000 03497nam a22004455i 4500
001 978-94-91216-29-9
003 DE-He213
005 20160302170422.0
007 cr nn 008mamaa
008 120301s2010 fr | s |||| 0|eng d
020 _a9789491216299
_9978-94-91216-29-9
024 7 _a10.2991/978-94-91216-29-9
_2doi
050 4 _aQ334-342
050 4 _aTJ210.2-211.495
072 7 _aUYQ
_2bicssc
072 7 _aTJFM1
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
100 1 _aRuan, Da.
_eauthor.
245 1 0 _aComputational Intelligence in Complex Decision Systems
_h[electronic resource] /
_cby Da Ruan.
264 1 _aParis :
_bAtlantis Press,
_c2010.
300 _aXIV, 388p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aAtlantis Computational Intelligence Systems,
_x1875-7650 ;
_v2
505 0 _aComputational Intelligence: Past, Today, and Future -- Uncertainty in Dynamically Changing Input Data -- Decision Making under Uncertainty by Possibilistic Linear Programming Problems -- Intelligent DecisionMaking in Training Based on Virtual Reality -- A Many-Valued Temporal Logic and Reasoning Framework for Decision Making -- A Statistical Approach to Complex Multi-Criteria Decisions -- A Web Based Assessment Tool via the Evidential Reasoning Approach -- An Intelligent Policy Simulator for Supporting Strategic Nuclear Policy Decision Making -- Computing withWords for Hierarchical and Distributed Decision-Making -- Realizing Policies by Projects Using Fuzzy Multiple Criteria Decision Making -- Evolutionary ComputationMethods for Fuzzy Decision Making on Load Dispatch Problems -- Intelligent Decision-Making for a Smart Home Environment with Multiple Occupants -- Applying a Choquet Integral Based Decision Making Approach to Evaluate Agile Supply Chain Strategies.
520 _aIn recent years, there has been a growing interest in the need for designing intelligent systems to address complex decision systems. One of the most challenging issues for the intelligent system is to effectively handle real-world uncertainties that cannot be eliminated. These uncertainties include various types of information that are incomplete, imprecise, fragmentary, not fully reliable, vague, contradictory, deficient, and overloading. The uncertainties result in a lack of the full and precise knowledge of the decision system, including the determining and selection of evaluation criteria, alternatives, weights, assignment scores, and the final integrated decision result. Computational intelligent techniques (including fuzzy logic, neural networks, and genetic algorithms etc.), which are complimentary to the existing traditional techniques, have shown great potential to solve these demanding, real-world decision problems that exist in uncertain and unpredictable environments. These technologies have formed the foundation for intelligent systems.
650 0 _aComputer science.
650 0 _aArtificial intelligence.
650 1 4 _aComputer Science.
650 2 4 _aArtificial Intelligence (incl. Robotics).
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
830 0 _aAtlantis Computational Intelligence Systems,
_x1875-7650 ;
_v2
856 4 0 _uhttp://dx.doi.org/10.2991/978-94-91216-29-9
912 _aZDB-2-SCS
999 _c195234
_d195234