By Margaret F. Shipley, Gary L. Stading (auth.), Salvatore Greco, Bernadette Bouchon-Meunier, Giulianella Coletti, Mario Fedrizzi, Benedetto Matarazzo, Ronald R. Yager (eds.)
These 4 volumes (CCIS 297, 298, 299, three hundred) represent the lawsuits of the 14th foreign convention on info Processing and administration of Uncertainty in Knowledge-Based structures, IPMU 2012, held in Catania, Italy, in July 2012. The 258 revised complete papers offered including six invited talks have been conscientiously reviewed and chosen from quite a few submissions. The papers are geared up in topical sections on fuzzy computer studying and online modeling; computing with phrases and choice making; tender computing in computing device imaginative and prescient; tough units and intricate facts research: idea and purposes; clever databases and knowledge procedure; info fusion platforms; philosophical and methodological features of sentimental computing; easy concerns in tough units; fortieth anniversary of the measures of fuziness; SPS11 uncertainty in profiling platforms and functions; dealing with uncertainty with copulas; formal easy methods to take care of uncertainty of many-valued occasions; linguistic summarization and outline of knowledge; fuzzy implications: conception and functions; sensing and information mining for educating and studying; conception and functions of intuitionistic fuzzy units; approximate elements of knowledge mining and database analytics; fuzzy numbers and their functions; details processing and administration of uncertainty in knowledge-based structures; aggregation features; obscure possibilities; probabilistic graphical types with imprecision: idea and purposes; trust functionality concept: fundamentals and/or functions; fuzzy uncertainty in economics and enterprise; new developments in De Finetti's strategy; fuzzy measures and integrals; multi standards selection making; uncertainty in privateness and defense; uncertainty within the spirit of Pietro Benvenuti; coopetition; online game thought; probabilistic approach.
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Extra info for Advances in Computational Intelligence: 14th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2012, Catania, Italy, July 9-13, 2012, Proceedings, Part IV
And i∗ denotes the focal points of the ith fuzzy ∗ rule. e. the ﬁrst data point is considered as a cluster center, forming the ﬁrst rule. The recursive density estimation clustering approach does not rely on useror problem-speciﬁc thresholds, diﬀerently as in methods like subtractive clustering or participatory learning, for example. Moreover, the density is evaluated recursively and the whole information that concerns the spatial distribution of all data is accumulated in a small number of variables .
34, 41–47 (1997) 20. : A new measure of consistency for positive reciprocal matrices. Computers and Mathematics with Applications 46, 1839–1845 (2003) 21. : Inconsistency of pair-wise comparison matrix with fuzzy elements on the geometric mean. Fuzzy Sets and Systems 161, 1604–1613 (2010) 22. : Highlights and critical points in the theory and application of the Analytic Hierarchy Process. European Journal of Operational Research 74, 426– 447 (1994) 23. : A scaling method for priorities in hierarchical structures.
The purpose of this paper is to study stock market forecast using evolving functional models and their application for US and Brazilian market data. Evolving fuzzy systems use data streams to continuously adapt the structure and functionality of fuzzy models to improve their performance, ensuring high generality. The evolving mechanism translates into an adaptive procedure to continuously capture gradual changes of models structure and parameters . Recently, applications of fuzzy systems for stock market forecasting include fuzzy decision trees , fuzzy neural networks  and hypernetwork models .