New machine learning-based prediction models for fracture energy of asphalt mixtures
This paper presents innovative machine learning methods called gene expression
programming (GEP) and hybrid artificial neural network/simulated annealing (ANN/SA) to …
programming (GEP) and hybrid artificial neural network/simulated annealing (ANN/SA) to …
A cross-benchmark comparison of 87 learning to rank methods
N Tax, S Bockting, D Hiemstra - Information processing & management, 2015 - Elsevier
Learning to rank is an increasingly important scientific field that comprises the use of
machine learning for the ranking task. New learning to rank methods are generally …
machine learning for the ranking task. New learning to rank methods are generally …
New machine learning prediction models for compressive strength of concrete modified with glass cullet
Purpose Recycled waste glasses have been widely used in Portland cement and concrete
as aggregate or supplementary cementitious material. Compressive strength is one of the …
as aggregate or supplementary cementitious material. Compressive strength is one of the …
Mobility prediction in mobile wireless networks
JA Torkestani - Journal of Network and Computer Applications, 2012 - Elsevier
In realistic mobile ad-hoc network scenarios, the hosts usually travel to the pre-specified
destinations, and often exhibit non-random motion behaviors. In such mobility patterns, the …
destinations, and often exhibit non-random motion behaviors. In such mobility patterns, the …
Last-position elimination-based learning automata
An update scheme of the state probability vector of actions is critical for learning automata
(LA). The most popular is the pursuit scheme that pursues the estimated optimal action and …
(LA). The most popular is the pursuit scheme that pursues the estimated optimal action and …
An adaptive bi-flight cuckoo search with variable nests for continuous dynamic optimization problems
This paper presents an adaptive bi-flight cuckoo search algorithm for continuous dynamic
optimization problems. Unlike the standard cuckoo search which relies on Levy flight, the …
optimization problems. Unlike the standard cuckoo search which relies on Levy flight, the …
Finding minimum weight connected dominating set in stochastic graph based on learning automata
JA Torkestani, MR Meybodi - Information Sciences, 2012 - Elsevier
Finding the minimum weight connected dominating set (MCDS) in an arbitrary graph is an
NP-hard problem and several heuristics and approximation methods have been proposed to …
NP-hard problem and several heuristics and approximation methods have been proposed to …
An adaptive energy-efficient area coverage algorithm for wireless sensor networks
JA Torkestani - Ad hoc networks, 2013 - Elsevier
The connected dominating set (CDS) concept has recently emerged as a promising
approach to the area coverage in wireless sensor network (WSN). However, the major …
approach to the area coverage in wireless sensor network (WSN). However, the major …
Incorporation of optimal computing budget allocation for ordinal optimization into learning automata
J Zhang, C Wang, D Zang… - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
A learning automaton (LA) is a powerful tool for reinforcement learning. Its action probability
vector plays two roles: 1) deciding when it converges, ie, total computing budget it has used …
vector plays two roles: 1) deciding when it converges, ie, total computing budget it has used …
User behavior analysis-based smart energy management for webpage ranking: Learning automata-based solution
Search engines are widely used for surfing the Internet. Different search engines vary with
respect to their accuracy and time to fetch the information from the distributed/centralized …
respect to their accuracy and time to fetch the information from the distributed/centralized …