Suchergebnisse - "Dynamic multi-objective evolutionary algorithms"

Memory-Assisted Dynamic Multi-Objective Evolutionary Algorithm for Feature Drift Problem

Weitere Verfasser: Sahmoud, Shaaban Topcuoglu, Haluk Rahmi

Schlagwörter: 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

Verfügbarkeit: https://hdl.handle.net/11424/226409

Memory-Assisted Dynamic Multi-Objective Evolutionary Algorithm for Feature Drift Problem

Weitere Verfasser: Sahmoud S., Topcuoglu H.R.

Schlagwörter: 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

Verfügbarkeit: https://hdl.handle.net/11424/248120
https://doi.org/10.1109/CEC48606.2020.9185730

Memory-Assisted Dynamic Multi-Objective Evolutionary Algorithm for Feature Drift Problem

Autoren: Sahmoud, Shaaban Topçuoğlu, Haluk Rahmi FSM Vakıf Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü

Weitere Verfasser: Sahmoud, Shaaban Topçuoğlu, Haluk Rahmi FSM Vakıf Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü

Schlagwörter: Dynamic Multi-Objective Evolutionary Algorithms, Learning in Non-Stationary Environments, Severity of Changes, Feature Drift, Memory-Based Algorithms

Dateibeschreibung: application/pdf

Relation: IEEE Congress on Evolutionary Computation (CEC); Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı; https://hdl.handle.net/11352/3545

Verfügbarkeit: https://hdl.handle.net/11352/3545

Dynamic multi-objective optimization algorithm based on decomposition and preference

Autoren: Hu, Yaru Zou, Juan Zheng, Jinhua et al.

Schlagwörter: Dynamic multi-objective evolutionary algorithms, Region of interest, Reference points, Changing preference point

Dateibeschreibung: application/pdf

Relation: https://dora.dmu.ac.uk/handle/2086/20858; https://doi.org/10.1016/j.ins.2021.04.055

Verfügbarkeit: https://dora.dmu.ac.uk/handle/2086/20858
https://doi.org/10.1016/j.ins.2021.04.055

Neural network based multi-objective evolutionary algorithm for dynamic workflow scheduling in cloud computing

Autoren: TOPCUOĞLU, HALUK RAHMİ Ismayilov, Goshgar Topcuoglu, Haluk Rahmi

Weitere Verfasser: TOPCUOĞLU, HALUK RAHMİ Ismayilov, Goshgar Topcuoglu, Haluk Rahmi

Schlagwörter: 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

Verfügbarkeit: https://hdl.handle.net/11424/235945
https://doi.org/10.1016/j.future.2019.08.012

A general framework based on dynamic multi-objective evolutionary algorithms for handling feature drifts on data streams

Autoren: TOPCUOĞLU, HALUK RAHMİ Sahmoud, Shaaban Topcuoglu, Haluk Rahmi

Weitere Verfasser: TOPCUOĞLU, HALUK RAHMİ Sahmoud, Shaaban Topcuoglu, Haluk Rahmi

Schlagwörter: 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

Verfügbarkeit: https://hdl.handle.net/11424/235882
https://doi.org/10.1016/j.future.2019.07.069

Dynamic Multi-Objective Workflow Scheduling for Cloud Computing Based on Evolutionary Algorithms

Weitere Verfasser: Sill, A Spillner, J Ismayilov, Goshgar et al.

Schlagwörter: 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

Verfügbarkeit: https://hdl.handle.net/11424/226081
https://doi.org/10.1109/UCC-Companion.2018.00042

A Type Detection Based Dynamic Multi-objective Evolutionary Algorithm

Autoren: TOPCUOĞLU, HALUK RAHMİ Sim, K Kaufmann, P et al.

Weitere Verfasser: TOPCUOĞLU, HALUK RAHMİ Sim, K Kaufmann, P et al.

Schlagwörter: 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

Verfügbarkeit: https://hdl.handle.net/11424/226045
https://doi.org/10.1007/978-3-319-77538-8_58

Exploiting characterization of dynamism for enhancing dynamic multi-objective evolutionary algorithms

Autoren: TOPCUOĞLU, HALUK RAHMİ Sahmoud, Shaaban Topcuoglu, Haluk Rahmi

Weitere Verfasser: TOPCUOĞLU, HALUK RAHMİ Sahmoud, Shaaban Topcuoglu, Haluk Rahmi

Schlagwörter: 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

Verfügbarkeit: https://hdl.handle.net/11424/235264
https://doi.org/10.1016/j.asoc.2019.105783