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All Outputs (101)

Building collaboration in multi-agent systems using reinforcement learning (2018)
Journal Article
Aydin, M. E., & Fellows, R. (2018). Building collaboration in multi-agent systems using reinforcement learning. Lecture Notes in Artificial Intelligence, 11056 LNAI, 201-212. https://doi.org/10.1007/978-3-319-98446-9_19

© Springer Nature Switzerland AG 2018. This paper presents a proof-of concept study for demonstrating the viability of building collaboration among multiple agents through standard Q learning algorithm embedded in particle swarm optimisation. Collabo... Read More about Building collaboration in multi-agent systems using reinforcement learning.

A parametric study for congestion control in queuing networks (2017)
Conference Proceeding
Malik, M. H., Majeed, A., Aydin, M. E., & Malik, M. H. (2017). A parametric study for congestion control in queuing networks. In ICFNDS '17: Proceedings of the International Conference on Future Networks and Distributed Systems. https://doi.org/10.1145/3102304.3105574

Congestion avoidance mechanisms are used to prevent the saturation of the bottleneck under mean-field domain where large numbers of TCP connections interact with one another. It is clear that selections of parameters play an important role on the per... Read More about A parametric study for congestion control in queuing networks.

Cognitive access point to handle delay sensitive traffic in WLANs (2015)
Conference Proceeding
Aydin, M., Malik, M. H., Aydin, M. E., & Awais, Q. (2015). Cognitive access point to handle delay sensitive traffic in WLANs. In 2015 IEEE International Conference on Computational Intelligence & Communication Technology (317-322). https://doi.org/10.1109/CICT.2015.137

© 2015 IEEE. Over the last few years, the widespread use of wireless local area networks (WLANs) continues to gain more and more impetus. Due to the increase in variety of multimedia applications such as voice, video and gaming traffic, it is paramou... Read More about Cognitive access point to handle delay sensitive traffic in WLANs.

Creep modelling of polypropylenes using artificial neural networks trained with Bee algorithms (2015)
Journal Article
Esen, I., Düʇenci, M., Düğenci, M., Aydemir, A., Esen, İ., & Aydin, M. E. (2015). Creep modelling of polypropylenes using artificial neural networks trained with Bee algorithms. Engineering Applications of Artificial Intelligence, 45, 71-79. https://doi.org/10.1016/j.engappai.2015.06.016

© 2015 Elsevier Ltd. All rights reserved. Polymeric materials, being capable of high mouldability, usability of long lifetime up to 50 years and availability at low cost properties compared to metallic materials, are in demand but finite element-base... Read More about Creep modelling of polypropylenes using artificial neural networks trained with Bee algorithms.

Stochastic model of TCP and UDP traffic in IEEE 802.11b/g (2014)
Conference Proceeding
Malik, M. H., Aydin, M., Shah, Z., & Hussain, S. (2014). Stochastic model of TCP and UDP traffic in IEEE 802.11b/g. In 2014 9th IEEE Conference on Industrial Electronics and Applications. , (2170-2175). https://doi.org/10.1109/ICIEA.2014.6931531

© 2014 IEEE. IEEE 802.11 networks have been widely explored since last decade and IEEE802.11g was proposed to increase the data rate of wireless networks up to 54Mbps which ensure backward capability with IEEE802.11b. The main goal of increasing the... Read More about Stochastic model of TCP and UDP traffic in IEEE 802.11b/g.

A memory-integrated artificial bee algorithm for 1-D bin packing problems (2014)
Presentation / Conference
Bayraktar, T., Aydin, M. E., & Dugenci, M. (2014, October). A memory-integrated artificial bee algorithm for 1-D bin packing problems. Paper presented at CIE 2014 - 44th International Conference on Computers and Industrial Engineering and IMSS 2014 - 9th International Symposium on Intelligent Manufacturing and Service Systems, Istanbul, Turkey

Swarm intelligence algorithms gain more attention with ever growing computing capabilities since they can provide diverse and useful solutions for ill-structured and complex problems. Artificial Bee Colony (ABC) algorithm is a recently developed prom... Read More about A memory-integrated artificial bee algorithm for 1-D bin packing problems.

Adaptive proportional fair parameterization based LTE scheduling using continuous actor-critic reinforcement learning (2014)
Conference Proceeding
Comsa, I. S., Zhang, S., Aydin, M., Chen, J., Kuonen, P., & Wagen, J. F. (2014). Adaptive proportional fair parameterization based LTE scheduling using continuous actor-critic reinforcement learning. In 2014 IEEE Global Communications Conference (4387-4393). https://doi.org/10.1109/GLOCOM.2014.7037498

© 2014 IEEE. Maintaining a desired trade-off performance between system throughput maximization and user fairness satisfaction constitutes a problem that is still far from being solved. In LTE systems, different tradeoff levels can be obtained by usi... Read More about Adaptive proportional fair parameterization based LTE scheduling using continuous actor-critic reinforcement learning.

Scheduling policies based on dynamic throughput and fairness tradeoff control in LTE-A networks (2014)
Conference Proceeding
Comşa, I. S., Aydin, M., Zhang, S., Kuonen, P., Wagen, J. F., & Lu, Y. (2014). Scheduling policies based on dynamic throughput and fairness tradeoff control in LTE-A networks. In 39th Annual IEEE Conference on Local Computer Networks (418-421). https://doi.org/10.1109/LCN.2014.6925806

© 2014 IEEE. In LTE-A cellular networks there is a fundamental trade-off between the cell throughput and fairness levels for preselected users which are sharing the same amount of resources at one transmission time interval (TTI). The static paramete... Read More about Scheduling policies based on dynamic throughput and fairness tradeoff control in LTE-A networks.

ITU-R and WINNER II path loss modeling of femtocells (2013)
Presentation / Conference
Kpojime, H. O., Safdar, G. A., & Aydin, M. E. (2013, November). ITU-R and WINNER II path loss modeling of femtocells. Presented at HET-NETs 2013, The 7th International Working Conference, Ilkley, West Yorkshire, UK

As cellular network users continue to grow; there is a need for in-creased user capacity, higher throughput and improved system performance. An important issue affecting cellular networks is to make services available to re-gions of bad or no recepti... Read More about ITU-R and WINNER II path loss modeling of femtocells.

Refining scheduling policies with genetic algorithms (2013)
Conference Proceeding
Aydin, M. E., Ogur, E., & Aydin, M. E. (2013). Refining scheduling policies with genetic algorithms. In Proceeding of the fifteenth annual conference companion on Genetic and evolutionary computation conference companion - GECCO '13 Companion (1513-1518). https://doi.org/10.1145/2464576.2482730

Genetic Algorithms (GAs) are popular approaches in solving various complex real-world problems. However, it is required that a careful attention is to be paid to the contextual knowledge as well as the implementation of genetic material and operators... Read More about Refining scheduling policies with genetic algorithms.

A novel learning-based spectrum sensing technique for cognitive radio networks (2013)
Conference Proceeding
Aydin, M. E., Aydin, M. E., Safdar, G. A., & Aslam, N. (2013). A novel learning-based spectrum sensing technique for cognitive radio networks. In 2013 27th International Conference on Advanced Information Networking and Applications Workshops (505-510). https://doi.org/10.1109/WAINA.2013.64

Spectrum sensing is one of the most challenging issues in Cognitive Radio (CR) networks. It should be performed efficiently to reduce number of false alarms and missed detections. This paper presents a novel approach, which employs collective intelli... Read More about A novel learning-based spectrum sensing technique for cognitive radio networks.

A multi-agent based approach for change management in manufacturing enterprises (2013)
Journal Article
Ayhan, M. B., Aydin, M. E., & Öztemel, E. (2015). A multi-agent based approach for change management in manufacturing enterprises. Journal of Intelligent Manufacturing, 26(5), 975-988. https://doi.org/10.1007/s10845-013-0794-2

© 2013, Springer Science+Business Media New York. Change management becomes an unavoidable necessity for manufacturing enterprises. Since change in business processes carries significant impact on the performance of manufacturing companies, a change... Read More about A multi-agent based approach for change management in manufacturing enterprises.

A quantitative approach for measuring process innovation: A case study in a manufacturing company (2013)
Journal Article
Ayhan, M. B., Öztemel, E., Aydin, M. E., & Yue, Y. (2013). A quantitative approach for measuring process innovation: A case study in a manufacturing company. International Journal of Production Research, 51(11), 3463-3475. https://doi.org/10.1080/00207543.2013.774495

Process management and innovation arguably remain among the concepts under focus of recent researches since there is no significantly outstanding method to measure and monitor the level of innovation in the manufacturing processes over a particular t... Read More about A quantitative approach for measuring process innovation: A case study in a manufacturing company.

Heuristic-based neural networks for stochastic dynamic lot sizing problem (2013)
Journal Article
Aydin, M. E., Düǧenci, M., Şenyiǧgit, E., Şenyiğit, E., Düğenci, M., Aydin, M. E., & Zeydan, M. (2013). Heuristic-based neural networks for stochastic dynamic lot sizing problem. Applied Soft Computing, 13(3), 1332-1339. https://doi.org/10.1016/j.asoc.2012.02.026

Multi-period single-item lot sizing problem under stochastic environment has been tackled by few researchers and remains in need of further studies. It is mathematically intractable due to its complex structure. In this paper, an optimum lot-sizing p... Read More about Heuristic-based neural networks for stochastic dynamic lot sizing problem.

A hybrid swarm intelligence algorithm for multiuser scheduling in HSDPA (2013)
Journal Article
Aydin, M. E., Aydin, M. E., Kwan, R., Leung, C., Maple, C., & Zhang, J. (2013). A hybrid swarm intelligence algorithm for multiuser scheduling in HSDPA. Applied Soft Computing, 13(5), 2990-2996. https://doi.org/10.1016/j.asoc.2011.12.007

Multiuser scheduling is an important aspect in the performance optimization of a wireless network since it allows multiple users to access a shared channel efficiently by exploiting multiuser diversity. To perform efficient scheduling, channel state... Read More about A hybrid swarm intelligence algorithm for multiuser scheduling in HSDPA.

Multiuser scheduling on the LTE downlink with meta-heuristic approaches (2013)
Journal Article
Aydin, M. E., Aydin, M. E., Kwan, R., & Wu, J. (2013). Multiuser scheduling on the LTE downlink with meta-heuristic approaches. Physical Communication, 9, 257-265. https://doi.org/10.1016/j.phycom.2012.01.004

In this paper, the issue of multi-user radio resource scheduling on the downlink of a Long Term Evolution (LTE) cellular communication system is addressed. An optimization model has been proposed earlier, where radio resources for multiple users are... Read More about Multiuser scheduling on the LTE downlink with meta-heuristic approaches.

A novel dynamic Q-learning-based scheduler technique for LTE-advanced technologies using neural networks (2012)
Conference Proceeding
Sorin Comsa, I., Zhang, S., Aydin, M., Kuonen, P., & Wagen, J. F. (2012). A novel dynamic Q-learning-based scheduler technique for LTE-advanced technologies using neural networks. In 37th Annual IEEE Conference on Local Computer Networks (332-335). https://doi.org/10.1109/LCN.2012.6423642

The tradeoff concept between system capacity and user fairness attracts a big interest in LTE-Advanced resource allocation strategies. By using static threshold values for throughput or fairness, regardless the network conditions, makes the scheduler... Read More about A novel dynamic Q-learning-based scheduler technique for LTE-advanced technologies using neural networks.

Multi objective resource scheduling in LTE networks using reinforcement learning (2012)
Journal Article
Wagen, J. F., Comşa, I. S., Aydin, M., Zhang, S., & Kuonen, P. (2012). Multi objective resource scheduling in LTE networks using reinforcement learning. International Journal of Distributed Systems and Technologies, 3(2), 39-57. https://doi.org/10.4018/jdst.2012040103

The use of the intelligent packet scheduling process is absolutely necessary in order to make the radio resources usage more efficient in recent high-bit-rate demanding radio access technologies such as Long Term Evolution (LTE). Packet scheduling pr... Read More about Multi objective resource scheduling in LTE networks using reinforcement learning.