Finding multiple possible critical paths using fuzzy PERT.
Chen, S M; Chang, T H
2001-01-01
Program evaluation and review techniques (PERT) is an efficient tool for large project management. In actual project control decisions, PERT has successfully been applied to business management, industry production, project scheduling control, logistics support, etc. However, classical PERT requires a crisp duration time representation for each activity. This requirement is often difficult for the decision-makers due to the fact that they usually can not estimate these values precisely. In recent years, some fuzzy PERT methods have been proposed based on fuzzy set theory for project management. However, there is a drawback in the existing fuzzy PERT methods, i.e., sometimes they maybe cannot find a critical path in a fuzzy project network. In this paper, we propose a fuzzy PERT algorithm to find multiple possible critical paths in a fuzzy project network, where the duration time of each activity in a fuzzy project network is represented by a fuzzy number. The proposed algorithm can overcome the drawback of the existing fuzzy PERT methods.
Nagoor Gani, A; Latha, S R
2016-01-01
A Hamiltonian cycle in a graph is a cycle that visits each node/vertex exactly once. A graph containing a Hamiltonian cycle is called a Hamiltonian graph. There have been several researches to find the number of Hamiltonian cycles of a Hamilton graph. As the number of vertices and edges grow, it becomes very difficult to keep track of all the different ways through which the vertices are connected. Hence, analysis of large graphs can be efficiently done with the assistance of a computer system that interprets graphs as matrices. And, of course, a good and well written algorithm will expedite the analysis even faster. The most convenient way to quickly test whether there is an edge between two vertices is to represent graphs using adjacent matrices. In this paper, a new algorithm is proposed to find fuzzy Hamiltonian cycle using adjacency matrix and the degree of the vertices of a fuzzy graph. A fuzzy graph structure is also modeled to illustrate the proposed algorithms with the selected air network of Indigo airlines.
Modeling and simulation of evacuation behavior using fuzzy logic in a goal finding application
Sharma, Sharad; Ogunlana, Kola; Sree, Swetha
2016-05-01
Modeling and simulation has been widely used as a training and educational tool for depicting different evacuation strategies and damage control decisions during evacuation. However, there are few simulation environments that can include human behavior with low to high levels of fidelity. It is well known that crowd stampede induced by panic leads to fatalities as people are crushed or trampled. Our proposed goal finding application can be used to model situations that are difficult to test in real-life due to safety considerations. It is able to include agent characteristics and behaviors. Findings of this model are very encouraging as agents are able to assume various roles to utilize fuzzy logic on the way to reaching their goals. Fuzzy logic is used to model stress, panic and the uncertainty of emotions. The fuzzy rules link these parts together while feeding into behavioral rules. The contributions of this paper lies in our approach of utilizing fuzzy logic to show learning and adaptive behavior of agents in a goal finding application. The proposed application will aid in running multiple evacuation drills for what-if scenarios by incorporating human behavioral characteristics that can scale from a room to building. Our results show that the inclusion of fuzzy attributes made the evacuation time of the agents closer to the real time drills.
A DNA sequence alignment algorithm using quality information and a fuzzy inference method
Institute of Scientific and Technical Information of China (English)
Kwangbaek Kim; Minhwan Kim; Youngwoon Woo
2008-01-01
DNA sequence alignment algorithms in computational molecular biology have been improved by diverse methods.In this paper.We propose a DNA sequence alignment that Uses quality information and a fuzzy inference method developed based on the characteristics of DNA fragments and a fuzzy logic system in order to improve conventional DNA sequence alignment methods that uses DNA sequence quality information.In conventional algorithms.DNA sequence alignment scores are calculated by the global sequence alignment algorithm proposed by Needleman-Wunsch,which is established by using quality information of each DNA fragment.However,there may be errors in the process of calculating DNA sequence alignment scores when the quality of DNA fragment tips is low.because only the overall DNA sequence quality information are used.In our proposed method.an exact DNA sequence alignment can be achieved in spite of the low quality of DNA fragment tips by improvement of conventional algorithms using quality information.Mapping score parameters used to calculate DNA sequence alignment scores are dynamically adjusted by the fuzzy logic system utilizing lengths of DNA fragments and frequencies of low quality DNA bases in the fragments.From the experiments by applying real genome data of National Center for Bioteclmology Information,we could see that the proposed method is more efficient than conventional algorithms.
Three fuzzy reasoning models as a decision suport aid, to find an electrical energy tariff
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Daniela GHINITA
2005-12-01
Full Text Available This contribution is a laboratory-work developed as an example of approximate (fuzzy reasoning for students, possible to be used as a decision – support to estimate an electrical energy (EE price for consumers. The three fuzzy tariff estimation models that are developed, integrate not only the S.C Electrica S.A.-single-supplier rate position, but and some (social constraints/ compulsions of National Authority of Settlements from Energy (NASE beginning with 1999, in this transition period from Romania. Although is possible, the paper not refer to a partial-price concrete case (internal tariff used in certain year, production price, transport price, distribution price, spot price, or an external price to be sold electrical energy, etc. This “laboratory-work-paper” shows how, by changing the parameters of S.C Electrica S.A. and NASE, it is possible to can perform sensitivity tests on the tariff function model, until can obtain an acceptable and true price. In this aim, the three fuzzy models use different rules for pricing: conservative, aggressive, and different order of words concerning the rules respectively, finally doing a comparation among prices and models. The paper not finished all fuzzy possibilities (rules which can influences the expected value of a some EE tariff but, with certitude, can create a discussion base, about the way of approximate/ fuzzy reasoning, as a modality to find and to refine an EE price.
Oral bacterial DNA findings in pericardial fluid
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Anne-Mari Louhelainen
2014-11-01
Full Text Available Background: We recently reported that large amounts of oral bacterial DNA can be found in thrombus aspirates of myocardial infarction patients. Some case reports describe bacterial findings in pericardial fluid, mostly done with conventional culturing and a few with PCR; in purulent pericarditis, nevertheless, bacterial PCR has not been used as a diagnostic method before. Objective: To find out whether bacterial DNA can be measured in the pericardial fluid and if it correlates with pathologic–anatomic findings linked to cardiovascular diseases. Methods: Twenty-two pericardial aspirates were collected aseptically prior to forensic autopsy at Tampere University Hospital during 2009–2010. Of the autopsies, 10 (45.5% were free of coronary artery disease (CAD, 7 (31.8% had mild and 5 (22.7% had severe CAD. Bacterial DNA amounts were determined using real-time quantitative PCR with specific primers and probes for all bacterial strains associated with endodontic disease (Streptococcus mitis group, Streptococcus anginosus group, Staphylococcus aureus/Staphylococcus epidermidis, Prevotella intermedia, Parvimonas micra and periodontal disease (Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Treponema denticola, Fusobacterium nucleatus, and Dialister pneumosintes. Results: Of 22 cases, 14 (63.6% were positive for endodontic and 8 (36.4% for periodontal-disease-associated bacteria. Only one case was positive for bacterial culturing. There was a statistically significant association between the relative amount of bacterial DNA in the pericardial fluid and the severity of CAD (p=0.035. Conclusions: Oral bacterial DNA was detectable in pericardial fluid and an association between the severity of CAD and the total amount of bacterial DNA in pericardial fluid was found, suggesting that this kind of measurement might be useful for clinical purposes.
Andryani, Diyah Septi; Bustamam, Alhadi; Lestari, Dian
2017-03-01
Clustering aims to classify the different patterns into groups called clusters. In this clustering method, we use n-mers frequency to calculate the distance matrix which is considered more accurate than using the DNA alignment. The clustering results could be used to discover biologically important sub-sections and groups of genes. Many clustering methods have been developed, while hard clustering methods considered less accurate than fuzzy clustering methods, especially if it is used for outliers data. Among fuzzy clustering methods, fuzzy c-means is one the best known for its accuracy and simplicity. Fuzzy c-means clustering uses membership function variable, which refers to how likely the data could be members into a cluster. Fuzzy c-means clustering works using the principle of minimizing the objective function. Parameters of membership function in fuzzy are used as a weighting factor which is also called the fuzzier. In this study we implement hybrid clustering using fuzzy c-means and divisive algorithm which could improve the accuracy of cluster membership compare to traditional partitional approach only. In this study fuzzy c-means is used in the first step to find partition results. Furthermore divisive algorithms will run on the second step to find sub-clusters and dendogram of phylogenetic tree. To find the best number of clusters is determined using the minimum value of Davies Bouldin Index (DBI) of the cluster results. In this research, the results show that the methods introduced in this paper is better than other partitioning methods. Finally, we found 3 clusters with DBI value of 1.126628 at first step of clustering. Moreover, DBI values after implementing the second step of clustering are always producing smaller IDB values compare to the results of using first step clustering only. This condition indicates that the hybrid approach in this study produce better performance of the cluster results, in term its DBI values.
Implementasi DNA Similarity Matching pada Perangkat Mobile dengan Sugeno Fuzzy Inference System
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Fahmi Akbar Saputra
2012-09-01
Full Text Available STR analysis merupakan teknik DNA profiling yang populer digunakan untuk mendapatkan profil DNA manusia yang bersifat unik dari sampel biologis yang didapatkan. Profil DNA tersebut terdiri dari beberapa lokus STR yang ditetapkan sebagai standar. Dalam praktiknya, permasalahan timbul ketika dalam proses analisis terjadi kontaminasi terhadap sampel biologis. Akibatnya, profil hasil proses analisis memiliki nilai ketidakpastian (uncertainty atau nilai pergeseran dan noise. Untuk permasalahan seperti ini, perangkat lunak bantu untuk proses pencocokan kemiripan DNA yang dikembangkan oleh National Institute of Standards and Technology (NIST, yaitu STR_MatchSamples, tidak mampu menangani. Hal ini dikarenakan STR_MatchSamples bekerja dengan logika crisp, sedangkan data profil DNA memiliki nilai-nilai ketidakpastian. Maka, untuk mengatasi permasalahan ketidakpastian pada profil DNA, digunakan sebuah metode fuzzy untuk pencocokan kemiripan DNA, yaitu sistem inferensi fuzzy Sugeno. Pada paper ini diberikan penjelasan mengenai metode sistem inferensi fuzzy Sugeno sebagai metode untuk pencocokan kemiripan DNA beserta implementasinya sebagai aplikasi web service yang bekerja pada sebuah server. Aplikasi tersebut dapat diakses oleh perangkat mobile bersistem operasi Android sebagai client aplikasi web service tersebut.
A fuzzy-set-theory-based approach to analyse species membership in DNA barcoding.
Zhang, A-B; Muster, C; Liang, H-B; Zhu, C-D; Crozier, R; Wan, P; Feng, J; Ward, R D
2012-04-01
Reliable assignment of an unknown query sequence to its correct species remains a methodological problem for the growing field of DNA barcoding. While great advances have been achieved recently, species identification from barcodes can still be unreliable if the relevant biodiversity has been insufficiently sampled. We here propose a new notion of species membership for DNA barcoding-fuzzy membership, based on fuzzy set theory-and illustrate its successful application to four real data sets (bats, fishes, butterflies and flies) with more than 5000 random simulations. Two of the data sets comprise especially dense species/population-level samples. In comparison with current DNA barcoding methods, the newly proposed minimum distance (MD) plus fuzzy set approach, and another computationally simple method, 'best close match', outperform two computationally sophisticated Bayesian and BootstrapNJ methods. The new method proposed here has great power in reducing false-positive species identification compared with other methods when conspecifics of the query are absent from the reference database.
Finding optimal step of fuzzy Newton-Cotes integration rules by using the CESTAC method
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Samad Noeiaghdam
2017-08-01
Full Text Available The aim of this work, is to evaluate the value of a fuzzy integral by applying the Newton-Cotes integration rules via a reliable scheme. In order to perform the numerical examples, the CADNA (Control of Accuracy and Debugging for Numerical Applications library and the CESTAC (Controle et Estimation Stochastique des Arrondis de Calculs method are applied based on the stochastic arithmetic. By using this method, the optimal number of points in the fuzzy numerical integration rules and the optimal approximate solution are obtained. Also, the accuracy of the fuzzy quadrature rules are discussed. An algorithm is given to illustrate the implementation of the method. In this case, the termination criterion is considered as the Hausdorff distance between two sequential results to be an informatical zero. Two sample fuzzy integrals are evaluated based on the proposed algorithm to show the importance and advantage of using the stochastic arithmetic in place of the floating-point arithmetic.
Construction of a fuzzy and Boolean logic gates based on DNA.
Zadegan, Reza M; Jepsen, Mette D E; Hildebrandt, Lasse L; Birkedal, Victoria; Kjems, Jørgen
2015-04-17
Logic gates are devices that can perform logical operations by transforming a set of inputs into a predictable single detectable output. The hybridization properties, structure, and function of nucleic acids can be used to make DNA-based logic gates. These devices are important modules in molecular computing and biosensing. The ideal logic gate system should provide a wide selection of logical operations, and be integrable in multiple copies into more complex structures. Here we show the successful construction of a small DNA-based logic gate complex that produces fluorescent outputs corresponding to the operation of the six Boolean logic gates AND, NAND, OR, NOR, XOR, and XNOR. The logic gate complex is shown to work also when implemented in a three-dimensional DNA origami box structure, where it controlled the position of the lid in a closed or open position. Implementation of multiple microRNA sensitive DNA locks on one DNA origami box structure enabled fuzzy logical operation that allows biosensing of complex molecular signals. Integrating logic gates with DNA origami systems opens a vast avenue to applications in the fields of nanomedicine for diagnostics and therapeutics.
Lim, Joon S
2009-03-01
Fuzzy neural networks (FNNs) have been successfully applied to generate predictive rules for medical or diagnostic data. This brief presents an approach to detect premature ventricular contractions (PVCs) using the neural network with weighted fuzzy membership functions (NEWFMs). The NEWFM classifies normal and PVC beats by the trained bounded sum of weighted fuzzy membership functions (BSWFMs) using wavelet transformed coefficients from the MIT-BIH PVC database. The eight generalized coefficients, locally related to the time signal, are extracted by the nonoverlap area distribution measurement method. The eight generalized coefficients are used for the three PVC data sets with reliable accuracy rates of 99.80%, 99.21%, and 98.78%, respectively, which means that the selected features are less dependent on the data sets. It is shown that the locations of the eight features are not only around the QRS complex that represents ventricular depolarization in the electrocardiogram (ECG) containing a Q wave, an R wave, and an S wave, but also the QR segment from the Q wave to the R wave has more discriminate information than the RS segment from the R wave to the S wave. The BSWFMs of the eight features trained by NEWFM are shown visually, which makes the features explicitly interpretable. Since each BSWFM combines multiple weighted fuzzy membership functions into one using the bounded sum, the eight small-sized BSWFMs can realize real-time PVC detection in a mobile environment.
Optimal Design of TS Fuzzy Control System Based on DNA Evolutionary Algorithm%采用DNA进化算法优化设计TS模糊控制器
Institute of Scientific and Technical Information of China (English)
翁妙凤
2003-01-01
The DNA evolutionary algorithm(DNA-EA)and the DNA genetic algorithm(DNA-GA)based on a new DNA encoding method are propsed based on the structure and the genetic mechanism of biological DNA. The DNA-EA and the DNA-GA are applied into the optimal design of TS fuzzy control system. The simulation results show the effectiveness of the two DNA algorithms, excellent self-learning capability. However, the DNA-EA is superior to the DNA-GA in the simulation performance.
Finding human promoter groups based on DNA physical properties
Zeng, Jia; Cao, Xiao-Qin; Zhao, Hongya; Yan, Hong
2009-10-01
DNA rigidity is an important physical property originating from the DNA three-dimensional structure. Although the general DNA rigidity patterns in human promoters have been investigated, their distinct roles in transcription are largely unknown. In this paper, we discover four highly distinct human promoter groups based on similarity of their rigidity profiles. First, we find that all promoter groups conserve relatively rigid DNAs at the canonical TATA box [a consensus TATA(A/T)A(A/T) sequence] position, which are important physical signals in binding transcription factors. Second, we find that the genes activated by each group of promoters share significant biological functions based on their gene ontology annotations. Finally, we find that these human promoter groups correlate with the tissue-specific gene expression.
Finding human promoter groups based on DNA physical properties.
Zeng, Jia; Cao, Xiao-Qin; Zhao, Hongya; Yan, Hong
2009-10-01
DNA rigidity is an important physical property originating from the DNA three-dimensional structure. Although the general DNA rigidity patterns in human promoters have been investigated, their distinct roles in transcription are largely unknown. In this paper, we discover four highly distinct human promoter groups based on similarity of their rigidity profiles. First, we find that all promoter groups conserve relatively rigid DNAs at the canonical TATA box [a consensus TATA(A/T)A(A/T) sequence] position, which are important physical signals in binding transcription factors. Second, we find that the genes activated by each group of promoters share significant biological functions based on their gene ontology annotations. Finally, we find that these human promoter groups correlate with the tissue-specific gene expression.
a Modified Genetic Algorithm for Finding Fuzzy Shortest Paths in Uncertain Networks
Heidari, A. A.; Delavar, M. R.
2016-06-01
In realistic network analysis, there are several uncertainties in the measurements and computation of the arcs and vertices. These uncertainties should also be considered in realizing the shortest path problem (SPP) due to the inherent fuzziness in the body of expert's knowledge. In this paper, we investigated the SPP under uncertainty to evaluate our modified genetic strategy. We improved the performance of genetic algorithm (GA) to investigate a class of shortest path problems on networks with vague arc weights. The solutions of the uncertain SPP with considering fuzzy path lengths are examined and compared in detail. As a robust metaheuristic, GA algorithm is modified and evaluated to tackle the fuzzy SPP (FSPP) with uncertain arcs. For this purpose, first, a dynamic operation is implemented to enrich the exploration/exploitation patterns of the conventional procedure and mitigate the premature convergence of GA technique. Then, the modified GA (MGA) strategy is used to resolve the FSPP. The attained results of the proposed strategy are compared to those of GA with regard to the cost, quality of paths and CPU times. Numerical instances are provided to demonstrate the success of the proposed MGA-FSPP strategy in comparison with GA. The simulations affirm that not only the proposed technique can outperform GA, but also the qualities of the paths are effectively improved. The results clarify that the competence of the proposed GA is preferred in view of quality quantities. The results also demonstrate that the proposed method can efficiently be utilized to handle FSPP in uncertain networks.
Fuzzy Boundary and Fuzzy Semiboundary
Athar, M.; Ahmad, B.
2008-01-01
We present several properties of fuzzy boundary and fuzzy semiboundary which have been supported by examples. Properties of fuzzy semi-interior, fuzzy semiclosure, fuzzy boundary, and fuzzy semiboundary have been obtained in product-related spaces. We give necessary conditions for fuzzy continuous (resp., fuzzy semicontinuous, fuzzy irresolute) functions. Moreover, fuzzy continuous (resp., fuzzy semicontinuous, fuzzy irresolute) functions have been characterized via fuzzy-derived (resp., fuzz...
Fuzzy logic sensing of G-quadruplex DNA and its cleavage reagents based on reduced graphene oxide.
Huang, Wei Tao; Zhang, Jian Rong; Xie, Wan Yi; Shi, Yan; Luo, Hong Qun; Li, Nian Bing
2014-07-15
Herein, by combining the merits of nanotechnology and fuzzy logic theory, we develop a simple, label-free, and general strategy based on an organic dye-graphene hybrid system for fluorescence intelligent sensing of G-quadruplexes (G4) formation, hydroxyl radical (HO∙), and Fe(2+) in vitro. By exploiting acridine orange (AO) dyes-graphene as a nanofilter and nanoswitch and the ability of graphene to interact with DNA with different structures, our approach can efficiently distinguish, quantitatively detect target analytes. In vitro assays with G4DNA demonstrated increases in fluorescence intensity of the AO-rGO system with a linear range of 16-338 nM and a detection limit as low as 2.0 nM. The requenched fluorescence of the G4TBA-AO-rGO system has a non-linear response to Fenton reagent. But this requenching reduces the fluorescence intensity in a manner proportional to the logarithm to the base 10 of the concentration of Fenton reagent in the range of 0.1-100 μM and 100-2000 μM, respectively. Furthermore, we develop a novel and intelligent sensing method based on fuzzy logic which mimics human reasoning, solves complex and non-linear problems, and transforms the numerical output into the language description output for potential application in biochemical systems, environmental monitoring systems, and molecular-level fuzzy logic computing system.
Poorbagher, Hadi; Moghaddam, Maryam Nasrollahpour; Eagderi, Soheil; Farahmand, Hamid
2016-07-01
The DNA breakage has been widely used in ecotoxicological studies to investigate effects of pesticides in fishes. The present study used a fuzzy inference system to quantify the breakage of DNA double strand in Aphanius sophiae exposed to the cypermethrin. The specimens were adapted to different temperatures and salinity for 14 days and then exposed to cypermethrin. DNA of each specimens were extracted, electrophoresed and photographed. A fuzzy system with three input variables and 27 rules were defined. The pixel value curve of DNA on each gel lane was obtained using ImageJ. The DNA breakage was quantified using the pixel value curve and fuzzy system. The defuzzified values were analyzed using a three-way analysis of variance. Cypermethrin had significant effects on DNA breakage. Fuzzy inference systems can be used as a tool to quantify the breakage of double strand DNA. DNA double strand of the gill of A. sophiae is sensitive enough to be used to detect cypermethrin in surface waters in concentrations much lower than those reported in previous studies.
The fuzzy space construction kit
Sykora, Andreas
2016-01-01
Fuzzy spaces like the fuzzy sphere or the fuzzy torus have received remarkable attention, since they appeared as objects in string theory. Although there are higher dimensional examples, the most known and most studied fuzzy spaces are realized as matrix algebras defined by three Hermitian matrices, which may be seen as fuzzy membrane or fuzzy surface. We give a mapping between directed graphs and matrix algebras defined by three Hermitian matrices and show that the matrix algebras of known two-dimensional fuzzy spaces are associated with unbranched graphs. By including branchings into the graphs we find matrix algebras that represent fuzzy spaces associated with surfaces having genus 2 and higher.
Energy Technology Data Exchange (ETDEWEB)
Lee, E.T.
1983-01-01
Algorithms for the construction of the Chomsky and Greibach normal forms for a fuzzy context-free grammar using the algebraic approach are presented and illustrated by examples. The results obtained in this paper may have useful applications in fuzzy languages, pattern recognition, information storage and retrieval, artificial intelligence, database and pictorial information systems. 16 references.
New scoring schema for finding motifs in DNA Sequences
Directory of Open Access Journals (Sweden)
Nowzari-Dalini Abbas
2009-03-01
Full Text Available Abstract Background Pattern discovery in DNA sequences is one of the most fundamental problems in molecular biology with important applications in finding regulatory signals and transcription factor binding sites. An important task in this problem is to search (or predict known binding sites in a new DNA sequence. For this reason, all subsequences of the given DNA sequence are scored based on an scoring function and the prediction is done by selecting the best score. By assuming no dependency between binding site base positions, most of the available tools for known binding site prediction are designed. Recently Tomovic and Oakeley investigated the statistical basis for either a claim of dependence or independence, to determine whether such a claim is generally true, and they presented a scoring function for binding site prediction based on the dependency between binding site base positions. Our primary objective is to investigate the scoring functions which can be used in known binding site prediction based on the assumption of dependency or independency in binding site base positions. Results We propose a new scoring function based on the dependency between all positions in biding site base positions. This scoring function uses joint information content and mutual information as a measure of dependency between positions in transcription factor binding site. Our method for modeling dependencies is simply an extension of position independency methods. We evaluate our new scoring function on the real data sets extracted from JASPAR and TRANSFAC data bases, and compare the obtained results with two other well known scoring functions. Conclusion The results demonstrate that the new approach improves known binding site discovery and show that the joint information content and mutual information provide a better and more general criterion to investigate the relationships between positions in the TFBS. Our scoring function is formulated by simple
GÜNER, Erdal
2007-01-01
Abstract. In this paper, .rstly some fundamental concepts are included re- lating to fuzzy topological spaces. Secondly, the fuzzy connected set is intro- duced. Finally, de.ning fuzzy contractible space, it is shown that X is a fuzzy contractible space if and only if X is fuzzy homotopic equivalent with a fuzzy single-point space.
Finding DNA Ends within a Haystack of Chromatin.
Banerjee, Ujjwal; Soutoglou, Evi
2016-09-01
Identifying DNA fragile sites is crucial to reveal hotspots of genomic rearrangements, yet their precise mapping has been a challenge. A new study in this issue of Molecular Cell (Canela et al., 2016) introduces a highly sensitive and accurate method to detect DNA breaks in vivo that can be adapted to various experimental and clinical settings.
Measurement of word frequencies in genomic DNA sequences based on partial alignment and fuzzy set.
Shida, Fumiya; Mizuta, Satoshi
2014-08-01
Accompanied with the rapid increase of the amount of data registered in the databases of biological sequences, the need for a fast method of sequence comparison applicable to sequences of large size is also increasing. In general, alignment is used for sequence comparison. However, the alignment may not be appropriate for comparison of sequences of large size such as whole genome sequences due to its large time complexity. In this article, we propose a semi alignment-free method of sequence comparison based on word frequency distributions, in which we partially use the alignment to measure word frequencies along with the idea of fuzzy set theory. Experiments with ten bacterial genome sequences demonstrated that the fuzzy measurements has the effect that facilitates discrimination between close relatives and distant relatives.
A Novel Weak Fuzzy Solution for Fuzzy Linear System
Directory of Open Access Journals (Sweden)
Soheil Salahshour
2016-03-01
Full Text Available This article proposes a novel weak fuzzy solution for the fuzzy linear system. As a matter of fact, we define the right-hand side column of the fuzzy linear system as a piecewise fuzzy function to overcome the related shortcoming, which exists in the previous findings. The strong point of this proposal is that the weak fuzzy solution is always a fuzzy number vector. Two complex and non-complex linear systems under uncertainty are tested to validate the effectiveness and correctness of the presented method.
Fuzzy Modeling for Uncertainty Nonlinear Systems with Fuzzy Equations
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Raheleh Jafari
2017-01-01
Full Text Available The uncertain nonlinear systems can be modeled with fuzzy equations by incorporating the fuzzy set theory. In this paper, the fuzzy equations are applied as the models for the uncertain nonlinear systems. The nonlinear modeling process is to find the coefficients of the fuzzy equations. We use the neural networks to approximate the coefficients of the fuzzy equations. The approximation theory for crisp models is extended into the fuzzy equation model. The upper bounds of the modeling errors are estimated. Numerical experiments along with comparisons demonstrate the excellent behavior of the proposed method.
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.
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.
An Efficient Approach in Analysis of DNA Base Calling Using Neural Fuzzy Model
2017-01-01
This paper presented the issues of true representation and a reliable measure for analyzing the DNA base calling is provided. The method implemented dealt with the data set quality in analyzing DNA sequencing, it is investigating solution of the problem of using Neurofuzzy techniques for predicting the confidence value for each base in DNA base calling regarding collecting the data for each base in DNA, and the simulation model of designing the ANFIS contains three subsystems and main system; obtain the three features from the subsystems and in the main system and use the three features to predict the confidence value for each base. This is achieving effective results with high performance in employment. PMID:28261268
An Improved Fuzzy Based Missing Value Estimation in DNA Microarray Validated by Gene Ranking
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Sujay Saha
2016-01-01
Full Text Available Most of the gene expression data analysis algorithms require the entire gene expression matrix without any missing values. Hence, it is necessary to devise methods which would impute missing data values accurately. There exist a number of imputation algorithms to estimate those missing values. This work starts with a microarray dataset containing multiple missing values. We first apply the modified version of the fuzzy theory based existing method LRFDVImpute to impute multiple missing values of time series gene expression data and then validate the result of imputation by genetic algorithm (GA based gene ranking methodology along with some regular statistical validation techniques, like RMSE method. Gene ranking, as far as our knowledge, has not been used yet to validate the result of missing value estimation. Firstly, the proposed method has been tested on the very popular Spellman dataset and results show that error margins have been drastically reduced compared to some previous works, which indirectly validates the statistical significance of the proposed method. Then it has been applied on four other 2-class benchmark datasets, like Colorectal Cancer tumours dataset (GDS4382, Breast Cancer dataset (GSE349-350, Prostate Cancer dataset, and DLBCL-FL (Leukaemia for both missing value estimation and ranking the genes, and the results show that the proposed method can reach 100% classification accuracy with very few dominant genes, which indirectly validates the biological significance of the proposed method.
Construction of a fuzzy and all Boolean logic gates based on DNA
DEFF Research Database (Denmark)
M. Zadegan, Reza; Jepsen, Mette D E; Hildebrandt, Lasse
2015-01-01
computing and biosensing. The ideal logic gate system should provide a wide selection of logical operations, and be integrable in multiple copies into more complex structures. Here we show the successful construction of a small DNA-based logic gate complex that produces fluorescent outputs corresponding......Logic gates are devices that can perform logical operations by transforming a set of inputs into a predictable single detectable output. The hybridization properties, structure, and function of nucleic acids can be used to make DNA-based logic gates. These devices are important modules in molecular...... to the operation of the six Boolean logic gates AND, NAND, OR, NOR, XOR, and XNOR. The logic gate complex is shown to work also when implemented in a three-dimensional DNA origami box structure, where it controlled the position of the lid in a closed or open position. Implementation of multiple microRNA sensitive...
Fuzzy Set Field and Fuzzy Metric
Gebru Gebray; B. Krishna Reddy
2014-01-01
The notation of fuzzy set field is introduced. A fuzzy metric is redefined on fuzzy set field and on arbitrary fuzzy set in a field. The metric redefined is between fuzzy points and constitutes both fuzziness and crisp property of vector. In addition, a fuzzy magnitude of a fuzzy point in a field is defined.
Chaira, Tamalika
2014-06-01
In this paper automatic leukocyte segmentation in pathological blood cell images is proposed using intuitionistic fuzzy and interval Type II fuzzy set theory. This is done to count different types of leukocytes for disease detection. Also, the segmentation should be accurate so that the shape of the leukocytes is preserved. So, intuitionistic fuzzy set and interval Type II fuzzy set that consider either more number of uncertainties or a different type of uncertainty as compared to fuzzy set theory are used in this work. As the images are considered fuzzy due to imprecise gray levels, advanced fuzzy set theories may be expected to give better result. A modified Cauchy distribution is used to find the membership function. In intuitionistic fuzzy method, non-membership values are obtained using Yager's intuitionistic fuzzy generator. Optimal threshold is obtained by minimizing intuitionistic fuzzy divergence. In interval type II fuzzy set, a new membership function is generated that takes into account the two levels in Type II fuzzy set using probabilistic T co norm. Optimal threshold is selected by minimizing a proposed Type II fuzzy divergence. Though fuzzy techniques were applied earlier but these methods failed to threshold multiple leukocytes in images. Experimental results show that both interval Type II fuzzy and intuitionistic fuzzy methods perform better than the existing non-fuzzy/fuzzy methods but interval Type II fuzzy thresholding method performs little bit better than intuitionistic fuzzy method. Segmented leukocytes in the proposed interval Type II fuzzy method are observed to be distinct and clear.
2010-05-01
the world of logic than friction in mechanics. — Charles Sanders Peirce 1 Rational deterrence theory rests on the foundation that...4 Kosko, Fuzzy Thinking, 4-17. 5 Daniel McNeill and Paul Freiberger, Fuzzy Logic: The Revolutionary Computer Technology That Is Changing Our...1 McNeill and Freiberger, Fuzzy Logic, 174. 2 Yarger, Little Book on Big Strategy, 16. 3 Mukaidono, Fuzzy Logic for
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 Cores and Fuzzy Balancedness
van Gulick, G.; Norde, H.W.
2011-01-01
We study the relation between the fuzzy core and balancedness for fuzzy games. For regular games, this relation has been studied by Bondareva (1963) and Shapley (1967). First, we gain insight in this relation when we analyse situations where the fuzzy game is continuous. Our main result shows that a
Fuzzy Cores and Fuzzy Balancedness
van Gulick, G.; Norde, H.W.
2011-01-01
We study the relation between the fuzzy core and balancedness for fuzzy games. For regular games, this relation has been studied by Bondareva (1963) and Shapley (1967). First, we gain insight in this relation when we analyse situations where the fuzzy game is continuous. Our main result shows that
Peterson, Leif E; Coleman, Matthew A
2008-01-01
Receiver operating characteristic (ROC) curves were generated to obtain classification area under the curve (AUC) as a function of feature standardization, fuzzification, and sample size from nine large sets of cancer-related DNA microarrays. Classifiers used included k nearest neighbor (kNN), näive Bayes classifier (NBC), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), learning vector quantization (LVQ1), logistic regression (LOG), polytomous logistic regression (PLOG), artificial neural networks (ANN), particle swarm optimization (PSO), constricted particle swarm optimization (CPSO), kernel regression (RBF), radial basis function networks (RBFN), gradient descent support vector machines (SVMGD), and least squares support vector machines (SVMLS). For each data set, AUC was determined for a number of combinations of sample size, total sum[-log(p)] of feature t-tests, with and without feature standardization and with (fuzzy) and without (crisp) fuzzification of features. Altogether, a total of 2,123,530 classification runs were made. At the greatest level of sample size, ANN resulted in a fitted AUC of 90%, while PSO resulted in the lowest fitted AUC of 72.1%. AUC values derived from 4NN were the most dependent on sample size, while PSO was the least. ANN depended the most on total statistical significance of features used based on sum[-log(p)], whereas PSO was the least dependent. Standardization of features increased AUC by 8.1% for PSO and -0.2% for QDA, while fuzzification increased AUC by 9.4% for PSO and reduced AUC by 3.8% for QDA. AUC determination in planned microarray experiments without standardization and fuzzification of features will benefit the most if CPSO is used for lower levels of feature significance (i.e., sum[-log(p)] ~ 50) and ANN is used for greater levels of significance (i.e., sum[-log(p)] ~ 500). When only standardization of features is performed, studies are likely to benefit most by using CPSO for low levels
Fuzzy Ideals and Fuzzy Distributive Lattices%Fuzzy Ideals and Fuzzy Distributive Lattices*
Institute of Scientific and Technical Information of China (English)
S.H.Dhanani; Y. S. Pawar
2011-01-01
Our main objective is to study properties of a fuzzy ideals (fuzzy dual ideals). A study of special types of fuzzy ideals (fuzzy dual ideals) is also furnished. Some properties of a fuzzy ideals (fuzzy dual ideals) are furnished. Properties of a fuzzy lattice homomorphism are discussed. Fuzzy ideal lattice of a fuzzy lattice is defined and discussed. Some results in fuzzy distributive lattice are proved.
Stepančič, Ziva
2014-10-01
Finding short patterns with residue variation in a set of sequences is still an open problem in genetics, since motif-finding techniques on DNA and protein sequences are inconclusive on real data sets and their performance varies on different species. Hence, finding new algorithms and evolving established methods are vital to further understanding of genome properties and the mechanisms of protein development. In this work, we present an approach to finding functional motifs in DNA sequences in connection to Gibbs sampling method. Starting points in the search space are partly determined via graphical representation of input sequences opposed to completely random initial points with the standard Gibbs sampling. Our algorithm is evaluated on synthetic as well as on real data sets by using several statistics, such as sensitivity, positive predictive value, specificity, performance, and correlation coefficient. Additionally, a comparison between our algorithm and the basic standard Gibbs sampling algorithm is made to show improvement in accuracy, repeatability, and performance.
On Fuzzy Simplex and Fuzzy Convex Hull
Institute of Scientific and Technical Information of China (English)
Dong QIU; Wei Quan ZHANG
2011-01-01
In this paper,we discuss fuzzy simplex and fuzzy convex hull,and give several representation theorems for fuzzy simplex and fuzzy convex hull.In addition,by giving a new characterization theorem of fuzzy convex hull,we improve some known results about fuzzy convex hull.
The Fuzzy Set by Fuzzy Interval
Dr.Pranita Goswami
2011-01-01
Fuzzy set by Fuzzy interval is atriangular fuzzy number lying between the two specified limits. The limits to be not greater than 2 and less than -2 by fuzzy interval have been discussed in this paper. Through fuzzy interval we arrived at exactness which is a fuzzymeasure and fuzzy integral
Directory of Open Access Journals (Sweden)
Mikael Collan
2015-01-01
Full Text Available This paper introduces new closeness coefficients for fuzzy similarity based TOPSIS. The new closeness coefficients are based on multidistance or fuzzy entropy, are able to take into consideration the level of similarity between analysed criteria, and can be used to account for the consistency or homogeneity of, for example, performance measuring criteria. The commonly known OWA operator is used in the aggregation process over the fuzzy similarity values. A range of orness values is considered in creating a fuzzy overall ranking for each object, after which the fuzzy rankings are ordered to find a final linear ranking. The presented method is numerically applied to a research and development project selection problem and the effect of using two new closeness coefficients based on multidistance and fuzzy entropy is numerically illustrated.
Computing the eigenvalues and eigenvectors of a fuzzy matrix
Directory of Open Access Journals (Sweden)
A. Kumar
2012-08-01
Full Text Available Computation of fuzzy eigenvalues and fuzzy eigenvectors of a fuzzy matrix is a challenging problem. Determining the maximal and minimal symmetric solution can help to find the eigenvalues. So, we try to compute these eigenvalues by determining the maximal and minimal symmetric solution of the fully fuzzy linear system $widetilde{A}widetilde{X}= widetilde{lambda} widetilde{X}.$
Minimal solution of singular LR fuzzy linear systems.
Nikuie, M; Ahmad, M Z
2014-01-01
In this paper, the singular LR fuzzy linear system is introduced. Such systems are divided into two parts: singular consistent LR fuzzy linear systems and singular inconsistent LR fuzzy linear systems. The capability of the generalized inverses such as Drazin inverse, pseudoinverse, and {1}-inverse in finding minimal solution of singular consistent LR fuzzy linear systems is investigated.
Incidental findings in the use of DNA to identify human remains: an ethical assessment.
Parker, Lisa S; London, Alex John; Aronson, Jay D
2013-02-01
DNA analysis is increasingly used to identify the remains of victims of conflicts and disasters. This is especially true in cases where remains are badly damaged and fragmented, or where antemortem records are unavailable. Incidental findings (IFs)-that is, genetics-related information for which investigators were not looking-may result from these identification efforts employing DNA analysis. Because of the critical role played by family members of the missing in identification efforts, as well as the familial nature of DNA, identification initiatives employing DNA analysis are particularly prone to reveal IFs about familial relationships, such as misattributed paternity or false beliefs about sibling relationships. Despite forensic scientists' widespread awareness of the possibility of generating IFs, to date there has been relatively little explicit guidance about their management. This paper fills that gap. It offers substantive guidance about the ethical management of IFs in this context. To ensure that the analysis addresses actual needs and practices in the field, one author (JDA) conducted semi-structured interviews with key informants from six regionally diverse organizations involved in post-conflict or post-disaster identification efforts. The paper first describes how methods of DNA analysis give rise to IFs. Next, it explains the importance of developing an ethically justified general policy for managing IFs and discusses features of DNA identification efforts that are relevant to such a policy. Then it presents an argument in support of a general policy of nondisclosure-specifically, that considerations of fair access to the individual and social benefits of identification efforts, and the concern to minimize and fairly distribute the risks of participation, support a policy of nondisclosure. It concludes by considering some implications of this argument for the choice among scientific practices involved in using DNA analysis to identify human remains
Incidental Findings in the Use of DNA to Identify Human Remains: An Ethical Assessment
Parker, Lisa S.; Aronson, Jay D.
2012-01-01
DNA analysis is increasingly used to identify the remains of victims of conflicts and disasters. This is especially true in cases where remains are badly damaged and fragmented, or where antemortem records are unavailable. Incidental findings (IFs)—that is, genetics-related information for which investigators were not looking—may result from these identification efforts employing DNA analysis. Because of the critical role played by family members of the missing in identification efforts, as well as the familial nature of DNA, identification initiatives employing DNA analysis are particularly prone to reveal IFs about familial relationships, such as misattributed paternity or false beliefs about sibling relationships. Despite forensic scientists’ widespread awareness of the possibility of generating IFs, to date there has been relatively little explicit guidance about their management. This paper fills that gap. It offers substantive guidance about the ethical management of IFs in this context. To ensure that the analysis addresses actual needs and practices in the field, one author (JDA) conducted semi-structured interviews with key informants from six regionally diverse organizations involved in post-conflict or post-disaster identification efforts. The paper first describes how methods of DNA analysis give rise to IFs. Next, it explains the importance of developing an ethically justified general policy for managing IFs and discusses features of DNA identification efforts that are relevant to such a policy. Then it presents an argument in support of a general policy of nondisclosure—specifically, that considerations of fair access to the individual and social benefits of identification efforts, and the concern to minimize and fairly distribute the risks of participation, support a policy of nondisclosure. It concludes by considering some implications of this argument for the choice among scientific practices involved in using DNA analysis to identify human
Egalitarianism in Convex Fuzzy Games
Brânzei, R.; Dimitrov, D.A.; Tijs, S.H.
2002-01-01
In this paper the egalitarian solution for convex cooperative fuzzy games is introduced.The classical Dutta-Ray algorithm for finding the constrained egalitarian solution for convex crisp games is adjusted to provide the egalitarian solution of a convex fuzzy game.This adjusted algorithm is also a f
Fuzzy Riesz subspaces, fuzzy ideals, fuzzy bands and fuzzy band projections
Hong Liang
2015-01-01
Fuzzy ordered linear spaces, Riesz spaces, fuzzy Archimedean spaces and $\\sigma$-complete fuzzy Riesz spaces were defined and studied in several works. Following the efforts along this line, we define fuzzy Riesz subspaces, fuzzy ideals, fuzzy bands and fuzzy band projections and establish their fundamental properties.
FFLP problem with symmetric trapezoidal fuzzy numbers
Directory of Open Access Journals (Sweden)
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.
Directory of Open Access Journals (Sweden)
Abdul Hameed Q. A. Al-Tai
2011-01-01
Full Text Available The aim of this paper is to introduce and study the fuzzy neighborhood, the limit fuzzy number, the convergent fuzzy sequence, the bounded fuzzy sequence, and the Cauchy fuzzy sequence on the base which is adopted by Abdul Hameed (every real number r is replaced by a fuzzy number r¯ (either triangular fuzzy number or singleton fuzzy set (fuzzy point. And then, we will consider that some results respect effect of the upper sequence on the convergent fuzzy sequence, the bounded fuzzy sequence, and the Cauchy fuzzy sequence.
Zadeh, Lofti A.
1988-01-01
The author presents a condensed exposition of some basic ideas underlying fuzzy logic and describes some representative applications. The discussion covers basic principles; meaning representation and inference; basic rules of inference; and the linguistic variable and its application to fuzzy control.
DEFF Research Database (Denmark)
Anker, Thomas Boysen; Kappel, Klemens; Eadie, Douglas
2012-01-01
This article clarifies the commonplace assumption that brands make promises by developing definitions of brand promise delivery. Distinguishing between clear and fuzzy brand promises, we develop definitions of what it is for a brand to deliver on fuzzy functional, symbolic, and experiential...
Factors associated with trace evidence analysis and DNA findings among police reported cases of rape
Forr, Camilla
2016-01-01
Background: The medical examination after rapes has two main goals: to provide high-quality care for the victim and to collect evidence to be used in the crime investigation. Collected samples are sent for forensic analysis upon police request. However, little is known about how the police select cases to be submitted for analysis. Furthermore, few studies report the DNA findings and associated factors. The aim of this study was to examine whether victim-, suspect- and assault characteristics...
A method for solving fully fuzzy linear system with trapezoidal fuzzy numbers
Directory of Open Access Journals (Sweden)
A. Kumar
2010-03-01
Full Text Available Different methods have been proposed for finding the non-negative solution of fully fuzzy linear system (FFLS i.e. fuzzy linear system with fuzzy coefficients involving fuzzy variables. To the best of our knowledge, there is no method in the literature for finding the non-negative solution of a FFLS without any restriction on the coefficient matrix. In this paper a new computational method is proposed to solve FFLS without any restriction on the coefficient matrix by representing all the parameters as trapezoidal fuzzy numbers.
AN IMPROVED FUZZY CLUSTERING ALGORITHM FOR MICROARRAY IMAGE SPOTS SEGMENTATION
Directory of Open Access Journals (Sweden)
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.
Blainey, Paul C.; Oijen, Antoine M. van; Banerjee, Anirban; Verdine, Gregory L.; Xie, X. Sunney; Hippel, Peter H. von
2006-01-01
A central mystery in the function of site-specific DNA-binding proteins is the detailed mechanism for rapid location and binding of target sites in DNA. Human oxoguanine DNA glycosylase 1 (hOgg1), for example, must search out rare 8-oxoguanine lesions to prevent transversion mutations arising from o
Drug-facilitated sexual assault in Ontario, Canada: toxicological and DNA findings.
Du Mont, Janice; Macdonald, Sheila; Rotbard, Nomi; Bainbridge, Deidre; Asllani, Eriola; Smith, Norman; Cohen, Marsha M
2010-08-01
The purpose of this study was to determine which persons reporting sexual assault to a hospital-based treatment centre may have been covertly drugged and to provide information about whether a sexual assault may have occurred. Each consecutive adolescent and adult presenting at a sexual assault treatment centre was screened for drug-facilitated sexual assault (DFSA). Urine was collected and tested for central nervous system active drugs. Oral, vaginal, and/or rectal swabs were tested for male DNA. Unexpected drugs were defined as those not reported as having been voluntarily consumed within the previous 72 h. Positive swabs for unexpected DNA were determined by whether the person reported having had consensual intercourse in the previous week. A total of 184 of 882 eligible participants met suspected DFSA criteria. Mean age was 25.8 years (SD=8.5), 96.2% were female and 64.7% White. Urine samples were positive for drugs in 44.9% of cases, alcohol in 12.9%, and both drugs and alcohol in 18.0%. The drugs found on toxicological screening were unexpected in 87 of the 135 (64.4%) cases with a positive drug finding and included cannabinoids (40.2%), cocaine (32.2%), amphetamines (13.8%), MDMA (9.2%), ketamine (2.3%), and GHB (1.1%). Male DNA was unexpected in 30 (46.9%) of 64 cases where it was found. Among those persons presenting to a sexual assault treatment centre with a suspicion of DFSA, the presence of unexpected drugs and male DNA was common, lending support for their contention that they had been intentionally drugged and sexually assaulted. Most unexpected drugs found were not those typically described as 'date rape drugs'.
Bounded solutions for fuzzy differential and integral equations
Energy Technology Data Exchange (ETDEWEB)
Nieto, Juan J. [Departamento de Analisis Matematico Facultad de Matematicas Universidad de Santiago de Compostela, 15782 (Spain)] e-mail: amnieto@usc.es; Rodriguez-Lopez, Rosana [Departamento de Analisis Matematico Facultad de Matematicas Universidad de Santiago de Compostela, 15782 (Spain)] e-mail: amrosana@usc.es
2006-03-01
We find sufficient conditions for the boundness of every solution of first-order fuzzy differential equations as well as certain fuzzy integral equations. Our results are based on several theorems concerning crisp differential and integral inequalities.
Nguyen, Hung T
2005-01-01
THE CONCEPT OF FUZZINESS Examples Mathematical modeling Some operations on fuzzy sets Fuzziness as uncertainty Exercises SOME ALGEBRA OF FUZZY SETS Boolean algebras and lattices Equivalence relations and partitions Composing mappings Isomorphisms and homomorphisms Alpha-cuts Images of alpha-level sets Exercises FUZZY QUANTITIES Fuzzy quantities Fuzzy numbers Fuzzy intervals Exercises LOGICAL ASPECTS OF FUZZY SETS Classical two-valued logic A three-valued logic Fuzzy logic Fuzzy and Lukasiewi
Fuzzy Set Approximations in Fuzzy Formal Contexts
Institute of Scientific and Technical Information of China (English)
Mingwen Shao; Shiqing Fan
2006-01-01
In this paper, a kind of multi-level formal concept is introduced. Based on the proposed multi-level formal concept, we present a pair of rough fuzzy set approximations within fuzzy formal contexts. By the proposed rough fuzzy set approximations, we can approximate a fuzzy set according to different precision level. We discuss the properties of the proposed approximation operators in detail.
Heterogeneity in DNA multiple alignments: modeling, inference, and applications in motif finding.
Chen, Gong; Zhou, Qing
2010-09-01
Transcription factors bind sequence-specific sites in DNA to regulate gene transcription. Identifying transcription factor binding sites (TFBSs) is an important step for understanding gene regulation. Although sophisticated in modeling TFBSs and their combinatorial patterns, computational methods for TFBS detection and motif finding often make oversimplified homogeneous model assumptions for background sequences. Since nucleotide base composition varies across genomic regions, it is expected to be helpful for motif finding to incorporate the heterogeneity into background modeling. When sequences from multiple species are utilized, variation in evolutionary conservation violates the common assumption of an identical conservation level in multiple alignments. To handle both types of heterogeneity, we propose a generative model in which a segmented Markov chain is used to partition a multiple alignment into regions of homogeneous nucleotide base composition and a hidden Markov model (HMM) is employed to account for different conservation levels. Bayesian inference on the model is developed via Gibbs sampling with dynamic programming recursions. Simulation studies and empirical evidence from biological data sets reveal the dramatic effect of background modeling on motif finding, and demonstrate that the proposed approach is able to achieve substantial improvements over commonly used background models.
DEFF Research Database (Denmark)
Berks, G.; Keyserlingk, Diedrich Graf von; Jantzen, Jan
2000-01-01
A symptom is a condition indicating the presence of a disease, especially, when regarded as an aid in diagnosis.Symptoms are the smallest units indicating the existence of a disease. A syndrome on the other hand is an aggregate, set or cluster of concurrent symptoms which together indicate...... and clustering are the basic concerns in medicine. Classification depends on definitions of the classes and their required degree of participant of the elements in the cases' symptoms. In medicine imprecise conditions are the rule and therefore fuzzy methods are much more suitable than crisp ones. Fuzzy c......-mean clustering is an easy and well improved tool, which has been applied in many medical fields. We used c-mean fuzzy clustering after feature extraction from an aphasia database. Factor analysis was applied on a correlation matrix of 26 symptoms of language disorders and led to five factors. The factors...
Energy Technology Data Exchange (ETDEWEB)
Mackey, Lester [Department of Statistics, Stanford University,Stanford, CA 94305 (United States); Nachman, Benjamin [Department of Physics, Stanford University,Stanford, CA 94305 (United States); SLAC National Accelerator Laboratory, Stanford University,2575 Sand Hill Rd, Menlo Park, CA 94025 (United States); Schwartzman, Ariel [SLAC National Accelerator Laboratory, Stanford University,2575 Sand Hill Rd, Menlo Park, CA 94025 (United States); Stansbury, Conrad [Department of Physics, Stanford University,Stanford, CA 94305 (United States)
2016-06-01
Collimated streams of particles produced in high energy physics experiments are organized using clustering algorithms to form jets. To construct jets, the experimental collaborations based at the Large Hadron Collider (LHC) primarily use agglomerative hierarchical clustering schemes known as sequential recombination. We propose a new class of algorithms for clustering jets that use infrared and collinear safe mixture models. These new algorithms, known as fuzzy jets, are clustered using maximum likelihood techniques and can dynamically determine various properties of jets like their size. We show that the fuzzy jet size adds additional information to conventional jet tagging variables in boosted topologies. Furthermore, we study the impact of pileup and show that with some slight modifications to the algorithm, fuzzy jets can be stable up to high pileup interaction multiplicities.
Dr.Pranita Goswami
2011-01-01
The Partial Fuzzy Set is a portion of the Fuzzy Set which is again a Fuzzy Set. In the Partial Fuzzy Set the baseline is shifted from 0 to 1 to any of its α cuts . In this paper we have fuzzified a portion of the Fuzzy Set by transformation
Motif finding in DNA sequences based on skipping nonconserved positions in background Markov chains.
Zhao, Xiaoyan; Sze, Sing-Hoi
2011-05-01
One strategy to identify transcription factor binding sites is through motif finding in upstream DNA sequences of potentially co-regulated genes. Despite extensive efforts, none of the existing algorithms perform very well. We consider a string representation that allows arbitrary ignored positions within the nonconserved portion of single motifs, and use O(2(l)) Markov chains to model the background distributions of motifs of length l while skipping these positions within each Markov chain. By focusing initially on positions that have fixed nucleotides to define core occurrences, we develop an algorithm to identify motifs of moderate lengths. We compare the performance of our algorithm to other motif finding algorithms on a few benchmark data sets, and show that significant improvement in accuracy can be obtained when the sites are sufficiently conserved within a given sample, while comparable performance is obtained when the site conservation rate is low. A software program (PosMotif ) and detailed results are available online at http://faculty.cse.tamu.edu/shsze/posmotif.
Fuzzy associative memories for instrument fault detection
Energy Technology Data Exchange (ETDEWEB)
Heger, A.S. [New Mexico Univ., Albuquerque, NM (United States). Dept. of Chemical and Nuclear Engineering; Holbert, K.E.; Ishaque, A.M. [Arizona State Univ., Tempe, AZ (United States)
1996-06-01
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).
Properties of fuzzy hyperplanes
Institute of Scientific and Technical Information of China (English)
ZHANG Zhong; LI Chuandong; WU Deyin
2004-01-01
Some properties of closed fuzzy matroid and those of its hyperplanes are investigated. A fuzzy hyperplane property,which extends the analog of a crisp matroid from crisp set systems to fuzzy set systems, is proved.
control of a dc motor using fuzzy logic control algorithm
African Journals Online (AJOL)
user
conditions such as changes in motor load demand, non- linearity ... Figure 1: Structure of a fuzzy logic controller (Source. [6]). A typical fuzzy logic ... mathematical modeling based on first principles; and via ..... applied. On the premise of these findings, it would be tactful in ... and Sugeno Type Fuzzy Inference Systems for Air.
Intuitionistic Fuzzy Cycles and Intuitionistic Fuzzy Trees
Alshehri, N. O.
2014-01-01
Connectivity has an important role in neural networks, computer network, and clustering. In the design of a network, it is important to analyze connections by the levels. The structural properties of intuitionistic fuzzy graphs provide a tool that allows for the solution of operations research problems. In this paper, we introduce various types of intuitionistic fuzzy bridges, intuitionistic fuzzy cut vertices, intuitionistic fuzzy cycles, and intuitionistic fuzzy trees in intuitionistic fuzzy graphs and investigate some of their interesting properties. Most of these various types are defined in terms of levels. We also describe comparison of these types. PMID:24701155
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-...
De Novo DNA Assembly with a Genetic Algorithm Finds Accurate Genomes Even with Suboptimal Fitness
Bucur, Doina; Squillero, Giovanni; Sim, Kevin
We design an evolutionary heuristic for the combinatorial problem of de-novo DNA assembly with short, overlapping, accurately sequenced single DNA reads of uniform length, from both strands of a genome without long repeated sequences. The representation of a candidate solution is a novel segmented
Energy Technology Data Exchange (ETDEWEB)
Berenstein, David [Department of Applied Mathematics and Theoretical Physics,University of Cambridge, Wilberforce Road, Cambridge CB3 0WA (United Kingdom); Department of Physics, University of California Santa Barbara,Santa Barbara, California 93106 (United States); Dzienkowski, Eric; Lashof-Regas, Robin [Department of Physics, University of California Santa Barbara,Santa Barbara, California 93106 (United States)
2015-08-27
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{sup ∗} field theory with a non-trivial charge density. The solutions we construct have a ℤ{sub 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.
Sanfilippo, Paul G; Hewitt, Alex W
2014-01-01
Approximately 10 years after the Human Genome Project unravelled the sequence of our DNA, the ENCyclopedia Of DNA Elements (ENCODE) Project sought to interpret it. Data from the recently completed project have shed new light on the proportion of biologically active human DNA, assigning a biochemical role to much of the sequence previously considered to be 'junk'. Many of these newly catalogued functional elements represent epigenetic mechanisms involved in regulation of gene expression. Analogous to an Ishihara plate, a gene-coding region of DNA (target dots) only comes into context when the non-coding DNA (surrounding dots) is appreciated. In this review we provide an overview of the ENCODE project, discussing the significance of these data for ophthalmic research and eye disease. The novel insights afforded by the ENCODE project will in time allow for the development of new therapeutic strategies in the management of common blinding disorders.
Fuzzy Economic Order Quantity Inventory Models Without Backordering
Institute of Scientific and Technical Information of China (English)
WANG Xiaobin; TANG Wansheng; ZHAO Ruiqing
2007-01-01
In economic order quantity models without backordering, both the stock cost of each unit quantity and the order cost of each cycle are characterized as independent fuzzy variables rather than fuzzy numbers as in previous studies. Based on an expected value criterion or a credibility criterion, a fuzzy expected value model and a fuzzy dependent hance programming (DCP) model are constructed. The purpose of the fuzzy expected value model is to find the optimal order quantity such that the fuzzy expected value of the total cost is minimal. The fuzzy DCP model is used to find the optimal order quantity for maximizing the credibility of an event such that the total cost in the planning periods does not exceed a certain budget level.Fuzzy simulations are designed to calculate the expected value of the fuzzy objective function and the credibility of each fuzzy event. A particle swarm optimization (PSO) algorithm based on a fuzzy simulation is designed, by integrating the fuzzy simulation and the PSO algorithm. Finally, a numerical example is given to illustrate the feasibility and validity of the proposed algorithm.
Some Additions to the Fuzzy Convergent and Fuzzy Bounded Sequence Spaces of Fuzzy Numbers
Şengönül, M.; Z. Zararsız
2011-01-01
Some properties of the fuzzy convergence and fuzzy boundedness of a sequence of fuzzy numbers were studied in Choi (1996). In this paper, we have consider, some important problems on these spaces and shown that these spaces are fuzzy complete module spaces. Also, the fuzzy α-, fuzzy β-, and fuzzy γ-duals of the fuzzy module spaces of fuzzy numbers have been computeded, and some matrix transformations are given.
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
Repeat Finding Techniques, Data Structures and Algorithms in DNA sequences: A Survey
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Freeson Kaniwa
2015-09-01
Full Text Available DNA sequencing technologies keep getting faster and cheaper leading to massive availability of entire human genomes. This massive availability calls for better analysis tools with a potential to realize a shift from reactive to predictive medicine. The challenge remains, since the entire human genomes need more space and processing power than that can be offered by a standard Desktop PC for their analysis. A background of key concepts surrounding the area of DNA analysis is given and a review of selected prominent algorithms used in this area. The significance of this paper would be to survey the concepts surrounding DNA analysis so as to provide a deep rooted understanding and knowledge transfer regarding existing approaches for DNA analysis using Burrows-Wheeler transform, Wavelet tree and their respective strengths and weaknesses. Consequent to this survey, the paper attempts to provide some directions for future research.
Fuzziness in Chang's fuzzy topological spaces
1999-01-01
It is known that fuzziness within the concept of openness of a fuzzy set in a Chang's fuzzy topological space (fts) is absent. In this paper we introduce a gradation of openness for the open sets of a Chang jts (X, $\\mathcal{T}$) by means of a map $\\sigma\\;:\\; I^{x}\\longrightarrow I\\left(I=\\left[0,1\\right]\\right)$, which is at the same time a fuzzy topology on X in Shostak 's sense. Then, we will be able to avoid the fuzzy point concept, and to introduce an adeguate theory f...
Representation Theorems for Fuzzy Random Sets and Fuzzy Stochastic Processes
Institute of Scientific and Technical Information of China (English)
无
1999-01-01
The fuzzy static and dynamic random phenomena in an abstract separable Banach space is discussed in this paper. The representation theorems for fuzzy set-valued random sets, fuzzy random elements and fuzzy set-valued stochastic processes are obtained.
Kosko, Bart
1991-01-01
Mappings between fuzzy cubes are discussed. This level of abstraction provides a surprising and fruitful alternative to the propositional and predicate-calculas reasoning techniques used in expert systems. It allows one to reason with sets instead of propositions. Discussed here are fuzzy and neural function estimators, neural vs. fuzzy representation of structured knowledge, fuzzy vector-matrix multiplication, and fuzzy associative memory (FAM) system architecture.
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S. Nazmul
2014-03-01
Full Text Available Notions of Lowen type fuzzy soft topological space are introduced and some of their properties are established in the present paper. Besides this, a combined structure of a fuzzy soft topological space and a fuzzy soft group, which is termed here as fuzzy soft topological group is introduced. Homomorphic images and preimages are also examined. Finally, some definitions and results on fuzzy soft set are studied.
Jiménez-Losada, Andrés
2017-01-01
This book offers a comprehensive introduction to cooperative game theory and a practice-oriented reference guide to new models and tools for studying bilateral fuzzy relations among several agents or players. It introduces the reader to several fuzzy models, each of which is first analyzed in the context of classical games (crisp games) and subsequently in the context of fuzzy games. Special emphasis is given to the value of Shapley, which is presented for the first time in the context of fuzzy games. Students and researchers will find here a self-contained reference guide to cooperative fuzzy games, characterized by a wealth of examples, descriptions of a wide range of possible situations, step-by-step explanations of the basic mathematical concepts involved, and easy-to-follow information on axioms and properties.
Probabilistic Quadratic Programming Problems with Some Fuzzy Parameters
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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.
Probabilistic and fuzzy logic in clinical diagnosis.
Licata, G
2007-06-01
In this study I have compared classic and fuzzy logic and their usefulness in clinical diagnosis. The theory of probability is often considered a device to protect the classical two-valued logic from the evidence of its inadequacy to understand and show the complexity of world [1]. This can be true, but it is not possible to discard the theory of probability. I will argue that the problems and the application fields of the theory of probability are very different from those of fuzzy logic. After the introduction on the theoretical bases of fuzzy approach to logic, I have reported some diagnostic argumentations employing fuzzy logic. The state of normality and the state of disease often fight their battle on scalar quantities of biological values and it is not hard to establish a correspondence between the biological values and the percent values of fuzzy logic. Accordingly, I have suggested some applications of fuzzy logic in clinical diagnosis and in particular I have utilised a fuzzy curve to recognise subjects with diabetes mellitus, renal failure and liver disease. The comparison between classic and fuzzy logic findings seems to indicate that fuzzy logic is more adequate to study the development of biological events. In fact, fuzzy logic is useful when we have a lot of pieces of information and when we dispose to scalar quantities. In conclusion, increasingly the development of technology offers new instruments to measure pathological parameters through scalar quantities, thus it is reasonable to think that in the future fuzzy logic will be employed more in clinical diagnosis.
Smart Spectrometer for Distributed Fuzzy Control
Benoit, Eric
2009-01-01
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 functionalities like signal processing, or configuration, only few of them include functionalities to elaborate the fuzzy representation of measurements. In this paper, we develop a solution where the numeric processing is performed locally by the sensor, and where fuzzy processing is exported towards another computing resource by means of the CAN network. This paper presents the concept and the application to a smart fuzzy spectrometer.
Intuitionistic supra fuzzy topological spaces
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Abbas, S.E. E-mail: sabbas73@yahoo.com
2004-09-01
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.
Intuitionistic fuzzy segmentation of medical images.
Chaira, Tamalika
2010-06-01
This paper proposes a novel and probably the first method, using Attanassov intuitionistic fuzzy set theory to segment blood vessels and also the blood cells in pathological images. This type of segmentation is very important in detecting different types of human diseases, e.g., an increase in the number of vessels may lead to cancer in prostates, mammary, etc. The medical images are not properly illuminated, and segmentation in that case becomes very difficult. A novel image segmentation approach using intuitionistic fuzzy set theory and a new membership function is proposed using restricted equivalence function from automorphisms, for finding the membership values of the pixels of the image. An intuitionistic fuzzy image is constructed using Sugeno type intuitionistic fuzzy generator. Local thresholding is applied to threshold medical images. The results showed a much better performance on poor contrast medical images, where almost all the blood vessels and blood cells are visible properly. There are several fuzzy and intuitionistic fuzzy thresholding methods, but these methods are not related to the medical images. To make a comparison with the proposed method with other thresholding methods, the method is compared with six nonfuzzy, fuzzy, and intuitionistic fuzzy methods.
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...
Xu, Zeshui
2014-01-01
This book provides the readers with a thorough and systematic introduction to hesitant fuzzy theory. It presents the most recent research results and advanced methods in the field. These includes: hesitant fuzzy aggregation techniques, hesitant fuzzy preference relations, hesitant fuzzy measures, hesitant fuzzy clustering algorithms and hesitant fuzzy multi-attribute decision making methods. Since its introduction by Torra and Narukawa in 2009, hesitant fuzzy sets have become more and more popular and have been used for a wide range of applications, from decision-making problems to cluster analysis, from medical diagnosis to personnel appraisal and information retrieval. This book offers a comprehensive report on the state-of-the-art in hesitant fuzzy sets theory and applications, aiming at becoming a reference guide for both researchers and practitioners in the area of fuzzy mathematics and other applied research fields (e.g. operations research, information science, management science and engineering) chara...
Fuzzy Logic Indoor Positioning System
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Roberto García Sánz
2008-12-01
Full Text Available The GPS system is not valid for positioning indoors, thus positioning systems are designed using Wi-Fi technology that allows location of a device inside buildings. The use of fuzzy logic is argued by the failure to find positioning systems based on this technology, which seeks toobserve how their use in this field
Analysis of construction dynamic plan using fuzzy critical path method
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Kurij Kazimir V.
2014-01-01
Full Text Available Critical Path Method (CPM technique has become widely recognized as valuable tool for the planning and scheduling large construction projects. The aim of this paper is to present an analytical method for finding the Critical Path in the precedence network diagram where the duration of each activity is represented by a trapezoidal fuzzy number. This Fuzzy Critical Path Method (FCPM uses a defuzzification formula for trapezoidal fuzzy number and applies it on the total float (slack time for each activity in the fuzzy precedence network to find the critical path. The method presented in this paper is very effective in determining the critical activities and finding the critical paths.
Recent Findings Concerning PAMAM Dendrimer Conjugates with Cyclodextrins as Carriers of DNA and RNA
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Keiichi Motoyama
2009-08-01
Full Text Available We have evaluated the potential use of various polyamidoamine (PAMAM dendrimer [dendrimer, generation (G 2-4] conjugates with cyclodextrins (CyDs as novel DNA and RNA carriers. Among the various dendrimer conjugates with CyDs, the dendrimer (G3 conjugate with α-CyD having an average degree of substitution (DS of 2.4 [α-CDE (G3, DS2] displayed remarkable properties as DNA, shRNA and siRNA delivery carriers through the sensor function of α-CDEs toward nucleic acid drugs, cell surface and endosomal membranes. In an attempt to develop cell-specific gene transfer carriers, we prepared sugar-appended α-CDEs. Of the various sugar-appended α-CDEs prepared, galactose- or mannose-appended α-CDEs provided superior gene transfer activity to α-CDE in various cells, but not cell-specific gene delivery ability. However, lactose-appended α-CDE [Lac-α-CDE (G2] was found to possess asialoglycoprotein receptor (AgpR-mediated hepatocyte-selective gene transfer activity, both in vitro and in vivo. Most recently, we prepared folate-poly(ethylene glycol-appended α-CDE [Fol-PαC (G3] and revealed that Fol-PαC (G3 imparted folate receptor (FR-mediated cancer cell-selective gene transfer activity. Consequently, α-CDEs bearing integrated, multifunctional molecules may possess the potential to be novel carriers for DNA, shRNA and siRNA.
Institute of Scientific and Technical Information of China (English)
李少波; 王继奎; 杨观赐
2014-01-01
为了解决主数据集成、web数据集成中的真值发现问题，提出了一种基于模糊偏序关系支持度计算模型的真值发现算法(FA-SDCM)。针对已有算法中，以描述相似度替代描述支持度进行计算，忽视了描述所含真值信息的不对称性问题，在分析描述本身特性的基础上，提出了描述蕴含概念，定义了基于模糊偏序关系的支持度计算模型，较好地解决了描述所含真值信息的不对称性问题。在考虑了数据源可信度及描述之间支持度对真值发现影响的基础上，基于迭代思想，提出了FA-SDCM算法。在Books-Authors数据集上进行实验，结果表明FA-SDCM算法比Vot e算法与TruthFinder算法具有更高的准确率。%In order to find the true values in master data integration and web data integration, we propose a true value finding algorithm (FA-SDCM) based on a support degree calculation model using fuzzy partial order relations. In existing algorithms, support degrees are usually substituted by similarity, which ignores the asymmetry in the true vales. In this paper, the concept of description containing is proposed through analyzing characteristics of descriptions, and then a support degree calculating model is developed based on fuzzy partial order relations to solve the description of asymmetric problems in the true values. Considering the influence of the data source reliability and the support degrees among descriptions on true value finding, the FA-SDCM algorithm is realized iteratively. An experiment has been carried on the Books-Authors data set, and the result shows that the FA-SDCM algorithm has better accuracy than the Vote and the TruthFinder algorithms.
Transformation and entropy for fuzzy rough sets
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
A new method for translating a fuzzy rough set to a fuzzy set is introduced and the fuzzy approximation of a fuzzy rough set is given.The properties of the fuzzy approximation of a fuzzy rough set are studied and a fuzzy entropy measure for fuzzy rough sets is proposed.This measure is consistent with similar considerations for ordinary fuzzy sets and is the result of the fuzzy approximation of fuzzy rough sets.
Institute of Scientific and Technical Information of China (English)
刘叙华; 邓安生
1994-01-01
A new approach of operator fuzzy logic, Boolean operator fuzzy logic (BOFL) based on Boolean algebra, is presented. The resolution principle is also introduced into BOFL. BOFL is a natural generalization of classical logic and can be applied to the qualitative description of fuzzy knowledge.
DEFF Research Database (Denmark)
Rodríguez, J. Tinguaro; Franco de los Ríos, Camilo; Gómez, Daniel
2015-01-01
In this paper we want to stress the relevance of paired fuzzy sets, as already proposed in previous works of the authors, as a family of fuzzy sets that offers a unifying view for different models based upon the opposition of two fuzzy sets, simply allowing the existence of different types...
Fuzzy Linguistic Topological Spaces
Kandasamy, W B Vasantha; Amal, K
2012-01-01
This book has five chapters. Chapter one is introductory in nature. Fuzzy linguistic spaces are introduced in chapter two. Fuzzy linguistic vector spaces are introduced in chapter three. Chapter four introduces fuzzy linguistic models. The final chapter suggests over 100 problems and some of them are at research level.
Howard, Ayanna
2005-01-01
The Fuzzy Logic Engine is a software package that enables users to embed fuzzy-logic modules into their application programs. Fuzzy logic is useful as a means of formulating human expert knowledge and translating it into software to solve problems. Fuzzy logic provides flexibility for modeling relationships between input and output information and is distinguished by its robustness with respect to noise and variations in system parameters. In addition, linguistic fuzzy sets and conditional statements allow systems to make decisions based on imprecise and incomplete information. The user of the Fuzzy Logic Engine need not be an expert in fuzzy logic: it suffices to have a basic understanding of how linguistic rules can be applied to the user's problem. The Fuzzy Logic Engine is divided into two modules: (1) a graphical-interface software tool for creating linguistic fuzzy sets and conditional statements and (2) a fuzzy-logic software library for embedding fuzzy processing capability into current application programs. The graphical- interface tool was developed using the Tcl/Tk programming language. The fuzzy-logic software library was written in the C programming language.
Some weakly mappings on intuitionistic fuzzy topological spaces
Zhen-Guo Xu; Fu-Gui Shi
2008-01-01
In this paper, we shall introduce concepts of fuzzy semiopen set, fuzzy semiclosed set, fuzzy semiinterior, fuzzy semiclosure on intuitionistic fuzzy topological space and fuzzy open (fuzzy closed) mapping, fuzzy irresolute mapping, fuzzy irresolute open (closed) mapping, fuzzy semicontinuous mapping and fuzzy semiopen (semiclosed) mapping between two intuitionistic fuzzy topological spaces. Moreover, we shall discuss their some properties.
Countable Fuzzy Topological Space and Countable Fuzzy Topological Vector Space
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Apu Kumar Saha
2015-06-01
Full Text Available This paper deals with countable fuzzy topological spaces, a generalization of the notion of fuzzy topological spaces. A collection of fuzzy sets F on a universe X forms a countable fuzzy topology if in the definition of a fuzzy topology, the condition of arbitrary supremum is relaxed to countable supremum. In this generalized fuzzy structure, the continuity of fuzzy functions and some other related properties are studied. Also the class of countable fuzzy topological vector spaces as a generalization of the class of fuzzy topological vector spaces has been introduced and investigated.
Genetic fuzzy system modeling and simulation of vascular behaviour
DEFF Research Database (Denmark)
Tang, Jiaowei; Boonen, Harrie C.M.
and find the optimal parameters in a Fuzzy Control set that can control the fluctuation of physical features in a blood vessel, based on experimental data (training data). Our solution is to create chromosomes or individuals composed of a sequence of parameters in the fuzzy system and find the best...... chromosome or individual to define the fuzzy system. The model is implemented by combining the Matlab Genetic algorithm and Fuzzy system toolboxes, respectively. To test the performance of this method, experimental data sets about calculated pressure change in different blood vessels after several chemical...... treatments are chosen as training and testing data sets. In the simulation, the fuzzy control system is trained by pressure data of one blood vessel and tested with pressure data of other blood vessels. Results: Right now, some rough results show that trained fuzzy control system can be used to predict...
Mathematics of Fuzzy Sets and Fuzzy Logic
Bede, Barnabas
2013-01-01
This book presents a mathematically-based introduction into the fascinating topic of Fuzzy Sets and Fuzzy Logic and might be used as textbook at both undergraduate and graduate levels and also as reference guide for mathematician, scientists or engineers who would like to get an insight into Fuzzy Logic. Fuzzy Sets have been introduced by Lotfi Zadeh in 1965 and since then, they have been used in many applications. As a consequence, there is a vast literature on the practical applications of fuzzy sets, while theory has a more modest coverage. The main purpose of the present book is to reduce this gap by providing a theoretical introduction into Fuzzy Sets based on Mathematical Analysis and Approximation Theory. Well-known applications, as for example fuzzy control, are also discussed in this book and placed on new ground, a theoretical foundation. Moreover, a few advanced chapters and several new results are included. These comprise, among others, a new systematic and constructive approach for fuzzy infer...
How we pass from fuzzy $po$-semigroups to fuzzy $po$-$\\Gamma$-semigroups
Kehayopulu, Niovi
2014-01-01
The results on fuzzy ordered semigroups (or on fuzzy semigroups) can be transferred to fuzzy ordered gamma (or to fuzzy gamma) semigroups. We show the way we pass from fuzzy ordered semigroups to fuzzy ordered gamma semigroups.
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Orlov A. I.
2016-05-01
Full Text Available Fuzzy sets are the special form of objects of nonnumeric nature. Therefore, in the processing of the sample, the elements of which are fuzzy sets, a variety of methods for the analysis of statistical data of any nature can be used - the calculation of the average, non-parametric density estimators, construction of diagnostic rules, etc. We have told about the development of our work on the theory of fuzziness (1975 - 2015. In the first of our work on fuzzy sets (1975, the theory of random sets is regarded as a generalization of the theory of fuzzy sets. In non-fiction series "Mathematics. Cybernetics" (publishing house "Knowledge" in 1980 the first book by a Soviet author fuzzy sets is published - our brochure "Optimization problems and fuzzy variables". This book is essentially a "squeeze" our research of 70-ies, ie, the research on the theory of stability and in particular on the statistics of objects of non-numeric nature, with a bias in the methodology. The book includes the main results of the fuzzy theory and its note to the random set theory, as well as new results (first publication! of statistics of fuzzy sets. On the basis of further experience, you can expect that the theory of fuzzy sets will be more actively applied in organizational and economic modeling of industry management processes. We discuss the concept of the average value of a fuzzy set. We have considered a number of statements of problems of testing statistical hypotheses on fuzzy sets. We have also proposed and justified some algorithms for restore relationships between fuzzy variables; we have given the representation of various variants of fuzzy cluster analysis of data and variables and described some methods of collection and description of fuzzy data
On generalized fuzzy strongly semiclosed sets in fuzzy topological spaces
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Oya Bedre Ozbakir
2002-01-01
semiclosed, generalized fuzzy almost-strongly semiclosed, generalized fuzzy strongly closed, and generalized fuzzy almost-strongly closed sets. In the light of these definitions, we also define some generalizations of fuzzy continuous functions and discuss the relations between these new classes of functions and other fuzzy continuous functions.
Row Reduced Echelon Form for Solving Fully Fuzzy System with Unknown Coefficients
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Ghassan Malkawi
2014-08-01
Full Text Available This study proposes a new method for finding a feasible fuzzy solution in positive Fully Fuzzy Linear System (FFLS, where the coefficients are unknown. The fully fuzzy system is transferred to linear system in order to obtain the solution using row reduced echelon form, thereafter; the crisp solution is restricted in obtaining the positive fuzzy solution. The fuzzy solution of FFLS is included crisp intervals, to assign alternative values of unknown entries of fuzzy numbers. To illustrate the proposed method, numerical examples are solved, where the entries of coefficients are unknown in right or left hand side, to demonstrate the contributions in this study.
Multiobjective fuzzy stochastic linear programming problems with inexact probability distribution
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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.
EXTENSION OF THE PROJECTION THEOREM ON HILBERT SPACE TO FUZZY HILBERT SPACE OVER FUZZY NUMBER SPACE
K. P. DEEPA; Dr.S.Chenthur Pandian
2012-01-01
In this paper, we extend the projection theorem on Hilbert space to its fuzzy version over fuzzy number space embedded with fuzzy number mapping. To prove this we discuss the concepts of fuzzy Hilbert space over fuzzy number space with fuzzy number mapping. The fuzzy orthogonality, fuzzy orthonormality, fuzzy complemented subset property etc. of fuzzy Hilbert space over fuzzy number space using fuzzy number mapping also been discussed.
Mahanta, J.; P. K. Das
2012-01-01
A new class of fuzzy closed sets, namely fuzzy weakly closed set in a fuzzy topological space is introduced and it is established that this class of fuzzy closed sets lies between fuzzy closed sets and fuzzy generalized closed sets. Alongwith the study of fundamental results of such closed sets, we define and characterize fuzzy weakly compact space and fuzzy weakly closed space.
Compactness in intuitionistic fuzzy topological spaces
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S. E. Abbas
2005-02-01
Full Text Available We introduce fuzzy almost continuous mapping, fuzzy weakly continuous mapping, fuzzy compactness, fuzzy almost compactness, and fuzzy near compactness in intuitionistic fuzzy topological space in view of the definition of Ã…Â ostak, and study some of their properties. Also, we investigate the behavior of fuzzy compactness under several types of fuzzy continuous mappings.
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...
Special functions in Fuzzy Analysis
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Angel Garrido
2006-01-01
Full Text Available In the treatment of Fuzzy Logic an useful tool appears: the membership function, with the information about the degree of completion of a condition which defines the respective Fuzzy Set or Fuzzy Relation. With their introduction, it is possible to prove some results on the foundations of Fuzzy Logic and open new ways in Fuzzy Analysis.
Vector-valued fuzzy multifunctions
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Ismat Beg
2001-01-01
Full Text Available Some of the properties of vector-valued fuzzy multifunctions are studied. The notion of sum fuzzy multifunction, convex hull fuzzy multifunction, close convex hull fuzzy multifunction, and upper demicontinuous are given, and some of the properties of these fuzzy multifunctions are investigated.
Approximate Reasoning with Fuzzy Booleans
Broek, van den P.M.; Noppen, J.A.R.
2004-01-01
This paper introduces, in analogy to the concept of fuzzy numbers, the concept of fuzzy booleans, and examines approximate reasoning with the compositional rule of inference using fuzzy booleans. It is shown that each set of fuzzy rules is equivalent to a set of fuzzy rules with singleton crisp ante
Fuzzy Sets and Mathematical Education.
Alsina, C.; Trillas, E.
1991-01-01
Presents the concept of "Fuzzy Sets" and gives some ideas for its potential interest in mathematics education. Defines what a Fuzzy Set is, describes why we need to teach fuzziness, gives some examples of fuzzy questions, and offers some examples of activities related to fuzzy sets. (MDH)
Fuzzy TOPSIS for Multiresponse Quality Problems in Wafer Fabrication Processes
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Chiun-Ming Liu
2013-01-01
Full Text Available The quality characteristics in the wafer fabrication process are diverse, variable, and fuzzy in nature. How to effectively deal with multiresponse quality problems in the wafer fabrication process is a challenging task. In this study, the fuzzy technique for order preference by similarity to an ideal solution (TOPSIS, one of the fuzzy multiattribute decision-analysis (MADA methods, is proposed to investigate the fuzzy multiresponse quality problem in integrated-circuit (IC wafer fabrication process. The fuzzy TOPSIS is one of the effective fuzzy MADA methods for dealing with decision-making problems under uncertain environments. First, a fuzzy TOPSIS methodology is developed by considering the ambiguity between quality characteristics. Then, a detailed procedure for the developed fuzzy TOPSIS approach is presented to show how the fuzzy wafer fabrication quality problems can be solved. Real-world data is collected from an IC semiconductor company and the developed fuzzy TOPSIS approach is applied to find an optimal combination of parameters. Results of this study show that the developed approach provides a satisfactory solution to the wafer fabrication multiresponse problem. This developed approach can be also applied to other industries for investigating multiple quality characteristics problems.
Further study of multigranulation T-fuzzy rough sets.
Li, Wentao; Zhang, Xiaoyan; Sun, Wenxin
2014-01-01
The optimistic multigranulation T-fuzzy rough set model was established based on multiple granulations under T-fuzzy approximation space by Xu et al., 2012. From the reference, a natural idea is to consider pessimistic multigranulation model in T-fuzzy approximation space. So, in this paper, the main objective is to make further studies according to Xu et al., 2012. The optimistic multigranulation T-fuzzy rough set model is improved deeply by investigating some further properties. And a complete multigranulation T-fuzzy rough set model is constituted by addressing the pessimistic multigranulation T-fuzzy rough set. The full important properties of multigranulation T-fuzzy lower and upper approximation operators are also presented. Moreover, relationships between multigranulation and classical T-fuzzy rough sets have been studied carefully. From the relationships, we can find that the T-fuzzy rough set model is a special instance of the two new types of models. In order to interpret and illustrate optimistic and pessimistic multigranulation T-fuzzy rough set models, a case is considered, which is helpful for applying these theories to practical issues.
Supplier Segmentation using Fuzzy Linguistic Preference Relations and Fuzzy Clustering
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Pegah Sagheb Haghighi
2014-04-01
Full Text Available In an environment characterized by its competitiveness, managing and monitoring relationships with suppliers are of the essence. Supplier management includes supplier segmentation. Existing literature demonstrates that suppliers are mostly segmented by computing their aggregated scores, without taking each supplier’s criterion value into account. The principle aim of this paper is to propose a supplier segmentation method that compares each supplier’s criterion value with exactly the same criterion of other suppliers. The Fuzzy Linguistic Preference Relations (LinPreRa based Analytic Hierarchy Process (AHP is first used to find the weight of each criterion. Then, Fuzzy c-means algorithm is employed to cluster suppliers based on their membership degrees. The obtained results show that the proposed method enhances the quality of the previous findings.
On fuzzy almost continuous convergence in fuzzy function spaces
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A.I. Aggour
2013-10-01
Full Text Available In this paper, we study the fuzzy almost continuous convergence of fuzzy nets on the set FAC(X, Y of all fuzzy almost continuous functions of a fuzzy topological space X into another Y. Also, we introduce the notions of fuzzy splitting and fuzzy jointly continuous topologies on the set FAC(X, Y and study some of its basic properties.
A New Type Fuzzy Module over Fuzzy Rings
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Ece Yetkin
2014-01-01
Full Text Available A new kind of fuzzy module over a fuzzy ring is introduced by generalizing Yuan and Lee’s definition of the fuzzy group and Aktaş and Çağman’s definition of fuzzy ring. The concepts of fuzzy submodule, and fuzzy module homomorphism are studied and some of their basic properties are presented analogous of ordinary module theory.
Solving type-2 fuzzy relation equations via semi-tensor product of matrices
Institute of Scientific and Technical Information of China (English)
Yongyi YAN; Zengqiang CHEN; Zhongxin LIU
2014-01-01
The problem of solving type-2 fuzzy relation equations is investigated. In order to apply semi-tensor product of matrices, a new matrix analysis method and tool, to solve type-2 fuzzy relation equations, a type-2 fuzzy relation is decomposed into two parts as principal sub-matrices and secondary sub-matrices;an r-ary symmetrical-valued type-2 fuzzy relation model and its corresponding symmetrical-valued type-2 fuzzy relation equation model are established. Then, two algorithms are developed for solving type-2 fuzzy relation equations, one of which gives a theoretical description for general type-2 fuzzy relation equations;the other one can find all the solutions to the symmetrical-valued ones. The results can improve designing type-2 fuzzy controllers, because it provides knowledge to search the optimal solutions or to find the reason if there is no solution. Finally some numerical examples verify the correctness of the results/algorithms.
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...
Triangular and Trapezoidal Fuzzy State Estimation with Uncertainty on Measurements
Directory of Open Access Journals (Sweden)
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.
Decision making with fuzzy probability assessments and fuzzy payoff
Institute of Scientific and Technical Information of China (English)
Song Yexin; Yin Di; Chen Mianyun
2005-01-01
A novel method for decision making with fuzzy probability assessments and fuzzy payoff is presented. The consistency of the fuzzy probability assessment is considered. A fuzzy aggregate algorithm is used to indicate the fuzzy expected payoff of alternatives. The level sets of each fuzzy expected payoff are then obtained by solving linear programming models. Based on a defuzzification function associated with the level sets of fuzzy number and a numerical integration formula (Newton-Cotes formula), an effective approach to rank the fuzzy expected payoff of alternatives is also developed to determine the best alternative. Finally, a numerical example is provided to illustrate the proposed method.
Directory of Open Access Journals (Sweden)
Somaye Yeylaghi
2017-06-01
Full Text Available In this paper, a novel hybrid method based on interval-valued fuzzy neural network for approximate of interval-valued fuzzy regression models, is presented. The work of this paper is an expansion of the research of real fuzzy regression models. In this paper interval-valued fuzzy neural network (IVFNN can be trained with crisp and interval-valued fuzzy data. Here a neural network is considered as a part of a large field called neural computing or soft computing. Moreover, in order to find the approximate parameters, a simple algorithm from the cost function of the fuzzy neural network is proposed. Finally, we illustrate our approach by some numerical examples and compare this method with existing methods.
Generation of fuzzy mathematical morphologies
2001-01-01
Fuzzy Mathematical Morphology aims to extend the binary morphological operators to grey-level images. In order to define the basic morphological operations fuzzy erosion, dilation, opening and closing, we introduce a general method based upon fuzzy implication and inclusion grade operators, including as particular case, other ones existing in related literature In the definition of fuzzy erosion and dilation we use several fuzzy implications (Annexe A, Table of fuzzy implic...
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.
Fuzzy Model for Trust Evaluation
Institute of Scientific and Technical Information of China (English)
Zhang Shibin; He Dake
2006-01-01
Based on fuzzy set theory, a fuzzy trust model is established by using membership function to describe the fuzziness of trust. The trust vectors of subjective trust are obtained based on a mathematical model of fuzzy synthetic evaluation. Considering the complicated and changeable relationships between various subjects, the multi-level mathematical model of fuzzy synthetic evaluation is introduced. An example of a two-level fuzzy synthetic evaluation model confirms the feasibility of the multi-level fuzzy synthesis evaluation model. The proposed fuzzy model for trust evaluation may provide a promising method for research of trust model in open networks.
DEFF Research Database (Denmark)
Jantzen, Jan
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......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...
DEFF Research Database (Denmark)
Jantzen, Jan
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......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...... 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...
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.
DEFF Research Database (Denmark)
Dotoli, M.; Jantzen, Jan
1999-01-01
The tutorial concerns automatic control of an inverted pendulum, especially rule based control by means of fuzzy logic. A ball balancer, implemented in a software simulator in Matlab, is used as a practical case study. The objectives of the tutorial are to teach the basics of fuzzy control......, and to show how to apply fuzzy logic in automatic control. The tutorial is distance learning, where students interact one-to-one with the teacher using e-mail....
DEFF Research Database (Denmark)
Dotoli, M.; Jantzen, Jan
1999-01-01
The tutorial concerns automatic control of an inverted pendulum, especially rule based control by means of fuzzy logic. A ball balancer, implemented in a software simulator in Matlab, is used as a practical case study. The objectives of the tutorial are to teach the basics of fuzzy control, and t......, 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....
DEFF Research Database (Denmark)
Jantzen, Jan
1998-01-01
Design of a fuzzy controller requires more design decisions than usual, for example regarding rule base, inference engine, defuzzification, and data pre- and post processing. This tutorial paper identifies and describes the design choices related to single-loop fuzzy control, based...... on an international standard which is underway. The paper contains also a design approach, which uses a PID controller as a starting point. A design engineer can view the paper as an introduction to fuzzy controller design....
Fuzzy Sliding Mode Control of Plate Vibrations
Directory of Open Access Journals (Sweden)
Manu Sharma
2010-01-01
Full Text Available In this paper, fuzzy logic is meshed with sliding mode control, in order to control vibrations of a cantilevered plate. Test plate is instrumented with a piezoelectric sensor patch and a piezoelectric actuator patch. Finite element method is used to obtain mathematical model of the test plate. A design approach of a sliding mode controller for linear systems with mismatched time-varying uncertainties is used in this paper. It is found that chattering around the sliding surface in the sliding mode control can be checked by the proposed fuzzy sliding mode control approach. With presented fuzzy sliding mode approach the actuator voltage time response has a smooth decay. This is important because an abrupt decay can excite higher modes in the structure. Fuzzy rule base consisting of nine rules, is generated from the sliding mode inequality. Experimental implementation of the control approach verify the theoretical findings. For experimental implementation, size of the problem is reduced using modal truncation technique. Modal displacements as well as velocities of first two modes are observed using real-time kalman observer. Real time implementation of fuzzy logic based control has always been a challenge because a given set of rules has to be executed in every sampling interval. Results in this paper establish feasibility of experimental implementation of presented fuzzy logic based controller for active vibration control.
Fuzzy logic program at SGS-Thomson
Pagni, Andrea; Poluzzi, Rinaldo; Rizzotto, GianGuido
1993-12-01
From its conception by Professor Lotfi A. Zadeh in the early '60s, Fuzzy Logic has slowly won acceptance, first in the academic world, then in industry. Its success is mainly due to the different perspective with which problems are tackled. Thanks to Fuzzy Logic we have moved from a numerical/analytical description to a quantitative/qualitative one. It is important to stress that this different perspective not only allows us to solve analysis/control problems at lower costs but can also allow otherwise insoluble problems to be solved at acceptable costs. Of course, it must be stressed that Fuzzy Systems cannot match the computational precision of traditional techniques but seek, instead, to find acceptable solutions in shorter times. Recognizing the enormous importance of fuzzy logic in the markets of the future, SGS-THOMSON intends to produce devices belonging to a new class of machines: Fuzzy Computational Machines. For this purpose a major research project has been established considering the architectural aspects and system implications of fuzzy logic, the development of dedicated VLSI components and supporting software.
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
The typical BDI (belief desire intention) model of agent is not efficiently computable and the strict logic expression is not easily applicable to the AUV (autonomous underwater vehicle) domain with uncertainties. In this paper, an AUV fuzzy neural BDI model is proposed. The model is a fuzzy neural network composed of five layers: input ( beliefs and desires) , fuzzification, commitment, fuzzy intention, and defuzzification layer. In the model, the fuzzy commitment rules and neural network are combined to form intentions from beliefs and desires. The model is demonstrated by solving PEG (pursuit-evasion game), and the simulation result is satisfactory.
RANDOM VARIABLE WITH FUZZY PROBABILITY
Institute of Scientific and Technical Information of China (English)
吕恩琳; 钟佑明
2003-01-01
Mathematic description about the second kind fuzzy random variable namely the random variable with crisp event-fuzzy probability was studied. Based on the interval probability and using the fuzzy resolution theorem, the feasible condition about a probability fuzzy number set was given, go a step further the definition arid characters of random variable with fuzzy probability ( RVFP ) and the fuzzy distribution function and fuzzy probability distribution sequence of the RVFP were put forward. The fuzzy probability resolution theorem with the closing operation of fuzzy probability was given and proved. The definition and characters of mathematical expectation and variance of the RVFP were studied also. All mathematic description about the RVFP has the closing operation for fuzzy probability, as a result, the foundation of perfecting fuzzy probability operation method is laid.
Relations Among Some Fuzzy Entropy Formulae
Institute of Scientific and Technical Information of China (English)
卿铭
2004-01-01
Fuzzy entropy has been widely used to analyze and design fuzzy systems, and many fuzzy entropy formulae have been proposed. For further in-deepth analysis of fuzzy entropy, the axioms and some important formulae of fuzzy entropy are introduced. Some equivalence results among these fuzzy entropy formulae are proved, and it is shown that fuzzy entropy is a special distance measurement.
Results on fuzzy soft topological spaces
Mahanta, J
2012-01-01
B. Tanay et. al. introduced and studied fuzzy soft topological spaces. Here we introduce fuzzy soft point and study the concept of neighborhood of a fuzzy soft point in a fuzzy soft topological space. We also study fuzzy soft closure and fuzzy soft interior. Separation axioms and connectedness are introduced and investigated for fuzzy soft topological spaces.
Matrix dynamics of fuzzy spheres
Jatkar, D P; Wadia, S R; Yogendran, K P; Jatkar, Dileep P.; Mandal, Gautam; Wadia, Spenta R.
2002-01-01
We study the dynamics of fuzzy two-spheres in a matrix model which represents string theory in the presence of RR flux. We analyze the stability of known static solutions of such a theory which contain commuting matrices and SU(2) representations. We find that irreducible as well as reducible representations are stable. Since the latter are of higher energy, this stability poses a puzzle. We resolve this puzzle by noting that reducible representations have marginal directions corresponding to non-spherical deformations. We obtain new static solutions by turning on these marginal deformations. These solutions now have instability or tachyonic directions. We discuss condensation of these tachyons which correspond to classical trajectories interpolating from multiple, small fuzzy spheres to a single, large sphere. We briefly discuss spatially independent configurations of a D3/D5 system described by the same matrix model which now possesses a supergravity dual.
Some properties of fuzzy soft proximity spaces.
Demir, İzzettin; Özbakır, Oya Bedre
2015-01-01
We study the fuzzy soft proximity spaces in Katsaras's sense. First, we show how a fuzzy soft topology is derived from a fuzzy soft proximity. Also, we define the notion of fuzzy soft δ-neighborhood in the fuzzy soft proximity space which offers an alternative approach to the study of fuzzy soft proximity spaces. Later, we obtain the initial fuzzy soft proximity determined by a family of fuzzy soft proximities. Finally, we investigate relationship between fuzzy soft proximities and proximities.
Some Properties of Fuzzy Soft Proximity Spaces
Demir, İzzettin; Özbakır, Oya Bedre
2015-01-01
We study the fuzzy soft proximity spaces in Katsaras's sense. First, we show how a fuzzy soft topology is derived from a fuzzy soft proximity. Also, we define the notion of fuzzy soft δ-neighborhood in the fuzzy soft proximity space which offers an alternative approach to the study of fuzzy soft proximity spaces. Later, we obtain the initial fuzzy soft proximity determined by a family of fuzzy soft proximities. Finally, we investigate relationship between fuzzy soft proximities and proximities. PMID:25793224
On Intuitionistic Fuzzy Filters of Intuitionistic Fuzzy Coframes
Directory of Open Access Journals (Sweden)
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.
Cheng, Chun-Pei; Lan, Kuo-Lun; Liu, Wen-Chun; Chang, Ting-Tsung; Tseng, Vincent S
2016-12-01
Hepatitis B viral (HBV) infection is strongly associated with an increased risk of liver diseases like cirrhosis or hepatocellular carcinoma (HCC). Many lines of evidence suggest that deletions occurring in HBV genomic DNA are highly associated with the activity of HBV via the interplay between aberrant viral proteins release and human immune system. Deletions finding on the HBV whole genome sequences is thus a very important issue though there exist underlying the challenges in mining such big and complex biological data. Although some next generation sequencing (NGS) tools are recently designed for identifying structural variations such as insertions or deletions, their validity is generally committed to human sequences study. This design may not be suitable for viruses due to different species. We propose a graphics processing unit (GPU)-based data mining method called DeF-GPU to efficiently and precisely identify HBV deletions from large NGS data, which generally contain millions of reads. To fit the single instruction multiple data instructions, sequencing reads are referred to as multiple data and the deletion finding procedure is referred to as a single instruction. We use Compute Unified Device Architecture (CUDA) to parallelize the procedures, and further validate DeF-GPU on 5 synthetic and 1 real datasets. Our results suggest that DeF-GPU outperforms the existing commonly-used method Pindel and is able to exactly identify the deletions of our ground truth in few seconds. The source code and other related materials are available at https://sourceforge.net/projects/defgpu/.
Properties of Bipolar Fuzzy Hypergraphs
M. Akram; 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.
Fuzzy Markov chains: uncertain probabilities
2002-01-01
We consider finite Markov chains where there are uncertainties in some of the transition probabilities. These uncertainties are modeled by fuzzy numbers. Using a restricted fuzzy matrix multiplication we investigate the properties of regular, and absorbing, fuzzy Markov chains and show that the basic properties of these classical Markov chains generalize to fuzzy Markov chains.
Achieving of Fuzzy Automata for Processing Fuzzy Logic
Institute of Scientific and Technical Information of China (English)
SHU Lan; WU Qing-e
2005-01-01
At present, there has been an increasing interest in neuron-fuzzy systems, the combinations of artificial neural networks with fuzzy logic. In this paper, a definition of fuzzy finite state automata (FFA) is introduced and fuzzy knowledge equivalence representations between neural networks, fuzzy systems and models of automata are discussed. Once the network has been trained, we develop a method to extract a representation of the FFA encoded in the recurrent neural network that recognizes the training rules.
Entropy of Fuzzy Partitions and Entropy of Fuzzy Dynamical Systems
Directory of Open Access Journals (Sweden)
Dagmar Markechová
2016-01-01
Full Text Available In the paper we define three kinds of entropy of a fuzzy dynamical system using different entropies of fuzzy partitions. It is shown that different definitions of the entropy of fuzzy partitions lead to different notions of entropies of fuzzy dynamical systems. The relationships between these entropies are studied and connections with the classical case are mentioned as well. Finally, an analogy of the Kolmogorov–Sinai Theorem on generators is proved for fuzzy dynamical systems.
DEFF Research Database (Denmark)
Jantzen, Jan
1998-01-01
A logic based on the two truth values True and False is sometimes inadequate when describing human reasoning. Fuzzy logic uses the whole interval between 0 (False) and 1 (True) to describe human reasoning. As a result, fuzzy logic is being applied in rule based automatic controllers, and this paper...
Extended Fuzzy Clustering Algorithms
U. Kaymak (Uzay); M. Setnes
2000-01-01
textabstractFuzzy clustering is a widely applied method for obtaining fuzzy models from data. It has been applied successfully in various fields including finance and marketing. Despite the successful applications, there are a number of issues that must be dealt with in practical applications of fuz
Complete fuzzy scheduling and fuzzy earned value management in construction projects
Institute of Scientific and Technical Information of China (English)
José Luís PONZ-TIENDA; Eugenio PELLICER; Víctor YEPES
2012-01-01
This paper aims to present a comprehensive proposal for project scheduling and control by applying fuzzy eamed value.It goes a step further than the existing literature:in the formulation of the fuzzy earned value we consider not only its duration,but also cost and production,and alternatives in the scheduling between the earliest and latest times.The mathematical model is implemented in a prototypical construction project with all the estimated values taken as fuzzy numbers.Our findings suggest that different possible schedules and the fuzzy arithmetic provide more objective results in uncertain environments than the traditional methodology.The proposed model allows for controlling the vagueness of the environment through the adjustment of the a-cut,adapting it to the specific circumstances of the project.
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
Prediction of Radiation Fog by DNA Computing
Ray, Kumar Sankar; Mondal, Mandrita
2015-01-01
In this paper we propose a wet lab algorithm for prediction of radiation fog by DNA computing. The concept of DNA computing is essentially exploited for generating the classifier algorithm in the wet lab. The classifier is based on a new concept of similarity based fuzzy reasoning suitable for wet lab implementation. This new concept of similarity based fuzzy reasoning is different from conventional approach to fuzzy reasoning based on similarity measure and also replaces the logical aspect o...
Axiomatic of Fuzzy Complex Numbers
Angel Garrido
2012-01-01
Fuzzy numbers are fuzzy subsets of the set of real numbers satisfying some additional conditions. Fuzzy numbers allow us to model very difficult uncertainties in a very easy way. Arithmetic operations on fuzzy numbers have also been developed, and are based mainly on the crucial Extension Principle. When operating with fuzzy numbers, the results of our calculations strongly depend on the shape of the membership functions of these numbers. Logically, less regular membership functions may lead ...
MODELING FUZZY GEOGRAPHIC OBJECTS WITHIN FUZZY FIELDS
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
To improve the current GIS functions in describing geographic objects w ith fuzziness,this paper begins with a discussion on the distance measure of sp atial objects based on the theory of sets and an introduction of dilation and er osion operators.Under the assumption that changes of attributes in a geographic region are gradual,the analytic expressions for the fuzzy objects of points,l ines and areas,and the description of their formal structures are presented.Th e analytic model of geographic objects by means of fuzzy fields is developed.We have shown that the 9-intersection model proposed by Egenhofer and Franzosa (19 91) is a special case of the model presented in the paper.
Sequence of inequalities among fuzzy mean difference divergence measures and their applications.
Tomar, Vijay Prakash; Ohlan, Anshu
2014-01-01
This paper presents a sequence of fuzzy mean difference divergence measures. The validity of these fuzzy mean difference divergence measures is proved axiomatically. In addition, it introduces a sequence of inequalities among some of these fuzzy mean difference divergence measures. The applications of proposed fuzzy mean difference divergence measures in the context of pattern recognition have been presented using a numerical example. It is shown that the proposed fuzzy mean difference divergence measures are well suited to use with linguistic variables. Finally, on establishing inequalities, we find that our proposed measures are computationally much more efficient.
A Brief History of Fuzzy Logic
Directory of Open Access Journals (Sweden)
Angel Garrido
2012-04-01
Full Text Available
The problems of uncertainty, imprecision and vagueness have been discussed for many years. These problems have been major topics in philosophical circles with much debate, in particular, about the nature of vagueness and the ability of traditional Boolean logic to cope with concepts and perceptions that are imprecise or vague. The Fuzzy Logic (which is usually translated into Castilian by “Lógica Borrosa”, or “Lógica Difusa”, but also by “Lógica Heurística” can be considered a bypass-valued logics (Multi-valued Logic, MVL, its acronym in English. It is founded on, and is closely related to-Fuzzy Sets Theory, and successfully applied on Fuzzy Systems. You might think that fuzzy logic is quite recent and what has worked for a short time, but its origins date back at least to the Greek philosophers and especially Plato (428-347 B.C.. It even seems plausible
to trace their origins in China and India. Because it seems that they were the first to consider that all things need not be of a certain type or quit, but there are a stopover between. That is, be the pioneers in considering that there may be varying degrees of truth and falsehood. In case of colors, for example, between white and black there is a whole infinite scale: the shades of gray. Some recent theorems show that in principle fuzzy logic can be used to model any continuous system, be it based
in AI, or physics, or biology, or economics, etc. Investigators in many fields may find that fuzzy, commonsense models are more useful, and many more accurate than are standard mathematical ones. We analyze here the history and development of this problem: Fuzziness, or “Borrosidad” (in Castilian, essential to work with Uncertainty.
Super Fuzzy Matrices and Super Fuzzy Models for Social Scientists
Kandasamy, W B Vasantha; Amal, K
2008-01-01
This book introduces the concept of fuzzy super matrices and operations on them. This book will be highly useful to social scientists who wish to work with multi-expert models. Super fuzzy models using Fuzzy Cognitive Maps, Fuzzy Relational Maps, Bidirectional Associative Memories and Fuzzy Associative Memories are defined here. The authors introduce 13 multi-expert models using the notion of fuzzy supermatrices. These models are described with illustrative examples. This book has three chapters. In the first chaper, the basic concepts about super matrices and fuzzy super matrices are recalled. Chapter two introduces the notion of fuzzy super matrices adn their properties. The final chapter introduces many super fuzzy multi expert models.
Impact of supersymmetry on the nonperturbative dynamics of fuzzy spheres
Anagnostopoulos, K N; Nagao, K; Nishimura, J; Anagnostopoulos, Konstantinos N.; Azuma, Takehiro; Nagao, Keiichi; Nishimura, Jun
2005-01-01
We study a 4d supersymmetric matrix model with a cubic term, which incorporates fuzzy spheres as classical solutions, using Monte Carlo simulations and perturbative calculations. The fuzzy sphere in the supersymmetric model turns out to be always stable if the large-N limit is taken in such a way that various correlation functions scale. This is in striking contrast to analogous bosonic models, where the fuzzy sphere decays into the pure Yang-Mills vacuum due to quantum effects when the coefficient of the cubic term becomes smaller than a critical value. We also find that the power-law tail of the eigenvalue distribution, which exists in the supersymmetric model without the cubic term, disappears in the presence of the fuzzy sphere in the large-N limit. Coincident fuzzy spheres turn out to be unstable, which implies that the dynamically generated gauge group is U(1).
A New Neuro-Fuzzy Adaptive Genetic Algorithm
Institute of Scientific and Technical Information of China (English)
ZHU Lili; ZHANG Huanchun; JING Yazhi
2003-01-01
Novel neuro-fuzzy techniques are used to dynamically control parameter settings of genetic algorithms (GAs). The benchmark routine is an adaptive genetic algorithm (AGA) that uses a fuzzy knowledge-based system to control GA parameters. The self-learning ability of the cerebellar model ariculation controller(CMAC) neural network makes it possible for on-line learning the knowledge on GAs throughout the run. Automatically designing and tuning the fuzzy knowledge-base system, neurofuzzy techniques based on CMAC can find the optimized fuzzy system for AGA by the renhanced learning method. The Results from initial experiments show a Dynamic Parametric AGA system designed by the proposed automatic method and indicate the general applicability of the neuro-fuzzy AGA to a wide range of combinatorial optimization.
Fuzzy Dot Structure of BG-algebras
Directory of Open Access Journals (Sweden)
Tapan Senapati
2014-09-01
Full Text Available In this paper, the notions of fuzzy dot subalgebras is introduced together with fuzzy normal dot subalgebras and fuzzy dot ideals of BG-algebras. The homomorphic image and inverse image are investigated in fuzzy dot subalgebras and fuzzy dot ideals of BG-algebras. Also, the notion of fuzzy relations on the family of fuzzy dot subalgebras and fuzzy dot ideals of BG-algebras are introduced with some related properties.
Structural Holes in Directed Fuzzy Social Networks
Renjie Hu; Guangyu Zhang
2014-01-01
The structural holes have been a key issue in fuzzy social network analysis. For undirected fuzzy social networks where edges are just present or absent undirected fuzzy relation and have no more information attached, many structural holes measures have been presented, such as key fuzzy structural holes, general fuzzy structural holes, strong fuzzy structural holes, and weak fuzzy structural holes. There has been a growing need to design structural holes measures for directed fuzzy social net...
Indian Academy of Sciences (India)
ALI EBRAHIMNEJAD
2016-03-01
Transportation problem (TP) is an important network structured linear programming problem that arises in several contexts and has deservedly received a great deal of attention in the literature. The central concept in this problem is to find the least total transportation cost of a commodity in order to satisfy demands at destinations using available supplies at origins in a crisp environment. In real life situations, the decision maker may not be sure about the precise values of the coefficients belonging to the transportation problem. The aim of this paper is to introduce a formulation of TP involving interval-valued trapezoidal fuzzy numbers for the transportation costs and values of supplies and demands. We propose a fuzzy linear programming approach for solvinginterval-valued trapezoidal fuzzy numbers transportation problem based on comparison of interval-valued fuzzy numbers by the help of signed distance ranking. To illustrate the proposed approach an application example issolved. It is demonstrated that study of interval-valued trapezoidal fuzzy numbers transportation problem gives rise to the same expected results as those obtained for TP with trapezoidal fuzzy numbers.
A New Approach for Solving Fully Fuzzy Linear Systems
Directory of Open Access Journals (Sweden)
Amit Kumar
2011-01-01
Full Text Available Several authors have proposed different methods to find the solution of fully fuzzy linear systems (FFLSs that is, fuzzy linear system with fuzzy coefficients involving fuzzy variables. But all the existing methods are based on the assumption that all the fuzzy coefficients and the fuzzy variables are nonnegative fuzzy numbers. In this paper a new method is proposed to solve an FFLS with arbitrary coefficients and arbitrary solution vector, that is, there is no restriction on the elements that have been used in the FFLS. The primary objective of this paper is thus to introduce the concept and a computational method for solving FFLS with no non negative constraint on the parameters. The method incorporates the principles of linear programming in solving an FFLS with arbitrary coefficients and is not only easier to understand but also widens the scope of fuzzy linear equations in scientific applications. To show the advantages of the proposed method over existing methods we solve three FFLSs.
Grosse, Harald; Grosse, Harald; Reiter, Gert
1998-01-01
We introduce the fuzzy supersphere as sequence of finite-dimensional, noncommutative $Z_{2}$-graded algebras tending in a suitable limit to a dense subalgebra of the $Z_{2}$-graded algebra of ${\\cal H}^{\\infty}$-functions on the $(2| 2)$-dimensional supersphere. Noncommutative analogues of the body map (to the (fuzzy) sphere) and the super-deRham complex are introduced. In particular we reproduce the equality of the super-deRham cohomology of the supersphere and the ordinary deRham cohomology of its body on the "fuzzy level".
A fuzzy disaggregation technique
Directory of Open Access Journals (Sweden)
Alessandro Polli
2013-05-01
Full Text Available The aim of this paper is to analyze a problem of time series disaggregation in presence of broad information lack. In this framework it is not possible to follow standard methodologies, like those stemming from the Chow and Lin algorithm and based on probabilistic assumptions. In general terms, when information sets are limited, instead of referring to probabilistic measures it could be more appropriate to adopt an uncertainty measure satisfying only some general properties, like the fuzzy one. After a synthetic survey about fuzzy aggregation operators, we introduce a fuzzy disaggregation technique, based on Choquet capacity theory and characterized by De Finetti coherence.
Axiomatic of Fuzzy Complex Numbers
Directory of Open Access Journals (Sweden)
Angel Garrido
2012-04-01
Full Text Available Fuzzy numbers are fuzzy subsets of the set of real numbers satisfying some additional conditions. Fuzzy numbers allow us to model very difficult uncertainties in a very easy way. Arithmetic operations on fuzzy numbers have also been developed, and are based mainly on the crucial Extension Principle. When operating with fuzzy numbers, the results of our calculations strongly depend on the shape of the membership functions of these numbers. Logically, less regular membership functions may lead to very complicated calculi. Moreover, fuzzy numbers with a simpler shape of membership functions often have more intuitive and more natural interpretations. But not only must we apply the concept and the use of fuzzy sets, and its particular case of fuzzy number, but also the new and interesting mathematical construct designed by Fuzzy Complex Numbers, which is much more than a correlate of Complex Numbers in Mathematical Analysis. The selected perspective attempts here that of advancing through axiomatic descriptions.
Intuitionistic Fuzzy Possibilistic C Means Clustering Algorithms
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Arindam Chaudhuri
2015-01-01
Full Text Available Intuitionistic fuzzy sets (IFSs provide mathematical framework based on fuzzy sets to describe vagueness in data. It finds interesting and promising applications in different domains. Here, we develop an intuitionistic fuzzy possibilistic C means (IFPCM algorithm to cluster IFSs by hybridizing concepts of FPCM, IFSs, and distance measures. IFPCM resolves inherent problems encountered with information regarding membership values of objects to each cluster by generalizing membership and nonmembership with hesitancy degree. The algorithm is extended for clustering interval valued intuitionistic fuzzy sets (IVIFSs leading to interval valued intuitionistic fuzzy possibilistic C means (IVIFPCM. The clustering algorithm has membership and nonmembership degrees as intervals. Information regarding membership and typicality degrees of samples to all clusters is given by algorithm. The experiments are performed on both real and simulated datasets. It generates valuable information and produces overlapped clusters with different membership degrees. It takes into account inherent uncertainty in information captured by IFSs. Some advantages of algorithms are simplicity, flexibility, and low computational complexity. The algorithm is evaluated through cluster validity measures. The clustering accuracy of algorithm is investigated by classification datasets with labeled patterns. The algorithm maintains appreciable performance compared to other methods in terms of pureness ratio.
Fuzzy Multi-objective Linear Programming Approach
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Amna Rehmat
2007-07-01
Full Text Available Traveling salesman problem (TSP is one of the challenging real-life problems, attracting researchers of many fields including Artificial Intelligence, Operations Research, and Algorithm Design and Analysis. The problem has been well studied till now under different headings and has been solved with different approaches including genetic algorithms and linear programming. Conventional linear programming is designed to deal with crisp parameters, but information about real life systems is often available in the form of vague descriptions. Fuzzy methods are designed to handle vague terms, and are most suited to finding optimal solutions to problems with vague parameters. Fuzzy multi-objective linear programming, an amalgamation of fuzzy logic and multi-objective linear programming, deals with flexible aspiration levels or goals and fuzzy constraints with acceptable deviations. In this paper, a methodology, for solving a TSP with imprecise parameters, is deployed using fuzzy multi-objective linear programming. An example of TSP with multiple objectives and vague parameters is discussed.
Enhanced Image Segmentation Using Fuzzy Logic
Manpreet singh
2013-01-01
This research work proposed an improved edge detection techniques using fuzzy sets. The problem is to find edges in the image, as a first step in the process of scene reconstruction. Edges are scale-dependent and an edge may comprise other edges, but at a definite scale, an edge still has no width. This paper has presented different edge detection operators and their benefit when they merge with fuzzy logic theory. This paper has achieved the accuracy of edge detection up to 94.89 %. The prop...
Fuzzy Mathematics for Raw Silk Size Control
Institute of Scientific and Technical Information of China (English)
HU Zheng-yu; YU Hai-feng; GU Ping
2008-01-01
With photographing and experiments,this paper divides the cocoon layers into three categories according to their colors,establishes three-color membership function based on fuzzy mathemtics,constructs fuzzy sets which satisfy the range of size contrd by using the ordinary set and attached fiequency of three color cocoons combination,then achieves the ordinary sets of range of size control by choosing λ-cut.Under these ordinary sets,each end does duality relative level,then sets up relative matrix and overall sequence and finds the membership function to iudge whether the size cmtrol is normal.
Homomorphic Properties of Fuzzy Rough Groups
Institute of Scientific and Technical Information of China (English)
QIN Ke-yun; ZHANG Xiao-hua
2012-01-01
This paper is devoted to the discussion of homomorphic properties of fuzzy rough groups.The fuzzy approximation space was generated by fuzzy normal subgroups and the fuzzy rough approximation operators were discussed in the frame of fuzzy rough set model.The basic properties of fuzzy rough approximation operators were obtained.
Some Results on Fuzzy Soft Topological Spaces
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Cigdem Gunduz (Aras
2013-01-01
Full Text Available We introduce some important properties of fuzzy soft topological spaces. Furthermore, fuzzy soft continuous mapping, fuzzy soft open and fuzzy soft closed mappings, and fuzzy soft homeomorphism for fuzzy soft topological spaces are given and structural characteristics are discussed and studied.
Fuzzy Rough Ring and Its Prop erties
Institute of Scientific and Technical Information of China (English)
REN Bi-jun; FU Yan-ling
2013-01-01
This paper is devoted to the theories of fuzzy rough ring and its properties. The fuzzy approximation space generated by fuzzy ideals and the fuzzy rough approximation operators were proposed in the frame of fuzzy rough set model. The basic properties of fuzzy rough approximation operators were analyzed and the consistency between approximation operators and the binary operation of ring was discussed.
Some Weaker Forms of Fuzzy Faintly Open Mappings
Hakeem A. Othman
2015-01-01
This paper is devoted to introduce and investigate some weak forms of fuzzy open mappings, namely fuzzy faintly semi open (fuzzy faintly semi closed), fuzzy faintly preopen (fuzzy faintly preclosed), fuzzy faintly $\\alpha$-open (fuzzy faintly $\\alpha$-closed), fuzzy faintly semi preopen (fuzzy faintly semi preclosed) and fuzzy faintly $sp$- open (fuzzy faintly $sp$- closed) mappings and their fundamental properties are obtained. Moreover, their relationship with other types of fuzzy open (clo...
Fuzzy Sets, Fuzzy S-Open and S-Closed Mappings
Ahmad, B; Athar Kharal
2009-01-01
Several properties of fuzzy semiclosure and fuzzy semi-interior of fuzzy sets defined by Yalvac (1988), have been established and supported by counterexamples. We also study the characterizations and properties of fuzzy semi-open and fuzzy semi-closed sets. Moreover, we define fuzzy s-open and fuzzy s-closed mappings and give some interesting characterizations.
Competitive exception learning using fuzzy frequency distributions
W.-M. van den Bergh (Willem-Max); J.H. van den Berg (Jan)
2000-01-01
textabstractA competitive exception learning algorithm for finding a non-linear mapping is proposed which puts the emphasis on the discovery of the important exceptions rather than the main rules. To do so,we first cluster the output space using a competitive fuzzy clustering algorithm and derive a
Extended Fuzzy Logic Programs with Fuzzy Answer Set Semantics
Saad, Emad
This paper extends fuzzy logic programs [12, 24] to allow the explicit representation of classical negation as well as non-monotonic negation, by introducing the notion of extended fuzzy logic programs. We present the fuzzy answer set semantics for the extended fuzzy logic programs, which is based on the classical answer set semantics of classical extended logic programs [7]. We show that the proposed semantics is a natural extension to the classical answer set semantics of classical extended logic programs [7]. Furthermore, we define fixpoint semantics for extended fuzzy logic programs with and without non-monotonic negation, and study their relationship to the fuzzy answer set semantics. In addition, we show that the fuzzy answer set semantics is reduced to the stable fuzzy model semantics for normal fuzzy logic programs introduced in [42]. The importance of that is computational methods developed for normal fuzzy logic programs can be applied to the extended fuzzy logic programs. Moreover, we show that extended fuzzy logic programs can be intuitively used for representing and reasoning about actions in fuzzy environment.
Precision control of inverter welding power sources by using T-S fuzzy systems
Institute of Scientific and Technical Information of China (English)
Zhou Yiqing; Huang Shisheng; Zhang Hongbing; Wang Zhenmin; Xie Shengmian
2007-01-01
The functional relationship of approximation accuracy and number of fuzzy sets is used to find the rational balance point between the control accuracy and the control cost of fuzzy systems. This approach efficiently eliminates the drawback of rapid control cost increase caused by blind increase of fuzzy set number in practical engineering. The sufficient conditions for T-S fuzzy systems as universal approximators are derived. A special T-S fuzzy system that satisfied these conditions is analyzed, and the simulation results show that when the number of fuzzy sets is increased moderately, the model parameters' training epochs can be effectually decreased while the model accuracy improved significantly. A practical welding power source controlled by a T-S fuzzy system is developed with satisfactory experimental results.
Fuzziness and Relevance Theory
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Grace Qiao Zhang
2005-01-01
This paper investigates how the phenomenon of fuzzy language, such as `many' in `Mary has many friends', can be explained by Relevance Theory. It is concluded that fuzzy language use conforms with optimal relevance in that it can achieve the greatest positive effect with the least processing effort. It is the communicators themselves who decide whether or not optimal relevance is achieved, rather than the language form (fuzzy or non-fuzzy) used. People can skillfully adjust the deployment of different language forms or choose appropriate interpretations to suit different situations and communication needs. However, there are two challenges to RT: a. to extend its theory from individual relevance to group relevance; b. to embrace cultural considerations (because when relevance principles and cultural protocols are in conflict, the latter tends to prevail).
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Renato César Scarparo
2002-01-01
Full Text Available En este trabajo se presentan y demuestran algunos resultados de D.T. Luc y C, Vargas referentes a multifunciones con dominio y blanco en espacios vectoriales topológicos de Hausdorff sobre R, como así mismo se explícita el concepto de multifunción fuzzy de acuerdo a Papageogiou, y se demuestran dos teorema de S. S. Chag, con respecto a las multifunciones fuzzy, proposiciones todas estas, que integran una línea de resultados necesarios para la demostración de desigualdades variacionales para multifunciones fuzzy, a su vez necesarias, para la extensión fuzzy de conocido teorema de Walras.
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.
Malhas, Othman Qasim
1993-10-01
The concept of “abacus logic” has recently been developed by the author (Malhas, n.d.). In this paper the relation of abacus logic to the concept of fuzziness is explored. It is shown that if a certain “regularity” condition is met, concepts from fuzzy set theory arise naturally within abacus logics. In particular it is shown that every abacus logic then has a “pre-Zadeh orthocomplementation”. It is also shown that it is then possible to associate a fuzzy set with every proposition of abacus logic and that the collection of all such sets satisfies natural conditions expected in systems of fuzzy logic. Finally, the relevance to quantum mechanics is discussed.
Dialectic operator fuzzy logic
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程晓春; 姜云飞; 刘叙华
1996-01-01
Dialectic operator fuzzy logic (DOFL) is presented which is relevant,paraconsistent and nonmonotonic.DOFL can vividly describe the belief revision in the cognitive process and can infer reasonably well while the knowledge is inconsistent,imprecise or incomplete.
Yildiz, Cemil; ABBAS, Fadhil
2011-01-01
The concepts of fuzzy regular-I-closed set and fuzzy semi-I-regular set in fuzzy ideal topological spaces are investigated and some of their properties are obtained. Key words: Topological, Spaces, Fuzzy, Regular, Sets
Brusca, Ignazio; Corrao, Salvatore; Li Vigni, Piero; Sucato, Rosa; La Chiusa, Stella Maria
2002-06-01
Identification of autoantibodies directed against nuclear antigens is a very important finding in the assessment of autoimmune rheumatic diseases. In particular, the anti-DNA autoantibodies have assumed a fundamental importance, both speculative and clinical, in the study of the systemic lupus erythemathous. The aim of the present review is to focalize on anti-DNA the mechanisms of both induction and production of anti-DNA autoantibodies, pathophysiologic and diagnostic and clinical aspects. For this purpose, forty years of studies on this topic have been reviewed. Aspects on different conformational shapes of double-stranded DNA have been discussed such as related pathogenetic and diagnostic ones. Finally, the review has dealt with experimental therapies, focusing on both animal models and the most recent clinical trials according to Evidence Based Medicine.
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.
Fuzzy variable linear programming with fuzzy technical coefficients
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Sanwar Uddin Ahmad
2012-11-01
Full Text Available Normal 0 false false false EN-US X-NONE X-NONE Fuzzy linear programming is an application of fuzzy set theory in linear decision making problems and most of these problems are related to linear programming with fuzzy variables. In this paper an approximate but convenient method for solving these problems with fuzzy non-negative technical coefficient and without using the ranking functions, is proposed. With the help of numerical examples, the method is illustrated.
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Mohammad Izadikhah
2012-01-01
Full Text Available Decision making problem is the process of finding the best option from all of the feasible alternatives. One of the most important concepts in decision making process is to identify the weights of criteria. In real-world situation, because of incomplete or non-obtainable information, the data (attributes are often not deterministic and can be treated in forms of fuzzy numbers. This paper investigates a method for deriving the weights of criteria from the pair-wise comparison matrix with fuzzy elements. Finding the weights of criteria has been one of the most important issues in the field of decision-making and the present method uses goal programming to solve the resulted model. In addition, using a ranking function we convert each obtained fuzzy weight to a crisp one, which makes it possible to compare the criteria. The proposed model of this paper is supported by several examples and a case study.
Intuitionistic fuzzy alpha-continuity and intuitionistic fuzzy precontinuity
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Joung Kon Jeon
2005-01-01
Full Text Available A characterization of intuitionistic fuzzy α-open set is given, and conditions for an IFS to be an intuitionistic fuzzy α-open set are provided. Characterizations of intuitionistic fuzzy precontinuous (resp., α-continuous mappings are given.
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Kyung Ho Kim
2001-01-01
Full Text Available We consider the semigroup S¯ of the fuzzy points of a semigroup S, and discuss the relation between the fuzzy interior ideals and the subsets of S¯ in an (intra-regular semigroup S.
Shapley's value for fuzzy games
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Raúl Alvarado Sibaja
2009-02-01
Full Text Available This is the continuation of a previous article titled "Fuzzy Games", where I defined a new type of games based on the Multilinear extensions f, of characteristic functions and most of standard theorems for cooperative games also hold for this new type of games: The fuzzy games. Now we give some other properties and the extension of the definition of Shapley¨s Value for Fuzzy Games Keywords: game theory, fuzzy sets, multiattribute decisions.
Compactness theorems of fuzzy semantics
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
The relationship among diverse fuzzy semantics vs. the corresponding logic consequence operators has been analyzed systematically. The results that compactness and logical compactness of fuzzy semantics are equivalent to compactness and continuity of the logic consequence operator induced by the semantics respectively have been proved under certain conditions. A general compactness theorem of fuzzy semantics have been established which says that every fuzzy semantics defined on a free algebra with members corresponding to continuous functions is compact.
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Kharatti Lal
2015-12-01
Full Text Available This section define a level subring or level ideals obtain a set of necessary and sufficient condition for the equality of two ideals and characterizes field in terms of its fuzzy ideals. It also presents a procedure to construct a fuzzy subrings (fuzzy ideals from any given ascending chain of subring ideal. We prove that the lattice of fuzzy congruence of group G (respectively ring R is isomorphic to the lattice of fuzzy normal subgroup of G (respectively fuzzy ideals of R.In Yuan Boond Wu wangrning investigated the relationship between the fuzzy ideals and the fuzzy congruences on a distributive lattice and obtained that the lattice of fuzzy ideals is isomorphic to the lattice of fuzzy congruences on a generalized Boolean algebra. Fuzzy group theory can be used to describe, symmetries and permutation in nature and mathematics. The fuzzy group is one of the oldest branches of abstract algebra. For example group can be used is classify to all of the forms chemical crystal can take. Group can be used to count the number of non-equivalent objects and permutation or symmetries. For example, the number of different is switching functions of n, variable when permutation of the input are allowed. Beside crystallography and combinatory group have application of quantum mechanics.
Possibility Intuitionistic Fuzzy Soft Set
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Maruah Bashir
2012-01-01
Full Text Available Possibility intuitionistic fuzzy soft set and its operations are introduced, and a few of their properties are studied. An application of possibility intuitionistic fuzzy soft sets in decision making is investigated. A similarity measure of two possibility intuitionistic fuzzy soft sets has been discussed. An application of this similarity measure in medical diagnosis has been shown.
Fuzzy Soft Compact Topological Spaces
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Seema Mishra
2016-01-01
Full Text Available In this paper, we have studied compactness in fuzzy soft topological spaces which is a generalization of the corresponding concept by R. Lowen in the case of fuzzy topological spaces. Several basic desirable results have been established. In particular, we have proved the counterparts of Alexander’s subbase lemma and Tychonoff theorem for fuzzy soft topological spaces.
Two-Point Fuzzy Ostrowski Type Inequalities
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Muhammad Amer Latif
2013-08-01
Full Text Available Two-point fuzzy Ostrowski type inequalities are proved for fuzzy Hölder and fuzzy differentiable functions. The two-point fuzzy Ostrowski type inequality for M-lipshitzian mappings is also obtained. It is proved that only the two-point fuzzy Ostrowski type inequality for M-lipshitzian mappings is sharp and as a consequence generalize the two-point fuzzy Ostrowski type inequalities obtained for fuzzy differentiable functions.
Energy Technology Data Exchange (ETDEWEB)
Pierre, V.C.; Kaiser, J.T.; Barton, J.K.; /Caltech
2007-07-12
We report the 1.1-angstrom resolution crystal structure of a bulky rhodium complex bound to two different DNA sites, mismatched and matched in the oligonucleotide 5'-(dCGGAAATTCCCG){sub 2}-3'. At the AC mismatch site, the structure reveals ligand insertion from the minor groove with ejection of both mismatched bases and elucidates how destabilized mispairs in DNA may be recognized. This unique binding mode contrasts with major groove intercalation, observed at a matched site, where doubling of the base pair rise accommodates stacking of the intercalator. Mass spectral analysis reveals different photocleavage products associated with the two binding modes in the crystal, with only products characteristic of mismatch binding in solution. This structure, illustrating two clearly distinct binding modes for a molecule with DNA, provides a rationale for the interrogation and detection of mismatches.
Aircraft nonlinear optimal control using fuzzy gain scheduling
Nusyirwan, I. F.; Kung, Z. Y.
2016-10-01
Fuzzy gain scheduling is a common solution for nonlinear flight control. The highly nonlinear region of flight dynamics is determined throughout the examination of eigenvalues and the irregular pattern of root locus plots that show the nonlinear characteristic. By using the optimal control for command tracking, the pitch rate stability augmented system is constructed and the longitudinal flight control system is established. The outputs of optimal control for 21 linear systems are fed into the fuzzy gain scheduler. This research explores the capability in using both optimal control and fuzzy gain scheduling to improve the efficiency in finding the optimal control gains and to achieve Level 1 flying qualities. The numerical simulation work is carried out to determine the effectiveness and performance of the entire flight control system. The simulation results show that the fuzzy gain scheduling technique is able to perform in real time to find near optimal control law in various flying conditions.
Tao, Meng-Hua; Zhou, Jiachen; Rialdi, Alexander P; Martinez, Regina; Dabek, Joanna; Scelo, Ghislaine; Lissowska, Jolanta; Chen, Jia; Boffetta, Paolo
2014-10-01
DNA methylation is a potential mechanism linking indoor air pollution to adverse health effects. Fetal and early-life environmental exposures have been associated with altered DNA methylation and play a critical role in progress of diseases in adulthood. We investigated whether exposure to indoor air pollution from solid fuels at different lifetime periods was associated with global DNA methylation and methylation at the IFG2/H19 imprinting control region (ICR) in a population-based sample of non-smoking women from Warsaw, Poland. Global methylation and IFG2/H19 ICR methylation were assessed in peripheral blood DNA from 42 non-smoking women with Luminometric Methylation Assay (LUMA) and quantitative pyrosequencing, respectively. Linear regression models were applied to estimate associations between indoor air pollution and DNA methylation in the blood. Compared to women without exposure, the levels of LUMA methylation for women who had ever exposed to both coal and wood were reduced 6.70% (95% CI: -13.36, -0.04). Using both coal and wood before age 20 was associated with 6.95% decreased LUMA methylation (95% CI: -13.79, -0.11). Further, the negative correlations were more significant with exposure to solid fuels for cooking before age 20. There were no clear associations between indoor solid fuels exposure before age 20 and through the lifetime and IFG2/H19 ICR methylation. Our study of non-smoking women supports the hypothesis that exposure to indoor air pollution from solid fuels, even early-life exposure, has the capacity to modify DNA methylation that can be detected in peripheral blood.
Determination of interrill soil erodibility coefficient based on Fuzzy and Fuzzy-Genetic Systems
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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
Bifundamental Fuzzy 2-Sphere and Fuzzy Killing Spinors
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Horatiu Nastase
2010-07-01
Full Text Available We review our construction of a bifundamental version of the fuzzy 2-sphere and its relation to fuzzy Killing spinors, first obtained in the context of the ABJM membrane model. This is shown to be completely equivalent to the usual (adjoint fuzzy sphere. We discuss the mathematical details of the bifundamental fuzzy sphere and its field theory expansion in a model-independent way. We also examine how this new formulation affects the twisting of the fields, when comparing the field theory on the fuzzy sphere background with the compactification of the 'deconstructed' (higher dimensional field theory.
Multiple Fuzzy Classification Systems
Scherer, Rafał
2012-01-01
Fuzzy classiﬁers are important tools in exploratory data analysis, which is a vital set of methods used in various engineering, scientiﬁc and business applications. Fuzzy classiﬁers use fuzzy rules and do not require assumptions common to statistical classiﬁcation. Rough set theory is useful when data sets are incomplete. It deﬁnes a formal approximation of crisp sets by providing the lower and the upper approximation of the original set. Systems based on rough sets have natural ability to work on such data and incomplete vectors do not have to be preprocessed before classiﬁcation. To achieve better performance than existing machine learning systems, fuzzy classifiers and rough sets can be combined in ensembles. Such ensembles consist of a ﬁnite set of learning models, usually weak learners. The present book discusses the three aforementioned ﬁelds – fuzzy systems, rough sets and ensemble techniques. As the trained ensemble should represent a single hypothesis, a lot of attention is placed o...
Possibilistic Exponential Fuzzy Clustering
Institute of Scientific and Technical Information of China (English)
Kiatichai Treerattanapitak; Chuleerat Jaruskulchai
2013-01-01
Generally,abnormal points (noise and outliers) cause cluster analysis to produce low accuracy especially in fuzzy clustering.These data not only stay in clusters but also deviate the centroids from their true positions.Traditional fuzzy clustering like Fuzzy C-Means (FCM) always assigns data to all clusters which is not reasonable in some circumstances.By reformulating objective function in exponential equation,the algorithm aggressively selects data into the clusters.However noisy data and outliers cannot be properly handled by clustering process therefore they are forced to be included in a cluster because of a general probabilistic constraint that the sum of the membership degrees across all clusters is one.In order to improve this weakness,possibilistic approach relaxes this condition to improve membership assignment.Nevertheless,possibilistic clustering algorithms generally suffer from coincident clusters because their membership equations ignore the distance to other clusters.Although there are some possibilistic clustering approaches that do not generate coincident clusters,most of them require the right combination of multiple parameters for the algorithms to work.In this paper,we theoretically study Possibilistic Exponential Fuzzy Clustering (PXFCM) that integrates possibilistic approach with exponential fuzzy clustering.PXFCM has only one parameter and not only partitions the data but also filters noisy data or detects them as outliers.The comprehensive experiments show that PXFCM produces high accuracy in both clustering results and outlier detection without generating coincident problems.
A Novel Approach to Implement Takagi-Sugeno Fuzzy Models.
Chang, Chia-Wen; Tao, Chin-Wang
2017-09-01
This paper proposes new algorithms based on the fuzzy c-regressing model algorithm for Takagi-Sugeno (T-S) fuzzy modeling of the complex nonlinear systems. A fuzzy c-regression state model (FCRSM) algorithm is a T-S fuzzy model in which the functional antecedent and the state-space-model-type consequent are considered with the available input-output data. The antecedent and consequent forms of the proposed FCRSM consists mainly of two advantages: one is that the FCRSM has low computation load due to only one input variable is considered in the antecedent part; another is that the unknown system can be modeled to not only the polynomial form but also the state-space form. Moreover, the FCRSM can be extended to FCRSM-ND and FCRSM-Free algorithms. An algorithm FCRSM-ND is presented to find the T-S fuzzy state-space model of the nonlinear system when the input-output data cannot be precollected and an assumed effective controller is available. In the practical applications, the mathematical model of controller may be hard to be obtained. In this case, an online tuning algorithm, FCRSM-FREE, is designed such that the parameters of a T-S fuzzy controller and the T-S fuzzy state model of an unknown system can be online tuned simultaneously. Four numerical simulations are given to demonstrate the effectiveness of the proposed approach.
Fuzzy Critical Path Method Based on Lexicographic Ordering
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Phani Bushan Rao P
2012-01-01
Full Text Available The Critical Path Method (CPM is useful for planning and control of complex projects. The CPM identifies the critical activities in the critical path of an activity network. The successful implementation of CPM requires the availability of clear determined time duration for each activity. However, in practical situations this requirement is usually hard to fulfil since many of activities will be executed for the first time. Hence, there is always uncertainty about the time durations of activities in the network planning. This has led to the development of fuzzy CPM. In this paper, we use a Lexicographic ordering method for ranking fuzzy numbers to a critical path method in a fuzzy project network, where the duration time of each activity is represented by a trapezoidal fuzzy number. The proposed method is compared with fuzzy CPM based on different ranking methods of fuzzy numbers. The comparison reveals that the method proposed in this paper is more effective in determining the activity criticalities and finding the critical path. This new method is simple in calculating fuzzy critical path than many methods proposed so far in literature.
Supplier Selection in Textile Industry Using Fuzzy MADM
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Mohammad Mokhtari
2013-06-01
Full Text Available Supplier selection, Inventory control and economy order quantity is always 1 of the most important issues in manufacturing industries and textile industry is no exception. Unfortunately traditional performances of some managers in this industry have led to bankrupting and closuring of some factories. In this study, we use fuzzy Delphi, fuzzy AHP and VIKOR under fuzzy environment as a decision tool to supplier selection. The aim of this study is develop a model with high reliability for supplier selection in textile industry. From fuzzy Delphi we extracted five essential criteria and with fuzzy AHP we weight these criteria and with VIKOR under fuzzy environment we choose the best suppliers. We construct a questionnaire for fuzzy AHP and VIKOR that it’s not needed to notice cost orientation or benefit orientation of criteria. Our finding shows that five criteria; quality, location, cost, trust and delivery are the most effective criteria in textile supplier selection area. According to our proposed method suppliers s9, s15, s16, s4, s5 are the best supplier.
Fuzzy Sets Applications in Civil Engineering Basic Areas
UĞUR, Latif Onur; BAYKAN, Umut Naci
2016-01-01
Civil engineering is a professional engineering discipline that deals with the design, construction, and maintenance of the physical and naturally built environment, including works like roads, bridges, canals, dams, and buildings. This paper presents some Fuzzy Logic (FL) applications in civil engeering discipline and shows the potential of facilities of FL in this area. The potential role of fuzzy sets in analysing system and human uncertainty is investigated in the paper. The main finding ...
Stern, Mariana C.; Lin, Jie; Figueroa, Jonine D.; Kelsey, Karl T.; Kiltie, Anne E.; Yuan, Jian-Min; Matullo, Giuseppe; Fletcher, Tony; Benhamou, Simone; Taylor, Jack A.; Placidi, Donatella; Zhang, Zuo-Feng; Steineck, Gunnar; Rothman, Nathaniel; Kogevinas, Manolis; Silverman, Debra; Malats, Nuria; Chanock, Stephen; Wu, Xifeng; Karagas, Margaret R.; Andrew, Angeline S.; Nelson, Heather H.; Bishop, D. Timothy; Sak, Sei Chung; Choudhury, Ananya; Barrett, Jennifer H; Elliot, Faye; Corral, Román; Joshi, Amit D.; Gago-Dominguez, Manuela; Cortessis, Victoria K.; Xiang, Yong-Bing; Vineis, Paolo; Sacerdote, Carlotta; Guarrera, Simonetta; Polidoro, Silvia; Allione, Alessandra; Gurzau, Eugen; Koppova, Kvetoslava; Kumar, Rajiv; Rudnai, Peter; Porru, Stefano; Carta, Angela; Campagna, Marcello; Arici, Cecilia; Park, SungShim Lani; Garcia-Closas, Montserrat
2009-01-01
Tobacco smoking is the most important and well-established bladder cancer risk factor, and a rich source of chemical carcinogens and reactive oxygen species that can induce damage to DNA in urothelial cells. Therefore, common variation in DNA repair genes might modify bladder cancer risk. In this study we present results from meta- and pooled analyses conducted as part of the International Consortium of Bladder Cancer. We included data on 10 single nucleotide polymorphisms corresponding to 7 DNA repair genes from 13 studies. Pooled- and meta-analyses included 5,282 cases and 5,954 controls of non-Latino white origin. We found evidence for weak but consistent associations with ERCC2 D312N (rs1799793) (per allele OR = 1.10; 95% CI = 1.01–1.19; p = 0.021), NBN E185Q (rs1805794) (per allele OR = 1.09; 95% CI = 1.01–1.18; p = 0.028), and XPC A499V (rs2228000) (per allele OR = 1.10; 95% CI = 1.00–1.21, p = 0.044). The association with NBN E185Q was limited to ever smokers (interaction p = 0.002), and was strongest for the highest levels of smoking dose and smoking duration. Overall, our study provides the strongest evidence to date for a role of common variants in DNA repair genes in bladder carcinogenesis. PMID:19706757
A comparative analysis between fuzzy topsis and simplified fuzzy topsis
Ahmad, Sharifah Aniza Sayed; Mohamad, Daud
2017-08-01
Fuzzy Multiple Criteria Decision Making plays an important role in solving problems in decision making under fuzzy environment. Among the popular methods used is the fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) where the solution is based on the shortest distance from its positive ideal solution and the farthest distance from its negative ideal solution. The fuzzy TOPSIS method was first introduced by Chen (2000). At present, there are several variants of fuzzy TOPSIS methods and each of them claimed to have its own advantages. In this paper, a comparative analysis is made between the classical fuzzy TOPSIS method proposed by Chen in 2000 and the simplified fuzzy TOPSIS proposed by Sodhi in 2012. The purpose of this study is to show the similarities and the differences between these two methods and also elaborate on their strengths and limitations as well. A comparison is also made by providing numerical examples of both methods.
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.
Stent, Gunther S.
1970-01-01
This history for molecular genetics and its explanation of DNA begins with an analysis of the Golden Jubilee essay papers, 1955. The paper ends stating that the higher nervous system is the one major frontier of biological inquiry which still offers some romance of research. (Author/VW)
-Fuzzy Ideals in Ordered Semigroups
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Asghar Khan
2009-01-01
Full Text Available We introduce the concept of 𝒩-fuzzy left (right ideals in ordered semigroups and characterize ordered semigroups in terms of 𝒩-fuzzy left (right ideals. We characterize left regular (right regular and left simple (right simple ordered semigroups in terms of 𝒩-fuzzy left (𝒩-fuzzy right ideals. The semilattice of left (right simple semigroups in terms of 𝒩-fuzzy left (right ideals is discussed.
Tuning of Fuzzy PID Controllers
DEFF Research Database (Denmark)
Jantzen, Jan
1998-01-01
Since fuzzy controllers are nonlinear, it is more difficult to set the controller gains compared to proportional-integral-derivative (PID) controllers. This research paper proposes a design procedure and a tuning procedure that carries tuning rules from the PID domain over to fuzzy single......-loop controllers. The idea is to start with a tuned, conventional PID controller, replace it with an equivalent linear fuzzy controller, make the fuzzy controller nonlinear, and eventually fine-tune the nonlinear fuzzy controller. This is relevant whenever a PID controller is possible or already implemented....
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.
Fuzzy Multiresolution Neural Networks
Ying, Li; Qigang, Shang; Na, Lei
A fuzzy multi-resolution neural network (FMRANN) based on particle swarm algorithm is proposed to approximate arbitrary nonlinear function. The active function of the FMRANN consists of not only the wavelet functions, but also the scaling functions, whose translation parameters and dilation parameters are adjustable. A set of fuzzy rules are involved in the FMRANN. Each rule either corresponding to a subset consists of scaling functions, or corresponding to a sub-wavelet neural network consists of wavelets with same dilation parameters. Incorporating the time-frequency localization and multi-resolution properties of wavelets with the ability of self-learning of fuzzy neural network, the approximation ability of FMRANN can be remarkable improved. A particle swarm algorithm is adopted to learn the translation and dilation parameters of the wavelets and adjusting the shape of membership functions. Simulation examples are presented to validate the effectiveness of FMRANN.
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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.
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Fu-Gui Shi
2010-01-01
Full Text Available The notion of (L,M-fuzzy σ-algebras is introduced in the lattice value fuzzy set theory. It is a generalization of Klement's fuzzy σ-algebras. In our definition of (L,M-fuzzy σ-algebras, each L-fuzzy subset can be regarded as an L-measurable set to some degree.
Agudo, Antonio; Peluso, Marco; Sala, Núria; Capellá, Gabriel; Munnia, Armelle; Piro, Sara; Marín, Fátima; Ibáñez, Raquel; Amiano, Pilar; Tormo, M José; Ardanaz, Eva; Barricarte, Aurelio; Chirlaque, M Dolores; Dorronsoro, Miren; Larrañaga, Nerea; Martínez, Carmen; Navarro, Carmen; Quirós, J Ramón; Sánchez, M José; González, Carlos A
2009-06-01
Aromatic compounds such as polycyclic aromatic hydrocarbons, arylamines and heterocyclic amines require metabolic activation to form metabolites able to bind to DNA, a process mediated by polymorphic enzymes. We measured aromatic DNA adducts in white blood cells by the (32)P-post-labelling assay in a sample of 296 healthy adults (147 men and 149 women) from five regions of Spain. We also analyzed functional polymorphisms in the metabolic genes CYP1A1, CYP1A2, EPHX1, GSTM1, GSTT1, NAT2 and SULT1A1. A significant increased level of DNA aromatic adducts was found related to the fast oxidation-hydrolysis phenotype defined by the polymorphism I462V in CYP1A1, the allele A in IVS1-154C>A of CYP1A2 and the combination Tyrosine-Arginine for Y113H and H139R of EPHX1. Geometric means (adducts per 10(-9) normal nucleotides) were 2.17, 4.04 and 6.30 for slow, normal and fast phenotypes, respectively (P-trend = 0.01). Slow acetylation by NAT2 was associated with a significant decrease in adduct level; subjects with slow alleles *5A and *7A/B had in average 1.56 x 10(-9)adducts, as compared with 5.60 for those with normal NAT2 activity (P-value = 0.01). No association was seen with polymorphisms of other metabolic genes such as GSTM1, GSTT1 or SULT1A1. We concluded that the metabolic pathways of oxidation, hydrolysis and acetylation are relevant to the formation of bulky DNA adducts. This could suggest a potential involvement of aromatic compounds in the formation of such adducts; however, given lack of specificity of the post-labeling assay, a firm conclusion cannot be drawn.
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D. Vaamonde
2014-12-01
Conclusions: In this high-intensity endurance athlete, sperm parameters, mainly sperm morphology and DNA fragmentation, are altered. Further knowledge is needed with regards nutritional antioxidant intake and other dietetic strategies oriented toward avoiding oxidative damage in semen of high-performance triathletes. Moreover, adequate nutritional strategies must be found and nutritional advice given to athletes so as to palliate or dampen the effects of exercise on semen quality.
DEFF Research Database (Denmark)
Jantzen, Jan
1998-01-01
Control problems in the process industry are dominated by non-linear and time-varying behaviour, many inner loops, and much interaction between the control loops. Fuzzy controllers have in some cases nevertheless mimicked the control actions of a human operator. For high level control and supervi......Control problems in the process industry are dominated by non-linear and time-varying behaviour, many inner loops, and much interaction between the control loops. Fuzzy controllers have in some cases nevertheless mimicked the control actions of a human operator. For high level control...
Energy Technology Data Exchange (ETDEWEB)
Venkatesh, B.; George, M.K. [Multimedia University (Malaysia). Faculty of Engineering and Technology; Gooi, H.B. [Nanyang Technological University (Singapore). School of Electrical and Electronics Engineering
2004-09-01
A new optimal reactive power flow (ORPF) method is proposed which considers the inclusion of unified powerflow controllers (UPFC). The modelling and inclusion of UPFC in the solution of power flow equations is presented. The ORPF problem is formulated as a fuzzy optimisation problem considering the objectives of minimising system transmission loss and obtaining the best voltage profile. The fuzzy formulation of the ORPF problem is solved using an EP algorithm. The proposed method is applied on the 6-bus and 57-bus IEEE test systems and on a 191-bus Indian electric power system. The results demonstrate the applicability of the method. (author)
Alexanian, G G; Immirzi, G; Ydri, B
2001-01-01
Regularization of quantum field theories (QFT's) can be achieved by quantizing the underlying manifold (spacetime or spatial slice) thereby replacing it by a non-commutative matrix model or a ``fuzzy manifold''. Such discretization by quantization is remarkably successful in preserving symmetries and topological features, and altogether overcoming the fermion-doubling problem. In this paper, we report on our work on the ``fuzzification'' of the four-dimensional CP2 and its QFT's. CP2 is not spin, but spin${}_c$. Its Dirac operator has many unique features. They are explained and their fuzzy versions are described.
Syropoulos, Apostolos
2011-01-01
Dialectica categories are a very versatile categorical model of linear logic. These have been used to model many seemingly different things (e.g., Petri nets and Lambek's calculus). In this note, we expand our previous work on fuzzy petri nets to deal with fuzzy topological systems. One basic idea is to use as the dualizing object in the Dialectica categories construction, the unit real interval [0,1], which has all the properties of a {\\em lineale}. The second basic idea is to generalize Vickers's notion of a topological system.
Al-saggaf, Alawi A
2008-01-01
This paper attempt has been made to explain a fuzzy commitment scheme. In the conventional Commitment schemes, both committed string m and valid opening key are required to enable the sender to prove the commitment. However there could be many instances where the transmission involves noise or minor errors arising purely because of the factors over which neither the sender nor the receiver have any control. The fuzzy commitment scheme presented in this paper is to accept the opening key that is close to the original one in suitable distance metric, but not necessarily identical. The concept itself is illustrated with the help of simple situation.
Objective probability and quantum fuzziness
Mohrhoff, U
2007-01-01
This paper offers a critique of the Bayesian approach to quantum mechanics in general and of a recent paper by Caves, Fuchs, and Schack in particular (quant-ph/0608190 v2). In this paper the Bayesian interpretation of Born probabilities is defended against what the authors call the "objective-preparations view". The fact that Caves et al. and the proponents of this view equally misconstrue the time dependence of quantum states, voids the arguments pressed by the former against the latter. After tracing the genealogy of this common error, I argue that the real oxymoron is not an unknown quantum state, as the Bayesians hold, but an unprepared quantum state. I further argue that the essential role of probability in quantum theory is to define and quantify an objective fuzziness. This, more than anything, legitimizes conjoining "objective" to "probability". The measurement problem is essentially the problem of finding a coherent way of thinking about this objective fuzziness, and about the supervenience of the ma...
Fuzzy Index to Evaluate Edge Detection in Digital Images
Perez-Ornelas, Felicitas; Mendoza, Olivia; Melin, Patricia; Castro, Juan R.; Rodriguez-Diaz, Antonio; Castillo, Oscar
2015-01-01
In literature, we can find different metrics to evaluate the detected edges in digital images, like Pratt's figure of merit (FOM), Jaccard’s index (JI) and Dice’s coefficient (DC). These metrics compare two images, the first one is the reference edges image, and the second one is the detected edges image. It is important to mention that all existing metrics must binarize images before their evaluation. Binarization step causes information to be lost because an incomplete image is being evaluated. In this paper, we propose a fuzzy index (FI) for edge evaluation that does not use a binarization step. In order to process all detected edges, images are represented in their fuzzy form and all calculations are made with fuzzy sets operators and fuzzy Euclidean distance between both images. Our proposed index is compared to the most used metrics using synthetic images, with good results. PMID:26115362
A Temporal Neuro-Fuzzy Monitoring System to Manufacturing Systems
Mahdaoui, Rafik; Mouss, Mohamed Djamel; Chouhal, Ouahiba
2011-01-01
Fault diagnosis and failure prognosis are essential techniques in improving the safety of many manufacturing systems. Therefore, on-line fault detection and isolation is one of the most important tasks in safety-critical and intelligent control systems. Computational intelligence techniques are being investigated as extension of the traditional fault diagnosis methods. This paper discusses the Temporal Neuro-Fuzzy Systems (TNFS) fault diagnosis within an application study of a manufacturing system. The key issues of finding a suitable structure for detecting and isolating ten realistic actuator faults are described. Within this framework, data-processing interactive software of simulation baptized NEFDIAG (NEuro Fuzzy DIAGnosis) version 1.0 is developed. This software devoted primarily to creation, training and test of a classification Neuro-Fuzzy system of industrial process failures. NEFDIAG can be represented like a special type of fuzzy perceptron, with three layers used to classify patterns and failures....
Product design on the basis of fuzzy quality function deployment
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
In the implementation of quality function deployment (QFD), the determination of the target values of engineering characteristics is a complex decision process with multiple variables and multiple objectives that should trade off, and optimize all kinds of conflicts and constraints. A fuzzy linear programming model (FLP) is proposed. On the basis of the inherent fuzziness of QFD system, triangular fuzzy numbers are used to represent all the relationships and correlations, and then, the functional relationships between the customer needs and engineering characteristics and the functional correlations among the engineering characteristics are determined with the information in the house of quality (HoQ) fully used. The fuzzy linear programming (FLP) model aims to find the optimal target values of the engineering characteristics to maximize the customer satisfaction. Finally, the proposed method is illustrated by a numerical example.
Design and Analysis of Fuzzy Metagraph Based Data Structures
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A.Thirunavukarasu
2012-11-01
Full Text Available Fuzzy metagraph is an emerging technique used in the design of many information processing systems like transaction processing systems, decision support systems, and workflow systems. Very often, evena carefully chosen graph data structure could be improvised to provide more efficiency in terms of time complexity or space complexity or both. In this paper, a well-designed fuzzy metagraph is proposed and distinct matrices have been developed to reduce the time-complexity. Fuzzy Expert System (FES integrated with theFuzzy Metagraph can yield excellent state-of-the-art decisions under complex circumstances which other graph structures find it very difficult. Thus a user with this effective decision making system can make effective and quick decisions to solve the problem.
A Development of Self-Organization Algorithm for Fuzzy Logic Controller
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Park, Y.M.; Moon, U.C. [Seoul National Univ. (Korea, Republic of). Coll. of Engineering; Lee, K.Y. [Pennsylvania State Univ., University Park, PA (United States). Dept. of Electrical Engineering
1994-09-01
This paper proposes a complete design method for an on-line self-organizing fuzzy logic controller without using any plant model. By mimicking the human learning process, the control algorithm finds control rules of a system for which little knowledge has been known. To realize this, a concept of Fuzzy Auto-Regressive Moving Average(FARMA) rule is introduced. In a conventional fuzzy logic control, knowledge on the system supplied by an expert is required in developing control rules. However, the proposed new fuzzy logic controller needs no expert in making control rules. Instead, rules are generated using the history of input-output pairs, and new inference and defuzzification methods are developed. The generated rules are strode in the fuzzy rule space and updated on-line by a self-organizing procedure. The validity of the proposed fuzzy logic control method has been demonstrated numerically in controlling an inverted pendulum. (author). 28 refs., 16 figs.
An introduction to fuzzy linear programming problems theory, methods and applications
Kaur, Jagdeep
2016-01-01
The book presents a snapshot of the state of the art in the field of fully fuzzy linear programming. The main focus is on showing current methods for finding the fuzzy optimal solution of fully fuzzy linear programming problems in which all the parameters and decision variables are represented by non-negative fuzzy numbers. It presents new methods developed by the authors, as well as existing methods developed by others, and their application to real-world problems, including fuzzy transportation problems. Moreover, it compares the outcomes of the different methods and discusses their advantages/disadvantages. As the first work to collect at one place the most important methods for solving fuzzy linear programming problems, the book represents a useful reference guide for students and researchers, providing them with the necessary theoretical and practical knowledge to deal with linear programming problems under uncertainty.
Mueen, Zeina; Ramli, Razamin; Zaibidi, Nerda Zura
2016-08-01
In this paper, we propose a procedure to find different performance measurements under crisp value terms for new single fuzzy queue FM/F(H1,H2)/1 with two classes, where arrival rate and service rates are all fuzzy numbers which are represented by triangular and trapezoidal fuzzy numbers. The basic idea is to obtain exact crisp values from the fuzzy value, which is more realistic in the practical queueing system. This is done by adopting left and right ranking method to remove the fuzziness before computing the performance measurements using conventional queueing theory. The main advantage of this approach is its simplicity in application, giving exact real data around fuzzy values. This approach can also be used in all types of queueing systems by taking two types of symmetrical linear membership functions. Numerical illustration is solved in this article to obtain two groups of crisp values in the queueing system under consideration.
Chaotic System Identification Based on a Fuzzy Wiener Model with Particle Swarm Optimization
Institute of Scientific and Technical Information of China (English)
LI Yong; TANG Ying-Gan
2010-01-01
@@ A fuzzy Wiener model is proposed to identify chaotic systems.The proposed fuzzy Wiener model consists of two parts,one is a linear dynamic subsystem and the other is a static nonlinear part,which is represented by the Takagi-Sugeno fuzzy model Identification of chaotic systems is converted to find optimal parameters of the fuzzy Wiener model by minimizing the state error between the original chaotic system and the fuzzy Wiener model.Particle swarm optimization algorithm,a global optimizer,is used to search the optimal parameter of the fuzzy Wiener model.The proposed method can identify the parameters of the linear part and nonlinear part simultaneously.Numerical simulations for Henón and Lozi chaotic system identification show the effectiveness of the proposed method.
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Wen-Jer Chang
2014-01-01
Full Text Available For nonlinear discrete-time stochastic systems, a fuzzy controller design methodology is developed in this paper subject to state variance constraint and passivity constraint. According to fuzzy model based control technique, the nonlinear discrete-time stochastic systems considered in this paper are represented by the discrete-time Takagi-Sugeno fuzzy models with multiplicative noise. Employing Lyapunov stability theory, upper bound covariance control theory, and passivity theory, some sufficient conditions are derived to find parallel distributed compensation based fuzzy controllers. In order to solve these sufficient conditions, an iterative linear matrix inequality algorithm is applied based on the linear matrix inequality technique. Finally, the fuzzy stabilization problem for nonlinear discrete ship steering stochastic systems is investigated in the numerical example to illustrate the feasibility and validity of proposed fuzzy controller design method.
Grey Prediction Fuzzy Control of the Target Tracking System in a Robot Weapon
Institute of Scientific and Technical Information of China (English)
WANG Jian-zhong; JI Jiang-tao; WANG Hong-ru
2007-01-01
Grey modeling can be used to predict the behavioral development of a system and find out the lead control values of the system. By using fuzzy inference, PID parameters can be adjusted on line by the fuzzy controller with PID parameters self-tuning. According to the characteristics of target tracking system in a robot weapon, grey prediction theory and fuzzy PID control ideas are combined. A grey prediction mathematical model is constructed and a fuzzy PID controller with grey prediction was developed. Simulation result shows fuzzy PID control algorithm with grey prediction is an efficient method that can improve the control equality and robustness of traditional PID control and fuzzy PID control, and has much better performance for target tracking.
A practical engineering method for fuzzy reliability analysis of mechanical structures
Energy Technology Data Exchange (ETDEWEB)
Li Bing; Zhu Meilin; Xu Kai
2000-03-01
The fuzzy sets theory in reliability analyses is studied. The structure stress is related to several other variables, such as structure sizes, material properties, external loads; in most cases, it is difficult to be expressed in a mathematical formula, and the related variables are not random variables, but fuzzy variables or other uncertain variables which have not only randomness but also fuzziness. In this paper, a novel approach is presented to use the finite element analysis as a 'numerical experiment' tool, and to find directly, by fuzzy linear regression method, the statistical property of the structure stress. Based on the fuzzy stress-random strength interference model proposed in this paper, the fuzzy reliability of the mechanical structure can be evaluated. The compressor blade of a given turbocharger is then introduced as a realistic example to illustrate the approach.
DEFF Research Database (Denmark)
Franco de los Rios, Camilo Andres; Hougaard, Jens Leth; Nielsen, Kurt
for decision support and multidimensional interval analysis. First, the original approach is extended using fuzzy set theory which makes it possible to handle both non-interval and interval data. Second, we re-examine the ranking procedure based on semi-equivalence classes and suggest a new complementary...
FUZZY PREFERENCES IN CONFLICTS
Institute of Scientific and Technical Information of China (English)
Mubarak S. AL-MUTAIRI; Keith W. HIPEL; Mohamed S. KAMEL
2008-01-01
A systematic fuzzy approach is developed to model fuzziness and uncertainties in the preferences of decision makers involved in a conflict. This unique fuzzy preference formulation is used within the paradigm of the Graph Model for Conflict Resolution in which a given dispute is modeled in terms of decision makers, each decision maker's courses of actions or options, and each decision maker's preferences concerning the states or outcomes which could take place. In order to be able to determine the stability of each state for each decision maker and the possible equilibria or resolutions, a range of solution concepts describing potential human behavior under conflict are defined for use with fuzzy preferences. More specifically, strong and weak definitions of stability are provided for the solution concepts called Nash, general metarational, symmetric metarational, and sequential stability. To illustrate how these solution concepts can be conveniently used in practice, they are applied to a dispute over the contamination of an aquifer by a chemical company located in Elmira, Ontario, Canada.
Fuzzy efficiency without convexity
DEFF Research Database (Denmark)
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...
Energy Technology Data Exchange (ETDEWEB)
Batic, Davide, E-mail: dbatic@uniandes.edu.c [Departamento de Matematica, Universidad de los Andes, Cra 1E, No. 18A-10, Bogota, Colombia Department of Mathematics, University of West Indies, Kingston (Jamaica); Nicolini, Piero, E-mail: nicolini@th.physik.uni-frankfurt.d [Frankfurt Institute for Advanced Studies (FIAS), Institut fuer Theoretische Physik, Johann Wolfgang Goethe-Universitaet, Ruth-Moufang-Strasse 1, 60438 Frankfurt am Main (Germany)
2010-08-16
We study the stability of the noncommutative Schwarzschild black hole interior by analysing the propagation of a massless scalar field between the two horizons. We show that the spacetime fuzziness triggered by the field higher momenta can cure the classical exponential blue-shift divergence, suppressing the emergence of infinite energy density in a region nearby the Cauchy horizon.
Method for solving fully fuzzy linear programming problems using deviation degree measure
Institute of Scientific and Technical Information of China (English)
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.
The Application of Imperialist Competitive Algorithm for Fuzzy Random Portfolio Selection Problem
EhsanHesamSadati, Mir; Bagherzadeh Mohasefi, Jamshid
2013-10-01
This paper presents an implementation of the Imperialist Competitive Algorithm (ICA) for solving the fuzzy random portfolio selection problem where the asset returns are represented by fuzzy random variables. Portfolio Optimization is an important research field in modern finance. By using the necessity-based model, fuzzy random variables reformulate to the linear programming and ICA will be designed to find the optimum solution. To show the efficiency of the proposed method, a numerical example illustrates the whole idea on implementation of ICA for fuzzy random portfolio selection problem.
On Nash Equilibrium Strategy of Two-person Zero-sum Games with Trapezoidal Fuzzy Payoffs
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Bapi Dutta
2014-09-01
Full Text Available In this paper, we investigate Nash equilibrium strategy of two-person zero-sum games with fuzzy payoffs. Based on fuzzy max order, Maeda and Cunlin constructed several models in symmetric triangular and asymmetric triangular fuzzy environment, respectively. We extended their models in trapezoidal fuzzy environment and proposed the existence of equilibrium strategies for these models. We also established the relation between Pareto Nash equilibrium strategy and parametric bi-matrix game. In addition, numerical examples are presented to find Pareto Nash equilibrium strategy and weak Pareto Nash equilibrium strategy from bi-matrix game.
Masudin, I.; Saputro, T. E.
2016-02-01
In today's technology, electronic trading transaction via internet has been utilized properly with rapid growth. This paper intends to evaluate related to B2C e-commerce website in order to find out the one which meets the usability factors better than another. The influential factors to B2C e-commerce website are determined for two big retailer websites. The factors are investigated based on the consideration of several studies and conformed to the website characteristics. The evaluation is conducted by using different methods namely fuzzy AHP and hierarchical fuzzy TOPSIS so that the final evaluation can be compared. Fuzzy triangular number is adopted to deal with imprecise judgment under fuzzy environment.
Fuzzy knowledge management for the semantic web
Ma, Zongmin; Yan, Li; Cheng, Jingwei
2014-01-01
This book goes to great depth concerning the fast growing topic of technologies and approaches of fuzzy logic in the Semantic Web. The topics of this book include fuzzy description logics and fuzzy ontologies, queries of fuzzy description logics and fuzzy ontology knowledge bases, extraction of fuzzy description logics and ontologies from fuzzy data models, storage of fuzzy ontology knowledge bases in fuzzy databases, fuzzy Semantic Web ontology mapping, and fuzzy rules and their interchange in the Semantic Web. The book aims to provide a single record of current research in the fuzzy knowledge representation and reasoning for the Semantic Web. The objective of the book is to provide the state of the art information to researchers, practitioners and graduate students of the Web intelligence and at the same time serve the knowledge and data engineering professional faced with non-traditional applications that make the application of conventional approaches difficult or impossible.
Intuitionistic Fuzzy Graphs with Categorical Properties
Directory of Open Access Journals (Sweden)
Hossein Rashmanlou
2015-09-01
Full Text Available The main purpose of this paper is to show the rationality of some operations, defined or to be defined, on intuitionistic fuzzy graphs. Firstly, three kinds of new product operations (called direct product, lexicographic product, and strong product are defined in intuitionistic fuzzy graphs, and some important notions on intuitionistic fuzzy graphs are demonstrated by characterizing these notions and their level counterparts graphs such as intuitionistic fuzzy complete graph, cartesian product of intuitionistic fuzzy graphs, composition of intuitionistic fuzzy graphs, union of intuitionistic fuzzy graphs, and join of intuitionistic fuzzy graphs. As a result, a kind of representations of intuitionistic fuzzy graphs and intuitionistic fuzzy complete graphs are given. Next, categorical goodness of intuitionistic fuzzy graphs is illustrated by proving that the category of intuitionistic fuzzy graphs and homomorphisms between them is isomorphic-closed, complete, and co-complete.
Probability representations of fuzzy systems
Institute of Scientific and Technical Information of China (English)
LI Hongxing
2006-01-01
In this paper, the probability significance of fuzzy systems is revealed. It is pointed out that COG method, a defuzzification technique used commonly in fuzzy systems, is reasonable and is the optimal method in the sense of mean square. Based on different fuzzy implication operators, several typical probability distributions such as Zadeh distribution, Mamdani distribution, Lukasiewicz distribution, etc. are given. Those distributions act as "inner kernels" of fuzzy systems. Furthermore, by some properties of probability distributions of fuzzy systems, it is also demonstrated that CRI method, proposed by Zadeh, for constructing fuzzy systems is basically reasonable and effective. Besides, the special action of uniform probability distributions in fuzzy systems is characterized. Finally, the relationship between CRI method and triple I method is discussed. In the sense of construction of fuzzy systems, when restricting three fuzzy implication operators in triple I method to the same operator, CRI method and triple I method may be related in the following three basic ways: 1) Two methods are equivalent; 2) the latter is a degeneration of the former; 3) the latter is trivial whereas the former is not. When three fuzzy implication operators in triple I method are not restricted to the same operator, CRI method is a special case of triple I method; that is, triple I method is a more comprehensive algorithm. Since triple I method has a good logical foundation and comprises an idea of optimization of reasoning, triple I method will possess a beautiful vista of application.
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.
Neuro-fuzzy system modeling based on automatic fuzzy clustering
Institute of Scientific and Technical Information of China (English)
Yuangang TANG; Fuchun SUN; Zengqi SUN
2005-01-01
A neuro-fuzzy system model based on automatic fuzzy clustering is proposed.A hybrid model identification algorithm is also developed to decide the model structure and model parameters.The algorithm mainly includes three parts:1) Automatic fuzzy C-means (AFCM),which is applied to generate fuzzy rules automatically,and then fix on the size of the neuro-fuzzy network,by which the complexity of system design is reducesd greatly at the price of the fitting capability;2) Recursive least square estimation (RLSE).It is used to update the parameters of Takagi-Sugeno model,which is employed to describe the behavior of the system;3) Gradient descent algorithm is also proposed for the fuzzy values according to the back propagation algorithm of neural network.Finally,modeling the dynamical equation of the two-link manipulator with the proposed approach is illustrated to validate the feasibility of the method.
Generalised Interval-Valued Fuzzy Soft Set
Shawkat Alkhazaleh; Abdul Razak Salleh
2012-01-01
We introduce the concept of generalised interval-valued fuzzy soft set and its operations and study some of their properties. We give applications of this theory in solving a decision making problem. We also introduce a similarity measure of two generalised interval-valued fuzzy soft sets and discuss its application in a medical diagnosis problem: fuzzy set; soft set; fuzzy soft set; generalised fuzzy soft set; generalised interval-valued fuzzy soft set; interval-valued fuzz...
On Intuitionistic Fuzzy Magnified Translation in Semigroups
Sardar, Sujit Kumar; Mandal, Manasi; Majumder, Samit Kumar
2011-01-01
The notion of intuitionistic fuzzy sets was introduced by Atanassov as a generalization of the notion of fuzzy sets. S.K Sardar and S.K. Majumder unified the idea of fuzzy translation and fuzzy multiplication of Vasantha Kandasamy to introduce the concept of fuzzy magnified translation in groups and semigroups. The purpose of this paper is to intuitionistically fuzzify(by using Atanassov's idea) the concept of fuzzy magnified translation in semigroups. Here among other results we obtain some ...
Lower and Upper Fuzzy Topological Subhypergroups
Institute of Scientific and Technical Information of China (English)
Irina CRISTEA; Jian Ming ZHAN
2013-01-01
This paper provides a new connection between algebraic hyperstructures and fuzzy sets.More specifically,using both properties of fuzzy topological spaces and those of fuzzy subhypergroups,we define the notions of lower (upper) fuzzy topological subhypergroups of a hypergroup endowed with a fuzzy topology.Some results concerning the image and the inverse image of a lower (upper) topological subhypergroup under a very good homomorphism of hypergroups (endowed with fuzzy topologies) are pointed out.
The squashed fuzzy sphere, fuzzy strings and the Landau problem
Andronache, Stefan
2015-01-01
We discuss the squashed fuzzy sphere, which is a projection of the fuzzy sphere onto the equatorial plane, and use it to illustrate the stringy aspects of noncommutative field theory. We elaborate explicitly how strings linking its two coincident sheets arise in terms of fuzzy spherical harmonics. In the large N limit, the matrix-model Laplacian is shown to correctly reproduce the semi-classical dynamics of these charged strings, as given by the Landau problem.
The squashed fuzzy sphere, fuzzy strings and the Landau problem
Andronache, Stefan; Steinacker, Harold C.
2015-07-01
We discuss the squashed fuzzy sphere, which is a projection of the fuzzy sphere onto the equatorial plane, and use it to illustrate the stringy aspects of noncommutative field theory. We elaborate explicitly how strings linking its two coincident sheets arise in terms of fuzzy spherical harmonics. In the large N limit, the matrix-model Laplacian is shown to correctly reproduce the semi-classical dynamics of these charged strings, as given by the Landau problem.
Genetic Algorithm Optimization for Determining Fuzzy Measures from Fuzzy Data
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Chen Li
2013-01-01
Full Text Available Fuzzy measures and fuzzy integrals have been successfully used in many real applications. How to determine fuzzy measures is a very difficult problem in these applications. Though there have existed some methodologies for solving this problem, such as genetic algorithms, gradient descent algorithms, neural networks, and particle swarm algorithm, it is hard to say which one is more appropriate and more feasible. Each method has its advantages. Most of the existed works can only deal with the data consisting of classic numbers which may arise limitations in practical applications. It is not reasonable to assume that all data are real data before we elicit them from practical data. Sometimes, fuzzy data may exist, such as in pharmacological, financial and sociological applications. Thus, we make an attempt to determine a more generalized type of general fuzzy measures from fuzzy data by means of genetic algorithms and Choquet integrals. In this paper, we make the first effort to define the σ-λ rules. Furthermore we define and characterize the Choquet integrals of interval-valued functions and fuzzy-number-valued functions based on σ-λ rules. In addition, we design a special genetic algorithm to determine a type of general fuzzy measures from fuzzy data.
GENERALIZED FUZZY FILTERS OF BL-ALGEBRAS
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
The concept of quasi-coincidence of a fuzzy interval value with an interval valued fuzzy set is considered. In fact, this is a generalization of quasi-coincidence of a fuzzy point with a fuzzy set. By using this new idea, the notion of interval valued (∈, ∈∨q)-fuzzy filters in BL-algebras which is a generalization of fuzzy filters of BL-algebras, is defined, and related properties are investigated. In particular, the concept of a fuzzy subgroup with thresholds is extended to the concept of an interval valued fuzzy filter with thresholds in BL-algebras.
On the intuitionistic fuzzy topological spaces
Energy Technology Data Exchange (ETDEWEB)
Saadati, Reza [Department of Mathematics, Azad University, Amol, P.O. Box 678 (Iran, Islamic Republic of)] e-mail: rsaadati@eml.cc; Park, Jin Han [Division of Mathematical Sciences, Pukyong National University, 599-1 Daeyeon, 3-Dong Nam-Gu, Pusan 608 737 (Korea, Republic of)] e-mail: jihpark@pknu.ac.kr
2006-01-01
In this paper, we define precompact set in intuitionistic fuzzy metric spaces and prove that any subset of an intuitionistic fuzzy metric space is compact if and only if it is precompact and complete. Also we define topologically complete intuitionistic fuzzy metrizable spaces and prove that any G{sub {delta}} set in a complete intuitionistic fuzzy metric spaces is a topologically complete intuitionistic fuzzy metrizable space and vice versa. Finally, we define intuitionistic fuzzy normed spaces and fuzzy boundedness for linear operators and so we prove that every finite dimensional intuitionistic fuzzy normed space is complete.
On the intuitionistic fuzzy topological spaces
Saadati, Reza; Park, Jin Han
2006-01-01
In this paper, we define precompact set in intuitionistic fuzzy metric spaces and prove that any subset of an intuitionistic fuzzy metric space is compact if and only if it is precompact and complete. Also we define topologically complete intuitionistic fuzzy metrizable spaces and prove that any $G_{\\delta }$ set in a complete intuitionistic fuzzy metric spaces is a topologically complete intuitionistic fuzzy metrizable space and vice versa. Finally, we define intuitionistic fuzzy normed spaces and fuzzy boundedness for linear operators and so we prove that every finite dimensional intuitionistic fuzzy normed space is complete.
Stochastic Optimal Estimation with Fuzzy Random Variables and Fuzzy Kalman Filtering
Institute of Scientific and Technical Information of China (English)
FENG Yu-hu
2005-01-01
By constructing a mean-square performance index in the case of fuzzy random variable, the optimal estimation theorem for unknown fuzzy state using the fuzzy observation data are given. The state and output of linear discrete-time dynamic fuzzy system with Gaussian noise are Gaussian fuzzy random variable sequences. An approach to fuzzy Kalman filtering is discussed. Fuzzy Kalman filtering contains two parts: a real-valued non-random recurrence equation and the standard Kalman filtering.
Fuzzy logic particle tracking velocimetry
Wernet, Mark P.
1993-01-01
Fuzzy logic has proven to be a simple and robust method for process control. Instead of requiring a complex model of the system, a user defined rule base is used to control the process. In this paper the principles of fuzzy logic control are applied to Particle Tracking Velocimetry (PTV). Two frames of digitally recorded, single exposure particle imagery are used as input. The fuzzy processor uses the local particle displacement information to determine the correct particle tracks. Fuzzy PTV is an improvement over traditional PTV techniques which typically require a sequence (greater than 2) of image frames for accurately tracking particles. The fuzzy processor executes in software on a PC without the use of specialized array or fuzzy logic processors. A pair of sample input images with roughly 300 particle images each, results in more than 200 velocity vectors in under 8 seconds of processing time.
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.
Immune Genetic Learning of Fuzzy Cognitive Map
Institute of Scientific and Technical Information of China (English)
LIN Chun-mei; HE Yue; TANG Bing-yong
2006-01-01
This paper presents a hybrid methodology of automatically constructing fuzzy cognitive map (FCM). The method uses immune genetic algorithm to learn the connection matrix of FCM. In the algorithm, the DNA coding method is used and an immune operator based on immune mechanism is constructed. The characteristics of the system and the experts' knowledge are abstracted as vaccine for restraining the degenerative phenomena during evolution so as to improve the algorithmic efficiency. Finally, an illustrative example is provided, and its results suggest that the method is capable of automatically generating FCM model.
Control of a dc motor using fuzzy logic control algorithm | Usoro ...
African Journals Online (AJOL)
This study sought to establish the impact of a fuzzy logic controller (FLC) and a ... A choice of seven membership functions was designed for the error and change in ... Based on the findings, it was observed that the fuzzy speed controlled DC ...
A critical study of fuzzy logic as a scientific method in social sciences ...
African Journals Online (AJOL)
A critical study of fuzzy logic as a scientific method in social sciences. ... PROMOTING ACCESS TO AFRICAN RESEARCH ... The findings of this study show that Fuzzy logic doesn't have basic and necessary features of a scientific method and ...
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.
Phase structures in fuzzy geometries
Govindarajan, T R; Gupta, K S; Martin, X
2012-01-01
We study phase structures of quantum field theories in fuzzy geometries. Several examples of fuzzy geometries as well as QFT's on such geometries are considered. They are fuzzy spheres and beyond as well as noncommutative deformations of BTZ blackholes. Analysis is done analytically and through simulations. Several features like novel stripe phases as well as spontaneous symmetry breaking avoiding Colemen, Mermin, Wagner theorem are brought out. Also we establish that these phases are stable due to topological obstructions.
Selection of Vendor Based on Intuitionistic Fuzzy Analytical Hierarchy Process
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Prabjot Kaur
2014-01-01
Full Text Available Business environment is characterized by greater domestic and international competitive position in the global market. Vendors play a key role in achieving the so-called corporate competition. It is not easy however to identify good vendors because evaluation is based on multiple criteria. In practice, for VSP most of the input information about the criteria is not known precisely. Intuitionistic fuzzy set is an extension of the classical fuzzy set theory (FST, which is a suitable way to deal with impreciseness. In other words, the application of intuitionistic fuzzy sets instead of fuzzy sets means the introduction of another degree of freedom called nonmembership function into the set description. In this paper, we proposed a triangular intuitionistic fuzzy number based approach for the vendor selection problem using analytical hierarchy process. The crisp data of the vendors is represented in the form of triangular intuitionistic fuzzy numbers. By applying AHP which involves decomposition, pairwise comparison, and deriving priorities for the various levels of the hierarchy, an overall crisp priority is obtained for ranking the best vendor. A numerical example illustrates our method. Lastly a sensitivity analysis is performed to find the most critical criterion on the basis of which vendor is selected.
Hybrid Neuro-Fuzzy Systems for Software Development Effort Estimation
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Rama Sree P
2012-12-01
Full Text Available The major prevailing challenges for Software Projects are Software Estimations like cost estimation, effort estimation, quality estimation and risk analysis. Though there are several algorithmiccost estimation models in practice, each model has its own pros and cons for estimation. There is still a need to find a model that gives accurate estimates. This paper is an attempt to experiment different types of Neuro-Fuzzy Models. Using the types of Neuro-Fuzzy Models for software effort prediction is a relatively unexplored area. Two case studies are used for this purpose. The first is based on NASA-93dataset and the other is based on Maxwell-62 dataset. The case studies were analyzed using six different criterions like Variance Accounted For (VAF, Mean Absolute Relative Error (MARE, VarianceAbsolute Relative Error (VARE, Mean Balance Relative Error (Mean BRE, Mean Magnitude Relative Error (MMRE and Prediction. From the results and from reasoning, it is concluded that Type BCompensationNeuro-Fuzzy Model with more fuzzy rules is best suitable for cases in which the datapoints are more linear. Type J Neuro-Fuzzy Model with more fuzzy rules is best suitable for cases in which the datapoints are not linear.
Fuzzy model investic do High-tech projektů
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Alžběta Kubíčková
2013-10-01
Full Text Available Purpose of the article: Relations among parameters of High-tech projects are very complex, vague, partially inconsistent and multidimensional. Optimal decisions to invest into High-tech companies require top field experts and knowledgeable investors. Therefore the conventional methods of investments analysis are not relevant. Therefore fuzzy logic is introduced. Methodology/methods: A fuzzy knowledge base is a flexible framework for acquisition of vague inconsistent knowledge items which are typical for knowledge economics and consequently for High-tech projects. The pooling of the records and / or observations represents a trade-off between minimal modification of the original data and elimination of inconsistencies among available sets of data. Scientific aim: The paper presents a detailed description of fuzzy model of investment decision making into High-tech firm’s projects. A set of conditional statements was used to formalize the effects of selected variables on investment feasibility of High-tech projects. The main aim is to quantify feasibilities of High-tech projects risk investors make good /not bad decisions. Findings: A set of 50 observations of High-tech companies was transformed into a set of 50 conditional statements using 14 variables. The result is the fuzzy model, which can be used to answer investors’ queries. Two queries are answered and presented in details as an example and as a nucleus of a fuzzy dialogue investor – computer. Conclusions: The main problem is the sparseness of the fuzzy model. Many fuzzy similarities are relatively low and the decision process is therefore often problematic. A much more complex set of variables must be applied to specify the fuzzy model to increase reliability of predictions and decisions.
COMPATIBLE EXTENSIONS OF FUZZY RELATIONS
Institute of Scientific and Technical Information of China (English)
Irina GEORGESCU
2003-01-01
In 1930 Szpilrajn proved that any strict partial order can be embedded in a strict linear order.This theorem was later refined by Dushnik and Miller (1941), Hansson (1968), Suzumura (1976),Donaldson and Weymark (1998), Bossert (1999). Particularly Suzumura introduced the important concept of compatible extension of a (crisp) relation. These extension theorems have an important role in welfare economics. In particular Szpilrajn theorem is the main tool for proving a known theorem of Richter that establishes the equivalence between rational and congruous consumers. In 1999 Duggan proved a general extension theorem that contains all these results. In this paper we introduce the notion of compatible extension of a fuzzy relation and we prove an extension theorem for fuzzy relations. Our result generalizes to fuzzy set theory the main part of Duggan's theorem. As applications we obtain fuzzy versions of the theorems of Szpilrajn, Hansson and Suzumura. We also prove that an asymmetric and transitive fuzzy relation has a compatible extension that is total, asymmetric and transitive.Our results can be useful in the theory of fuzzy consumers. We can prove that any rational fuzzyconsumer is congruous, extending to a fuzzy context a part of Richter's theorem. To prove that acongruous fuzzy consumer is rational remains an open problem. A proof of this result can somehowuse a fuzzy version of Szpilrajn theorem.
Fuzzy-Contextual Contrast Enhancement.
Parihar, Anil; Verma, Om; Khanna, Chintan
2017-02-08
This paper presents contrast enhancement algorithms based on fuzzy contextual information of the images. We introduce fuzzy similarity index and fuzzy contrast factor to capture the neighborhood characteristics of a pixel. A new histogram, using fuzzy contrast factor of each pixel is developed, and termed as the fuzzy dissimilarity histogram (FDH). A cumulative distribution function (CDF) is formed with normalized values of FDH and used as a transfer function to obtain the contrast enhanced image. The algorithm gives good contrast enhancement and preserves the natural characteristic of the image. In order to develop a contextual intensity transfer function, we introduce a fuzzy membership function based on fuzzy similarity index and coefficient of variation of the image. The contextual intensity transfer function is designed using the fuzzy membership function to achieve final contrast enhanced image. The overall algorithm is referred as the fuzzy contextual contrast-enhancement (FCCE) algorithm. The proposed algorithms are compared with conventional and state-of-art contrast enhancement algorithms. The quantitative and visual assessment of the results is performed. The results of quantitative measures are statistically analyzed using t-test. The exhaustive experimentation and analysis show the proposed algorithm efficiently enhances contrast and yields in natural visual quality images.
A New View on Fuzzy Hypermodules
Institute of Scientific and Technical Information of China (English)
Jian Ming ZHAN; Bijan DAVVAZ; K. P. SHUM
2007-01-01
We describe the relationship between the fuzzy sets and the algebraic hyperstructures.In fact,this paper is a continuation of the ideas presented by Davvaz in (Fuzzy Sets Syst.,117: 477-484,2001) and Bhakat and Das in (Fuzzy Sets Syst.,80: 359-368,1996).The concept of the quasi-coincidence of a fuzzy interval value with an interval-valued fuzzy set is introduced and this is a naturalgeneralization of the quasi-coincidence of a fuzzy point in fuzzy sets.By using this new idea,the conceptof interval-valued (α,β)-fuzzy sub-hypermodules of a hypermodule is defined.This newly definedinterval-valued (α,β)-fuzzy sub-hypermodule is a generalization of the usual fuzzy sub-hypermodule.We shall study such fuzzy sub-hypermodules and consider the implication-based interval-valued fuzzysub-hypermodules of a hypermodule.
Fuzzy dot ideals and fuzzy dot H-ideals of BCH-algebras
Institute of Scientific and Technical Information of China (English)
PENG Jia-yin
2008-01-01
The notions of fuzzy dot ideals and fuzzy dot H-ideals in BCH-algebras are intro duced,several appropriate examples are provided,and their some properties are investigated.The relations among fuzzy ideal,fuzzy H-ideal,fuzzy dot ideal and fuzzy dot H-ideals in BCH algebras are discussed,several equivalent depictions of fuzzy dot ideal are obtained. How to deal with the homomorphic image and inverse image of fuzzy dot ideals (fuzzy dot H-ideals) are studied. The relations between a fuzzy dot ideal (fuzzy dot H-ideal) in BCH-algebras and a fuzzy dot ideal (fuzzy dot H-ideal) in the product algebra of BCH-algebras are given.
Fuzzy Perfect Mappings and Q-Compactness in Smooth Fuzzy Topological Spaces
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C. Kalaivani
2014-03-01
Full Text Available We point out that the product of two fuzzy closed sets of smooth fuzzy topological spaces need not be fuzzy closed with respect to the the existing notion of product smooth fuzzy topology. To get this property, we introduce a new suitable product smooth fuzzy topology. We investigate whether F1×F2 and (F,H are weakly smooth fuzzy continuity whenever F1, F2, F and H are weakly smooth fuzzy continuous. Using this new product smooth fuzzy topology, we define smooth fuzzy perfect mapping and prove that composition of two smooth fuzzy perfect mappings is smooth fuzzy perfect under some additional conditions. We also introduce two new notions of compactness called Q-compactness and Q-α-compactness; and discuss the compactness of the image of a Q-compact set (Q-α-compact set under a weakly smooth fuzzy continuous function ((α,β-weakly smooth fuzzy continuous function.
Fuzzy controllers based on some fuzzy implication operators and their response functions
Institute of Scientific and Technical Information of China (English)
LI Hongxing; YOU Fei; PENG Jiayin
2004-01-01
The fuzzy controllers constructed by 23 fuzzy implication operators based on CRI algorithm and their response functions are discussed.The conclusions show that the fuzzy controllers constructed by 9 fuzzy implication operators are universal approximators to continuous functions and can be used in practical fuzzy control systems.And these 9 fuzzy implication operators except for Einstein operator intersection are all the adjoint pairs of some fuzzy implication operators.Besides, there are 3 other fuzzy controllers formed by fuzzy implication operators being regarded approximately as fitted functions.
Fuzzy controlofanylonpolymerizationsemi-batchreactor
Wakabayashi, C; Embiruçu, Marcelo; Fontes, Cristiano; Kalid, Ricardo
2009-01-01
Acesso restrito: Texto completo. p. 537-553 Batch and semi-batch polymerization reactors with specified trajectories for certain process variables present challenging control problems. This work reports, results and procedures related to the application of PI (proportional and integral) fuzzy control in a semi-batch reactor for the production of nylon 6. Closed loop simulation results were based on a phenomenological model adjusted for a commercial reactor and they attest to the potential ...
Institute of Scientific and Technical Information of China (English)
曹立明
1990-01-01
By the similarity between the syllogism in logic and a path proposition in graph theory,a new concept,fuzzy reasoning graph G has been given in this paper. Transitive closure has been studied and used to do reasoning related to self-loop in G,and an algorithm has been designed to cope with reasoning in other cycles in G. Both approaches are applicable and efficient.
Pham, T. D.
2016-12-01
Recurrence plots display binary texture of time series from dynamical systems with single dots and line structures. Using fuzzy recurrence plots, recurrences of the phase-space states can be visualized as grayscale texture, which is more informative for pattern analysis. The proposed method replaces the crucial similarity threshold required by symmetrical recurrence plots with the number of cluster centers, where the estimate of the latter parameter is less critical than the estimate of the former.
Emergent fuzzy geometry and fuzzy physics in four dimensions
Ydri, Badis; Rouag, Ahlam; Ramda, Khaled
2017-03-01
A detailed Monte Carlo calculation of the phase diagram of bosonic mass-deformed IKKT Yang-Mills matrix models in three and six dimensions with quartic mass deformations is given. Background emergent fuzzy geometries in two and four dimensions are observed with a fluctuation given by a noncommutative U (1) gauge theory very weakly coupled to normal scalar fields. The geometry, which is determined dynamically, is given by the fuzzy spheres SN2 and SN2 × SN2 respectively. The three and six matrix models are effectively in the same universality class. For example, in two dimensions the geometry is completely stable, whereas in four dimensions the geometry is stable only in the limit M ⟶ ∞, where M is the mass of the normal fluctuations. The behaviors of the eigenvalue distribution in the two theories are also different. We also sketch how we can obtain a stable fuzzy four-sphere SN2 × SN2 in the large N limit for all values of M as well as models of topology change in which the transition between spheres of different dimensions is observed. The stable fuzzy spheres in two and four dimensions act precisely as regulators which is the original goal of fuzzy geometry and fuzzy physics. Fuzzy physics and fuzzy field theory on these spaces are briefly discussed.
Performance comparison of fuzzy and non-fuzzy classification methods
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B. Simhachalam
2016-07-01
Full Text Available In data clustering, partition based clustering algorithms are widely used clustering algorithms. Among various partition algorithms, fuzzy algorithms, Fuzzy c-Means (FCM, Gustafson–Kessel (GK and non-fuzzy algorithm, k-means (KM are most popular methods. k-means and Fuzzy c-Means use standard Euclidian distance measure and Gustafson–Kessel uses fuzzy covariance matrix in their distance metrics. In this work, a comparative study of these algorithms with different famous real world data sets, liver disorder and wine from the UCI repository is presented. The performance of the three algorithms is analyzed based on the clustering output criteria. The results were compared with the results obtained from the repository. The results showed that Gustafson–Kessel produces close results to Fuzzy c-Means. Further, the experimental results demonstrate that k-means outperforms the Fuzzy c-Means and Gustafson–Kessel algorithms. Thus the efficiency of k-means is better than that of Fuzzy c-Means and Gustafson–Kessel algorithms.
fuzzy control technique fuzzy control technique applied to modified ...
African Journals Online (AJOL)
eobe
ABSTRACT. In this paper, fuzzy control technique is applied to the modified mathematical model for malaria control presented ... be devised for rule-based systems that deals with continuous ... necessary to use fuzzy logic as it is not easy to follow a particular .... point movement and control is realized and designed. (e.g. α1 ...
Almost Fuzzy Compactness in L-fuzzy Top ological Spaces
Institute of Scientific and Technical Information of China (English)
Li Hong-yan; Cui Wei
2015-01-01
In this paper, the notion of almost fuzzy compactness is defined in L-fuzzy topological spaces by means of inequality, where L is a completely distributive DeMorgan algebra. Its properties are discussed and many characterizations of it are presented.
How to combine probabilistic and fuzzy uncertainties in fuzzy control
Nguyen, Hung T.; Kreinovich, Vladik YA.; Lea, Robert
1991-01-01
Fuzzy control is a methodology that translates natural-language rules, formulated by expert controllers, into the actual control strategy that can be implemented in an automated controller. In many cases, in addition to the experts' rules, additional statistical information about the system is known. It is explained how to use this additional information in fuzzy control methodology.
Fuzzy Reasoning Methods by Choosing Different Fuzzy Counters and Analysis of Effect
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Different fuzzy reasoning methods were gave by choosing different fuzzy counters. This article generally introduced the basic structure of fuzzy controller,and compared and analysised the reasoning effect of fuzzy reasoning methods and the effect of computer simulating control basicly on different fuzzy counters.
L-Fuzzy Semi-Preopen Operator in L-Fuzzy Topological Spaces
Ghareeb, A
2010-01-01
In this paper, we give the concept of L-fuzzy Semi-Preopen operator in L-fuzzy topological spaces, and use them to score L-fuzzy SP-cmpactnness in L-fuzzy topological spaces. We also study the relationship between L-fuzzy SP-compactness and SP-compactness in L-topological spaces.
Fuzzy MCDM Based on Fuzzy Relational Degree Analysis
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
This paper presents a new fuzzy multiple criteria (both qualitative and quantitative) decision-making (MCDM) method based on fuzzy relational degree analysis. The concepts of fuzzy set theory are used to construct a weighted suitability decision matrix to evaluate the weighted suitability of different alternatives versus various criteria. The positive ideal solution and negative ideal solution are then obtained by using a method of ranking fuzzy numbers, and the fuzzy relational degrees of different alternatives versus positive ideal solution and negative ideal solution are calculated by using the proposed arithmetic. Finally, the relative relational degrees of various alternatives versus positive ideal solution are ranked to determine the best alternative. A numerical example is provided to illustrate the proposed method at the end of this paper.
Directory of Open Access Journals (Sweden)
Özlem Türkşen
2013-01-01
Full Text Available The solution set of a multi-response experiment is characterized by Pareto solution set. In this paper, the multi-response experiment is dealed in a fuzzy framework. The responses and model parameters are considered as triangular fuzzy numbers which indicate the uncertainty of the data set. Fuzzy least square approach and fuzzy modified NSGA-II (FNSGA-II are used for modeling and optimization, respectively. The obtained fuzzy Pareto solution set is grouped by using fuzzy relational clustering approach. Therefore, it could be easier to choose the alternative solutions to make better decision. A fuzzy response valued real data set is used as an application.
On Fuzzy Ideals of BL-Algebras
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Biao Long Meng
2014-01-01
Full Text Available In this paper we investigate further properties of fuzzy ideals of a BL-algebra. The notions of fuzzy prime ideals, fuzzy irreducible ideals, and fuzzy Gödel ideals of a BL-algebra are introduced and their several properties are investigated. We give a procedure to generate a fuzzy ideal by a fuzzy set. We prove that every fuzzy irreducible ideal is a fuzzy prime ideal but a fuzzy prime ideal may not be a fuzzy irreducible ideal and prove that a fuzzy prime ideal ω is a fuzzy irreducible ideal if and only if ω0=1 and |Im(ω|=2. We give the Krull-Stone representation theorem of fuzzy ideals in BL-algebras. Furthermore, we prove that the lattice of all fuzzy ideals of a BL-algebra is a complete distributive lattice. Finally, it is proved that every fuzzy Boolean ideal is a fuzzy Gödel ideal, but the converse implication is not true.
Directory of Open Access Journals (Sweden)
Grzegorz Dymek
2015-01-01
set to be a fuzzy ideal are given. The relationships between ideals and fuzzy ideals of a BN-algebra are established. The homomorphic properties of fuzzy ideals of a BN-algebra are provided. Finally, characterizations of Noetherian BN-algebras and Artinian BN-algebras via fuzzy ideals are obtained.
On Fuzzy Ideals of BL-Algebras
Xin, Xiao Long
2014-01-01
In this paper we investigate further properties of fuzzy ideals of a BL-algebra. The notions of fuzzy prime ideals, fuzzy irreducible ideals, and fuzzy Gödel ideals of a BL-algebra are introduced and their several properties are investigated. We give a procedure to generate a fuzzy ideal by a fuzzy set. We prove that every fuzzy irreducible ideal is a fuzzy prime ideal but a fuzzy prime ideal may not be a fuzzy irreducible ideal and prove that a fuzzy prime ideal ω is a fuzzy irreducible ideal if and only if ω(0) = 1 and |Im(ω)| = 2. We give the Krull-Stone representation theorem of fuzzy ideals in BL-algebras. Furthermore, we prove that the lattice of all fuzzy ideals of a BL-algebra is a complete distributive lattice. Finally, it is proved that every fuzzy Boolean ideal is a fuzzy Gödel ideal, but the converse implication is not true. PMID:24892085
FUZZY ALGEBRA IN TRIANGULAR NORM SYSTEM
Institute of Scientific and Technical Information of China (English)
宋晓秋; 潘志
1994-01-01
Triangular norm is a powerful tool in the theory research and application development of fuzzy sets. In this paper, using the triangular norm, we introduce some concepts such as fuzzy algebra, fuzzy o algebra and fuzzy monotone class, and discuss the relations among them, obtaining the following main conclusions.
Set Theory and Arithmetic in Fuzzy Logic
Běhounek, L. (Libor); Haniková, Z. (Zuzana)
2015-01-01
This chapter offers a review of Petr Hájek’s contributions to first-order axiomatic theories in fuzzy logic (in particular, ZF-style fuzzy set theories, arithmetic with a fuzzy truth predicate, and fuzzy set theory with unrestricted comprehension schema). Generalizations of Hájek’s results in these areas to MTL as the background logic are presented and discussed.
AN ALGORITHM OF TEST FOR FUZZY CODES
Institute of Scientific and Technical Information of China (English)
MoZhiwen; PenJiayin
2001-01-01
Abstract. How to verify that a given fuzzy set A∈F(X ) is a fuzzy code? In this paper, an al-gorithm of test has been introduced and studied with the example of test. The measure notionfor a fuzzy code and a precise formulation of fuzzy codes and words have been discussed.
Fuzzy clustering with Minkowski distance
P.J.F. Groenen (Patrick); U. Kaymak (Uzay); J.M. van Rosmalen (Joost)
2006-01-01
textabstractDistances in the well known fuzzy c-means algorithm of Bezdek (1973) are measured by the squared Euclidean distance. Other distances have been used as well in fuzzy clustering. For example, Jajuga (1991) proposed to use the L_1-distance and Bobrowski and Bezdek (1991) also used the L_inf
Duality in Dynamic Fuzzy Systems
Yoshida, Yuji
1995-01-01
This paper shows the resolvent equation, the maximum principle and the co-balayage theorem for a dynamic fuzzy system. We define a dual system for the dynamic fuzzy system, and gives a duality for Snell's optimal stopping problem by the dual system.
Efficient adaptive fuzzy control scheme
Papp, Z.; Driessen, B.J.F.
1995-01-01
The paper presents an adaptive nonlinear (state-) feedback control structure, where the nonlinearities are implemented as smooth fuzzy mappings defined as rule sets. The fine tuning and adaption of the controller is realized by an indirect adaptive scheme, which modifies the parameters of the fuzzy
Representation of Fuzzy Symmetric Relations
1986-03-19
Std Z39-18 REPRESENTATION OF FUZZY SYMMETRIC RELATIONS L. Valverde Dept. de Matematiques i Estadistica Universitat Politecnica de Catalunya Avda...REPRESENTATION OF FUZZY SYMMETRIC RELATIONS L. "Valverde* Dept. de Matematiques i Estadistica Universitat Politecnica de Catalunya Avda. Diagonal, 649
Teaching Machines to Think Fuzzy
Technology Teacher, 2004
2004-01-01
Fuzzy logic programs for computers make them more human. Computers can then think through messy situations and make smart decisions. It makes computers able to control things the way people do. Fuzzy logic has been used to control subway trains, elevators, washing machines, microwave ovens, and cars. Pretty much all the human has to do is push one…
FINDCLUS : Fuzzy INdividual Differences CLUStering
Giordani, Paolo; Kiers, Henk A. L.
ADditive CLUStering (ADCLUS) is a tool for overlapping clustering of two-way proximity matrices (objects x objects). In Simple Additive Fuzzy Clustering (SAFC), a variant of ADCLUS is introduced providing a fuzzy partition of the objects, that is the objects belong to the clusters with the so-called
Institute of Scientific and Technical Information of China (English)
沈理
1997-01-01
A fuzzy logic control VLSI chip,F100,for industry process real-time control has been designed and fabricated with 0.8μm CMOS technology.The chip has the features of simplicity,felexibility and generality.This paper presents the Fuzzy control inrerence method of the chip,its VLSI implementation,and testing esign consideration.
Fuzzy linguistic model for interpolation
Energy Technology Data Exchange (ETDEWEB)
Abbasbandy, S. [Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran 14778 (Iran, Islamic Republic of); Department of Mathematics, Faculty of Science, Imam Khomeini International University, Qazvin 34194-288 (Iran, Islamic Republic of); Adabitabar Firozja, M. [Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran 14778 (Iran, Islamic Republic of)
2007-10-15
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.
ON FUZZY h-IDEALS OF HEMIRINGS
Institute of Scientific and Technical Information of China (English)
Xueling MA; Jianming ZHAN
2007-01-01
The concept of quasi-coincidence of a fuzzy interval value in an interval valued fuzzy set is considered. In fact, this concept is a generalized concept of the quasi-coincidence of a fuzzy point in a fuzzy set. By using this new concept, the authors define the notion of interval valued (∈, ∈ Vq)-fuzzy h-ideals of hemirings and study their related properties. In addition, the authors also extend the concept of a fuzzy subgroup with thresholds to the concept of an interval valued fuzzy h-ideal with thresholds in hemirings.
A new fuzzy edge detection algorithm
Institute of Scientific and Technical Information of China (English)
SunWei; XiaLiangzheng
2003-01-01
Based upon the maximum entropy theorem of information theory, a novel fuzzy approach for edge detection is presented. Firsdy, a definition of fuzzy partition entropy is proposed after introducing the concepts of fuzzy probability and fuzzy partition. The relation of the probability partition and the fuzzy c-partition of the image gradient are used in the algorithm. Secondly, based on the conditional probabilities and the fuzzy partition, the optimal thresholding is searched adaptively through the maximum fuzzy entropy principle, and then the edge image is obtained. Lastly, an edge-enhancing procedure is executed on the edge image. The experimental results show that the proposed approach performs well.
Image matching navigation based on fuzzy information
Institute of Scientific and Technical Information of China (English)
田玉龙; 吴伟仁; 田金文; 柳健
2003-01-01
In conventional image matching methods, the image matching process is mostly based on image statistic information. One aspect neglected by all these methods is that there is much fuzzy information contained in these images. A new fuzzy matching algorithm based on fuzzy similarity for navigation is presented in this paper. Because the fuzzy theory is of the ability of making good description of the fuzzy information contained in images, the image matching method based on fuzzy similarity would look forward to producing good performance results. Experimental results using matching algorithm based on fuzzy information also demonstrate its reliability and practicability.
On Intuitionistic Fuzzy Magnified Translation in Semigroups
Sardar, Sujit Kumar; Majumder, Samit Kumar
2011-01-01
The notion of intuitionistic fuzzy sets was introduced by Atanassov as a generalization of the notion of fuzzy sets. S.K Sardar and S.K. Majumder unified the idea of fuzzy translation and fuzzy multiplication of Vasantha Kandasamy to introduce the concept of fuzzy magnified translation in groups and semigroups. The purpose of this paper is to intuitionistically fuzzify(by using Atanassov's idea) the concept of fuzzy magnified translation in semigroups. Here among other results we obtain some characterization theorems of regular, intra-regular, left(right) regular semigroups in terms of intuitionistic fuzzy magnified translation.
On the L-fuzzy topological spaces
Energy Technology Data Exchange (ETDEWEB)
Saadati, Reza [Islamic Azad University-Aiatollah Amoly Branch, Amol 678 (Iran, Islamic Republic of); Department of Mathematics and Computer Science, Amirkabir University of Technology, 424 Hafez Avenue, Tehran 15914 (Iran, Islamic Republic of)], E-mail: rsaadati@eml.cc
2008-09-15
As a natural generalization of fuzzy metric spaces due to George and Veeramani [George A, Veeramani P. On some result in fuzzy metric space. Fuzzy Sets Syst 1994;64:395-9], the present author defined the notion of L-fuzzy metric spaces. In this paper we prove some known results of metric spaces including Uniform continuity theorem and Ascoli-Arzela theorem for L-fuzzy metric spaces. We also prove that every L-fuzzy metric space has a countably locally finite basis and use this result to conclude that every L-fuzzy metric space is metrizable.
Single Machine Scheduling Problem with Fuzzy Due Dates and Fuzzy Precedence%模糊交货期和模糊优先下的单机调度问题
Institute of Scientific and Technical Information of China (English)
谢源; 谢剑英; 黄芹华
2005-01-01
A single machine scheduling problem involving fuzzy due dates and fuzzy precedence constraints is investigated. The fuzzy precedence reflects the satisfaction level with respect to precedence between two jobs. A membership function is associated with each job Ji, which describes the degree of satisfaction with respect to completion time of Ji. For the bi-criteria scheduling problem, an O ( n3 ) algorithm is proposed for finding nondominated solutions.
Concept Approximation between Fuzzy Ontologies
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Fuzzy ontologies are efficient tools to handle fuzzy and uncertain knowledge on the semantic web; but there are heterogeneity problems when gaining interoperability among different fuzzy ontologies. This paper uses concept approximation between fuzzy ontologies based on instances to solve the heterogeneity problems. It firstly proposes an instance selection technology based on instance clustering and weighting to unify the fuzzy interpretation of different ontologies and reduce the number of instances to increase the efficiency. Then the paper resolves the problem of computing the approximations of concepts into the problem of computing the least upper approximations of atom concepts. It optimizes the search strategies by extending atom concept sets and defining the least upper bounds of concepts to reduce the searching space of the problem. An efficient algorithm for searching the least upper bounds of concept is given.
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.
Modelling on fuzzy control systems
Institute of Scientific and Technical Information of China (English)
LI; Hongxing(李洪兴); WANG; Jiayin(王加银); MIAO; Zhihong(苗志宏)
2002-01-01
A kind of modelling method for fuzzy control systems is first proposed here, which is calledmodelling method based on fuzzy inference (MMFI). It should be regarded as the third modelling method thatis different from two well-known modelling methods, that is, the first modelling method, mechanism modellingmethod (MMM), and the second modelling method, system identification modelling method (SlMM). Thismethod can, based on the interpolation mechanism on fuzzy logic system, transfer a group of fuzzy inferencerules describing a practice system into a kind of nonlinear differential equation with variable coefficients, calledHX equations, so that the mathematical model of the system can be obtained. This means that we solve thedifficult problem of how to get a model represented as differential equations on a complicated or fuzzy controlsystem.
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...
Data fusion based on fuzzy measures
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Choquet integral based on fuzzy measure is a very popular data fusion approach. A major problem in applying the Choquet integral is how to determine a large number of fuzzy measures as the number of attributes increases. The λ-fuzzy measure proposed by Sugeno is a powerful method to resolve this problem. However, the modeling ability of the λ-fuzzy measure is too limited to satisfy actual requirements. In this paper, an extended λ-fuzzy measure is proposed using Shapley value index, and the limitation of the λ-fuzzy measure is significantly overcome under little additional computational loads. The extended fuzzy measure has stronger modeling power than the λ-fuzzy measure, straightforwardly representing interaction among attributes. We apply the extended fuzzy measure to an artificial data set and a real dataset in an iron-steel plant. The results verify the usefulness of the extended fuzzy measure compared with other main existing methods.
Ozyer, Tansel; Alhajj, Reda; Barker, Ken
2005-03-01
This paper proposes an intelligent intrusion detection system (IDS) which is an integrated approach that employs fuzziness and two of the well-known data mining techniques: namely classification and association rule mining. By using these two techniques, we adopted the idea of using an iterative rule learning that extracts out rules from the data set. Our final intention is to predict different behaviors in networked computers. To achieve this, we propose to use a fuzzy rule based genetic classifier. Our approach has two main stages. First, fuzzy association rule mining is applied and a large number of candidate rules are generated for each class. Then the rules pass through pre-screening mechanism in order to reduce the fuzzy rule search space. Candidate rules obtained after pre-screening are used in genetic fuzzy classifier to generate rules for the specified classes. Classes are defined as Normal, PRB-probe, DOS-denial of service, U2R-user to root and R2L- remote to local. Second, an iterative rule learning mechanism is employed for each class to find its fuzzy rules required to classify data each time a fuzzy rule is extracted and included in the system. A Boosting mechanism evaluates the weight of each data item in order to help the rule extraction mechanism focus more on data having relatively higher weight. Finally, extracted fuzzy rules having the corresponding weight values are aggregated on class basis to find the vote of each class label for each data item.
On Fuzzy Improper Integral and Its Application for Fuzzy Partial Differential Equations
ElHassan ElJaoui; Said Melliani
2016-01-01
We establish some important results about improper fuzzy Riemann integrals; we prove some properties of fuzzy Laplace transforms, which we apply for solving some fuzzy linear partial differential equations of first order, under generalized Hukuhara differentiability.
On Fuzzy Improper Integral and Its Application for Fuzzy Partial Differential Equations
Directory of Open Access Journals (Sweden)
ElHassan ElJaoui
2016-01-01
Full Text Available We establish some important results about improper fuzzy Riemann integrals; we prove some properties of fuzzy Laplace transforms, which we apply for solving some fuzzy linear partial differential equations of first order, under generalized Hukuhara differentiability.
Web Fuzzy Clustering and a Case Study
Institute of Scientific and Technical Information of China (English)
LIU Mao-fu; HE Jing; HE Yan-xiang; HU Hui-jun
2004-01-01
We combine the web usage mining and fuzzy clustering and give the concept of web fuzzy clustering, and then put forward the web fuzzy clustering processing model which is discussed in detail. Web fuzzy clustering can be used in the web users clustering and web pages clustering. In the end, a case study is given and the result has proved the feasibility of using web fuzzy clustering in web pages clustering.
Delay Computation Using Fuzzy Logic Approach
Directory of Open Access Journals (Sweden)
Ramasesh G. R.
2012-10-01
Full Text Available The paper presents practical application of fuzzy sets and system theory in predicting delay, with reasonable accuracy, a wide range of factors pertaining to construction projects. In this paper we shall use fuzzy logic to predict delays on account of Delayed supplies and Labor shortage. It is observed that the project scheduling software use either deterministic method or probabilistic method for computation of schedule durations, delays, lags and other parameters. In other words, these methods use only quantitative inputs leaving-out the qualitative aspects associated with individual activity of work. The qualitative aspect viz., the expertise of the mason or the lack of experience can have a significant impact on the assessed duration. Such qualitative aspects do not find adequate representation in the Project Scheduling software. A realistic project is considered for which a PERT chart has been prepared using showing all the major activities in reasonable detail. This project has been periodically updated until its completion. It is observed that some of the activities are delayed due to extraneous factors resulting in the overall delay of the project. The software has the capability to calculate the overall delay through CPM (Critical Path Method when each of the activity-delays is reported. We shall now demonstrate that by using fuzzy logic, these delays could have been predicted well in advance.
Improvement of Fuzzy Image Contrast Enhancement Using Simulated Ergodic Fuzzy Markov Chains
Directory of Open Access Journals (Sweden)
Behrouz Fathi-Vajargah
2014-01-01
Full Text Available This paper presents a novel fuzzy enhancement technique using simulated ergodic fuzzy Markov chains for low contrast brain magnetic resonance imaging (MRI. The fuzzy image contrast enhancement is proposed by weighted fuzzy expected value. The membership values are then modified to enhance the image using ergodic fuzzy Markov chains. The qualitative performance of the proposed method is compared to another method in which ergodic fuzzy Markov chains are not considered. The proposed method produces better quality image.
Fuzzy 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.
Jung, Hye-Young; Leem, Sangseob; Lee, Sungyoung; Park, Taesung
2016-12-01
Gene-gene interaction (GGI) is one of the most popular approaches for finding the missing heritability of common complex traits in genetic association studies. The multifactor dimensionality reduction (MDR) method has been widely studied for detecting GGIs. In order to identify the best interaction model associated with disease susceptibility, MDR compares all possible genotype combinations in terms of their predictability of disease status from a simple binary high(H) and low(L) risk classification. However, this simple binary classification does not reflect the uncertainty of H/L classification. We regard classifying H/L as equivalent to defining the degree of membership of two risk groups H/L. By adopting the fuzzy set theory, we propose Fuzzy MDR which takes into account the uncertainty of H/L classification. Fuzzy MDR allows the possibility of partial membership of H/L through a membership function which transforms the degree of uncertainty into a [0,1] scale. The best genotype combinations can be selected which maximizes a new fuzzy set based accuracy measure. Two simulation studies are conducted to compare the power of the proposed Fuzzy MDR with that of MDR. Our results show that Fuzzy MDR has higher power than MDR. We illustrate the proposed Fuzzy MDR by analysing bipolar disorder (BD) trait of the WTCCC dataset to detect GGI associated with BD. We propose a novel Fuzzy MDR method to detect gene-gene interaction by taking into account the uncertainly of H/L classification and show that it has higher power than MDR. Fuzzy MDR can be easily extended to handle continuous phenotypes as well. The program written in R for the proposed Fuzzy MDR is available at https://statgen.snu.ac.kr/software/FuzzyMDR. Copyright Â© 2016 Elsevier Ltd. All rights reserved.
Fuzzy-logic-assisted surgical planning in adolescent idiopathic scoliosis.
Nault, Marie-Lyne; Labelle, Hubert; Aubin, Carl-Eric; Sangole, Archana; Balazinski, Marek
2009-06-01
Selection of appropriate curve fusion levels for surgery in adolescent idiopathic scoliosis (AIS) is a complex and difficult task and, despite numerous publications, still remains a highly controversial topic. To evaluate a fuzzy-logic-based surgical planning tool by comparing the results suggested by the software with the average outcome recommended by a panel of 5 expert spinal deformity surgeons. It is hypothesized that, given the same information, the fuzzy-logic tool will perform as favorably as the surgeons. Proof-of-concept study evaluating the use of a fuzzy-logic-assisted surgical planning tool in AIS to select the appropriate spinal curve to be instrumented. A cohort of 30 AIS surgical cases with a main thoracic curve was used. Each case included standard measurements recorded from preoperative standing postero-anterior and lateral, supine side bending, and 1-year postoperative standing radiographs. Five experienced spinal deformity surgeons evaluated each case independently and gave their preferred levels of instrumentation and fusion. The cases were then presented to the fuzzy-logic tool to determine whether the high thoracic and/or lumbar curves were to be instrumented. For each case, a percentage value was obtained indicating inclusion/exclusion of the respective curves in the surgical instrumentation procedure. Kappa statistics was used to compare the model output and the average decision of the surgeons. Kappa values of 0.71 and 0.64 were obtained, respectively, for the proximal thoracic and lumbar curves models, thus suggesting a good agreement of the fusion recommendations made by the fuzzy-logic tool and the surgeons. Given the same information, the fuzzy-logic-assisted recommendation of the curve to be instrumented compared favorably with the collective decision of the surgeons. The findings thus suggest that a fuzzy-logic approach is helpful in assisting surgeons with the preoperative selection of curve instrumentation and fusion levels in AIS.
Directory of Open Access Journals (Sweden)
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.
Optimization of type-2 fuzzy controllers using the bee colony algorithm
Amador, Leticia
2017-01-01
This book focuses on the fields of fuzzy logic, bio-inspired algorithm; especially bee colony optimization algorithm and also considering the fuzzy control area. The main idea is that this areas together can to solve various control problems and to find better results. In this book we test the proposed method using two benchmark problems; the problem for filling a water tank and the problem for controlling the trajectory in an autonomous mobile robot. When Interval Type-2 Fuzzy Logic System is implemented to model the behavior of systems, the results show a better stabilization, because the analysis of uncertainty is better. For this reason we consider in this book the proposed method using fuzzy systems, fuzzy controllers, and bee colony optimization algorithm improve the behavior of the complex control problems.
Institute of Scientific and Technical Information of China (English)
HU Hong; LI Su; WANG YunJiu; QI XiangLin; SHI ZhongZhi
2008-01-01
Analytical study of large-scale nonlinear neural circuits is a difficult task. Here we analyze the function of neural systems by probing the fuzzy logical framework of the neural cells' dynamical equations. Al-though there is a close relation between the theories of fuzzy logical systems and neural systems and many papers investigate this subject, most investigations focus on finding new functions of neural systems by hybridizing fuzzy logical and neural system. In this paper, the fuzzy logical framework of neural cells is used to understand the nonlinear dynamic attributes of a common neural system by abstracting the fuzzy logical framework of a neural cell. Our analysis enables the educated design of network models for classes of computation. As an example, a recurrent network model of the primary visual cortex has been built and tested using this approach.
The matrix representation of fuzzy knowledge and its application to the expert systems design
Directory of Open Access Journals (Sweden)
V. Levchenko
1993-02-01
Full Text Available An approach to the diagnostic type expert systems design based on the special matrix representation of fuzzy predicates in the tribute model of the problem domain is presented. Intensive representation of predicates by means of sectional matrices is an analogue of the conjunctive normal form. Rules, positive examples and negative examples (in general, all fuzzy can be used to form knowledge base. Diagnostics problem is thought of as finding some attribute values provided that the information about other attribute values is available. Logical inference is based on an equivalent transformation of the matrix to that containing all prime disjuncts by using the operation of fuzzy resolution . Two strategies to carry out such transformation are described. On the basis of formalism presented the expert system shell EDIP is developed, the first version of that is non-fuzzy and the second one allows working with fuzzy data and conclusions.
Institute of Scientific and Technical Information of China (English)
2008-01-01
Analytical study of large-scale nonlinear neural circuits is a difficult task. Here we analyze the function of neural systems by probing the fuzzy logical framework of the neural cells’ dynamical equations. Al- though there is a close relation between the theories of fuzzy logical systems and neural systems and many papers investigate this subject, most investigations focus on finding new functions of neural systems by hybridizing fuzzy logical and neural system. In this paper, the fuzzy logical framework of neural cells is used to understand the nonlinear dynamic attributes of a common neural system by abstracting the fuzzy logical framework of a neural cell. Our analysis enables the educated design of network models for classes of computation. As an example, a recurrent network model of the primary visual cortex has been built and tested using this approach.
Fuzzy logic and information fusion to commemorate the 70th birthday of Professor Gaspar Mayor
Sastre, Joan
2016-01-01
This book offers a timely report on key theories and applications of soft-computing. Written in honour of Professor Gaspar Mayor on his 70th birthday, it primarily focuses on areas related to his research, including fuzzy binary operators, aggregation functions, multi-distances, and fuzzy consensus/decision models. It also discusses a number of interesting applications such as the implementation of fuzzy mathematical morphology based on Mayor-Torrens t-norms. Importantly, the different chapters, authored by leading experts, present novel results and offer new perspectives on different aspects of Mayor’s research. The book also includes an overview of evolutionary fuzzy systems, a topic that is not one of Mayor’s main areas of interest, and a final chapter written by the Spanish pioneer in fuzzy logic, Professor E. Trillas. Computer and decision scientists, knowledge engineers and mathematicians alike will find here an authoritative overview of key soft-computing concepts and techniques.
Hu, Hong; Li, Su; Wang, YunJiu; Qi, XiangLin; Shi, ZhongZhi
2008-10-01
Analytical study of large-scale nonlinear neural circuits is a difficult task. Here we analyze the function of neural systems by probing the fuzzy logical framework of the neural cells' dynamical equations. Although there is a close relation between the theories of fuzzy logical systems and neural systems and many papers investigate this subject, most investigations focus on finding new functions of neural systems by hybridizing fuzzy logical and neural system. In this paper, the fuzzy logical framework of neural cells is used to understand the nonlinear dynamic attributes of a common neural system by abstracting the fuzzy logical framework of a neural cell. Our analysis enables the educated design of network models for classes of computation. As an example, a recurrent network model of the primary visual cortex has been built and tested using this approach.
A review of Fuzzy Based QoS Web Service Discovery
Directory of Open Access Journals (Sweden)
R.Buvanesvari
2013-03-01
Full Text Available Recently, web service has become an important issue for developers. Selecting a specific service is a crucial task. Some approaches develop extensive description and publication mechanisms while others use syntactic, semantic, and structural reviews of Web service specifications. It is very crucial for finding the most suitable web service from a large collection of web services for successful execution of applications. In many cases, the value of a QoS property may not be precisely defined. Recently, fuzzy is considered as the dominant approaches in Web services which can deal with fuzzy constraints have been proposed. Therefore fuzzy logic can be applied to support for representing such imprecise QoS constraints. In this paper, we will present an overview which focus on developing fuzzy-based approach for Web service discovery. This paper also describes the web service challenges on fuzzy mechanism that summarized and analyzed in order to assess their benefits and limitations.
Energy Technology Data Exchange (ETDEWEB)
Oostra, R.J.; Bleeker-Wagemakers, E.M.; Zwart, R. [Ophthalmic Research Institute, Amsterdam (Netherlands)] [and others
1995-10-01
Three mtDNA point mutations at nucleotide position (np) 3460, at np 11778 and at np 14484, are thought to be of primary importance in the pathogenesis of Leber hereditary optic neuropathy (LHON), a maternally inherited disease characterized by subacute central vision loss. These mutations are present in genes coding for subunits of complex I (NADH dehydrogenase) of the respiratory chain, occur exclusively in LHON maternal pedigrees, and have never been reported to occur together. Johns and Neufeld postulated that an mtDNA mutation at np 9438, in the gene coding for one of the subunits (COX III) of complex IV (cytochrome c oxidase), was also of primary importance. Johns and Neufeld (1993) found this mutation, which changed a conserved glycine to a serine, in 5 unrelated LHON probands who did not carry one of the presently known primary mutations, but they did not find it in 400 controls. However, the role of this sequence variant has been questioned in the Journal when it has been found to occur in apparently healthy African and Cuban individuals. Subsequently, Johns et al. described this mutation in two Cuban individuals presenting with optic and peripheral neuropathy. 22 refs., 1 fig., 1 tab.
Risk Mapping of Cutaneous Leishmaniasis via a Fuzzy C Means-based Neuro-Fuzzy Inference System
Akhavan, P.; Karimi, M.; Pahlavani, P.
2014-10-01
Finding pathogenic factors and how they are spread in the environment has become a global demand, recently. Cutaneous Leishmaniasis (CL) created by Leishmania is a special parasitic disease which can be passed on to human through phlebotomus of vector-born. Studies show that economic situation, cultural issues, as well as environmental and ecological conditions can affect the prevalence of this disease. In this study, Data Mining is utilized in order to predict CL prevalence rate and obtain a risk map. This case is based on effective environmental parameters on CL and a Neuro-Fuzzy system was also used. Learning capacity of Neuro-Fuzzy systems in neural network on one hand and reasoning power of fuzzy systems on the other, make it very efficient to use. In this research, in order to predict CL prevalence rate, an adaptive Neuro-fuzzy inference system with fuzzy inference structure of fuzzy C Means clustering was applied to determine the initial membership functions. Regarding to high incidence of CL in Ilam province, counties of Ilam, Mehran, and Dehloran have been examined and evaluated. The CL prevalence rate was predicted in 2012 by providing effective environmental map and topography properties including temperature, moisture, annual, rainfall, vegetation and elevation. Results indicate that the model precision with fuzzy C Means clustering structure rises acceptable RMSE values of both training and checking data and support our analyses. Using the proposed data mining technology, the pattern of disease spatial distribution and vulnerable areas become identifiable and the map can be used by experts and decision makers of public health as a useful tool in management and optimal decision-making.
Risk Mapping of Cutaneous Leishmaniasis via a Fuzzy C Means-based Neuro-Fuzzy Inference System
Directory of Open Access Journals (Sweden)
P. Akhavan
2014-10-01
Full Text Available Finding pathogenic factors and how they are spread in the environment has become a global demand, recently. Cutaneous Leishmaniasis (CL created by Leishmania is a special parasitic disease which can be passed on to human through phlebotomus of vector-born. Studies show that economic situation, cultural issues, as well as environmental and ecological conditions can affect the prevalence of this disease. In this study, Data Mining is utilized in order to predict CL prevalence rate and obtain a risk map. This case is based on effective environmental parameters on CL and a Neuro-Fuzzy system was also used. Learning capacity of Neuro-Fuzzy systems in neural network on one hand and reasoning power of fuzzy systems on the other, make it very efficient to use. In this research, in order to predict CL prevalence rate, an adaptive Neuro-fuzzy inference system with fuzzy inference structure of fuzzy C Means clustering was applied to determine the initial membership functions. Regarding to high incidence of CL in Ilam province, counties of Ilam, Mehran, and Dehloran have been examined and evaluated. The CL prevalence rate was predicted in 2012 by providing effective environmental map and topography properties including temperature, moisture, annual, rainfall, vegetation and elevation. Results indicate that the model precision with fuzzy C Means clustering structure rises acceptable RMSE values of both training and checking data and support our analyses. Using the proposed data mining technology, the pattern of disease spatial distribution and vulnerable areas become identifiable and the map can be used by experts and decision makers of public health as a useful tool in management and optimal decision-making.
Fuzzy logic and neural networks in artificial intelligence and pattern recognition
Sanchez, Elie
1991-10-01
With the use of fuzzy logic techniques, neural computing can be integrated in symbolic reasoning to solve complex real world problems. In fact, artificial neural networks, expert systems, and fuzzy logic systems, in the context of approximate reasoning, share common features and techniques. A model of Fuzzy Connectionist Expert System is introduced, in which an artificial neural network is designed to construct the knowledge base of an expert system from, training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the synaptic connections in an AND-OR structure: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through min-max fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feedforward network is described and first illustrated in a biomedical application (medical diagnosis assistance from inflammatory-syndromes/proteins profiles). Then, it is shown how this methodology can be utilized for handwritten pattern recognition (characters play the role of diagnoses): in a fuzzy neuron describing a number for example, the linguistic weights represent fuzzy sets on cross-detecting lines and the numerical weights reflect the importance (or weakness) of connections between cross-detecting lines and characters.
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.
Strong sum distance in fuzzy graphs.
Tom, Mini; Sunitha, Muraleedharan Shetty
2015-01-01
In this paper the idea of strong sum distance which is a metric, in a fuzzy graph is introduced. Based on this metric the concepts of eccentricity, radius, diameter, center and self centered fuzzy graphs are studied. Some properties of eccentric nodes, peripheral nodes and central nodes are obtained. A characterisation of self centered complete fuzzy graph is obtained and conditions under which a fuzzy cycle is self centered are established. We have proved that based on this metric, an eccentric node of a fuzzy tree G is a fuzzy end node of G and a node is an eccentric node of a fuzzy tree if and only if it is a peripheral node of G and the center of a fuzzy tree consists of either one or two neighboring nodes. The concepts of boundary nodes and interior nodes in a fuzzy graph based on strong sum distance are introduced. Some properties of boundary nodes, interior nodes and complete nodes are studied.
A Different Web-Based Geocoding Service Using Fuzzy Techniques
Pahlavani, P.; Abbaspour, R. A.; Zare Zadiny, A.
2015-12-01
Geocoding - the process of finding position based on descriptive data such as address or postal code - is considered as one of the most commonly used spatial analyses. Many online map providers such as Google Maps, Bing Maps and Yahoo Maps present geocoding as one of their basic capabilities. Despite the diversity of geocoding services, users usually face some limitations when they use available online geocoding services. In existing geocoding services, proximity and nearness concept is not modelled appropriately as well as these services search address only by address matching based on descriptive data. In addition there are also some limitations in display searching results. Resolving these limitations can enhance efficiency of the existing geocoding services. This paper proposes the idea of integrating fuzzy technique with geocoding process to resolve these limitations. In order to implement the proposed method, a web-based system is designed. In proposed method, nearness to places is defined by fuzzy membership functions and multiple fuzzy distance maps are created. Then these fuzzy distance maps are integrated using fuzzy overlay technique for obtain the results. Proposed methods provides different capabilities for users such as ability to search multi-part addresses, searching places based on their location, non-point representation of results as well as displaying search results based on their priority.
A DIFFERENT WEB-BASED GEOCODING SERVICE USING FUZZY TECHNIQUES
Directory of Open Access Journals (Sweden)
P. Pahlavani
2015-12-01
Full Text Available Geocoding – the process of finding position based on descriptive data such as address or postal code - is considered as one of the most commonly used spatial analyses. Many online map providers such as Google Maps, Bing Maps and Yahoo Maps present geocoding as one of their basic capabilities. Despite the diversity of geocoding services, users usually face some limitations when they use available online geocoding services. In existing geocoding services, proximity and nearness concept is not modelled appropriately as well as these services search address only by address matching based on descriptive data. In addition there are also some limitations in display searching results. Resolving these limitations can enhance efficiency of the existing geocoding services. This paper proposes the idea of integrating fuzzy technique with geocoding process to resolve these limitations. In order to implement the proposed method, a web-based system is designed. In proposed method, nearness to places is defined by fuzzy membership functions and multiple fuzzy distance maps are created. Then these fuzzy distance maps are integrated using fuzzy overlay technique for obtain the results. Proposed methods provides different capabilities for users such as ability to search multi-part addresses, searching places based on their location, non-point representation of results as well as displaying search results based on their priority.
Applying fuzzy analytic network process in quality function deployment model
Directory of Open Access Journals (Sweden)
Mohammad Ali Afsharkazemi
2012-08-01
Full Text Available In this paper, we propose an empirical study of QFD implementation when fuzzy numbers are used to handle the uncertainty associated with different components of the proposed model. We implement fuzzy analytical network to find the relative importance of various criteria and using fuzzy numbers we calculate the relative importance of these factors. The proposed model of this paper uses fuzzy matrix and house of quality to study the products development in QFD and also the second phase i.e. part deployment. In most researches, the primary objective is only on CRs to implement the quality function deployment and some other criteria such as production costs, manufacturing costs etc were disregarded. The results of using fuzzy analysis network process based on the QFD model in Daroupat packaging company to develop PVDC show that the most important indexes are being waterproof, resistant pill packages, and production cost. In addition, the PVDC coating is the most important index in terms of company experts’ point of view.
Fuzzy Clustering Methods and their Application to Fuzzy Modeling
DEFF Research Database (Denmark)
Kroszynski, Uri; Zhou, Jianjun
1999-01-01
Fuzzy modeling techniques based upon the analysis of measured input/output data sets result in a set of rules that allow to predict system outputs from given inputs. Fuzzy clustering methods for system modeling and identification result in relatively small rule-bases, allowing fast, yet accurate...... prediction of outputs. This article presents an overview of some of the most popular clustering methods, namely Fuzzy Cluster-Means (FCM) and its generalizations to Fuzzy C-Lines and Elliptotypes. The algorithms for computing cluster centers and principal directions from a training data-set are described....... A method to obtain an optimized number of clusters is outlined. Based upon the cluster's characteristics, a behavioural model is formulated in terms of a rule-base and an inference engine. The article reviews several variants for the model formulation. Some limitations of the methods are listed...
DEFF Research Database (Denmark)
Hassan, Saima; Ahmadieh Khanesar, Mojtaba; Hajizadeh, Amin
2017-01-01
Learning of fuzzy parameters for system modeling using evolutionary algorithms is an interesting topic. In this paper, two optimal design and tuning of Interval type-2 fuzzy logic system are proposed using hybrid learning algorithms. The consequent parameters of the interval type-2 fuzzy logic....../D) in the second hybrid algorithm. Root mean square error and maximum absolute error as the two accuracy objective are utilized to find the Pareto-optimal solution with the MOPSO and MOEA/D respectively. The proposed hybrid multi-objective designs of the interval type-2 fuzzy logic system are utilized...
Fuzzy Nonnative Phonolexical Representations Lead to Fuzzy Form-to-Meaning Mappings.
Cook, Svetlana V; Pandža, Nick B; Lancaster, Alia K; Gor, Kira
2016-01-01
The present paper explores nonnative (L2) phonological encoding of lexical entries and dissociates the difficulties associated with L2 phonological and phonolexical encoding by focusing on similarly sounding L2 words that are not differentiated by difficult phonological contrasts. We test two main claims of the fuzzy lexicon hypothesis: (1) L2 fuzzy phonolexical representations are not fully specified and lack details at both phonological and phonolexical levels of representation (Experiment 1); and (2) fuzzy phonolexical representations can lead to establishing incorrect form-to-meaning mappings (Experiment 2). The Russian-English Translation Judgment Task (Experiment 1, TJT) explores how the degree of phonolexical similarity between a word and its lexical competitor affects lexical access of Russian words. Words with smaller phonolexical distance (e.g., parent-parrot) show longer reaction times and lower accuracy compared to words with a larger phonolexical distance (e.g., parent-parchment) in lower-proficiency nonnative speakers, and, to a lesser degree, higher-proficiency speakers. This points to a lack of detail in nonnative phonolexical representations necessary for efficient lexical access. The Russian Pseudo-Semantic Priming task (Experiment 2, PSP) addresses the vulnerability of form-to-meaning mappings as a consequence of fuzzy phonolexical representations in L2. We primed the target with a word semantically related to its phonological competitor, or a potentially confusable word. The findings of Experiment 2 extend the results of Experiment 1 that, unlike native speakers, nonnative speakers do not properly encode phonolexical information. As a result, they are prone to access an incorrect lexical representation of a competitor word, as indicated by a slowdown in the judgments to confusable words. The study provides evidence that fuzzy phonolexical representations result in unfaithful form-to-meaning mappings, which lead to retrieval of incorrect semantic
Fuzzy Nonnative Phonolexical Representations Lead to Fuzzy Form-to-Meaning Mappings
Directory of Open Access Journals (Sweden)
Svetlana V Cook
2016-09-01
Full Text Available The present paper explores nonnative (L2 phonological encoding of lexical entries and dissociates the difficulties associated with L2 phonological and phonolexical encoding by focusing on similarly sounding L2 words that are not differentiated by difficult phonological contrasts. We test two main claims of the fuzzy lexicon hypothesis: (1 L2 fuzzy phonolexical representations are not fully specified and lack details at both phonological and phonolexical levels of representation (Experiment 1; and (2 fuzzy phonolexical representations can lead to establishing incorrect form-to-meaning mappings (Experiment 2.The Russian-English Translation Priming task (Experiment 1, TJT explores how the degree of phonolexical similarity between a word and its lexical competitor affects lexical access of Russian words. Words with smaller phonolexical distance (e.g., parent - parrot show longer reaction times and lower accuracy compared to words with a larger phonolexical distance (e.g., parent – parchment in lower-proficiency nonnative speakers, and, to a lesser degree, higher-proficiency speakers. This points to a lack of detail in nonnative phonolexical representations necessary for efficient lexical access. The Russian Pseudo-Semantic Priming task (Experiment 2, PSP addresses the vulnerability of form-to-meaning mappings as a consequence of fuzzy phonolexical representations in L2. We primed the target with a word semantically related to its phonological competitor, or a potentially confusable word. The findings of Experiment 2 extend the results of Experiment 1 that, unlike native speakers, nonnative speakers do not properly encode phonolexical information. As a result, they are prone to access an incorrect lexical representation of a competitor word, as indicated by a slowdown in the judgments to confusable words.The study provides evidence that fuzzy phonolexical representations result in unfaithful form-to-meaning mappings, which lead to retrieval of
Fuzzy Nonnative Phonolexical Representations Lead to Fuzzy Form-to-Meaning Mappings
Cook, Svetlana V.; Pandža, Nick B.; Lancaster, Alia K.; Gor, Kira
2016-01-01
The present paper explores nonnative (L2) phonological encoding of lexical entries and dissociates the difficulties associated with L2 phonological and phonolexical encoding by focusing on similarly sounding L2 words that are not differentiated by difficult phonological contrasts. We test two main claims of the fuzzy lexicon hypothesis: (1) L2 fuzzy phonolexical representations are not fully specified and lack details at both phonological and phonolexical levels of representation (Experiment 1); and (2) fuzzy phonolexical representations can lead to establishing incorrect form-to-meaning mappings (Experiment 2). The Russian-English Translation Judgment Task (Experiment 1, TJT) explores how the degree of phonolexical similarity between a word and its lexical competitor affects lexical access of Russian words. Words with smaller phonolexical distance (e.g., parent–parrot) show longer reaction times and lower accuracy compared to words with a larger phonolexical distance (e.g., parent–parchment) in lower-proficiency nonnative speakers, and, to a lesser degree, higher-proficiency speakers. This points to a lack of detail in nonnative phonolexical representations necessary for efficient lexical access. The Russian Pseudo-Semantic Priming task (Experiment 2, PSP) addresses the vulnerability of form-to-meaning mappings as a consequence of fuzzy phonolexical representations in L2. We primed the target with a word semantically related to its phonological competitor, or a potentially confusable word. The findings of Experiment 2 extend the results of Experiment 1 that, unlike native speakers, nonnative speakers do not properly encode phonolexical information. As a result, they are prone to access an incorrect lexical representation of a competitor word, as indicated by a slowdown in the judgments to confusable words. The study provides evidence that fuzzy phonolexical representations result in unfaithful form-to-meaning mappings, which lead to retrieval of incorrect
SHORTEST PATH ARC LENGTH NETWORK USING TRIANGULAR INTUITIONISTIC FUZZY NUMBER
Directory of Open Access Journals (Sweden)
A.D.CHANDRASEKARAN
2016-04-01
Full Text Available In this paper, an intuitionistic fuzzy shortest path is presented to find the optimal path in a network which a fuzzy number, instead of a positive integer is assigned to each arc length. The algorithm is based on the idea that firstly from all the shortest paths from source to destination, an arc with shortest length is computed and then the Euclidean distance is computed for all the paths with the arc of minimum distance. Finally an illustrative numerical example is given to express the proposed work.
EFFICIENT SUBSPACE CLUSTERING FOR HIGHER DIMENSIONAL DATA USING FUZZY ENTROPY
Institute of Scientific and Technical Information of China (English)
C.PALANISAMY; S.SELVAN
2009-01-01
In this paper we propose a novel method for identifying relevant subspaces using fuzzy entropy and perform clustering. This measure discriminates the real distribution better by using membership functions for measuring class match degrees. Hence the fuzzy entropy reflects more information in the actual disbution of patterns in the subspaces. We use a heuristic procedure based on the silhouette criterion to find the number of clusters. The presented theories and algorithms are evaluated through experiments on a collection of benchmark data sets. Empirical results have shown its favorable performance in comparison with several other clustering algorithms.
Gravitational correction to fuzzy string in metastable brane configuration
Energy Technology Data Exchange (ETDEWEB)
Kasai, Aya [Department of Physics, Kyushu University, Fukuoka 810-8581 (Japan); Ookouchi, Yutaka [Department of Physics, Kyushu University, Fukuoka 810-8581 (Japan); Faculty of Arts and Science, Kyushu University, Fukuoka 819-0395 (Japan)
2015-06-16
We study dynamics of a cosmic string in a metastable brane configuration in Type IIA string theory. We first discuss a decay process of the cosmic string via a fuzzy brane (equivalently bubble/string bound state) by neglecting gravitational corrections in ten-dimension. We find that depending on the strength of the magnetic field induced on the bubble, the decay rate can be either larger or smaller than that of O(4) symmetric bubble. Then, we investigate gravitational corrections to the fuzzy brane by using the extremal black NS-five brane solution, which makes the lifetime of the metastable state longer.
UNDERSTANDING OF FUZZY OPTIMIZATION:THEORIES AND METHODS
Institute of Scientific and Technical Information of China (English)
TANG Jiafu; WANG Dingwei; Richard Y K FUNG; Kai-Leung Yung
2004-01-01
A brief summary on and comprehensive understanding of fuzzy optimizationis presentedThis summary is made on aspects of fuzzy modelling and fuzzy optimization,classification and formulation for the fuzzy optimization problems, models and methods.The importance of interpretation of the problem and formulation of the optimal solutionin fuzzy sense are emphasized in the summary of the fuzzy optimization.
Majorizational Choosing of SeveralDifferent Fuzzy Counter Operator
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
Different fuzzy reasoning methods were made by choosing different fuzzy operater. This article generally introduced the basic structure of fuzzy controller ,and gave several different fuzzy controllers ,and compared and analyzed different fuzzy counters in theory and computer simulating control and realized majorizational choosing of several fuzzy counters.
Fuzzy random variables — I. definitions and theorems
Kwakernaak, H.
1978-01-01
Fuzziness is discussed in the context of multivalued logic, and a corresponding view of fuzzy sets is given. Fuzzy random variables are introduced as random variables whose values are not real but fuzzy numbers, and subsequently redefined as a particular kind of fuzzy set. Expectations of fuzzy
Fuzzy random variables — I. definitions and theorems
Kwakernaak, Huibert
1978-01-01
Fuzziness is discussed in the context of multivalued logic, and a corresponding view of fuzzy sets is given. Fuzzy random variables are introduced as random variables whose values are not real but fuzzy numbers, and subsequently redefined as a particular kind of fuzzy set. Expectations of fuzzy rand
A Bibliography on Fuzzy Automata, Grammars and Lanuages
Asveld, P.R.J.
1996-01-01
This bibliography contains references to papers on fuzzy formal languages, the generation of fuzzy languages by means of fuzzy grammars, the recognition of fuzzy languages by fuzzy automata and machines, as well as some applications of fuzzy set theory to syntactic pattern recognition, linguistics a
A Bibliography on Fuzzy Automata, Grammars and Lanuages
Asveld, Peter R.J.
1995-01-01
This bibliography contains references to papers on fuzzy formal languages, the generation of fuzzy languages by means of fuzzy grammars, the recognition of fuzzy languages by fuzzy automata and machines, as well as some applications of fuzzy set theory to syntactic pattern recognition, linguistics a
Fuzzy random variables — I. definitions and theorems
Kwakernaak, H.
1978-01-01
Fuzziness is discussed in the context of multivalued logic, and a corresponding view of fuzzy sets is given. Fuzzy random variables are introduced as random variables whose values are not real but fuzzy numbers, and subsequently redefined as a particular kind of fuzzy set. Expectations of fuzzy rand
Fuzzy Content-Based Retrieval in Image Databases.
Wu, Jian Kang; Narasimhalu, A. Desai
1998-01-01
Proposes a fuzzy-image database model and a concept of fuzzy space; describes fuzzy-query processing in fuzzy space and fuzzy indexing on complete fuzzy vectors; and uses an example image database, the computer-aided facial-image inference and retrieval system (CAFIIR), for explanation throughout. (Author/LRW)
13. workshop fuzzy systems. Proceedings; 13. Workshop Fuzzy Systeme. Beitraege
Energy Technology Data Exchange (ETDEWEB)
Mikut, R.; Reischl, M. (eds.)
2003-11-01
This volume contains the papers presented at the 13th workshop on fuzzy systems of TC 5.2.2 'Fuzzy Control' of the VDI/VDE-Gesellschaft fuer Mess- und Automatisierungstechnik (GMA) and the TG 'Fuzzy Systems and Soft Computing' of the Gesellschaft fuer Informatik (GI), which took place at Dortmund on November 19-21, 2003. New methods and applications of fuzzy logic, artificial neuronal nets and evolutionary algorithms were presented. The focus was on automation, e.g. in chemical engineering, energy engineering, motor car engineering, robotics and medical engineering. Other applications, e.g. data mining for technical and non-technical applications, were gone into as well. [German] Dieser Tagungsband enthaelt die Beitraege des 13. Workshops ''Fuzzy System'' des Fachausschusses 5.22 ''Fuzzy Control'' der VDI/VDE-Gesellschaft fuer Mess- und Automatisierungstechnik (GMA) und der Fachgruppe ''Fuzzy-Systeme und Soft-Computing'' der Gesellschaft fuer Informatik (GI), der vom 19.-21. November 2003 im Haus Bommerholz, Dortmund, stattfindet. Der jaehrliche Workshop unseres Fachausschusses bietet ein Forum zur Diskussion neuer methodischer Ansaetze und industrieller Anwendungen auf dem Gebiet der Fuzzy-Logik und in angrenzenden Gebieten wie Kuenstlichen Neuronalen Netzen und Evolutionaeren Algorithmen. Besondere Schwerpunkte sind automatisierungstechnische Anwendungen, z.B. in der Verfahrenstechnik, Energietechnik, Kfz-Technik, Robotik und Medizintechnik, aber auch Loesungen in anderen Problemgebieten (z.B. Data Mining fuer technische und nichttechnische Anwendungen) sind von Interesse. (orig.)
FuzzySTAR: Fuzzy set theory of axiomatic design review
Huang, GQ; Jiang, Z
2002-01-01
Product development involves multiple phases. Design review (DR) is an essential activity formally conducted to ensure a smooth transition from one phase to another. Such a formal DR is usually a multicriteria decision problem, involving multiple disciplines. This paper proposes a systematic framework for DR using fuzzy set theory. This fuzzy approach to DR is considered particularly relevant for several reasons. First, information available at early design phases is often incomplete and impr...
Rough Set Fuzzy Optimum Selecting in Multidisciplinary System
Institute of Scientific and Technical Information of China (English)
LIU Xu-lin; SONG Bao-wei; WANG Jin-hua; CHEN Jie
2008-01-01
Scheme evaluation and selection is an optimum selecting and sequencing problem with multi-objective and multi- level. It can't follow single objective function or rule. Meanwhile, these objectives are coupled with each other and the at- tribution information is fuzzy also. It is necessary to find an effective evaluation method which can consider all conditions and restrictions. In this paper, AHP and rough set theory are applied to fuzzy optimization to determine important weight of each attribution. The rough set fuzzy optimum selection is used to eliminate the useless information. Autonomous un- derwater vehicle (AUV) is large-scah systems with many coupled design variables and objective functions. Their scheme evaluation and selection are very important, which relate to multiple factors, such as reliability;security, service time; the lifeeyele, etc. Results of application in torpedo design indicate that this method is feasible.
New Definition for Fuzzy Constraint Satisfaction Problem and its Applications
Ghasemiesfeh, Golnaz
2011-01-01
{\\it Fuzzy Constraint Satisfaction Problem} ($FCSP$) is a kind of relaxed Constraint Satisfaction Problems, which models constraints as fuzzy relations. In this paper, we introduce a new definition for $FCSP$ to show that complexity of providing a solution for a given $FCSP$ is equal to complexity of finding a solution for a corresponding given {\\it Fuzzy Graph Homomorphism Problem} ($FGHP$). In the other words, we prove that $minimorphismFCSP_{_{3}}$ is polynomially equivalent to $minFHom_{1}^{\\phantom{1}G,H}$. Furthermore, we transform these concepts to a Categorical framework and prove that the corresponding functor $F$, from category of $FCSP$s to category of $FGHP$s and the reverse functor $L$ are adjoints of each other. Finally, we show how we can use this new definition of $FCSP$ in modeling various optimization problems such as {\\it Network On Chip Problem} ($NoC$).
Rough Fuzzy Relation on Two Universal Sets
Directory of Open Access Journals (Sweden)
Xuan Thao Nguyen
2014-03-01
Full Text Available Fuzzy set theory was introduced by L.A. Zadeh in 1965. Immediately, it has many applications in practice and in building databases, one of which is the construction of a fuzzy relational database based on similar relationship. The study of cases of fuzzy relations in different environments will help us understand its applications. In this paper, the rough fuzzy relation on Cartesian product of two universe sets is defined, and then the algebraic properties of them, such as the max, min, and composition of two rough fuzzy relations are examined. Finally, reflexive, α-reflexive, symmetric and transitive rough fuzzy relations on two universe sets are also defined.
Institute of Scientific and Technical Information of China (English)
饶三平
2012-01-01
基于完备剩余格,本文在模糊完备格中,引入模糊Prime元概念.给出了模糊Prime元的等价刻画,证明了所有的模糊Prime元构成的模糊集是模糊完全分配格.%Based on complete residuated lattices, the concept of fuzzy Prime elements in fuzzy complete lattices is given, then the equivalent characterization of fuzzy Prime elements is obtained. We also prove that the fuzzy subsets of fuzzy Prime elements is a fuzzy completely distributice lattice.
FUZZY EPQ INVENTORY MODELS WITH BACKORDER
Institute of Scientific and Technical Information of China (English)
Xiaobin WANG; Wansheng TANG
2009-01-01
This paper considers the economic production quantity (EPQ) problem with backorder in which the setup cost, the holding cost and the backorder cost are characterized as fuzzy variables, respectively. Following expected value criterion and chance constrained criterion, a fuzzy expected value model (EVM) and a chance constrained programming (CCP) model are constructed. Then fuzzy simulations are employed to estimate the expected value of fuzzy variable and α-level minimal average cost. In order to solve the CCP model, a particle swarm optimization (PSO) algorithm based on the fuzzy simulation is designed. Finally, the effectiveness of PSO algorithm based on the fuzzy simulation is illustrated by a numerical example.
Adaptive Fuzzy Control for CVT Vehicle
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
On the simple continuously variable transmission (CVT) driveline model, the design of adaptive fuzzy control system for CVT vehicle is presented. The adaptive fuzzy control system consists of a scaling factor self-tuning fuzzy-PI throttle controller, and a hybrid fuzzy-PID CVT ratio and brake controller. The presented adaptive fuzzy control strategy is vehicle model independent, which depends only on the instantaneous vehicle states, but does not depend on vehicle parameters. So it has good robustness against uncertain vehicle parameters and exogenous load disturbance. Simulation results show that the proposed adaptive fuzzy strategy has good adaptability and practicality value.
Type-2 fuzzy fractional derivatives
Mazandarani, Mehran; Najariyan, Marzieh
2014-07-01
In this paper, we introduce two definitions of the differentiability of type-2 fuzzy number-valued functions of fractional order. The definitions are in the sense of Riemann-Liouville and Caputo derivative of order β ɛ (0, 1), and based on type-2 Hukuhara difference and H2-differentiability. The existence and uniqueness of the solutions of type-2 fuzzy fractional differential equations (T2FFDEs) under Caputo type-2 fuzzy fractional derivative and the definition of Laplace transform of type-2 fuzzy number-valued functions are also given. Moreover, the approximate solution to T2FFDE by a Predictor-Evaluate-Corrector-Evaluate (PECE) method is presented. Finally, the approximate solutions of two examples of linear and nonlinear T2FFDEs are obtained using the PECE method, and some cases of T2FFDEs applications in some sciences are presented.
Intuitionistic fuzzy hierarchical clustering algorithms
Institute of Scientific and Technical Information of China (English)
Xu Zeshui
2009-01-01
Intuitionistic fuzzy set (IFS) is a set of 2-tuple arguments, each of which is characterized by a mem-bership degree and a nonmembership degree. The generalized form of IFS is interval-valued intuitionistic fuzzy set (IVIFS), whose components are intervals rather than exact numbers. IFSs and IVIFSs have been found to be very useful to describe vagueness and uncertainty. However, it seems that little attention has been focused on the clus-tering analysis of IFSs and IVIFSs. An intuitionistic fuzzy hierarchical algorithm is introduced for clustering IFSs, which is based on the traditional hierarchical clustering procedure, the intuitionistic fuzzy aggregation operator, and the basic distance measures between IFSs: the Hamming distance, normalized Hamming, weighted Hamming, the Euclidean distance, the normalized Euclidean distance, and the weighted Euclidean distance. Subsequently, the algorithm is extended for clustering IVIFSs. Finally the algorithm and its extended form are applied to the classifications of building materials and enterprises respectively.
Fuzzy indicators for customer retention
National Research Council Canada - National Science Library
Valenzuela-Fernández, Leslier; Nicolas, Carolina; Gil-Lafuente, Jaime; Merigó, José M
2016-01-01
.... Nevertheless, one cannot ignore the existence of a gap on how to measure this relationship. Following this idea, this study proposes six fuzzy key performance indicators that aims to measure customer retention and loyalty of the portfolio...
Directory of Open Access Journals (Sweden)
V. Lakshmana Gomathi Nayagam
2007-01-01
Full Text Available The notion of fuzzy filters was studied by Vicente and Aranguren (1988, Lowen (1979, and Ramakrishnan and Nayagam (2002. The notion of fuzzily compactness was introduced and studied by Ramakrishnan and Nayagam (2002. In this paper, an equivalent condition of fuzzily compactness is studied and a new notion of semi-Hausdorffness on fuzzy filters, which cannot be defined in crisp theory of filters, is introduced and studied.
FUZZY LOGIC IN LEGAL EDUCATION
Directory of Open Access Journals (Sweden)
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
2005-01-01
A new all-electronic Particle Image Velocimetry technique that can efficiently map high speed gas flows has been developed in-house at the NASA Lewis Research Center. Particle Image Velocimetry is an optical technique for measuring the instantaneous two component velocity field across a planar region of a seeded flow field. A pulsed laser light sheet is used to illuminate the seed particles entrained in the flow field at two instances in time. One or more charged coupled device (CCD) cameras can be used to record the instantaneous positions of particles. Using the time between light sheet pulses and determining either the individual particle displacements or the average displacement of particles over a small subregion of the recorded image enables the calculation of the fluid velocity. Fuzzy logic minimizes the required operator intervention in identifying particles and computing velocity. Using two cameras that have the same view of the illumination plane yields two single exposure image frames. Two competing techniques that yield unambiguous velocity vector direction information have been widely used for reducing the single-exposure, multiple image frame data: (1) cross-correlation and (2) particle tracking. Correlation techniques yield averaged velocity estimates over subregions of the flow, whereas particle tracking techniques give individual particle velocity estimates. For the correlation technique, the correlation peak corresponding to the average displacement of particles across the subregion must be identified. Noise on the images and particle dropout result in misidentification of the true correlation peak. The subsequent velocity vector maps contain spurious vectors where the displacement peaks have been improperly identified. Typically these spurious vectors are replaced by a weighted average of the neighboring vectors, thereby decreasing the independence of the measurements. In this work, fuzzy logic techniques are used to determine the true
A novel definition of L-fuzzy lattice based on fuzzy set.
Zhang, Jun-Fang
2013-01-01
The concept of L-fuzzy lattice is presented by means of an L-fuzzy partially ordered set. An L-fuzzy partially ordered set A is an L-fuzzy lattice if and only if one of A[a], A([a]), and A(a) is a lattice.
On The Transition Probabilities for the Fuzzy States of a Fuzzy Markov Chain
Directory of Open Access Journals (Sweden)
J.Earnest Lazarus Piriyakumar
2015-12-01
Full Text Available In this paper the theory of fuzzy logic is mixed with the theory of Markov systems and the abstraction of a Markov system with fuzzy states introduced. The notions such as fuzzy transient, fuzzy recurrent etc., were introduced. The results based on these notions are introduced.
Directory of Open Access Journals (Sweden)
Zhe Zhang
2014-06-01
Full Text Available Purpose: The aim of this paper is to deal with the supply chain management (SCM with quantity discount policy under the complex fuzzy environment, which is characterized as the bi-fuzzy variables. By taking into account the strategy and the process of decision making, a bi-fuzzy nonlinear multiple objective decision making (MODM model is presented to solve the proposed problem.Design/methodology/approach: The bi-fuzzy variables in the MODM model are transformed into the trapezoidal fuzzy variables by the DMs's degree of optimism ?1 and ?2, which are de-fuzzified by the expected value index subsequently. For solving the complex nonlinear model, a multi-objective adaptive particle swarm optimization algorithm (MO-APSO is designed as the solution method.Findings: The proposed model and algorithm are applied to a typical example of SCM problem to illustrate the effectiveness. Based on the sensitivity analysis of the results, the bi-fuzzy nonlinear MODM SCM model is proved to be sensitive to the possibility level ?1.Practical implications: The study focuses on the SCM under complex fuzzy environment in SCM, which has a great practical significance. Therefore, the bi-fuzzy MODM model and MO-APSO can be further applied in SCM problem with quantity discount policy.Originality/value: The bi-fuzzy variable is employed in the nonlinear MODM model of SCM to characterize the hybrid uncertain environment, and this work is original. In addition, the hybrid crisp approach is proposed to transferred to model to an equivalent crisp one by the DMs's degree of optimism and the expected value index. Since the MODM model consider the bi-fuzzy environment and quantity discount policy, so this paper has a great practical significance.
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.
Fuzzy-rough set and fuzzy ID3 decision approaches to knowledge discovery in datasets
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O. G. Elbarbary
2012-07-01
Full Text Available Fuzzy rough sets are the generalization of traditional rough sets to deal with both fuzziness and vagueness in data. The existing researches on fuzzy rough sets mainly concentrate on the construction of approximation operators. Less effort has been put on the knowledge discovery in datasets with fuzzy rough sets. This paper mainly focuses on knowledge discovery in datasets with fuzzy rough sets. After analyzing the previous works on knowledge discovery with fuzzy rough sets, we introduce formal concepts of attribute reduction with fuzzy rough sets and completely study the structure of attribute reduction.
Construction of Fuzzy Map for Autonomous Mobile Robots Based on Fuzzy Confidence Model
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Jung-Fu Hou
2014-01-01
Full Text Available This paper presents the use of fuzzy models to explicitly consider sensor uncertainty and finite resolution in solving the SLAM (simultaneous localization and mapping problem for autonomous mobile robots. The approach establishes fuzzy confidence models in describing occupied obstacles and available space. The problem is transformed into an optimization task of minimizing the alignment error between newly scanned local fuzzy maps and selected parts of a developing global fuzzy map. In aligning local fuzzy maps into a global fuzzy map, we developed a prediction strategy to crop the most potential part from the sensed local fuzzy maps to be overlapped with the global fuzzy map. A mobile vehicle equipped with a laser range finder, the Hokuyo URG-04LX, is used to demonstrate the procedure of fuzzy map building. Experimental results show that the proposed architecture is effective in generating a comprehensive global fuzzy map, which is suitable for both human comprehension and path design during real-time navigation.
FUZZY ARITHMETIC AND SOLVING OF THE STATIC GOVERNING EQUATIONS OF FUZZY FINITE ELEMENT METHOD
Institute of Scientific and Technical Information of China (English)
郭书祥; 吕震宙; 冯立富
2002-01-01
The key component of finite element analysis of structures with fuzzy parameters,which is associated with handling of some fuzzy information and arithmetic relation of fuzzy variables, was the solving of the governing equations of fuzzy finite element method. Based on a given interval representation of fuzzy numbers, some arithmetic rules of fuzzy numbers and fuzzy variables were developed in terms of the properties of interval arithmetic.According to the rules and by the theory of interval finite element method, procedures for solving the static governing equations of fuzzy finite element method of structures were presented. By the proposed procedure, the possibility distributions of responses of fuzzy structures can be generated in terms of the membership functions of the input fuzzy numbers.It is shown by a numerical example that the computational burden of the presented procedures is low and easy to implement. The effectiveness and usefulness of the presented procedures are also illustrated.
The Relationship of Between Fuzzy Power Groups and Fuzzy Quotient Groups%Fuzzy幂群与Fuzzy商群的相互关系
Institute of Scientific and Technical Information of China (English)
闫广霞; 米洪海; 施雅婷
2006-01-01
In this paper, we extend the concept of fuzzy quotient groups. The structures of fuzzy power groups and fuzzy quotient groups are discussed. The relationship between fuzzy power groups and fuzzy quotient groups are considered.
A CAD MODEL FOR FUZZY CONCURRENT TOLERANCE
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
Research situation of concurrent tolerance design has been analyzed. As fuzzy factors are objective and unavoidable in concurrent tolerance design, fuzzy optimization theory is applied in the design. A new mathematical model of concurrent tolerance design is constructed.
Analysis of Fuzzy Words in Legal English
Institute of Scientific and Technical Information of China (English)
赵波
2015-01-01
With the development of legal English,fuzzy words are poured into legislative language and judicial practice constantly.Hence,this paper aims at exploring the application and funtion of different kinds of fuzzy words in legal English.
Compound Option Pricing under Fuzzy Environment
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Xiandong Wang
2014-01-01
Full Text Available Considering the uncertainty of a financial market includes two aspects: risk and vagueness; in this paper, fuzzy sets theory is applied to model the imprecise input parameters (interest rate and volatility. We present the fuzzy price of compound option by fuzzing the interest and volatility in Geske’s compound option pricing formula. For each α, the α-level set of fuzzy prices is obtained according to the fuzzy arithmetics and the definition of fuzzy-valued function. We apply a defuzzification method based on crisp possibilistic mean values of the fuzzy interest rate and fuzzy volatility to obtain the crisp possibilistic mean value of compound option price. Finally, we present a numerical analysis to illustrate the compound option pricing under fuzzy environment.
Fuzzy differential equations in various approaches
Gomes, Luciana Takata; Bede, Barnabas
2015-01-01
This book may be used as reference for graduate students interested in fuzzy differential equations and researchers working in fuzzy sets and systems, dynamical systems, uncertainty analysis, and applications of uncertain dynamical systems. Beginning with a historical overview and introduction to fundamental notions of fuzzy sets, including different possibilities of fuzzy differentiation and metric spaces, this book moves on to an overview of fuzzy calculus thorough exposition and comparison of different approaches. Innovative theories of fuzzy calculus and fuzzy differential equations using fuzzy bunches of functions are introduced and explored. Launching with a brief review of essential theories, this book investigates both well-known and novel approaches in this field; such as the Hukuhara differentiability and its generalizations as well as differential inclusions and Zadeh’s extension. Through a unique analysis, results of all these theories are examined and compared.
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...
Xu, Yan; Suzuki, Yuta; Ishizuka, Takumi; Xiao, Chao-Da; Liu, Xiao; Hayashi, Tetsuya; Komiyama, Makoto
2014-08-15
Telomeric repeat-containing RNA is a non-coding RNA molecule newly found in mammalian cells. The telomere RNA has been found to localize to the telomere DNA, but how the newly discovered RNA molecule interacts with telomere DNA is less known. In this study, using the click chemistry we successfully found that a 6-mer human telomere RNA and 16-mer human telomere DNA sequence can form a DNA-RNA hybrid type G-quadruplex structure. Detection of the click-reaction products directly probes DNA-RNA G-quadruplex structures in a complicated solution, whereas traditional methods such as NMR and crystallography may not be suitable. Importantly, we found that formation of DNA-RNA G-quadruplex induced an exonuclease resistance for telomere DNA, indicating that such structures might be important for protecting telomeric DNA from enzyme digestion to avoid telomere DNA shortening. These results provide the direct evidence for formation of DNA-RNA hybrid G-quadruplex structure by human telomere DNA and RNA sequence, suggesting DNA-RNA hybrid G-quadruplex structure associated between telomere DNA and RNA may respond to chromosome end protection and/or present a valuable target for drug design.
Cheap diagnosis using structural modelling and fuzzy-logic based detection
DEFF Research Database (Denmark)
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......Practical fault diagnosis can be based on simple, yet efficient, analysis of redundant information about the state of a plant, and diagnostic algorithms can be made without detailed and expensive modelling efforts. This paper shows how it is possible, using structural analysis, to find redundancy...
A Framework to Measure the Service Quality of Distributor with Fuzzy Graph Theoretic Approach
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Tarun Kumar Gupta
2016-01-01
Full Text Available A combination of fuzzy logic and graph theoretic approach has been used to find the service quality of distributor in a manufacturing supply chain management. This combination is termed as the fuzzy graph theoretic (FGT approach. Initially the identified factors were grouped by SPSS (statistical package for social science software and then the digraph approach was applied. The interaction and inheritance values were calculated by fuzzy graph theory approach in terms of permanent function. Then a single numerical index was calculated by using permanent function which indicates the distributor service quality. This method can be used to compare the service quality of different distributors.
The lattices of group fuzzy congruences and normal fuzzy subsemigroups on E-inversive semigroups.
Wang, Shoufeng
2014-01-01
The aim of this paper is to investigate the lattices of group fuzzy congruences and normal fuzzy subsemigroups on E-inversive semigroups. We prove that group fuzzy congruences and normal fuzzy subsemigroups determined each other in E-inversive semigroups. Moreover, we show that the set of group t-fuzzy congruences and the set of normal subsemigroups with tip t in a given E-inversive semigroup form two mutually isomorphic modular lattices for every t ∈ [0,1].
An Intelligent Trading System with Fuzzy Rules and Fuzzy Capital Management
Naranjo, Rodrigo; Meco, Albert; Arroyo Gallardo, Javier; Santos Peñas, Matilde
2015-01-01
In this work we are proposing a trading system where fuzzy logic is applied not only for defining the trading rules, but also for managing the capital to invest. In fact, two fuzzy decision support systems are developed. The first one uses fuzzy logic to design the trading rules and to apply the stock market technical indicators. The second one enhances this fuzzy trading system adding a fuzzy strategy to manage the capital to trade. Additionally, a new technical market indicator that produce...
On Some Fuzzy Filters in Pseudo-BCI Algebras
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Xiaohong Zhang
2014-01-01
Full Text Available Some new properties of fuzzy associative filters (also known as fuzzy associative pseudo-filters, fuzzy p-filter (also known as fuzzy pseudo-p-filters, and fuzzy a-filter (also known as fuzzy pseudo-a-filters in pseudo-BCI algebras are investigated. By these properties, the following important results are proved: (1 a fuzzy filter (also known as fuzzy pseudo-filters of a pseudo-BCI algebra is a fuzzy associative filter if and only if it is a fuzzy a-filter; (2 a filter (also known as pseudo-filter of a pseudo-BCI algebra is associative if and only if it is an a-filter (also call it pseudo-a filter; (3 a fuzzy filter of a pseudo-BCI algebra is fuzzy a-filter if and only if it is both a fuzzy p-filter and a fuzzy q-filter.
De-Donatis, Gian Marco; Zhao, Zhengyi; Wang, Shaoying; Huang, Lisa P; Schwartz, Chad; Tsodikov, Oleg V; Zhang, Hui; Haque, Farzin; Guo, Peixuan
2014-01-01
Double-stranded DNA translocation is ubiquitous in living systems. Cell mitosis, bacterial binary fission, DNA replication or repair, homologous recombination, Holliday junction resolution, viral genome packaging and cell entry all involve biomotor-driven dsDNA translocation. Previously, biomotors have been primarily classified into linear and rotational motors. We recently discovered a third class of dsDNA translocation motors in Phi29 utilizing revolution mechanism without rotation. Analogically, the Earth rotates around its own axis every 24 hours, but revolves around the Sun every 365 days. Single-channel DNA translocation conductance assay combined with structure inspections of motor channels on bacteriophages P22, SPP1, HK97, T7, T4, Phi29, and other dsDNA translocation motors such as bacterial FtsK and eukaryotic mimiviruses or vaccinia viruses showed that revolution motor is widespread. The force generation mechanism for revolution motors is elucidated. Revolution motors can be differentiated from rotation motors by their channel size and chirality. Crystal structure inspection revealed that revolution motors commonly exhibit channel diameters larger than 3 nm, while rotation motors that rotate around one of the two separated DNA strands feature a diameter smaller than 2 nm. Phi29 revolution motor translocated double- and tetra-stranded DNA that occupied 32% and 64% of the narrowest channel cross-section, respectively, evidencing that revolution motors exhibit channel diameters significantly wider than the dsDNA. Left-handed oriented channels found in revolution motors drive the right-handed dsDNA via anti-chiral interaction, while right-handed channels observed in rotation motors drive the right-handed dsDNA via parallel threads. Tethering both the motor and the dsDNA distal-end of the revolution motor does not block DNA packaging, indicating that no rotation is required for motors of dsDNA phages, while a small-angle left-handed twist of dsDNA that is
Financial Performance Evaluation of Turkish Energy Companies with Fuzzy AHP and Fuzzy TOPSIS Methods
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Kemal Eyuboglu
2016-07-01
Full Text Available Turkey’s economy has expanded in recent years with the increase in energy consumption. Energy is a key input in production and plays a crucial role in the development of an economy. Energy sector interacts with other sectors hence the performances of energy firms are inevitable to follow-up. In the study thirteen energy firms are evaluated with 5 main and 15 sub-criteria for the period of 2008-2013. The 15 sub-criteria are classified in the following main criteria: liquidity, activity, financial leverage, profitability and growth ratios. The weights of the ratios are determined by Fuzzy AHP and then Fuzzy TOPSIS method is used for the rankings of the energy firms. Traditional multi-criteria decision making methods are not used in this study, due to the fact that they are insufficient under uncertainty. After 2008 global financial crisis, the uncertainty has increased all over the world hence the usage of fuzzy methods can provide better results under these conditions. Findings show that Avrasya Oil, Turcas and Aksu have the highest ranking.
Neuro-fuzzy Control of Integrating Processes
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Anna Vasičkaninová
2011-11-01
Full Text Available Fuzzy technology is adaptive and easily applicable in different areas.Fuzzy logic provides powerful tools to capture the perceptionof natural phenomena. The paper deals with tuning of neuro-fuzzy controllers for integrating plant and for integrating plantswith time delay. The designed approach is verified on three examples by simulations and compared plants with classical PID control.Designed fuzzy controllers lead to better closed-loop control responses then classical PID controllers.
An Investigation into Fuzzy Clustering and Classification.
1984-07-01
Introduction to Fuzzy Sets The theory of fuzzy sets was developed by Lofti Zadeh in 1965(4). The impetus behind the introduction of the fuzzy set was...Syntactic Pattern Recoonition: An Introduction, Reading, Massachussetts, Addison-Wesley, 1978 4. Zadeh , Lofti A., "Fuzzy Sets", Information and...where the models based on crisp set theory fall short of providing a useful description of things, people, or places. So, as Professor Zadeh proposed
Linear Design Approach to a Fuzzy Controller
DEFF Research Database (Denmark)
Jantzen, Jan
1999-01-01
A ball-balancer, basically an inverted pendulum problem, is stabilised by a linear controller. With certain design choices, a fuzzy controller is equivalent to a summation; thus it can replace the linear controller. It can be claimed, that the fuzzy controller performs at least as well...... as the linear controller, since the linear controller is contained in the fuzzy controller. The approach makes it somewhat easier to design a fuzzy controller....
Operations on Intuitionistic Fuzzy Graph Structures
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Muhammad Akram
2016-12-01
Full Text Available An intuitionistic fuzzy graph structure (IFGS is a generalization of an intuitionistic fuzzy graph. The concept of intuitionistic fuzzy graph structure is introduced and investigated in this paper. Some operations including union, join, Cartesian product, cross product, lexicographic product, strong product and composition on intuitionistic fuzzy graph structures are defined and elaborated with a number of examples. Some basic properties of these operations are also presented.
Fuzzy Clustering Using C-Means Method
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Georgi Krastev
2015-05-01
Full Text Available The cluster analysis of fuzzy clustering according to the fuzzy c-means algorithm has been described in this paper: the problem about the fuzzy clustering has been discussed and the general formal concept of the problem of the fuzzy clustering analysis has been presented. The formulation of the problem has been specified and the algorithm for solving it has been described.
Aggregation Operator Based Fuzzy Pattern Classifier Design
DEFF Research Database (Denmark)
Mönks, Uwe; Larsen, Henrik Legind
2009-01-01
This paper presents a novel modular fuzzy pattern classifier design framework for intelligent automation systems, developed on the base of the established Modified Fuzzy Pattern Classifier (MFPC) and allows designing novel classifier models which are hardware-efficiently implementable. The perfor......This paper presents a novel modular fuzzy pattern classifier design framework for intelligent automation systems, developed on the base of the established Modified Fuzzy Pattern Classifier (MFPC) and allows designing novel classifier models which are hardware-efficiently implementable...
Fuzzy Based composition Control of Distillation Column
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Guru.R
2013-04-01
Full Text Available This paper proposed a control scheme based on fuzzy logic for a methanol - water system of bubble cap distillation column. Fuzzy rule base and Inference System of fuzzy (FIS is planned to regulatethe reflux ratio (manipulated variable to obtain the preferred product composition (methanol for a distillation column. Comparisons are made with conventional controller and the results confirmed the potentials of the proposed strategy of fuzzy control.
Consistent linguistic fuzzy preference relations method with ranking fuzzy numbers
Ridzuan, Siti Amnah Mohd; Mohamad, Daud; Kamis, Nor Hanimah
2014-12-01
Multi-Criteria Decision Making (MCDM) methods have been developed to help decision makers in selecting the best criteria or alternatives from the options given. One of the well known methods in MCDM is the Consistent Fuzzy Preference Relation (CFPR) method, essentially utilizes a pairwise comparison approach. This method was later improved to cater subjectivity in the data by using fuzzy set, known as the Consistent Linguistic Fuzzy Preference Relations (CLFPR). The CLFPR method uses the additive transitivity property in the evaluation of pairwise comparison matrices. However, the calculation involved is lengthy and cumbersome. To overcome this problem, a method of defuzzification was introduced by researchers. Nevertheless, the defuzzification process has a major setback where some information may lose due to the simplification process. In this paper, we propose a method of CLFPR that preserves the fuzzy numbers form throughout the process. In obtaining the desired ordering result, a method of ranking fuzzy numbers is utilized in the procedure. This improved procedure for CLFPR is implemented to a case study to verify its effectiveness. This method is useful for solving decision making problems and can be applied to many areas of applications.
Decomposed fuzzy systems and their application in direct adaptive fuzzy control.
Hsueh, Yao-Chu; Su, Shun-Feng; Chen, Ming-Chang
2014-10-01
In this paper, a novel fuzzy structure termed as the decomposed fuzzy system (DFS) is proposed to act as the fuzzy approximator for adaptive fuzzy control systems. The proposed structure is to decompose each fuzzy variable into layers of fuzzy systems, and each layer is to characterize one traditional fuzzy set. Similar to forming fuzzy rules in traditional fuzzy systems, layers from different variables form the so-called component fuzzy systems. DFS is proposed to provide more adjustable parameters to facilitate possible adaptation in fuzzy rules, but without introducing a learning burden. It is because those component fuzzy systems are independent so that it can facilitate minimum distribution learning effects among component fuzzy systems. It can be seen from our experiments that even when the rule number increases, the learning time in terms of cycles is still almost constant. It can also be found that the function approximation capability and learning efficiency of the DFS are much better than that of the traditional fuzzy systems when employed in adaptive fuzzy control systems. Besides, in order to further reduce the computational burden, a simplified DFS is proposed in this paper to satisfy possible real time constraints required in many applications. From our simulation results, it can be seen that the simplified DFS can perform fairly with a more concise decomposition structure.
On T-Fuzzy Ideals in Nearrings
Directory of Open Access Journals (Sweden)
Muhammad Akram
2007-01-01
Full Text Available We introduce the notion of fuzzy ideals in nearrings with respect to a t-norm T and investigate some of their properties. Using T-fuzzy ideals, characterizations of Artinian and Noetherian nearrings are established. Some properties of T-fuzzy ideals of the quotient nearrings are also considered.
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;
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…
Fuzzy image processing in sun sensor
Mobasser, S.; Liebe, C. C.; Howard, A.
2003-01-01
This paper will describe how the fuzzy image processing is implemented in the instrument. Comparison of the Fuzzy image processing and a more conventional image processing algorithm is provided and shows that the Fuzzy image processing yields better accuracy then conventional image processing.
Function Approximation Using Probabilistic Fuzzy Systems
J.H. van den Berg (Jan); U. Kaymak (Uzay); R.J. Almeida e Santos Nogueira (Rui Jorge)
2011-01-01
textabstractWe consider function approximation by fuzzy systems. Fuzzy systems are typically used for approximating deterministic functions, in which the stochastic uncertainty is ignored. We propose probabilistic fuzzy systems in which the probabilistic nature of uncertainty is taken into account.
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.
Possible use of fuzzy logic in database
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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.
Compactness in L-Fuzzy Topological Spaces
Luna-Torres, Joaquin
2010-01-01
We give a definition of compactness in L-fuzzy topological spaces and provide a characterization of compact L-fuzzy topological spaces, where L is a complete quasi-monoidal lattice with some additional structures, and we present a version of Tychonoff's theorem within the category of L-fuzzy topological spaces.
Full averaging of fuzzy impulsive differential inclusions
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Natalia V. Skripnik
2010-09-01
Full Text Available In this paper the substantiation of the method of full averaging for fuzzy impulsive differential inclusions is studied. We extend the similar results for impulsive differential inclusions with Hukuhara derivative (Skripnik, 2007, for fuzzy impulsive differential equations (Plotnikov and Skripnik, 2009, and for fuzzy differential inclusions (Skripnik, 2009.
Design New Robust Self Tuning Fuzzy Backstopping Methodology
Omid Avatefipour; Farzin Piltan; Mahmoud Reza Safaei Nasrabad; Ghasem Sahamijoo; Alireza Khalilian
2014-01-01
This research is focused on proposed Proportional-Integral (PI) like fuzzy adaptive backstopping fuzzy algorithms based on Proportional-Derivative (PD) fuzzy rule base with the adaptation laws derived in the Lyapunov sense. Adaptive SISO PI like fuzzy adaptive backstopping fuzzy method has two main objectives; the first objective is design a SISO fuzzy system to compensate for the model uncertainties of the system, and the second objective is focused on the design PI like fuzzy controller bas...
On Characterization of Rough Type-2 Fuzzy Sets
Tao Zhao; Zhenbo Wei
2016-01-01
Rough sets theory and fuzzy sets theory are important mathematical tools to deal with uncertainties. Rough fuzzy sets and fuzzy rough sets as generalizations of rough sets have been introduced. Type-2 fuzzy set provides additional degree of freedom, which makes it possible to directly handle high uncertainties. In this paper, the rough type-2 fuzzy set model is proposed by combining the rough set theory with the type-2 fuzzy set theory. The rough type-2 fuzzy approximation operators induced f...
Fuzzy Rules for Ant Based Clustering Algorithm
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Amira Hamdi
2016-01-01
Full Text Available This paper provides a new intelligent technique for semisupervised data clustering problem that combines the Ant System (AS algorithm with the fuzzy c-means (FCM clustering algorithm. Our proposed approach, called F-ASClass algorithm, is a distributed algorithm inspired by foraging behavior observed in ant colonyT. The ability of ants to find the shortest path forms the basis of our proposed approach. In the first step, several colonies of cooperating entities, called artificial ants, are used to find shortest paths in a complete graph that we called graph-data. The number of colonies used in F-ASClass is equal to the number of clusters in dataset. Hence, the partition matrix of dataset founded by artificial ants is given in the second step, to the fuzzy c-means technique in order to assign unclassified objects generated in the first step. The proposed approach is tested on artificial and real datasets, and its performance is compared with those of K-means, K-medoid, and FCM algorithms. Experimental section shows that F-ASClass performs better according to the error rate classification, accuracy, and separation index.
Directory of Open Access Journals (Sweden)
Singh Chaman
2013-01-01
Full Text Available In this paper, an integrated inventory model is developed from the perspective of a single vendor and multi-buyers for deteriorating items under fuzzy environment and inflation. In the development of the model, it is assumed that all costs parameters, demand and the production rates are imprecise in nature; they are represented by the trapezoidal fuzzy numbers, as these parameters are not constant and can be disturbed due to daily market changes. We use function principle as arithmetic operations to find the total inventory cost in fuzzy sense and Graded Mean - Integration Representation Method to defuzzify the fuzzy total inventory cost. Inflation is used to find the present worth of total cost. Since the optimal policy of buyers may not be the most economical for a vendor, thus to deal with this situation, integrated cost policy is used to reach the optimal policy. Finally, a numerical example is given to illustrate the model.
A systematic approach for fine-tuning of fuzzy controllers applied to WWTPs
DEFF Research Database (Denmark)
Ruano, M.V.; Ribes, J.; Sin, Gürkan;
2010-01-01
A systematic approach for fine-tuning fuzzy controllers has been developed and evaluated for an aeration control system implemented in a WWTR The challenge with the application of fuzzy controllers to WWTPs is simply that they contain many parameters, which need to be adjusted for different WWTP...... applications. To this end, a methodology based on model simulations is used that employs three statistical methods: (i) Monte-Carlo procedure: to find proper initial conditions, (ii) Identifiability analysis: to find an identifiable parameter subset of the fuzzy controller and (iii) minimization algorithm......: to fine-tune the identifiable parameter subset of the controller. Indeed, the initial location found by Monte-Carlo simulations provided better results than using trial and error approach when identifying parameters of the fuzzy controller. The identifiable subset was reduced to 4 parameters from a total...
Qiu, Zhi-Jing; Lu, Yuan-Xue; Li, Chao-Qun; Dong, Yang; Smith, James F; Wang, Yin-Zheng
2015-07-03
Petrocosmea Oliver (Gesneriaceae) currently comprises 38 species with four non-nominate varieties, nearly all of which have been described solely from herbarium specimens. However, the dried specimens have obscured the full range of extremely diverse morphological variation that exists in the genus and has resulted in a poor subgeneric classification system that does not reflect the evolutionary history of this group. It is important to develop innovative methods to find new morphological traits and reexamine and reevaluate the traditionally used morphological data based on new hypothesis. In addition, Petrocosmea is a mid-sized genus but exhibits extreme diverse floral variants. This makes the genus of particular interest in addressing the question whether there are any key factors that is specifically associated with their evolution and diversification. Here we present the first phylogenetic analyses of the genus based on dense taxonomic sampling and multiple genes combined with a comprehensive morphological investigation. Maximum-parsimony, maximum likelihood and Bayesian analyses of molecular data from two nuclear DNA and six cpDNA regions support the monophyly of Petrocosmea and recover five major clades within the genus, which is strongly corroborated by the reconstruction of ancestral states for twelve new morphological characters directly observed from living material. Ancestral area reconstruction shows that its most common ancestor was likely located east and southeast of the Himalaya-Tibetan plateau. The origin of Petrocosmea from a potentially Raphiocarpus-like ancestor might have involved a series of morphological modifications from caulescent to acaulescent habit as well as from a tetrandrous flower with a long corolla-tube to a diandrous flower with a short corolla-tube, also evident in the vestigial caulescent habit and transitional floral form in clade A that is sister to the remainder of the genus. Among the five clades in Petrocosmea, the
Competencies assessment using fuzzy logic
Directory of Open Access Journals (Sweden)
Matej Jevšček
2016-06-01
Full Text Available Research Question: Competencies evaluation is complex. The question is how to evaluate a competency which was assessed with 360° feedback, in one result using fuzzy logic tools so the result represents an actual competency development in an individual. Purpose: The purpose and goal of the study is to determine a possible process of competency evaluation that would enable creating a single competency assessment using fuzzy logic methods. Method: The theoretical part examines the current state and terminology of competencies and fuzzy logic. The empirical part consists of a quantitative research study. Data from the survey questionnaire was used for model testing. Results: An example of an »Initiative« competency evaluation model is created and tested in the research study. Testing confirmed that evaluation using fuzzy logic is efficient. Organization: The study directly affects the development of the HR function in organizations. It enables an easier and more oriented competency evaluation. Society: The study enables easier orientation in competencies development that can improve the social order as well as social responsibility and the environment indirectly. Originality: The study presents a new competency evaluation model using fuzzy logic. Limitations/Future Research: The study is restricted to one competency and certain assessors. Further research could explore the model with several assessors of the same rank.
Fuzzy logic of Aristotelian forms
Energy Technology Data Exchange (ETDEWEB)
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.
Fuzzy Logic for Incidence Geometry.
Tserkovny, Alex
The paper presents a mathematical framework for approximate geometric reasoning with extended objects in the context of Geography, in which all entities and their relationships are described by human language. These entities could be labelled by commonly used names of landmarks, water areas, and so forth. Unlike single points that are given in Cartesian coordinates, these geographic entities are extended in space and often loosely defined, but people easily perform spatial reasoning with extended geographic objects "as if they were points." Unfortunately, up to date, geographic information systems (GIS) miss the capability of geometric reasoning with extended objects. The aim of the paper is to present a mathematical apparatus for approximate geometric reasoning with extended objects that is usable in GIS. In the paper we discuss the fuzzy logic (Aliev and Tserkovny, 2011) as a reasoning system for geometry of extended objects, as well as a basis for fuzzification of the axioms of incidence geometry. The same fuzzy logic was used for fuzzification of Euclid's first postulate. Fuzzy equivalence relation "extended lines sameness" is introduced. For its approximation we also utilize a fuzzy conditional inference, which is based on proposed fuzzy "degree of indiscernibility" and "discernibility measure" of extended points.
Fuzzy Logic for Incidence Geometry
2016-01-01
The paper presents a mathematical framework for approximate geometric reasoning with extended objects in the context of Geography, in which all entities and their relationships are described by human language. These entities could be labelled by commonly used names of landmarks, water areas, and so forth. Unlike single points that are given in Cartesian coordinates, these geographic entities are extended in space and often loosely defined, but people easily perform spatial reasoning with extended geographic objects “as if they were points.” Unfortunately, up to date, geographic information systems (GIS) miss the capability of geometric reasoning with extended objects. The aim of the paper is to present a mathematical apparatus for approximate geometric reasoning with extended objects that is usable in GIS. In the paper we discuss the fuzzy logic (Aliev and Tserkovny, 2011) as a reasoning system for geometry of extended objects, as well as a basis for fuzzification of the axioms of incidence geometry. The same fuzzy logic was used for fuzzification of Euclid's first postulate. Fuzzy equivalence relation “extended lines sameness” is introduced. For its approximation we also utilize a fuzzy conditional inference, which is based on proposed fuzzy “degree of indiscernibility” and “discernibility measure” of extended points. PMID:27689133
An Approach for Solving Goal Programming Problems using Interval Type-2 Fuzzy Goals
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Juan Carlos Figueroa-García
2015-08-01
Full Text Available This paper presents a proposal for solving goal problems involving multiple experts opinions and perceptions. In goal programming problems where no statistical data about their goals exist, the use of information coming from experts becomes the last reliable source. This way, we propose an approach to model this kind of goals using Interval Type-2 fuzzy sets, and a simple method for finding an optimal solution based on previous methods that have been proposed for classical fuzzy sets.
Ant Colony System for a Fuzzy Adjacent Multiple-Level Warehouse Layout Problem
Institute of Scientific and Technical Information of China (English)
ZHANG Qiang; YU Ying-zi; LAI K K
2006-01-01
A warehouse layout problem where the warehouse has more than one level and both the distance from the cell to the receive/exit bay and demand of item types are fuzzy variables is proposed. The problem is to find a layout with the minimum transportation cost subject to adjacency and other constraints. A fuzzy expected value model is given and an ant colony system is designed to solve the problem. Computational results indicate the efficiency and effectiveness of the method.
FINE-GRAINED DISTRIBUTED MULTIMEDIA SYNCHRONIZA- TION MODEL--ENHANCED FUZZY-TIMING PETRI NET
Institute of Scientific and Technical Information of China (English)
韩莹洁; 孙永强; 吴哲辉
2001-01-01
A fine-grained distributed multimedia synchronization model--Enhanced Fuzzy timing Petri Net was proposed which is good at modeling indeterminacy and fuzzy. To satisfy the need of maximum tolerable jitter, the sufficient conditions are given in intra-object synchronization. Method to find a proper granularity in inter-object synchronization is also given to satisfy skew. Exceptions are detected and corrected as early as possible using restricted blocking method.
Implementing fuzzy polynomial interpolation (FPI and fuzzy linear regression (LFR
Directory of Open Access Journals (Sweden)
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.
Need for fuzzy morphology: erosion as a fuzzy marker
Dougherty, Edward R.; Sinha, Divyendu
1992-03-01
The need for fuzzy mathematical morphology is explained in terms of the need for fuzzy erosion in certain types of applications, especially where erosion is serving as a marker, as with hit-or-miss shape recognition. Since erosion is defined by fitting, there at once arises a need for relating fuzzified set inclusion and mathematical morphology. The result is a very general class of Minkowski algebras based upon an axiomatic description of indicator functions that yield acceptable set-inclusion fuzzifications and a subclass of richer Minkowski algebras resulting from an analytic formulation for indicators that is constrained by the axioms.
Fuzzy evaluation method using fuzzy rule approach in multicriteria analysis
Directory of Open Access Journals (Sweden)
Othman Mahmod
2008-01-01
Full Text Available A multicriteria analysis in ranking the quality of teaching using fuzzy rule is proposed. The proposed method uses the application of fuzzy sets and approximate reasoning in deciding the ranking of the quality of teaching in several courses. The proposed method introduces normalizing data which dampen the extreme value that exists in the data. The use of the model is suitable in evaluating situations that involve subjectivity, vagueness and imprecise information. Experimental results are comparable and the method performs better in some domains. .
Reverse triple I method of fuzzy reasoning
Institute of Scientific and Technical Information of China (English)
宋士吉; 吴澄
2002-01-01
A theory of reverse triple I method with sustention degree is presented by using the implication operator R0 in every step of the fuzzy reasoning. Its computation formulas of supremum for fuzzy modus ponens and infimum for fuzzy modus tollens are given respectively. Moreover, through the generalization of this problem, the corresponding formulas of ?-reverse triple I method with sustention degree are also obtained. In addition, the theory of reverse triple I method with restriction degree is proposed as well by using the operator R0, and the computation formulas of infimum for fuzzy modus ponens and supremum for fuzzy modus tollens are shown.
Relationship between fuzzy controllers and PID controllers
Institute of Scientific and Technical Information of China (English)
李洪兴
1999-01-01
The internal relations between fuzzy controllers and PID controllers are revealed. First, it is pointed out that a fuzzy controller with one input and one output is just a piecewise P controller. Then it is proved that a fuzzy controller with two inputs and one output is just a piecewise PD (or I) controller with interaction between P and D (or PI). At last, the conclusion that a fuzzy controller with three inputs and one output is just a piecewise PID controller with interaction among P, I and D is given. Moreover, a kind of difference scheme of fuzzy controllers is designed.
On Intuitionistic Fuzzy Context-Free Languages
Directory of Open Access Journals (Sweden)
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.
Truth-value transmittal fuzzy reasoning interpolator
Institute of Scientific and Technical Information of China (English)
YAN Jianping; LEUNG Yee
2005-01-01
In this paper, we firstly associate fuzzy reasoning algorithm with the interpolation algorithm and discuss the limitation of defuzzification methods used commonly in the fuzzy reasoning algorithm. Secondly, we give a new fuzzy reasoning algorithm in case of single input, called the truth-value transmittal method, and discuss its properties. Finally, we analyze the rationality to adopy the truth-value transmittal method as the defuzzification method of full implication triple I method, and show that although CRI and triple I fuzzy reasoning method are different from fuzzy output set, they are uniform finally under the truth-value transmittal defuzzification method.
Generalized fuzzy ideals of near-rings
Institute of Scientific and Technical Information of China (English)
ZHAN Jian-ming; Dawaz B.
2009-01-01
The concept of ((∈),(∈)V (q))-fuzzy subnear-rings (ideals) of a near-ring is introduced and some of its related properties are investigated. In particular, the relationships among ordinary fuzzy subnear-rings (ideals), (∈,∈V q)-fuzzy subnear-rings (ideals) and ((∈),(∈)V (q))-fuzzy subnearrings (ideals) of near-rings are described. Finally, some characterization of [μ]t is given by means of (∈,∈V q)-fuzzy ideals.
A novel fuzzy sensor fusion algorithm
Institute of Scientific and Technical Information of China (English)
FU Hua; YANG Yi-kui; MA Ke; LIU Yu-jia
2011-01-01
A novel fusion algorithm was given based on fuzzy similarity and fuzzy integral theory.First,it calculated the fuzzy similarity among a certain sensor's measurement values and the multiple sensors' objective prediction values to determine the importance weight of each sensor and realize multi-sensor data fusion.Then according to the determined importance weight,an intelligent fusion system based on fuzzy integral theory was given,which can solve FEI-DEO and DEI-DEO fusion problems and realize the decision fusion.Simulation results were proved that fuzzy integral algorithm has enhanced the capability of handling the uncertain information and improved the intelligence degrees.
CONSIDERING NEIGHBORHOOD INFORMATION IN IMAGE FUZZY CLUSTERING
Institute of Scientific and Technical Information of China (English)
Huang Ning; Zhu Minhui; Zhang Shourong
2002-01-01
Fuzzy C-means clustering algorithm is a classical non-supervised classification method.For image classification, fuzzy C-means clustering algorithm makes decisions on a pixel-by-pixel basis and does not take advantage of spatial information, regardless of the pixels' correlation. In this letter, a novel fuzzy C-means clustering algorithm is introduced, which is based on image's neighborhood system. During classification procedure, the novel algorithm regards all pixels'fuzzy membership as a random field. The neighboring pixels' fuzzy membership information is used for the algorithm's iteration procedure. As a result, the algorithm gives a more smooth classification result and cuts down the computation time.
Fuzzy clustering of mechanisms
Indian Academy of Sciences (India)
Amitabha Ghosh; Dilip Kumar Pratihar; M V V Amarnath; Guenter Dittrich; Jorg Mueller
2012-10-01
During the course of development of Mechanical Engineering, a large number of mechanisms (that is, linkages to perform various types of tasks) have been conceived and developed. Quite a few atlases and catalogues were prepared by the designers of machines and mechanical systems. However, often it is felt that a clustering technique for handling the list of large number of mechanisms can be very useful,if it is developed based on a scientiﬁc principle. In this paper, it has been shown that the concept of fuzzy sets can be conveniently used for this purpose, if an adequate number of properly chosen attributes (also called characteristics) are identiﬁed. Using two clustering techniques, the mechanisms have been classiﬁed in the present work and in future, it may be extended to develop an expert system, which can automate type synthesis phase of mechanical design. To the best of the authors’ knowledge, this type of clustering of mechanisms has not been attempted before. Thus, this is the ﬁrst attempt to cluster the mechanisms based on some quantitative measures. It may help the engineers to carry out type synthesis of the mechanisms.
Metrics on Noncompact Fuzzy Number Space (E^)n
Institute of Scientific and Technical Information of China (English)
冯玉瑚
2004-01-01
The theory of metric spaces of fuzzy numbers has been established and found very convenient in many research fields on fuzzy analysis such as fuzzy integrals and differentials, fuzzy differential equations, fuzzy random variables and fuzzy stochastic processes etc.. But, a large part of this theory heavily depends on the condition that fuzzy number has to have compact support set and so fails to analyze and apply noncompact fuzzy numbers. The purpose of this paper is to introduce three classes of metrics on noncompact fuzzy number space and to discuss their basic properties, completeness and separability in detail.
Fuzzy Entropy： Axiomatic Definition and Neural Networks Model
Institute of Scientific and Technical Information of China (English)
QINGMing; CAOYue; HUANGTian-min
2004-01-01
The measure of uncertainty is adopted as a measure of information. The measures of fuzziness are known as fuzzy information measures. The measure of a quantity of fuzzy information gained from a fuzzy set or fuzzy system is known as fuzzy entropy. Fuzzy entropy has been focused and studied by many researchers in various fields. In this paper, firstly, the axiomatic definition of fuzzy entropy is discussed. Then, neural networks model of fuzzy entropy is proposed, based on the computing capability of neural networks. In the end, two examples are discussed to show the efficiency of the model.
Application of fuzzy logic to social choice theory
Mordeson, John N; Clark, Terry D
2015-01-01
Fuzzy social choice theory is useful for modeling the uncertainty and imprecision prevalent in social life yet it has been scarcely applied and studied in the social sciences. Filling this gap, Application of Fuzzy Logic to Social Choice Theory provides a comprehensive study of fuzzy social choice theory.The book explains the concept of a fuzzy maximal subset of a set of alternatives, fuzzy choice functions, the factorization of a fuzzy preference relation into the ""union"" (conorm) of a strict fuzzy relation and an indifference operator, fuzzy non-Arrowian results, fuzzy versions of Arrow's
Weakly continuous functions on mixed fuzzy topological spaces
Directory of Open Access Journals (Sweden)
Binod Chandra Tripathy
2014-04-01
Full Text Available The notions of continuity was generalized in the fuzzy setting by Chang (1968. Later on Azad (1981 introduced some weaker form of fuzzy continuity like fuzzy almost continuity, fuzzy semi-continuity and fuzzy weak continuity. These are natural generalization of the corresponding weaker forms of continuity in topological spaces. Recently Arya and Singal (2001a and b introduce another weaker form of fuzzy continuity, namely fuzzy subweakly continuity as a natural generalization of subweak continuity introduced by Rose (1984. In this paper we introduce fuzzy weak continuity in mixed fuzzy topological space.
Fuzzy Morphological Polynomial Image Representation
Directory of Open Access Journals (Sweden)
Chin-Pan Huang
2010-01-01
Full Text Available A novel signal representation using fuzzy mathematical morphology is developed. We take advantage of the optimum fuzzy fitting and the efficient implementation of morphological operators to extract geometric information from signals. The new representation provides results analogous to those given by the polynomial transform. Geometrical decomposition of a signal is achieved by windowing and applying sequentially fuzzy morphological opening with structuring functions. The resulting representation is made to resemble an orthogonal expansion by constraining the results of opening to equate adapted structuring functions. Properties of the geometric decomposition are considered and used to calculate the adaptation parameters. Our procedure provides an efficient and flexible representation which can be efficiently implemented in parallel. The application of the representation is illustrated in data compression and fractal dimension estimation temporal signals and images.
Cooperative Answering of Fuzzy Queries
Institute of Scientific and Technical Information of China (English)
Narjes Hachani; Mohamed Ali Ben Hassine; Hanène Chettaoui; Habib Ounelli
2009-01-01
The majority of existing information systems deals with crisp data through crisp database systems. Traditional Database Management Systems (DBMS) have not taken into account imprecision so one can say there is some sort of lack of flexibility. The reason is that queries retrieve only elements which precisely match to the given Boolean query. That is, an element belongs to the result if the query is true for this element; otherwise, no answers are returned to the user. The aim of this paper is to present a cooperative approach to handling empty answers of fuzzy conjunctive queries by referring to the Formal Concept Analysis (FCA) theory and fuzzy logic. We present an architecture which combines FCA and databases. The processing of fuzzy queries allows detecting the minimal reasons of empty answers. We also use concept lattice in order to provide the user with the nearest answers in the case of a query failure.
Identification Filtering with fuzzy estimations
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J.J Medel J
2012-10-01
Full Text Available A digital identification filter interacts with an output reference model signal known as a black-box output system. The identification technique commonly needs the transition and gain matrixes. Both estimation cases are based on mean square criterion obtaining of the minimum output error as the best estimation filtering. The evolution system represents adaptive properties that the identification mechanism includes considering the fuzzy logic strategies affecting in probability sense the evolution identification filter. The fuzzy estimation filter allows in two forms describing the transition and the gain matrixes applying actions that affect the identification structure. Basically, the adaptive criterion conforming the inference mechanisms set, the Knowledge and Rule bases, selecting the optimal coefficients in distribution form. This paper describes the fuzzy strategies applied to the Kalman filter transition function, and gain matrixes. The simulation results were developed using Matlab©.
Contra continuity and almost contra continuity in generalized fuzzy topological spaces
Bhattacharya, Baby; Chakraborty, Jayasree
2015-05-01
In this paper we introduce fuzzy contra continuity and almost contra continuity in generalized fuzzy topological space. Fuzzy almost contra continuity is weaker than fuzzy contra continuity in generalized fuzzy topological space. Then we investigate their characterizations and properties. We also established some equivalent relation on fuzzy contra continuity and fuzzy almost contra continuity in generalized fuzzy topological spaces.
Parallel Fuzzy P+Fuzzy I+Fuzzy D Controller:Design and Performance Evaluation
Institute of Scientific and Technical Information of China (English)
Vineet Kumar; A.P.Mittal
2010-01-01
In this paper,a parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative (FP+FI+FD) controller is proposed.It is derived from the conventional parallel proportional-integral-derivative (PID) controller.It preserves the linear structure of a conventional parallel PID controller,with analytical formulas.The final shape of the controller is a discrete-time fuzzy version of a conventional parallel PID controller.Computer simulations are performed to evaluate the performance of the FP+FI+FD controller for setpoint tracking and load-disturbance rejection for some complex processes,such as first-and second-order processes with delay,inverse response process with and without delay and higher order processes.Also,the performance of the proposed fuzzy controller is evaluated experimentally on highly nonlinear liquid-flow process with a hysteresis characteristic due to a pneumatic control valve.The simulation and real time control is done using National InstrumentTM hardware and software (LabVIEWTM).The response of the FP+FI+FD controller is compared with the conventional parallel PID controller,tuned with the Ziegler-Nichols (Z-H) and (A)str(o)mH(a)gglund (A-H) tuning technique.It is observed that the FP+FI+FD controller performed much better than the conventional PI/PID controller.Simulation and experimental results demonstrate the effectiveness of the proposed parallel FP+FI+FD controller.
Hypotheses testing for fuzzy robust regression parameters
Energy Technology Data Exchange (ETDEWEB)
Kula, Kamile Sanli [Ahi Evran University, Department of Mathematics, 40200 Kirsehir (Turkey)], E-mail: sanli2004@hotmail.com; Apaydin, Aysen [Ankara University, Department of Statistics, 06100 Ankara (Turkey)], E-mail: apaydin@science.ankara.edu.tr
2009-11-30
The classical least squares (LS) method is widely used in regression analysis because computing its estimate is easy and traditional. However, LS estimators are very sensitive to outliers and to other deviations from basic assumptions of normal theory [Huynh H. A comparison of four approaches to robust regression. Psychol Bull 1982;92:505-12; Stephenson D. 2000. Available from: (http://folk.uib.no/ngbnk/kurs/notes/node38.html); Xu R, Li C. Multidimensional least-squares fitting with a fuzzy model. Fuzzy Sets and Systems 2001;119:215-23.]. If there exists outliers in the data set, robust methods are preferred to estimate parameters values. We proposed a fuzzy robust regression method by using fuzzy numbers when x is crisp and Y is a triangular fuzzy number and in case of outliers in the data set, a weight matrix was defined by the membership function of the residuals. In the fuzzy robust regression, fuzzy sets and fuzzy regression analysis was used in ranking of residuals and in estimation of regression parameters, respectively [Sanli K, Apaydin A. Fuzzy robust regression analysis based on the ranking of fuzzy sets. Inernat. J. Uncertainty Fuzziness and Knowledge-Based Syst 2008;16:663-81.]. In this study, standard deviation estimations are obtained for the parameters by the defined weight matrix. Moreover, we propose another point of view in hypotheses testing for parameters.
Anaesthesia monitoring using fuzzy logic.
Baig, Mirza Mansoor; Gholamhosseini, Hamid; Kouzani, Abbas; Harrison, Michael J
2011-10-01
Humans have a limited ability to accurately and continuously analyse large amount of data. In recent times, there has been a rapid growth in patient monitoring and medical data analysis using smart monitoring systems. Fuzzy logic-based expert systems, which can mimic human thought processes in complex circumstances, have indicated potential to improve clinicians' performance and accurately execute repetitive tasks to which humans are ill-suited. The main goal of this study is to develop a clinically useful diagnostic alarm system based on fuzzy logic for detecting critical events during anaesthesia administration. The proposed diagnostic alarm system called fuzzy logic monitoring system (FLMS) is presented. New diagnostic rules and membership functions (MFs) are developed. In addition, fuzzy inference system (FIS), adaptive neuro fuzzy inference system (ANFIS), and clustering techniques are explored for developing the FLMS' diagnostic modules. The performance of FLMS which is based on fuzzy logic expert diagnostic systems is validated through a series of off-line tests. The training and testing data set are selected randomly from 30 sets of patients' data. The accuracy of diagnoses generated by the FLMS was validated by comparing the diagnostic information with the one provided by an anaesthetist for each patient. Kappa-analysis was used for measuring the level of agreement between the anaesthetist's and FLMS's diagnoses. When detecting hypovolaemia, a substantial level of agreement was observed between FLMS and the human expert (the anaesthetist) during surgical procedures. The diagnostic alarm system FLMS demonstrated that evidence-based expert diagnostic systems can diagnose hypovolaemia, with a substantial degree of accuracy, in anaesthetized patients and could be useful in delivering decision support to anaesthetists.
Fuzzy Stochastic Optimization Theory, Models and Applications
Wang, Shuming
2012-01-01
Covering in detail both theoretical and practical perspectives, this book is a self-contained and systematic depiction of current fuzzy stochastic optimization that deploys the fuzzy random variable as a core mathematical tool to model the integrated fuzzy random uncertainty. It proceeds in an orderly fashion from the requisite theoretical aspects of the fuzzy random variable to fuzzy stochastic optimization models and their real-life case studies. The volume reflects the fact that randomness and fuzziness (or vagueness) are two major sources of uncertainty in the real world, with significant implications in a number of settings. In industrial engineering, management and economics, the chances are high that decision makers will be confronted with information that is simultaneously probabilistically uncertain and fuzzily imprecise, and optimization in the form of a decision must be made in an environment that is doubly uncertain, characterized by a co-occurrence of randomness and fuzziness. This book begins...
Introduction to fuzzy logic using Matlab
Sivanandam, SN; Deepa, S N
2006-01-01
Fuzzy Logic, at present is a hot topic, among academicians as well various programmers. This book is provided to give a broad, in-depth overview of the field of Fuzzy Logic. The basic principles of Fuzzy Logic are discussed in detail with various solved examples. The different approaches and solutions to the problems given in the book are well balanced and pertinent to the Fuzzy Logic research projects. The applications of Fuzzy Logic are also dealt to make the readers understand the concept of Fuzzy Logic. The solutions to the problems are programmed using MATLAB 6.0 and the simulated results are given. The MATLAB Fuzzy Logic toolbox is provided for easy reference.
Fuzzy Clustering - Principles, Methods and Examples
DEFF Research Database (Denmark)
Kroszynski, Uri; Zhou, Jianjun
1998-01-01
One of the most remarkable advances in the field of identification and control of systems -in particular mechanical systems- whose behaviour can not be described by means of the usual mathematical models, has been achieved by the application of methods of fuzzy theory.In the framework of a study...... about identification of "black-box" properties by analysis of system input/output data sets, we have prepared an introductory note on the principles and the most popular data classification methods used in fuzzy modeling. This introductory note also includes some examples that illustrate the use...... of the methods. The examples were solved by hand and served as a test bench for exploration of the MATLAB capabilities included in the Fuzzy Control Toolbox. The fuzzy clustering methods described include Fuzzy c-means (FCM), Fuzzy c-lines (FCL) and Fuzzy c-elliptotypes (FCE)....
Adaptive fuzzy controllers based on variable universe
Institute of Scientific and Technical Information of China (English)
李洪兴
1999-01-01
Adaptive fuzzy controllers by means of variable universe are proposed based on interpolation forms of fuzzy control. First, monotonicity of control rules is defined, and it is proved that the monotonicity of interpolation functions of fuzzy control is equivalent to the monotonicity of control rules. This means that there is not any contradiction among the control rules under the condition for the control rules being monotonic. Then structure of the contraction-expansion factor is discussed. At last, three models of adaptive fuzzy control based on variable universe are given which are adaptive fuzzy control model with potential heredity, adaptive fuzzy control model with obvious heredity and adaptive fuzzy control model with successively obvious heredity.
Strong Limit Theorems for Arbitrary Fuzzy Stochastic Sequences
Institute of Scientific and Technical Information of China (English)
FEI Wei-yin
2008-01-01
Based on fuzzy random variables, the concept of fuzzy stochastic sequences is defined. Strong limit theorems for fuzzy stochastic sequences are established. Some known results in non-fuzzy stochastic sequences are extended. In order to prove results of this paper, the notion of fuzzy martingale difference sequences is also introduced.
Some Duality Results for Fuzzy Nonlinear Programming Problem
Sangeeta Jaiswal; Geetanjali Panda
2012-01-01
The concept of duality plays an important role in optimization theory. This paper discusses some relations between primal and dual nonlinear programming problems in fuzzy environment. Here, fuzzy feasible region for a general fuzzy nonlinear programming is formed and the concept of fuzzy feasible solution is defined. First order dual relation for fuzzy nonlinear programming problem is studied.
Generalized semi-extremally disconnectedness in double fuzzy topological spaces
Directory of Open Access Journals (Sweden)
Fatimah M. Mohammed
2017-03-01
Full Text Available In this paper we introduce the concepts of (r, s-generalized fuzzy semi-extremally disconnectedness spaces and study the effect of generalized double fuzzy semi-irresolute and generalized double fuzzy semiopen functions in this space. Moreover, we investigate some interesting relationship between generalized double fuzzy semiopen functions and (r, s-generalized fuzzy semi-extremally disconnectedness spaces.
Fuzzy simulation in concurrent engineering
Kraslawski, A.; Nystrom, L.
1992-01-01
Concurrent engineering is becoming a very important practice in manufacturing. A problem in concurrent engineering is the uncertainty associated with the values of the input variables and operating conditions. The problem discussed in this paper concerns the simulation of processes where the raw materials and the operational parameters possess fuzzy characteristics. The processing of fuzzy input information is performed by the vertex method and the commercial simulation packages POLYMATH and GEMS. The examples are presented to illustrate the usefulness of the method in the simulation of chemical engineering processes.
Ruspini, Enrique H.
1991-01-01
Summarized here are the results of recent research on the conceptual foundations of fuzzy logic. The focus is primarily on the principle characteristics of a model that quantifies resemblance between possible worlds by means of a similarity function that assigns a number between 0 and 1 to every pair of possible worlds. Introduction of such a function permits one to interpret the major constructs and methods of fuzzy logic: conditional and unconditional possibility and necessity distributions and the generalized modus ponens of Zadeh on the basis of related metric relationships between subsets of possible worlds.
Fuzzy sets and autonomous navigation
Lea, Robert N.
1987-01-01
The use of fuzzy sets in modeling the human expert for certain Space Shuttle navigation problems is discussed with particular reference to onboard and ground console data monitoring tasks traditionally performed by astronauts and engineers. Specific problems include determining the quality of sensor data and of the filter state. The results obtained in this study indicate that fuzzy sets can be successfully used in modeling human reaction to rules in decision-making processes. They can also be used within software systems where guidelines have traditionally been used to set strict tolerances.
Fuzzy simulation in concurrent engineering
Kraslawski, A.; Nystrom, L.
1992-01-01
Concurrent engineering is becoming a very important practice in manufacturing. A problem in concurrent engineering is the uncertainty associated with the values of the input variables and operating conditions. The problem discussed in this paper concerns the simulation of processes where the raw materials and the operational parameters possess fuzzy characteristics. The processing of fuzzy input information is performed by the vertex method and the commercial simulation packages POLYMATH and GEMS. The examples are presented to illustrate the usefulness of the method in the simulation of chemical engineering processes.
Fuzzy social choice models explaining the government formation process
C Casey, Peter; A Goodman, Carly; Pook, Kelly Nelson; N Mordeson, John; J Wierman, Mark; D Clark, Terry
2014-01-01
This book explores the extent to which fuzzy set logic can overcome some of the shortcomings of public choice theory, particularly its inability to provide adequate predictive power in empirical studies. Especially in the case of social preferences, public choice theory has failed to produce the set of alternatives from which collective choices are made. The book presents empirical findings achieved by the authors in their efforts to predict the outcome of government formation processes in European parliamentary and semi-presidential systems. Using data from the Comparative Manifesto Project (CMP), the authors propose a new approach that reinterprets error in the coding of CMP data as ambiguity in the actual political positions of parties on the policy dimensions being coded. The range of this error establishes parties’ fuzzy preferences. The set of possible outcomes in the process of government formation is then calculated on the basis of both the fuzzy Pareto set and the fuzzy maximal set, and the pre...
Fuzzy peak hour for urban road traffic network
Tian, Zhao; Jia, Li-Min; Dong, Hong-Hui; Zhang, Zun-Dong; Ye, Yang-Dong
2015-06-01
Traffic congestion is now nearly ubiquitous in many urban areas and frequently occurs during rush hour periods. Rush hour avoidance is an effective way to ease traffic congestion. It is significant to calculate the rush hour for alleviating traffic congestion. This paper provides a method to calculate the fuzzy peak hour of the urban traffic network considering the flow, speed and occupancy. The process of calculation is based on betweenness centrality of network theory, optimal separation method, time period weighting, probability-possibility transformations and trapezoidal approximations of fuzzy numbers. The fuzzy peak hour of the urban road traffic network (URTN) is a trapezoidal fuzzy number [m1, m2, m3, m4]. It helps us (i) to confirm a more detailed traffic condition at each moment, (ii) to distinguish the five traffic states of the traffic network in one day, (iii) to analyze the characteristic of appearance and disappearance processes of the each traffic state and (iv) to find out the time pattern of residents travel in one city.
Universal fuzzy models and universal fuzzy controllers for discrete-time nonlinear systems.
Gao, Qing; Feng, Gang; Dong, Daoyi; Liu, Lu
2015-05-01
This paper investigates the problems of universal fuzzy model and universal fuzzy controller for discrete-time nonaffine nonlinear systems (NNSs). It is shown that a kind of generalized T-S fuzzy model is the universal fuzzy model for discrete-time NNSs satisfying a sufficient condition. The results on universal fuzzy controllers are presented for two classes of discrete-time stabilizable NNSs. Constructive procedures are provided to construct the model reference fuzzy controllers. The simulation example of an inverted pendulum is presented to illustrate the effectiveness and advantages of the proposed method. These results significantly extend the approach for potential applications in solving complex engineering problems.
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
Fuzzy PID controller combines with closed-loop optimal fuzzy reasoning for pitch control system
Li, Yezi; Xiao, Cheng; Sun, Jinhao
2013-03-01
PID and fuzzy PID controller are applied into the pitch control system. PID control has simple principle and its parameters setting are rather easy. Fuzzy control need not to establish the mathematical of the control system and has strong robustness. The advantages of fuzzy PID control are simple, easy in setting parameters and strong robustness. Fuzzy PID controller combines with closed-loop optimal fuzzy reasoning (COFR), which can effectively improve the robustness, when the robustness is special requirement. MATLAB software is used for simulations, results display that fuzzy PID controller which combines with COFR has better performances than PID controller when errors exist.
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.
CALCULATION OF FUZZY RELIABILITYIN THE CASE OF RANDOM STRESSAND FUZZY FATIGUE STRENGTH
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
The fuzzy sets theory is introduced into the fatigue reliability analysis.The concepts of maximizing set and minimizing set are developed to decide the ordering value of each fuzzy number,and these values can be used to determine the order of the fuzzy numbers.On the basis of the works mentioned above,the membership function defining the fuzzy safety event can be calculated,and then the fuzzy reliability in the case of random stress and fuzzy fatigue strength is deduced.An example is given to illustrate the method.
A fuzzy control design case: The fuzzy PLL
Teodorescu, H. N.; Bogdan, I.
1992-01-01
The aim of this paper is to present a typical fuzzy control design case. The analyzed controlled systems are the phase-locked loops (PLL's)--classic systems realized in both analogic and digital technology. The crisp PLL devices are well known.
Fuzzy set applications in engineering optimization: Multilevel fuzzy optimization
Diaz, Alejandro R.
1989-01-01
A formulation for multilevel optimization with fuzzy objective functions is presented. With few exceptions, formulations for fuzzy optimization have dealt with a one-level problem in which the objective is the membership function of a fuzzy set formed by the fuzzy intersection of other sets. In the problem examined here, the goal set G is defined in a more general way, using an aggregation operator H that allows arbitrary combinations of set operations (union, intersection, addition) on the individual sets Gi. This is a straightforward extension of the standard form, but one that makes possible the modeling of interesting evaluation strategies. A second, more important departure from the standard form will be the construction of a multilevel problem analogous to the design decomposition problem in optimization. This arrangement facilitates the simulation of a system design process in which different components of the system are designed by different teams, and different levels of design detail become relevant at different time stages in the process: global design features early, local features later in the process.
Directory of Open Access Journals (Sweden)
Emer Bernal
2017-01-01
Full Text Available In this paper we are presenting a method using fuzzy logic for dynamic parameter adaptation in the imperialist competitive algorithm, which is usually known by its acronym ICA. The ICA algorithm was initially studied in its original form to find out how it works and what parameters have more effect upon its results. Based on this study, several designs of fuzzy systems for dynamic adjustment of the ICA parameters are proposed. The experiments were performed on the basis of solving complex optimization problems, particularly applied to benchmark mathematical functions. A comparison of the original imperialist competitive algorithm and our proposed fuzzy imperialist competitive algorithm was performed. In addition, the fuzzy ICA was compared with another metaheuristic using a statistical test to measure the advantage of the proposed fuzzy approach for dynamic parameter adaptation.
Institute of Scientific and Technical Information of China (English)
LI Hong-gang; PAN Xian-bing
2008-01-01
We introduced a new class of fuzzy set-valued variational inclusions with (H,η)-monotone mappings. Using the resolvent operator method in Hilbert spaces, we suggested a new proximal point algorithm for finding approximate solutions, which strongly converge to the exact solution of a fuzzy set-valued variational inclusion with (H,η)-monotone. The results improved and generalized the general quasi-variational inclusions with fuzzy set-valued mappings proposed by Jin and Tian [Jin MM, Perturbed proximal point algorithm for general quasi-variational inclusions with fuzzy set-valued mappings, OR Transactions, 2005, 9(3): 31-38, (In Chinese); Tian YX, Generalized nonlinear implicit quasi-variational inclusions with fuzzy mappings, Computers & Mathematics with Applications, 2001, 42: 101-108].
Design of Takagi-Sugeno fuzzy model based nonlinear sliding model controller
Institute of Scientific and Technical Information of China (English)
Xu Yong; Chen Zengqiang; Yuan Zhuzhi
2005-01-01
A design method is presented for Takagi-Sugeno (T-S) fuzzy model based nonlinear sliding model controller. First, the closed-loop fuzzy system is divided into a set of dominant local linear systems according to operating sub-regions. In each sub-region the fuzzy system consists of nominal linear system and a group of interacting systems. Then the controller composed two parts is designed. One part is designed to control the nominal system, the other is designed to control the interacting systems with sliding mode theory. The proposed controller can improve the robustness and guarantee tracking performance of the fuzzy system. Stability is guaranteed without finding a common positive definite matrix.
Modeling of type-2 fuzzy cubic B-spline surface for flood data problem in Malaysia
Bidin, Mohd Syafiq; Wahab, Abd. Fatah
2017-08-01
Malaysia possesses a low and sloping land areas which may cause flood. The flood phenomenon can be analyzed if the surface data of the study area can be modeled by geometric modeling. Type-2 fuzzy data for the flood data is defined using type-2 fuzzy set theory in order to solve the uncertainty of complex data. Then, cubic B-spline surface function is used to produce a smooth surface. Three main processes are carried out to find a solution to crisp type-2 fuzzy data which is fuzzification (α-cut operation), type-reduction and defuzzification. Upon conducting these processes, Type-2 Fuzzy Cubic B-Spline Surface Model is applied to visualize the surface data of the flood areas that are complex uncertainty.
Control of a Quadrotor Using a Smart Self-Tuning Fuzzy PID Controller
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Deepak Gautam
2013-11-01
Full Text Available This paper deals with the modelling, simulation-based controller design and path planning of a four rotor helicopter known as a quadrotor. All the drags, aerodynamic, coriolis and gyroscopic effect are neglected. A Newton-Euler formulation is used to derive the mathematical model. A smart self-tuning fuzzy PID controller based on an EKF algorithm is proposed for the attitude and position control of the quadrotor. The PID gains are tuned using a self-tuning fuzzy algorithm. The self-tuning of fuzzy parameters is achieved based on an EKF algorithm. A smart selection technique and exclusive tuning of active fuzzy parameters is proposed to reduce the computational time. Dijkstra’s algorithm is used for path planning in a closed and known environment filled with obstacles and/or boundaries. The Dijkstra algorithm helps avoid obstacle and find the shortest route from a given initial position to the final position.
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Deepa Joshi
2014-07-01
Full Text Available In this paper, an intuitionistic fuzzy TOPSIS method for multi-criteria decision making (MCDM problem to rank the alternatives is proposed. The proposed method is based on distance measure and intuitionistic fuzzy entropy. The proposed method also uses conversion theorem to convert fuzzy set to intuitionistic fuzzy set given by Jurio et al. (2010. A real case study is taken as an example to find the ranking of four organizations: Bajaj steel, H.D.F.C. bank, Tata steel and Infotech enterprises using real data. In order to compare the different rankingS, they are applied in a portfolio selection problem. Different portfolios are constructed and are analyzed for their risk and return. It is observed that if the portfolios are constructed using the ranking obtained with proposed method, the return is increased with slight increment in risk.
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Shadan Sadigh Behzadi
2011-12-01
Full Text Available In this paper, Adomian decomposition method (ADM and homotopy analysis method (HAM are proposed to solving the fuzzy nonlinear Volterra-Fredholm integral equation of the second kind$(FVFIE-2$. we convert a fuzzy nonlinear Volterra-Fredholm integral equation to a nonlinear system of Volterra-Fredholm integral equation in crisp case. we use ADM , HAM and find the approximate solution of this system and hence obtain an approximation for fuzzy solution of the nonlinear fuzzy Volterra-Fredholm integral equation. Also, the existence and uniqueness of the solution and convergence of the proposed methods are proved. Examples is given and the results reveal that homotopy analysis method is very effective and simple compared with the Adomian decomposition method.
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Nguyen Kim Quoc
2015-08-01
Full Text Available The bottleneck control by active queue management mechanisms at network nodes is essential. In recent years, some researchers have used fuzzy argument to improve the active queue management mechanisms to enhance the network performance. However, the projects using the fuzzy controller depend heavily on professionals and their parameters cannot be updated according to changes in the network, so the effectiveness of this mechanism is not high. Therefore, we propose a model combining the fuzzy controller with neural network (FNN to overcome the limitations above. Results of the training of the neural networks will find the optimal parameters for the adaptive fuzzy controller well to changes of the network. This improves the operational efficiency of the active queue management mechanisms at network nodes.
A technical study and analysis on fuzzy similarity based models for text classification
Puri, Shalini; 10.5121/ijdkp.2012.2201
2012-01-01
In this new and current era of technology, advancements and techniques, efficient and effective text document classification is becoming a challenging and highly required area to capably categorize text documents into mutually exclusive categories. Fuzzy similarity provides a way to find the similarity of features among various documents. In this paper, a technical review on various fuzzy similarity based models is given. These models are discussed and compared to frame out their use and necessity. A tour of different methodologies is provided which is based upon fuzzy similarity related concerns. It shows that how text and web documents are categorized efficiently into different categories. Various experimental results of these models are also discussed. The technical comparisons among each model's parameters are shown in the form of a 3-D chart. Such study and technical review provide a strong base of research work done on fuzzy similarity based text document categorization.
Institute of Scientific and Technical Information of China (English)
PAN Feng; FU Qiang; LIANG Chuan; LIU Dong
2003-01-01
Owing to overcoming the characteristics that there are many economic and technical indexes which are fuzzy and incompatibility to each other in evaluating investment project,a new method is proposed.The method is based on the matter-element analysis and combined with the concepts of fuzzy mathematics,which is called the method of fuzzy matter-element analysis.It constructs the compound fuzzy matter element with the investment projects,evaluation factors and their fuzzy value.Through establishing the best subjection degree (fuzzy value),complex fuzzy matter element of relational coefficient and weight aggregation of fuzzy matter-element model,the writer achieves on optimum order of the investment projects according to the calculated relational degree and finds the best project.In this paper,the calculation of weight adopts the analytical hierarchy process method(AHP).Through the actual example,it shows that the model is simple and its calculation is reliable.It is very significant for the engineering evaluated bid and investment decision.
Chaney, A.; Stern, A.
2017-02-01
Four-dimensional manifolds with changing signature are obtained by taking the large N limit of fuzzy C P2 solutions to a Lorentzian matrix model. The regions of Lorentzian signature give toy models of closed universes which exhibit cosmological singularities. These singularities are resolved at finite N , as the underlying C P2 solutions are expressed in terms of finite matrix elements.
Rankings from Fuzzy Pairwise Comparisons
Broek, van den Pim; Noppen, Joost; Mohammadian, M.
2006-01-01
We propose a new method for deriving rankings from fuzzy pairwise comparisons. It is based on the observation that quantification of the uncertainty of the pairwise comparisons should be used to obtain a better crisp ranking, instead of a fuzzified version of the ranking obtained from crisp pairwise
Fuzzy logic controllers on chip
Acosta, Nelson; Simonelli, Daniel Horacio
2002-01-01
This paper analyzes a fuzzy logic (FL) oriented instruction set (micro)controller and their implementations on FIPSOC1. VHDL code is synthesized using a small portion of FIPSOC FPGA2. This circuits are used from the mP8051 FIPSOC built-in microcontroller to provide efficient arithmetic operations such as multipliers, dividers, minimums and maximums.
Fuzzy audit risk modeling algorithm
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Zohreh Hajihaa
2011-07-01
Full Text Available Fuzzy logic has created suitable mathematics for making decisions in uncertain environments including professional judgments. One of the situations is to assess auditee risks. During recent years, risk based audit (RBA has been regarded as one of the main tools to fight against fraud. The main issue in RBA is to determine the overall audit risk an auditor accepts, which impact the efficiency of an audit. The primary objective of this research is to redesign the audit risk model (ARM proposed by auditing standards. The proposed model of this paper uses fuzzy inference systems (FIS based on the judgments of audit experts. The implementation of proposed fuzzy technique uses triangular fuzzy numbers to express the inputs and Mamdani method along with center of gravity are incorporated for defuzzification. The proposed model uses three FISs for audit, inherent and control risks, and there are five levels of linguistic variables for outputs. FISs include 25, 25 and 81 rules of if-then respectively and officials of Iranian audit experts confirm all the rules.
Fuzzy Evidence in Identification, Forecasting and Diagnosis
Rotshtein, Alexander P
2012-01-01
The purpose of this book is to present a methodology for designing and tuning fuzzy expert systems in order to identify nonlinear objects; that is, to build input-output models using expert and experimental information. The results of these identifications are used for direct and inverse fuzzy evidence in forecasting and diagnosis problem solving. The book is organised as follows: Chapter 1 presents the basic knowledge about fuzzy sets, genetic algorithms and neural nets necessary for a clear understanding of the rest of this book. Chapter 2 analyzes direct fuzzy inference based on fuzzy if-then rules. Chapter 3 is devoted to the tuning of fuzzy rules for direct inference using genetic algorithms and neural nets. Chapter 4 presents models and algorithms for extracting fuzzy rules from experimental data. Chapter 5 describes a method for solving fuzzy logic equations necessary for the inverse fuzzy inference in diagnostic systems. Chapters 6 and 7 are devoted to inverse fuzzy inference based on fu...
Time dependence of entanglement entropy on the fuzzy sphere
Sabella-Garnier, Philippe
2017-08-01
We numerically study the behaviour of entanglement entropy for a free scalar field on the noncommutative ("fuzzy") sphere after a mass quench. It is known that the entanglement entropy before a quench violates the usual area law due to the non-local nature of the theory. By comparing our results to the ordinary sphere, we find results that, despite this non-locality, are compatible with entanglement being spread by ballistic propagation of entangled quasi-particles at a speed no greater than the speed of light. However, we also find that, when the pre-quench mass is much larger than the inverse of the short-distance cutoff of the fuzzy sphere (a regime with no commutative analogue), the entanglement entropy spreads faster than allowed by a local model.
Learning fuzzy logic control system
Lung, Leung Kam
1994-01-01
The performance of the Learning Fuzzy Logic Control System (LFLCS), developed in this thesis, has been evaluated. The Learning Fuzzy Logic Controller (LFLC) learns to control the motor by learning the set of teaching values that are generated by a classical PI controller. It is assumed that the classical PI controller is tuned to minimize the error of a position control system of the D.C. motor. The Learning Fuzzy Logic Controller developed in this thesis is a multi-input single-output network. Training of the Learning Fuzzy Logic Controller is implemented off-line. Upon completion of the training process (using Supervised Learning, and Unsupervised Learning), the LFLC replaces the classical PI controller. In this thesis, a closed loop position control system of a D.C. motor using the LFLC is implemented. The primary focus is on the learning capabilities of the Learning Fuzzy Logic Controller. The learning includes symbolic representation of the Input Linguistic Nodes set and Output Linguistic Notes set. In addition, we investigate the knowledge-based representation for the network. As part of the design process, we implement a digital computer simulation of the LFLCS. The computer simulation program is written in 'C' computer language, and it is implemented in DOS platform. The LFLCS, designed in this thesis, has been developed on a IBM compatible 486-DX2 66 computer. First, the performance of the Learning Fuzzy Logic Controller is evaluated by comparing the angular shaft position of the D.C. motor controlled by a conventional PI controller and that controlled by the LFLC. Second, the symbolic representation of the LFLC and the knowledge-based representation for the network are investigated by observing the parameters of the Fuzzy Logic membership functions and the links at each layer of the LFLC. While there are some limitations of application with this approach, the result of the simulation shows that the LFLC is able to control the angular shaft position of the
Rule based fuzzy logic approach for classification of fibromyalgia syndrome.
Arslan, Evren; Yildiz, Sedat; Albayrak, Yalcin; Koklukaya, Etem
2016-06-01
Fibromyalgia syndrome (FMS) is a chronic muscle and skeletal system disease observed generally in women, manifesting itself with a widespread pain and impairing the individual's quality of life. FMS diagnosis is made based on the American College of Rheumatology (ACR) criteria. However, recently the employability and sufficiency of ACR criteria are under debate. In this context, several evaluation methods, including clinical evaluation methods were proposed by researchers. Accordingly, ACR had to update their criteria announced back in 1990, 2010 and 2011. Proposed rule based fuzzy logic method aims to evaluate FMS at a different angle as well. This method contains a rule base derived from the 1990 ACR criteria and the individual experiences of specialists. The study was conducted using the data collected from 60 inpatient and 30 healthy volunteers. Several tests and physical examination were administered to the participants. The fuzzy logic rule base was structured using the parameters of tender point count, chronic widespread pain period, pain severity, fatigue severity and sleep disturbance level, which were deemed important in FMS diagnosis. It has been observed that generally fuzzy predictor was 95.56 % consistent with at least of the specialists, who are not a creator of the fuzzy rule base. Thus, in diagnosis classification where the severity of FMS was classified as well, consistent findings were obtained from the comparison of interpretations and experiences of specialists and the fuzzy logic approach. The study proposes a rule base, which could eliminate the shortcomings of 1990 ACR criteria during the FMS evaluation process. Furthermore, the proposed method presents a classification on the severity of the disease, which was not available with the ACR criteria. The study was not limited to only disease classification but at the same time the probability of occurrence and severity was classified. In addition, those who were not suffering from FMS were
Fuzzy Prime Ideals in Fuzzy Semigroups%Fuzzy半群中的Fuzzy素理想
Institute of Scientific and Technical Information of China (English)
谭宜家
2001-01-01
探讨Fuzzy半群中Fuzzy素理想、Fuzzy完全素理想与Fuzzy理想的根的一些代数性质，证明Fuzzy半群中每一个Fuzzy理想是Fuzzy完全半素理想当且仅当它可表为一族Fuzzy完全素理想之交。%In this paper,we obtain some algebraic properties of fuzzy prime ideals,fuzzy completely prime ideals and radicals of fuzzy ideals in fuzzy semigroups,and show that a fuzzy ideal in a fuzzy simigroup is a fuzzy completely semiprime ideal if and only if it is an intersectin of a family of fuzzy completely prime ideals.
An Enhanced Fuzzy Multi Criteria Decision Making Model with A proposed Polygon Fuzzy Number
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Samah Bekheet
2014-06-01
Full Text Available Decisions in real world applications are often made under the presence of conflicting, uncertain, incomplete and imprecise information. Fuzzy multi Criteria Decision making (FMCDM approach provides a powerful approach for drawing rational decisions under uncertainty given in the form of linguistic values. Linguistic values are usually represented as fuzzy numbers. Most of researchers adopt either triangle or trapezoidal fuzzy numbers. Since triangle, intervals, and even singleton are special cases of Trapezoidal fuzzy numbers, so, for most researchers Trapezoidal fuzzy numbers are considered Generalized fuzzy numbers (GFN. In this paper, we introduce polygon fuzzy number (PFN as the actual form of GFN. The proposed form of PFN provides higher flexibility to decision makers to express their own linguistic rather than other form of fuzzy numbers. The given illustrative example ensures such ability for better handling of the FMCDM problems.
Fuzzy Control Strategies in Human Operator and Sport Modeling
Ivancevic, Tijana T; Markovic, Sasa
2009-01-01
The motivation behind mathematically modeling the human operator is to help explain the response characteristics of the complex dynamical system including the human manual controller. In this paper, we present two different fuzzy logic strategies for human operator and sport modeling: fixed fuzzy-logic inference control and adaptive fuzzy-logic control, including neuro-fuzzy-fractal control. As an application of the presented fuzzy strategies, we present a fuzzy-control based tennis simulator.
FUZZY STABILITY ANALYSIS OF MODE COUPLING CHATTER ON CUTTING PROCESS
Institute of Scientific and Technical Information of China (English)
1998-01-01
The influence of fuzzy uncertainty factors is considered on the analysis of chatter occurring during machine tool cutting process. Using fuzzy mathematics analysis methods, a detailed discussion over fuzzy stability analysis problems is presented related to the mode coupling chatter with respect to intrinsic structure fuzzy factors, and the possibility distribution of the fuzzy stability cutting range and the confidence level expressions of the fuzzy stability cutting width are given.
Compound fuzzy model for thermal performance of refrigeration compressors
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
The fuzzy method is introduced to the calculation of thermal performance of refrigeration compressors. A compound model combining classical thermodynamic theory and fuzzy theory is presented and compared with a simple fuzzy model without classical thermodynamic fundamentals. Case study of refrigeration compressors shows that the compound fuzzy model and the simple fuzzy model are both more efficient than the classical thermodynamic method. However, the compound fuzzy model is of better precision and adaptability.
Behavior of impulsive fuzzy cellular neural networks with distributed delays
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Kelin Li
2007-04-01
Full Text Available In this paper, we investigate a generalized model of fuzzy cellular neural networks with distributed delays and impulses. By employing the theory of topological degree, M-matrix and Lypunov functional, we find sufficient conditions for the existence, uniqueness and global exponential stability of both the equilibrium point and the periodic solution. Two examples are given to illustrate the results obtained here.
Optimal fuzzy PID control tuned with genetic algorithms
Santos, Carlos Miguel Almeida
2013-01-01
Fuzzy logic controllers (FLC) are intelligent systems, based on heuristic knowledge, that have been largely applied in numerous areas of everyday life. They can be used to describe a linear or nonlinear system and are suitable when a real system is not known or too difficult to find their model. FLC provide a formal methodology for representing, manipulating and implementing a human heuristic knowledge on how to control a system. These controllers can be seen as artificial decision makers tha...
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Norazrizal Aswad Abdul Rahman
2015-07-01
Full Text Available In this paper, we study the classical Sumudu transform in fuzzy environment, referred to as the fuzzy Sumudu transform (FST. We also propose some results on the properties of the FST, such as linearity, preserving, fuzzy derivative, shifting and convolution theorem. In order to show the capability of the FST, we provide a detailed procedure to solve fuzzy differential equations (FDEs. A numerical example is provided to illustrate the usage of the FST.
A note on the solution of fuzzy transportation problem using fuzzy linear system
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P. Senthilkumar
2013-08-01
Full Text Available In this paper, we discuss the solution of a fuzzy transportation problem, with fuzzy quantities. The problem is solved in two stages. In the first stage, the fuzzy transportation problem is reduced to crisp system by using the lower and upper bounds of fuzzy quantities. In the second stage, the crisp transportation problems are solved by usual simplex method. The procedure is illustrated with numerical examples.
Taste Identification of Tea Through a Fuzzy Neural Network Based on Fuzzy C-means Clustering
Institute of Scientific and Technical Information of China (English)
ZHENG Yan; ZHOU Chun-guang
2003-01-01
In this paper, we present a fuzzy neural network model based on Fuzzy C-Means (FCM) clustering algorithm to realize the taste identification of tea. The proposed method can acquire the fuzzy subset and its membership function in an automatic way with the aid of FCM clustering algorithm. Moreover, we improve the fuzzy weighted inference approach. The proposed model is illustrated with the simulation of taste identification of tea.
Huang, Jeng-Sheng; Chao, Paul C.-P.; Fung, Rong-Fong; Lai, Cheng-Liang
2003-06-01
This study is dedicated to design effective control schemes to suppress transverse vibration of an axially moving string system by adjusting the axial tension of the string. To this end, a continuous model in the form of partial differential equations is first established to describe the system dynamics. Using an energy-like system functional as a Lyapunov function, a sliding-mode controller (SMC) is designed to be applied when the level of vibration is not small. Due to non-analyticity of the SMC control effort generated as vibration level becoming small, two intelligent control schemes are proposed to complete the task — fuzzy sliding-mode control (FSMC) and fuzzy neural network control (FNNC). Both control approaches are based on a common structure of fuzzy control, taking switching function and its derivative as inputs and tension variation as output to reduce the transverse vibration of the string. In the framework of FSMC, genetic algorithm (GA) is utilized to search for the optimal scalings for the inputs; in addition, the technique of regionwise linear fuzzy logic control (RLFLC) is employed to simplify the computation procedure of the fuzzy reasoning. On the other hand, FNNC is proposed for conducting on-line tuning of control parameters to overcome model uncertainty. Numerical simulations are conducted to verify the effectiveness of controllers. Satisfactory stability and vibration suppression are attained for all controllers with the findings that the FSMC assisted by GA holds the advantage of fast convergence with a precise model while the FNNC is robust to model uncertainty and environmental disturbance although a relatively slower convergence could be present.
Fuzzy-TOPSIS Method with Multi-goal
Institute of Scientific and Technical Information of China (English)
PANG Jin-hui; ZHANG Qiang
2009-01-01
To develop the technique for order preference by similarity to an ideal solution,namely,TOPSIS method with multi-goal in fuzzy decision environment.Firstly,a new approach to constructing fuzzy decision matrix by Choquet integral was proposed in muhi-goal decision system.Secondly,the concepts of fuzzy positive-ideal solution and fuzzy negative-ideal solution related to the fuzzy decision matrix were given.Finally,the credibility measure was adopted to calculate the distances to fuzzy positive-ideal solution and fuzzy negative-ideal solution.The presented fuzzy-TOPSIS method embodies well both the predetermined preferences and the weights of goals.
A fuzzy expert system for diabetes decision support application.
Lee, Chang-Shing; Wang, Mei-Hui
2011-02-01
An increasing number of decision support systems based on domain knowledge are adopted to diagnose medical conditions such as diabetes and heart disease. It is widely pointed that the classical ontologies cannot sufficiently handle imprecise and vague knowledge for some real world applications, but fuzzy ontology can effectively resolve data and knowledge problems with uncertainty. This paper presents a novel fuzzy expert system for diabetes decision support application. A five-layer fuzzy ontology, including a fuzzy knowledge layer, fuzzy group relation layer, fuzzy group domain layer, fuzzy personal relation layer, and fuzzy personal domain layer, is developed in the fuzzy expert system to describe knowledge with uncertainty. By applying the novel fuzzy ontology to the diabetes domain, the structure of the fuzzy diabetes ontology (FDO) is defined to model the diabetes knowledge. Additionally, a semantic decision support agent (SDSA), including a knowledge construction mechanism, fuzzy ontology generating mechanism, and semantic fuzzy decision making mechanism, is also developed. The knowledge construction mechanism constructs the fuzzy concepts and relations based on the structure of the FDO. The instances of the FDO are generated by the fuzzy ontology generating mechanism. Finally, based on the FDO and the fuzzy ontology, the semantic fuzzy decision making mechanism simulates the semantic description of medical staff for diabetes-related application. Importantly, the proposed fuzzy expert system can work effectively for diabetes decision support application.
Combinational reasoning of quantitative fuzzy topological relations for simple fuzzy regions.
Liu, Bo; Li, Dajun; Xia, Yuanping; Ruan, Jian; Xu, Lili; Wu, Huanyi
2015-01-01
In recent years, formalization and reasoning of topological relations have become a hot topic as a means to generate knowledge about the relations between spatial objects at the conceptual and geometrical levels. These mechanisms have been widely used in spatial data query, spatial data mining, evaluation of equivalence and similarity in a spatial scene, as well as for consistency assessment of the topological relations of multi-resolution spatial databases. The concept of computational fuzzy topological space is applied to simple fuzzy regions to efficiently and more accurately solve fuzzy topological relations. Thus, extending the existing research and improving upon the previous work, this paper presents a new method to describe fuzzy topological relations between simple spatial regions in Geographic Information Sciences (GIS) and Artificial Intelligence (AI). Firstly, we propose a new definition for simple fuzzy line segments and simple fuzzy regions based on the computational fuzzy topology. And then, based on the new definitions, we also propose a new combinational reasoning method to compute the topological relations between simple fuzzy regions, moreover, this study has discovered that there are (1) 23 different topological relations between a simple crisp region and a simple fuzzy region; (2) 152 different topological relations between two simple fuzzy regions. In the end, we have discussed some examples to demonstrate the validity of the new method, through comparisons with existing fuzzy models, we showed that the proposed method can compute more than the existing models, as it is more expressive than the existing fuzzy models.