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Toplam kayıt 27, listelenen: 11-20
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 ...
Iris Segmentation in Uncooperative and Unconstrained Environments: State-of-the-art, Datasets and Future Research Directions
(Elsevier, 2021)
Most of the classical iris recognition systems require cooperation from users and assume ideal conditions during iris image acquisition. In uncooperative and unconstrained environments, the performance of these classical ...
An Adaptive Feature Extraction Method for Classification of Covid-19 X-Ray Images
(Springer Science and Business Media Deutschland GmbH, 2022)
This study aims to detect Covid-19 disease in the fastest and most accurate way from X-ray images by developing a new
feature extraction method and deep learning model . Partitioned Tridiagonal Enhanced Multivariance ...
Bi-criteria Simulated Annealing for the Curriculum-based Course Timetabling Problem With Robustness Approximation
(Springer, 2022)
In the process of developing a university’s weekly course timetable, changes in the data, such as the available time periods
of professors or rooms, render the timetable infeasible, requiring the administrators to repair ...
Maximizing Coverage and Maintaining Connectivity in WSN and Decentralized Iot: An Efficient Metaheuristic-Based Method for Environment-Aware Node Deployment
(Springer, 2022)
The node deployment problem is a non-deterministic polynomial time (NP-hard). This study proposes a new and efficient
method to solve this problem without the need for predefined circumstances about the environments ...
DeepCAN: A Modular Deep Learning System for Automated Cell Counting and Viability Analysis
(IEEE, 2022)
Precise and quick monitoring of key cytometric features such as cell count, cell size, cell morphology,
and DNA content is crucial for applications in biotechnology, medical sciences, and cell culture research. Traditionally, ...
A Novel Intelligent Traffic Recovery Model for Emergency Vehicles Based on Context-aware Reinforcement Learning
(Elsevier, 2023)
Management of traffic emergencies has become very popular in recent years. However,
timely response to emergencies and recovering from an emergency is an important prob-
lem in itself. The strategies in the current ...
PSCSO: Enhanced Sand Cat Swarm Optimization Inspired by the Political System to Solve Complex Problems
(Elsevier, 2023)
The Sand Cat Swarm Optimization (SCSO) algorithm is a recently introduced metaheuristic with balanced
behavior in the exploration and exploitation phases. However, it is not fast in convergence and may not be
successful ...
Dynamic Multi-Objective Evolutionary Algorithms in Noisy Environments
(Elsevier, 2023)
Real-world multi-objective optimization problems encounter different types of uncertainty that
may affect the quality of solutions. One common type is the stochastic noise that contaminates
the objective functions. Another ...