Advanced Computational Methods for Knowledge Engineering by Nguyen Van Thoai (auth.), Ngoc Thanh Nguyen, Tien van Do, PDF

By Nguyen Van Thoai (auth.), Ngoc Thanh Nguyen, Tien van Do, Hoai An le Thi (eds.)

ISBN-10: 3319002929

ISBN-13: 9783319002927

ISBN-10: 3319002937

ISBN-13: 9783319002934

The publication involves 29 prolonged chapters which were chosen and invited from the submissions to the 1st overseas convention on laptop technological know-how, utilized arithmetic and Applications (ICCSAMA 2013) hung on 9-10 may perhaps, 2013 in Warsaw, Poland. The e-book is prepared into 5 components, that are: complicated Optimization equipment and Their purposes, Queuing concept and purposes, Computational equipment for wisdom Engineering, wisdom Engineering with Cloud and Grid Computing, and common sense established equipment for choice Making and information Mining, respectively. All chapters within the e-book talk about theoretical and useful concerns attached with computational equipment and optimization tools for wisdom engineering.

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Extra resources for Advanced Computational Methods for Knowledge Engineering

Example text

For a convex function θ, the subdifferential of θ at x0 ∈ domθ := {x ∈ Rn : θ(x0 ) < +∞}, denoted by ∂θ(x0 ), is defined by ∂θ(x0 ) := {y ∈ Rn : θ(x) ≥ θ(x0 ) + x − x0 , y , ∀x ∈ Rn }, and the conjugate θ∗ of θ is θ∗ (y) := sup{ x, y − θ(x) : x ∈ Rn }, y ∈ Rn . A general DC program is that of the form: α = inf{F (x) := G(x) − H(x) | x ∈ Rn }, (11) where G, H are lower semi-continuous proper convex functions on Rn . Such a function F is called a DC function, and G − H a DC decomposition of F while G and H are the DC components of F .

Note that, since f is an IPH function, it follows that f (x) ≥ 0 ∀x ∈ IRn+ . So, if there is a point y ∈ Q(S) with f (y) = 0, then ‘everything is done’: y is a global optimal solution of Problem (7). Thus, we assume that f (y) > 0 ∀y ∈ Q(S), and our method for computing a lower bound μ(S) is based on the following. Proposition 1. Let U be the n × n matrix with columns u1 , · · · , un . t. i )λi − t ≤ 0, y ∈ Q(S) i=1 Uλ ∈ D (12) n λi = 1 i=1 λ ≥ 0, where for each y ∈ Q(S), the point py is constructed by (5) and the min-type function py (x) is defined by (3).

Global Minimization of Increasing Positively Homogeneous Functions over the Unit Simplex. Annals of Operations Research 98, 171–187 (2000) 3. : Continuous selections of linear functions and nonsmooth critical point theory. Nonlinear Analysis, TMA 24, 385–407 (1995) 4. : Constructive Nonsmooth Analysis, Peter Lang, Frankfurt am Main (1995) 5. : Introduction to Global Optimization, 2nd edn. Kluwer, Dordrecht (2000) 6. : DC Programming: Overview. Journal of Optimization Theory and Applications 103, 1–43 (1999) 7.

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Advanced Computational Methods for Knowledge Engineering by Nguyen Van Thoai (auth.), Ngoc Thanh Nguyen, Tien van Do, Hoai An le Thi (eds.)

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