from different perspectives, as the authors hail from different disciplines and therefore use fuzzy logic for different purposes.  The book aims at showing how fuzzy logic has evolved since the first theory formulation by Lotfi A. Zadeh in his seminal paper on Fuzzy Sets in 1965. Fuzzy theories and implementation grew at an impressive speed and achieved significant results, especially on the applicative side. The study of fuzzy logic and its practice spread all over the world, from Europe to Asia, America and Oceania. The editors believe that, thanks to the drive of young researchers, fuzzy logic will be able to face the challenging goals posed by computing with words. New frontiers of knowledge are waiting to be explored. In order to motivate young people to engage in the ...

Sputtering properties of tungsten 'fuzzy' surfaces

International Nuclear Information System (INIS)

Nishijima, D.; Baldwin, M.J.; Doerner, R.P.; Yu, J.H.

2011-01-01

Sputtering yields of He-induced W 'fuzzy' surfaces bombarded by Ar have been measured in the linear divertor plasma simulator PISCES-B. It is found that the sputtering yield of a fuzzy surface, Y fuzzy , decreases with increasing fuzzy layer thickness, L, and saturates at ∼10% of that of a smooth surface, Y smooth , at L > 1 μm. The reduction in the sputtering yield is suspected to be due mainly to the porous structure of fuzz, since the ratio, Y fuzzy /Y smooth follows (1 - p fuzz ), where p fuzz is the fuzz porosity. Further, Y fuzzy /Y smooth is observed to increase with incident ion energy, E i . This may be explained by an energy dependent change in the angular distribution of sputtered W atoms, since at lower E i , the angular distribution is observed to become more butterfly-shaped. That is, a larger fraction of sputtered W atoms can line-of-sight deposit/stick onto neighboring fuzz nanostructures for lower E i butterfly distributions, resulting in lower ratio of Y fuzzy /Y smooth .

Influence of fuzzy norms and other heuristics on "Mixed fuzzy rule formation" - [Corrigendum

OpenAIRE

Gabriel, Thomas R.; Berthold, Michael R.

2008-01-01

We hereby correct an error in Ref. [2], in which we studied the influence of various parameters that affect the generalization performance of fuzzy models constructed using the mixed fuzzy rule formation method [1].

On the Power of Fuzzy Markup Language

CERN Document Server

Loia, Vincenzo; Lee, Chang-Shing; Wang, Mei-Hui

2013-01-01

One of the most successful methodology that arose from the worldwide diffusion of Fuzzy Logic is Fuzzy Control. After the first attempts dated in the seventies, this methodology has been widely exploited for controlling many industrial components and systems. At the same time, and very independently from Fuzzy Logic or Fuzzy Control, the birth of the Web has impacted upon almost all aspects of computing discipline. Evolution of Web, Web 2.0 and Web 3.0 has been making scenarios of ubiquitous computing much more feasible;  consequently information technology has been thoroughly integrated into everyday objects and activities. What happens when Fuzzy Logic meets Web technology? Interesting results might come out, as you will discover in this book. Fuzzy Mark-up Language is a son of this synergistic view, where some technological issues of Web are re-interpreted taking into account the transparent notion of Fuzzy Control, as discussed here.  The concept of a Fuzzy Control that is conceived and modeled in terms...

Neuro-fuzzy Control of Integrating Processes

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Anna Vasičkaninová

2011-11-01

Full Text Available Fuzzy technology is adaptive and easily applicable in different areas.Fuzzy logic provides powerful tools to capture the perceptionof natural phenomena. The paper deals with tuning of neuro-fuzzy controllers for integrating plant and for integrating plantswith time delay. The designed approach is verified on three examples by simulations and compared plants with classical PID control.Designed fuzzy controllers lead to better closed-loop control responses then classical PID controllers.

Frechet differentiation of nonlinear operators between fuzzy normed spaces

International Nuclear Information System (INIS)

Yilmaz, Yilmaz

2009-01-01

By the rapid advances in linear theory of fuzzy normed spaces and fuzzy bounded linear operators it is natural idea to set and improve its nonlinear peer. We aimed in this work to realize this idea by introducing fuzzy Frechet derivative based on the fuzzy norm definition in Bag and Samanta [Bag T, Samanta SK. Finite dimensional fuzzy normed linear spaces. J Fuzzy Math 2003;11(3):687-705]. The definition is divided into two part as strong and weak fuzzy Frechet derivative so that it is compatible with strong and weak fuzzy continuity of operators. Also we restate fuzzy compact operator definition of Lael and Nouroizi [Lael F, Nouroizi K. Fuzzy compact linear operators. Chaos, Solitons and Fractals 2007;34(5):1584-89] as strongly and weakly fuzzy compact by taking into account the compatibility. We prove also that weak Frechet derivative of a nonlinear weakly fuzzy compact operator is also weakly fuzzy compact.

Solution of Fuzzy Differential Equations Using Fuzzy Sumudu Transforms

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Raheleh Jafari

2018-01-01

Full Text Available The uncertain nonlinear systems can be modeled with fuzzy differential equations (FDEs and the solutions of these equations are applied to analyze many engineering problems. However, it is very difficult to obtain solutions of FDEs. In this paper, the solutions of FDEs are approximated by utilizing the fuzzy Sumudu transform (FST method. Significant theorems are suggested in order to explain the properties of FST. The proposed method is validated with three real examples.

using fuzzy logic in image processing

International Nuclear Information System (INIS)

Ashabrawy, M.A.F.

2002-01-01

due to the unavoidable merge between computer and mathematics, the signal processing in general and the processing in particular have greatly improved and advanced. signal processing deals with the processing of any signal data for use by a computer, while image processing deals with all kinds of images (just images). image processing involves the manipulation of image data for better appearance and viewing by people; consequently, it is a rapidly growing and exciting field to be involved in today . this work takes an applications - oriented approach to image processing .the applications; the maps and documents of the first egyptian research reactor (ETRR-1), the x-ray medical images and the fingerprints image. since filters, generally, work continuous ranges rather than discrete values, fuzzy logic techniques are more convenient.thee techniques are powerful in image processing and can deal with one- dimensional, 1-D and two - dimensional images, 2-D images as well

Design of interpretable fuzzy systems

CERN Document Server

Cpałka, Krzysztof

2017-01-01

This book shows that the term “interpretability” goes far beyond the concept of readability of a fuzzy set and fuzzy rules. It focuses on novel and precise operators of aggregation, inference, and defuzzification leading to flexible Mamdani-type and logical-type systems that can achieve the required accuracy using a less complex rule base. The individual chapters describe various aspects of interpretability, including appropriate selection of the structure of a fuzzy system, focusing on improving the interpretability of fuzzy systems designed using both gradient-learning and evolutionary algorithms. It also demonstrates how to eliminate various system components, such as inputs, rules and fuzzy sets, whose reduction does not adversely affect system accuracy. It illustrates the performance of the developed algorithms and methods with commonly used benchmarks. The book provides valuable tools for possible applications in many fields including expert systems, automatic control and robotics.

Comparison of Fuzzy AHP and Fuzzy TOPSIS for Road Pavement Maintenance Prioritization: Methodological Exposition and Case Study

OpenAIRE

Yashon O. Ouma; J. Opudo; S. Nyambenya

2015-01-01

For road pavement maintenance and repairs prioritization, a multiattribute approach that compares fuzzy Analytical Hierarchy Process (AHP) and fuzzy Technique for Order Preference by Ideal Situation (TOPSIS) is evaluated. The pavement distress data was collected through empirical condition surveys and rating by pavement experts. In comparison to the crisp AHP, the fuzzy AHP and fuzzy TOPSIS pairwise comparison techniques are considered to be more suitable for the subjective analysis of the pa...

Approximations of Fuzzy Systems

Directory of Open Access Journals (Sweden)

Vinai K. Singh

2013-03-01

Full Text Available A fuzzy system can uniformly approximate any real continuous function on a compact domain to any degree of accuracy. Such results can be viewed as an existence of optimal fuzzy systems. Li-Xin Wang discussed a similar problem using Gaussian membership function and Stone-Weierstrass Theorem. He established that fuzzy systems, with product inference, centroid defuzzification and Gaussian functions are capable of approximating any real continuous function on a compact set to arbitrary accuracy. In this paper we study a similar approximation problem by using exponential membership functions

Fuzzy-based HAZOP study for process industry

Energy Technology Data Exchange (ETDEWEB)

Ahn, Junkeon; Chang, Daejun, E-mail: djchang@kaist.edu

2016-11-05

Highlights: • HAZOP is the important technique to evaluate system safety and its risks while process operations. • Fuzzy theory can handle the inherent uncertainties of process systems for the HAZOP. • Fuzzy-based HAZOP considers the aleatory and epistemic uncertainties and provides the risk level with less uncertainty. • Risk acceptance criteria should be considered regarding the transition region for each risk. - Abstract: This study proposed a fuzzy-based HAZOP for analyzing process hazards. Fuzzy theory was used to express uncertain states. This theory was found to be a useful approach to overcome the inherent uncertainty in HAZOP analyses. Fuzzy logic sharply contrasted with classical logic and provided diverse risk values according to its membership degree. Appropriate process parameters and guidewords were selected to describe the frequency and consequence of an accident. Fuzzy modeling calculated risks based on the relationship between the variables of an accident. The modeling was based on the mean expected value, trapezoidal fuzzy number, IF-THEN rules, and the center of gravity method. A cryogenic LNG (liquefied natural gas) testing facility was the objective process for the fuzzy-based and conventional HAZOPs. The most significant index is the frequency to determine risks. The comparison results showed that the fuzzy-based HAZOP provides better sophisticated risks than the conventional HAZOP. The fuzzy risk matrix presents the significance of risks, negligible risks, and necessity of risk reduction.

Supply chain management under fuzziness recent developments and techniques

CERN Document Server

Öztayşi, Başar

2014-01-01

Supply Chain Management Under Fuzziness presents recently developed fuzzy models and techniques for supply chain management. These include: fuzzy PROMETHEE, fuzzy AHP, fuzzy ANP, fuzzy VIKOR, fuzzy DEMATEL, fuzzy clustering, fuzzy linear programming, and fuzzy inference systems. The book covers both practical applications and new developments concerning these methods. This book offers an excellent resource for researchers and practitioners in supply chain management and logistics, and will provide them with new suggestions and directions for future research. Moreover, it will support graduate students in their university courses, such as specialized courses on supply chains and logistics, as well as related courses in the fields of industrial engineering, engineering management and business administration.