04345nam 22005655 450 991048298740332120200706041832.03-319-96104-710.1007/978-3-319-96104-0(CKB)4100000005323432(DE-He213)978-3-319-96104-0(MiAaPQ)EBC5921096(PPN)229502741(EXLCZ)99410000000532343220180712d2019 u| 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierNumerical and Evolutionary Optimization – NEO 2017 /edited by Leonardo Trujillo, Oliver Schütze, Yazmin Maldonado, Paul Valle1st ed. 2019.Cham :Springer International Publishing :Imprint: Springer,2019.1 online resource (XIV, 312 p. 137 illus.) Studies in Computational Intelligence,1860-949X ;785Includes index.3-319-96103-9 Deterministic Parameter Control in Differential Evolution with Combined Variants for Constrained Search Spaces -- A Descent Method for Equality and Inequality Constrained Multiobjective Optimization Problems -- Evaluating Memetic Building Spatial Design Optimisation Using Hypervolume Indicator Gradient Ascent -- Fitting Multiple Ellipses with PEARL and a Multi-objective Genetic Algorithm -- Analyzing Evolutionary Art Audience Interaction by Means of a Kinect Based Non-Intrusive Method -- Applying Control Theory to Optimize the Inventory Holding Costs in Supply Chains -- On the Selection of Tuning Parameters in Predictive Controllers Based on NSGA-II -- IDA-PBC Controller Tuning Using Steepest Descent -- Self-Tuning for a SISO-Type Fuzzy Control Based on the Relay Feedback Approach -- Optimal Design Of Sliding Mode Control Combined with Positive Position Feedback -- Biot’s Parameters Estimation In Ultrasound Propagation Through Cancellous Bone -- Optimal Sizing of Low-DropOut Voltage Regulators by NSGA-II and PVT Analysis -- Genetic Optimization of Fuzzy Systems for the Classification of Treated Water Quality -- Stabilization Based on Fuzzy System for Structures Affected by External Disturbances -- Comparison of Two Methods for I/Q Imbalance Compensation Applied in RF Power Amplifiers -- An Application of Data Envelopment Analysis to the Performance Assessment of Online Social Networks Usage in Mazatlan Hotel Organizations. .This book features 15 chapters based on the Numerical and Evolutionary Optimization (NEO 2017) workshop, held from September 27 to 29 in the city of Tijuana, Mexico. The event gathered researchers from two complimentary fields to discuss the theory, development and application of state-of-the-art techniques to address search and optimization problems. The lively event included 7 invited talks and 64 regular talks covering a wide range of topics, from evolutionary computer vision and machine learning with evolutionary computation, to set oriented numeric and steepest descent techniques. Including research submitted by the NEO community, the book provides informative and stimulating material for future research in the field.Studies in Computational Intelligence,1860-949X ;785Computational intelligenceArtificial intelligenceComputational Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/T11014Artificial Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/I21000Computational intelligence.Artificial intelligence.Computational Intelligence.Artificial Intelligence.519.3Trujillo Leonardoedthttp://id.loc.gov/vocabulary/relators/edtSchütze Oliveredthttp://id.loc.gov/vocabulary/relators/edtMaldonado Yazminedthttp://id.loc.gov/vocabulary/relators/edtValle Pauledthttp://id.loc.gov/vocabulary/relators/edtMiAaPQMiAaPQMiAaPQBOOK9910482987403321Numerical and Evolutionary Optimization – NEO 20172843818UNINA