دانلود رایگان مجموعه مقالات علمی اشپرینگر در زمینه منطق فازی — بخش چهل و هشتم

منطق فازی (Fuzzy Logic) اولین بار در پی تنظیم نظریه مجموعه‌های فازی به وسیله پروفسور لطفی زاده (۱۹۶۵ میلادی) در صحنه محاسبات نو ظاهر شد. در واقع منطق فازی از منطق ارزش‌های «صفر و یک» نرم‌افزارهای کلاسیک فراتر رفته و درگاهی جدید برای دنیای علوم نرم‌افزاری و رایانه‌ها می‌گشاید، زیرا فضای شناور و نامحدود بین اعداد صفر و یک را نیز در منطق و استدلال‌های خود به کار می‌گیرد. در ادامه مقالات علمی انتشارات بین المللی اشپرینگر (Springer) در زمینه منطق فازی (Fuzzy Logic) برای دانلود آمده است. می توانید برای دانلود هر یک از مقالات از سرور دانلود متلب سایت، بر روی لینک دانلود هر یک از آن ها، کلیک کنید.

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دانلود رایگان مجموعه مقالات علمی اشپرینگر در زمینه منطق فازی — فهرست اصلی

عنوان اصلی مقاله Computer-augmented decision making
نوع مقاله مقاله ژورنال
نویسندگان C. P. Whaley
چکیده / توضیح The principal judgmental components of multiattribute decision making are examined here with specific reference to how these components can be captured electronically. Once captured, a function, rule, or algorithm may be executed for the integration of this information and the selection of the optimal alternative(s). Two kinds of algorithms are discussed: one based on linear models, the other on fuzzy-set theory and ratio scaling. With on-line support and certain assumptions about human biases (which lead to nonoptimal decisions), the quality of decisions can be enhanced considerably. The principal concerns are with end-user acceptance of computer augmented decisions.
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عنوان اصلی مقاله Vertical similarity in spoken word recognition: Multiple lexical activation, individual differences, and the role of sentence context
نوع مقاله مقاله ژورنال
نویسندگان Cynthia M. Connine, Dawn G. Blasko, Jian Wang
چکیده / توضیح Four experiments investigated acoustic-phonetic similarity in the mapping process between the speech signal and lexical representations (vertical similarity). Auditory stimuli were used where ambiguous initial phonemes rendered a phoneme sequence lexically ambiguous (perceptual-lexical ambiguities). A cross-modal priming paradigm (Experiments 1, 2, and 3) showed facilitation for targets related to both interpretations of the ambiguities, indicating multiple activation. Experiment 4 investigated individual differences and the role of sentence context in vertical similarity mapping. The results support a model where spoken word recognition proceeds via goodness-of-fit mapping between speech and lexical representations that is not influenced by sentence context.
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عنوان اصلی مقاله Applying Occam’s razor in modeling cognition: A Bayesian approach
نوع مقاله مقاله ژورنال
نویسندگان In Jae Myung, Mark A. Pitt
چکیده / توضیح In mathematical modeling of cognition, it is important to have well-justified criteria for choosing among differing explanations (i.e., models) of observed data. This paper introduces a Bayesian model selection approach that formalizes Occam’s razor, choosing the simplest model that describes the data well. The choice of a model is carried out by taking into account not only the traditional model selection criteria (i.e., a model’s fit to the data and the number of parameters) but also the extension of the parameter space, and, most importantly, the functional form of the model (i.e., the way in which the parameters are combined in the model’s equation). An advantage of the approach is that it can be applied to the comparison of non-nested models as well as nested ones. Application examples are presented and implications of the results for evaluating models of cognition are discussed.
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عنوان اصلی مقاله Theoretical and empirical review of multinomial process tree modeling
نوع مقاله مقاله ژورنال
نویسندگان William H. Batchelder, David M. Riefer
چکیده / توضیح We review a current and popular class of cognitive models calledmultinomial processing tree (MPT) models. MPT models are simple, substantively motivated statistical models that can be applied to categorical data. They are useful as data-analysis tools for measuring underlying or latent cognitive capacities and as simple models for representing and testing competing psychological theories. We formally describe the cognitive structure and parametric properties of the class of MPT models and provide an inferential statistical analysis for the entire class. Following this, we provide a comprehensive review of over 80 applications of MPT models to a variety of substantive areas in cognitive psychology, including various types of human memory, visual and auditory perception, and logical reasoning. We then address a number of theoretical issues relevant to the creation and evaluation of MPT models, including model development, model validity, discrete-state assumptions, statistical issues, and the relation between MPT models and other mathematical models. In the conclusion, we consider the current role of MPT models in psychological research and possible future directions.
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عنوان اصلی مقاله Conceptual combination: Conjunction and negation of natural concepts
نوع مقاله مقاله ژورنال
نویسندگان James A. Hampton
چکیده / توضیح The operation of negation on combinations of natural categories was examined in two experiments. In the first, category membership ratings of lists of items were obtained for pairs of concepts considered individually and in two logical combinations: conjunctions (e.g., “Tools which are also Weapons”) and negated conjunctions—forms of those conjunctions in which the modifier noun category was negated (“Tools which arenot Weapons”). For conjunctions, results supported earlier findings of overextension and the geometric averaging of constituent membership values (Hampton, 1988b). Previous findings of concept dominance and noncommutativity within conjunctions were also replicated, both for typicality ratings and for probability of class membership. For negated conjunctions, the pattern of dominance was similar but interacted with order within the conjunction. Negated conjunctions were also overextended. The second experiment explored how the attributes of negated conjunctions were derived from those of the two component concepts. Frequency of generation of attributes expressed positively (has wheels) or negatively (has no wheels) followed rated frequency in the negated category. The distinctiveness of an attribute to distinguish the complement from the head-noun class was associated with the generation of attributes, particularly when there was relatively high overlap between the two categories.
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عنوان اصلی مقاله Intelligence: Exact computation or biofunctional cognition
نوع مقاله مقاله ژورنال
نویسندگان Antony Satyadas, Asghar Iran-Nejad, Hui Chuan Chen, Brad Chissom
چکیده / توضیح What is it that makes human beings so good at fuzzy judgments and so poor at precise computation? This paper first addresses this question in the context of a biofunctional theory of how the nervous system functions and then discusses a fuzzy intelligence evaluation system for determing the intelligence of individuals.
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عنوان اصلی مقاله BayesGCM: Software for Bayesian inference with the generalized context model
نوع مقاله مقاله ژورنال
نویسندگان Wolf Vanpaemel
چکیده / توضیح This article describes and demonstrates the BayesGCM software package. The software is designed to perform Bayesian analysis with the generalized context model (GCM). It is intended to make the GCM easily accessible to a general public of experimental, social, and clinical psychologists interested in category learning, sensitivity, and attention. The software uses MATLAB and relies on WinBUGS to draw samples from the posterior distribution of the GCM’s parameters. The returned output comprises the full set of posterior samples, summary descriptive statistics, and graphs of the posterior distribution for each parameter of interest.
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عنوان اصلی مقاله Word knowledge influences character perception
نوع مقاله مقاله ژورنال
نویسندگان Xingshan Li, Alexander Pollatsek
چکیده / توضیح In two experiments, we examined whether context information can affect the activity of the nodes at the character level. Chinese readers viewed two Chinese characters; one was intact, but the other (the target) was embedded in a rectangle of visual noise and increased in visibility over time. The two characters constituted a word in one condition but did not in the other condition. The task was to press a button to indicate whether the character in the noise was at the top or bottom of the rectangle. (They did not have to identify the character.) Response times were faster in the word condition than in the nonword condition. Because the “wordness” of the stimulus was logically irrelevant to judging the location of the target character, the data indicate that processing at the word level can feed back to fairly low-level judgments, such as where a character is.
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عنوان اصلی مقاله English semantic word-pair norms and a searchable Web portal for experimental stimulus creation
نوع مقاله مقاله ژورنال
نویسندگان Erin M. Buchanan, Jessica L. Holmes, Marilee L. Teasley, Keith A. Hutchison
چکیده / توضیح As researchers explore the complexity of memory and language hierarchies, the need to expand normed stimulus databases is growing. Therefore, we present 1,808 words, paired with their features and concept–concept information, that were collected using previously established norming methods (McRae, Cree, Seidenberg, & McNorgan Behavior Research Methods 37:547–559, 2005). This database supplements existing stimuli and complements the Semantic Priming Project (Hutchison, Balota, Cortese, Neely, Niemeyer, Bengson, & Cohen-Shikora 2010). The data set includes many types of words (including nouns, verbs, adjectives, etc.), expanding on previous collections of nouns and verbs (Vinson & Vigliocco Journal of Neurolinguistics 15:317–351, 2008). We describe the relation between our and other semantic norms, as well as giving a short review of word-pair norms. The stimuli are provided in conjunction with a searchable Web portal that allows researchers to create a set of experimental stimuli without prior programming knowledge. When researchers use this new database in tandem with previous norming efforts, precise stimuli sets can be created for future research endeavors.
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عنوان اصلی مقاله Automated recognition of spikes in 1 Hz data recorded at the Easter Island magnetic observatory
نوع مقاله مقاله ژورنال
نویسندگان Anatoly Soloviev, Arnaud Chulliat, Shamil Bogoutdinov, Alexei Gvishiani, Sergey Agayan, Aline Peltier, Benoit Heumez
چکیده / توضیح In the present paper we apply a recently developed pattern recognition algorithm SPs to the problem of automated detection of artificial disturbances in one-second magnetic observatory data. The SPs algorithm relies on the theory of discrete mathematical analysis, which has been developed by some of the authors for more than 10 years. It continues the authors’ research in the morphological analysis of time series using fuzzy logic techniques. We show that, after a learning phase, this algorithm is able to recognize artificial spikes uniformly with low probabilities of target miss and false alarm. In particular, a 94% spike recognition rate and a 6% false alarm rate were achieved as a result of the algorithm application to raw one-second data acquired at the Easter Island magnetic observatory. This capability is critical and opens the possibility to use the SPs algorithm in an operational environment.
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