Results 121 to 130 of about 5,538,102 (159)

Contrasting Global and Patient-Specific Regression Models via a Neural Network Representation. [PDF]

Biom J
Behrens M, Stolz D, Papakonstantinou E, Nolde JM, Bellerino G, Rohde A, Hess M, Binder H.   +7 more
europepmc   +1 more source

Enhanced artificial satellite search algorithm with memory and evolutionary operator for PID controller parameter estimation. [PDF]

Sci Rep
Issa M.
europepmc   +1 more source

An enhanced Borg algorithmic framework for solving the hydro-thermal-wind Co-scheduling problem

Energy, 2021
Abstract An enhanced Borg (EBorg) algorithm has been proposed to solve the dual-objective short-term hydro-thermal-wind co-scheduling (HTW-CS) problem, aiming at minimizing the cost and emissions associated with electric power generation while satisfying various hydraulic and electric constraints.
Bin Ji, Binqiao Zhang, Samson S. Yu, Dezhi Zhang, Xiaohui Yuan   +4 more
openaire   +3 more sources

Scalability Analysis of the Asynchronous, Master-Slave Borg Multiobjective Evolutionary Algorithm

2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum, 2013
The Borg Multiobjective Evolutionary Algorithm (MOEA) is a new, efficient, and robust optimizer that outperforms competing optimization methods on numerous complex engineering problems. To date, the Borg MOEA has been successfully applied to problems ranging from aerospace applications to water resources engineering.
David Hadka, Kamesh Madduri, Patrick M. Reed   +2 more
openaire   +3 more sources

Benchmarking the Borg algorithm on the Biobjective bbob-biobj Testbed

Proceedings of the Companion Conference on Genetic and Evolutionary Computation, 2023
The Borg MOEA [8] is an optimization algorithm, designed to handle real-world problems of a multi objective and multimodal nature. In this report, we examine the effectiveness of Borg for solving optimization problems with only two objectives. To this end, we benchmark the performance of the algorithm on the bbob-biobj test suite via the COCO platform,
Dimo Brockhoff, Pascal Capetillo, Jonathan Hornewall, Raphael Walker   +3 more
openaire   +1 more source

Maximizing Social Influence in Nearly Optimal Time

ACM-SIAM Symposium on Discrete Algorithms, 2012
Diffusion is a fundamental graph process, underpinning such phenomena as epidemic disease contagion and the spread of innovation by word-of-mouth. We address the algorithmic problem of finding a set of k initial seed nodes in a network so that the ...
C. Borgs, Mickey Brautbar, J. Chayes, Brendan Lucier   +3 more
semanticscholar   +1 more source

Using VADER sentiment and SVM for predicting customer response sentiment

Expert systems with applications, 2020
Customer support is important to corporate operations, which involves dealing with disgruntled customer and content customers that can have different requirements. As such, it is important to quickly extract the sentiment of support errands.
Anton Borg, Martin Boldt
semanticscholar   +1 more source

Whole-genome-sequencing of triple negative breast cancers in a population-based clinical study

Nature Medicine, 2019
Whole-genome sequencing (WGS) brings comprehensive insights to cancer genome interpretation. To explore the clinical value of WGS, we sequenced 254 triple-negative breast cancers (TNBCs) for which associated treatment and outcome data were collected ...
J. Staaf, D. Głodzik, A. Bosch, J. Vallon-Christersson, C. Reuterswärd, J. Häkkinen, A. Degasperi, T. Amarante, L. Saal, C. Hegardt, Hilary Stobart, A. Ehinger, C. Larsson, L. Rydén, N. Loman, M. Malmberg, A. Kvist, H. Ehrencrona, Helen R. Davies, Å. Borg, S. Nik-Zainal   +20 more
semanticscholar   +1 more source

Triage, Machine Learning, Algorithms, and Becoming the Borg

Annals of Emergency Medicine, 2018
Stephen M, Schenkel, Robert L, Wears
openaire   +2 more sources