Titlebook: Optimization and Learning; Third International Bernabé Dorronsoro,Patricia Ruiz,El-Ghazali Talbi Conference proceedings 2020 Springer Natu

JAMB

Learning Variables Structure Using Evolutionary Algorithms to Improve Predictive Performance However, most of these works are based on simple linear models (or variations) or do make the assumption of knowing a pre-defined variable grouping structure in advance, something that will not always be possible. This paper presents a hybrid genetic algorithm and machine learning approach which ai

Collision

Nausea

Intelligent Electric Drive Management for Plug-in Hybrid Busesen they are frequently charged, they also enable societal benefits (emissions- and noise-related) associated with electric buses. Thanks to geofencing, pure electric drive of PH buses can be assigned to specific locations via a back-office system. As a result, PH buses not only can fulfil zero-emiss

Limerick

A Heuristic Algorithm for the Set k-Cover Problemhile the coverage cost is minimized. The case of . refers to the classical SCP. SkCP has many applications including in computational biology. We develop a simple and effective heuristic for both weighted and unweighted SkCP. In the weighted SkCP, there is a cost associated with a column and in the

hypertension

東西

畸形

Learning Patterns for Complex Event Detection in Robot Sensor Datadata is recorded. The sensor data recordings are classified in terms of events or outcomes that characterize the task. These classified recordings are then used to learn simple rules that describe the events using a simple, domain specific language, in a human-readable and interpretable way.

incontinence

hauteur

A Capacity-Enhanced Local Search for the 5G Cell Switch-off Problem and it is also clearly in conflict with one of the target design requirements of 5G systems: a 90% reduction of the power consumption. In order to address this issue, switching off a number of SBSs in periods of low traffic demand has been standardized as an recognized strategy to save energy. But

licence

Clustering a 2d Pareto Front: P-center Problems Are Solvable in Polynomial Timep-center problems, both in the discrete and continuous versions, become solvable with a dynamic programming algorithm. Having . points, the complexity of clustering is . (resp. .) time and .(.) memory space for the continuous (resp. discrete) .-center problem for ., and in . time for such 2-center p