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
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
Multiobjective fuzzy stochastic linear programming problems with inexact probability distribution
Hamadameen, Abdulqader Othman [Optimization, Department of Mathematical Sciences, Faculty of Science, UTM (Malaysia); Zainuddin, Zaitul Marlizawati [Department of Mathematical Sciences, Faculty of Science, UTM (Malaysia)
2014-06-19
This study deals with multiobjective fuzzy stochastic linear programming problems with uncertainty probability distribution which are defined as fuzzy assertions by ambiguous experts. The problem formulation has been presented and the two solutions strategies are; the fuzzy transformation via ranking function and the stochastic transformation when α{sup –}. cut technique and linguistic hedges are used in the uncertainty probability distribution. The development of Sen’s method is employed to find a compromise solution, supported by illustrative numerical example.
Probability Estimation in the Framework of Intuitionistic Fuzzy Evidence Theory
Yafei Song
2015-01-01
Full Text Available Intuitionistic fuzzy (IF evidence theory, as an extension of Dempster-Shafer theory of evidence to the intuitionistic fuzzy environment, is exploited to process imprecise and vague information. Since its inception, much interest has been concentrated on IF evidence theory. Many works on the belief functions in IF information systems have appeared. Although belief functions on the IF sets can deal with uncertainty and vagueness well, it is not convenient for decision making. This paper addresses the issue of probability estimation in the framework of IF evidence theory with the hope of making rational decision. Background knowledge about evidence theory, fuzzy set, and IF set is firstly reviewed, followed by introduction of IF evidence theory. Axiomatic properties of probability distribution are then proposed to assist our interpretation. Finally, probability estimations based on fuzzy and IF belief functions together with their proofs are presented. It is verified that the probability estimation method based on IF belief functions is also potentially applicable to classical evidence theory and fuzzy evidence theory. Moreover, IF belief functions can be combined in a convenient way once they are transformed to interval-valued possibilities.
Majid Moshtagh Khorasani
2009-04-01
Full Text Available
Billingsley, Patrick
2012-01-01
Praise for the Third Edition "It is, as far as I'm concerned, among the best books in math ever written....if you are a mathematician and want to have the top reference in probability, this is it." (Amazon.com, January 2006) A complete and comprehensive classic in probability and measure theory Probability and Measure, Anniversary Edition by Patrick Billingsley celebrates the achievements and advancements that have made this book a classic in its field for the past 35 years. Now re-issued in a new style and format, but with the reliable content that the third edition was revered for, this
Word Similarity from Dictionaries: Inferring Fuzzy Measures from Fuzzy Graphs
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.
Measurement uncertainty and probability
Willink, Robin
2013-01-01
A measurement result is incomplete without a statement of its 'uncertainty' or 'margin of error'. But what does this statement actually tell us? By examining the practical meaning of probability, this book discusses what is meant by a '95 percent interval of measurement uncertainty', and how such an interval can be calculated. The book argues that the concept of an unknown 'target value' is essential if probability is to be used as a tool for evaluating measurement uncertainty. It uses statistical concepts, such as a conditional confidence interval, to present 'extended' classical methods for evaluating measurement uncertainty. The use of the Monte Carlo principle for the simulation of experiments is described. Useful for researchers and graduate students, the book also discusses other philosophies relating to the evaluation of measurement uncertainty. It employs clear notation and language to avoid the confusion that exists in this controversial field of science.
Quantum probability measures and tomographic probability densities
Amosov, GG; Man'ko, [No Value
2004-01-01
Using a simple relation of the Dirac delta-function to generalized the theta-function, the relationship between the tomographic probability approach and the quantum probability measure approach with the description of quantum states is discussed. The quantum state tomogram expressed in terms of the
Human error probability quantification using fuzzy methodology in nuclear plants
Nascimento, Claudio Souza do
2010-01-01
This work obtains Human Error Probability (HEP) estimates from operator's actions in response to emergency situations a hypothesis on Research Reactor IEA-R1 from IPEN. It was also obtained a Performance Shaping Factors (PSF) evaluation in order to classify them according to their influence level onto the operator's actions and to determine these PSF actual states over the plant. Both HEP estimation and PSF evaluation were done based on Specialists Evaluation using interviews and questionnaires. Specialists group was composed from selected IEA-R1 operators. Specialist's knowledge representation into linguistic variables and group evaluation values were obtained through Fuzzy Logic and Fuzzy Set Theory. HEP obtained values show good agreement with literature published data corroborating the proposed methodology as a good alternative to be used on Human Reliability Analysis (HRA). (author)
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.
Consolidity analysis for fully fuzzy functions, matrices, probability and statistics
Walaa Ibrahim Gabr
2015-03-01
Full Text Available The paper presents a comprehensive review of the know-how for developing the systems consolidity theory for modeling, analysis, optimization and design in fully fuzzy environment. The solving of systems consolidity theory included its development for handling new functions of different dimensionalities, fuzzy analytic geometry, fuzzy vector analysis, functions of fuzzy complex variables, ordinary differentiation of fuzzy functions and partial fraction of fuzzy polynomials. On the other hand, the handling of fuzzy matrices covered determinants of fuzzy matrices, the eigenvalues of fuzzy matrices, and solving least-squares fuzzy linear equations. The approach demonstrated to be also applicable in a systematic way in handling new fuzzy probabilistic and statistical problems. This included extending the conventional probabilistic and statistical analysis for handling fuzzy random data. Application also covered the consolidity of fuzzy optimization problems. Various numerical examples solved have demonstrated that the new consolidity concept is highly effective in solving in a compact form the propagation of fuzziness in linear, nonlinear, multivariable and dynamic problems with different types of complexities. Finally, it is demonstrated that the implementation of the suggested fuzzy mathematics can be easily embedded within normal mathematics through building special fuzzy functions library inside the computational Matlab Toolbox or using other similar software languages.
Class dependency of fuzzy relational database using relational calculus and conditional probability
Deni Akbar, Mohammad; Mizoguchi, Yoshihiro; Adiwijaya
2018-03-01
In this paper, we propose a design of fuzzy relational database to deal with a conditional probability relation using fuzzy relational calculus. In the previous, there are several researches about equivalence class in fuzzy database using similarity or approximate relation. It is an interesting topic to investigate the fuzzy dependency using equivalence classes. Our goal is to introduce a formulation of a fuzzy relational database model using the relational calculus on the category of fuzzy relations. We also introduce general formulas of the relational calculus for the notion of database operations such as ’projection’, ’selection’, ’injection’ and ’natural join’. Using the fuzzy relational calculus and conditional probabilities, we introduce notions of equivalence class, redundant, and dependency in the theory fuzzy relational database.
Fuzzy probability based fault tree analysis to propagate and quantify epistemic uncertainty
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
Fuzzy Failure Probability of Transmission Pipelines in the Niger ...
We undertake the apportioning of failure possibility on twelve identified third party activities contributory to failure of transmission pipelines in the Niger Delta region of Nigeria, using the concept of fuzzy possibility scores. Expert elicitation technique generates linguistic variables that are transformed using fuzzy set theory ...
Fuzzy Treatment of Candidate Outliers in Measurements
Giampaolo E. D'Errico
2012-01-01
Full Text Available Robustness against the possible occurrence of outlying observations is critical to the performance of a measurement process. Open questions relevant to statistical testing for candidate outliers are reviewed. A novel fuzzy logic approach is developed and exemplified in a metrology context. A simulation procedure is presented and discussed by comparing fuzzy versus probabilistic models.
Na, Man Gyun; Oh, Seungrohk
2002-01-01
A neuro-fuzzy inference system combined with the wavelet denoising, principal component analysis (PCA), and sequential probability ratio test (SPRT) methods has been developed to monitor the relevant sensor using the information of other sensors. The parameters of the neuro-fuzzy inference system that estimates the relevant sensor signal are optimized by a genetic algorithm and a least-squares algorithm. The wavelet denoising technique was applied to remove noise components in input signals into the neuro-fuzzy system. By reducing the dimension of an input space into the neuro-fuzzy system without losing a significant amount of information, the PCA was used to reduce the time necessary to train the neuro-fuzzy system, simplify the structure of the neuro-fuzzy inference system, and also, make easy the selection of the input signals into the neuro-fuzzy system. By using the residual signals between the estimated signals and the measured signals, the SPRT is applied to detect whether the sensors are degraded or not. The proposed sensor-monitoring algorithm was verified through applications to the pressurizer water level, the pressurizer pressure, and the hot-leg temperature sensors in pressurized water reactors
Markowitz portfolio optimization model employing fuzzy measure
Ramli, Suhailywati; Jaaman, Saiful Hafizah
2017-04-01
Markowitz in 1952 introduced the mean-variance methodology for the portfolio selection problems. His pioneering research has shaped the portfolio risk-return model and become one of the most important research fields in modern finance. This paper extends the classical Markowitz's mean-variance portfolio selection model applying the fuzzy measure to determine the risk and return. In this paper, we apply the original mean-variance model as a benchmark, fuzzy mean-variance model with fuzzy return and the model with return are modeled by specific types of fuzzy number for comparison. The model with fuzzy approach gives better performance as compared to the mean-variance approach. The numerical examples are included to illustrate these models by employing Malaysian share market data.
Word Similarity From Dictionaries: Inferring Fuzzy Measures From Fuzzy Graphs
Torra
2008-01-01
Full Text Available 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.
Introduction to probability and measure
Parthasarathy, K R
2005-01-01
According to a remark attributed to Mark Kac 'Probability Theory is a measure theory with a soul'. This book with its choice of proofs, remarks, examples and exercises has been prepared taking both these aesthetic and practical aspects into account.
Complex Fuzzy Set-Valued Complex Fuzzy Measures and Their Properties
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
Two New Measures of Fuzzy Divergence and Their Properties
Om Parkash
2006-06-01
Full Text Available Several measures of directed divergence and their corresponding measures of fuzzy divergence are available in the exiting literature. Two new measures of fuzzy divergence have been developed and their desirable properties have been discussed.
Yu, D.; Kastenberg, W.E.; Okrent, D.
1994-01-01
A new approach is presented for evaluating the uncertainties inherent in severe accident management strategies. At first, this analysis considers accident management as a decision problem (i.e., applying a strategy compared with do nothing) and uses an influence diagram. To evaluate imprecise node probabilities in the influence diagram, the analysis introduces the concept of a fuzzy probability. When fuzzy logic is applied, fuzzy probabilities are easily propagated to obtain results. In addition, the results obtained provide not only information similar to the classical approach, which uses point-estimate values, but also additional information regarding the impact of using imprecise input data. As an illustrative example, the proposed methodology is applied to the evaluation of the drywell flooding strategy for a long-term station blackout sequence at the Peach Bottom nuclear power plant. The results show that the drywell flooding strategy is beneficial for preventing reactor vessel breach. It is also effective for reducing the probability of containment failure for both liner melt-through and late overpressurization. Even though uncertainty exists in the results, flooding is preferred to do nothing when evaluated in terms of two risk measures: early and late fatalities
Doubravsky, Karel; Dohnal, Mirko
2015-01-01
Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (re)checked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items) can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities) are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details.
Karel Doubravsky
Full Text Available Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (rechecked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details.
Using Fuzzy Probability Weights in Cumulative Prospect Theory
Užga-Rebrovs Oļegs
2016-12-01
Full Text Available During the past years, a rapid growth has been seen in the descriptive approaches to decision choice. As opposed to normative expected utility theory, these approaches are based on the subjective perception of probabilities by the individuals, which takes place in real situations of risky choice. The modelling of this kind of perceptions is made on the basis of probability weighting functions. In cumulative prospect theory, which is the focus of this paper, decision prospect outcome weights are calculated using the obtained probability weights. If the value functions are constructed in the sets of positive and negative outcomes, then, based on the outcome value evaluations and outcome decision weights, generalised evaluations of prospect value are calculated, which are the basis for choosing an optimal prospect.
Performance measurement with fuzzy data envelopment analysis
Tavana, Madjid
2014-01-01
The intensity of global competition and ever-increasing economic uncertainties has led organizations to search for more efficient and effective ways to manage their business operations. Data envelopment analysis (DEA) has been widely used as a conceptually simple yet powerful tool for evaluating organizational productivity and performance. Fuzzy DEA (FDEA) is a promising extension of the conventional DEA proposed for dealing with imprecise and ambiguous data in performance measurement problems. This book is the first volume in the literature to present the state-of-the-art developments and applications of FDEA. It is designed for students, educators, researchers, consultants and practicing managers in business, industry, and government with a basic understanding of the DEA and fuzzy logic concepts.
Wu, Yunna; Geng, Shuai; Xu, Hu; Zhang, Haobo
2014-01-01
Highlights: • Experts’ opinions are expressed by using the intuitionistic fuzzy values. • Fuzzy measure is used to solve the dependence problem of criteria. • The compensatory problem of performance scores is reasonably processed. - Abstract: Project selection plays an important role in the entire life cycle of wind farm project and the multi-criteria decision making (MCDM) methods are very important in the whole wind farm project plan selection process. There are problems in the present MCDM methods decrease evaluation quality of the wind farm project plans: first, the information loss exists in the wind farm project plan evaluation process. Second, it is difficult to satisfy the independent assumption of the multi-criteria decision making methods used in the wind farm project plan evaluation in fact. Third, the compensatory problem of performance scores of the wind farm project plans is processed unreasonably. Hence the innovation points of this paper are as follows: first, the intuitionistic fuzzy numbers are used instead of fuzzy numbers or numerical values to reflect the experts’ intuitive preferences to decrease the probability of information loss; second, the fuzzy measure is used to rate the important degrees of criteria in order to avoid the independent assumption and to increase the reasonability; third, the partial compensatory problem of performance scores is well processed by using intuitionistic fuzzy Choquet (IFC) operator and generalized intuitionistic fuzzy ordered geometric averaging (GIFOGA) operator. These operators can deal with the compensatory performance scores and non-compensatory performance scores respectively. Finally, a case study demonstrates the effectiveness of decision framework
Use of an influence diagram and fuzzy probability for evaluating accident management in a BWR
Yu, Donghan; Okrent, D.; Kastenberg, W.E.
1993-01-01
This paper develops a new approach for evaluating severe accident management strategies. At first, this approach considers accident management as a decision problem (i.e., ''applying a strategy'' vs. ''do nothing'') and uses influence diagrams. This approach introduces the concept of a ''fuzzy probability'' in the evaluation of an influence diagram. When fuzzy logic is applied, fuzzy probabilities in an influence diagram can be easily propagated to obtain results. In addition, the results obtained provide not only information similar to the classical approach using point-estimate values, but also additional information regarding the impact from imprecise input data. The proposed methodology is applied to the evaluation of the drywell flooding strategy for a long-term station blackout sequence in the Peach Bottom nuclear power plant. The results show that the drywell flooding strategy seems to be beneficial for preventing reactor vessel breach. It is also effective for reducing the probability of the containment failure for both liner melt-through and late overpressurization. Even though there exists uncertainty in the results, ''flooding'' is preferred to ''do nothing'' when evaluated in terms of expected consequences, i.e., early and late fatalities
Çiğdem ÖZARİ
2018-01-01
Full Text Available In this study, we have worked on developing a brand-new index called Fuzzy-bankruptcy index. The aim of this index is to find out the default probability of any company X, independent from the sector it belongs. Fuzzy logic is used to state the financial ratiointerruption change related with time and inside different sectors, the new index is created to eliminate the number of the relativity of financial ratios. The four input variables inside the five main input variables used for the fuzzy process, are chosen from both factor analysis and clustering and the last input variable calculated from Merton Model. As we analyze in the past cases of the default history of companies, one could explore different reasons such as managerial arrogance, fraud and managerial mistakes, that are responsible for the very poor endings of prestigious companies like Enron, K-Mart. Because of these kind of situations, we try to design a model which one could be able to get a better view of a company’s financial position, and it couldbe prevent credit loan companies from investing in the wrong company and possibly from losing all investments using our Fuzzy-bankruptcy index.
Probability Measures on Groups IX
1989-01-01
The latest in this series of Oberwolfach conferences focussed on the interplay between structural probability theory and various other areas of pure and applied mathematics such as Tauberian theory, infinite-dimensional rotation groups, central limit theorems, harmonizable processes, and spherical data. Thus it was attended by mathematicians whose research interests range from number theory to quantum physics in conjunction with structural properties of probabilistic phenomena. This volume contains 5 survey articles submitted on special invitation and 25 original research papers.
Triangular and Trapezoidal Fuzzy State Estimation with Uncertainty on Measurements
Mohammad Sadeghi Sarcheshmah
2012-01-01
Full Text Available In this paper, a new method for uncertainty analysis in fuzzy state estimation is proposed. The uncertainty is expressed in measurements. Uncertainties in measurements are modelled with different fuzzy membership functions (triangular and trapezoidal. To find the fuzzy distribution of any state variable, the problem is formulated as a constrained linear programming (LP optimization. The viability of the proposed method would be verified with the ones obtained from the weighted least squares (WLS and the fuzzy state estimation (FSE in the 6-bus system and in the IEEE-14 and 30 bus system.
Estimation of Fuzzy Measures Using Covariance Matrices in Gaussian Mixtures
Nishchal K. Verma
2012-01-01
Full Text Available This paper presents a novel computational approach for estimating fuzzy measures directly from Gaussian mixtures model (GMM. The mixture components of GMM provide the membership functions for the input-output fuzzy sets. By treating consequent part as a function of fuzzy measures, we derived its coefficients from the covariance matrices found directly from GMM and the defuzzified output constructed from both the premise and consequent parts of the nonadditive fuzzy rules that takes the form of Choquet integral. The computational burden involved with the solution of λ-measure is minimized using Q-measure. The fuzzy model whose fuzzy measures were computed using covariance matrices found in GMM has been successfully applied on two benchmark problems and one real-time electric load data of Indian utility. The performance of the resulting model for many experimental studies including the above-mentioned application is found to be better and comparable to recent available fuzzy models. The main contribution of this paper is the estimation of fuzzy measures efficiently and directly from covariance matrices found in GMM, avoiding the computational burden greatly while learning them iteratively and solving polynomial equations of order of the number of input-output variables.
Fuzzy Relational Databases: Representational Issues and Reduction Using Similarity Measures.
Prade, Henri; Testemale, Claudette
1987-01-01
Compares and expands upon two approaches to dealing with fuzzy relational databases. The proposed similarity measure is based on a fuzzy Hausdorff distance and estimates the mismatch between two possibility distributions using a reduction process. The consequences of the reduction process on query evaluation are studied. (Author/EM)
Sohrab Khanmohammadi
2013-11-01
Full Text Available A Wireless Sensor Network (WSN is a collection of low-cost, low-power and large-scale wireless sensor nodes. Routing protocols are an important topic in WSN. Every sensor node should use a proper mechanism to transmit the generated packets to its destination, usually a base station. In previous works, routing protocols use the global information of the network that causes the redundant packets to be increased. Moreover, it leads to an increase in the network traffic, to a decrease in the delivery ratio of data packets, and to a reduction in network life. In this paper, we propose a new inferential routing protocol called SFRRP (Static Three-Dimensional Fuzzy Routing based on the Receiving Probability. The proposed protocol solves the above mentioned problems considerably. The data packets are transmitted by hop-to-hop delivery to the base station. It uses a fuzzy procedure to transmit the sensed data or the buffered data packets to one of the neighbors called selected node. In the proposed fuzzy system, the distance and number of neighbors are input variables, while the receiving probability is the output variable. SFRRP just uses the local neighborhood information to forward the packets and is not needed by any redundant packet for route discovery. The proposed protocol has some advantages such as a high delivery ratio, less delay time, high network life, and less network traffic. The performance of the proposed protocol surpasses the performance of the Flooding routing protocol in terms of delivery ratio, delay time and network lifetime.
Pablo J. Villacorta
2016-07-01
Full Text Available Markov chains are well-established probabilistic models of a wide variety of real systems that evolve along time. Countless examples of applications of Markov chains that successfully capture the probabilistic nature of real problems include areas as diverse as biology, medicine, social science, and engineering. One interesting feature which characterizes certain kinds of Markov chains is their stationary distribution, which stands for the global fraction of time the system spends in each state. The computation of the stationary distribution requires precise knowledge of the transition probabilities. When the only information available is a sequence of observations drawn from the system, such probabilities have to be estimated. Here we review an existing method to estimate fuzzy transition probabilities from observations and, with them, obtain the fuzzy stationary distribution of the resulting fuzzy Markov chain. The method also works when the user directly provides fuzzy transition probabilities. We provide an implementation in the R environment that is the first available to the community and serves as a proof of concept. We demonstrate the usefulness of our proposal with computational experiments on a toy problem, namely a time-homogeneous Markov chain that guides the randomized movement of an autonomous robot that patrols a small area.
Fuzzy measure analysis of public attitude towards the use of nuclear energy
Nishiwaki, Y.; Preyssl, C.; Onisawa, T.; Sen'ichi Mokuya
1996-01-01
It is important to identify the structure of public acceptance or rejection when new technologies are developed and implemented The structure of attitudes should have the essential attributes and their interrelation. In such a structural analysis the attitudes need to be decomposed into meaningful attributes by a suitable model However, the data obtained in this type of study may be more or less subjective and fuzzy, and the following problems may be pointed out: (1.) A man does net always have an additive measure such as probability to evaluate fuzzy objects, (2.) The attributes of an object in bis evaluation process are not always independent of each other. In either case a linear model may not be applicable. This paper is concerned with applying fuzzy measures and fuzzy integrals to analyze public attitude towards the use of nuclear energy. We applied the fuzzy measures and fuzzy integrals to analyze public attitude towards the use of nuclear energy by distributing questionnaires to about 100 students of Engineering Department of Kinki University, Higashi-Osaka, Osaka, Japan. Before and after the Chernobyl Accident we noticed a distinct difference in mental structure Before the accident, the students of pro-nuclear group were whole-heartedly in favour of the use of nuclear energy, based on fringe benefits, impacts on society and economic progress, but after the accident they showed a favourable attitude towards the use of nuclear energy based on economic progress, but with some reservation because of the potential threats. (author)
Gholamreza Norouzi
2015-01-01
Full Text Available In project management context, time management is one of the most important factors affecting project success. This paper proposes a new method to solve research project scheduling problems (RPSP containing Fuzzy Graphical Evaluation and Review Technique (FGERT networks. Through the deliverables of this method, a proper estimation of project completion time (PCT and success probability can be achieved. So algorithms were developed to cover all features of the problem based on three main parameters “duration, occurrence probability, and success probability.” These developed algorithms were known as PR-FGERT (Parallel and Reversible-Fuzzy GERT networks. The main provided framework includes simplifying the network of project and taking regular steps to determine PCT and success probability. Simplifications include (1 equivalent making of parallel and series branches in fuzzy network considering the concepts of probabilistic nodes, (2 equivalent making of delay or reversible-to-itself branches and impact of changing the parameters of time and probability based on removing related branches, (3 equivalent making of simple and complex loops, and (4 an algorithm that was provided to resolve no-loop fuzzy network, after equivalent making. Finally, the performance of models was compared with existing methods. The results showed proper and real performance of models in comparison with existing methods.
Introduction to probability and measure theories
Partasarati, K.
1983-01-01
Chapters of probability and measured theories are presented. The Borele images of spaces with the measure into each other and in separate metric spaces are studied. The Kolmogorov theorem on the continuation of probabilies is drawn from the theorem on the measure continuation to the projective limits of spaces with measure. The integration theory is plotted, measures on multiplications of spaces are studied. The theory of conventional mathematical expectations by projections in Hilbert space is presented. In conclusion, the theory of weak convergence of measures of elements of the theory of characteristic functions and the theory of invariant and quasi-invariant measures on groups and homogeneous spaces is given
Nascimento, C.S. do; Mesquita, R.N. de
2009-01-01
Recent studies point human error as an important factor for many industrial and nuclear accidents: Three Mile Island (1979), Bhopal (1984), Chernobyl and Challenger (1986) are classical examples. Human contribution to these accidents may be better understood and analyzed by using Human Reliability Analysis (HRA), which has being taken as an essential part on Probabilistic Safety Analysis (PSA) of nuclear plants. Both HRA and PSA depend on Human Error Probability (HEP) for a quantitative analysis. These probabilities are extremely affected by the Performance Shaping Factors (PSF), which has a direct effect on human behavior and thus shape HEP according with specific environment conditions and personal individual characteristics which are responsible for these actions. This PSF dependence raises a great problem on data availability as turn these scarcely existent database too much generic or too much specific. Besides this, most of nuclear plants do not keep historical records of human error occurrences. Therefore, in order to overcome this occasional data shortage, a methodology based on Fuzzy Inference and expert judgment was employed in this paper in order to determine human error occurrence probabilities and to evaluate PSF's on performed actions by operators in a nuclear power plant (IEA-R1 nuclear reactor). Obtained HEP values were compared with reference tabled data used on current literature in order to show method coherence and valid approach. This comparison leads to a conclusion that this work results are able to be employed both on HRA and PSA enabling efficient prospection of plant safety conditions, operational procedures and local working conditions potential improvements (author)
Nascimento, Claudio Souza do
2010-07-01
This work obtains Human Error Probability (HEP) estimates from operator's actions in response to emergency situations a hypothesis on Research Reactor IEA-R1 from IPEN. It was also obtained a Performance Shaping Factors (PSF) evaluation in order to classify them according to their influence level onto the operator's actions and to determine these PSF actual states over the plant. Both HEP estimation and PSF evaluation were done based on Specialists Evaluation using interviews and questionnaires. Specialists group was composed from selected IEA-R1 operators. Specialist's knowledge representation into linguistic variables and group evaluation values were obtained through Fuzzy Logic and Fuzzy Set Theory. HEP obtained values show good agreement with literature published data corroborating the proposed methodology as a good alternative to be used on Human Reliability Analysis (HRA). (author)
Measurement of the resonance escape probability
Anthony, J.P.; Bacher, P.; Lheureux, L.; Moreau, J.; Schmitt, A.P.
1957-01-01
The average cadmium ratio in natural uranium rods has been measured, using equal diameter natural uranium disks. These values correlated with independent measurements of the lattice buckling, enabled us to calculate values of the resonance escape probability for the G1 reactor with one or the other of two definitions. Measurements were performed on 26 mm and 32 mm rods, giving the following values for the resonance escape probability p: 0.8976 ± 0.005 and 0.912 ± 0.006 (d. 26 mm), 0.8627 ± 0.009 and 0.884 ± 0.01 (d. 32 mm). The influence of either definition on the lattice parameters is discussed, leading to values of the effective integral. Similar experiments have been performed with thorium rods. (author) [fr
A fuzzy MCDM framework based on fuzzy measure and fuzzy integral for agile supplier evaluation
Dursun, Mehtap
2017-06-01
Supply chains need to be agile in order to response quickly to the changes in today's competitive environment. The success of an agile supply chain depends on the firm's ability to select the most appropriate suppliers. This study proposes a multi-criteria decision making technique for conducting an analysis based on multi-level hierarchical structure and fuzzy logic for the evaluation of agile suppliers. The ideal and anti-ideal solutions are taken into consideration simultaneously in the developed approach. The proposed decision approach enables the decision-makers to use linguistic terms, and thus, reduce their cognitive burden in the evaluation process. Furthermore, a hierarchy of evaluation criteria and their related sub-criteria is employed in the presented approach in order to conduct a more effective analysis.
Shiryaev, A N
1996-01-01
This book contains a systematic treatment of probability from the ground up, starting with intuitive ideas and gradually developing more sophisticated subjects, such as random walks, martingales, Markov chains, ergodic theory, weak convergence of probability measures, stationary stochastic processes, and the Kalman-Bucy filter Many examples are discussed in detail, and there are a large number of exercises The book is accessible to advanced undergraduates and can be used as a text for self-study This new edition contains substantial revisions and updated references The reader will find a deeper study of topics such as the distance between probability measures, metrization of weak convergence, and contiguity of probability measures Proofs for a number of some important results which were merely stated in the first edition have been added The author included new material on the probability of large deviations, and on the central limit theorem for sums of dependent random variables
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.
A Hybrid Fuzzy Model for Lean Product Development Performance Measurement
Osezua Aikhuele, Daniel; Mohd Turan, Faiz
2016-02-01
In the effort for manufacturing companies to meet up with the emerging consumer demands for mass customized products, many are turning to the application of lean in their product development process, and this is gradually moving from being a competitive advantage to a necessity. However, due to lack of clear understanding of the lean performance measurements, many of these companies are unable to implement and fully integrated the lean principle into their product development process. Extensive literature shows that only few studies have focus systematically on the lean product development performance (LPDP) evaluation. In order to fill this gap, the study therefore proposed a novel hybrid model based on Fuzzy Reasoning Approach (FRA), and the extension of Fuzzy-AHP and Fuzzy-TOPSIS methods for the assessment of the LPDP. Unlike the existing methods, the model considers the importance weight of each of the decision makers (Experts) since the performance criteria/attributes are required to be rated, and these experts have different level of expertise. The rating is done using a new fuzzy Likert rating scale (membership-scale) which is designed such that it can address problems resulting from information lost/distortion due to closed-form scaling and the ordinal nature of the existing Likert scale.
Measures, Probability and Holography in Cosmology
Phillips, Daniel
This dissertation compiles four research projects on predicting values for cosmological parameters and models of the universe on the broadest scale. The first examines the Causal Entropic Principle (CEP) in inhomogeneous cosmologies. The CEP aims to predict the unexpectedly small value of the cosmological constant Lambda using a weighting by entropy increase on causal diamonds. The original work assumed a purely isotropic and homogeneous cosmology. But even the level of inhomogeneity observed in our universe forces reconsideration of certain arguments about entropy production. In particular, we must consider an ensemble of causal diamonds associated with each background cosmology and we can no longer immediately discard entropy production in the far future of the universe. Depending on our choices for a probability measure and our treatment of black hole evaporation, the prediction for Lambda may be left intact or dramatically altered. The second related project extends the CEP to universes with curvature. We have found that curvature values larger than rho k = 40rhom are disfavored by more than $99.99% and a peak value at rhoLambda = 7.9 x 10-123 and rhok =4.3rho m for open universes. For universes that allow only positive curvature or both positive and negative curvature, we find a correlation between curvature and dark energy that leads to an extended region of preferred values. Our universe is found to be disfavored to an extent depending the priors on curvature. We also provide a comparison to previous anthropic constraints on open universes and discuss future directions for this work. The third project examines how cosmologists should formulate basic questions of probability. We argue using simple models that all successful practical uses of probabilities originate in quantum fluctuations in the microscopic physical world around us, often propagated to macroscopic scales. Thus we claim there is no physically verified fully classical theory of probability. We
Dynamic equivalence relation on the fuzzy measure algebras
Roya Ghasemkhani
2017-04-01
Full Text Available The main goal of the present paper is to extend classical results from the measure theory and dynamical systems to the fuzzy subset setting. In this paper, the notion of dynamic equivalence relation is introduced and then it is proved that this relation is an equivalence relation. Also, a new metric on the collection of all equivalence classes is introduced and it is proved that this metric is complete.
On fuzzy semantic similarity measure for DNA coding.
Ahmad, Muneer; Jung, Low Tang; Bhuiyan, Md Al-Amin
2016-02-01
A coding measure scheme numerically translates the DNA sequence to a time domain signal for protein coding regions identification. A number of coding measure schemes based on numerology, geometry, fixed mapping, statistical characteristics and chemical attributes of nucleotides have been proposed in recent decades. Such coding measure schemes lack the biologically meaningful aspects of nucleotide data and hence do not significantly discriminate coding regions from non-coding regions. This paper presents a novel fuzzy semantic similarity measure (FSSM) coding scheme centering on FSSM codons׳ clustering and genetic code context of nucleotides. Certain natural characteristics of nucleotides i.e. appearance as a unique combination of triplets, preserving special structure and occurrence, and ability to own and share density distributions in codons have been exploited in FSSM. The nucleotides׳ fuzzy behaviors, semantic similarities and defuzzification based on the center of gravity of nucleotides revealed a strong correlation between nucleotides in codons. The proposed FSSM coding scheme attains a significant enhancement in coding regions identification i.e. 36-133% as compared to other existing coding measure schemes tested over more than 250 benchmarked and randomly taken DNA datasets of different organisms. Copyright © 2015 Elsevier Ltd. All rights reserved.
Yafei Song
2014-01-01
Full Text Available As a generation of ordinary fuzzy set, the concept of intuitionistic fuzzy set (IFS, characterized both by a membership degree and by a nonmembership degree, is a more flexible way to cope with the uncertainty. Similarity measures of intuitionistic fuzzy sets are used to indicate the similarity degree between intuitionistic fuzzy sets. Although many similarity measures for intuitionistic fuzzy sets have been proposed in previous studies, some of those cannot satisfy the axioms of similarity or provide counterintuitive cases. In this paper, a new similarity measure and weighted similarity measure between IFSs are proposed. It proves that the proposed similarity measures satisfy the properties of the axiomatic definition for similarity measures. Comparison between the previous similarity measures and the proposed similarity measure indicates that the proposed similarity measure does not provide any counterintuitive cases. Moreover, it is demonstrated that the proposed similarity measure is capable of discriminating difference between patterns.
Aihong Ren
2016-01-01
This paper is concerned with a class of fully fuzzy bilevel linear programming problems where all the coefficients and decision variables of both objective functions and the constraints are fuzzy numbers. A new approach based on deviation degree measures and a ranking function method is proposed to solve these problems. We first introduce concepts of the feasible region and the fuzzy optimal solution of a fully fuzzy bilevel linear programming problem. In order to obtain a fuzzy optimal solut...
Trending in Probability of Collision Measurements
Vallejo, J. J.; Hejduk, M. D.; Stamey, J. D.
2015-01-01
A simple model is proposed to predict the behavior of Probabilities of Collision (P(sub c)) for conjunction events. The model attempts to predict the location and magnitude of the peak P(sub c) value for an event by assuming the progression of P(sub c) values can be modeled to first order by a downward-opening parabola. To incorporate prior information from a large database of past conjunctions, the Bayes paradigm is utilized; and the operating characteristics of the model are established through a large simulation study. Though the model is simple, it performs well in predicting the temporal location of the peak (P(sub c)) and thus shows promise as a decision aid in operational conjunction assessment risk analysis.
Method for solving fully fuzzy linear programming problems using deviation degree measure
Haifang Cheng; Weilai Huang; Jianhu Cai
2013-01-01
A new ful y fuzzy linear programming (FFLP) prob-lem with fuzzy equality constraints is discussed. Using deviation degree measures, the FFLP problem is transformed into a crispδ-parametric linear programming (LP) problem. Giving the value of deviation degree in each constraint, the δ-fuzzy optimal so-lution of the FFLP problem can be obtained by solving this LP problem. An algorithm is also proposed to find a balance-fuzzy optimal solution between two goals in conflict: to improve the va-lues of the objective function and to decrease the values of the deviation degrees. A numerical example is solved to il ustrate the proposed method.
Xiao Luo
2017-01-01
Full Text Available An intuitionistic fuzzy VIKOR (IF-VIKOR method is proposed based on a new distance measure considering the waver of intuitionistic fuzzy information. The method aggregates all individual decision-makers’ assessment information based on intuitionistic fuzzy weighted averaging operator (IFWA, determines the weights of decision-makers and attributes objectively using intuitionistic fuzzy entropy, calculates the group utility and individual regret by the new distance measure, and then reaches a compromise solution. It can be effectively applied to multiattribute decision-making (MADM problems where the weights of decision-makers and attributes are completely unknown and the attribute values are intuitionistic fuzzy numbers (IFNs. The validity and stability of this method are verified by example analysis and sensitivity analysis, and its superiority is illustrated by the comparison with the existing method.
Modeling and measuring the effects of imprecision using fuzzy theory and bayesian theory
Yu, Dong Han; Park, Won S.
1999-01-01
This study presents two approaches for evaluating the imprecision inherent in the PRA. Current PRA methodology uses expert opinion in the assessment of rare event probabilities. The problem is that these probabilities may be difficult to estimate even though reasonable engineering judgment is applied. This occurs because expert opinion under incomplete knowledge and limited data is inherently imprecise and uncertain in the analysis of severe accident management. In this case, the concept of uncertainty about a probability value, namely the high-order uncertainty, would be both intuitively appealing and potentially useful. This analysis considers first an accident management as a decision problem (i.e., 'applying a strategy' vs. 'do nothing') and uses an influence diagram. Then, the analysis applies two approaches to evaluate imprecise node probabilities in the influence diagram: 'a fuzzy probability' and 'an interval-valued subjective probability'. For the propagation of subjective probabilities, the analysis uses the Monte-Carlo simulation. In case of fuzzy probabilities, the fuzzy logic is applied to propagate them. We believe that these approaches can allow us to understand uncertainties associated with severe accident management strategy since they offer additional information regarding the impact from imprecise input data
Using inferred probabilities to measure the accuracy of imprecise forecasts
Paul Lehner
2012-11-01
Full Text Available Research on forecasting is effectively limited to forecasts that are expressed with clarity; which is to say that the forecasted event must be sufficiently well-defined so that it can be clearly resolved whether or not the event occurred and forecasts certainties are expressed as quantitative probabilities. When forecasts are expressed with clarity, then quantitative measures (scoring rules, calibration, discrimination, etc. can be used to measure forecast accuracy, which in turn can be used to measure the comparative accuracy of different forecasting methods. Unfortunately most real world forecasts are not expressed clearly. This lack of clarity extends to both the description of the forecast event and to the use of vague language to express forecast certainty. It is thus difficult to assess the accuracy of most real world forecasts, and consequently the accuracy the methods used to generate real world forecasts. This paper addresses this deficiency by presenting an approach to measuring the accuracy of imprecise real world forecasts using the same quantitative metrics routinely used to measure the accuracy of well-defined forecasts. To demonstrate applicability, the Inferred Probability Method is applied to measure the accuracy of forecasts in fourteen documents examining complex political domains. Key words: inferred probability, imputed probability, judgment-based forecasting, forecast accuracy, imprecise forecasts, political forecasting, verbal probability, probability calibration.
Probability measures, Lévy measures and analyticity in time
Barndorff-Nielsen, Ole Eiler; Hubalek, Friedrich
2008-01-01
We investigate the relation of the semigroup probability density of an infinite activity Lévy process to the corresponding Lévy density. For subordinators, we provide three methods to compute the former from the latter. The first method is based on approximating compound Poisson distributions...
Probability Measures, Lévy Measures, and Analyticity in Time
Barndorff-Nielsen, Ole Eiler; Hubalek, Friedrich
We investigate the relation of the semigroup probability density of an infinite activity Lévy process to the corresponding Lévy density. For subordinators we provide three methods to compute the former from the latter. The first method is based on approximating compound Poisson distributions...
Reliable Portfolio Selection Problem in Fuzzy Environment: An mλ Measure Based Approach
Yuan Feng
2017-04-01
Full Text Available This paper investigates a fuzzy portfolio selection problem with guaranteed reliability, in which the fuzzy variables are used to capture the uncertain returns of different securities. To effectively handle the fuzziness in a mathematical way, a new expected value operator and variance of fuzzy variables are defined based on the m λ measure that is a linear combination of the possibility measure and necessity measure to balance the pessimism and optimism in the decision-making process. To formulate the reliable portfolio selection problem, we particularly adopt the expected total return and standard variance of the total return to evaluate the reliability of the investment strategies, producing three risk-guaranteed reliable portfolio selection models. To solve the proposed models, an effective genetic algorithm is designed to generate the approximate optimal solution to the considered problem. Finally, the numerical examples are given to show the performance of the proposed models and algorithm.
Omidvar, Mohsen; Mazloumi, Adel; Mohammad Fam, Iraj; Nirumand, Fereshteh
2017-01-01
Resilience engineering (RE) can be an alternative technique to the traditional risk assessment and management techniques, to predict and manage safety conditions of modern socio-technical organizations. While traditional risk management approaches are retrospective and highlight error calculation and computation of malfunction possibilities, resilience engineering seeks ways to improve capacity at all levels of organizations in order to build strong yet flexible processes. Considering the resilience potential measurement as a concern in complex working systems, the aim of this study was to quantify the resilience by the help of fuzzy sets and Multi-Criteria Decision-Making (MCDM) techniques. In this paper, we adopted the fuzzy analytic hierarchy process (FAHP) method to measure resilience in a gas refinery plant. A resilience assessment framework containing six indicators, each with its own sub-indicators, was constructed. Then, the fuzzy weights of the indicators and the sub-indicators were derived from pair-wise comparisons conducted by experts. The fuzzy evaluating vectors of the indicators and the sub-indicators computed according to the initial assessment data. Finally, the Comprehensive Resilience Index (CoRI), Resilience Grade (RG), and Resilience Early Warning Grade (REWG) were established. To demonstrate the applicability of the proposed method, an illustrative example in a gas refinery complex (an instance of socio-technical systems) was provided. CoRI of the refinery ranked as "III". In addition, for the six main indicators, RG and REWG ranked as "III" and "NEWZ", respectively, except for C3, in which RG ranked as "II", and REWG ranked as "OEWZ". The results revealed the engineering practicability and usefulness of the proposed method in resilience evaluation of socio-technical systems.
The Motion Path Study of Measuring Robot Based on Variable Universe Fuzzy Control
Ma Guoqing
2017-01-01
Full Text Available For the problem of measuring robot requires a higher positioning, firstly learning about the error overview of the system, analysised the influence of attitude, speed and other factors on systematic errors. Then collected and analyzed the systematic error curve in the track to complete the planning process. The last adding fuzzy control in both cases, by comparing with the original system, can found that the method based on fuzzy control system can significantly reduce the error during the motion.
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.
Novel Distance Measure in Fuzzy TOPSIS for Supply Chain Strategy Based Supplier Selection
B. Pardha Saradhi
2016-01-01
Full Text Available In today’s highly competitive environment, organizations need to evaluate and select suppliers based on their manufacturing strategy. Identification of supply chain strategy of the organization, determination of decision criteria, and methods of supplier selection are appearing to be the most important components in research area in the field of supply chain management. In this paper, evaluation of suppliers is done based on the balanced scorecard framework using new distance measure in fuzzy TOPSIS by considering the supply chain strategy of the manufacturing organization. To take care of vagueness in decision making, trapezoidal fuzzy number is assumed for pairwise comparisons to determine relative weights of perspectives and criteria of supplier selection. Also, linguistic variables specified in terms of trapezoidal fuzzy number are considered for the payoff values of criteria of the suppliers. These fuzzy numbers satisfied the Jensen based inequality. A detailed application of the proposed methodology is illustrated.
Measurement and probability a probabilistic theory of measurement with applications
Rossi, Giovanni Battista
2014-01-01
Measurement plays a fundamental role both in physical and behavioral sciences, as well as in engineering and technology: it is the link between abstract models and empirical reality and is a privileged method of gathering information from the real world. Is it possible to develop a single theory of measurement for the various domains of science and technology in which measurement is involved? This book takes the challenge by addressing the following main issues: What is the meaning of measurement? How do we measure? What can be measured? A theoretical framework that could truly be shared by scientists in different fields, ranging from physics and engineering to psychology is developed. The future in fact will require greater collaboration between science and technology and between different sciences. Measurement, which played a key role in the birth of modern science, can act as an essential interdisciplinary tool and language for this new scenario. A sound theoretical basis for addressing key problems in mea...
Gap probability - Measurements and models of a pecan orchard
Strahler, Alan H.; Li, Xiaowen; Moody, Aaron; Liu, YI
1992-01-01
Measurements and models are compared for gap probability in a pecan orchard. Measurements are based on panoramic photographs of 50* by 135 view angle made under the canopy looking upwards at regular positions along transects between orchard trees. The gap probability model is driven by geometric parameters at two levels-crown and leaf. Crown level parameters include the shape of the crown envelope and spacing of crowns; leaf level parameters include leaf size and shape, leaf area index, and leaf angle, all as functions of canopy position.
Chiang, Shu-Yin; Kan, Yao-Chiang; Chen, Yun-Shan; Tu, Ying-Ching; Lin, Hsueh-Chun
2016-12-03
Ubiquitous health care (UHC) is beneficial for patients to ensure they complete therapeutic exercises by self-management at home. We designed a fuzzy computing model that enables recognizing assigned movements in UHC with privacy. The movements are measured by the self-developed body motion sensor, which combines both accelerometer and gyroscope chips to make an inertial sensing node compliant with a wireless sensor network (WSN). The fuzzy logic process was studied to calculate the sensor signals that would entail necessary features of static postures and dynamic motions. Combinations of the features were studied and the proper feature sets were chosen with compatible fuzzy rules. Then, a fuzzy inference system (FIS) can be generated to recognize the assigned movements based on the rules. We thus implemented both fuzzy and adaptive neuro-fuzzy inference systems in the model to distinguish static and dynamic movements. The proposed model can effectively reach the recognition scope of the assigned activity. Furthermore, two exercises of upper-limb flexion in physical therapy were applied for the model in which the recognition rate can stand for the passing rate of the assigned motions. Finally, a web-based interface was developed to help remotely measure movement in physical therapy for UHC.
Shu-Yin Chiang
2016-12-01
Full Text Available Ubiquitous health care (UHC is beneficial for patients to ensure they complete therapeutic exercises by self-management at home. We designed a fuzzy computing model that enables recognizing assigned movements in UHC with privacy. The movements are measured by the self-developed body motion sensor, which combines both accelerometer and gyroscope chips to make an inertial sensing node compliant with a wireless sensor network (WSN. The fuzzy logic process was studied to calculate the sensor signals that would entail necessary features of static postures and dynamic motions. Combinations of the features were studied and the proper feature sets were chosen with compatible fuzzy rules. Then, a fuzzy inference system (FIS can be generated to recognize the assigned movements based on the rules. We thus implemented both fuzzy and adaptive neuro-fuzzy inference systems in the model to distinguish static and dynamic movements. The proposed model can effectively reach the recognition scope of the assigned activity. Furthermore, two exercises of upper-limb flexion in physical therapy were applied for the model in which the recognition rate can stand for the passing rate of the assigned motions. Finally, a web-based interface was developed to help remotely measure movement in physical therapy for UHC.
The distribution function of a probability measure on a Polish ultrametric space
Galvez-Rodriguez, J.F.; Sanchez-Granero, M.A.
2017-07-01
In applied sciences, the scientific community uses simultaneously different kinds of information coming from several sources in order to infer a conclusion or working decision. In the literature there are many techniques for merging the information and providing, hence, a meaningful fused data. In mostpractical cases such fusion methods are based on aggregation operators on somenumerical values, i.e. the aim of the fusion process is to obtain arepresentative number from a finite sequence of numerical data. In the aforementioned cases, the input data presents some kind of imprecision and for thisreason it is represented as fuzzy sets. Moreover, in such problems the comparisons between the numerical values that represent the information described by the fuzzy sets become necessary. The aforementioned comparisons are made by means of a distance defined on fuzzy sets. Thus, the numerical operators aggregating distances between fuzzy sets as incoming data play a central role in applied problems. Recently, J.J. Nieto and A. Torres gave some applications of the aggregation of distances on fuzzy sets to the study of real medical data in /cite{Nieto}. These applications are based on the notion of segment joining two given fuzzy sets and on the notion of set of midpoints between fuzzy sets. A few results obtained by Nieto and Torres have been generalized in turn by Casasnovas and Rossell/'{o} in /cite{Casas,Casas2}. Nowadays, quasi-metrics provide efficient tools in some fields of computer science and in bioinformatics. Motivated by the exposed facts, a study of segments joining two fuzzy sets and of midpoints between fuzzy sets when the measure, used for comparisons, is a quasi-metric has been made in /cite{Casas3, SebVal2013,TiradoValero}. (Author)
Introduction to Fuzzy Set Theory
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.
Relations Among Some Fuzzy Entropy Formulae
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.
Aihong Ren
2016-01-01
Full Text Available This paper is concerned with a class of fully fuzzy bilevel linear programming problems where all the coefficients and decision variables of both objective functions and the constraints are fuzzy numbers. A new approach based on deviation degree measures and a ranking function method is proposed to solve these problems. We first introduce concepts of the feasible region and the fuzzy optimal solution of a fully fuzzy bilevel linear programming problem. In order to obtain a fuzzy optimal solution of the problem, we apply deviation degree measures to deal with the fuzzy constraints and use a ranking function method of fuzzy numbers to rank the upper and lower level fuzzy objective functions. Then the fully fuzzy bilevel linear programming problem can be transformed into a deterministic bilevel programming problem. Considering the overall balance between improving objective function values and decreasing allowed deviation degrees, the computational procedure for finding a fuzzy optimal solution is proposed. Finally, a numerical example is provided to illustrate the proposed approach. The results indicate that the proposed approach gives a better optimal solution in comparison with the existing method.
Evaluating probability measures related to subsurface flow and transport
Cawlfield, J.D.
1991-01-01
Probabilistic modeling approaches are being used increasingly in order to carry out quantified risk analysis and to evaluate the uncertainty existing in subsurface flow and transport analyses. The work presented in this paper addresses three issues: comparison of common probabilistic modeling techniques, recent results regarding the sensitivity of probability measures to likely changes in the uncertain variables for transport in porous media, and a discussion of some questions regarding fundamental modeling philosophy within a probabilistic framework. Recent results indicate that uncertainty regarding average flow velocity controls the probabilistic outcome, while uncertainty in the dispersivity and diffusion coefficient does not seem very important. Uncertainty of reaction terms is important only at early times in the transport process. Questions are posed regarding (1) the inclusion of macrodispersion in a probabilistic analysis, (2) statistics of flow velocity and (3) the notion of an ultimate probability measure for subsurface flow analyses
Komal
2018-05-01
Nowadays power consumption is increasing day-by-day. To fulfill failure free power requirement, planning and implementation of an effective and reliable power management system is essential. Phasor measurement unit(PMU) is one of the key device in wide area measurement and control systems. The reliable performance of PMU assures failure free power supply for any power system. So, the purpose of the present study is to analyse the reliability of a PMU used for controllability and observability of power systems utilizing available uncertain data. In this paper, a generalized fuzzy lambda-tau (GFLT) technique has been proposed for this purpose. In GFLT, system components' uncertain failure and repair rates are fuzzified using fuzzy numbers having different shapes such as triangular, normal, cauchy, sharp gamma and trapezoidal. To select a suitable fuzzy number for quantifying data uncertainty, system experts' opinion have been considered. The GFLT technique applies fault tree, lambda-tau method, fuzzified data using different membership functions, alpha-cut based fuzzy arithmetic operations to compute some important reliability indices. Furthermore, in this study ranking of critical components of the system using RAM-Index and sensitivity analysis have also been performed. The developed technique may be helpful to improve system performance significantly and can be applied to analyse fuzzy reliability of other engineering systems. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
The Shapley value for a fuzzy poverty measurement
Lamia ASNAOUI
2015-05-01
Full Text Available This article studies the relationship between poverty, inequality and growth. In classical political economic model, we introduce a residual term to maintain the identity of the model. It does not permit us to find the exact contribution of each factor. To derive the results of the decomposition, the Shapley value augmented by the fuzzy approach is used. In order to take its full advantage, it is of interest to calculate the marginal contribution of each factor in the variation of poverty. An application based on individual wellbeing data from Tunisian households is presented to illustrate use of the proposed concepts.
Measurement of probability distributions for internal stresses in dislocated crystals
Wilkinson, Angus J.; Tarleton, Edmund; Vilalta-Clemente, Arantxa; Collins, David M. [Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PH (United Kingdom); Jiang, Jun; Britton, T. Benjamin [Department of Materials, Imperial College London, Royal School of Mines, Exhibition Road, London SW7 2AZ (United Kingdom)
2014-11-03
Here, we analyse residual stress distributions obtained from various crystal systems using high resolution electron backscatter diffraction (EBSD) measurements. Histograms showing stress probability distributions exhibit tails extending to very high stress levels. We demonstrate that these extreme stress values are consistent with the functional form that should be expected for dislocated crystals. Analysis initially developed by Groma and co-workers for X-ray line profile analysis and based on the so-called “restricted second moment of the probability distribution” can be used to estimate the total dislocation density. The generality of the results are illustrated by application to three quite different systems, namely, face centred cubic Cu deformed in uniaxial tension, a body centred cubic steel deformed to larger strain by cold rolling, and hexagonal InAlN layers grown on misfitting sapphire and silicon carbide substrates.
Analysis of selected structures for model-based measuring methods using fuzzy logic
Hampel, R.; Kaestner, W.; Fenske, A.; Vandreier, B.; Schefter, S. [Hochschule fuer Technik, Wirtschaft und Sozialwesen Zittau/Goerlitz (FH), Zittau (DE). Inst. fuer Prozesstechnik, Prozessautomatisierung und Messtechnik e.V. (IPM)
2000-07-01
Monitoring and diagnosis of safety-related technical processes in nuclear enginering can be improved with the help of intelligent methods of signal processing such as analytical redundancies. This chapter gives an overview about combined methods in form of hybrid models using model based measuring methods (observer) and knowledge-based methods (fuzzy logic). Three variants of hybrid observers (fuzzy-supported observer, hybrid observer with variable gain and hybrid non-linear operating point observer) are explained. As a result of the combination of analytical and fuzzy-based algorithms a new quality of monitoring and diagnosis is achieved. The results will be demonstrated in summary for the example water level estimation within pressure vessels (pressurizer, steam generator, and Boiling Water Reactor) with water-steam mixture during the accidental depressurization. (orig.)
Analysis of selected structures for model-based measuring methods using fuzzy logic
Hampel, R.; Kaestner, W.; Fenske, A.; Vandreier, B.; Schefter, S.
2000-01-01
Monitoring and diagnosis of safety-related technical processes in nuclear engineering can be improved with the help of intelligent methods of signal processing such as analytical redundancies. This chapter gives an overview about combined methods in form of hybrid models using model based measuring methods (observer) and knowledge-based methods (fuzzy logic). Three variants of hybrid observers (fuzzy-supported observer, hybrid observer with variable gain and hybrid non-linear operating point observer) are explained. As a result of the combination of analytical and fuzzy-based algorithms a new quality of monitoring and diagnosis is achieved. The results will be demonstrated in summary for the example water level estimation within pressure vessels (pressurizer, steam generator, and Boiling Water Reactor) with water-steam mixture during the accidental depressurization. (orig.)
Ikonomopoulos, A.; Tsoukalas, L.H.
1993-01-01
A novel approach is described for measuring variables with operational significance in a complex system such as a nuclear reactor. The methodology is based on the integration of artificial neural networks with fuzzy reasoning. Neural networks are used to map dynamic time series to a set of user-defined linguistic labels called fuzzy values. The process takes place in a manner analogous to that of measurement. Hence, the entire procedure is referred to as virtual measurement and its software implementation as a virtual measuring device. An optimization algorithm based on information criteria and fuzzy algebra augments the process and assists in the identification of different states of the monitored parameter. The proposed technique is applied for monitoring parameters such as performance, valve position, transient type, and reactivity. The results obtained from the application of the neural network-fuzzy reasoning integration in a high power research reactor clearly demonstrate the excellent tolerance of the virtual measuring device to faulty signals as well as its ability to accommodate noisy inputs
Ďuračiová, Renata; Rášová, Alexandra; Lieskovský, Tibor
2017-12-01
When combining spatial data from various sources, it is often important to determine similarity or identity of spatial objects. Besides the differences in geometry, representations of spatial objects are inevitably more or less uncertain. Fuzzy set theory can be used to address both modelling of the spatial objects uncertainty and determining the identity, similarity, and inclusion of two sets as fuzzy identity, fuzzy similarity, and fuzzy inclusion. In this paper, we propose to use fuzzy measures to determine the similarity or identity of two uncertain spatial object representations in geographic information systems. Labelling the spatial objects by the degree of their similarity or inclusion measure makes the process of their identification more efficient. It reduces the need for a manual control. This leads to a more simple process of spatial datasets update from external data sources. We use this approach to get an accurate and correct representation of historical streams, which is derived from contemporary digital elevation model, i.e. we identify the segments that are similar to the streams depicted on historical maps.
Ďuračiová Renata
2017-12-01
Full Text Available When combining spatial data from various sources, it is often important to determine similarity or identity of spatial objects. Besides the differences in geometry, representations of spatial objects are inevitably more or less uncertain. Fuzzy set theory can be used to address both modelling of the spatial objects uncertainty and determining the identity, similarity, and inclusion of two sets as fuzzy identity, fuzzy similarity, and fuzzy inclusion. In this paper, we propose to use fuzzy measures to determine the similarity or identity of two uncertain spatial object representations in geographic information systems. Labelling the spatial objects by the degree of their similarity or inclusion measure makes the process of their identification more efficient. It reduces the need for a manual control. This leads to a more simple process of spatial datasets update from external data sources. We use this approach to get an accurate and correct representation of historical streams, which is derived from contemporary digital elevation model, i.e. we identify the segments that are similar to the streams depicted on historical maps.
A short course on measure and probability theories
Pebay, Philippe Pierre
2004-02-01
This brief Introduction to Measure Theory, and its applications to Probabilities, corresponds to the lecture notes of a seminar series given at Sandia National Laboratories in Livermore, during the spring of 2003. The goal of these seminars was to provide a minimal background to Computational Combustion scientists interested in using more advanced stochastic concepts and methods, e.g., in the context of uncertainty quantification. Indeed, most mechanical engineering curricula do not provide students with formal training in the field of probability, and even in less in measure theory. However, stochastic methods have been used more and more extensively in the past decade, and have provided more successful computational tools. Scientists at the Combustion Research Facility of Sandia National Laboratories have been using computational stochastic methods for years. Addressing more and more complex applications, and facing difficult problems that arose in applications showed the need for a better understanding of theoretical foundations. This is why the seminar series was launched, and these notes summarize most of the concepts which have been discussed. The goal of the seminars was to bring a group of mechanical engineers and computational combustion scientists to a full understanding of N. WIENER'S polynomial chaos theory. Therefore, these lectures notes are built along those lines, and are not intended to be exhaustive. In particular, the author welcomes any comments or criticisms.
Slope stability probability classification, Waikato Coal Measures, New Zealand
Lindsay, P.; Gillard, G.R.; Moore, T.A. [CRL Energy, PO Box 29-415, Christchurch (New Zealand); Campbell, R.N.; Fergusson, D.A. [Solid Energy North, Private Bag 502, Huntly (New Zealand)
2001-01-01
Ferm classified lithological units have been identified and described in the Waikato Coal Measures in open pits in the Waikato coal region. These lithological units have been classified geotechnically by mechanical tests and discontinuity measurements. Using these measurements slope stability probability classifications (SSPC) have been quantified based on an adaptation of Hack's [Slope Stability Probability Classification, ITC Delft Publication, Enschede, Netherlands, vol. 43, 1998, 273 pp.] SSPC system, which places less influence on rock quality designation and unconfined compressive strength than previous slope/rock mass rating systems. The Hack weathering susceptibility rating has been modified by using chemical index of alteration values determined from XRF major element analyses. Slaking is an important parameter in slope stability in the Waikato Coal Measures lithologies and hence, a non-subjective method of assessing slaking in relation to the chemical index of alteration has been introduced. Another major component of this adapted SSPC system is the inclusion of rock moisture content effects on slope stability. The main modifications of Hack's SSPC system are the introduction of rock intact strength derived from the modified Mohr-Coulomb failure criterion, which has been adapted for varying moisture content, weathering state and confining pressure. It is suggested that the subjectivity in assessing intact rock strength within broad bands in the initial SSPC system is a major weakness of the initial system. Initial results indicate a close relationship between rock mass strength values, calculated from rock mass friction angles and rock mass cohesion values derived from two established rock mass classification methods (modified Hoek-Brown failure criteria and MRMR) and the adapted SSPC system. The advantage of the modified SSPC system is that slope stability probabilities based on discontinuity-independent and discontinuity-dependent data and a
Comment on "Measurements without probabilities in the final state proposal"
Cohen, Eliahu; Nowakowski, Marcin
2018-04-01
The final state proposal [G. T. Horowitz and J. M. Maldacena, J. High Energy Phys. 04 (2004) 008, 10.1088/1126-6708/2004/04/008] is an attempt to relax the apparent tension between string theory and semiclassical arguments regarding the unitarity of black hole evaporation. Authors Bousso and Stanford [Phys. Rev. D 89, 044038 (2014), 10.1103/PhysRevD.89.044038] analyze thought experiments where an infalling observer first verifies the entanglement between early and late Hawking modes and then verifies the interior purification of the same Hawking particle. They claim that "probabilities for outcomes of these measurements are not defined" and therefore suggest that "the final state proposal does not offer a consistent alternative to the firewall hypothesis." We show, in contrast, that one may define all the relevant probabilities based on the so-called ABL rule [Y. Aharonov, P. G. Bergmann, and J. L. Lebowitz, Phys. Rev. 134, B1410 (1964), 10.1103/PhysRev.134.B1410], which is better suited for this task than the decoherence functional. We thus assert that the analysis of Bousso and Stanford cannot yet rule out the final state proposal.
Measuring Robustness of Timetables at Stations using a Probability Distribution
Jensen, Lars Wittrup; Landex, Alex
Stations are often the limiting capacity factor in a railway network. This induces interdependencies, especially at at-grade junctions, causing network effects. This paper presents three traditional methods that can be used to measure the complexity of a station, indicating the robustness...... of the station’s infrastructure layout and plan of operation. However, these three methods do not take the timetable at the station into consideration. Therefore, two methods are introduced in this paper, making it possible to estimate the robustness of different timetables at a station or different...... infrastructure layouts given a timetable. These two methods provide different precision at the expense of a more complex calculation process. The advanced and more precise method is based on a probability distribution that can describe the expected delay between two trains as a function of the buffer time...
Using fuzzy gap analysis to measure service quality of medical tourism in Taiwan.
Ho, Li-Hsing; Feng, Shu-Yun; Yen, Tieh-Min
2015-01-01
The purpose of this paper is intended to create a model to measure quality of service, using fuzzy linguistics to analyze the quality of service of medical tourism in Taiwan so as to find the direction for improvement of service quality in medical tourism. The study developed fuzzy questionnaires based on the characteristics of medical tourism quality of service in Taiwan. Questionnaires were delivered and recovered from February to April 2014, using random sampling according to the proportion of medical tourism companies in each region, and 150 effective samples were obtained. The critical quality of service level is found through the fuzzy gap analysis using questionnaires examining expectations and perceptions of customers, as the direction for continuous improvement. From the study, the primary five critical service items that improve the quality of service for medical tourism in Taiwan include, in order: the capability of the service provider to provide committed medical tourism services reliably and accurately, facility service providers in conjunction with the services provided, the cordial and polite attitude of the service provider eliciting a sense of trust from the customer, professional ability of medical (nursing) personnel in hospital and reliability of service provider. The contribution of this study is to create a fuzzy gap analysis to assess the performance of medical tourism service quality, identify key quality characteristics and provide a direction for improvement and development for medical tourism service quality in Taiwan.
Slope stability probability classification, Waikato Coal Measures, New Zealand
Lindsay, P.; Campbell, R.; Fergusson, D.A.; Ferm, J.C.; Gillard, G.R.; Moore, T.A. [CRL Energy Ltd., Christchurch (New Zealand)
1999-07-01
Ferm classified lithological units have been identified and described in the Waikato Coal Measures in open pits in the Waikato coal region. These lithological units have been classified geotechnically with mechanical tests and discontinuity measurements. Using these measurements, slope stability probability classification (SSPC) have been quantified based on an adaption of Hack's SSPC system which places less influence on rock quality designation and unconfined compressive strength than previous rock mass rating systems. An attempt has been made to modify the Hack weathering susceptibility rating by using chemical index of alteration values from XRF major element analysis. Another major component of this adapted SSPC system is the inclusion of rock moisture content effects on slope stability. The paper explains the systematic initial approach of using the adapted SSPC system to classify slope stability in the Waikato open pit coal mines. The XRF major element results obtained for lithologies in the Waikato coal region may be a useful mine management tool to quantify stratigraphic thickness and palaeoweathering from wash drill cuttings. 14 refs., 7 figs., 3 tabs.
Pairwise Comparison and Distance Measure of Hesitant Fuzzy Linguistic Term Sets
Han-Chen Huang
2014-01-01
Full Text Available A hesitant fuzzy linguistic term set (HFLTS, allowing experts using several possible linguistic terms to assess a qualitative linguistic variable, is very useful to express people’s hesitancy in practical decision-making problems. Up to now, a little research has been done on the comparison and distance measure of HFLTSs. In this paper, we present a comparison method for HFLTSs based on pairwise comparisons of each linguistic term in the two HFLTSs. Then, a distance measure method based on the pairwise comparison matrix of HFLTSs is proposed, and we prove that this distance is equal to the distance of the average values of HFLTSs, which makes the distance measure much more simple. Finally, the pairwise comparison and distance measure methods are utilized to develop two multicriteria decision-making approaches under hesitant fuzzy linguistic environments. The results analysis shows that our methods in this paper are more reasonable.
Modeling and control of an unstable system using probabilistic fuzzy inference system
Sozhamadevi N.
2015-09-01
Full Text Available A new type Fuzzy Inference System is proposed, a Probabilistic Fuzzy Inference system which model and minimizes the effects of statistical uncertainties. The blend of two different concepts, degree of truth and probability of truth in a unique framework leads to this new concept. This combination is carried out both in Fuzzy sets and Fuzzy rules, which gives rise to Probabilistic Fuzzy Sets and Probabilistic Fuzzy Rules. Introducing these probabilistic elements, a distinctive probabilistic fuzzy inference system is developed and this involves fuzzification, inference and output processing. This integrated approach accounts for all of the uncertainty like rule uncertainties and measurement uncertainties present in the systems and has led to the design which performs optimally after training. In this paper a Probabilistic Fuzzy Inference System is applied for modeling and control of a highly nonlinear, unstable system and also proved its effectiveness.
Akram, Rasoul
2013-11-01
Full Text Available The implementation of lean manufacturing concepts has had a significant impact on various industries. Many companies around the world have attempted to implement lean manufacturing, but the lack of an obvious understanding of lean measurement and its performance has caused its implementation to fail. This paper presents an innovative approach by using fuzzy TOPSIS to measure the production leanness of manufacturing systems, as a paradigm. This approach is applied to the Parizan Sanat company.
Rahmanita, E.; Widyaningrum, V. T.; Kustiyahningsih, Y.; Purnama, J.
2018-04-01
SMEs have a very important role in the development of the economy in Indonesia. SMEs assist the government in terms of creating new jobs and can support household income. The number of SMEs in Madura and the number of measurement indicators in the SME mapping so that it requires a method.This research uses Fuzzy Analytic Network Process (FANP) method for performance measurement SME. The FANP method can handle data that contains uncertainty. There is consistency index in determining decisions. Performance measurement in this study is based on a perspective of the Balanced Scorecard. This research approach integrated internal business perspective, learning, and growth perspective and fuzzy Analytic Network Process (FANP). The results of this research areframework a priority weighting of assessment indicators SME.
Hossien Pourghassem
2011-04-01
Full Text Available Relevance feedback approaches is used to improve the performance of content-based image retrieval systems. In this paper, a novel relevance feedback approach based on similarity measure modification in an X-ray image retrieval system based on fuzzy representation using fuzzy attributed relational graph (FARG is presented. In this approach, optimum weight of each feature in feature vector is calculated using similarity rate between query image and relevant and irrelevant images in user feedback. The calculated weight is used to tune fuzzy graph matching algorithm as a modifier parameter in similarity measure. The standard deviation of the retrieved image features is applied to calculate the optimum weight. The proposed image retrieval system uses a FARG for representation of images, a fuzzy matching graph algorithm as similarity measure and a semantic classifier based on merging scheme for determination of the search space in image database. To evaluate relevance feedback approach in the proposed system, a standard X-ray image database consisting of 10000 images in 57 classes is used. The improvement of the evaluation parameters shows proficiency and efficiency of the proposed system.
Probabilistic fuzzy systems as additive fuzzy systems
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
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...
Özlem TÜRKŞEN
2018-03-01
Full Text Available Some of the experimental designs can be composed of replicated response measures in which the replications cannot be identified exactly and may have uncertainty different than randomness. Then, the classical regression analysis may not be proper to model the designed data because of the violation of probabilistic modeling assumptions. In this case, fuzzy regression analysis can be used as a modeling tool. In this study, the replicated response values are newly formed to fuzzy numbers by using descriptive statistics of replications and golden ratio. The main aim of the study is obtaining the most suitable fuzzy model for replicated response measures through fuzzification of the replicated values by taking into account the data structure of the replications in statistical framework. Here, the response and unknown model coefficients are considered as triangular type-1 fuzzy numbers (TT1FNs whereas the inputs are crisp. Predicted fuzzy models are obtained according to the proposed fuzzification rules by using Fuzzy Least Squares (FLS approach. The performances of the predicted fuzzy models are compared by using Root Mean Squared Error (RMSE criteria. A data set from the literature, called wheel cover component data set, is used to illustrate the performance of the proposed approach and the obtained results are discussed. The calculation results show that the combined formulation of the descriptive statistics and the golden ratio is the most preferable fuzzification rule according to the well-known decision making method, called TOPSIS, for the data set.
Measurement of low energy neutrino absorption probability in thallium 205
Freedman, M.S.
1986-01-01
A major aspect of the P-P neutrino flux determination using thallium 205 is the very difficult problem of experimentally demonstrating the neutrino reaction cross section with about 10% accuracy. One will soon be able to completely strip the electrons from atomic thallium 205 and to maintain the bare nucleus in this state in the heavy storage ring to be built at GSI Darmstadt. This nucleus can decay by emitting a beta-minus particle into the bound K-level of the daughter lead 205 ion as the only energetically open decay channel, (plus, of course, an antineutrino). This single channel beta decay explores the same nuclear wave functions of initial and final states as does the neutrino capture in atomic thallium 205, and thus its probability or rate is governed by the same nuclear matrix elements that affect both weak interactions. Measuring the rate of accumulation of lead 205 ions in the circulating beam of thallium 205 ions gives directly the cross section of the neutrino capture reaction. The calculations of the expected rates under realistic experimental conditions will be shown to be very favorable for the measurement. A special calibration experiment to verify this method and check the theoretical calculations will be suggested. Finally, the neutrino cross section calculation based on the observed rate of the single channel beta-minus decay reaction will be shown. Demonstrating bound state beta decay may be the first verification of the theory of this very important process that influences beta decay rates of several isotopes in stellar interiors, e.g., Re-187, that play important roles in geologic and cosmologic dating and nucleosynthesis. 21 refs., 2 figs
Fuzzy Logic System for Intermixed Biogas and Photovoltaics Measurement and Control
Liston Matindife
2018-01-01
Full Text Available This study develops a new integrated measurement and control system for intermixed biogas and photovoltaic systems to achieve safe and optimal energy usage. Literature and field studies show that existing control methods on small- to medium-scale systems fall short of comprehensive system optimization and fault diagnosis, hence the need to revisit these control methods. The control strategy developed in this study is intelligent as it is wholly based on fuzzy logic algorithms. Fuzzy logic controllers due to their superior nonlinear problem solving capabilities to classical controllers considerably simplify controller design. The mathematical models that define classical controllers are difficult or impossible to realize in biogas and photovoltaic generation process. A microcontroller centered fuzzy logic measurement and control embedded system is designed and developed on the existing hybrid biogas and photovoltaic installations. The designed system is able to accurately predict digester stability, quantify biogas output, and carry out biogas fault detection and control. Optimized battery charging and photovoltaic fault detection and control are also successfully implemented. The system is able to optimize the operation and performance of biogas and photovoltaic energy generation.
Chong Wu
2014-01-01
Full Text Available As an important content in fuzzy mathematics, similarity measure is used to measure the similarity degree between two fuzzy sets. Considering the existing similarity measures, most of them do not consider the hesitancy degree and some methods considering the hesitancy degree are based on the intuitionistic fuzzy sets, intuitionistic fuzzy values. It may cause some counterintuitive results in some cases. In order to make up for the drawback, we present a new approach to construct the similarity measure between two interval-valued intuitionistic fuzzy sets using the entropy measure and considering the hesitancy degree. In particular, the proposed measure was demonstrated to yield a similarity measure. Besides, some examples are given to prove the practicality and effectiveness of the new measure. We also apply the similarity measure to expert system to solve the problems on pattern recognition and the multicriteria group decision making. In these examples, we also compare it with existing methods such as other similarity measures and the ideal point method.
M. Amiri
2012-10-01
Full Text Available Mutual fund is one of the most popular techniques for many people to invest their funds where a professional fund manager invests people's funds based on some special predefined objectives; therefore, performance evaluation of mutual funds is an important problem. This paper proposes a multi-objective portfolio optimization to offer asset allocation. The proposed model clusters mutual funds with two methods based on six characteristics including rate of return, variance, semivariance, turnover rate, Treynor index and Sharpe index. Semivariance is used as a downside risk measure. The proposed model of this paper uses fuzzy variables for return rate and semivariance. A multi-objective fuzzy mean-semivariance portfolio optimization model is implemented and fuzzy programming technique is adopted to solve the resulted problem. The proposed model of this paper has gathered the information of mutual fund traded on Nasdaq from 2007 to 2009 and Pareto optimal solutions are obtained considering different weights for objective functions. The results of asset allocation, rate of return and risk of each cluster are also determined and they are compared with the results of two clustering methods.
Logarithmic Similarity Measure between Interval-Valued Fuzzy Sets and Its Fault Diagnosis Method
Zhikang Lu
2018-02-01
Full Text Available Fault diagnosis is an important task for the normal operation and maintenance of equipment. In many real situations, the diagnosis data cannot provide deterministic values and are usually imprecise or uncertain. Thus, interval-valued fuzzy sets (IVFSs are very suitable for expressing imprecise or uncertain fault information in real problems. However, existing literature scarcely deals with fault diagnosis problems, such as gasoline engines and steam turbines with IVFSs. However, the similarity measure is one of the important tools in fault diagnoses. Therefore, this paper proposes a new similarity measure of IVFSs based on logarithmic function and its fault diagnosis method for the first time. By the logarithmic similarity measure between the fault knowledge and some diagnosis-testing samples with interval-valued fuzzy information and its relation indices, we can determine the fault type and ranking order of faults corresponding to the relation indices. Then, the misfire fault diagnosis of the gasoline engine and the vibrational fault diagnosis of a turbine are presented to demonstrate the simplicity and effectiveness of the proposed diagnosis method. The fault diagnosis results of gasoline engine and steam turbine show that the proposed diagnosis method not only gives the main fault types of the gasoline engine and steam turbine but also provides useful information for multi-fault analyses and predicting future fault trends. Hence, the logarithmic similarity measure and its fault diagnosis method are main contributions in this study and they provide a useful new way for the fault diagnosis with interval-valued fuzzy information.
D. Nijssen
2009-08-01
. With regard to these known unknowns the bias of the simulations was considered by imprecise probabilities. Probabilities, derived from measured flood data were combined with probabilities which were estimated from long simulated series. To consider imprecise probabilities, fuzzy sets were used to distinguish the results between more or less possible design floods. The need for such a differentiated view on the performance of flood protection systems is demonstrated by a case study.
Statistical Methods for Fuzzy Data
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
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.
The first order fuzzy predicate logic (I)
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
Fuzzy logic modeling of EIS measurements on lithium-ion batteries
Singh, Pritpal; Vinjamuri, Ramana; Wang, Xiquan; Reisner, David
2006-01-01
A fuzzy logic-based state of health (SOH) meter is being developed for lithium-ion (Li-ion) batteries for potential use in portable defibrillators. Electrochemical impedance spectroscopy (EIS) measurements have been made from which input parameters for a fuzzy logic model to estimate the state of charge (SOC) and SOH are derived. The batteries are discharged continuously at a 1.4 A load current to simulate the constant current draw during the monitoring and recording of a patient's EKG, and periodically interrupted by 10 A pulses to simulate the battery discharge to charge up the capacitor that is in turn discharged to supply high voltage to the electrodes for the defibrillation of the patient. The test procedures included both voltage recovery and EIS measurements, and were made as the batteries were being discharged and over 30 charge/discharge cycles. Accurate models have been developed to estimate the number of pulses that the battery pack can deliver at various stages of its cycle life (SOC measure) and the number of charge/discharge cycles (SOH measure) that it had undergone
Zhang, Jian-Hua; Peng, Xiao-Di; Liu, Hua; Raisch, Jörg; Wang, Ru-Bin
2013-12-01
The human operator's ability to perform their tasks can fluctuate over time. Because the cognitive demands of the task can also vary it is possible that the capabilities of the operator are not sufficient to satisfy the job demands. This can lead to serious errors when the operator is overwhelmed by the task demands. Psychophysiological measures, such as heart rate and brain activity, can be used to monitor operator cognitive workload. In this paper, the most influential psychophysiological measures are extracted to characterize Operator Functional State (OFS) in automated tasks under a complex form of human-automation interaction. The fuzzy c-mean (FCM) algorithm is used and tested for its OFS classification performance. The results obtained have shown the feasibility and effectiveness of the FCM algorithm as well as the utility of the selected input features for OFS classification. Besides being able to cope with nonlinearity and fuzzy uncertainty in the psychophysiological data it can provide information about the relative importance of the input features as well as the confidence estimate of the classification results. The OFS pattern classification method developed can be incorporated into an adaptive aiding system in order to enhance the overall performance of a large class of safety-critical human-machine cooperative systems.
Wahyudi, R. D.
2017-11-01
The problem was because of some indicators qualitatively assessed had been discussed in engineering field. Whereas, qualitative assessment was presently used in certain occasion including in engineering field, for instance, the assessment of service satisfaction. Probably, understanding of satisfaction definition caused bias if customers had their own definition of satisfactory level of service. Therefore, the use of fuzzy logic in SERVQUAL as service satisfaction measurement tool would probably be useful. This paper aimed to investigate the role of fuzzy in SERVQUAL by comparing result measurement of SERVQUAL and fuzzy SERVQUAL for study case of hotel service evaluation. Based on data processing, initial result showed that there was no significant different between them. Thus, either implementation of fuzzy SERVQUAL in different case or study about the role of fuzzy logic in SERVQUAL would be interesting further discussed topic.
FSILP: fuzzy-stochastic-interval linear programming for supporting municipal solid waste management.
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.
Xie, Hong-Bo; Dokos, Socrates
2013-01-01
A new method, namely fuzzy central tendency measure (fCTM) analysis, that could enable measurement of the variability of a time series, is presented in this study. Tests on simulated data sets show that fCTM is superior to the conventional central tendency measure (CTM) in several respects, including improved relative consistency and robustness to noise. The proposed fCTM method was applied to electromyograph (EMG) signals recorded during sustained isometric contraction for tracking local muscle fatigue. The results showed that the fCTM increased significantly during the development of muscle fatigue, and it was more sensitive to the fatigue phenomenon than mean frequency (MNF), the most commonly-used muscle fatigue indicator.
2010-01-01
Background Murray score is the result of an equation that gives all its variables the same linear contribution and weight and makes use of consented cut-offs. Everyday physicians' vocabulary is full of terms (adjectives) like: little, small, low, high, etc. that they handle in an intuitive and not always linear way to make therapeutic decisions. The purpose of this paper is to develop a fuzzy logic (FL) vision of Murray's score variables to enable the measurement of physicians' knowledge, experience and intuition in diagnosing lung injury and test if they followed Murray's equation predictions. Methods For a prospective survey carried out among a team of professionals (aged 29 to 53) in a University Hospital Intensive Care Unit, twelve physicians filled in two questionnaires. In the first one they had to define the ranks which should be categorized as normal, moderate and severe for three of four Murray variables. In another questionnaire, which represented all probable combinations of those categories, they had to tick the pulmonary condition as: no injury, mild, moderate, and ARDS. This procedure gave rise to a Fuzzy Inference System designed to provide the degree of severity as sensed by the group. Results The survey showed fuzzy frontiers for the categories and fuzzy diagnosis. In all, 45% of the hypothetical patients (n 18,013) were equally diagnosed by the survey and Murray's equation, whereas another 51% was overestimated in one level by the survey. Physicians agreed with 96.5% of ARDS cases according to Murray's test but only 11.6% of its mild cases were equally diagnosed by the survey. Nonlinearity of the survey reasoning (high relevance to gas exchange and chest film) was apparent. Conclusions The contiguous categories of the variables confirm the existence of fuzzy frontiers. An overestimation was found in the surveyed group's interpretation of severity. This overestimation was mainly due to the different weight assigned to PO2/FiO2 and chest film
Yeboah-Boateng, Ezer Osei
2013-01-01
There are various threats that militate against SMEs in developing economies. However, most SMEs fall on the conservative “TV News Effect” of most-publicized cyber-threats or incidences, with disproportionate mitigation measures. This paper endeavors to establish a taxonomy of threat agents to fill...... in the void. Various fuzzy similarity measures based on multi-attribute decision-making techniques have been employed in the evaluation. The taxonomy offers a panoramic view of cyber-threats in assessing mission-critical assets, and serves as a benchmark for initiating appropriate mitigation strategies. SMEs...... in developing economies were strategically interviewed for their expert opinions on various business and security metrics. The study established that natural disasters, which are perennial in most developing economies, are the most critical cyber-threat agent, whilst social engineering is the least critical...
Approximation of Measurement Results of “Emergency” Signal Reception Probability
Gajda Stanisław
2017-08-01
Full Text Available The intended aim of this article is to present approximation results of the exemplary measurements of EMERGENCY signal reception probability. The probability is under-stood as a distance function between the aircraft and a ground-based system under established conditions. The measurements were approximated using the properties of logistic functions. This probability, as a distance function, enables to determine the range of the EMERGENCY signal for a pre-set confidence level.
Creating Clinical Fuzzy Automata with Fuzzy Arden Syntax.
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.
Interpretation of the results of statistical measurements. [search for basic probability model
Olshevskiy, V. V.
1973-01-01
For random processes, the calculated probability characteristic, and the measured statistical estimate are used in a quality functional, which defines the difference between the two functions. Based on the assumption that the statistical measurement procedure is organized so that the parameters for a selected model are optimized, it is shown that the interpretation of experimental research is a search for a basic probability model.
A measure of mutual divergence among a number of probability distributions
J. N. Kapur
1987-01-01
major inequalities due to Shannon, Renyi and Holder. The inequalities are then used to obtain some useful results in information theory. In particular measures are obtained to measure the mutual divergence among two or more probability distributions.
Ardehali, M.M.; Saboori, M.; Teshnelab, M.
2004-01-01
Energy efficiency enhancement is achieved by utilizing control algorithms that reduce overshoots and undershoots as well as unnecessary fluctuations in the amount of energy input to energy consuming systems during transient operation periods. It is hypothesized that application of control methodologies with characteristics that change with time and according to the system dynamics, identified as dynamic energy efficiency measures (DEEM), achieves the desired enhancement. The objective of this study is to simulate and analyze the effects of fuzzy logic based tuning of proportional integral derivative (F-PID) and proportional sum derivative (F-PSD) controllers for a heating and cooling energy system while accounting for the dynamics of the major system components. The procedure to achieve the objective includes utilization of fuzzy logic rules to determine the PID and PSD controllers gain coefficients so that the control laws for regulating the heat exchangers heating or cooling energy inputs are determined in each time step of the operation period. The performances of the F-PID and F-PSD controllers are measured by means of two cost functions that are based on quadratic forms of the energy input and deviation from a set point temperature. It is found that application of the F-PID control algorithm, as a DEEM, results in lower costs for energy input and deviation from a set point temperature by 24% and 17% as compared to a PID and 13% and 8% as compared to a PSD, respectively. It is also shown that the F-PSD performance is better than that of the F-PID controller
Lina Zhao
2015-09-01
Full Text Available Entropy provides a valuable tool for quantifying the regularity of physiological time series and provides important insights for understanding the underlying mechanisms of the cardiovascular system. Before any entropy calculation, certain common parameters need to be initialized: embedding dimension m, tolerance threshold r and time series length N. However, no specific guideline exists on how to determine the appropriate parameter values for distinguishing congestive heart failure (CHF from normal sinus rhythm (NSR subjects in clinical application. In the present study, a thorough analysis on the selection of appropriate values of m, r and N for sample entropy (SampEn and recently proposed fuzzy measure entropy (FuzzyMEn is presented for distinguishing two group subjects. 44 long-term NRS and 29 long-term CHF RR interval recordings from http://www.physionet.org were used as the non-pathological and pathological data respectively. Extreme (>2 s and abnormal heartbeat RR intervals were firstly removed from each RR recording and then the recording was segmented with a non-overlapping segment length N of 300 and 1000, respectively. SampEn and FuzzyMEn were performed for each RR segment under different parameter combinations: m of 1, 2, 3 and 4, and r of 0.10, 0.15, 0.20 and 0.25 respectively. The statistical significance between NSR and CHF groups under each combination of m, r and N was observed. The results demonstrated that the selection of m, r and N plays a critical role in determining the SampEn and FuzzyMEn outputs. Compared with SampEn, FuzzyMEn shows a better regularity when selecting the parameters m and r. In addition, FuzzyMEn shows a better relative consistency for distinguishing the two groups, that is, the results of FuzzyMEn in the NSR group were consistently lower than those in the CHF group while SampEn were not. The selections of m of 2 and 3 and r of 0.10 and 0.15 for SampEn and the selections of m of 1 and 2 whenever r (herein
Tatari, Farzaneh; Akbarzadeh-T, Mohammad-R; Sabahi, Ahmad
2012-12-01
In this paper, we present an agent-based system for distributed risk assessment of breast cancer development employing fuzzy and probabilistic computing. The proposed fuzzy multi agent system consists of multiple fuzzy agents that benefit from fuzzy set theory to demonstrate their soft information (linguistic information). Fuzzy risk assessment is quantified by two linguistic variables of high and low. Through fuzzy computations, the multi agent system computes the fuzzy probabilities of breast cancer development based on various risk factors. By such ranking of high risk and low risk fuzzy probabilities, the multi agent system (MAS) decides whether the risk of breast cancer development is high or low. This information is then fed into an insurance premium adjuster in order to provide preventive decision making as well as to make appropriate adjustment of insurance premium and risk. This final step of insurance analysis also provides a numeric measure to demonstrate the utility of the approach. Furthermore, actual data are gathered from two hospitals in Mashhad during 1 year. The results are then compared with a fuzzy distributed approach. Copyright © 2012 Elsevier Inc. All rights reserved.
Fuzzy Entropy： Axiomatic Definition and Neural Networks Model
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.
Quantum probabilities of composite events in quantum measurements with multimode states
Yukalov, V I; Sornette, D
2013-01-01
The problem of defining quantum probabilities of composite events is considered. This problem is of great importance for the theory of quantum measurements and for quantum decision theory, which is a part of measurement theory. We show that the Lüders probability of consecutive measurements is a transition probability between two quantum states and that this probability cannot be treated as a quantum extension of the classical conditional probability. The Wigner distribution is shown to be a weighted transition probability that cannot be accepted as a quantum extension of the classical joint probability. We suggest the definition of quantum joint probabilities by introducing composite events in multichannel measurements. The notion of measurements under uncertainty is defined. We demonstrate that the necessary condition for mode interference is the entanglement of the composite prospect together with the entanglement of the composite statistical state. As an illustration, we consider an example of a quantum game. Special attention is paid to the application of the approach to systems with multimode states, such as atoms, molecules, quantum dots, or trapped Bose-condensed atoms with several coherent modes. (paper)
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.
A probability measure for random surfaces of arbitrary genus and bosonic strings in 4 dimensions
Albeverio, S.; Hoeegh-Krohn, R.; Paycha, S.; Scarlatti, S.
1989-01-01
We define a probability measure describing random surfaces in R D , 3≤D≤13, parametrized by compact Riemann surfaces of arbitrary genus. The measure involves the path space measure for scalar fields with exponential interaction in 2 space time dimensions. We show that it gives a mathematical realization of Polyakov's heuristic measure for bosonic strings. (orig.)
The Construction of a Vague Fuzzy Measure Through L1 Parameter Optimization
2012-08-26
Programming v. 1.21, http://cvxr.com/cvx, (2011) 11 [3] E.J. Candes, J. Romberg and T. Tao. Robust Uncertainty Principles: Exact Signal Reconstruction From...Annales de I’institut Fourer, 5 (1954), pp. 131-295 [9] D. Diakoulaki, C. Antunes and A. Martins. MCDA in Energy Planning, Int. Series in Operations...formance and Tests , Fuzzy Sets and Systems, Vol. 65, Issues 2-3 (1994), pp.255-271 [15] M. Grabisch. Fuzzy Integral in Multicriteria Decision Making, Fuzzy
Shawkat Alkhazaleh
2011-01-01
Full Text Available We introduce the concept of possibility fuzzy soft set and its operation and study some of its properties. We give applications of this theory in solving a decision-making problem. We also introduce a similarity measure of two possibility fuzzy soft sets and discuss their application in a medical diagnosis problem.
Quantum Zeno and anti-Zeno effects measured by transition probabilities
Zhang, Wenxian, E-mail: wxzhang@whu.edu.cn [School of Physics and Technology, Wuhan University, Wuhan, Hubei 430072 (China); Department of Optical Science and Engineering, Fudan University, Shanghai 200433 (China); CEMS, RIKEN, Saitama 351-0198 (Japan); Kavli Institute for Theoretical Physics China, CAS, Beijing 100190 (China); Kofman, A.G. [CEMS, RIKEN, Saitama 351-0198 (Japan); Department of Physics, The University of Michigan, Ann Arbor, MI 48109-1040 (United States); Zhuang, Jun [Department of Optical Science and Engineering, Fudan University, Shanghai 200433 (China); You, J.Q. [Beijing Computational Science Research Center, Beijing 10084 (China); Department of Physics, Fudan University, Shanghai 200433 (China); CEMS, RIKEN, Saitama 351-0198 (Japan); Nori, Franco [CEMS, RIKEN, Saitama 351-0198 (Japan); Department of Physics, The University of Michigan, Ann Arbor, MI 48109-1040 (United States)
2013-10-30
Using numerical calculations, we compare the transition probabilities of many spins in random magnetic fields, subject to either frequent projective measurements, frequent phase modulations, or a mix of modulations and measurements. For various distribution functions, we find the transition probability under frequent modulations is suppressed most if the pulse delay is short and the evolution time is larger than a critical value. Furthermore, decay freezing occurs only under frequent modulations as the pulse delay approaches zero. In the large pulse-delay region, however, the transition probabilities under frequent modulations are highest among the three control methods.
Radiation protection and fuzzy set theory
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
A neuro-fuzzy inference system for sensor monitoring
Na, Man Gyun
2001-01-01
A neuro-fuzzy inference system combined with the wavelet denoising, PCA (principal component analysis) and SPRT (sequential probability ratio test) methods has been developed to monitor the relevant sensor using the information of other sensors. The paramters of the neuro-fuzzy inference system which estimates the relevant sensor signal are optimized by a genetic algorithm and a least-squares algorithm. The wavelet denoising technique was applied to remove noise components in input signals into the neuro-fuzzy system. By reducing the dimension of an input space into the neuro-fuzzy system without losing a significant amount of information, the PCA was used to reduce the time necessary to train the neuro-fuzzy system, simplify the structure of the neuro-fuzzy inference system and also, make easy the selection of the input signals into the neuro-fuzzy system. By using the residual signals between the estimated signals and the measured signals, the SPRT is applied to detect whether the sensors are degraded or not. The proposed sensor-monitoring algorithm was verified through applications to the pressurizer water level, the pressurizer pressure, and the hot-leg temperature sensors in pressurized water reactors
Birchall, A.; Muirhead, C.R.; James, A.C.
1988-01-01
An analytical expression has been derived for the k-sum distribution, formed by summing k random variables from a lognormal population. Poisson statistics are used with this distribution to derive distribution of intake when breathing an atmosphere with a constant particle number concentration. Bayesian inference is then used to calculate the posterior probability distribution of concentrations from a given measurement. This is combined with the above intake distribution to give the probability distribution of intake resulting from a single measurement of activity made by an ideal sampler. It is shown that the probability distribution of intake is very dependent on the prior distribution used in Bayes' theorem. The usual prior assumption, that all number concentrations are equally probable, leads to an imbalance in the posterior intake distribution. This can be resolved if a new prior proportional to w -2/3 is used, where w is the expected number of particles collected. (author)
Marshman, Emily; Singh, Chandralekha
2017-01-01
A solid grasp of the probability distributions for measuring physical observables is central to connecting the quantum formalism to measurements. However, students often struggle with the probability distributions of measurement outcomes for an observable and have difficulty expressing this concept in different representations. Here we first describe the difficulties that upper-level undergraduate and PhD students have with the probability distributions for measuring physical observables in quantum mechanics. We then discuss how student difficulties found in written surveys and individual interviews were used as a guide in the development of a quantum interactive learning tutorial (QuILT) to help students develop a good grasp of the probability distributions of measurement outcomes for physical observables. The QuILT strives to help students become proficient in expressing the probability distributions for the measurement of physical observables in Dirac notation and in the position representation and be able to convert from Dirac notation to position representation and vice versa. We describe the development and evaluation of the QuILT and findings about the effectiveness of the QuILT from in-class evaluations. (paper)
Bou-Fakhreddine, Bassam; Mougharbel, Imad; Faye, Alain; Abou Chakra, Sara; Pollet, Yann
2018-03-01
Accurate daily river flow forecast is essential in many applications of water resources such as hydropower operation, agricultural planning and flood control. This paper presents a forecasting approach to deal with a newly addressed situation where hydrological data exist for a period longer than that of meteorological data (measurements asymmetry). In fact, one of the potential solutions to resolve measurements asymmetry issue is data re-sampling. It is a matter of either considering only the hydrological data or the balanced part of the hydro-meteorological data set during the forecasting process. However, the main disadvantage is that we may lose potentially relevant information from the left-out data. In this research, the key output is a Two-Phase Constructive Fuzzy inference hybrid model that is implemented over the non re-sampled data. The introduced modeling approach must be capable of exploiting the available data efficiently with higher prediction efficiency relative to Constructive Fuzzy model trained over re-sampled data set. The study was applied to Litani River in the Bekaa Valley - Lebanon by using 4 years of rainfall and 24 years of river flow daily measurements. A Constructive Fuzzy System Model (C-FSM) and a Two-Phase Constructive Fuzzy System Model (TPC-FSM) are trained. Upon validating, the second model has shown a primarily competitive performance and accuracy with the ability to preserve a higher day-to-day variability for 1, 3 and 6 days ahead. In fact, for the longest lead period, the C-FSM and TPC-FSM were able of explaining respectively 84.6% and 86.5% of the actual river flow variation. Overall, the results indicate that TPC-FSM model has provided a better tool to capture extreme flows in the process of streamflow prediction.
Assembly for the measurement of the most probable energy of directed electron radiation
Geske, G.
1987-01-01
This invention relates to a setup for the measurement of the most probable energy of directed electron radiation up to 50 MeV. The known energy-range relationship with regard to the absorption of electron radiation in matter is utilized by an absorber with two groups of interconnected radiation detectors embedded in it. The most probable electron beam energy is derived from the quotient of both groups' signals
Abolfazl Danaei
2013-10-01
Full Text Available This paper presents an empirical investigation to measure the performance of a mining firm in province of Semnan, Iran based on fuzzy fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL technique. The proposed study of this paper uses strength, weakness, opportunity and threat (SWOT technique to analyze the firm and using DEMATEL rank various items based on their relative importance. Based on the results of our survey, cost reduction and increase investment in mining sector are the most important components of this survey. The study also compares the results with similar study, which has recently been accomplished and we believe the proposed model is capable of detecting possible threats and helping us provide possible actions.
Liu, Chuang; Lam, H. K.
2015-01-01
In this paper, we propose a polynomial fuzzy observer controller for nonlinear systems, where the design is achieved through the stability analysis of polynomial-fuzzy-model-based (PFMB) observer-control system. The polynomial fuzzy observer estimates the system states using estimated premise variables. The estimated states are then employed by the polynomial fuzzy controller for the feedback control of nonlinear systems represented by the polynomial fuzzy model. The system stability of the P...
Fuzzy-DEA model for measuring the efficiency of transport quality
Dragan S. Pamučar
2011-10-01
Full Text Available Data envelopment analysis (DEA is becoming increasingly important as a tool for evaluating and improving the performance of manufacturing and service operations. It has been extensively applied in performance evaluation and benchmarking of schools, hospitals, bank branches, production plants, etc. DEA enables mathematical programming for implicit evaluation of the ratio between a number of input and output performance parameters. The result is quantification of the efficiency of business opportunities and providing insight into some flaws from the level of top management. Levels of efficiency determined under the same parametres make this analytical process objective and allow for the application of best practices based on the assessment of the overall efficiency. This paper presents a fuzzy-DEA model for evaluating the effectiveness of urban and suburban public transport- USPT. A fuzzy-DEA model provides insight into the current transport quality provided by USPT and proposes for the improvement of inefficient systems up to the level of best standards possible. Such quantification makes long-term stability of USPT possible. Since most of the acquired data is characterized by a high degree of imprecision, subjectivity and uncertainty, fuzzy logic was used for displaying them. Fuzzy linguistic descriptors are given in the output parameters of DEA models. In this way, fuzzy logic enables the exploitation of tolerance that exists in imprecision, uncertainty and partial accuracy of the acquired research results.
Seyyed Abdolhossein Arami
2017-01-01
Full Text Available Prioritization of watersheds in order to perform administrative measures is necessary and inevitable. Determining areas of top priority for flood control projects is a managerial decision that should be approved by studies of physical, social and economic status of the region of interesrt and by assessing the outcomes of the past operations. Therefore, the aim of this research was to study morphological and physiographic characteristics, and to use geographic information systems (GIS and multi-criteria decision-making methods (MCDM, to identify the critical sub-basins which have the tendency to be destructed, in Galikesh watershed, Golestan province. This watershed is important, yet critical, in terms of land use change, erosion and flooding in the Golestan Province, Iran. In total, nine morphological parameters were used to prioritize sub-watersheds using fuzzy analytic hierarchy process (FAHP. The morphological parameters were by some means linked to watershed drainage system. Based on FAHP approach, sub-basins, as vulnerable zones, have been evaluated and cetegorized in five priority levels (very low, low, medium, high and very high levels. The results showed that 44.44% and 22.22% of sub-basins were categorized respectively under average, and high to very high levels, suggesting that the conservation and management measures are essential in order to maintain stability in the region. Thus, the FAHP technique is a practical and convenient method to show potential zones in order to implement effective management strategies, especially in areas where data availability is low and soil diversity is high. Finally, it can be said that without having to encounter high costs and a waste of time, sub-basins could be categorized by means of morphometric parameters in order to implement conservational measures to simutaneously conserve soil and the environment
Measurements of transition probabilities in the range from vacuum ultraviolet to infrared
Peraza Fernandez, M.C.
1992-01-01
In this memory we describe the design, testing and calibration of different spectrometers to measure transition probabilities from the vacuum ultraviolet to the infrared spectral region. For the infrared measurements we have designed and performed a phase sensitive detection system, using an InGaAs photodiode like detector. With this system we have determined the transition probabilities of infrared lines of KrI and XeI. For these lines we haven't found previous measurements. In the vacuum ultraviolet spectral region we have designed a 3 m normal incidence monochromator where we have installed an optical multichannel analyzer. We have tested its accurate working, obtaining the absorption spectrum of KrI. In the visible region we have obtained the emission spectrum of Al using different spectral: hallow-cathode lamp and Nd: YAG laser produced Al plasma. With these spectra we have determined different atomic parameters like transition probabilities and electron temperatures.(author). 83 refs
N. M. ISHAK
2017-10-01
Full Text Available The purpose of this study is to define the suitable thermoplastic matrix for fibre metal laminate for automotive front hood utilisation. To achieve the accurate and reliable results, the decision making process involved subjective and objective weighting where the combination of Fuzzy VIKOR and entropy method have been applied. Fuzzy VIKOR is used for ranking purpose and entropy method is used to determine the objective weighting. The result shows that polypropylene is the best thermoplastic matrix for fibre metal laminate by satisfying two compromise solutions with validation using least VIKOR index value scored 0.00, compared to low density polyethylene, high density polyethylene and polystyrene. Through a combination of Fuzzy VIKOR and entropy, it is proved that this method gives a higher degree of confidence to the decision maker especially for fibre metal laminate thermoplastic matrix selection due to its systematic and scientific selection method involving MCDM.
The distribution function of a probability measure on a space with a fractal structure
Sanchez-Granero, M.A.; Galvez-Rodriguez, J.F.
2017-07-01
In this work we show how to define a probability measure with the help of a fractal structure. One of the keys of this approach is to use the completion of the fractal structure. Then we use the theory of a cumulative distribution function on a Polish ultrametric space and describe it in this context. Finally, with the help of fractal structures, we prove that a function satisfying the properties of a cumulative distribution function on a Polish ultrametric space is a cumulative distribution function with respect to some probability measure on the space. (Author)
Asfahani, J.; Abdul Ghani, B.; Ahmad, Z.
2015-01-01
Fuzzy analysis technique is proposed in this research for interpreting the combination of nuclear and electrical well logging data, which include natural gamma ray, density and neutron-porosity, while the electrical well logging include long and short normal. The main objective of this work is to describe, characterize and establish the lithology of the large extended basaltic areas in southern Syria. Kodana well logging measurements have been used and interpreted for testing and applying the proposed technique. The established lithological cross section shows the distribution and the identification of four kinds of basalt, which are hard massive basalt, hard basalt, pyroclastic basalt and the alteration basalt products, clay. The fuzzy analysis technique is successfully applied on the Kodana well logging data, and can be therefore utilized as a powerful tool for interpreting huge well logging data with higher number of variables required for lithological estimations. - Highlights: • Apply fuzzy analysis technique on the nuclear and electrical well logging data of Kodana well in Southern Syria. • Determine and differentiate between four kinds of basalt. • Establish the lithological section of the studied well.
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.
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.
Measurement of the spark probability in single gap parallel plate chambers
Arefiev, A.; Bencze, Gy.L.; Choumilov, E.; Civinini, C.; Dalla Santa, F.; D'Alessandro, R.; Ferrando, A.; Fouz, M.C.; Golovkin, V.; Kholodenko, A.; Iglesias, A.; Ivochkin, V.; Josa, M.I.; Malinin, A.; Meschini, M.; Misyura, S.; Pojidaev, V.; Salicio, J.M.
1996-01-01
We present results on the measurements of the spark probability with CO 2 and CF 4 /CO 2 (80/20) mixture, at atmospheric pressure, using 1.5 mm gas gap parallel plate chambers, working at a gas gain ranging from 4.5 x 10 2 to 3.3 x 10 4 . (orig.)
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.
Fuzzy efficiency without convexity
Hougaard, Jens Leth; Balezentis, Tomas
2014-01-01
approach builds directly upon the definition of Farrell's indexes of technical efficiency used in crisp FDH. Therefore we do not require the use of fuzzy programming techniques but only utilize ranking probabilities of intervals as well as a related definition of dominance between pairs of intervals. We...
Measurement of the Mis-identification Probability of τ Leptons from Hadronic Jets and from Electrons
The ATLAS collaboration
2011-01-01
Measurements of the mis-identification probability of QCD jets and electrons as hadronically decaying τ leptons using tag-and-probe methods are described. The analyses are based on 35pb−1 of proton-proton collision data, taken by the ATLAS experiment at a center-of-mass energy of sqrt(s) = 7 TeV. The mis-identification probabilities range between 10% and 0.1% for QCD jets, and about (1 − 2)% for electrons. They depend on the identification algorithm chosen, the pT and the number of prongs of the τ candidate, and on the amount of pile up present in the event.
Measurement of D-T neutron penetration probability spectra for iron ball shell systems
Duan Shaojie
1998-06-01
The D-T neutron penetration probability spectra are measured for iron ball shell systems of the series of samples used in the experiments, and the penetration curves are presented. As the detector is near to samples, the measured results being approximately corrected are compared with those in the literature, and it is shown that the former is compatible with the latter in the range of the experimental error
Hidden measurements, hidden variables and the volume representation of transition probabilities
Oliynyk, Todd A.
2005-01-01
We construct, for any finite dimension $n$, a new hidden measurement model for quantum mechanics based on representing quantum transition probabilities by the volume of regions in projective Hilbert space. For $n=2$ our model is equivalent to the Aerts sphere model and serves as a generalization of it for dimensions $n \\geq 3$. We also show how to construct a hidden variables scheme based on hidden measurements and we discuss how joint distributions arise in our hidden variables scheme and th...
FINDING STANDARD DEVIATION OF A FUZZY NUMBER
Fokrul Alom Mazarbhuiya
2017-01-01
Two probability laws can be root of a possibility law. Considering two probability densities over two disjoint ranges, we can define the fuzzy standard deviation of a fuzzy variable with the help of the standard deviation two random variables in two disjoint spaces.
On the mathematics of fuzziness
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.
Li, Xin; Zhang, Lu; Tang, Ying; Huang, Shanguo
2018-03-01
The light-tree-based optical multicasting (LT-OM) scheme provides a spectrum- and energy-efficient method to accommodate emerging multicast services. Some studies focus on the survivability technologies for LTs against a fixed number of link failures, such as single-link failure. However, a few studies involve failure probability constraints when building LTs. It is worth noting that each link of an LT plays different important roles under failure scenarios. When calculating the failure probability of an LT, the importance of its every link should be considered. We design a link importance incorporated failure probability measuring solution (LIFPMS) for multicast LTs under independent failure model and shared risk link group failure model. Based on the LIFPMS, we put forward the minimum failure probability (MFP) problem for the LT-OM scheme. Heuristic approaches are developed to address the MFP problem in elastic optical networks. Numerical results show that the LIFPMS provides an accurate metric for calculating the failure probability of multicast LTs and enhances the reliability of the LT-OM scheme while accommodating multicast services.
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...
New measurements of spontaneous transition probabilities for beryllium-like ions
Lang, J.; Hardcastle, R.A.; McWhirter, R.W.P.; Spurrett, P.H.
1986-06-01
The authors describe measurements of spectral line intensities for pairs of transitions having common upper levels and thus derive the branching ratios of their spontaneous radiative transition probabilities. These are then combined with the results of measurements of the radiative lifetimes of the upper levels by other authors to obtain values of the individual transition probabilities. The results are for transitions in NIV, OV and NeVII and are given with a claimed accuracy of between 7% and 38%. These are compared with values calculated theoretically. For some of the simpler electric dipole transitions good agreement is found. On the other hand for some of the other transitions which in certain cases are only possible because of configuration interaction disparities between the present measurements and theory are as large as x5. (author)
Wolf Attack Probability: A Theoretical Security Measure in Biometric Authentication Systems
Une, Masashi; Otsuka, Akira; Imai, Hideki
This paper will propose a wolf attack probability (WAP) as a new measure for evaluating security of biometric authentication systems. The wolf attack is an attempt to impersonate a victim by feeding “wolves” into the system to be attacked. The “wolf” means an input value which can be falsely accepted as a match with multiple templates. WAP is defined as a maximum success probability of the wolf attack with one wolf sample. In this paper, we give a rigorous definition of the new security measure which gives strength estimation of an individual biometric authentication system against impersonation attacks. We show that if one reestimates using our WAP measure, a typical fingerprint algorithm turns out to be much weaker than theoretically estimated by Ratha et al. Moreover, we apply the wolf attack to a finger-vein-pattern based algorithm. Surprisingly, we show that there exists an extremely strong wolf which falsely matches all templates for any threshold value.
Estimation of (n,f) Cross-Sections by Measuring Reaction Probability Ratios
Plettner, C; Ai, H; Beausang, C W; Bernstein, L A; Ahle, L; Amro, H; Babilon, M; Burke, J T; Caggiano, J A; Casten, R F; Church, J A; Cooper, J R; Crider, B; Gurdal, G; Heinz, A; McCutchan, E A; Moody, K; Punyon, J A; Qian, J; Ressler, J J; Schiller, A; Williams, E; Younes, W
2005-04-21
Neutron-induced reaction cross-sections on unstable nuclei are inherently difficult to measure due to target activity and the low intensity of neutron beams. In an alternative approach, named the 'surrogate' technique, one measures the decay probability of the same compound nucleus produced using a stable beam on a stable target to estimate the neutron-induced reaction cross-section. As an extension of the surrogate method, in this paper they introduce a new technique of measuring the fission probabilities of two different compound nuclei as a ratio, which has the advantage of removing most of the systematic uncertainties. This method was benchmarked in this report by measuring the probability of deuteron-induced fission events in coincidence with protons, and forming the ratio P({sup 236}U(d,pf))/P({sup 238}U(d,pf)), which serves as a surrogate for the known cross-section ratio of {sup 236}U(n,f)/{sup 238}U(n,f). IN addition, the P({sup 238}U(d,d{prime}f))/P({sup 236}U(d,d{prime}f)) ratio as a surrogate for the {sup 237}U(n,f)/{sup 235}U(n,f) cross-section ratio was measured for the first time in an unprecedented range of excitation energies.
Evolution of probability measures by cellular automata on algebraic topological Markov chains
ALEJANDRO MAASS
2003-01-01
Full Text Available In this paper we review some recent results on the evolution of probability measures under cellular automata acting on a fullshift. In particular we discuss the crucial role of the attractiveness of maximal measures. We enlarge the context of the results of a previous study of topological Markov chains that are Abelian groups; the shift map is an automorphism of this group. This is carried out by studying the dynamics of Markov measures by a particular additive cellular automata. Many of these topics were within the focus of Francisco Varela's mathematical interests.
Fuzzy Clustering Methods and their Application to Fuzzy Modeling
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...
Focusing on a Probability Element: Parameter Selection of Message Importance Measure in Big Data
She, Rui; Liu, Shanyun; Dong, Yunquan; Fan, Pingyi
2017-01-01
Message importance measure (MIM) is applicable to characterize the importance of information in the scenario of big data, similar to entropy in information theory. In fact, MIM with a variable parameter can make an effect on the characterization of distribution. Furthermore, by choosing an appropriate parameter of MIM,it is possible to emphasize the message importance of a certain probability element in a distribution. Therefore, parametric MIM can play a vital role in anomaly detection of bi...
Measurement of K-electron capture probability in the decay of 87Y
Prasad, N.V.S.V.; Murty, G.S.K.; Rao, M.V.S.C.; Sastry, D.L.
1993-01-01
The K-electron capture probability for the 1/2 - to 3/2 - transition in the decay of 87 Y to the 873.0 keV level in the daughter 87 Sr was measured for the first time using an x-γ summing method. The experimental P K value was found to be 0.911 ± 0.047, in agreement with the theoretical value of 0.878. (author)
Measurement of K-electron capture probability in the decay of [sup 87]Y
Prasad, N.V.S.V.; Murty, G.S.K.; Rao, M.V.S.C.; Sastry, D.L. (Andhra Univ., Visakhapatnam (India). Labs. for Nuclear Research); Chintalapudi, S.N. (Inter University Consortium for DAE Facilities, Calcutta (India))
1993-04-01
The K-electron capture probability for the 1/2[sup -] to 3/2[sup -]transition in the decay of [sup 87]Y to the 873.0 keV level in the daughter [sup 87]Sr was measured for the first time using an x-[gamma] summing method. The experimental P[sub K] value was found to be 0.911 [+-] 0.047, in agreement with the theoretical value of 0.878. (author).
Measurement of vacancy transfer probability from K to L shell using ...
73, No. 4. — journal of. October 2009 physics pp. 711–718. Measurement of vacancy transfer probability from K to L shell using K-shell fluorescence yields. ¨O S¨O˘GÜT1,∗, E BÜYÜKKASAP2, A KÜC¸ ÜK¨ONDER1 and T TARAKC¸ IO ˇGLU1. 1Department of Physics, Faculty of Science and Letters, Kahramanmaras Sütçü ˙ ...
Fuzzy statistical decision-making theory and applications
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...
Carvalho, John P; Gawrysiak, Michael J; Hellmuth, Julianne C; McNulty, James K; Magidson, Jessica F; Lejuez, C W; Hopko, Derek R
2011-06-01
Behavioral models of depression implicate decreased response-contingent positive reinforcement (RCPR) as critical toward the development and maintenance of depression (Lewinsohn, 1974). Given the absence of a psychometrically sound self-report measure of RCPR, the Reward Probability Index (RPI) was developed to measure access to environmental reward and to approximate actual RCPR. In Study 1 (n=269), exploratory factor analysis supported a 20-item two-factor model (Reward Probability, Environmental Suppressors) with strong internal consistency (α=.90). In Study 2 (n=281), confirmatory factor analysis supported this two-factor structure and convergent validity was established through strong correlations between the RPI and measures of activity, avoidance, reinforcement, and depression (r=.65 to .81). Discriminant validity was supported via smaller correlations between the RPI and measures of social support and somatic anxiety (r=-.29 to -.40). Two-week test-retest reliability was strong (r=.69). In Study 3 (n=33), controlling for depression symptoms, hierarchical regression supported the incremental validity of the RPI in predicting daily diary reports of environmental reward. The RPI represents a parsimonious, reliable, and valid measure that may facilitate understanding of the etiology of depression and its relationship to overt behaviors. Copyright © 2011. Published by Elsevier Ltd.
Audio Query by Example Using Similarity Measures between Probability Density Functions of Features
Marko Helén
2010-01-01
Full Text Available This paper proposes a query by example system for generic audio. We estimate the similarity of the example signal and the samples in the queried database by calculating the distance between the probability density functions (pdfs of their frame-wise acoustic features. Since the features are continuous valued, we propose to model them using Gaussian mixture models (GMMs or hidden Markov models (HMMs. The models parametrize each sample efficiently and retain sufficient information for similarity measurement. To measure the distance between the models, we apply a novel Euclidean distance, approximations of Kullback-Leibler divergence, and a cross-likelihood ratio test. The performance of the measures was tested in simulations where audio samples are automatically retrieved from a general audio database, based on the estimated similarity to a user-provided example. The simulations show that the distance between probability density functions is an accurate measure for similarity. Measures based on GMMs or HMMs are shown to produce better results than that of the existing methods based on simpler statistics or histograms of the features. A good performance with low computational cost is obtained with the proposed Euclidean distance.
Relational Demonic Fuzzy Refinement
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.
Fuzzy resource optimization for safeguards
Zardecki, A.; Markin, J.T.
1991-01-01
Authorization, enforcement, and verification -- three key functions of safeguards systems -- form the basis of a hierarchical description of the system risk. When formulated in terms of linguistic rather than numeric attributes, the risk can be computed through an algorithm based on the notion of fuzzy sets. Similarly, this formulation allows one to analyze the optimal resource allocation by maximizing the overall detection probability, regarded as a linguistic variable. After summarizing the necessary elements of the fuzzy sets theory, we outline the basic algorithm. This is followed by a sample computation of the fuzzy optimization. 10 refs., 1 tab
Fuzzy mathematics method for theoretical analysis of ground movements due to underground excavation
Li Wenxiu (Changsa Research Institute of Mining and Metallurgy, Changsa (China))
1991-07-01
The analysis of the rock mass movements due to excavation operations is one of the many important problems of rock mass mechanics. It is difficult to calculate the ground movements due to underground excavation accurately because of the complexity of the problem. In this paper, the application is described of the fuzzy probability measures to the analysis of ground movements. Based on the definition of the fuzzy probability measure, the theories for both the two-dimensional and three-dimensional problems are developed and are applied to the analysis of ground movements due to underground excavation. 31 refs., 5 figs.
Gocmen, C.
2007-01-01
When the total solar eclipse came into question, people connected the eclipse with the earthquake dated 17.08.1999. We thought if any physical parameters change during total solar eclipse on the earth, we could measure this changing and we did the project 'To Measure Probable Physical Changes On The Earth During Total Solar Eclipse Using Geophysical Methods' We did gravity, magnetic and self-potential measurements at Konya and Ankara during total solar eclipse (29, March, 2006) and the day before eclipse and the day after eclipse. The measurements went on three days continuously twenty-four hours at Konya and daytime in Ankara. Bogazici University Kandilli Observatory gave us magnetic values in Istanbul and we compare the values with our magnetic values. Turkish State Meteorological Service sent us temperature and air pressure observations during three days, in Konya and Ankara. We interpreted all of them
Koglin, Johnathon
Accurate nuclear reaction data from a few keV to tens of MeV and across the table of nuclides is essential to a number of applications of nuclear physics, including national security, nuclear forensics, nuclear astrophysics, and nuclear energy. Precise determination of (n, f) and neutron capture cross sections for reactions in high- ux environments are particularly important for a proper understanding of nuclear reactor performance and stellar nucleosynthesis. In these extreme environments reactions on short-lived and otherwise difficult-to-produce isotopes play a significant role in system evolution and provide insights into the types of nuclear processes taking place; a detailed understanding of these processes is necessary to properly determine cross sections far from stability. Indirect methods are often attempted to measure cross sections on isotopes that are difficult to separate in a laboratory setting. Using the surrogate approach, the same compound nucleus from the reaction of interest is created through a "surrogate" reaction on a different isotope and the resulting decay is measured. This result is combined with appropriate reaction theory for compound nucleus population, from which the desired cross sections can be inferred. This method has shown promise, but the theoretical framework often lacks necessary experimental data to constrain models. In this work, dual arrays of silicon telescope particle identification detectors and photovoltaic (solar) cell fission fragment detectors have been used to measure the fission probability of the 240Pu(alpha, alpha'f) reaction - a surrogate for the 239Pu(n, f) - and fission of 35.9(2)MeV at eleven scattering angles from 40° to 140° in 10° intervals and at nuclear excitation energies up to 16MeV. Within experimental uncertainty, the maximum fission probability was observed at the neutron separation energy for each alpha scattering angle. Fission probabilities were separated into five 500 keV bins from 5:5MeV to
Measure of librarian pressure using fuzzy inference system: A case study in Longyan University
Huang, Jian-Jing
2014-10-01
As the hierarchy of middle managers in college's librarian. They may own much work pressure from their mind. How to adapt psychological problem, control the emotion and keep a good relationship in their work place, it becomes an important issue. Especially, they work in China mainland environment. How estimate the librarians work pressure and improve the quality of service in college libraries. Those are another serious issues. In this article, the authors would like discuss how can we use fuzzy inference to test librarian work pressure.
Fuzzy stochastic damage mechanics (FSDM based on fuzzy auto-adaptive control theory
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.
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.
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.
Measurement on K-electron capture probability in the decay of {sup 97}Ru
Kalayani, V.D.M.L.; Vara Prasad, N.V.S.; Chandrasekhar Rao, M.V.S.; Satyanarayana, G.; Sastry, D.L. [Swami Jnanananda Laboratories for Nuclear Research, Andhra University, Visakhapatnam (India); Chintalapudi, S.N. [Inter University Consortium for DEA Facililities, Calcutta (India)
1999-08-01
The K-electron capture probabilities of two strong allowed transitions 5/2{sup +}{yields}5/2{sup +} and 5/2{sup +}{yields}7/2{sup +} were measured in the decay of {sup 97}Ru employing the X-{gamma} internal summing technique. The two P{sub K} experimental values were found to be 0.884{+-}0.046 and 0.886{+-}0.018 in agreement with the theoretical values 0.878 and 0.878, respectively. The theoretical values are seen to be insensitive for Q{sub EC} values above 200 keV.
Measurement on K-electron capture probability in the decay of 97Ru
Kalayani, V.D.M.L.; Vara Prasad, N.V.S.; Chandrasekhar Rao, M.V.S.; Satyanarayana, G.; Sastry, D.L.; Chintalapudi, S.N.
1999-01-01
The K-electron capture probabilities of two strong allowed transitions 5/2 + →5/2 + and 5/2 + →7/2 + were measured in the decay of 97 Ru employing the X-γ internal summing technique. The two P K experimental values were found to be 0.884±0.046 and 0.886±0.018 in agreement with the theoretical values 0.878 and 0.878, respectively. The theoretical values are seen to be insensitive for Q EC values above 200 keV
Global sensitivity analysis for fuzzy inputs based on the decomposition of fuzzy output entropy
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.
Nuijten, M J
1999-07-01
The aim of the present study is to describe a refinement of a previously presented method, based on the concept of point sensitivity, to deal with uncertainty in economic studies. The original method was refined by the incorporation of probability distributions which allow a more accurate assessment of the level of uncertainty in the model. In addition, a bootstrap method was used to create a probability distribution for a fixed input variable based on a limited number of data points. The original method was limited in that the sensitivity measurement was based on a uniform distribution of the variables and that the overall sensitivity measure was based on a subjectively chosen range which excludes the impact of values outside the range on the overall sensitivity. The concepts of the refined method were illustrated using a Markov model of depression. The application of the refined method substantially changed the ranking of the most sensitive variables compared with the original method. The response rate became the most sensitive variable instead of the 'per diem' for hospitalisation. The refinement of the original method yields sensitivity outcomes, which greater reflect the real uncertainty in economic studies.
Measurement of transition probabilities in Kr II UV and visible spectral lines
Mar, S; Val, J A del; RodrIguez, F; Pelaez, R J; Gonzalez, V R; Gonzalo, A B; Castro, A de; Aparicio, J A
2006-01-01
This work reports an extensive collection of 120 atomic transition probabilities of Kr II lines in the spectral region 350-720 nm, all of them measured in an emission experiment. For many of them, these are the first data up to the authors' knowledge. Relative intensity measurements have been obtained on a pulsed discharge lamp and the absolute A ki -values have been calculated by considering the available data from the literature as reference for the plasma temperature diagnosis. Excitation temperature (14 000-28 000 K) has been determined by using the Boltzmann-plot method. The plasma electron density (0.2-0.8 x 10 23 m -3 ) has been determined by two-wavelength interferometry. This work extends a previous one already published by our laboratory [1, 2]. Comparisons have also been made with previous literature values
Reliability assessment for thickness measurements of pipe wall using probability of detection
Nakamoto, Hiroyuki; Kojima, Fumio; Kato, Sho
2013-01-01
This paper proposes a reliability assessment method for thickness measurements of pipe wall using probability of detection (POD). Thicknesses of pipes are measured by qualified inspectors with ultrasonic thickness gauges. The inspection results are affected by human factors of the inspectors and include some errors, because the inspectors have different experiences and frequency of inspections. In order to ensure reliability for inspection results, first, POD evaluates experimental results of pipe-wall thickness inspection. We verify that the results have differences depending on inspectors including qualified inspectors. Second, two human factors that affect POD are indicated. Finally, it is confirmed that POD can identify the human factors and ensure reliability for pipe-wall thickness inspections. (author)
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)
An Improved Fuzzy C-Means Algorithm for the Implementation of Demand Side Management Measures
Ioannis Panapakidis
2017-09-01
Full Text Available Load profiling refers to a procedure that leads to the formulation of daily load curves and consumer classes regarding the similarity of the curve shapes. This procedure incorporates a set of unsupervised machine learning algorithms. While many crisp clustering algorithms have been proposed for grouping load curves into clusters, only one soft clustering algorithm is utilized for the aforementioned purpose, namely the Fuzzy C-Means (FCM algorithm. Since the benefits of soft clustering are demonstrated in a variety of applications, the potential of introducing a novel modification of the FCM in the electricity consumer clustering process is examined. Additionally, this paper proposes a novel Demand Side Management (DSM strategy for load management of consumers that are eligible for the implementation of Real-Time Pricing (RTP schemes. The DSM strategy is formulated as a constrained optimization problem that can be easily solved and therefore, making it a useful tool for retailers’ decision-making framework in competitive electricity markets.
Weise, K.
2004-06-01
Recent metrological developments concerning measurement uncertainty, founded on Bayesian statistics, give rise to a revision of several parts of the DIN 25482 and ISO 11929 standard series. These series stipulate detection limits and decision thresholds for ionizing-radiation measurements. Part 3 and, respectively, part 4 of them deal with measurements by use of linear-scale analogue ratemeters. A normal frequency distribution of the momentary ratemeter indication for a fixed count rate value is assumed. The actual distribution, which is first calculated numerically by solving an integral equation, differs, however, considerably from the normal distribution although this one represents an approximation of it for sufficiently large values of the count rate to be measured. As is shown, this similarly holds true for the Bayesian probability distribution of the count rate for sufficiently large given measured values indicated by the ratemeter. This distribution follows from the first one mentioned by means of the Bayes theorem. Its expectation value and variance are needed for the standards to be revised on the basis of Bayesian statistics. Simple expressions are given by the present standards for estimating these parameters and for calculating the detection limit and the decision threshold. As is also shown, the same expressions can similarly be used as sufficient approximations by the revised standards if, roughly, the present indicated value exceeds the reciprocal ratemeter relaxation time constant. (orig.)
Measurement of the resonance escape probability; Mesure de l'absorption resonnante
Anthony, J P; Bacher, P; Lheureux, L; Moreau, J; Schmitt, A P [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires
1957-07-01
The average cadmium ratio in natural uranium rods has been measured, using equal diameter natural uranium disks. These values correlated with independent measurements of the lattice buckling, enabled us to calculate values of the resonance escape probability for the G1 reactor with one or the other of two definitions. Measurements were performed on 26 mm and 32 mm rods, giving the following values for the resonance escape probability p: 0.8976 {+-} 0.005 and 0.912 {+-} 0.006 (d. 26 mm), 0.8627 {+-} 0.009 and 0.884 {+-} 0.01 (d. 32 mm). The influence of either definition on the lattice parameters is discussed, leading to values of the effective integral. Similar experiments have been performed with thorium rods. (author) [French] Nous avons mesure le rapport cadmium moyen dans des barres d'uranium a l'aide de disques d'uranium naturel de meme diametre que ces dernieres. Ces mesures nous ont permis, conjointement avec des mesures de Laplacien du reseau, de determiner deux facteurs antitrappes du reacteur G1 correspondant a deux definitions exposees. Les mesures ont ete faites sur deux diametres de barres 26 et 32 mm. Resultats: 0.8976 {+-} 0.005 and 0.912 {+-} 0.006 (d. 26 mm), 0.8627 {+-} 0.009 and 0.884 {+-} 0.01 (d. 32 mm). L'influence de ces deux definitions sur les divers parametres du reseau, est discutee. La determination de 'p' pour un diametre de barres d'uranium de 26 mm, et les mesures de variation de Laplacien, nous ont permis de calculer une valeur de l'integrale effective correspondant a chaque definition. Les mesures analogues faites sur des barres de thorium sont egalement indiquees. (auteur)
Morishita, K.; Ishino, S.; Sekimura, N.
1995-01-01
The spatial distributions of atomic displacement at the end of the collisional phase of cascade damage processes were calculated using the computer simulation code MARLOWE, which is based on the binary collision approximation (BCA). The densities of the atomic displacement were evaluated in high dense regions (HDRs) of cascades in several pure metals (Fe, Ni, Cu, Ag, Au, Mo and W). They were compared with the measured cascade collapse probabilities reported in the literature where TEM observations were carried out using thin metal foils irradiated by low-dose ions at room temperature. We found that there exists the minimum or ''critical'' values of the atomic displacement densities for the HDR to collapse into TEM-visible vacancy clusters. The critical densities are generally independent of the cascade energy in the same metal. Furthermore, the material dependence of the critical densities can be explained by the difference in the vacancy mobility at the melting temperature of target materials. This critical density calibration, which is extracted from the ion-irradiation experiments and the BCA simulations, is applied to estimation of cascade collapse probabilities in the metals irradiated by fusion neutrons. (orig.)
Hasuike, Takashi; Ishii, Hiroaki; Katagiri, Hideki
2009-01-01
This paper considers a bi-criteria general 0-1 random fuzzy programming problem based on the degree of necessity which include some previous 0-1 stochastic and fuzzy programming problems. The proposal problem is not well-defined due to including randomness and fuzziness. Therefore, by introducing chance constraint and fuzzy goals for objectives, and considering the maximization of the aspiration level for total profit and the degree of necessity that the objective function's value satisfies the fuzzy goal, the main problem is transformed into a deterministic equivalent problem. Furthermore, by using the assumption that each random variable is distributed according to a normal distribution, the problem is equivalently transformed into a basic 0-1 programming problem, and the efficient strict solution method to find an optimal solution is constructed.
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....
Rumetshofer, M.; Heim, P.; Thaler, B.; Ernst, W. E.; Koch, M.; von der Linden, W.
2018-06-01
Ultrafast dynamical processes in photoexcited molecules can be observed with pump-probe measurements, in which information about the dynamics is obtained from the transient signal associated with the excited state. Background signals provoked by pump and/or probe pulses alone often obscure these excited-state signals. Simple subtraction of pump-only and/or probe-only measurements from the pump-probe measurement, as commonly applied, results in a degradation of the signal-to-noise ratio and, in the case of coincidence detection, the danger of overrated background subtraction. Coincidence measurements additionally suffer from false coincidences, requiring long data-acquisition times to keep erroneous signals at an acceptable level. Here we present a probabilistic approach based on Bayesian probability theory that overcomes these problems. For a pump-probe experiment with photoelectron-photoion coincidence detection, we reconstruct the interesting excited-state spectrum from pump-probe and pump-only measurements. This approach allows us to treat background and false coincidences consistently and on the same footing. We demonstrate that the Bayesian formalism has the following advantages over simple signal subtraction: (i) the signal-to-noise ratio is significantly increased, (ii) the pump-only contribution is not overestimated, (iii) false coincidences are excluded, (iv) prior knowledge, such as positivity, is consistently incorporated, (v) confidence intervals are provided for the reconstructed spectrum, and (vi) it is applicable to any experimental situation and noise statistics. Most importantly, by accounting for false coincidences, the Bayesian approach allows us to run experiments at higher ionization rates, resulting in a significant reduction of data acquisition times. The probabilistic approach is thoroughly scrutinized by challenging mock data. The application to pump-probe coincidence measurements on acetone molecules enables quantitative interpretations
Magalhaes, A.N. de; Lambert-Torres, G.; Rissino, S.; Silva, M.F. da; Silva, L.E. Borges da; Carvalho, L.M.R. de
2009-07-01
It is not an easy task to frame uncertainty measurement problems by means of differential equations quickly and satisfactorily. Therefore, it is necessary to adapt the method for data representation by conditional fuzzy propositions for modeling uncertainties measurement and their effect on the propagation. This method provides a parametric adjustment for fuzzy sets of assumptions, and the functions of consequence of each rule in the manner of a parable. The paper introduces concepts of sources of errors in measures, fundamentals of fuzzy logic, description of the algorithm method, application to error detection and representation of global uncertainty.
Neutrosophic Probability, Set, And Logic (first version)
Smarandache, Florentin
2000-01-01
This project is a part of a National Science Foundation interdisciplinary project proposal. Starting from a new viewpoint in philosophy, the neutrosophy, one extends the classical "probability theory", "fuzzy set" and "fuzzy logic" to , and respectively. They are useful in artificial intelligence, neural networks, evolutionary programming, neutrosophic dynamic systems, and quantum mechanics.
Measuring space-time fuzziness with high energy γ-ray detectors
Cattaneo Paolo Walter
2017-01-01
Full Text Available There are several suggestions to probe space-time fuzziness (also known as space-time foam due to the quantum mechanics nature of space-time. These effects are predicted to be very small, being related to the Planck length, so that the only hope to experimentally detect them is to look at particles propagating along cosmological distances. Some phenomenological approaches suggest that photons originating from pointlike sources at cosmological distance experience path length fluctuation that could be detected. Also the direction of flight of such photons may be subject to a dispersion such that the image of a point-like source is blurred and detected as a disk. An experimentally accessible signature may be images of point-like sources larger that the size due to the Point Spread Function of the instrument. This additional broadening should increase with distance and photon energy. Some concrete examples that can be studied with the AGILE and FERMI-LAT γ -ray satellite experiments are discussed.
Reliability and safety analyses under fuzziness
Onisawa, T.; Kacprzyk, J.
1995-01-01
Fuzzy theory, for example possibility theory, is compatible with probability theory. What is shown so far is that probability theory needs not be replaced by fuzzy theory, but rather that the former works much better in applications if it is combined with the latter. In fact, it is said that there are two essential uncertainties in the field of reliability and safety analyses: One is a probabilistic uncertainty which is more relevant for mechanical systems and the natural environment, and the other is fuzziness (imprecision) caused by the existence of human beings in systems. The classical probability theory alone is therefore not sufficient to deal with uncertainties in humanistic system. In such a context this collection of works will put a milestone in the arguments of probability theory and fuzzy theory. This volume covers fault analysis, life time analysis, reliability, quality control, safety analysis and risk analysis. (orig./DG). 106 figs
Half-life measurements and photon emission probabilities of frequently applied radioisotopes
Schoetzig, U.; Schrader, H.
1998-09-01
It belongs to the duties of the PTB department for 'Radioactivity' to determine the radioactivity emitted by radioactive radiation sources and publish their specific decay data, also called ''standards'', so that appliers of such sources may calibrate their equipment accordingly, as e.g. photon detectors. Further data required for proper calibration are those defining the photon emission probability per decay, P(E), at the relevant photon energy E. The emission rate R(E) is derived from the activity A, by the calculus R(E)=A x P(E), and the half-lives of decay, T 1 /2, together with the standards are used for determining the time of measurement. The calibration quality essentially is determined by those two parameters and the incertainties involved. The PTB 'Radioactivity' department therefore publishes for users recommended decay data elaborated and used by the experts at PTB. The tabulated data are either measured at PTB, or critically selected from data compilations of other publication sources. The tabulated decay data presented here are intended to serve as a source of reference for laboratory work and should be used in combination with the comprehensive data collections available (see the bibliography of this document: 86BRFI, 91TECD, 96FI, Nuclear Data Sheets, e.g. 98ND84). (orig./CB) [de
Shiryaev, Albert N
2016-01-01
This book contains a systematic treatment of probability from the ground up, starting with intuitive ideas and gradually developing more sophisticated subjects, such as random walks, martingales, Markov chains, the measure-theoretic foundations of probability theory, weak convergence of probability measures, and the central limit theorem. Many examples are discussed in detail, and there are a large number of exercises. The book is accessible to advanced undergraduates and can be used as a text for independent study. To accommodate the greatly expanded material in the third edition of Probability, the book is now divided into two volumes. This first volume contains updated references and substantial revisions of the first three chapters of the second edition. In particular, new material has been added on generating functions, the inclusion-exclusion principle, theorems on monotonic classes (relying on a detailed treatment of “π-λ” systems), and the fundamental theorems of mathematical statistics.
Asmussen, Søren; Albrecher, Hansjörg
The book gives a comprehensive treatment of the classical and modern ruin probability theory. Some of the topics are Lundberg's inequality, the Cramér-Lundberg approximation, exact solutions, other approximations (e.g., for heavy-tailed claim size distributions), finite horizon ruin probabilities......, extensions of the classical compound Poisson model to allow for reserve-dependent premiums, Markov-modulation, periodicity, change of measure techniques, phase-type distributions as a computational vehicle and the connection to other applied probability areas, like queueing theory. In this substantially...... updated and extended second version, new topics include stochastic control, fluctuation theory for Levy processes, Gerber–Shiu functions and dependence....
Measurements of atomic transition probabilities in highly ionized atoms by fast ion beams
Martinson, I.; Curtis, L.J.; Lindgaerd, A.
1977-01-01
A summary is given of the beam-foil method by which level lifetimes and transition probabilities can be determined in atoms and ions. Results are presented for systems of particular interest for fusion research, such as the Li, Be, Na, Mg, Cu and Zn isoelectronic sequences. The available experimental material is compared to theoretical transition probabilities. (author)
Mosbeh R. Kaloop
2015-10-01
Full Text Available This study describes the performance assessment of the Huangpu Bridge in Guangzhou, China based on long-term monitoring in real-time by the kinematic global positioning system (RTK-GPS technique. Wavelet transformde-noising is applied to filter the GPS measurements, while the adaptive neuro-fuzzy inference system (ANFIS time series output-only model is used to predict the deformations of GPS-bridge monitoring points. In addition, GPS and accelerometer monitoring systems are used to evaluate the bridge oscillation performance. The conclusions drawn from investigating the numerical results show that: (1the wavelet de-noising of the GPS measurements of the different recording points on the bridge is a suitable tool to efficiently eliminate the signal noise and extract the different deformation components such as: semi-static and dynamic displacements; (2 the ANFIS method with two multi-input single output model is revealed to powerfully predict GPS movement measurements and assess the bridge deformations; and (3 The installed structural health monitoring system and the applied ANFIS movement prediction performance model are solely sufficient to assure bridge safety based on the analyses of the different filtered movement components.
Vitelli, Chiara; Spagnolo, Nicolo; Toffoli, Lorenzo; Sciarrino, Fabio; De Martini, Francesco
2010-01-01
We consider the high-gain spontaneous parametric down-conversion in a noncollinear geometry as a paradigmatic scenario to investigate the quantum-to-classical transition by increasing the pump power, that is, the average number of generated photons. The possibility of observing quantum correlations in such a macroscopic quantum system through dichotomic measurement will be analyzed by addressing two different measurement schemes, based on different dichotomization processes. More specifically, we will investigate the persistence of nonlocality in an increasing size (n/2)-spin singlet state by studying the change in the correlations form as n increases, both in the ideal case and in presence of losses. We observe a fast decrease in the amount of Bell's inequality violation for increasing system size. This theoretical analysis is supported by the experimental observation of macro-macro correlations with an average number of photons of about 10 3 . Our results shed light on the practical extreme difficulty of observing nonlocality by performing such a dichotomic fuzzy measurement.
Senvar, M. O.; Vayvay, O.; Kurt, E.; Hloch, Sergej
2014-01-01
Roč. 21, č. 1 (2014), s. 155-162 ISSN 1330-3651 Institutional support: RVO:68145535 Keywords : balanced scorecard * fuzzy * automotive Subject RIV: JQ - Machines ; Tools Impact factor: 0.579, year: 2014
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...
A. Taravat
2014-10-01
Full Text Available Public spaces accessibility has become one of the important factors in urban planning. Therefore, considerable attention has been given to measure accessibility to public spaces on the UK, US and Canada, but there are few studies outside the anglophone world especially in developing countries such as Iran. In this study an attempt has been made to measure objective accessibility to public spaces (parks, school, library and administrative using fuzzy majority GIS-based multicriteria decision analysis. This method is for defining the priority for distribution of urban facilities and utilities as the first step towards elimination of social justice. In order to test and demonstrate the presented model, the comprehensive plan of Malayer city has been considered for ranking in three objectives and properties in view of index per capital (Green space, sport facilities and major cultural centers like library and access index. The results can be used to inform the local planning process and the GIS approach can be expanded into other local authority domains. The results shows that the distribution of facilities in Malayer city has followed on the base of cost benefit law and the human aspect of resource allocation programming of facilities (from centre to suburbs of the city.
Mehrdad Kargari
2018-01-01
Full Text Available An effective hybrid model has been proposed by combining ANP, SERVQUAL, and DEMATEL techniques. This model aims to meet different purposes of the hotels and diverse needs of customers at different stages, that is, reservation, reception, accommodation, catering, and check-out. High quality services are ensured when customer expectations have been provided at the expectation level of the customers or beyond that. SERVQUAL model is used to assess the performance of the organizations in terms of five dimensions: responsiveness, empathy, reliability, assurance, and tangibles. Super matrix calculations and pair comparisons required in ANP model have been carried out using DEMATEL model in order to measure the influence of performance assessment measures on each other. In this paper, SERVQUAL model parameters have been considered as the expectations of the hotel clients. Then these customer expectations have been analyzed using DEMATEL model and finally have been ranked using ANP model. Parameters of SERVQUAL model are comprised of verbal and vague criteria in terms of the responses provided by the organizations and customers. This has led to fuzzy conditions in this research. The hybrid model provided better results compared with each individual model, in terms of meeting customer satisfaction and the organization’s objectives.
Taravat, A.; Yari, A.; Rajaei, M.; Mousavian, R.
2014-10-01
Public spaces accessibility has become one of the important factors in urban planning. Therefore, considerable attention has been given to measure accessibility to public spaces on the UK, US and Canada, but there are few studies outside the anglophone world especially in developing countries such as Iran. In this study an attempt has been made to measure objective accessibility to public spaces (parks, school, library and administrative) using fuzzy majority GIS-based multicriteria decision analysis. This method is for defining the priority for distribution of urban facilities and utilities as the first step towards elimination of social justice. In order to test and demonstrate the presented model, the comprehensive plan of Malayer city has been considered for ranking in three objectives and properties in view of index per capital (Green space, sport facilities and major cultural centers like library and access index). The results can be used to inform the local planning process and the GIS approach can be expanded into other local authority domains. The results shows that the distribution of facilities in Malayer city has followed on the base of cost benefit law and the human aspect of resource allocation programming of facilities (from centre to suburbs of the city).
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.
Integrating Fuzzy AHP and Fuzzy ARAS for evaluating financial performance
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.
Yampolsky, M; Salafia, C M; Shlakhter, O
2013-06-01
While the mean shape of human placenta is round with centrally inserted umbilical cord, significant deviations from this ideal are fairly common, and may be clinically meaningful. Traditionally, they are explained by trophotropism. We have proposed a hypothesis explaining typical variations in placental shape by randomly determined fluctuations in the growth process of the vascular tree. It has been recently reported that umbilical cord displacement in a birth cohort has a log-normal probability distribution, which indicates that the displacement between an initial point of origin and the centroid of the mature shape is a result of accumulation of random fluctuations of the dynamic growth of the placenta. To confirm this, we investigate statistical distributions of other features of placental morphology. In a cohort of 1023 births at term digital photographs of placentas were recorded at delivery. Excluding cases with velamentous cord insertion, or missing clinical data left 1001 (97.8%) for which placental surface morphology features were measured. Best-fit statistical distributions for them were obtained using EasyFit. The best-fit distributions of umbilical cord displacement, placental disk diameter, area, perimeter, and maximal radius calculated from the cord insertion point are of heavy-tailed type, similar in shape to log-normal distributions. This is consistent with a stochastic origin of deviations of placental shape from normal. Deviations of placental shape descriptors from average have heavy-tailed distributions similar in shape to log-normal. This evidence points away from trophotropism, and towards a spontaneous stochastic evolution of the variants of placental surface shape features. Copyright © 2013 Elsevier Ltd. All rights reserved.
Probabilistic Quadratic Programming Problems with Some Fuzzy Parameters
S. K. Barik
2012-01-01
making problem by using some specified random variables and fuzzy numbers. In the present paper, randomness is characterized by Weibull random variables and fuzziness is characterized by triangular and trapezoidal fuzzy number. A defuzzification method has been introduced for finding the crisp values of the fuzzy numbers using the proportional probability density function associated with the membership functions of these fuzzy numbers. An equivalent deterministic crisp model has been established in order to solve the proposed model. Finally, a numerical example is presented to illustrate the solution procedure.
Fuzzy tree automata and syntactic pattern recognition.
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.
Intelligent control-I: review of fuzzy logic and fuzzy set theory
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)
Christensen, Line Hjorth
"Fuzzy stuff". Exploring the displacement of the design sketch. What kind of knowledge can historical sketches reveal when they have outplayed their primary instrumental function in the design process and are moved into a museum collection? What are the rational benefits of ‘archival displacement...
Human Error Analysis by Fuzzy-Set
Situmorang, Johnny
1996-01-01
In conventional HRA the probability of Error is treated as a single and exact value through constructing even tree, but in this moment the Fuzzy-Set Theory is used. Fuzzy set theory treat the probability of error as a plausibility which illustrate a linguistic variable. Most parameter or variable in human engineering been defined verbal good, fairly good, worst etc. Which describe a range of any value of probability. For example this analysis is quantified the human error in calibration task, and the probability of miscalibration is very low
Production of 147Eu for gamma-ray emission probability measurement
Katoh, Keiji; Marnada, Nada; Miyahara, Hiroshi
2002-01-01
Gamma-ray emission probability is one of the most important decay parameters of radionuclide and many researchers are paying efforts to improve the certainty of it. The certainties of γ-ray emission probabilities for neutron-rich nuclides are being improved little by little, but the improvements of those for proton-rich nuclides are still insufficient. Europium-147 that decays by electron capture or β + -particle emission is a proton-rich nuclide and the γ-ray emission probabilities evaluated by Mateosian and Peker have large uncertainties. They referred to only one report concerning with γ-ray emission probabilities. Our final purpose is to determine the precise γ-ray emission probabilities of 147 Eu from disintegration rates and γ-ray intensities by using a 4πβ-γ coincidence apparatus. Impurity nuclides affect largely to the determination of disintegration rate; therefore, a highly pure 147 Eu source is required. This short note will describe the most proper energy for 147 Eu production through 147 Sm(p, n) reaction. (author)
Trending in Probability of Collision Measurements via a Bayesian Zero-Inflated Beta Mixed Model
Vallejo, Jonathon; Hejduk, Matt; Stamey, James
2015-01-01
We investigate the performance of a generalized linear mixed model in predicting the Probabilities of Collision (Pc) for conjunction events. Specifically, we apply this model to the log(sub 10) transformation of these probabilities and argue that this transformation yields values that can be considered bounded in practice. Additionally, this bounded random variable, after scaling, is zero-inflated. Consequently, we model these values using the zero-inflated Beta distribution, and utilize the Bayesian paradigm and the mixed model framework to borrow information from past and current events. This provides a natural way to model the data and provides a basis for answering questions of interest, such as what is the likelihood of observing a probability of collision equal to the effective value of zero on a subsequent observation.
Relational Demonic Fuzzy Refinement
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...
Bellemare, C.; Kroger, S.; van Soest, A.H.O.
2008-01-01
We combine choice data in the ultimatum game with the expectations of proposers elicited by subjective probability questions to estimate a structural model of decision making under uncertainty. The model, estimated using a large representative sample of subjects from the Dutch population, allows
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.
Human factors and fuzzy set theory for safety analysis
Nishiwaki, Y.
1987-01-01
Human reliability and performance is affected by many factors: medical, physiological and psychological, etc. The uncertainty involved in human factors may not necessarily be probabilistic, but fuzzy. Therefore, it is important to develop a theory by which both the non-probabilistic uncertainties, or fuzziness, of human factors and the probabilistic properties of machines can be treated consistently. In reality, randomness and fuzziness are sometimes mixed. From the mathematical point of view, probabilistic measures may be considered a special case of fuzzy measures. Therefore, fuzzy set theory seems to be an effective tool for analysing man-machine systems. The concept 'failure possibility' based on fuzzy sets is suggested as an approach to safety analysis and fault diagnosis of a large complex system. Fuzzy measures and fuzzy integrals are introduced and their possible applications are also discussed. (author)
A Fuzzy Approach for Integrated Measure of Object-Oriented Software Testability
Vandana Gupta; K. K. Aggarwal; Yogesh Singh
2005-01-01
For large software systems, testing phase seems to have profound effect on the overall acceptability and quality of the final product. The success of this activity can be judged by measuring the testability of the software. A good measure for testability can better manage the testing effort and time. Different Object Oriented Metrics are used in measurement of object-oriented testability but none of them is alone sufficient to give an overall reflection of software testabi...
Measuring survival time: a probability-based approach useful in healthcare decision-making.
2011-01-01
In some clinical situations, the choice between treatment options takes into account their impact on patient survival time. Due to practical constraints (such as loss to follow-up), survival time is usually estimated using a probability calculation based on data obtained in clinical studies or trials. The two techniques most commonly used to estimate survival times are the Kaplan-Meier method and the actuarial method. Despite their limitations, they provide useful information when choosing between treatment options.
Fuzzy associative memories for instrument fault detection
Heger, A.S.
1996-01-01
A fuzzy logic instrument fault detection scheme is developed for systems having two or three redundant sensors. In the fuzzy logic approach the deviation between each signal pairing is computed and classified into three fuzzy sets. A rule base is created allowing the human perception of the situation to be represented mathematically. Fuzzy associative memories are then applied. Finally, a defuzzification scheme is used to find the centroid location, and hence the signal status. Real-time analyses are carried out to evaluate the instantaneous signal status as well as the long-term results for the sensor set. Instantaneous signal validation results are used to compute a best estimate for the measured state variable. The long-term sensor validation method uses a frequency fuzzy variable to determine the signal condition over a specific period. To corroborate the methodology synthetic data representing various anomalies are analyzed with both the fuzzy logic technique and the parity space approach. (Author)
Marini P.
2016-01-01
Full Text Available Fission and gamma decay probabilities of 237U and 239Np have been measured, for the first time simultaneously in dedicated experiments, via the surrogate reactions 238U(3He, 4He and 238U(3He,d, respectively. While a good agreement between our data and neutron-induced data is found for fission probabilities, gamma decay probabilities are several times higher than the corresponding neutron-induced data for each studied nucleus. We study the role of the different spin distributions populated in the surrogate and neutron-induced reactions. The compound nucleus spin distribution populated in the surrogate reaction is extracted from the measured gamma-decay probabilities, and used as input parameter in the statistical model to predict fission probabilities to be compared to our data. A strong disagreement between our data and the prediction is obtained. Preliminary results from an additional dedicated experiment confirm the observed discrepancies, indicating the need of a better understanding of the formation and decay processes of the compound nucleus.
Location Discovery Based on Fuzzy Geometry in Passive Sensor Networks
Rui Wang
2011-01-01
Full Text Available Location discovery with uncertainty using passive sensor networks in the nation's power grid is known to be challenging, due to the massive scale and inherent complexity. For bearings-only target localization in passive sensor networks, the approach of fuzzy geometry is introduced to investigate the fuzzy measurability for a moving target in R2 space. The fuzzy analytical bias expressions and the geometrical constraints are derived for bearings-only target localization. The interplay between fuzzy geometry of target localization and the fuzzy estimation bias for the case of fuzzy linear observer trajectory is analyzed in detail in sensor networks, which can realize the 3-dimensional localization including fuzzy estimate position and velocity of the target by measuring the fuzzy azimuth angles at intervals of fixed time. Simulation results show that the resulting estimate position outperforms the traditional least squares approach for localization with uncertainty.
Expert Opinion Elicitation Using Fuzzy Set Theory and Distempers-Shaker's Theory
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
An Entropy-Based Measure for Assessing Fuzziness in Logistic Regression
Weiss, Brandi A.; Dardick, William
2016-01-01
This article introduces an entropy-based measure of data-model fit that can be used to assess the quality of logistic regression models. Entropy has previously been used in mixture-modeling to quantify how well individuals are classified into latent classes. The current study proposes the use of entropy for logistic regression models to quantify…
Fuzzy One-Class Classification Model Using Contamination Neighborhoods
Lev V. Utkin
2012-01-01
Full Text Available A fuzzy classification model is studied in the paper. It is based on the contaminated (robust model which produces fuzzy expected risk measures characterizing classification errors. Optimal classification parameters of the models are derived by minimizing the fuzzy expected risk. It is shown that an algorithm for computing the classification parameters is reduced to a set of standard support vector machine tasks with weighted data points. Experimental results with synthetic data illustrate the proposed fuzzy model.
A FUZZY LOGIC APPROACH TO MEASURE THE PRECISE TESTABILITY INDEX OF SOFTWARE
NAVDEEP KAUR,; MANINDERPAL SINGH
2011-01-01
Many of the software fails as a result of poor quality. For large software projects testing has a deep influence on the overall acceptability and quality of the final software. Testability of the software can be effectively measured form the testability effort and the time required to test the software. In today’s software development environment, object oriented design and development become important. There is strong relationship between the object oriented metrics and the testability effor...
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
Gu, Yong; Angelaki, Dora E; DeAngelis, Gregory C
2014-07-01
Trial by trial covariations between neural activity and perceptual decisions (quantified by choice Probability, CP) have been used to probe the contribution of sensory neurons to perceptual decisions. CPs are thought to be determined by both selective decoding of neural activity and by the structure of correlated noise among neurons, but the respective roles of these factors in creating CPs have been controversial. We used biologically-constrained simulations to explore this issue, taking advantage of a peculiar pattern of CPs exhibited by multisensory neurons in area MSTd that represent self-motion. Although models that relied on correlated noise or selective decoding could both account for the peculiar pattern of CPs, predictions of the selective decoding model were substantially more consistent with various features of the neural and behavioral data. While correlated noise is essential to observe CPs, our findings suggest that selective decoding of neuronal signals also plays important roles.
Measuring public opinion on alcohol policy: a factor analytic study of a US probability sample.
Latimer, William W; Harwood, Eileen M; Newcomb, Michael D; Wagenaar, Alexander C
2003-03-01
Public opinion has been one factor affecting change in policies designed to reduce underage alcohol use. Extant research, however, has been criticized for using single survey items of unknown reliability to define adult attitudes on alcohol policy issues. The present investigation addresses a critical gap in the literature by deriving scales on public attitudes, knowledge, and concerns pertinent to alcohol policies designed to reduce underage drinking using a US probability sample survey of 7021 adults. Five attitudinal scales were derived from exploratory and confirmatory factor analyses addressing policies to: (1) regulate alcohol marketing, (2) regulate alcohol consumption in public places, (3) regulate alcohol distribution, (4) increase alcohol taxes, and (5) regulate youth access. The scales exhibited acceptable psychometric properties and were largely consistent with a rational framework which guided the survey construction.
Jesús Caja
2016-06-01
Full Text Available A method for analysing the effect of different hypotheses about the type of the input quantities distributions of a measurement model is presented here so that the developed algorithms can be simplified. As an example, a model of indirect measurements with optical coordinate measurement machine was employed to evaluate these different hypotheses. As a result of the different experiments, the assumption that the different variables of the model can be modelled as normal distributions is proved.
Fuzziness and fuzzy modelling in Bulgaria's energy policy decision-making dilemma
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)
Kaschek, K.; Ernst, G.K.; Boetticher, W.
1984-01-01
Absolute transition probabilities of nine 5s-5p transitions of Kr I have been evaluated by using the hook method. The plasma was produced in a shock tube. The population density of the 5s-levels was calculated, under the assumption of LTE, from the electron density and the ground state number measured by means of a dual wavelength interferometer. An evaluation is given which proves the validity of the LTE assumption. (orig.)
Intuitionistic supra fuzzy topological spaces
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
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...
Viscosity measurement - probably a means for detecting radiation treatment of spices?
Heide, L.; Albrich, S.; Boegl, K.W.
1987-12-01
The viscosity of 13 different spices and dried vegetables in total was measured. Optimal conditions were first determined for each product, i.e. concentration, pH-value, temperature, particle size and soaking time. For method evaluation, examinations were primarily performed to study the effect of storage, the reproducibility and the influence of the different varieties of the same spice. In supplement, for pepper, the viscosity was measured as a function of radiation dose. In summation, significant changes in the gel forming capability after irradiation could be observed after preliminary experiments in 8 dried spices (ginger, carrots, leek, cloves, pepper, celery, cinnamon and onions). With 3 spices (ginger, pepper and cinnamon) could the results from examining all different varieties of the same spice be substantiated. An additional influence of storage time on viscosity could not be proved during the investigative period of 8 months. Generally seen, there is no possibility of being able to identify an irradiated spice on the basis of viscosity measurements alone, since the difference between the varieties of one and the same spice is considerably great. However, radiation treatment can be reliably excluded with ginger, pepper and cinnamon, if the viscosities are high (10-20 Pa x s). (orig./MG) [de
A neuro-fuzzy inference system for sensor failure detection using wavelet denoising, PCA and SPRT
Na, Man Gyun
2001-01-01
In this work, a neuro-fuzzy inference system combined with the wavelet denoising, PCA(principal component analysis) and SPRT (sequential probability ratio test) methods is developed to detect the relevant sensor failure using other sensor signals. The wavelet denoising technique is applied to remove noise components in input signals into the neuro-fuzzy system. The PCA is used to reduce the dimension of an input space without losing a significant amount of information, The PCA makes easy the selection of the input signals into the neuro-fuzzy system. Also, a lower dimensional input space usually reduces the time necessary to train a neuro-fuzzy system. The parameters of the neuro-fuzzy inference system which estimates the relevant sensor signal are optimized by a genetic algorithm and a least-squares algorithm. The residuals between the estimated signals and the measured signals are used to detect whether the sensors are failed or not. The SPRT is used in this failure detection algorithm. The proposed sensor-monitoring algorithm was verified through applications to the pressurizer water level and the hot-leg flowrate sensors in pressurized water reactors
Why fuzzy controllers should be fuzzy
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
MEASURING MODEL FOR BAD LOANS IN BANKS. THE DEFAULT PROBABILITY MODEL.
SOCOL ADELA
2010-12-01
Full Text Available The banking sectors of the transition countries have progressed remarkably in the last 20 years. In fact, banking in most transition countries has largely shaken off the traumas of the transition eraAt the start of the 21st century banks in these countries look very much like banks elsewhere. That is, they are by no means problem free but they are struggling with the same issues as banks in other emerging market countries during the financial crises conditions. The institutional environment differs considerably among the countries. The goal we set with this article is to examine in terms of methodology the most important assessment criteria of a measuring model for bad loans.
Flows in networks under fuzzy conditions
Bozhenyuk, Alexander Vitalievich; Kacprzyk, Janusz; Rozenberg, Igor Naymovich
2017-01-01
This book offers a comprehensive introduction to fuzzy methods for solving flow tasks in both transportation and networks. It analyzes the problems of minimum cost and maximum flow finding with fuzzy nonzero lower flow bounds, and describes solutions to minimum cost flow finding in a network with fuzzy arc capacities and transmission costs. After a concise introduction to flow theory and tasks, the book analyzes two important problems. The first is related to determining the maximum volume for cargo transportation in the presence of uncertain network parameters, such as environmental changes, measurement errors and repair work on the roads. These parameters are represented here as fuzzy triangular, trapezoidal numbers and intervals. The second problem concerns static and dynamic flow finding in networks under fuzzy conditions, and an effective method that takes into account the network’s transit parameters is presented here. All in all, the book provides readers with a practical reference guide to state-of-...
Fuzzy Neuroidal Nets and Recurrent Fuzzy Computations
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
Fuzzy Itand#244; Integral Driven by a Fuzzy Brownian Motion
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.
Jae Won Bang
2015-05-01
Full Text Available With the rapid increase of 3-dimensional (3D content, considerable research related to the 3D human factor has been undertaken for quantitatively evaluating visual discomfort, including eye fatigue and dizziness, caused by viewing 3D content. Various modalities such as electroencephalograms (EEGs, biomedical signals, and eye responses have been investigated. However, the majority of the previous research has analyzed each modality separately to measure user eye fatigue. This cannot guarantee the credibility of the resulting eye fatigue evaluations. Therefore, we propose a new method for quantitatively evaluating eye fatigue related to 3D content by combining multimodal measurements. This research is novel for the following four reasons: first, for the evaluation of eye fatigue with high credibility on 3D displays, a fuzzy-based fusion method (FBFM is proposed based on the multimodalities of EEG signals, eye blinking rate (BR, facial temperature (FT, and subjective evaluation (SE; second, to measure a more accurate variation of eye fatigue (before and after watching a 3D display, we obtain the quality scores of EEG signals, eye BR, FT and SE; third, for combining the values of the four modalities we obtain the optimal weights of the EEG signals BR, FT and SE using a fuzzy system based on quality scores; fourth, the quantitative level of the variation of eye fatigue is finally obtained using the weighted sum of the values measured by the four modalities. Experimental results confirm that the effectiveness of the proposed FBFM is greater than other conventional multimodal measurements. Moreover, the credibility of the variations of the eye fatigue using the FBFM before and after watching the 3D display is proven using a t-test and descriptive statistical analysis using effect size.
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...
Fuzzy Graph Language Recognizability
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.
Fuzzy Gauge Capability (Cg and Cgk) through Buckley Approach
Seyed Habib A. Rahmati; Mohsen Sadegh Amalnick
2015-01-01
Different terms of the Statistical Process Control (SPC) has sketch in the fuzzy environment. However, Measurement System Analysis (MSA), as a main branch of the SPC, is rarely investigated in fuzzy area. This procedure assesses the suitability of the data to be used in later stages or decisions of the SPC. Therefore, this research focuses on some important measures of MSA and through a new method introduces the measures in fuzzy environment. In this method, which works b...
Intuitionistic Fuzzy Subbialgebras and Duality
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.
Allabakash, S.; Yasodha, P.; Bianco, L.; Venkatramana Reddy, S.; Srinivasulu, P.; Lim, S.
2017-09-01
This paper presents the efficacy of a "tuned" fuzzy logic method at determining the height of the boundary layer using the measurements from a 1280 MHz lower atmospheric radar wind profiler located in Gadanki (13.5°N, 79°E, 375 mean sea level), India, and discusses the diurnal and seasonal variations of the measured convective boundary layer over this tropical station. The original fuzzy logic (FL) method estimates the height of the atmospheric boundary layer combining the information from the range-corrected signal-to-noise ratio, the Doppler spectral width of the vertical velocity, and the vertical velocity itself, measured by the radar, through a series of thresholds and rules, which did not prove to be optimal for our radar system and geographical location. For this reason the algorithm was tuned to perform better on our data set. Atmospheric boundary layer heights obtained by this tuned FL method, the original FL method, and by a "standard method" (that only uses the information from the range-corrected signal-to-noise ratio) are compared with those obtained from potential temperature profiles measured by collocated Global Positioning System Radio Sonde during years 2011 and 2013. The comparison shows that the tuned FL method is more accurate than the other methods. Maximum convective boundary layer heights are observed between 14:00 and 15:00 local time (LT = UTC + 5:30) for clear-sky days. These daily maxima are found to be lower during winter and postmonsoon seasons and higher during premonsoon and monsoon seasons, due to net surface radiation and convective processes over this region being more intense during premonsoon and monsoon seasons and less intense in winter and postmonsoon seasons.
Integration, measure and probability
Pitt, H R
2012-01-01
Introductory treatment develops the theory of integration in a general context, making it applicable to other branches of analysis. More specialized topics include convergence theorems and random sequences and functions. 1963 edition.
Chemin, J.F.; Andriamonje, S.; Guezet, D.; Thibaud, J.P.; Aguer, P.; Hannachi, F.; Bruandet, J.F.
1984-01-01
We have measured, for the first time, the ionization probability Psub(1s sigma) of the 1s sigma molecular orbital in the way into a nuclear reaction (in half a collision at zero impact parameter) in a near symmetric collision 58 Ni + 54 Fe at 230 MeV leads to a compound nucleus of 112 Xe highly excited which decays first by sequential emission of charged particles and then by sequential emission of gamma rays. The determination of Psub(1s sigma) is based on the coincidence measurement between X-rays and γ-rays and the Doppler shift method is used to discrimine the ''atomic'' and ''nuclear'' X-rays
Optimality Conditions for Fuzzy Number Quadratic Programming with Fuzzy Coefficients
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.
Countable Fuzzy Topological Space and Countable Fuzzy Topological Vector Space
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.
Recurrent fuzzy ranking methods
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.
Knowledge typology for imprecise probabilities.
Wilson, G. D. (Gregory D.); Zucker, L. J. (Lauren J.)
2002-01-01
When characterizing the reliability of a complex system there are often gaps in the data available for specific subsystems or other factors influencing total system reliability. At Los Alamos National Laboratory we employ ethnographic methods to elicit expert knowledge when traditional data is scarce. Typically, we elicit expert knowledge in probabilistic terms. This paper will explore how we might approach elicitation if methods other than probability (i.e., Dempster-Shafer, or fuzzy sets) prove more useful for quantifying certain types of expert knowledge. Specifically, we will consider if experts have different types of knowledge that may be better characterized in ways other than standard probability theory.
Mohammad Hemati
2011-07-01
Full Text Available An increase competition on today's economy has created motivation for many organizations to look for different alternatives on better serving the customers. There are always some budget limitations on any customer relationship method, which leads us to prioritize different alternatives. In this paper, we present an empirical method based on an integrated Kano and fuzzy analytical hierarchy procedure to rank suitable alternatives. The proposed model of this paper uses a questionnaire survey to gather customer's opinions and implements the method for a real-world case study of transportation planning. The questionnaire includes 37 questions distributed among 976 passengers for two trips in Iran. The results indicate that driver's physical and mental health, buss equipments with GPS functionality and familiarity of drivers with road and road's conditions play important role on choosing a transportation company.
An adaptive map-matching algorithm based on hierarchical fuzzy system from vehicular GPS data.
Jinjun Tang
Full Text Available An improved hierarchical fuzzy inference method based on C-measure map-matching algorithm is proposed in this paper, in which the C-measure represents the certainty or probability of the vehicle traveling on the actual road. A strategy is firstly introduced to use historical positioning information to employ curve-curve matching between vehicle trajectories and shapes of candidate roads. It improves matching performance by overcoming the disadvantage of traditional map-matching algorithm only considering current information. An average historical distance is used to measure similarity between vehicle trajectories and road shape. The input of system includes three variables: distance between position point and candidate roads, angle between driving heading and road direction, and average distance. As the number of fuzzy rules will increase exponentially when adding average distance as a variable, a hierarchical fuzzy inference system is then applied to reduce fuzzy rules and improve the calculation efficiency. Additionally, a learning process is updated to support the algorithm. Finally, a case study contains four different routes in Beijing city is used to validate the effectiveness and superiority of the proposed method.
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...
Burke, J. T. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Hughes, R. O. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Escher, J. E. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Scielzo, N. D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Casperson, R. J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Ressler, J. J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Saastamoinen, A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Ota, S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Park, H. I. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Ross, T. J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); McCleskey, M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); McCleskey, E. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Austin, R. E. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Rapisarda, G. G. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2017-09-21
This technical report documents the surrogate reaction method and experimental results used to determine the desired neutron induced cross sections of ^{87}Y(n,g) and the known ^{90}Zr(n,g) cross section. This experiment was performed at the STARLiTeR apparatus located at Texas A&M Cyclotron Institute using the K150 Cyclotron which produced a 28.56 MeV proton beam. The proton beam impinged on Y and Zr targets to produce the nuclear reactions ^{89}Y(p,d)^{88}Y and ^{92}Zr(p,d)^{91}Zr. Both particle singles data and particle-gamma ray coincident data were measured during the experiment. This data was used to determine the γ-ray probability as a function of energy for these reactions. The results for the γ-ray probabilities as a function of energy for both these nuclei are documented here. For completeness, extensive tabulated and graphical results are provided in the appendices.
Indeterminacy, linguistic semantics and fuzzy logic
Novak, V. [Univ. of Ostrava (Czech Republic)
1996-12-31
In this paper, we discuss the indeterminacy phenomenon which has two distinguished faces, namely uncertainty modeled especially by the probability theory and vagueness, modeled by fuzzy logic. Other important mathematical model of vagueness is provided by the Alternative Set Theory. We focus on some of the basic concepts of these theories in connection with mathematical modeling of the linguistic semantics.
Moeller, O.
2005-01-01
This work reports on results from two Recoil-Distance-Doppler-Shift lifetime measurements of excited states in 155 Dy and 178 Os. The experiments were carried out at the GASP spektrometer of the Laboratori Nazional i di Legnaro in combination with the Cologne plunger apparatus. The main purpose of the performed experiments was to test the predictions of the X(5) critical point symmetry in these two nuclei. In 156 Dy and 178 Os 29 lifetimes of excited states were derived using the Differential-Decay-Curve method. In weaker reaction channels the nuclei 155 Dy, 157 Dy and 177 Os were populated. In these nuclei 32 additional lifetimes were measured, most of them for the first time. In order to calculate absolute transition probabilities from the measured lifetimes of the first excited band in 156 Dy, essential branching ratios were derived from the measured data with a very small systematic error ( 178 Os confirm the consistency of a X(5) description in these nuclei. A comparision with the well established X(5)-like nuclei in the N=90 isotones gives an agreement with the X(5) description of at least the same quality. (orig.)
A first course in fuzzy logic, fuzzy dynamical systems, and biomathematics theory and applications
de Barros, Laécio Carvalho; Lodwick, Weldon Alexander
2017-01-01
This book provides an essential introduction to the field of dynamical models. Starting from classical theories such as set theory and probability, it allows readers to draw near to the fuzzy case. On one hand, the book equips readers with a fundamental understanding of the theoretical underpinnings of fuzzy sets and fuzzy dynamical systems. On the other, it demonstrates how these theories are used to solve modeling problems in biomathematics, and presents existing derivatives and integrals applied to the context of fuzzy functions. Each of the major topics is accompanied by examples, worked-out exercises, and exercises to be completed. Moreover, many applications to real problems are presented. The book has been developed on the basis of the authors’ lectures to university students and is accordingly primarily intended as a textbook for both upper-level undergraduates and graduates in applied mathematics, statistics, and engineering. It also offers a valuable resource for practitioners such as mathematical...
Measurement on K-electron capture probabilities in the decay of [sup 183]Re and [sup 168]Tm
Prasad, N.V.S.V.; Rao, M.V.S.C.; Reddy, S.B.; Satyanarayana, G.; Sastry, D.L. (Andhra Univ., Visakhapatnam (India). Swami Jnanananda Labs. for Nuclear Research); Murty, G.S.K. (UNDNJ, Newark, NJ (United States). Dept. of Radiology); Chintalapudi, S.N. (Inter University Consortium for DAE Facilities, Calcutta (India))
1994-03-01
The K-electron capture probabilities for the 5/2[sup +] to 3/2[sup -]transition in the electron capture decay of [sup 183]Re to the 208.805 keV level in the daughter [sup 183]W and for the 3[sup (+)] to 3[sup -]and 3[sup (+)] to 4[sup -] transitions in the electron capture decay of [sup 168]Tm to the 1541.4 keV and 1093.0 keV levels, respectively, in the daughter [sup 168]Er were measured for the first time using an x-[gamma] summing method. The experimental P[sub K] values are reported in this paper, together with those due to theory, and discussed. (Author).
Sputtering properties of tungsten 'fuzzy' surfaces
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 .
Improving Ranking Using Quantum Probability
Melucci, Massimo
2011-01-01
The paper shows that ranking information units by quantum probability differs from ranking them by classical probability provided the same data used for parameter estimation. As probability of detection (also known as recall or power) and probability of false alarm (also known as fallout or size) measure the quality of ranking, we point out and show that ranking by quantum probability yields higher probability of detection than ranking by classical probability provided a given probability of ...
Benci, Vieri; Horsten, Leon; Wenmackers, Sylvia
We propose an alternative approach to probability theory closely related to the framework of numerosity theory: non-Archimedean probability (NAP). In our approach, unlike in classical probability theory, all subsets of an infinite sample space are measurable and only the empty set gets assigned
Solving fully fuzzy transportation problem using pentagonal fuzzy numbers
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.
A COMPARISON OF TWO FUZZY CLUSTERING TECHNIQUES
Samarjit Das
2013-10-01
Full Text Available - In fuzzy clustering, unlike hard clustering, depending on the membership value, a single object may belong exactly to one cluster or partially to more than one cluster. Out of a number of fuzzy clustering techniques Bezdek’s Fuzzy C-Means and GustafsonKessel clustering techniques are well known where Euclidian distance and Mahalanobis distance are used respectively as a measure of similarity. We have applied these two fuzzy clustering techniques on a dataset of individual differences consisting of fifty feature vectors of dimension (feature three. Based on some validity measures we have tried to see the performances of these two clustering techniques from three different aspects- first, by initializing the membership values of the feature vectors considering the values of the three features separately one at a time, secondly, by changing the number of the predefined clusters and thirdly, by changing the size of the dataset.
Integrating Fuzzy AHP and Fuzzy ARAS for evaluating financial performance
Abdolhamid Safaei Ghadikolaei; Saber Khalili Esbouei
2014-01-01
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 ...
Joseph, Maria L; Carriquiry, Alicia
2010-11-01
Collection of dietary intake information requires time-consuming and expensive methods, making it inaccessible to many resource-poor countries. Quantifying the association between simple measures of usual dietary diversity and usual nutrient intake/adequacy would allow inferences to be made about the adequacy of micronutrient intake at the population level for a fraction of the cost. In this study, we used secondary data from a dietary intake study carried out in Bangladesh to assess the association between 3 food group diversity indicators (FGI) and calcium intake; and the association between these same 3 FGI and a composite measure of nutrient adequacy, mean probability of adequacy (MPA). By implementing Fuller's error-in-the-equation measurement error model (EEM) and simple linear regression (SLR) models, we assessed these associations while accounting for the error in the observed quantities. Significant associations were detected between usual FGI and usual calcium intakes, when the more complex EEM was used. The SLR model detected significant associations between FGI and MPA as well as for variations of these measures, including the best linear unbiased predictor. Through simulation, we support the use of the EEM. In contrast to the EEM, the SLR model does not account for the possible correlation between the measurement errors in the response and predictor. The EEM performs best when the model variables are not complex functions of other variables observed with error (e.g. MPA). When observation days are limited and poor estimates of the within-person variances are obtained, the SLR model tends to be more appropriate.
Smart Spectrometer for Distributed Fuzzy Control
Benoit, Eric; Foulloy, Laurent
2009-01-01
Document rédigé sous FrameMaker (pas sous Latex); International audience; If the main use of colour measurement is the metrology, it is now possible to find industrial control applications which uses this information. Using colour in process control leads to specific problems where human perception has to be replaced by colour sensors. This paper relies on the fuzzy representation of colours that can be taken into account by fuzzy controllers. If smart sensors already include intelligent func...
A Fuzzy Aproach For Facial Emotion Recognition
Gîlcă, Gheorghe; Bîzdoacă, Nicu-George
2015-09-01
This article deals with an emotion recognition system based on the fuzzy sets. Human faces are detected in images with the Viola - Jones algorithm and for its tracking in video sequences we used the Camshift algorithm. The detected human faces are transferred to the decisional fuzzy system, which is based on the variable fuzzyfication measurements of the face: eyebrow, eyelid and mouth. The system can easily determine the emotional state of a person.
Fuzzy Optimization of Option Pricing Model and Its Application in Land Expropriation
Aimin Heng
2014-01-01
Full Text Available Option pricing is irreversible, fuzzy, and flexible. The fuzzy measure which is used for real option pricing is a useful supplement to the traditional real option pricing method. Based on the review of the concepts of the mean and variance of trapezoidal fuzzy number and the combination with the Carlsson-Fuller model, the trapezoidal fuzzy variable can be used to represent the current price of land expropriation and the sale price of land on the option day. Fuzzy Black-Scholes option pricing model can be constructed under fuzzy environment and problems also can be solved and discussed through numerical examples.
Generalized Probability-Probability Plots
Mushkudiani, N.A.; Einmahl, J.H.J.
2004-01-01
We introduce generalized Probability-Probability (P-P) plots in order to study the one-sample goodness-of-fit problem and the two-sample problem, for real valued data.These plots, that are constructed by indexing with the class of closed intervals, globally preserve the properties of classical P-P
Decomposition of fuzzy continuity and fuzzy ideal continuity via fuzzy idealization
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.
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
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...
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.
FUZZY RINGS AND ITS PROPERTIES
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
Application of the fuzzy theory to simulation of batch fermentation
Filev, D P; Kishimoto, M; Sengupta, S; Yoshida, T; Taguchi, H
1985-12-01
A new approach for system identification with a linguistic model of batch fermentation processes is proposed. The fuzzy theory was applied in order to reduce the uncertainty of quantitative description of the processes by use of qualitative characteristics. An example of fuzzy modeling was illustrated in the simulation of batch ethanol production from molasses after interpretation of the new method, and extension of the fuzzy model was also discussed for several cases of different measurable variables.
Earth Data Analysis Center, University of New Mexico — USFS, State Forestry, BLM, and DOI fire occurrence point locations from 1987 to 2008 were combined and converted into a fire occurrence probability or density grid...
Metamathematics of fuzzy logic
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.
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....
Regional SAR Image Segmentation Based on Fuzzy Clustering with Gamma Mixture Model
Li, X. L.; Zhao, Q. H.; Li, Y.
2017-09-01
Most of stochastic based fuzzy clustering algorithms are pixel-based, which can not effectively overcome the inherent speckle noise in SAR images. In order to deal with the problem, a regional SAR image segmentation algorithm based on fuzzy clustering with Gamma mixture model is proposed in this paper. First, initialize some generating points randomly on the image, the image domain is divided into many sub-regions using Voronoi tessellation technique. Each sub-region is regarded as a homogeneous area in which the pixels share the same cluster label. Then, assume the probability of the pixel to be a Gamma mixture model with the parameters respecting to the cluster which the pixel belongs to. The negative logarithm of the probability represents the dissimilarity measure between the pixel and the cluster. The regional dissimilarity measure of one sub-region is defined as the sum of the measures of pixels in the region. Furthermore, the Markov Random Field (MRF) model is extended from pixels level to Voronoi sub-regions, and then the regional objective function is established under the framework of fuzzy clustering. The optimal segmentation results can be obtained by the solution of model parameters and generating points. Finally, the effectiveness of the proposed algorithm can be proved by the qualitative and quantitative analysis from the segmentation results of the simulated and real SAR images.
Ash, Robert B; Lukacs, E
1972-01-01
Real Analysis and Probability provides the background in real analysis needed for the study of probability. Topics covered range from measure and integration theory to functional analysis and basic concepts of probability. The interplay between measure theory and topology is also discussed, along with conditional probability and expectation, the central limit theorem, and strong laws of large numbers with respect to martingale theory.Comprised of eight chapters, this volume begins with an overview of the basic concepts of the theory of measure and integration, followed by a presentation of var
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.
Fuzzy control and identification
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.
FUZZY ACCEPTANCE SAMPLING AND CHARACTERISTIC CURVES
Ebru Turano?lu
2012-02-01
Full Text Available Acceptance sampling is primarily used for the inspection of incoming or outgoing lots. Acceptance sampling refers to the application of specific sampling plans to a designated lot or sequence of lots. The parameters of acceptance sampling plans are sample sizes and acceptance numbers. In some cases, it may not be possible to define acceptance sampling parameters as crisp values. These parameters can be expressed by linguistic variables. The fuzzy set theory can be successfully used to cope with the vagueness in these linguistic expressions for acceptance sampling. In this paper, the main distributions of acceptance sampling plans are handled with fuzzy parameters and their acceptance probability functions are derived. Then the characteristic curves of acceptance sampling are examined under fuzziness. Illustrative examples are given.
Bayesian image processing of data from fuzzy pattern sources
Liang, Z.; Hart, H.
1986-01-01
In some radioisotopic organ image applications, a priori or supplementary source information may exist and can be characterized in terms of probability density functions P (phi) of the source elements {phi/sub j/} = phi (where phi/sub j/ (j = 1,2,..α) is the estimated average photon emission in voxel j per unit time at t = 0). For example, in cardiac imaging studies it is possible to evaluate the radioisotope concentration of the blood filling the cardiac chambers independently as a function of time by peripheral measurement. The blood concentration information in effect serves to limit amplitude uncertainty to the chamber boundary voxels and thus reduces the extent of amplitude ambiguities in the overall cardiac imaging reconstruction. The a priori or supplementary information may more generally be spatial, amplitude-dependent probability distributions P(phi), fuzzy patterns superimposed upon a background
A fuzzy neural network for sensor signal estimation
Na, Man Gyun
2000-01-01
In this work, a fuzzy neural network is used to estimate the relevant sensor signal using other sensor signals. Noise components in input signals into the fuzzy neural network are removed through the wavelet denoising technique. Principal component analysis (PCA) is used to reduce the dimension of an input space without losing a significant amount of information. A lower dimensional input space will also usually reduce the time necessary to train a fuzzy-neural network. Also, the principal component analysis makes easy the selection of the input signals into the fuzzy neural network. The fuzzy neural network parameters are optimized by two learning methods. A genetic algorithm is used to optimize the antecedent parameters of the fuzzy neural network and a least-squares algorithm is used to solve the consequent parameters. The proposed algorithm was verified through the application to the pressurizer water level and the hot-leg flowrate measurements in pressurized water reactors
On logical, algebraic, and probabilistic aspects of fuzzy set theory
Mesiar, Radko
2016-01-01
The book is a collection of contributions by leading experts, developed around traditional themes discussed at the annual Linz Seminars on Fuzzy Set Theory. The different chapters have been written by former PhD students, colleagues, co-authors and friends of Peter Klement, a leading researcher and the organizer of the Linz Seminars on Fuzzy Set Theory. The book also includes advanced findings on topics inspired by Klement’s research activities, concerning copulas, measures and integrals, as well as aggregation problems. Some of the chapters reflect personal views and controversial aspects of traditional topics, while others deal with deep mathematical theories, such as the algebraic and logical foundations of fuzzy set theory and fuzzy logic. Originally thought as an homage to Peter Klement, the book also represents an advanced reference guide to the mathematical theories related to fuzzy logic and fuzzy set theory with the potential to stimulate important discussions on new research directions in the fiel...
Quantum Probabilities as Behavioral Probabilities
Vyacheslav I. Yukalov
2017-03-01
Full Text Available We demonstrate that behavioral probabilities of human decision makers share many common features with quantum probabilities. This does not imply that humans are some quantum objects, but just shows that the mathematics of quantum theory is applicable to the description of human decision making. The applicability of quantum rules for describing decision making is connected with the nontrivial process of making decisions in the case of composite prospects under uncertainty. Such a process involves deliberations of a decision maker when making a choice. In addition to the evaluation of the utilities of considered prospects, real decision makers also appreciate their respective attractiveness. Therefore, human choice is not based solely on the utility of prospects, but includes the necessity of resolving the utility-attraction duality. In order to justify that human consciousness really functions similarly to the rules of quantum theory, we develop an approach defining human behavioral probabilities as the probabilities determined by quantum rules. We show that quantum behavioral probabilities of humans do not merely explain qualitatively how human decisions are made, but they predict quantitative values of the behavioral probabilities. Analyzing a large set of empirical data, we find good quantitative agreement between theoretical predictions and observed experimental data.
Portfolio Selection Based on Distance between Fuzzy Variables
Weiyi Qian
2014-01-01
Full Text Available This paper researches portfolio selection problem in fuzzy environment. We introduce a new simple method in which the distance between fuzzy variables is used to measure the divergence of fuzzy investment return from a prior one. Firstly, two new mathematical models are proposed by expressing divergence as distance, investment return as expected value, and risk as variance and semivariance, respectively. Secondly, the crisp forms of the new models are also provided for different types of fuzzy variables. Finally, several numerical examples are given to illustrate the effectiveness of the proposed approach.
Rojas-Nandayapa, Leonardo
Tail probabilities of sums of heavy-tailed random variables are of a major importance in various branches of Applied Probability, such as Risk Theory, Queueing Theory, Financial Management, and are subject to intense research nowadays. To understand their relevance one just needs to think...... analytic expression for the distribution function of a sum of random variables. The presence of heavy-tailed random variables complicates the problem even more. The objective of this dissertation is to provide better approximations by means of sharp asymptotic expressions and Monte Carlo estimators...
Toward a generalized probability theory: conditional probabilities
Cassinelli, G.
1979-01-01
The main mathematical object of interest in the quantum logic approach to the foundations of quantum mechanics is the orthomodular lattice and a set of probability measures, or states, defined by the lattice. This mathematical structure is studied per se, independently from the intuitive or physical motivation of its definition, as a generalized probability theory. It is thought that the building-up of such a probability theory could eventually throw light on the mathematical structure of Hilbert-space quantum mechanics as a particular concrete model of the generalized theory. (Auth.)
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.
On Intuitionistic Fuzzy Filters of Intuitionistic Fuzzy Coframes
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.
Properties of Bipolar Fuzzy Hypergraphs
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.
Cheap diagnosis using structural modelling and fuzzy-logic based detection
Izadi-Zamanabadi, Roozbeh; Blanke, Mogens; Katebi, Serajeddin
2003-01-01
relations for linear or non-linear dynamic behaviour, and combine this with fuzzy output observer design to provide an effective diagnostic approach. An adaptive neuro-fuzzy inference method is used. A fuzzy adaptive threshold is employed to cope with practical uncertainty. The methods are demonstrated...... using measurements on a ship propulsion system subject to simulated faults....
Generalized coherent state approach to star products and applications to the fuzzy sphere
Alexanian, G.; Pinzul, A.; Stern, A.
2001-01-01
We construct a star product associated with an arbitrary two-dimensional Poisson structure using generalized coherent states on the complex plane. From our approach one easily recovers the star product for the fuzzy torus, and also one for the fuzzy sphere. For the latter we need to define the 'fuzzy' stereographic projection to the plane and the fuzzy sphere integration measure, which in the commutative limit reduce to the usual formulae for the sphere
Fraassen, B.C. van
1979-01-01
The interpretation of probabilities in physical theories are considered, whether quantum or classical. The following points are discussed 1) the functions P(μ, Q) in terms of which states and propositions can be represented, are classical (Kolmogoroff) probabilities, formally speaking, 2) these probabilities are generally interpreted as themselves conditional, and the conditions are mutually incompatible where the observables are maximal and 3) testing of the theory typically takes the form of confronting the expectation values of observable Q calculated with probability measures P(μ, Q) for states μ; hence, of comparing the probabilities P(μ, Q)(E) with the frequencies of occurrence of the corresponding events. It seems that even the interpretation of quantum mechanics, in so far as it concerns what the theory says about the empirical (i.e. actual, observable) phenomena, deals with the confrontation of classical probability measures with observable frequencies. This confrontation is studied. (Auth./C.F.)
Shah, M.L.; Sahoo, A.C.; Pulhani, A.K.; Gupta, G.P.; Dikshit, B.; Bhatia, M.S.; Suri, B.M.
2014-01-01
Laser-induced photoionization and fluorescence signals were simultaneously observed in atomic samarium using Nd:YAG-pumped dye lasers. Two-color, three-photon photoionization and two-color fluorescence signals were recorded simultaneously as a function of the second-step laser power for two photoionization pathways. The density matrix formalism has been employed to analyze these signals. Two-color laser-induced fluorescence signal depends on the laser powers used for the first and second-step transitions as well as the first and second-step transition probability whereas two-color, three-photon photoionization signal depends on the third-step transition cross-section at the second-step laser wavelength along with the laser powers and transition probability for the first and second-step transitions. Two-color laser-induced fluorescence was used to measure the second-step transition probability. The second-step transition probability obtained was used to infer the photoionization cross-section. Thus, the methodology combining two-color, three-photon photoionization and two-color fluorescence signals in a single experiment has been established for the first time to measure the second-step transition probability as well as the photoionization cross-section. - Highlights: • Laser-induced photoionization and fluorescence signals have been simultaneously observed. • The density matrix formalism has been employed to analyze these signals. • Two-color laser-induced fluorescence was used to measure the second-step transition probability. • The second-step transition probability obtained was used to infer the photoionization cross-section. • Transition probability and photoionization cross-section have been measured in a single experiment
SIMULATION OF DRIVER’S LOCOMOTIVE-HANDLING ACTIVITY USING THE THEORY OF FUZZY GRAPHS
T. V. Butko
2015-03-01
Full Text Available Purpose. The efficiency and safety of locomotive control improving is important and relevant scientific and practical problem. Every driver during the trains-handling bases on his experience and knowledge, that is why the compilation and detection the most efficient ways to control the locomotive-handling is one of the stages of measures development to reduce transportation costs. The purpose of this paper is a formalization process description of locomotive-handling and quality parameters determination of this process. Methodology. In order to achieve this goal the theory of fuzzy probabilistic graphs was used. Vertices of the graph correspond to the events start and end operations at train-handling. The graph arcs describe operations on train-handling. Graph consists of thirteen peaks corresponding to the main control actions of the engine-driver. The weighting factors of transitions between vertices are assigned by fuzzy numbers. Their values were obtained by expert estimates. Fuzzy probabilities and transition time are presented as numbers with trapezoidal membership function. Findings. Using successive merging of parallel arcs, loops and vertices elimination, the equivalent fuzzy graph of train-handling and the corresponding L-matrix were obtained. Equivalent graph takes into account separately activity of the driver during normal operation and during emergency situations. Originality. The theoretical foundations of describing process formalization in driver’s locomotive-handling activity were developed using the fuzzy probabilistic graph. The parameters characterizing the decision-making process of engineer were obtained. Practical value. With the resulting model it is possible to estimate the available reserves for the quality improvement of locomotive-handling. Reduction in the time for decision-making will lead to the approximation the current mode of control to the rational one and decrease costs of hauling operations. And reduction
Grinstead, Charles M; Snell, J Laurie
2011-01-01
This book explores four real-world topics through the lens of probability theory. It can be used to supplement a standard text in probability or statistics. Most elementary textbooks present the basic theory and then illustrate the ideas with some neatly packaged examples. Here the authors assume that the reader has seen, or is learning, the basic theory from another book and concentrate in some depth on the following topics: streaks, the stock market, lotteries, and fingerprints. This extended format allows the authors to present multiple approaches to problems and to pursue promising side discussions in ways that would not be possible in a book constrained to cover a fixed set of topics. To keep the main narrative accessible, the authors have placed the more technical mathematical details in appendices. The appendices can be understood by someone who has taken one or two semesters of calculus.
Dorogovtsev, A Ya; Skorokhod, A V; Silvestrov, D S; Skorokhod, A V
1997-01-01
This book of problems is intended for students in pure and applied mathematics. There are problems in traditional areas of probability theory and problems in the theory of stochastic processes, which has wide applications in the theory of automatic control, queuing and reliability theories, and in many other modern science and engineering fields. Answers to most of the problems are given, and the book provides hints and solutions for more complicated problems.
Clinical effect of fuzzy numbers based on center of gravity
Jane
2011-10-05
Oct 5, 2011 ... In this study, a model called “fuzzy reasoning model” was proposed for ... variables were crisp and the value of the binary response variable ... research, to measure the severity of disease or pain in .... Thus, for a new fuzzy case, our model can predict its possibilistic ..... by Comparing Membership Functions.
New similarity of triangular fuzzy number and its application.
Zhang, Xixiang; Ma, Weimin; Chen, Liping
2014-01-01
The similarity of triangular fuzzy numbers is an important metric for application of it. There exist several approaches to measure similarity of triangular fuzzy numbers. However, some of them are opt to be large. To make the similarity well distributed, a new method SIAM (Shape's Indifferent Area and Midpoint) to measure triangular fuzzy number is put forward, which takes the shape's indifferent area and midpoint of two triangular fuzzy numbers into consideration. Comparison with other similarity measurements shows the effectiveness of the proposed method. Then, it is applied to collaborative filtering recommendation to measure users' similarity. A collaborative filtering case is used to illustrate users' similarity based on cloud model and triangular fuzzy number; the result indicates that users' similarity based on triangular fuzzy number can obtain better discrimination. Finally, a simulated collaborative filtering recommendation system is developed which uses cloud model and triangular fuzzy number to express users' comprehensive evaluation on items, and result shows that the accuracy of collaborative filtering recommendation based on triangular fuzzy number is higher.
Value-at-risk estimation with fuzzy histograms
Almeida, R.J.; Kaymak, U.
2008-01-01
Value at risk (VaR) is a measure for senior management that summarises the financial risk a company faces into one single number. In this paper, we consider the use of fuzzy histograms for quantifying the value-at-risk of a portfolio. It is shown that the use of fuzzy histograms provides a good
Construction of fuzzy automata by fuzzy experiments
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
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.
Stockall, Linnaea; Stringfellow, Andrew; Marantz, Alec
2004-01-01
Visually presented letter strings consistently yield three MEG response components: the M170, associated with letter-string processing (Tarkiainen, Helenius, Hansen, Cornelissen, & Salmelin, 1999); the M250, affected by phonotactic probability, (Pylkkanen, Stringfellow, & Marantz, 2002); and the M350, responsive to lexical frequency (Embick,…
Model predictive control using fuzzy decision functions
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 fuzzy logic decision support system for assessing clinical nutritional risk
Ali Mohammad Hadianfard
2015-04-01
Full Text Available Introduction: Studies have indicated a global high prevalence of hospital malnutrition on admission and during hospitalization. Clinical Nutritional Risk Screen (CNRS is a way to identify malnutrition and manage nutritional interventions. Several traditional and non-computer based tools have been suggested for screening nutritional risk levels. The present study was an attempt to employ a computer based fuzzy model decision support system as a nutrition-screening tool for inpatients. Method: This is an applied modeling study. The system architecture was designed based on the fuzzy logic model including input data, inference engine, and output. A clinical nutritionist entered nineteen input variables using a windows-based graphical user interface. The inference engine was involved with knowledge obtained from literature and the construction of ‘IF-THEN’ rules. The output of the system was stratification of patients into four risk levels from ‘No’ to ‘High’ where a number was also allocated to them as a nutritional risk grade. All patients (121 people admitted during implementing the system participated in testing the model. The classification tests were used to measure the CNRS fuzzy model performance. IBM SPSS version 21 was utilized as a tool for data analysis with α = 0.05 as a significance level. Results: Results showed that sensitivity, specificity, accuracy, and precision of the fuzzy model performance were 91.67% (±4.92, 76% (±7.6, 88.43% (±5.7, and 93.62% (±4.32, respectively. Instant performance on admission and very low probability of mistake in predicting malnutrition risk level may justify using the model in hospitals. Conclusion: To conclude, the fuzzy model-screening tool is based on multiple nutritional risk factors, having the capability of classifying inpatients into several nutritional risk levels and identifying the level of required nutritional intervention.
Approximations of Fuzzy Systems
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
Quality Improvement of Liver Ultrasound Images Using Fuzzy Techniques.
Bayani, Azadeh; Langarizadeh, Mostafa; Radmard, Amir Reza; Nejad, Ahmadreza Farzaneh
2016-12-01
Liver ultrasound images are so common and are applied so often to diagnose diffuse liver diseases like fatty liver. However, the low quality of such images makes it difficult to analyze them and diagnose diseases. The purpose of this study, therefore, is to improve the contrast and quality of liver ultrasound images. In this study, a number of image contrast enhancement algorithms which are based on fuzzy logic were applied to liver ultrasound images - in which the view of kidney is observable - using Matlab2013b to improve the image contrast and quality which has a fuzzy definition; just like image contrast improvement algorithms using a fuzzy intensification operator, contrast improvement algorithms applying fuzzy image histogram hyperbolization, and contrast improvement algorithms by fuzzy IF-THEN rules. With the measurement of Mean Squared Error and Peak Signal to Noise Ratio obtained from different images, fuzzy methods provided better results, and their implementation - compared with histogram equalization method - led both to the improvement of contrast and visual quality of images and to the improvement of liver segmentation algorithms results in images. Comparison of the four algorithms revealed the power of fuzzy logic in improving image contrast compared with traditional image processing algorithms. Moreover, contrast improvement algorithm based on a fuzzy intensification operator was selected as the strongest algorithm considering the measured indicators. This method can also be used in future studies on other ultrasound images for quality improvement and other image processing and analysis applications.
Fuzzy Rough Ring and Its Prop erties
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.
Weidman, Aaron C; Steckler, Conor M; Tracy, Jessica L
2017-03-01
Although affective science has seen an explosion of interest in measuring subjectively experienced distinct emotional states, most existing self-report measures tap broad affect dimensions and dispositional emotional tendencies, rather than momentary distinct emotions. This raises the question of how emotion researchers are measuring momentary distinct emotions in their studies. To address this question, we reviewed the self-report measurement practices regularly used for the purpose of assessing momentary distinct emotions, by coding these practices as observed in a representative sample of articles published in Emotion from 2001-2011 (n = 467 articles; 751 studies; 356 measurement instances). This quantitative review produced several noteworthy findings. First, researchers assess many purportedly distinct emotions (n = 65), a number that differs substantially from previously developed emotion taxonomies. Second, researchers frequently use scales that were not systematically developed, and that include items also used to measure at least 1 other emotion on a separate scale in a separate study. Third, the majority of scales used include only a single item, and had unknown reliability. Together, these tactics may create ambiguity regarding which emotions are being measured in empirical studies, and conceptual inconsistency among measures of purportedly identical emotions across studies. We discuss the implications of these problematic practices, and conclude with recommendations for how the field might improve the way it measures emotions. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
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.
Fuzzy stochastic multiobjective programming
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.
FUZZY BASED CONTRAST STRETCHING FOR MEDICAL IMAGE ENHANCEMENT
T.C. Raja Kumar
2011-07-01
Full Text Available Contrast Stretching is an important part in medical image processing applications. Contrast is the difference between two adjacent pixels. Fuzzy statistical values are analyzed and better results are produced in the spatial domain of the input image. The histogram mapping produces the resultant image with less impulsive noise and smooth nature. The probabilities of gray values are generated and the fuzzy set is determined from the position of the input image pixel. The result indicates the good performance of the proposed fuzzy based stretching. The inverse transform of the real values are mapped with the input image to generate the fuzzy statistics. This approach gives a flexible image enhancement for medical images in the presence of noises.
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 forecasting based on fuzzy-trend logical relationship groups.
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.
Jiang, Wen; Wei, Boya
2018-02-01
The theory of intuitionistic fuzzy sets (IFS) is widely used for dealing with vagueness and the Dempster-Shafer (D-S) evidence theory has a widespread use in multiple criteria decision-making problems under uncertain situation. However, there are many methods to aggregate intuitionistic fuzzy numbers (IFNs), but the aggregation operator to fuse basic probability assignment (BPA) is rare. Power average (P-A) operator, as a powerful operator, is useful and important in information fusion. Motivated by the idea of P-A power, in this paper, a new operator based on the IFS and D-S evidence theory is proposed, which is named as intuitionistic fuzzy evidential power average (IFEPA) aggregation operator. First, an IFN is converted into a BPA, and the uncertainty is measured in D-S evidence theory. Second, the difference between BPAs is measured by Jousselme distance and a satisfying support function is proposed to get the support degree between each other effectively. Then the IFEPA operator is used for aggregating the original IFN and make a more reasonable decision. The proposed method is objective and reasonable because it is completely driven by data once some parameters are required. At the same time, it is novel and interesting. Finally, an application of developed models to the 'One Belt, One road' investment decision-making problems is presented to illustrate the effectiveness and feasibility of the proposed operator.
Analytical fuzzy approach to biological data analysis
Weiping Zhang
2017-03-01
Full Text Available The assessment of the physiological state of an individual requires an objective evaluation of biological data while taking into account both measurement noise and uncertainties arising from individual factors. We suggest to represent multi-dimensional medical data by means of an optimal fuzzy membership function. A carefully designed data model is introduced in a completely deterministic framework where uncertain variables are characterized by fuzzy membership functions. The study derives the analytical expressions of fuzzy membership functions on variables of the multivariate data model by maximizing the over-uncertainties-averaged-log-membership values of data samples around an initial guess. The analytical solution lends itself to a practical modeling algorithm facilitating the data classification. The experiments performed on the heartbeat interval data of 20 subjects verified that the proposed method is competing alternative to typically used pattern recognition and machine learning algorithms.
Fuzzy spheres from inequivalent coherent states quantizations
Gazeau, Jean Pierre; Huguet, Eric; Lachieze-Rey, Marc; Renaud, Jacques
2007-01-01
The existence of a family of coherent states (CS) solving the identity in a Hilbert space allows, under certain conditions, to quantize functions defined on the measure space of CS parameters. The application of this procedure to the 2-sphere provides a family of inequivalent CS quantizations based on the spin spherical harmonics (the CS quantization from usual spherical harmonics appears to give a trivial issue for the Cartesian coordinates). We compare these CS quantizations to the usual (Madore) construction of the fuzzy sphere. Due to these differences, our procedure yields new types of fuzzy spheres. Moreover, the general applicability of CS quantization suggests similar constructions of fuzzy versions of a large variety of sets
Operational budgeting using fuzzy goal programming
Saeed Mohammadi
2013-10-01
Full Text Available Having an efficient budget normally has different advantages such as measuring the performance of various organizations, setting appropriate targets and promoting managers based on their achievements. However, any budgeting planning requires prediction of different cost components. There are various methods for budgeting planning such as incremental budgeting, program budgeting, zero based budgeting and performance budgeting. In this paper, we present a fuzzy goal programming to estimate operational budget. The proposed model uses fuzzy triangular as well as interval number to estimate budgeting expenses. The proposed study of this paper is implemented for a real-world case study in province of Qom, Iran and the results are analyzed.
Shorack, Galen R
2017-01-01
This 2nd edition textbook offers a rigorous introduction to measure theoretic probability with particular attention to topics of interest to mathematical statisticians—a textbook for courses in probability for students in mathematical statistics. It is recommended to anyone interested in the probability underlying modern statistics, providing a solid grounding in the probabilistic tools and techniques necessary to do theoretical research in statistics. For the teaching of probability theory to post graduate statistics students, this is one of the most attractive books available. Of particular interest is a presentation of the major central limit theorems via Stein's method either prior to or alternative to a characteristic function presentation. Additionally, there is considerable emphasis placed on the quantile function as well as the distribution function. The bootstrap and trimming are both presented. Martingale coverage includes coverage of censored data martingales. The text includes measure theoretic...
Analysis of event tree with imprecise inputs by fuzzy set theory
Ahn, Kwang Il; Chun, Moon Hyun
1990-01-01
Fuzzy set theory approach is proposed as a method to analyze event trees with imprecise or linguistic input variables such as 'likely' or 'improbable' instead of the numerical probability. In this paper, it is shown how the fuzzy set theory can be applied to the event tree analysis. The result of this study shows that the fuzzy set theory approach can be applied as an acceptable and effective tool for analysis of the event tree with fuzzy type of inputs. Comparisons of the fuzzy theory approach with the probabilistic approach of computing probabilities of final states of the event tree through subjective weighting factors and LHS technique show that the two approaches have common factors and give reasonable results
Shapley's value for fuzzy games
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.
Chen, Xiao; Li, Yaan; Yu, Jing; Li, Yuxing
2018-01-01
For fast and more effective implementation of tracking multiple targets in a cluttered environment, we propose a multiple targets tracking (MTT) algorithm called maximum entropy fuzzy c-means clustering joint probabilistic data association that combines fuzzy c-means clustering and the joint probabilistic data association (PDA) algorithm. The algorithm uses the membership value to express the probability of the target originating from measurement. The membership value is obtained through fuzzy c-means clustering objective function optimized by the maximum entropy principle. When considering the effect of the public measurement, we use a correction factor to adjust the association probability matrix to estimate the state of the target. As this algorithm avoids confirmation matrix splitting, it can solve the high computational load problem of the joint PDA algorithm. The results of simulations and analysis conducted for tracking neighbor parallel targets and cross targets in a different density cluttered environment show that the proposed algorithm can realize MTT quickly and efficiently in a cluttered environment. Further, the performance of the proposed algorithm remains constant with increasing process noise variance. The proposed algorithm has the advantages of efficiency and low computational load, which can ensure optimum performance when tracking multiple targets in a dense cluttered environment.
Keller, James M; Fogel, David B
2016-01-01
This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary computation. The text focuses on inspiration, design, theory, and practical aspects of implementing procedures to solve real-world problems. While other books in the three fields that comprise computational intelligence are written by specialists in one discipline, this book is co-written by current former Editor-in-Chief of IEEE Transactions on Neural Networks and Learning Systems, a former Editor-in-Chief of IEEE Transactions on Fuzzy Systems, and the founding Editor-in-Chief of IEEE Transactions on Evolutionary Computation. The coverage across the three topics is both uniform and consistent in style and notation. Discusses single-layer and multilayer neural networks, radial-basi function networks, and recurrent neural networks Covers fuzzy set theory, fuzzy relations, fuzzy logic interference, fuzzy clustering and classification, fuzzy measures and fuzz...
CHARACTERIZATIONS OF FUZZY SOFT PRE SEPARATION AXIOMS
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...
Bimodal fuzzy analytic hierarchy process (BFAHP) for coronary heart disease risk assessment.
Sabahi, Farnaz
2018-04-04
Rooted deeply in medical multiple criteria decision-making (MCDM), risk assessment is very important especially when applied to the risk of being affected by deadly diseases such as coronary heart disease (CHD). CHD risk assessment is a stochastic, uncertain, and highly dynamic process influenced by various known and unknown variables. In recent years, there has been a great interest in fuzzy analytic hierarchy process (FAHP), a popular methodology for dealing with uncertainty in MCDM. This paper proposes a new FAHP, bimodal fuzzy analytic hierarchy process (BFAHP) that augments two aspects of knowledge, probability and validity, to fuzzy numbers to better deal with uncertainty. In BFAHP, fuzzy validity is computed by aggregating the validities of relevant risk factors based on expert knowledge and collective intelligence. By considering both soft and statistical data, we compute the fuzzy probability of risk factors using the Bayesian formulation. In BFAHP approach, these fuzzy validities and fuzzy probabilities are used to construct a reciprocal comparison matrix. We then aggregate fuzzy probabilities and fuzzy validities in a pairwise manner for each risk factor and each alternative. BFAHP decides about being affected and not being affected by ranking of high and low risks. For evaluation, the proposed approach is applied to the risk of being affected by CHD using a real dataset of 152 patients of Iranian hospitals. Simulation results confirm that adding validity in a fuzzy manner can accrue more confidence of results and clinically useful especially in the face of incomplete information when compared with actual results. Applying the proposed BFAHP on CHD risk assessment of the dataset, it yields high accuracy rate above 85% for correct prediction. In addition, this paper recognizes that the risk factors of diastolic blood pressure in men and high-density lipoprotein in women are more important in CHD than other risk factors. Copyright © 2018 Elsevier Inc. All
Determination of interrill soil erodibility coefficient based on Fuzzy and Fuzzy-Genetic Systems
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
Probability of identification: adulteration of American Ginseng with Asian Ginseng.
Harnly, James; Chen, Pei; Harrington, Peter De B
2013-01-01
The AOAC INTERNATIONAL guidelines for validation of botanical identification methods were applied to the detection of Asian Ginseng [Panax ginseng (PG)] as an adulterant for American Ginseng [P. quinquefolius (PQ)] using spectral fingerprints obtained by flow injection mass spectrometry (FIMS). Samples of 100% PQ and 100% PG were physically mixed to provide 90, 80, and 50% PQ. The multivariate FIMS fingerprint data were analyzed using soft independent modeling of class analogy (SIMCA) based on 100% PQ. The Q statistic, a measure of the degree of non-fit of the test samples with the calibration model, was used as the analytical parameter. FIMS was able to discriminate between 100% PQ and 100% PG, and between 100% PQ and 90, 80, and 50% PQ. The probability of identification (POI) curve was estimated based on the SD of 90% PQ. A digital model of adulteration, obtained by mathematically summing the experimentally acquired spectra of 100% PQ and 100% PG in the desired ratios, agreed well with the physical data and provided an easy and more accurate method for constructing the POI curve. Two chemometric modeling methods, SIMCA and fuzzy optimal associative memories, and two classification methods, partial least squares-discriminant analysis and fuzzy rule-building expert systems, were applied to the data. The modeling methods correctly identified the adulterated samples; the classification methods did not.
A neural fuzzy controller learning by fuzzy error propagation
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.
Fuzzy logic model to quantify risk perception
Bukh, Julia; Dickstein, Phineas
2008-01-01
The aim of this study is a quantification of public risk perception towards the nuclear field so as to be considered in decision making whenever the public involvement is sought. The proposed model includes both qualitative factors such as familiarity and voluntariness and numerical factors influencing risk perception, such as probability of occurrence and severity of consequence. Since part of these factors can be characterized only by qualitative expressions and the determination of them are linked with vagueness, imprecision and uncertainty, the most suitable method for the risk level assessment is Fuzzy Logic, which models qualitative aspects of knowledge and reasoning processes without employing precise quantitative analyses. This work, then, offers a Fuzzy-Logic based mean of representing the risk perception by a single numerical feature, which can be weighted and accounted for in decision making procedures. (author)
Identification of different geologic units using fuzzy constrained resistivity tomography
Singh, Anand; Sharma, S. P.
2018-01-01
Different geophysical inversion strategies are utilized as a component of an interpretation process that tries to separate geologic units based on the resistivity distribution. In the present study, we present the results of separating different geologic units using fuzzy constrained resistivity tomography. This was accomplished using fuzzy c means, a clustering procedure to improve the 2D resistivity image and geologic separation within the iterative minimization through inversion. First, we developed a Matlab-based inversion technique to obtain a reliable resistivity image using different geophysical data sets (electrical resistivity and electromagnetic data). Following this, the recovered resistivity model was converted into a fuzzy constrained resistivity model by assigning the highest probability value of each model cell to the cluster utilizing fuzzy c means clustering procedure during the iterative process. The efficacy of the algorithm is demonstrated using three synthetic plane wave electromagnetic data sets and one electrical resistivity field dataset. The presented approach shows improvement on the conventional inversion approach to differentiate between different geologic units if the correct number of geologic units will be identified. Further, fuzzy constrained resistivity tomography was performed to examine the augmentation of uranium mineralization in the Beldih open cast mine as a case study. We also compared geologic units identified by fuzzy constrained resistivity tomography with geologic units interpreted from the borehole information.
Probability and Bayesian statistics
1987-01-01
This book contains selected and refereed contributions to the "Inter national Symposium on Probability and Bayesian Statistics" which was orga nized to celebrate the 80th birthday of Professor Bruno de Finetti at his birthplace Innsbruck in Austria. Since Professor de Finetti died in 1985 the symposium was dedicated to the memory of Bruno de Finetti and took place at Igls near Innsbruck from 23 to 26 September 1986. Some of the pa pers are published especially by the relationship to Bruno de Finetti's scientific work. The evolution of stochastics shows growing importance of probability as coherent assessment of numerical values as degrees of believe in certain events. This is the basis for Bayesian inference in the sense of modern statistics. The contributions in this volume cover a broad spectrum ranging from foundations of probability across psychological aspects of formulating sub jective probability statements, abstract measure theoretical considerations, contributions to theoretical statistics an...
The foundations of fuzzy control
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.
А. М. Невиніцин
2000-12-01
Full Text Available The paper deals with the problem of definition of optimal and ultimate-acceptable interruptions in training for operations in emergency cases of flight. The theory of fuzzy sets is applied for this purpose and built are belonging functions of a linguistic variable "professional preparation level". For the 1st, 2nd and 3rd classes of air traffic controllers the optimal and ultimate-acceptable interruptions in learning are determined depending on the type of emergency case of flight
SOS based robust H(∞) fuzzy dynamic output feedback control of nonlinear networked control systems.
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.
Abbas Parchami
2016-09-01
Full Text Available Such as other statistical problems, we may confront with uncertain and fuzzy concepts in quality control. One particular case in process capability analysis is a situation in which specification limits are two fuzzy sets. In such a uncertain and vague environment, the produced product is not qualified with a two-valued Boolean view, but to some degree depending on the decision-maker strictness and the quality level of the produced product. This matter can be cause to a rational decision-making on the quality of the production line. First, a comprehensive approach is presented in this paper for modeling the fuzzy quality concept. Then, motivations and advantages of applying this flexible approach instead of using classical quality are mentioned.
Dipak Kumar Jana
2017-06-01
Full Text Available In real world applications supply, demand and transportation costs per unit of the quantities in multi-objective transportation problems may be hardly specified accurately because of the changing economic and environmental conditions. It is also significant that the time required for transportation should be minimized. In this paper, we have presented three reduction methods for a type-2 triangular fuzzy variable (T2TrFV by adopting the critical value (CV. Three generalized expected values (optimistic, CV and pessimistic are derived for T2TrFVs with some special cases. Then a multi-objective profit transportation problem (MOPTP with fixed charge (FC cost has been formulated and solved in type-2 fuzzy environment. Unit transportation costs, FC, selling prices, unit transport times, loading and unloading times, total supply capacities and demands are all considered as triangular Type-2 fuzzy numbers. The MOPTP has been converted into a single objective by using the goal programming technique and the weighted sum method. The deterministic model is then solved using the Generalized Reduced Gradient method Lingo 14.0. Numerical experiments with some sensitivity analysis are illustrated the application and effectiveness of the proposed approaches.
Lugtig, Peter; Toepoel, Vera
2016-01-01
Respondents in an Internet panel survey can often choose which device they use to complete questionnaires: a traditional PC, laptop, tablet computer, or a smartphone. Because all these devices have different screen sizes and modes of data entry, measurement errors may differ between devices. Using
Properties of Risk Measures of Generalized Entropy in Portfolio Selection
Rongxi Zhou
2017-12-01
Full Text Available This paper systematically investigates the properties of six kinds of entropy-based risk measures: Information Entropy and Cumulative Residual Entropy in the probability space, Fuzzy Entropy, Credibility Entropy and Sine Entropy in the fuzzy space, and Hybrid Entropy in the hybridized uncertainty of both fuzziness and randomness. We discover that none of the risk measures satisfy all six of the following properties, which various scholars have associated with effective risk measures: Monotonicity, Translation Invariance, Sub-additivity, Positive Homogeneity, Consistency and Convexity. Measures based on Fuzzy Entropy, Credibility Entropy, and Sine Entropy all exhibit the same properties: Sub-additivity, Positive Homogeneity, Consistency, and Convexity. These measures based on Information Entropy and Hybrid Entropy, meanwhile, only exhibit Sub-additivity and Consistency. Cumulative Residual Entropy satisfies just Sub-additivity, Positive Homogeneity, and Convexity. After identifying these properties, we develop seven portfolio models based on different risk measures and made empirical comparisons using samples from both the Shenzhen Stock Exchange of China and the New York Stock Exchange of America. The comparisons show that the Mean Fuzzy Entropy Model performs the best among the seven models with respect to both daily returns and relative cumulative returns. Overall, these results could provide an important reference for both constructing effective risk measures and rationally selecting the appropriate risk measure under different portfolio selection conditions.
Dasgupta, Arunima; Sastry, K. L. N.; Dhinwa, P. S.; Rathore, V. S.; Nathawat, M. S.
2013-08-01
Desertification risk assessment is important in order to take proper measures for its prevention. Present research intends to identify the areas under risk of desertification along with their severity in terms of degradation in natural parameters. An integrated model with fuzzy membership analysis, fuzzy rule-based inference system and geospatial techniques was adopted, including five specific natural parameters namely slope, soil pH, soil depth, soil texture and NDVI. Individual parameters were classified according to their deviation from mean. Membership of each individual values to be in a certain class was derived using the normal probability density function of that class. Thus if a single class of a single parameter is with mean μ and standard deviation σ, the values falling beyond μ + 2 σ and μ - 2 σ are not representing that class, but a transitional zone between two subsequent classes. These are the most important areas in terms of degradation, as they have the lowest probability to be in a certain class, hence highest probability to be extended or narrowed down in next or previous class respectively. Eventually, these are the values which can be easily altered, under extrogenic influences, hence are identified as risk areas. The overall desertification risk is derived by incorporating the different risk severity of each parameter using fuzzy rule-based interference system in GIS environment. Multicriteria based geo-statistics are applied to locate the areas under different severity of desertification risk. The study revealed that in Kota, various anthropogenic pressures are accelerating land deterioration, coupled with natural erosive forces. Four major sources of desertification in Kota are, namely Gully and Ravine erosion, inappropriate mining practices, growing urbanization and random deforestation.
Heide, L; Albrich, S; Boegl, K W; Mohr, E; Wichmann, G
1987-12-01
The viscosity of 13 different spices and dried vegetables in total was measured. Optimal conditions were first determined for each product, i.e. concentration, pH-value, temperature, particle size and soaking time. For method evaluation, examinations were primarily performed to study the effect of storage, the reproducibility and the influence of the different varieties of the same spice. In supplement, for pepper, the viscosity was measured as a function of radiation dose. In summation, significant changes in the gel forming capability after irradiation could be observed after preliminary experiments in 8 dried spices (ginger, carrots, leek, cloves, pepper, celery, cinnamon and onions). With 3 spices (ginger, pepper and cinnamon) could the results from examining all different varieties of the same spice be substantiated. An additional influence of storage time on viscosity could not be proved during the investigative period of 8 months. Generally seen, there is no possibility of being able to identify an irradiated spice on the basis of viscosity measurements alone, since the difference between the varieties of one and the same spice is considerably great. However, radiation treatment can be reliably excluded with ginger, pepper and cinnamon, if the viscosities are high (10-20 Pa x s).
Sadowski, Lukasz
2013-01-01
In recent years, the corrosion of steel reinforcement has become a major problem in the construction industry. Therefore, much attention has been given to developing methods of predicting the service life of reinforced concrete structures. The progress of corrosion cannot be visually assessed until a crack or a delamination appears. The corrosion process can be tracked using several electrochemical techniques. Most commonly the half-cell potential measurement technique is used for this purpose. However, it is generally accepted that it should be supplemented with other techniques. Hence, a methodology for assessing the probability of corrosion in concrete slabs by means of a combination of two methods, that is, the half-cell potential method and the concrete resistivity method, is proposed. An assessment of the probability of corrosion in reinforced concrete structures carried out using the proposed methodology is presented. 200 mm thick 750 mm × 750 mm reinforced concrete slab specimens were investigated. Potential E corr and concrete resistivity ρ in each point of the applied grid were measured. The experimental results indicate that the proposed methodology can be successfully used to assess the probability of corrosion in concrete structures.
Lukasz Sadowski
2013-01-01
Full Text Available In recent years, the corrosion of steel reinforcement has become a major problem in the construction industry. Therefore, much attention has been given to developing methods of predicting the service life of reinforced concrete structures. The progress of corrosion cannot be visually assessed until a crack or a delamination appears. The corrosion process can be tracked using several electrochemical techniques. Most commonly the half-cell potential measurement technique is used for this purpose. However, it is generally accepted that it should be supplemented with other techniques. Hence, a methodology for assessing the probability of corrosion in concrete slabs by means of a combination of two methods, that is, the half-cell potential method and the concrete resistivity method, is proposed. An assessment of the probability of corrosion in reinforced concrete structures carried out using the proposed methodology is presented. 200 mm thick 750 mm × 750 mm reinforced concrete slab specimens were investigated. Potential Ecorr and concrete resistivity ρ in each point of the applied grid were measured. The experimental results indicate that the proposed methodology can be successfully used to assess the probability of corrosion in concrete structures.
A NEW METHOD FOR CONSTRUCTING CONFIDENCE INTERVAL FOR CPM BASED ON FUZZY DATA
Bahram Sadeghpour Gildeh
2011-06-01
Full Text Available A measurement control system ensures that measuring equipment and measurement processes are fit for their intended use and its importance in achieving product quality objectives. In most real life applications, the observations are fuzzy. In some cases specification limits (SLs are not precise numbers and they are expressed in fuzzy terms, s o that the classical capability indices could not be applied. In this paper we obtain 100(1 - α% fuzzy confidence interval for C pm fuzzy process capability index, where instead of precise quality we have two membership functions for specification limits.
Fuzzy rationality and parameter elicitation in decision analysis
Nikolova, Natalia D.; Tenekedjiev, Kiril I.
2010-07-01
It is widely recognised by decision analysts that real decision-makers always make estimates in an interval form. An overview of techniques to find an optimal alternative among such with imprecise and interval probabilities is presented. Scalarisation methods are outlined as most appropriate. A proper continuation of such techniques is fuzzy rational (FR) decision analysis. A detailed representation of the elicitation process influenced by fuzzy rationality is given. The interval character of probabilities leads to the introduction of ribbon functions, whose general form and special cases are compared with the p-boxes. As demonstrated, approximation of utilities in FR decision analysis does not depend on the probabilities, but the approximation of probabilities is dependent on preferences.
Linguistic fuzzy selection of liquid levelmeters in nuclear facilities
Ghyym, S. H.
1999-01-01
In this work, a selection methodology of liquid levelmeters, especially, level sensors in non-nuclear category, to be installed in nuclear facilities is developed using a linguistic fuzzy approach. Depending on defuzzification techniques, the linguistic fuzzy methodology leads to either linguistic (exactly, fully-linguistic) or cardinal (i.e., semi-linguistic) evaluation. In the case of the linguistic method, for each alternative, fuzzy preference index is converted to linguistic utility value by means of a similarity measure determining the degree of similarity between fuzzy index and linguistic ratings. For the cardinal method, the index is translated to cardinal overall utility value. According to these values, alternatives of interest are linguistically or numerically evaluated and a suitable alternative can be selected. Under given selection criteria, the suitable selections out of some liquid levelmeters for nuclear facilities are dealt with using the linguistic fuzzy methodology proposed. Then, linguistic fuzzy evaluation results are compared with numerical results available in the literature. It is found that as to a suitable option the linguistic fuzzy selection is in agreement with the crisp numerical selection. In addition, this comparison shows that the fully-linguistic method facilitates linguistic interpretation regarding evaluation results
Linguistic fuzzy selection of liquid levelmeters in nuclear facilities
Ghyym, S. H. [KEPRI, Taejon (Korea, Republic of)
1999-10-01
In this work, a selection methodology of liquid levelmeters, especially, level sensors in non-nuclear category, to be installed in nuclear facilities is developed using a linguistic fuzzy approach. Depending on defuzzification techniques, the linguistic fuzzy methodology leads to either linguistic (exactly, fully-linguistic) or cardinal (i.e., semi-linguistic) evaluation. In the case of the linguistic method, for each alternative, fuzzy preference index is converted to linguistic utility value by means of a similarity measure determining the degree of similarity between fuzzy index and linguistic ratings. For the cardinal method, the index is translated to cardinal overall utility value. According to these values, alternatives of interest are linguistically or numerically evaluated and a suitable alternative can be selected. Under given selection criteria, the suitable selections out of some liquid levelmeters for nuclear facilities are dealt with using the linguistic fuzzy methodology proposed. Then, linguistic fuzzy evaluation results are compared with numerical results available in the literature. It is found that as to a suitable option the linguistic fuzzy selection is in agreement with the crisp numerical selection. In addition, this comparison shows that the fully-linguistic method facilitates linguistic interpretation regarding evaluation results.
Mauro Zaninelli
2014-04-01
Full Text Available Intramammary infection affects the quality and quantity of dairy goat milk. Health status (HS and milk quality can be monitored by electrical conductivity (EC. The aim of the study was to determine the detection potential of EC when measured on-line on a daily basis and compared with readings from previous milkings. Milk yields (MYs were investigated with the same approach. To evaluate these relative traits, a multivariate model based on fuzzy logic technology – which provided interesting results in cows – was used. Two foremilk samples from 8 healthy Saanen goats were measured daily over the course of six months. Bacteriological tests and somatic cells counts were used to define the HS. On-line EC measurements for each gland and MYs were also considered. Predicted deviations of EC and MY were calculated using a moving-average model and entered in the fuzzy logic model. The reported accuracy has a sensitivity of 81% and a specificity of 69%. Conclusions show that fuzzy logic is an interesting approach for dairy goats, since it offered better accuracy than other methods previously published. Nevertheless, specificity was lower than in dairy cows, probably due to the lack of a significant decrease of MY in diseased glands. Still, results show that the detection of the HS characteristics with EC is improved, when measured on-line, daily and compared with the readings from previous milkings.
Introduction to probability with R
Baclawski, Kenneth
2008-01-01
FOREWORD PREFACE Sets, Events, and Probability The Algebra of Sets The Bernoulli Sample Space The Algebra of Multisets The Concept of Probability Properties of Probability Measures Independent Events The Bernoulli Process The R Language Finite Processes The Basic Models Counting Rules Computing Factorials The Second Rule of Counting Computing Probabilities Discrete Random Variables The Bernoulli Process: Tossing a Coin The Bernoulli Process: Random Walk Independence and Joint Distributions Expectations The Inclusion-Exclusion Principle General Random Variable
Irreversibility and conditional probability
Stuart, C.I.J.M.
1989-01-01
The mathematical entropy - unlike physical entropy - is simply a measure of uniformity for probability distributions in general. So understood, conditional entropies have the same logical structure as conditional probabilities. If, as is sometimes supposed, conditional probabilities are time-reversible, then so are conditional entropies and, paradoxically, both then share this symmetry with physical equations of motion. The paradox is, of course that probabilities yield a direction to time both in statistical mechanics and quantum mechanics, while the equations of motion do not. The supposed time-reversibility of both conditionals seems also to involve a form of retrocausality that is related to, but possibly not the same as, that described by Costa de Beaurgard. The retrocausality is paradoxically at odds with the generally presumed irreversibility of the quantum mechanical measurement process. Further paradox emerges if the supposed time-reversibility of the conditionals is linked with the idea that the thermodynamic entropy is the same thing as 'missing information' since this confounds the thermodynamic and mathematical entropies. However, it is shown that irreversibility is a formal consequence of conditional entropies and, hence, of conditional probabilities also. 8 refs. (Author)
Neuro-fuzzy system modeling based on automatic fuzzy clustering
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.
Hierarchical type-2 fuzzy aggregation of fuzzy controllers
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.
Fuzzy logic based ELF magnetic field estimation in substations
Kosalay, I.
2008-01-01
This paper examines estimation of the extremely low frequency magnetic fields (MF) in the power substation. First, the results of the previous relevant research studies and the MF measurements in a sample power substation are presented. Then, a fuzzy logic model based on the geometric definitions in order to estimate the MF distribution is explained. Visual software, which has a three-dimensional screening unit, based on the fuzzy logic technique, has been developed. (authors)
A Fuzzy Method for Medical Diagnosis of Headache
Ahn, Jeong-Yong; Mun, Kill-Sung; Kim, Young-Hyun; Oh, Sun-Young; Han, Beom-Soo
In this note we propose a fuzzy diagnosis of headache. The method is based on the relations between symptoms and diseases. For this purpose, we suggest a new diagnosis measure using the occurrence information of patient's symptoms and develop an improved interview chart with fuzzy degrees assigned according to the relation among symptoms and three labels of headache. The proposed method is illustrated by two examples.
Fuzzy Fiber Sensors for Structural Composite Health Monitoring (Preprint)
2011-12-01
fuzzy fibers to applied strain was measured in the following configurations: individual fiber, fiber tow, tow in matrix, and tow in laminated composite...panels, 12″ × 12″, were fabricated with IM7/977-2 prepreg unidirectional carbon fiber tape. Three panels each were prepared with unidirectional [0]8 or...were fabricated with 6″-long fuzzy fiber strain sensors embedded at the midpoint of the laminate plies. Eight straight-sided specimens (as shown in
Determination of bounds on failure probability in the presence of ...
In particular, fuzzy set theory provides a more rational framework for ..... indicating that the random variations inT andO2 do not affect failure probability significantly. ... The upper-bound for PF shown in figure 6 can be used in decision-making.
Fuzzy control. Fundamentals, stability and design of fuzzy controllers
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.)
Probability Aggregates in Probability Answer Set Programming
Saad, Emad
2013-01-01
Probability answer set programming is a declarative programming that has been shown effective for representing and reasoning about a variety of probability reasoning tasks. However, the lack of probability aggregates, e.g. {\\em expected values}, in the language of disjunctive hybrid probability logic programs (DHPP) disallows the natural and concise representation of many interesting problems. In this paper, we extend DHPP to allow arbitrary probability aggregates. We introduce two types of p...
Hideki Katagiri
2017-10-01
Full Text Available This paper considers linear programming problems (LPPs where the objective functions involve discrete fuzzy random variables (fuzzy set-valued discrete random variables. New decision making models, which are useful in fuzzy stochastic environments, are proposed based on both possibility theory and probability theory. In multi-objective cases, Pareto optimal solutions of the proposed models are newly defined. Computational algorithms for obtaining the Pareto optimal solutions of the proposed models are provided. It is shown that problems involving discrete fuzzy random variables can be transformed into deterministic nonlinear mathematical programming problems which can be solved through a conventional mathematical programming solver under practically reasonable assumptions. A numerical example of agriculture production problems is given to demonstrate the applicability of the proposed models to real-world problems in fuzzy stochastic environments.
Fuzzy pharmacology: theory and applications.
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.
Stochastic Optimal Estimation with Fuzzy Random Variables and Fuzzy Kalman Filtering
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.
Intuitionistic fuzzy aggregation and clustering
Xu, Zeshui
2012-01-01
This book offers a systematic introduction to the clustering algorithms for intuitionistic fuzzy values, the latest research results in intuitionistic fuzzy aggregation techniques, the extended results in interval-valued intuitionistic fuzzy environments, and their applications in multi-attribute decision making, such as supply chain management, military system performance evaluation, project management, venture capital, information system selection, building materials classification, and operational plan assessment, etc.
Aller, D.; Hohl, R.; Mair, F.; Schiesser, H.-H.
2003-04-01
Extreme hailfall can cause massive damage to building structures. For the insurance and reinsurance industry it is essential to estimate the probable maximum hail loss of their portfolio. The probable maximum loss (PML) is usually defined with a return period of 1 in 250 years. Statistical extrapolation has a number of critical points, as historical hail loss data are usually only available from some events while insurance portfolios change over the years. At the moment, footprints are derived from historical hail damage data. These footprints (mean damage patterns) are then moved over a portfolio of interest to create scenario losses. However, damage patterns of past events are based on the specific portfolio that was damaged during that event and can be considerably different from the current spread of risks. A new method for estimating the probable maximum hail loss to a building portfolio is presented. It is shown that footprints derived from historical damages are different to footprints of hail kinetic energy calculated from radar reflectivity measurements. Based on the relationship between radar-derived hail kinetic energy and hail damage to buildings, scenario losses can be calculated. A systematic motion of the hail kinetic energy footprints over the underlying portfolio creates a loss set. It is difficult to estimate the return period of losses calculated with footprints derived from historical damages being moved around. To determine the return periods of the hail kinetic energy footprints over Switzerland, 15 years of radar measurements and 53 years of agricultural hail losses are available. Based on these data, return periods of several types of hailstorms were derived for different regions in Switzerland. The loss set is combined with the return periods of the event set to obtain an exceeding frequency curve, which can be used to derive the PML.
Where do we stand with fuzzy project scheduling?
Bonnal, Pierre; Lacoste, Germain
2004-01-01
Fuzzy project scheduling has interested several researchers in the past two decades; about 20 articles have been written on this issue. Contrary to stochastic project-scheduling approaches that are used by many project schedulers, and even if the axiomatic associated to the theory of probabilities is not always compatible with decision-making situations, fuzzy project-scheduling approaches that are most suited to these situations have been kept in the academic sphere. This paper starts by recalling the differences one can observe between uncertainty and imprecision. Then most of the published research works that have been done in this field are summarized. Finally, a framework for addressing the resource-constrained fuzzy project- scheduling problem is proposed. This framework uses temporal linguistic descriptors, which might become very interesting features to the project-scheduling practitioners.
Stock and option portfolio using fuzzy logic approach
Sumarti, Novriana; Wahyudi, Nanang
2014-03-01
Fuzzy Logic in decision-making process has been widely implemented in various problems in industries. It is the theory of imprecision and uncertainty that was not based on probability theory. Fuzzy Logic adds values of degree between absolute true and absolute false. It starts with and builds on a set of human language rules supplied by the user. The fuzzy systems convert these rules to their mathematical equivalents. This could simplify the job of the system designer and the computer, and results in much more accurate representations of the way systems behave in the real world. In this paper we examine the decision making process of stock and option trading by the usage of MACD (Moving Average Convergence Divergence) technical analysis and Option Pricing with Fuzzy Logic approach. MACD technical analysis is for the prediction of the trends of underlying stock prices, such as bearish (going downward), bullish (going upward), and sideways. By using Fuzzy C-Means technique and Mamdani Fuzzy Inference System, we define the decision output where the value of MACD is high then decision is "Strong Sell", and the value of MACD is Low then the decision is "Strong Buy". We also implement the fuzzification of the Black-Scholes option-pricing formula. The stock and options methods are implemented on a portfolio of one stock and its options. Even though the values of input data, such as interest rates, stock price and its volatility, cannot be obtain accurately, these fuzzy methods can give a belief degree of the calculated the Black-Scholes formula so we can make the decision on option trading. The results show the good capability of the methods in the prediction of stock price trends. The performance of the simulated portfolio for a particular period of time also shows good return.
Ultrafuzziness Optimization Based on Type II Fuzzy Sets for Image Thresholding
Hudan Studiawan
2010-11-01
Full Text Available Image thresholding is one of the processing techniques to provide high quality preprocessed image. Image vagueness and bad illumination are common obstacles yielding in a poor image thresholding output. By assuming image as fuzzy sets, several different fuzzy thresholding techniques have been proposed to remove these obstacles during threshold selection. In this paper, we proposed an algorithm for thresholding image using ultrafuzziness optimization to decrease uncertainty in fuzzy system by common fuzzy sets like type II fuzzy sets. Optimization was conducted by involving ultrafuzziness measurement for background and object fuzzy sets separately. Experimental results demonstrated that the proposed image thresholding method had good performances for images with high vagueness, low level contrast, and grayscale ambiguity.
Intelligent tuning of vibration mitigation process for single link manipulator using fuzzy logic
Ahmed A. Ali
2017-08-01
Full Text Available In this work, active vibration mitigation for smart single link manipulator is presented. Two piezoelectric transducers were utilized to act as actuator and sensor respectively. Classical Proportional (P controller was tested numerically and experimentally. The comparison between measured results showed good agreement. The proposed work includes the introducing of fuzzy logic for tuning controller's gain within finite element method. Classical Proportional-Integral (PI, Fuzzy-P and Fuzzy-PI controllers were totally integrated as a series of [IF-Then] states and solved numerically by using Finite Element (FE solver (ANSYS. Proposed method will pave the way on solving the tuning process totally within single FE solver with high efficiency. Proposed method satisfied mitigation in the overall free response with about 52% and 74% of the manipulator settling time when Fuzzy-P and Fuzzy-PI controllers were activated respectively. This contribution can be utilized for many other applications related to fuzzy topics.
Fuzzy Mutual Information Based min-Redundancy and Max-Relevance Heterogeneous Feature Selection
Daren Yu
2011-08-01
Full Text Available Feature selection is an important preprocessing step in pattern classification and machine learning, and mutual information is widely used to measure relevance between features and decision. However, it is difficult to directly calculate relevance between continuous or fuzzy features using mutual information. In this paper we introduce the fuzzy information entropy and fuzzy mutual information for computing relevance between numerical or fuzzy features and decision. The relationship between fuzzy information entropy and differential entropy is also discussed. Moreover, we combine fuzzy mutual information with qmin-Redundancy-Max-Relevanceq, qMax-Dependencyq and min-Redundancy-Max-Dependencyq algorithms. The performance and stability of the proposed algorithms are tested on benchmark data sets. Experimental results show the proposed algorithms are effective and stable.
Scaling Qualitative Probability
Burgin, Mark
2017-01-01
There are different approaches to qualitative probability, which includes subjective probability. We developed a representation of qualitative probability based on relational systems, which allows modeling uncertainty by probability structures and is more coherent than existing approaches. This setting makes it possible proving that any comparative probability is induced by some probability structure (Theorem 2.1), that classical probability is a probability structure (Theorem 2.2) and that i...
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.
Coufal, David
2017-01-01
Roč. 319, 15 July (2017), s. 1-27 ISSN 0165-0114 R&D Projects: GA MŠk(CZ) LD13002 Institutional support: RVO:67985807 Keywords : fuzzy systems * radial functions * coherence 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: 2.718, year: 2016
Contributions to quantum probability
Fritz, Tobias
2010-01-01
Chapter 1: On the existence of quantum representations for two dichotomic measurements. Under which conditions do outcome probabilities of measurements possess a quantum-mechanical model? This kind of problem is solved here for the case of two dichotomic von Neumann measurements which can be applied repeatedly to a quantum system with trivial dynamics. The solution uses methods from the theory of operator algebras and the theory of moment problems. The ensuing conditions reveal surprisingly simple relations between certain quantum-mechanical probabilities. It also shown that generally, none of these relations holds in general probabilistic models. This result might facilitate further experimental discrimination between quantum mechanics and other general probabilistic theories. Chapter 2: Possibilistic Physics. I try to outline a framework for fundamental physics where the concept of probability gets replaced by the concept of possibility. Whereas a probabilistic theory assigns a state-dependent probability value to each outcome of each measurement, a possibilistic theory merely assigns one of the state-dependent labels ''possible to occur'' or ''impossible to occur'' to each outcome of each measurement. It is argued that Spekkens' combinatorial toy theory of quantum mechanics is inconsistent in a probabilistic framework, but can be regarded as possibilistic. Then, I introduce the concept of possibilistic local hidden variable models and derive a class of possibilistic Bell inequalities which are violated for the possibilistic Popescu-Rohrlich boxes. The chapter ends with a philosophical discussion on possibilistic vs. probabilistic. It can be argued that, due to better falsifiability properties, a possibilistic theory has higher predictive power than a probabilistic one. Chapter 3: The quantum region for von Neumann measurements with postselection. It is determined under which conditions a probability distribution on a finite set can occur as the outcome
Contributions to quantum probability
Fritz, Tobias
2010-06-25
Chapter 1: On the existence of quantum representations for two dichotomic measurements. Under which conditions do outcome probabilities of measurements possess a quantum-mechanical model? This kind of problem is solved here for the case of two dichotomic von Neumann measurements which can be applied repeatedly to a quantum system with trivial dynamics. The solution uses methods from the theory of operator algebras and the theory of moment problems. The ensuing conditions reveal surprisingly simple relations between certain quantum-mechanical probabilities. It also shown that generally, none of these relations holds in general probabilistic models. This result might facilitate further experimental discrimination between quantum mechanics and other general probabilistic theories. Chapter 2: Possibilistic Physics. I try to outline a framework for fundamental physics where the concept of probability gets replaced by the concept of possibility. Whereas a probabilistic theory assigns a state-dependent probability value to each outcome of each measurement, a possibilistic theory merely assigns one of the state-dependent labels ''possible to occur'' or ''impossible to occur'' to each outcome of each measurement. It is argued that Spekkens' combinatorial toy theory of quantum mechanics is inconsistent in a probabilistic framework, but can be regarded as possibilistic. Then, I introduce the concept of possibilistic local hidden variable models and derive a class of possibilistic Bell inequalities which are violated for the possibilistic Popescu-Rohrlich boxes. The chapter ends with a philosophical discussion on possibilistic vs. probabilistic. It can be argued that, due to better falsifiability properties, a possibilistic theory has higher predictive power than a probabilistic one. Chapter 3: The quantum region for von Neumann measurements with postselection. It is determined under which conditions a probability distribution on a
Model uncertainty and probability
Parry, G.W.
1994-01-01
This paper discusses the issue of model uncertainty. The use of probability as a measure of an analyst's uncertainty as well as a means of describing random processes has caused some confusion, even though the two uses are representing different types of uncertainty with respect to modeling a system. The importance of maintaining the distinction between the two types is illustrated with a simple example
Nishiwaki, Yasushi [Nuclear Reactor Laboratory, Tokyo Institute of Technology, Tokyo (Japan); Nuclear Reactor Laboratoroy, Kinki University, Fuse City, Osaka Precture (Japan)
1961-11-25
Since it has been observed in Spring of 1954 that a considerable amount of fission products mixture fell with the rain following a large scale nuclear detonation conducted in Bikini area in the South Pacific by the United States Atomic Energy Commission, it has become important, especially from the health physics standpoint, to estimate the effective average age of the fission products mixture after the nuclear detonation. If the energy transferred to the atmospheric air at the time of nuclear detonation is large enough (order of megaton at the distance of about 4000 km), the probable time and test site of nuclear detonation may be estimated with considerable accuracy, from the records of the pressure wave caused by the detonation in the microbarographs at different meteorological stations. Even in this case, in order to estimate the possible correlation between the artificial radioactivity observed in the rain and the probable detonation, it is often times desirable to estimate the effective age of the fission products mixture in the rain from the decay measurement of the radioactivity.
Nishiwaki, Yasushi
1961-01-01
Since it has been observed in Spring of 1954 that a considerable amount of fission products mixture fell with the rain following a large scale nuclear detonation conducted in Bikini area in the South Pacific by the United States Atomic Energy Commission, it has become important, especially from the health physics standpoint, to estimate the effective average age of the fission products mixture after the nuclear detonation. If the energy transferred to the atmospheric air at the time of nuclear detonation is large enough (order of megaton at the distance of about 4000 km), the probable time and test site of nuclear detonation may be estimated with considerable accuracy, from the records of the pressure wave caused by the detonation in the microbarographs at different meteorological stations. Even in this case, in order to estimate the possible correlation between the artificial radioactivity observed in the rain and the probable detonation, it is often times desirable to estimate the effective age of the fission products mixture in the rain from the decay measurement of the radioactivity
Nguyen, Hung T; Wu, Berlin; Xiang, Gang
2012-01-01
In many practical situations, we are interested in statistics characterizing a population of objects: e.g. in the mean height of people from a certain area. Most algorithms for estimating such statistics assume that the sample values are exact. In practice, sample values come from measurements, and measurements are never absolutely accurate. Sometimes, we know the exact probability distribution of the measurement inaccuracy, but often, we only know the upper bound on this inaccuracy. In this case, we have interval uncertainty: e.g. if the measured value is 1.0, and inaccuracy is bounded by 0.1, then the actual (unknown) value of the quantity can be anywhere between 1.0 - 0.1 = 0.9 and 1.0 + 0.1 = 1.1. In other cases, the values are expert estimates, and we only have fuzzy information about the estimation inaccuracy. This book shows how to compute statistics under such interval and fuzzy uncertainty. The resulting methods are applied to computer science (optimal scheduling of different processors), to in...
Operational budgeting using fuzzy goal programming
Saeed Mohammadi; Kamran Feizi; Ali Khatami Firouz Abadi
2013-01-01
Having an efficient budget normally has different advantages such as measuring the performance of various organizations, setting appropriate targets and promoting managers based on their achievements. However, any budgeting planning requires prediction of different cost components. There are various methods for budgeting planning such as incremental budgeting, program budgeting, zero based budgeting and performance budgeting. In this paper, we present a fuzzy goal programming to estimate oper...
Fuzzy logic controller to improve powerline communication
Tirrito, Salvatore
2015-12-01
The Power Line Communications (PLC) technology allows the use of the power grid in order to ensure the exchange of data information among devices. This work proposes an approach, based on Fuzzy Logic, that dynamically manages the amplitude of the signal, with which each node transmits, by processing the master-slave link quality measured and the master-slave distance. The main objective of this is to reduce both the impact of communication interferences induced and power consumption.
Lee, Seongkon; Kim, Jongwook [Korea Institute of Energy Research (Korea, Republic of). Energy Policy Research Center; Mogi, Gento [Tokyo Univ. (Japan). Graduate School of Engineering; Hui, K.S. [Hong Kong City Univ. (China). Manufacturing Engineering and Engineering Management
2010-07-01
list of evaluation criteria for assessing and prioritize hydrogen energy technologies in the sector of hydrogen ETRM with finite resources and R and D funds. The criteria are composed of economic impact, commercial potential, inner capacity, and technical spin-off. Hydrogen ETRM supplies primary energy technologies to be developed with a long-term view for the low carbon green growth. We suggest Korea's long-term direction and strategy for developing hydrogen energy technologies in the sector of hydrogen ETRM with the hydrogen economy. The main purpose of this research is to assess the priority of hydrogen energy technologies in the sector of hydrogen ETRM since we allocate and invest R and D budgets strategically as an extended research [1]. In this paper, we focus on the assessment of hydrogen energy technologies econometrically by using an integrated 2- stage approach, which is fuzzy analytic hierarchy (Fuzzy AHP) process and the data envelopment analysis (DEA) in the sector of hydrogen energy technologies. The research results suggest the most efficient hydrogen energy technology is selected by the multi-criteria decision making approach. In addition it also provides Korean hydrogen energy technology policymakers and decision makers with the right hydrogen energy technologies econometrically as they implement a strategic R and D plan. This extended abstract is composed as follows: Section 2 presents the fuzzy sets and numbers, Section 3 includes the Fuzzy AHP concepts. Section 4 presents the DEA approach. Section 5 shows the numerical examples. Finally, Section 6 presents the conclusions. (orig.)
Representing Uncertainty by Probability and Possibility
of uncertain parameters. Monte Carlo simulation is readily used for practical calculations. However, an alternative approach is offered by possibility theory making use of possibility distributions such as intervals and fuzzy intervals. This approach is well suited to represent lack of knowledge or imprecision......Uncertain parameters in modeling are usually represented by probability distributions reflecting either the objective uncertainty of the parameters or the subjective belief held by the model builder. This approach is particularly suited for representing the statistical nature or variance...
On New Cautious Structural Reliability Models in the Framework of imprecise Probabilities
Utkin, Lev V.; Kozine, Igor
2010-01-01
models and gen-eralizing conventional ones to imprecise probabili-ties. The theoretical setup employed for this purpose is imprecise statistical reasoning (Walley 1991), whose general framework is provided by upper and lower previsions (expectations). The appeal of this theory is its ability to capture......Uncertainty of parameters in engineering design has been modeled in different frameworks such as inter-val analysis, fuzzy set and possibility theories, ran-dom set theory and imprecise probability theory. The authors of this paper for many years have been de-veloping new imprecise reliability...... both aleatory (stochas-tic) and epistemic uncertainty and the flexibility with which information can be represented. The previous research of the authors related to generalizing structural reliability models to impre-cise statistical measures is summarized in Utkin & Kozine (2002) and Utkin (2004...
Fuzzy linguistic model for interpolation
Abbasbandy, S.; Adabitabar Firozja, M.
2007-01-01
In this paper, a fuzzy method for interpolating of smooth curves was represented. We present a novel approach to interpolate real data by applying the universal approximation method. In proposed method, fuzzy linguistic model (FLM) applied as universal approximation for any nonlinear continuous function. Finally, we give some numerical examples and compare the proposed method with spline method
ABC Algorithm based Fuzzy Modeling of Optical Glucose Detection
SARACOGLU, O. G.
2016-08-01
Full Text Available This paper presents a modeling approach based on the use of fuzzy reasoning mechanism to define a measured data set obtained from an optical sensing circuit. For this purpose, we implemented a simple but effective an in vitro optical sensor to measure glucose content of an aqueous solution. Measured data contain analog voltages representing the absorbance values of three wavelengths measured from an RGB LED in different glucose concentrations. To achieve a desired model performance, the parameters of the fuzzy models are optimized by using the artificial bee colony (ABC algorithm. The modeling results presented in this paper indicate that the fuzzy model optimized by the algorithm provide a successful modeling performance having the minimum mean squared error (MSE of 0.0013 which are in clearly good agreement with the measurements.
Fuzzy Logic in Medicine and Bioinformatics
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.
Algebraic Aspects of Families of Fuzzy Languages
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
Fuzzy control in environmental engineering
Chmielowski, Wojciech Z
2016-01-01
This book is intended for engineers, technicians and people who plan to use fuzzy control in more or less developed and advanced control systems for manufacturing processes, or directly for executive equipment. Assuming that the reader possesses elementary knowledge regarding fuzzy sets and fuzzy control, by way of a reminder, the first parts of the book contain a reminder of the theoretical foundations as well as a description of the tools to be found in the Matlab/Simulink environment in the form of a toolbox. The major part of the book presents applications for fuzzy controllers in control systems for various manufacturing and engineering processes. It presents seven processes and problems which have been programmed using fuzzy controllers. The issues discussed concern the field of Environmental Engineering. Examples are the control of a flood wave passing through a hypothetical, and then the real Dobczyce reservoir in the Raba River, which is located in the upper Vistula River basin in Southern Poland, th...
Design of interpretable fuzzy systems
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.
On Intuitionistic Fuzzy Sets Theory
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.
Safety critical application of fuzzy control
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
Image matching navigation based on fuzzy information
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.
CAC Algorithm Based on Fuzzy Logic
Ľubomír DOBOŠ
2009-05-01
Full Text Available Quality of Service (QoS represent one ofmajor parameters that describe mobile wirelesscommunication systems. Thanks growing popularity ofmobile communication in last years, there is anincreasing expansion of connection admission controlschemes (CAC that plays important role in QoSdelivering in terms of connection blocking probability,connection dropping probability, data loss rate andsignal quality.With expansion of services provided by the mobilenetworks growing the requirements to QoS andtogether growing requirements to CAC schemes.Therefore, still more sophisticated CAC schemes arerequired to guarantee the QoS. This paper containsshort introduction into division of connectionadmission control schemes and presents thresholdoriented CAC scheme with fuzzy logic used foradaptation of the threshold value.
S. Ebrahimnejad
2012-04-01
Full Text Available The complexity of large-scale projects has led to numerous risks in their life cycle. This paper presents a new risk evaluation approach in order to rank the high risks in large-scale projects and improve the performance of these projects. It is based on the fuzzy set theory that is an effective tool to handle uncertainty. It is also based on an extended VIKOR method that is one of the well-known multiple criteria decision-making (MCDM methods. The proposed decision-making approach integrates knowledge and experience acquired from professional experts, since they perform the risk identification and also the subjective judgments of the performance rating for high risks in terms of conflicting criteria, including probability, impact, quickness of reaction toward risk, event measure quantity and event capability criteria. The most notable difference of the proposed VIKOR method with its traditional version is just the use of fuzzy decision-matrix data to calculate the ranking index without the need to ask the experts. Finally, the proposed approach is illustrated with a real-case study in an Iranian power plant project, and the associated results are compared with two well-known decision-making methods under a fuzzy environment.
Briggs, William M.
2012-01-01
The probability leakage of model M with respect to evidence E is defined. Probability leakage is a kind of model error. It occurs when M implies that events $y$, which are impossible given E, have positive probability. Leakage does not imply model falsification. Models with probability leakage cannot be calibrated empirically. Regression models, which are ubiquitous in statistical practice, often evince probability leakage.
Poussier, E.; Rambaut, M.
1986-01-01
Detection consists of a measurement of a counting rate. A probability of wrong detection is associated with this counting rate and with an average estimated rate of noise. Detection consists also in comparing the wrong detection probability to a predeterminated rate of wrong detection. The comparison can use tabulated values. Application is made to corpuscule radiation detection [fr
Fuzzy chance constrained linear programming model for scrap charge optimization in steel production
Rong, Aiying; Lahdelma, Risto
2008-01-01
the uncertainty based on fuzzy set theory and constrain the failure risk based on a possibility measure. Consequently, the scrap charge optimization problem is modeled as a fuzzy chance constrained linear programming problem. Since the constraints of the model mainly address the specification of the product...
A comparative study of fuzzy target selection methods in direct marketing
Costa Sousa, da J.M.; Kaymak, U.; Madeira, S.
2002-01-01
Target selection in direct marketing is an important data mining problem for which fuzzy modeling can be used. The paper compares several fuzzy modeling techniques applied to target selection based on recency, frequency and monetary value measures. The comparison uses cross validation applied to
Expected utility with lower probabilities
Hendon, Ebbe; Jacobsen, Hans Jørgen; Sloth, Birgitte
1994-01-01
An uncertain and not just risky situation may be modeled using so-called belief functions assigning lower probabilities to subsets of outcomes. In this article we extend the von Neumann-Morgenstern expected utility theory from probability measures to belief functions. We use this theory...
Fuzzy portfolio model with fuzzy-input return rates and fuzzy-output proportions
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.
Assessment of the Degree of Consistency of the System of Fuzzy Rules
Pospelova Lyudmila Yakovlevna
2013-12-01
Full Text Available The article analyses recent achievements and publications and shows that difficulties of explaining the nature of fuzziness and equivocation arise in socio-economic models that use the traditional paradigm of classical rationalism (computational, agent and econometric models. The accumulated collective experience of development of optimal models confirms prospectiveness of application of the fuzzy set approach in modelling the society. The article justifies the necessity of study of the nature of inconsistency in fuzzy knowledge bases both on the generalised ontology level and on pragmatic functional level of the logical inference. The article offers the method of search for logical and conceptual contradictions in the form of a combination of the abduction and modus ponens. It discusses the key issue of the proposed method: what properties should have the membership function of the secondary fuzzy set, which describes in fuzzy inference models such a resulting state of the object of management, which combines empirically incompatible properties with high probability. The degree of membership of the object of management in several incompatible classes with respect to the fuzzy output variable is the degree of fuzziness of the “Intersection of all results of the fuzzy inference of the set, applied at some input of rules, is an empty set” statement. The article describes an algorithm of assessment of the degree of consistency. It provides an example of the step-by-step detection of contradictions in statistical fuzzy knowledge bases at the pragmatic functional level of the logical output. The obtained results of testing in the form of sets of incompatible facts, output chains, sets of non-crossing intervals and computed degrees of inconsistency allow experts timely elimination of inadmissible contradictions and, at the same time, increase of quality of recommendations and assessment of fuzzy expert systems.
Improvement of Fuzzy Image Contrast Enhancement Using Simulated Ergodic Fuzzy Markov Chains
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.
The World of Combinatorial Fuzzy Problems and the Efficiency of Fuzzy Approximation Algorithms
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...
Koo, Reginald; Jones, Martin L.
2011-01-01
Quite a number of interesting problems in probability feature an event with probability equal to 1/e. This article discusses three such problems and attempts to explain why this probability occurs with such frequency.
Goldberg, Samuel
1960-01-01
Excellent basic text covers set theory, probability theory for finite sample spaces, binomial theorem, probability distributions, means, standard deviations, probability function of binomial distribution, more. Includes 360 problems with answers for half.
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.
Whittle, Peter
1992-01-01
This book is a complete revision of the earlier work Probability which ap peared in 1970. While revised so radically and incorporating so much new material as to amount to a new text, it preserves both the aim and the approach of the original. That aim was stated as the provision of a 'first text in probability, de manding a reasonable but not extensive knowledge of mathematics, and taking the reader to what one might describe as a good intermediate level'. In doing so it attempted to break away from stereotyped applications, and consider applications of a more novel and significant character. The particular novelty of the approach was that expectation was taken as the prime concept, and the concept of expectation axiomatized rather than that of a probability measure. In the preface to the original text of 1970 (reproduced below, together with that to the Russian edition of 1982) I listed what I saw as the advantages of the approach in as unlaboured a fashion as I could. I also took the view that the text...
Sanchez, Mauricio A; Castro, Juan R
2017-01-01
In this book, a series of granular algorithms are proposed. A nature inspired granular algorithm based on Newtonian gravitational forces is proposed. A series of methods for the formation of higher-type information granules represented by Interval Type-2 Fuzzy Sets are also shown, via multiple approaches, such as Coefficient of Variation, principle of justifiable granularity, uncertainty-based information concept, and numerical evidence based. And a fuzzy granular application comparison is given as to demonstrate the differences in how uncertainty affects the performance of fuzzy information granules.
Hudec Miroslav
2011-01-01
Full Text Available Structured Query Language (SQL is used to obtain data from relational databases. Fuzzy improvement of SQL queries has advantages in cases when the user cannot unambiguously define selection criteria or when the user wants to examine data that almost meet the given criteria. In this paper we examine a realization of the fuzzy querying concept. For this purposes the fuzzy generalized logical condition for the WHERE part of the SQL is created. It allows users to create queries by linguistic terms. The proposed model is an extension of the SQL so that no modification inside databases has to be undertaken.
Fuzzy expert systems using CLIPS
Le, Thach C.
1994-01-01
This paper describes a CLIPS-based fuzzy expert system development environment called FCLIPS and illustrates its application to the simulated cart-pole balancing problem. FCLIPS is a straightforward extension of CLIPS without any alteration to the CLIPS internal structures. It makes use of the object-oriented and module features in CLIPS version 6.0 for the implementation of fuzzy logic concepts. Systems of varying degrees of mixed Boolean and fuzzy rules can be implemented in CLIPS. Design and implementation issues of FCLIPS will also be discussed.
FUZZY DECISION MAKING MODEL FOR BYZANTINE AGREEMENT
S. MURUGAN
2014-04-01
Full Text Available Byzantine fault tolerance is of high importance in the distributed computing environment where malicious attacks and software errors are common. A Byzantine process sends arbitrary messages to every other process. An effective fuzzy decision making approach is proposed to eliminate the Byzantine behaviour of the services in the distributed environment. It is proposed to derive a fuzzy decision set in which the alternatives are ranked with grade of membership and based on that an appropriate decision can be arrived on the messages sent by the different services. A balanced decision is to be taken from the messages received across the services. To accomplish this, Hurwicz criterion is used to balance the optimistic and pessimistic views of the decision makers on different services. Grades of membership for the services are assessed using the non-functional Quality of Service parameters and have been estimated using fuzzy entropy measure which logically ranks the participant services. This approach for decision making is tested by varying the number of processes, varying the number of faulty services, varying the message values sent to different services and considering the variation in the views of the decision makers about the services. The experimental result shows that the decision reached is an enhanced one and in case of conflict, the proposed approach provides a concrete result, whereas decision taken using the Lamport’s algorithm is an arbitrary one.
Algebraic Hyperstructures and Fuzzy Logic in the Treatment of Uncertainty
Antonio Maturo; Annamaria Porreca
2016-01-01
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 ...
Lark, R. Murray
2014-05-01
Conventionally the uncertainty of a conventional soil map has been expressed in terms of the mean purity of its map units: the probability that the soil profile class examined at a site would be found to correspond to the eponymous class of the simple map unit that is delineated there (Burrough et al, 1971). This measure of uncertainty has an intuitive meaning and is used for quality control in soil survey contracts (Western, 1978). However, it may be of limited value to the manager or policy maker who wants to decide whether the map provides a basis for decision making, and whether the cost of producing a better map would be justified. In this study I extend a published analysis of the economic implications of uncertainty in a soil map (Giasson et al., 2000). A decision analysis was developed to assess the economic value of imperfect soil map information for agricultural land use planning. Random error matrices for the soil map units were then generated, subject to constraints which ensure consistency with fixed frequencies of the different soil classes. For each error matrix the mean map unit purity was computed, and the value of the implied imperfect soil information was computed by the decision analysis. An alternative measure of the uncertainty in a soil map was considered. This is the mean soil map information which is the difference between the information content of a soil observation, at a random location in the region, and the information content of a soil observation given that the map unit is known. I examined the relationship between the value of imperfect soil information and the purity and information measures of map uncertainty. In both cases there was considerable variation in the economic value of possible maps with fixed values of the uncertainty measure. However, the correlation was somewhat stronger with the information measure, and there was a clear upper bound on the value of an imperfect soil map when the mean information takes some
Wang Yajun
2008-12-01
Full Text Available In order to address the complex uncertainties caused by interfacing between the fuzziness and randomness of the safety problem for embankment engineering projects, and to evaluate the safety of embankment engineering projects more scientifically and reasonably, this study presents the fuzzy logic modeling of the stochastic finite element method (SFEM based on the harmonious finite element (HFE technique using a first-order approximation theorem. Fuzzy mathematical models of safety repertories were introduced into the SFEM to analyze the stability of embankments and foundations in order to describe the fuzzy failure procedure for the random safety performance function. The fuzzy models were developed with membership functions with half depressed gamma distribution, half depressed normal distribution, and half depressed echelon distribution. The fuzzy stochastic mathematical algorithm was used to comprehensively study the local failure mechanism of the main embankment section near Jingnan in the Yangtze River in terms of numerical analysis for the probability integration of reliability on the random field affected by three fuzzy factors. The result shows that the middle region of the embankment is the principal zone of concentrated failure due to local fractures. There is also some local shear failure on the embankment crust. This study provides a referential method for solving complex multi-uncertainty problems in engineering safety analysis.
Pemodelan Sistem Fuzzy Dengan Menggunakan Matlab
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.
Implementation of Steiner point of fuzzy set.
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.
Fuzzy histogram for internal and external fuzzy directional relations
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...
Solution of Fuzzy Differential Equations Using Fuzzy Sumudu Transforms
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.
TRStalker: an efficient heuristic for finding fuzzy tandem repeats.
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.
Theta-Generalized closed sets in fuzzy topological spaces
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)
Development of Fuzzy Logic and Soft Computing Methodologies
Zadeh, L. A.; Yager, R.
1999-01-01
Our earlier research on computing with words (CW) has led to a new direction in fuzzy logic which points to a major enlargement of the role of natural languages in information processing, decision analysis and control. This direction is based on the methodology of computing with words and embodies a new theory which is referred to as the computational theory of perceptions (CTP). An important feature of this theory is that it can be added to any existing theory - especially to probability theory, decision analysis, and control - and enhance the ability of the theory to deal with real-world problems in which the decision-relevant information is a mixture of measurements and perceptions. The new direction is centered on an old concept - the concept of a perception - a concept which plays a central role in human cognition. The ability to reason with perceptions perceptions of time, distance, force, direction, shape, intent, likelihood, truth and other attributes of physical and mental objects - underlies the remarkable human capability to perform a wide variety of physical and mental tasks without any measurements and any computations. Everyday examples of such tasks are parking a car, driving in city traffic, cooking a meal, playing golf and summarizing a story. Perceptions are intrinsically imprecise. Imprecision of perceptions reflects the finite ability of sensory organs and ultimately, the brain, to resolve detail and store information. More concretely, perceptions are both fuzzy and granular, or, for short, f-granular. Perceptions are f-granular in the sense that: (a) the boundaries of perceived classes are not sharply defined; and (b) the elements of classes are grouped into granules, with a granule being a clump of elements drawn together by indistinguishability, similarity. proximity or functionality. F-granularity of perceptions may be viewed as a human way of achieving data compression. In large measure, scientific progress has been, and continues to be
A reduced-form intensity-based model under fuzzy environments
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.
Wong, Linda; Hill, Beth L; Hunsberger, Benjamin C; Bagwell, C Bruce; Curtis, Adam D; Davis, Bruce H
2015-01-01
Leuko64™ (Trillium Diagnostics) is a flow cytometric assay that measures neutrophil CD64 expression and serves as an in vitro indicator of infection/sepsis or the presence of a systemic acute inflammatory response. Leuko64 assay currently utilizes QuantiCALC, a semiautomated software that employs cluster algorithms to define cell populations. The software reduces subjective gating decisions, resulting in interanalyst variability of state modeling (PSM). Four hundred and fifty-seven human blood samples were processed using the Leuko64 assay. Samples were analyzed on four different flow cytometer models: BD FACSCanto II, BD FACScan, BC Gallios/Navios, and BC FC500. A probability state model was designed to identify calibration beads and three leukocyte subpopulations based on differences in intensity levels of several parameters. PSM automatically calculates CD64 index values for each cell population using equations programmed into the model. GemStone software uses PSM that requires no operator intervention, thus totally automating data analysis and internal quality control flagging. Expert analysis with the predicate method (QuantiCALC) was performed. Interanalyst precision was evaluated for both methods of data analysis. PSM with GemStone correlates well with the expert manual analysis, r(2) = 0.99675 for the neutrophil CD64 index values with no intermethod bias detected. The average interanalyst imprecision for the QuantiCALC method was 1.06% (range 0.00-7.94%), which was reduced to 0.00% with the GemStone PSM. The operator-to-operator agreement in GemStone was a perfect correlation, r(2) = 1.000. Automated quantification of CD64 index values produced results that strongly correlate with expert analysis using a standard gate-based data analysis method. PSM successfully evaluated flow cytometric data generated by multiple instruments across multiple lots of the Leuko64 kit in all 457 cases. The probability-based method provides greater objectivity, higher
Basem Mohamed Elomda
2013-07-01
Full Text Available This paper presents a new extension to Fuzzy Decision Maps (FDMs by allowing use of fuzzy linguistic values to represent relative importance among criteria in the preference matrix as well as representing relative influence among criteria for computing the steady-state matrix in the stage of Fuzzy Cognitive Map (FCM. The proposed model is called the Linguistic Fuzzy Decision Networks (LFDNs. The proposed LFDN provides considerable flexibility to decision makers when solving real world Multi-Criteria Decision-Making (MCDM problems. The performance of the proposed LFDN model is compared with the original FDM using a previously published case study. The result of comparison ensures the ability to draw the same decisions with a more realistic decision environment.
Using Fuzzy Gaussian Inference and Genetic Programming to Classify 3D Human Motions
Khoury, Mehdi; Liu, Honghai
This research introduces and builds on the concept of Fuzzy Gaussian Inference (FGI) (Khoury and Liu in Proceedings of UKCI, 2008 and IEEE Workshop on Robotic Intelligence in Informationally Structured Space (RiiSS 2009), 2009) as a novel way to build Fuzzy Membership Functions that map to hidden Probability Distributions underlying human motions. This method is now combined with a Genetic Programming Fuzzy rule-based system in order to classify boxing moves from natural human Motion Capture data. In this experiment, FGI alone is able to recognise seven different boxing stances simultaneously with an accuracy superior to a GMM-based classifier. Results seem to indicate that adding an evolutionary Fuzzy Inference Engine on top of FGI improves the accuracy of the classifier in a consistent way.
Datta, D.; Joshi, M.L.
2006-01-01
Environmental modeling with a satisfaction levels of the end user in relation to a defined parameter coupled with imprecision that stems from the field data is a key issue. In the context of this issue success of possibility theory based on fuzzy sets has high visibility in comparison with conventional probability theory. Environmental impact assessments of a high level waste repository is focused using the new approach because the problems under consideration includes a number of qualitative uncertainties at different levels, apart from being quite complex; decision-maker's need to have a transparent assessment result that will enable him to understand underlying assumptions and to judge resulting doses. Fuzzy distributions have been tried to resolve the issues related to the safety of environment from the waste repository. Paper describes the details of fuzzy distribution, fuzzy logic and its possible application to deal the qualitative and quantitative uncertainty in connection with waste repository. (author)
Prescribed Performance Fuzzy Adaptive Output-Feedback Control for Nonlinear Stochastic Systems
Lili Zhang
2014-01-01
Full Text Available A prescribed performance fuzzy adaptive output-feedback control approach is proposed for a class of single-input and single-output nonlinear stochastic systems with unmeasured states. Fuzzy logic systems are used to identify the unknown nonlinear system, and a fuzzy state observer is designed for estimating the unmeasured states. Based on the backstepping recursive design technique and the predefined performance technique, a new fuzzy adaptive output-feedback control method is developed. It is shown that all the signals of the resulting closed-loop system are bounded in probability and the tracking error remains an adjustable neighborhood of the origin with the prescribed performance bounds. A simulation example is provided to show the effectiveness of the proposed approach.
FUZZY LOGIC IN LEGAL EDUCATION
Z. Gonul BALKIR
2011-04-01
Full Text Available The necessity of examination of every case within its peculiar conditions in social sciences requires different approaches complying with the spirit and nature of social sciences. Multiple realities require different and various perceptual interpretations. In modern world and social sciences, interpretation of perception of valued and multi-valued have been started to be understood by the principles of fuzziness and fuzzy logic. Having the verbally expressible degrees of truthness such as true, very true, rather true, etc. fuzzy logic provides the opportunity for the interpretation of especially complex and rather vague set of information by flexibility or equivalence of the variables’ of fuzzy limitations. The methods and principles of fuzzy logic can be benefited in examination of the methodological problems of law, especially in the applications of filling the legal loopholes arising from the ambiguities and interpretation problems in order to understand the legal rules in a more comprehensible and applicable way and the efficiency of legal implications. On the other hand, fuzzy logic can be used as a technical legal method in legal education and especially in legal case studies and legal practice applications in order to provide the perception of law as a value and the more comprehensive and more quality perception and interpretation of value of justice, which is the core value of law. In the perception of what happened as it has happened in legal relationships and formations, the understanding of social reality and sociological legal rules with multi valued sense perspective and the their applications in accordance with the fuzzy logic’s methods could create more equivalent and just results. It can be useful for the young lawyers and law students as a facilitating legal method especially in the materialization of the perception and interpretation of multi valued and variables. Using methods and principles of fuzzy logic in legal
On the mathematics of fuzziness
Kerre, E. [Ghent Univ. (Belgium)
1994-12-31
During the past twenty-five years, the scientific community has been working very extensively on the development of reliable models for the representation and manipulation of impreciseness and uncertainty that pervade the real world. Fuzzy set theory is one of the most popular theories able to treat incomplete information. In this paper, the basic mathematical principles underlying fuzzy set theory are outlined. Special attention is paid to the way that set theory has influenced the development of mathematics in a positive way.
On the mathematics of fuzziness
Kerre, E.
1994-01-01
During the past twenty-five years, the scientific community has been working very extensively on the development of reliable models for the representation and manipulation of impreciseness and uncertainty that pervade the real world. Fuzzy set theory is one of the most popular theories able to treat incomplete information. In this paper, the basic mathematical principles underlying fuzzy set theory are outlined. Special attention is paid to the way that set theory has influenced the development of mathematics in a positive way
Liu, X.; Fang, K.
1986-01-01
A theoretical study in fuzzy reasoning on Horn Set is presented in this paper. The authors first introduce the concepts of λ-Horn Set of clauses and λ-Input Half Lock deduction. They then use the λ-resolution method to discuss fuzzy reasoning on λ-Horn set of clauses. It is proved that the proposed λ-Input Half Lock resolution method is complete with the rules in certain format
A Fuzzy Query Mechanism for Human Resource Websites
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.
AN IMPROVED FUZZY CLUSTERING ALGORITHM FOR MICROARRAY IMAGE SPOTS SEGMENTATION
V.G. Biju
2015-11-01
Full Text Available An automatic cDNA microarray image processing using an improved fuzzy clustering algorithm is presented in this paper. The spot segmentation algorithm proposed uses the gridding technique developed by the authors earlier, for finding the co-ordinates of each spot in an image. Automatic cropping of spots from microarray image is done using these co-ordinates. The present paper proposes an improved fuzzy clustering algorithm Possibility fuzzy local information c means (PFLICM to segment the spot foreground (FG from background (BG. The PFLICM improves fuzzy local information c means (FLICM algorithm by incorporating typicality of a pixel along with gray level information and local spatial information. The performance of the algorithm is validated using a set of simulated cDNA microarray images added with different levels of AWGN noise. The strength of the algorithm is tested by computing the parameters such as the Segmentation matching factor (SMF, Probability of error (pe, Discrepancy distance (D and Normal mean square error (NMSE. SMF value obtained for PFLICM algorithm shows an improvement of 0.9 % and 0.7 % for high noise and low noise microarray images respectively compared to FLICM algorithm. The PFLICM algorithm is also applied on real microarray images and gene expression values are computed.
Algebraic Hyperstructures and Fuzzy Logic in the Treatment of Uncertainty
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.
Invariant probabilities of transition functions
Zaharopol, Radu
2014-01-01
The structure of the set of all the invariant probabilities and the structure of various types of individual invariant probabilities of a transition function are two topics of significant interest in the theory of transition functions, and are studied in this book. The results obtained are useful in ergodic theory and the theory of dynamical systems, which, in turn, can be applied in various other areas (like number theory). They are illustrated using transition functions defined by flows, semiflows, and one-parameter convolution semigroups of probability measures. In this book, all results on transition probabilities that have been published by the author between 2004 and 2008 are extended to transition functions. The proofs of the results obtained are new. For transition functions that satisfy very general conditions the book describes an ergodic decomposition that provides relevant information on the structure of the corresponding set of invariant probabilities. Ergodic decomposition means a splitting of t...
Piasecki, E.
2009-01-01
Heavy-ion collisions often produce a fusion barrier distribution with structures displaying a fingerprint of couplings to highly collective excitations [1]. Basically the same distribution can be obtained from large-angle quasi-elastic scattering, though here the role of the many weak direct-reaction channels is unclear. For 2 0N e + 9 0Z r we have observed the barrier structures expected for the highly deformed neon projectile, but for 2 0N e + 9 2Z r we find completely smooth distribution (see Fig.1). We find that transfer channels in these systems are of similar strength but single particle excitations are significantly stronger in the latter case. They apparently reduce the 'resolving power' of the quasi-elastic channel, what leads to smeared out, or 'fuzzy' barrier distribution. This is the first case when such a phenomenon has been observed.(author)
Probability mapping of contaminants
Rautman, C.A.; Kaplan, P.G. [Sandia National Labs., Albuquerque, NM (United States); McGraw, M.A. [Univ. of California, Berkeley, CA (United States); Istok, J.D. [Oregon State Univ., Corvallis, OR (United States); Sigda, J.M. [New Mexico Inst. of Mining and Technology, Socorro, NM (United States)
1994-04-01
Exhaustive characterization of a contaminated site is a physical and practical impossibility. Descriptions of the nature, extent, and level of contamination, as well as decisions regarding proposed remediation activities, must be made in a state of uncertainty based upon limited physical sampling. The probability mapping approach illustrated in this paper appears to offer site operators a reasonable, quantitative methodology for many environmental remediation decisions and allows evaluation of the risk associated with those decisions. For example, output from this approach can be used in quantitative, cost-based decision models for evaluating possible site characterization and/or remediation plans, resulting in selection of the risk-adjusted, least-cost alternative. The methodology is completely general, and the techniques are applicable to a wide variety of environmental restoration projects. The probability-mapping approach is illustrated by application to a contaminated site at the former DOE Feed Materials Production Center near Fernald, Ohio. Soil geochemical data, collected as part of the Uranium-in-Soils Integrated Demonstration Project, have been used to construct a number of geostatistical simulations of potential contamination for parcels approximately the size of a selective remediation unit (the 3-m width of a bulldozer blade). Each such simulation accurately reflects the actual measured sample values, and reproduces the univariate statistics and spatial character of the extant data. Post-processing of a large number of these equally likely statistically similar images produces maps directly showing the probability of exceeding specified levels of contamination (potential clean-up or personnel-hazard thresholds).
Probability mapping of contaminants
Rautman, C.A.; Kaplan, P.G.; McGraw, M.A.; Istok, J.D.; Sigda, J.M.
1994-01-01
Exhaustive characterization of a contaminated site is a physical and practical impossibility. Descriptions of the nature, extent, and level of contamination, as well as decisions regarding proposed remediation activities, must be made in a state of uncertainty based upon limited physical sampling. The probability mapping approach illustrated in this paper appears to offer site operators a reasonable, quantitative methodology for many environmental remediation decisions and allows evaluation of the risk associated with those decisions. For example, output from this approach can be used in quantitative, cost-based decision models for evaluating possible site characterization and/or remediation plans, resulting in selection of the risk-adjusted, least-cost alternative. The methodology is completely general, and the techniques are applicable to a wide variety of environmental restoration projects. The probability-mapping approach is illustrated by application to a contaminated site at the former DOE Feed Materials Production Center near Fernald, Ohio. Soil geochemical data, collected as part of the Uranium-in-Soils Integrated Demonstration Project, have been used to construct a number of geostatistical simulations of potential contamination for parcels approximately the size of a selective remediation unit (the 3-m width of a bulldozer blade). Each such simulation accurately reflects the actual measured sample values, and reproduces the univariate statistics and spatial character of the extant data. Post-processing of a large number of these equally likely statistically similar images produces maps directly showing the probability of exceeding specified levels of contamination (potential clean-up or personnel-hazard thresholds)
Chance-constrained programming models for capital budgeting with NPV as fuzzy parameters
Huang, Xiaoxia
2007-01-01
In an uncertain economic environment, experts' knowledge about outlays and cash inflows of available projects consists of much vagueness instead of randomness. Investment outlays and annual net cash flows of a project are usually predicted by using experts' knowledge. Fuzzy variables can overcome the difficulties in predicting these parameters. In this paper, capital budgeting problem with fuzzy investment outlays and fuzzy annual net cash flows is studied based on credibility measure. Net present value (NPV) method is employed, and two fuzzy chance-constrained programming models for capital budgeting problem are provided. A fuzzy simulation-based genetic algorithm is provided for solving the proposed model problems. Two numerical examples are also presented to illustrate the modelling idea and the effectiveness of the proposed algorithm.
Muzafar Shah, Mazlina; Fatah Wahab, Abdul
2017-09-01
There are an abnormal electric activities or irregular interference in brain of epilepsy patient. Then a sensor will be put in patient’s scalp to measure and records all electric activities in brain. The result of the records known as Electroencephalography (EEG). The EEG has been transfer to flat EEG because it’s easier to analyze. In this study, the uncertainty in flat EEG data will be considered as fuzzy digital space. The purpose of this research is to show that the flat EEG is fuzzy topological digital space. Therefore, the main focus for this research is to introduce fuzzy topological digital space concepts with their properties such as neighbourhood, interior and closure by using fuzzy set digital concept and Chang’s fuzzy topology approach. The product fuzzy topology digital also will be shown. By introduce this concept, the data in flat EEG can considering having fuzzy topology digital properties and can identify the area in fuzzy digital space that has been affected by epilepsy seizure in epileptic patient’s brain.
Yan Sun
2018-01-01
Full Text Available Capacity uncertainty is a common issue in the transportation planning field. However, few studies discuss the intermodal routing problem with service capacity uncertainty. Based on our previous study on the intermodal routing under deterministic capacity consideration, we systematically explore how service capacity uncertainty influences the intermodal routing decision. First of all, we adopt trapezoidal fuzzy numbers to describe the uncertain information of the service capacity, and further transform the deterministic capacity constraint into a fuzzy chance constraint based on fuzzy credibility measure. We then integrate such fuzzy chance constraint into the mixed-integer linear programming (MILP model proposed in our previous study to develop a fuzzy chance-constrained programming model. To enable the improved model to be effectively programmed in the standard mathematical programming software and solved by exact solution algorithms, a crisp equivalent linear reformulation of the fuzzy chance constraint is generated. Finally, we modify the empirical case presented in our previous study by replacing the deterministic service capacities with trapezoidal fuzzy ones. Using the modified empirical case, we utilize sensitivity analysis and fuzzy simulation to analyze the influence of service capacity uncertainty on the intermodal routing decision, and summarize some interesting insights that are helpful for decision makers.
Application of Fuzzy Optimization to the Orienteering Problem
Madhushi Verma
2015-01-01
Full Text Available This paper deals with the orienteering problem (OP which is a combination of two well-known problems (i.e., travelling salesman problem and the knapsack problem. OP is an NP-hard problem and is useful in appropriately modeling several challenging applications. As the parameters involved in these applications cannot be measured precisely, depicting them using crisp numbers is unrealistic. Further, the decision maker may be satisfied with graded satisfaction levels of solutions, which cannot be formulated using a crisp program. To deal with the above-stated two issues, we formulate the fuzzy orienteering problem (FOP and provide a method to solve it. Here we state the two necessary conditions of OP of maximizing the total collected score and minimizing the time taken to traverse a path (within the specified time bound as fuzzy goals and the remaining necessary conditions as crisp constraints. Using the max-min formulation of the fuzzy sets obtained from the fuzzy goals, we calculate the fuzzy decision sets (Z and Z∗ that contain the feasible paths and the desirable paths, respectively, along with the degrees to which they are acceptable. To efficiently solve large instances of FOP, we also present a parallel algorithm on CREW PRAM model.
Cluster analysis by optimal decomposition of induced fuzzy sets
Backer, E
1978-01-01
Nonsupervised pattern recognition is addressed and the concept of fuzzy sets is explored in order to provide the investigator (data analyst) additional information supplied by the pattern class membership values apart from the classical pattern class assignments. The basic ideas behind the pattern recognition problem, the clustering problem, and the concept of fuzzy sets in cluster analysis are discussed, and a brief review of the literature of the fuzzy cluster analysis is given. Some mathematical aspects of fuzzy set theory are briefly discussed; in particular, a measure of fuzziness is suggested. The optimization-clustering problem is characterized. Then the fundamental idea behind affinity decomposition is considered. Next, further analysis takes place with respect to the partitioning-characterization functions. The iterative optimization procedure is then addressed. The reclassification function is investigated and convergence properties are examined. Finally, several experiments in support of the method suggested are described. Four object data sets serve as appropriate test cases. 120 references, 70 figures, 11 tables. (RWR)
Fuzzy logic based variable speed wind generation system
Simoes, M.G. [Sao Paulo Univ., SP (Brazil). Escola Politecnica. PMC - Mecatronica; Bose, B.K. [Tennessee Univ., Knoxville, TN (United States). Dept. of Electrical Engineering; Spiegel, Ronal J. [Environmental Protection Agency, Research Triangle Park, NC (United States). Air and Energy Engineering Research Lab.
1996-12-31
This work demonstrates the successful application of fuzzy logic to enhance the performance and control of a variable speed wind generation system. A maximum power point tracker control is performed with three fuzzy controllers, without wind velocity measurement, and robust to wind vortex and turbine torque ripple. A squirrel cage induction generator feeds the power to a double-sided PWM converter system which pumps the power to a utility grid or supplies to an autonomous system. The fuzzy logic controller FLC-1 searches on-line the generator speed so that the aerodynamic efficiency of the wind turbine is optimized. A second fuzzy controller FLC-2 programs the machine flux by on-line search so as to optimize the machine-converter system wind vortex. Detailed analysis and simulation studies were performed for development of the control strategy and fuzzy algorithms, and a DSP TMS320C30 based hardware with C control software was built for the performance evaluation of a laboratory experimental set-up. The theoretical development was fully validated and the system is ready to be reproduced in a higher power installation. (author) 7 refs., 3 figs., 1 tab.
On Fuzzy β-I-open sets and Fuzzy β-I-continuous functions
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
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.
Wan, Neng; Lin, Ge
2016-12-01
Smartphones have emerged as a promising type of equipment for monitoring human activities in environmental health studies. However, degraded location accuracy and inconsistency of smartphone-measured GPS data have limited its effectiveness for classifying human activity patterns. This study proposes a fuzzy classification scheme for differentiating human activity patterns from smartphone-collected GPS data. Specifically, a fuzzy logic reasoning was adopted to overcome the influence of location uncertainty by estimating the probability of different activity types for single GPS points. Based on that approach, a segment aggregation method was developed to infer activity patterns, while adjusting for uncertainties of point attributes. Validations of the proposed methods were carried out based on a convenient sample of three subjects with different types of smartphones. The results indicate desirable accuracy (e.g., up to 96% in activity identification) with use of this method. Two examples were provided in the appendix to illustrate how the proposed methods could be applied in environmental health studies. Researchers could tailor this scheme to fit a variety of research topics.
Supply chain management under fuzziness recent developments and techniques
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.
Adaptive Fuzzy Output-Feedback Method Applied to Fin Control for Time-Delay Ship Roll Stabilization
Rui Bai
2014-01-01
Full Text Available The ship roll stabilization by fin control system is considered in this paper. Assuming that angular velocity in roll cannot be measured, an adaptive fuzzy output-feedback control is investigated. The fuzzy logic system is used to approximate the uncertain term of the controlled system, and a fuzzy state observer is designed to estimate the unmeasured states. By utilizing the fuzzy state observer and combining the adaptive backstepping technique with adaptive fuzzy control design, an observer-based adaptive fuzzy output-feedback control approach is developed. It is proved that the proposed control approach can guarantee that all the signals in the closed-loop system are semiglobally uniformly ultimately bounded (SGUUB, and the control strategy is effective to decrease the roll motion. Simulation results are included to illustrate the effectiveness of the proposed approach.
Stability Analysis of Interconnected Fuzzy Systems Using the Fuzzy Lyapunov Method
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.
Philosophical theories of probability
Gillies, Donald
2000-01-01
The Twentieth Century has seen a dramatic rise in the use of probability and statistics in almost all fields of research. This has stimulated many new philosophical ideas on probability. Philosophical Theories of Probability is the first book to present a clear, comprehensive and systematic account of these various theories and to explain how they relate to one another. Gillies also offers a distinctive version of the propensity theory of probability, and the intersubjective interpretation, which develops the subjective theory.
Fuzzy relational calculus theory, applications and software
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...
Compound Option Pricing under Fuzzy Environment
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.
A Geometric Fuzzy-Based Approach for Airport Clustering
Maria Nadia Postorino
2014-01-01
Full Text Available Airport classification is a common need in the air transport field due to several purposes—such as resource allocation, identification of crucial nodes, and real-time identification of substitute nodes—which also depend on the involved actors’ expectations. In this paper a fuzzy-based procedure has been proposed to cluster airports by using a fuzzy geometric point of view according to the concept of unit-hypercube. By representing each airport as a point in the given reference metric space, the geometric distance among airports—which corresponds to a measure of similarity—has in fact an intrinsic fuzzy nature due to the airport specific characteristics. The proposed procedure has been applied to a test case concerning the Italian airport network and the obtained results are in line with expectations.
Performance evaluation of enterprise architecture using fuzzy sequence diagram
Mohammad Atasheneh
2014-01-01
Full Text Available Developing an Enterprise Architecture is a complex task and to control the complexity of the regulatory framework we need to measure the relative performance of one system against other available systems. On the other hand, enterprise architecture cannot be organized without the use of a logical structure. The framework provides a logical structure for classifying architectural output. Among the common architectural framework, the C4ISR framework and methodology of the product is one of the most popular techniques. In this paper, given the existing uncertainties in system development and information systems, a new version of UML called Fuzzy-UML is proposed for enterprise architecture development based on fuzzy Petri nets. In addition, the performance of the system is also evaluated based on Fuzzy sequence diagram.
Burkill, Sarah; Couper, Mick P; Conrad, Frederick; Clifton, Soazig; Tanton, Clare; Phelps, Andrew; Datta, Jessica; Mercer, Catherine H; Sonnenberg, Pam; Prah, Philip; Mitchell, Kirstin R; Wellings, Kaye; Johnson, Anne M; Copas, Andrew J
2014-01-01
Background Nonprobability Web surveys using volunteer panels can provide a relatively cheap and quick alternative to traditional health and epidemiological surveys. However, concerns have been raised about their representativeness. Objective The aim was to compare results from different Web panels with a population-based probability sample survey (n=8969 aged 18-44 years) that used computer-assisted self-interview (CASI) for sensitive behaviors, the third British National Survey of Sexual Attitudes and Lifestyles (Natsal-3). Methods Natsal-3 questions were included on 4 nonprobability Web panel surveys (n=2000 to 2099), 2 using basic quotas based on age and sex, and 2 using modified quotas based on additional variables related to key estimates. Results for sociodemographic characteristics were compared with external benchmarks and for sexual behaviors and opinions with Natsal-3. Odds ratios (ORs) were used to express differences between the benchmark data and each survey for each variable of interest. A summary measure of survey performance was the average absolute OR across variables. Another summary measure was the number of key estimates for which the survey differed significantly (at the 5% level) from the benchmarks. Results For sociodemographic variables, the Web surveys were less representative of the general population than Natsal-3. For example, for men, the average absolute OR for Natsal-3 was 1.14, whereas for the Web surveys the average absolute ORs ranged from 1.86 to 2.30. For all Web surveys, approximately two-thirds of the key estimates of sexual behaviors were different from Natsal-3 and the average absolute ORs ranged from 1.32 to 1.98. Differences were appreciable even for questions asked by CASI in Natsal-3. No single Web survey performed consistently better than any other did. Modified quotas slightly improved results for men, but not for women. Conclusions Consistent with studies from other countries on less sensitive topics, volunteer Web
Interpretations of probability
Khrennikov, Andrei
2009-01-01
This is the first fundamental book devoted to non-Kolmogorov probability models. It provides a mathematical theory of negative probabilities, with numerous applications to quantum physics, information theory, complexity, biology and psychology. The book also presents an interesting model of cognitive information reality with flows of information probabilities, describing the process of thinking, social, and psychological phenomena.
Fuzzy Arden Syntax: A fuzzy programming language for medicine.
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
Berrazouane, S.; Mohammedi, K.
2014-01-01
Highlights: • Optimized fuzzy logic controller (FLC) for operating a standalone hybrid power system based on cuckoo search algorithm. • Comparison between optimized fuzzy logic controller based on cuckoo search and swarm intelligent. • Loss of power supply probability and levelized energy cost are introduced. - Abstract: This paper presents the development of an optimized fuzzy logic controller (FLC) for operating a standalone hybrid power system based on cuckoo search algorithm. The FLC inputs are batteries state of charge (SOC) and net power flow, FLC outputs are the power rate of batteries, photovoltaic and diesel generator. Data for weekly solar irradiation, ambient temperature and load profile are used to tune the proposed controller by using cuckoo search algorithm. The optimized FLC is able to minimize loss of power supply probability (LPSP), excess energy (EE) and levelized energy cost (LEC). Moreover, the results of CS optimization are better than of particle swarm optimization PSO for fuzzy system controller
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)
Probability theory a foundational course
Pakshirajan, R P
2013-01-01
This book shares the dictum of J. L. Doob in treating Probability Theory as a branch of Measure Theory and establishes this relation early. Probability measures in product spaces are introduced right at the start by way of laying the ground work to later claim the existence of stochastic processes with prescribed finite dimensional distributions. Other topics analysed in the book include supports of probability measures, zero-one laws in product measure spaces, Erdos-Kac invariance principle, functional central limit theorem and functional law of the iterated logarithm for independent variables, Skorohod embedding, and the use of analytic functions of a complex variable in the study of geometric ergodicity in Markov chains. This book is offered as a text book for students pursuing graduate programs in Mathematics and or Statistics. The book aims to help the teacher present the theory with ease, and to help the student sustain his interest and joy in learning the subject.
Linear positivity and virtual probability
Hartle, James B.
2004-01-01
We investigate the quantum theory of closed systems based on the linear positivity decoherence condition of Goldstein and Page. The objective of any quantum theory of a closed system, most generally the universe, is the prediction of probabilities for the individual members of sets of alternative coarse-grained histories of the system. Quantum interference between members of a set of alternative histories is an obstacle to assigning probabilities that are consistent with the rules of probability theory. A quantum theory of closed systems therefore requires two elements: (1) a condition specifying which sets of histories may be assigned probabilities and (2) a rule for those probabilities. The linear positivity condition of Goldstein and Page is the weakest of the general conditions proposed so far. Its general properties relating to exact probability sum rules, time neutrality, and conservation laws are explored. Its inconsistency with the usual notion of independent subsystems in quantum mechanics is reviewed. Its relation to the stronger condition of medium decoherence necessary for classicality is discussed. The linear positivity of histories in a number of simple model systems is investigated with the aim of exhibiting linearly positive sets of histories that are not decoherent. The utility of extending the notion of probability to include values outside the range of 0-1 is described. Alternatives with such virtual probabilities cannot be measured or recorded, but can be used in the intermediate steps of calculations of real probabilities. Extended probabilities give a simple and general way of formulating quantum theory. The various decoherence conditions are compared in terms of their utility for characterizing classicality and the role they might play in further generalizations of quantum mechanics
Fuzzy upper bounds and their applications
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.
Neuro-fuzzy Control of Integrating Processes
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.
FFLP problem with symmetric trapezoidal fuzzy numbers
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.
Failure probability under parameter uncertainty.
Gerrard, R; Tsanakas, A
2011-05-01
In many problems of risk analysis, failure is equivalent to the event of a random risk factor exceeding a given threshold. Failure probabilities can be controlled if a decisionmaker is able to set the threshold at an appropriate level. This abstract situation applies, for example, to environmental risks with infrastructure controls; to supply chain risks with inventory controls; and to insurance solvency risks with capital controls. However, uncertainty around the distribution of the risk factor implies that parameter error will be present and the measures taken to control failure probabilities may not be effective. We show that parameter uncertainty increases the probability (understood as expected frequency) of failures. For a large class of loss distributions, arising from increasing transformations of location-scale families (including the log-normal, Weibull, and Pareto distributions), the article shows that failure probabilities can be exactly calculated, as they are independent of the true (but unknown) parameters. Hence it is possible to obtain an explicit measure of the effect of parameter uncertainty on failure probability. Failure probability can be controlled in two different ways: (1) by reducing the nominal required failure probability, depending on the size of the available data set, and (2) by modifying of the distribution itself that is used to calculate the risk control. Approach (1) corresponds to a frequentist/regulatory view of probability, while approach (2) is consistent with a Bayesian/personalistic view. We furthermore show that the two approaches are consistent in achieving the required failure probability. Finally, we briefly discuss the effects of data pooling and its systemic risk implications. © 2010 Society for Risk Analysis.
Application of Fuzzy Clustering in Modeling of a Water Hydraulics System
Zhou, Jianjun; Kroszynski, Uri
2000-01-01
This article presents a case study of applying fuzzy modeling techniques for a water hydraulics system. The obtained model is intended to provide a basis for model-based control of the system. Fuzzy clustering is used for classifying measured input-output data points into partitions. The fuzzy...... model is extracted from the obtained partitions. The identified model has been evaluated by comparing measurements with simulation results. The evaluation shows that the identified model is capable of describing the system dynamics over a reasonably wide frequency range....
Fuzzy mobile-robot positioning in intelligent spaces using wireless sensor networks.
Herrero, David; Martínez, Humberto
2011-01-01
This work presents the development and experimental evaluation of a method based on fuzzy logic to locate mobile robots in an Intelligent Space using wireless sensor networks (WSNs). The problem consists of locating a mobile node using only inter-node range measurements, which are estimated by radio frequency signal strength attenuation. The sensor model of these measurements is very noisy and unreliable. The proposed method makes use of fuzzy logic for modeling and dealing with such uncertain information. Besides, the proposed approach is compared with a probabilistic technique showing that the fuzzy approach is able to handle highly uncertain situations that are difficult to manage by well-known localization methods.
A SELF-ORGANISING FUZZY LOGIC CONTROLLER
ES Obe
One major drawback of fuzzy logic controllers is the difficulty encountered in the construction of a rule- base ... The greatest limitation of fuzzy logic control is the lack ..... c(kT)= e(kT)-e((k-1)T). (16) .... with the aid of fuzzy models”, It in Industrial.
Forecasting Enrollments with Fuzzy Time Series.
Song, Qiang; Chissom, Brad S.
The concept of fuzzy time series is introduced and used to forecast the enrollment of a university. Fuzzy time series, an aspect of fuzzy set theory, forecasts enrollment using a first-order time-invariant model. To evaluate the model, the conventional linear regression technique is applied and the predicted values obtained are compared to the…
On the intuitionistic fuzzy inner product spaces
Goudarzi, M.; Vaezpour, S.M.; Saadati, R.
2009-01-01
In this paper, the definition of intuitionistic fuzzy inner product is given. By virtue of this definition, some convergence theorems, Schwarts inequality and the orthogonal concept for intuitionistic fuzzy inner product spaces are established and introduced. Moreover the relationship between this kind of spaces and intuitionistic fuzzy normed spaces is considered.
Fuzzy control of pressurizer dynamic process
Ming Zhedong; Zhao Fuyu
2006-01-01
Considering the characteristics of pressurizer dynamic process, the fuzzy control system that takes the advantages of both fuzzy controller and PID controller is designed for the dynamic process in pressurizer. The simulation results illustrate this type of composite control system is with better qualities than those of single fuzzy controller and single PID controller. (authors)
Possible use of fuzzy logic in database
Vaclav Bezdek
2011-04-01
Full Text Available The article deals with fuzzy logic and its possible use in database systems. At first fuzzy thinking style is shown on a simple example. Next the advantages of the fuzzy approach to database searching are considered on the database of used cars in the Czech Republic.
Effectiveness of Securities with Fuzzy Probabilistic Return
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
The majority rule in a fuzzy environment.
Montero, Javier
1986-01-01
In this paper, an axiomatic approach to rational decision making in a fuzzy environment is studied. In particular, the majority rule is proposed as a rational way for aggregating fuzzy opinions in a group, when such agroup is defined as a fuzzy set.
The fuzzy approach to statistical analysis
Coppi, Renato; Gil, Maria A.; Kiers, Henk A. L.
2006-01-01
For the last decades, research studies have been developed in which a coalition of Fuzzy Sets Theory and Statistics has been established with different purposes. These namely are: (i) to introduce new data analysis problems in which the objective involves either fuzzy relationships or fuzzy terms;
Fuqian Shi
2012-01-01
Full Text Available Emotional cellular (EC, proposed in our previous works, is a kind of semantic cell that contains kernel and shell and the kernel is formalized by a triple- L = , where P denotes a typical set of positive examples relative to word-L, d is a pseudodistance measure on emotional two-dimensional space: valence-arousal, and δ is a probability density function on positive real number field. The basic idea of EC model is to assume that the neighborhood radius of each semantic concept is uncertain, and this uncertainty will be measured by one-dimensional density function δ. In this paper, product form features were evaluated by using ECs and to establish the product style database, fuzzy case based reasoning (FCBR model under a defined similarity measurement based on fuzzy nearest neighbors (FNN incorporating EC was applied to extract product styles. A mathematical formalized inference system for product style was also proposed, and it also includes uncertainty measurement tool emotional cellular. A case study of style acquisition of mobile phones illustrated the effectiveness of the proposed methodology.
Excluding joint probabilities from quantum theory
Allahverdyan, Armen E.; Danageozian, Arshag
2018-03-01
Quantum theory does not provide a unique definition for the joint probability of two noncommuting observables, which is the next important question after the Born's probability for a single observable. Instead, various definitions were suggested, e.g., via quasiprobabilities or via hidden-variable theories. After reviewing open issues of the joint probability, we relate it to quantum imprecise probabilities, which are noncontextual and are consistent with all constraints expected from a quantum probability. We study two noncommuting observables in a two-dimensional Hilbert space and show that there is no precise joint probability that applies for any quantum state and is consistent with imprecise probabilities. This contrasts with theorems by Bell and Kochen-Specker that exclude joint probabilities for more than two noncommuting observables, in Hilbert space with dimension larger than two. If measurement contexts are included into the definition, joint probabilities are not excluded anymore, but they are still constrained by imprecise probabilities.
Fuzzy commutative algebra and its application in mechanical engineering
Han, J.; Song, H.
1996-01-01
Based on literature data, this paper discusses the whole mathematical structure about point-fuzzy number set F(R). By introducing some new operations about addition, subtraction, multiplication, division and scalar multiplication, we prove that F(R) can form fuzzy linear space, fuzzy commutative ring, fuzzy commutative algebra in order. Furthermore, we get that A is fuzzy commutative algebra for any fuzzy subset. At last, we give an application of point-fuzzy number to mechanical engineering
Meitzler, Thomas J.
The field of computer vision interacts with fields such as psychology, vision research, machine vision, psychophysics, mathematics, physics, and computer science. The focus of this thesis is new algorithms and methods for the computation of the probability of detection (Pd) of a target in a cluttered scene. The scene can be either a natural visual scene such as one sees with the naked eye (visual), or, a scene displayed on a monitor with the help of infrared sensors. The relative clutter and the temperature difference between the target and background (DeltaT) are defined and then used to calculate a relative signal -to-clutter ratio (SCR) from which the Pd is calculated for a target in a cluttered scene. It is shown how this definition can include many previous definitions of clutter and (DeltaT). Next, fuzzy and neural -fuzzy techniques are used to calculate the Pd and it is shown how these methods can give results that have a good correlation with experiment. The experimental design for actually measuring the Pd of a target by observers is described. Finally, wavelets are applied to the calculation of clutter and it is shown how this new definition of clutter based on wavelets can be used to compute the Pd of a target.
Sub-optimal control of fuzzy linear dynamical systems under granular differentiability concept.
Mazandarani, Mehran; Pariz, Naser
2018-05-01
This paper deals with sub-optimal control of a fuzzy linear dynamical system. The aim is to keep the state variables of the fuzzy linear dynamical system close to zero in an optimal manner. In the fuzzy dynamical system, the fuzzy derivative is considered as the granular derivative; and all the coefficients and initial conditions can be uncertain. The criterion for assessing the optimality is regarded as a granular integral whose integrand is a quadratic function of the state variables and control inputs. Using the relative-distance-measure (RDM) fuzzy interval arithmetic and calculus of variations, the optimal control law is presented as the fuzzy state variables feedback. Since the optimal feedback gains are obtained as fuzzy functions, they need to be defuzzified. This will result in the sub-optimal control law. This paper also sheds light on the restrictions imposed by the approaches which are based on fuzzy standard interval arithmetic (FSIA), and use strongly generalized Hukuhara and generalized Hukuhara differentiability concepts for obtaining the optimal control law. The granular eigenvalues notion is also defined. Using an RLC circuit mathematical model, it is shown that, due to their unnatural behavior in the modeling phenomenon, the FSIA-based approaches may obtain some eigenvalues sets that might be different from the inherent eigenvalues set of the fuzzy dynamical system. This is, however, not the case with the approach proposed in this study. The notions of granular controllability and granular stabilizability of the fuzzy linear dynamical system are also presented in this paper. Moreover, a sub-optimal control for regulating a Boeing 747 in longitudinal direction with uncertain initial conditions and parameters is gained. In addition, an uncertain suspension system of one of the four wheels of a bus is regulated using the sub-optimal control introduced in this paper. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Fuzzy cluster means algorithm for the diagnosis of confusable disease
... end platform while Microsoft Access was used as the database application. The system gives a measure of each disease within a set of confusable disease. The proposed system had a classification accuracy of 60%. Keywords: Artificial Intelligence, expert system Fuzzy cluster – means Algorithm, physician, Diagnosis ...
A NEURO FUZZY MODEL FOR THE INVESTIGATION OF ...
Several factors may contribute directly or indirectly to the structural failure of metallic pipes. The most important of which is corrosion. Corrosivity of pipes is not a directly measurable parameter as pipe corrosion is a very random phenomenon. The main aim of the present study is to develop a neuro-fuzzy model capable of ...
Control of a classical microtron and application of fuzzy logic
Krist, Pavel; Bila, Jiri
2011-01-01
Control problems of the classical microtron with a Kapitza type accelerating cavity were addressed. A fuzzy controller was used, which enabled the system to be controlled even though the accelerating voltage, whose setting is vital for maintaining the accelerator in the stable state, cannot not be measured
Ortega, Ivan; Coburn, Sean; Berg, Larry K.; Lantz, Kathy; Michalsky, Joseph; Ferrare, Richard A.; Hair, Johnathan W.; Hostetler, Chris A.; Volkamer, Rainer
2016-01-01
The multiannual global mean of aerosol optical depth at 550 nm (AOD_{550}) over land is ~0.19, and that over oceans is ~0.13. About 45 % of the Earth surface shows AOD_{550} smaller than 0.1. There is a need for measurement techniques that are optimized to measure aerosol optical properties under low AOD conditions. We present an inherently calibrated retrieval (i.e., no need for radiance calibration) to simultaneously measure AOD and the aerosol phase function parameter, g, based on measurements of azimuth distributions of the Raman scattering probability (RSP), the near-absolute rotational Raman scattering (RRS) intensity. We employ radiative transfer model simulations to show that for solar azimuth RSP measurements at solar elevation and solar zenith angle (SZA) smaller than 80°, RSP is insensitive to the vertical distribution of aerosols and maximally sensitive to changes in AOD and g under near-molecular scattering conditions. The University of Colorado two-dimensional Multi-AXis Differential Optical Absorption Spectroscopy (CU 2-D-MAX-DOAS) instrument was deployed as part of the Two Column Aerosol Project (TCAP) at Cape Cod, MA, during the summer of 2012 to measure direct sun spectra and RSP from scattered light spectra at solar relative azimuth angles (SRAAs) between 5 and 170°. During two case study days with (1) high aerosol load (17 July, 0.3 < AOD_{430} < 0.6) and (2) near-molecular scattering conditions (22 July, AOD_{430} < 0.13) we compare RSP-based retrievals of AOD_{430} and g with data from a co-located CIMEL sun photometer, Multi-Filter Rotating Shadowband Radiometer (MFRSR), and an airborne High Spectral Resolution Lidar (HSRL-2). The average difference (relative to DOAS) for AOD_{430} is +0.012 ± 0.023 (CIMEL), -0.012 ± 0.024 (MFRSR), -0.011 ± 0.014 (HSRL-2), and +0.023 ± 0.013 (CIMEL_{AOD} - MFRSR_{AOD}) and yields the following
Fuzzy logic of Aristotelian forms
Perlovsky, L.I. [Nichols Research Corp., Lexington, MA (United States)
1996-12-31
Model-based approaches to pattern recognition and machine vision have been proposed to overcome the exorbitant training requirements of earlier computational paradigms. However, uncertainties in data were found to lead to a combinatorial explosion of the computational complexity. This issue is related here to the roles of a priori knowledge vs. adaptive learning. What is the a-priori knowledge representation that supports learning? I introduce Modeling Field Theory (MFT), a model-based neural network whose adaptive learning is based on a priori models. These models combine deterministic, fuzzy, and statistical aspects to account for a priori knowledge, its fuzzy nature, and data uncertainties. In the process of learning, a priori fuzzy concepts converge to crisp or probabilistic concepts. The MFT is a convergent dynamical system of only linear computational complexity. Fuzzy logic turns out to be essential for reducing the combinatorial complexity to linear one. I will discuss the relationship of the new computational paradigm to two theories due to Aristotle: theory of Forms and logic. While theory of Forms argued that the mind cannot be based on ready-made a priori concepts, Aristotelian logic operated with just such concepts. I discuss an interpretation of MFT suggesting that its fuzzy logic, combining a-priority and adaptivity, implements Aristotelian theory of Forms (theory of mind). Thus, 2300 years after Aristotle, a logic is developed suitable for his theory of mind.
Erwin Arya Winanto; Imam Santoso
2017-01-01
This study aimed to identify, determine and formulate the mitigation strategies of shallot supply chain risk using Fuzzy FMEA and AHP. Risk identification was performed on shallot supply chain actors include farmers (suppliers), tengkulak (distributors) and pengecer (retailers). Fuzzy FMEA was used as a tool to measure the risks identified priorities. AHP was used as a tool for determining the weighting strategies in supply chain risk mitigation strategies. Research showed that there were som...
Study on application of adaptive fuzzy control and neural network in the automatic leveling system
Xu, Xiping; Zhao, Zizhao; Lan, Weiyong; Sha, Lei; Qian, Cheng
2015-04-01
This paper discusses the adaptive fuzzy control and neural network BP algorithm in large flat automatic leveling control system application. The purpose is to develop a measurement system with a flat quick leveling, Make the installation on the leveling system of measurement with tablet, to be able to achieve a level in precision measurement work quickly, improve the efficiency of the precision measurement. This paper focuses on the automatic leveling system analysis based on fuzzy controller, Use of the method of combining fuzzy controller and BP neural network, using BP algorithm improve the experience rules .Construct an adaptive fuzzy control system. Meanwhile the learning rate of the BP algorithm has also been run-rate adjusted to accelerate convergence. The simulation results show that the proposed control method can effectively improve the leveling precision of automatic leveling system and shorten the time of leveling.
An Alternative Estimation of Market Volatility based on Fuzzy Transform
Troiano, Luigi; Villa, Elena Mejuto; Kriplani, Pravesh
2017-01-01
Realization of uncertainty of prices is captured by volatility, that is the tendency of prices to vary along a period of time. This is generally measured as standard deviation of daily returns. In this paper we propose and investigate the application of fuzzy transform and its inverse as an alternative measure of volatility. The measure obtained is compatible with the definition of risk measure given by Luce. A comparison with standard definition is performed by considering the NIFTY 50 stock...
Implementing fuzzy polynomial interpolation (FPI and fuzzy linear regression (LFR
Maria Cristina Floreno
1996-05-01
Full Text Available This paper presents some preliminary results arising within a general framework concerning the development of software tools for fuzzy arithmetic. The program is in a preliminary stage. What has been already implemented consists of a set of routines for elementary operations, optimized functions evaluation, interpolation and regression. Some of these have been applied to real problems.This paper describes a prototype of a library in C++ for polynomial interpolation of fuzzifying functions, a set of routines in FORTRAN for fuzzy linear regression and a program with graphical user interface allowing the use of such routines.
Quick fuzzy backpropagation algorithm.
Nikov, A; Stoeva, S
2001-03-01
A modification of the fuzzy backpropagation (FBP) algorithm called QuickFBP algorithm is proposed, where the computation of the net function is significantly quicker. It is proved that the FBP algorithm is of exponential time complexity, while the QuickFBP algorithm is of polynomial time complexity. Convergence conditions of the QuickFBP, resp. the FBP algorithm are defined and proved for: (1) single output neural networks in case of training patterns with different targets; and (2) multiple output neural networks in case of training patterns with equivalued target vector. They support the automation of the weights training process (quasi-unsupervised learning) establishing the target value(s) depending on the network's input values. In these cases the simulation results confirm the convergence of both algorithms. An example with a large-sized neural network illustrates the significantly greater training speed of the QuickFBP rather than the FBP algorithm. The adaptation of an interactive web system to users on the basis of the QuickFBP algorithm is presented. Since the QuickFBP algorithm ensures quasi-unsupervised learning, this implies its broad applicability in areas of adaptive and adaptable interactive systems, data mining, etc. applications.
TOWARDS FINDING A NEW KERNELIZED FUZZY C-MEANS CLUSTERING ALGORITHM
Samarjit Das
2014-04-01
Full Text Available Kernelized Fuzzy C-Means clustering technique is an attempt to improve the performance of the conventional Fuzzy C-Means clustering technique. Recently this technique where a kernel-induced distance function is used as a similarity measure instead of a Euclidean distance which is used in the conventional Fuzzy C-Means clustering technique, has earned popularity among research community. Like the conventional Fuzzy C-Means clustering technique this technique also suffers from inconsistency in its performance due to the fact that here also the initial centroids are obtained based on the randomly initialized membership values of the objects. Our present work proposes a new method where we have applied the Subtractive clustering technique of Chiu as a preprocessor to Kernelized Fuzzy CMeans clustering technique. With this new method we have tried not only to remove the inconsistency of Kernelized Fuzzy C-Means clustering technique but also to deal with the situations where the number of clusters is not predetermined. We have also provided a comparison of our method with the Subtractive clustering technique of Chiu and Kernelized Fuzzy C-Means clustering technique using two validity measures namely Partition Coefficient and Clustering Entropy.
On Intuitionistic Fuzzy Context-Free Languages
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.
Schildt, G.H.
1997-01-01
A fuzzy controller for safety related process control is presented for applications in the field of NPPs. The size of necessary rules is relatively small. Thus, there exists a real chance for verification and validation of software due to the fact that the whole software can be structured into standard fuzzy software (like fuzzyfication, inference algorithms, and defuzzyfication), real-time operating system software, and the contents of the rule base. Furthermore, there is an excellent advantage fuel to real-time behaviour, because program execution time is much more predictable than for conventional PID-controller software. Additionally, up to now special know-how does exist to prove stability of fuzzy controller. Hardware design has been done due to fundamental principles of safety technique like watch dog function, dynamization principles, and quiescent current principle. (author). 3 refs, 5 figs
Schildt, G.H.
1996-01-01
After an introduction into safety terms a fuzzy controller for safety related process control will be presented, especially for applications in the field of NPPs. One can show that the size of necessary rules is relatively small. Thus, there exists a real chance for verification and validation of software due to the fact that the whole software can be structured into standard fuzzy software (like fuzzyfication, inference algorithms, and defuzzyfication), real-time operating system software, and the contents of the rule base. Furthermore, there is an excellent advantage due to real-time behaviour, because program execution time can be much more planned than for conventional PID-controller software. Additionally, up to now special know-how does exist to prove stability of fuzzy controller. Hardware design has been done due to fundamental principles of safety technique like watch dog function, dynamization principle, and quiescent current principle
Schildt, G H [Technische Univ., Vienna (Austria)
1997-07-01
A fuzzy controller for safety related process control is presented for applications in the field of NPPs. The size of necessary rules is relatively small. Thus, there exists a real chance for verification and validation of software due to the fact that the whole software can be structured into standard fuzzy software (like fuzzyfication, inference algorithms, and defuzzyfication), real-time operating system software, and the contents of the rule base. Furthermore, there is an excellent advantage fuel to real-time behaviour, because program execution time is much more predictable than for conventional PID-controller software. Additionally, up to now special know-how does exist to prove stability of fuzzy controller. Hardware design has been done due to fundamental principles of safety technique like watch dog function, dynamization principles, and quiescent current principle. (author). 3 refs, 5 figs.
Combining fuzzy mathematics with fuzzy logic to solve business management problems
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.
The quantum probability calculus
Jauch, J.M.
1976-01-01
The Wigner anomaly (1932) for the joint distribution of noncompatible observables is an indication that the classical probability calculus is not applicable for quantum probabilities. It should, therefore, be replaced by another, more general calculus, which is specifically adapted to quantal systems. In this article this calculus is exhibited and its mathematical axioms and the definitions of the basic concepts such as probability field, random variable, and expectation values are given. (B.R.H)
Choice Probability Generating Functions
Fosgerau, Mogens; McFadden, Daniel L; Bierlaire, Michel
This paper considers discrete choice, with choice probabilities coming from maximization of preferences from a random utility field perturbed by additive location shifters (ARUM). Any ARUM can be characterized by a choice-probability generating function (CPGF) whose gradient gives the choice...... probabilities, and every CPGF is consistent with an ARUM. We relate CPGF to multivariate extreme value distributions, and review and extend methods for constructing CPGF for applications....