Search Results - "Dynamic Multi-objective Evolutionary Algorithms"
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Subject Terms: dynamic multi-objective evolutionary algorithms, learning in non-stationary environments, severity of changes, feature drift, memory-based algorithms, FEATURE-SELECTION, OPTIMIZATION
Relation: 2020 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC); IEEE Congress on Evolutionary Computation; https://hdl.handle.net/11424/226409; WOS:000703998201116
Availability: https://hdl.handle.net/11424/226409
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Contributors: Sahmoud S., Topcuoglu H.R.
Subject Terms: dynamic multi-objective evolutionary algorithms, feature drift, learning in non-stationary environments, memory-based algorithms, severity of changes
Relation: 2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings; https://hdl.handle.net/11424/248120
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Subject Terms: Dynamic Multi-Objective Evolutionary Algorithms, Learning in Non-Stationary Environments, Severity of Changes, Feature Drift, Memory-Based Algorithms
File Description: application/pdf
Relation: IEEE Congress on Evolutionary Computation (CEC); Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı; https://hdl.handle.net/11352/3545
Availability: https://hdl.handle.net/11352/3545
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Authors: et al.
Subject Terms: Dynamic multi-objective evolutionary algorithms, Region of interest, Reference points, Changing preference point
File Description: application/pdf
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Subject Terms: Workflow scheduling, Resource failures, Changing number of objectives, Dynamic multi-objective evolutionary algorithms, Neural networks, OPTIMIZATION, COST
Relation: FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE; https://hdl.handle.net/11424/235945; WOS:000501936300025
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Subject Terms: Feature drift, Classification of data streams, Dynamic multi-objective evolutionary algorithms, Filter-based feature selection, FEATURE-SELECTION, OPTIMIZATION
Relation: FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE; https://hdl.handle.net/11424/235882; WOS:000501936300004
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Contributors: et al.
Subject Terms: Workflow scheduling, resource failures, dynamic multi-objective evolutionary algorithms, OPTIMIZATION
Relation: 2018 IEEE/ACM INTERNATIONAL CONFERENCE ON UTILITY AND CLOUD COMPUTING COMPANION (UCC COMPANION); International Conference on Utility and Cloud Computing; https://hdl.handle.net/11424/226081; WOS:000458720100025
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Authors: et al.
Contributors: et al.
Subject Terms: Dynamic Multi-objective Optimization Problems, Non-dominated Sorting Genetic Algorithm (NSGA-II), Type detection, Dynamic Multi-objective Evolutionary Algorithms, NSGA-II, OPTIMIZATION
Relation: APPLICATIONS OF EVOLUTIONARY COMPUTATION, EVOAPPLICATIONS 2018; Lecture Notes in Computer Science; https://hdl.handle.net/11424/226045; WOS:000433244800058
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Subject Terms: Dynamic multi-objective optimization problems, Dynamic multi-objective evolutionary algorithms, Change detection, Characterization of change, OPTIMIZATION
Relation: APPLIED SOFT COMPUTING; https://hdl.handle.net/11424/235264; WOS:000500691600063
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