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 court cases of the 14th overseas 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 rigorously reviewed and chosen from quite a few submissions. The papers are geared up in topical sections on fuzzy desktop studying and online modeling; computing with phrases and choice making; delicate computing in laptop imaginative and prescient; tough units and complicated facts research: conception and functions; clever databases and data process; info fusion platforms; philosophical and methodological facets of soppy computing; easy concerns in tough units; fortieth anniversary of the measures of fuziness; SPS11 uncertainty in profiling structures and functions; dealing with uncertainty with copulas; formal how to care for uncertainty of many-valued occasions; linguistic summarization and outline of knowledge; fuzzy implications: concept and purposes; sensing and information mining for instructing and studying; concept and purposes 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; vague possibilities; probabilistic graphical types with imprecision: idea and functions; trust functionality idea: fundamentals and/or purposes; fuzzy uncertainty in economics and company; new developments in De Finetti's strategy; fuzzy measures and integrals; multi standards determination making; uncertainty in privateness and safeguard; uncertainty within the spirit of Pietro Benvenuti; coopetition; online game conception; probabilistic approach.
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Additional resources 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
Modified Net Present Value under Uncertainties TV α = [CFi1l (α ) x (1 + k rrl (α ) ) n −1 , CFi1r (α ) x(1 + k rrr (α ) ) n−1 ] + [CFil2(α ) x(1 + k rrl (α ) ) n− 2 , CFi r2(α ) x(1 + k rrr (α ) ) n −2 ] + ... + [CFinl (α ) , CFinr (α ) ] 15 (15) where: TV l (α ) = CFi1l (α ) x(1 + k rrl (α ) ) n −1 + CFil2(α ) x(1 + k rrl (α ) ) n −2 + ... + CFinl (α ) (16) TV r (α ) = CFi1r (α ) x(1 + k rrr (α ) ) n −1 + CFi r2(α ) x(1 + k rrr (α ) ) n − 2 + ... + CFinr (α ) (17) Step 2: Calculation of the fuzzy Present Value (PVα).
Evolving Systems: Methodology and Applications. , Hoboken (2010) 2. : An approach to online identiﬁcation of Takagi-Sugeno fuzzy models. IEEE Transactions on Systems, Man, and Cybernetics – Part B: Cybernetics 4(1), 484–498 (2004) 3. : Evolving fuzzy systems from data streams in real-time. In: 2006 International Symposium on Evolving Fuzzy Systems, Ambleside, September 7-9, pp. 29–35 (2006) 4. : Surveying stock market forecasting techniques Part II: Soft computing methods. Expert Systems with Applications 36(3), 5931– 5941 (2009) 5.
Min w (9) i,j=1 wi Since ln( w ) = ln wi − ln wj , problem (9) can be interpreted as the minimization j of the Euclidean distance between ln(A) and the logarithmic image ln(AC ) = wi ))n×n ∈ L of a consistent matrix. Then, the solution of (9) can be obtained (ln( w j by orthogonally projecting ln(A) on L. From the relevant fact that L = ln(A∗ ) is a linear subspace of Rn×n , it follows that A∗ is the image of L through the inverse function exp(·), where the function is again deﬁned componentwise on matrix elements.