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Fuzzy Information Processing Society (NAFIPS), 2012 Annual Meeting of the North American

Date 6-8 Aug. 2012

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Displaying Results 1 - 25 of 112
  • 2012 Annual Meeting of the North American Fuzzy Information Processing Society [Front cover]

    Publication Year: 2012 , Page(s): c1
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  • 2012 Annual Meeting of the North American Fuzzy Information Processing Society [Copyright notice]

    Publication Year: 2012 , Page(s): 1
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  • Special thank you to our sponsor

    Publication Year: 2012 , Page(s): 1
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  • Papers

    Publication Year: 2012 , Page(s): 1 - 8
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  • Administration and committees

    Publication Year: 2012 , Page(s): 1 - 3
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  • Message from NAFIPS general chairs

    Publication Year: 2012 , Page(s): 1
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  • Message from NAFIPS 2012 program chairs

    Publication Year: 2012 , Page(s): 1 - 2
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  • [Abstracts for six special sessions]

    Publication Year: 2012 , Page(s): 1 - 3
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    Summary form only given. Provides an abstract for each of the six tutorial presentations and a brief professional biography of each presenter. View full abstract»

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  • Author

    Publication Year: 2012 , Page(s): 1 - 8
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  • Fuzzy calculus via extension of the derivative and integral operators and fuzzy differential equations

    Publication Year: 2012 , Page(s): 1 - 5
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (632 KB) |  | HTML iconHTML  

    We define the concepts of derivative and integral of fuzzy functions using the extension principle of Zadeh on the corresponding classical operators. Here are some of its properties and we articulate a version of the Fundamental Theorem of Calculus for fuzzy functions and ensure the existence of a solution of fuzzy initial value problem under certain conditions. A method of solving fuzzy initial value problem is presented and an application of a decay model is solved and interpreted within a fuzzy context. View full abstract»

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  • Some comments on excluded middle and contradiction laws as limit values in fuzzy logic

    Publication Year: 2012 , Page(s): 1 - 5
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (751 KB) |  | HTML iconHTML  

    This paper presents some results about the laws of excluded middle and contradiction of classical logic in fuzzy logic because in the latter, in general, are not satisfied. The aim is to present conditions under which these two laws as limit values are met with the correct choice of the fuzzy logical connectors. View full abstract»

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  • Contributions of fuzzy logic and bounded rationality to cognitive machines in organizations

    Publication Year: 2012 , Page(s): 1 - 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (114 KB) |  | HTML iconHTML  

    This research is about cognitive machines in organizations which has been influenced by the scientific works of Herbert A. Simon on Administrative Behavior and Bounded Rationality, and Lotfi A. Zadeh on Fuzzy Systems and Computational Theory of Perceptions, developed in the period between the middle and the end of the 20th century. It contributes with the unification of theories and results of these two brilliant researchers, and it suggests that both players are worthy of Nobel Prize in Economics 1978 instead the first one alone. View full abstract»

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  • A technique for deriving analytical structure of a general class of interval type-2 TS fuzzy controllers

    Publication Year: 2012 , Page(s): 1 - 6
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1625 KB) |  | HTML iconHTML  

    Type-2 (T2) fuzzy controllers have been widely treated as black boxes in that their input-output mathematical relationships (i.e., analytical structures) are unknown. In contrast, any conventional controller's analytical structure is always known. Revealing the analytical structure is important as it will lay a solid foundation for better understanding, more insightful analysis, and more effective design of T2 fuzzy control systems. In this paper, we developed a technique for deriving the analytical structure of a general class of interval T2 TS fuzzy controllers. View full abstract»

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  • Crisp and fuzzy cluster validity: Generalized intra-inter silhouette index

    Publication Year: 2012 , Page(s): 1 - 6
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1038 KB) |  | HTML iconHTML  

    Based on a framework, that casts the problem of clustering a set of data points as a problem of clustering the associated pairwise distances, this study generalizes the silhouette measure to fuzzy partitions, in turn, proposing an outstanding tool to the validation of crisp and fuzzy clustering results. View full abstract»

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  • A fuzzy linear regression model for interval type-2 fuzzy sets

    Publication Year: 2012 , Page(s): 1 - 5
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1502 KB) |  | HTML iconHTML  

    This paper presents a regression model for interval type-2 fuzzy sets based on the least squares estimation technique. Unknown coefficients are assumed to be triangular fuzzy numbers. The basic idea is to determine aggregation intervals for type-1 fuzzy sets, membership functions of whose are low membership function and upper membership function of interval type-2 fuzzy set. These aggregation intervals were called weighted intervals. Low and upper membership functions of input and output interval type-2 fuzzy sets for developed regression models are considered as piecewise linear functions. View full abstract»

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  • A hybrid approach to develop an interval type-2 fuzzy logic system

    Publication Year: 2012 , Page(s): 1 - 5
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (667 KB) |  | HTML iconHTML  

    After more than three decades since the introduction of linguistic variables and their application to approximate reasoning by Zadeh [1], the ability of fuzzy logic systems (FLSs) for modeling real world applications is not a secret to anyone. Currently there are two basic approaches to determine fuzzy model of a system in the literature which are, 1-direct approach, and 2-indirect approach. In direct approach rules are generated via knowledge extraction from experienced experts, while in indirect approach historical data of a system determine the governing rules. The first method is involved with extracting knowledge from experts who in some cases are not available, or they avoid providing us with useful information. In the second method which is dealt with historical data, clustering is the proper tool for structure identification of a system under investigation. Determining the structure of a system relying only on past data also has its own problems. In this paper we try to develop a hybrid approach in interval type-2 fuzzy system modeling (IT2FSM) which benefits from the advantages of both direct and indirect methods. At first stage the modified approach to interval type-2 fuzzy c-mean clustering (IT2FCM) is applied to identify the structure of system and in the second stage the hybrid of direct and indirect approach in system modeling is used to complete the rule base of a model. View full abstract»

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  • A fuzzy multi-criteria approach for evaluating biofuels feedstocks

    Publication Year: 2012 , Page(s): 1 - 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (717 KB) |  | HTML iconHTML  

    In this paper, we develop a fuzzy holistic approach evaluating the conventional and advanced biofuels feedstocks in meeting multiple economic, environmental and social criteria of the biofuels policies and capturing the uncertainties of policy evaluation and design processes. We use a multi-criteria approach PROMETHEE (Preference Ranking Organization METHod for Enrichment Evaluations) and fuzzy set theory to show how missing information, fuzziness, and ambiguity in decision making processes can be internalized in the process of creating a sustainable biofuels policy. View full abstract»

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  • Type-2 fuzzy rule base system with parameter optimization for forecasting of tardiness

    Publication Year: 2012 , Page(s): 1 - 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (821 KB) |  | HTML iconHTML  

    This paper addresses an interval type-2 fuzzy hybrid rule-based system in order to predict the amount of tardiness where tardiness variables are represented by interval type-2 membership functions. For this purpose, interval type-2 fuzzy disjunctive normal forms and fuzzy conjunctive normal forms are utilized in the inference engine. The main contribution of this paper is to present the interval type-2 fuzzy hybrid rule-based system, which is the combination of Mamdani and Sugeno methods. In order to forecast the future amount of tardiness for continuous casting operation in a steel company in Canada, an autoregressive moving average model is used in the consequents of the rules. Parameters of the system are optimized by applying Adaptive-Network-Based Fuzzy Inference System (ANFIS). This method is compared with interval type-2 fuzzy Takagi-Sugeno-Kang method in MATLAB, multiple-regression, and two other Type-1 fuzzy methods in literature. The results of computing the mean square error of these methods show that our proposed method has less error and high accuracy in comparison with other methods. View full abstract»

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  • Powers of indistinguishability operators

    Publication Year: 2012 , Page(s): 1 - 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (699 KB) |  | HTML iconHTML  

    The application of a t-norm more than one time to the same object can be seen as the modelization of a semantic reinforcement of it. From a mathematical viewpoint, this operation can be seen as powers. Depending on the properties the t-norm fulfills several interesting properties emerge. This work will study what is the effect of the application of powers to indistinguishability operators, sets of extensionals, upper and lower approximations. It will be proved that there is a tight relation between the powers of an indistinguishability and their respective sets of extensionals, upper and lower approximations, and how this can be interpreted from a semantic point of view. View full abstract»

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  • Coordinated control of circulating fluidized bed boiler based on the fuzzy PID control

    Publication Year: 2012 , Page(s): 1 - 7
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1167 KB) |  | HTML iconHTML  

    In this paper, a new sequential relay feedback method for the tuning of decentralized PID controllers in intelligent coordinated control systems (CCS). Based on the specified phase and gain margin, the parameters of the fuzzy self-adjusting PID controllers and the fuzzy gain scheduling PID controllers are determined. The scheme is implemented through the function code in typical DCSs (EDPF-NT, XDPS, etc). It has been used for control of the 300MW circulating fluidized bed (CFB) units. The industrial applications show that the scheme achieves better performance in the specific range of load variations. View full abstract»

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  • Conjectures in De Morgan algebras

    Publication Year: 2012 , Page(s): 1 - 6
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (544 KB) |  | HTML iconHTML  

    This paper is devoted to cover a lack existing since the first paper of one of the authors on `conjectures' in the setting of ortholattices was published in 1999: the case with De Morgan algebras, and fuzzy sets once endowed with the algebra given by the triplet (min, max, 1-id). View full abstract»

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  • A new computational fuzzy time series model to forecast number of outpatient visits

    Publication Year: 2012 , Page(s): 1 - 6
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (200 KB) |  | HTML iconHTML  

    Forecasting number of outpatient visits is pre-eminent for patient planning, medical resource utilization and overall management of health care system to a certain extent. Aim of forecasting the outpatient visits can also be seemed in terms of individual care. In addition, accurate prediction of outpatient visits in hospitals can play a significant role in health insurance plans and for deciding reimbursement system. As such, main challenge in healthcare simulation is to produce a realistic model that must utilize efficient techniques for managing complex time series data and should be capable of generating forecasted value with almost negligible error. We proposed forecasting model based on fuzzy time series that rectifies the existing imperfections and overcome the drawbacks of previous approaches. Novice concept introduced to eliminate the inadequacies by way of defining the universe of discourse on historical data. Model also endeavors to pontificate the issue of improving forecasting accuracy through the new idea of event discretization function. This was quite encouraging as it highlights the impact of trend & seasonal components by yielding dynamic change of values from time t to t+1. This fuzzy computing time series model is designed by joint consideration of three key points (1) Event discretization of time series data (2) Frequency density based partitioning (3) Creation of Fuzzy logical relationships in optimized way. Subsequently, performance of the proposed model is demonstrated and compared with some of the pre-existing forecasting methods on same outpatient data. In general, findings of the study are interesting and superior in terms of least Average Forecasting Error Rate (AFER) and Mean Square Error (MSE) values. View full abstract»

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  • Dynamical construction of binary relations in coreference detection

    Publication Year: 2012 , Page(s): 1 - 6
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1057 KB) |  | HTML iconHTML  

    Modern database systems allow to describe information from the real world in a well structured manner. Unfortunately, many databases cope with quality problems. One of these problems is the existence of coreferent data, which means that the same real world entity is described multiple times within one database. Due to errors, inaccuracies and lack of standardization, coreferent data are not bound to be equal, which makes the finding of coreferent data a challenging topic. In this paper, we contribute to the field of coreference detection by proposing an automated and dynamical method for the construction of a binary relation R that models semantical knowledge between attribute values. The advantages of the proposed method are two folded: no effort must be put in construction of knowledge bases and mismatches between the database and the knowledge base are avoided. View full abstract»

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  • A fast learning algorithm for uninorm-based fuzzy neural networks

    Publication Year: 2012 , Page(s): 1 - 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (551 KB) |  | HTML iconHTML  

    This paper suggests a fast learning algorithm for weighted uninorm-based neural networks. Fuzzy neural networks are models capable to approximate functions with high accuracy and to generate transparent models through extraction of linguistic information from the resulting topology. A fuzzy neural network model based on weighted uninorms has been developed recently. It was shown that this model approximates any continuous real function on a compact subset. In this paper we introduce a fast learning algorithm for this class of fuzzy neural networks based on ideas from extreme learning machine. The algorithm is detailed and computational experiments reported to illustrate the accuracy and time efficiency of the learning approach. The results show that neural fuzzy model is accurate and learning speed is as good as or faster than alternative neural network models. View full abstract»

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  • Simulation of language evolution using Fuzzy Grammars

    Publication Year: 2012 , Page(s): 1 - 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (591 KB) |  | HTML iconHTML  

    Many computer simulations try to explain language evolution with socially oriented scenarios in multi-agent systems by applying methods such as genetic algorithms and neural networks. In this paper a new approach based on modifications to the classic Ant Colony Optimization algorithm is proposed. Ants are provided with a Fuzzy Grammar and the ability to embed a message in the pheromone. By fuzzifying the grammar, ants are able to modify the degree of membership of the production rules to gradually adopt a foreign language. View full abstract»

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