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Veri Madenciliği Teknikleriyle Türkçe Web Sayfalarının Kategorize Edilmesi
(IEEE, 2017)
Günümüzde artan veri miktarıyla başa çıkabilmek için tek başına insan gücünün kullanılması mümkün görünmemektedir. Bu sebeple benzer dokümanları bir araya gruplayabilecek ya da dokümanları, önceden tanımlı kategorilere ...
Konvolüsyonel Sinir Ağlarında Hiper-Parametre Optimizasyonu Yöntemlerinin İncelenmesi
(Gazi Üniversitesi, 2019)
Konvolüsyonel Sinir Ağları (KSA), katmanlarının en az bir tanesinde matris çarpımı yerine konvolüsyon işleminin kullanıldığı çok katmanlı yapay sinir ağlarının bir türüdür. Özellikle bilgisayarlı görü çalışmalarında çok ...
Integer Programming Versus Constraint Programming: a Course Timetabling Case Study
(University of Cincinnati Industrial Engineering, 2019)
In this study, two solution approaches are compared for a real-world, moderate-size but a highly constrained university
course timetabling problem. The first approach is developing an integer programming model and solving ...
Clustering Electricity Market Participants Via FRM Models
(IOS Press, 2020)
Collateral mechanism in the Electricity Market ensures the payments are executed on a timely manner; thus maintains
the continuous cash flow. In order to value collaterals, Takasbank, the authorized central settlement ...
Minimum Penalty Perturbation Heuristics for Curriculum-Based Timetables Subject to Multiple Disruptions
(Elsevier, 2021)
Course timetables are often rendered infeasible due to unexpected changes in requirements and must be
repaired. Given an initial timetable, planners prefer a repaired timetable whose quality is worsened as little as
possible ...
Robust University Course Timetabling Problem Subject to Single and Multiple Disruptions
(Elsevier, 2020)
University course timetables are often finalized in stages, in between which, changes in the data make the earlier version infeasible. As each version is announced to the community, it is desirable to have a robust initial ...
A Bi-criteria Hybrid Genetic Algorithm with Robustness Objective for the Course Timetabling Problem
(Elsevier, 2018)
Traditional methods of generating timetables may yield high-quality solutions, but they may not yield robust solutions that may easily be adapted to changing inputs. Incorporating late changes by making minimum modifications ...
Multi-Objective Simulated Annealing for Hyper-Parameter Optimization in Convolutional Neural Networks
(PeerJ, Inc., 2021)
In this study, we model a CNN hyper-parameter optimization problem as a
bi-criteria optimization problem, where the first objective being the classification
accuracy and the second objective being the computational ...
Hyper-Parameter Selection in Convolutional Neural Networks Using Microcanonical Optimization Algorithm
(The Institute of Electrical and Electronics Engineers, 2020)
The success of Convolutional Neural Networks is highly dependent on the selected architecture
and the hyper-parameters. The need for the automatic design of the networks is especially important
for complex architectures ...
Bi-Criteria Simulated Annealing Algorithms for the Robust University Course Timetabling Problem
(PATAT, 2018)
A bi-criteria version of the curriculum-based university timetabling
problem of ITC-2007 is solved using a multi-objective simulated annealing
(MOSA) algorithm that identifies an approximation to the optimal Pareto
front. ...
