Results 51 to 60 of about 786,097 (340)
Evolutionary Synthesis of HVAC System Configurations: Algorithm Development. [PDF]
, 2008 This paper describes the development of an optimization procedure for the synthesis of novel heating, ventilating, and air-conditioning (HVAC) system configurations. Novel HVAC system designs can be synthesized using model-based optimization methods. The
Angelov, Plamen +4 more
core +3 more sources
A New DG Multiobjective Optimization Method Based on an Improved Evolutionary Algorithm
Journal of Applied Mathematics, 2013 A distribution generation (DG) multiobjective optimization method based on an improved Pareto evolutionary algorithm is investigated in this paper. The improved Pareto evolutionary algorithm, which introduces a penalty factor in the objective function ...
Wanxing Sheng +4 more
doaj +1 more source
An Investigation Into the use of Swarm Intelligence for an Evolutionary Algorithm Optimisation; The Optimisation Performance of Differential Evolution Algorithm Coupled with Stochastic Diffusion Search [PDF]
, 2011 The integration of Swarm Intelligence (SI) algorithms and Evolutionary algorithms (EAs) might be one of the future approaches in the Evolutionary Computation (EC).
al-Rifaie, Mohammad Majid +2 more
core
An adaptation reference-point-based multiobjective evolutionary algorithm [PDF]
, 2019 The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.It is well known that maintaining a good balance between convergence and diversity is crucial to the ...
Fu, Liuwei +6 more
core +1 more source
Parameter Control in Evolutionary Algorithms [PDF]
, 2007 The issue of setting the values of various parameters of an evolutionary algorithm is crucial for good performance. In this paper we discuss how to do this, beginning with the issue of whether these values are best set in advance or are best changed during evolution. We provide a classification of different approaches based on a number of complementary
Eiben, Aguston +3 more
openaire +8 more sources
Molecular Oncology, EarlyView.Circulating tumor DNA (ctDNA) offers a possibility for different applications in early and late stage breast cancer management. In early breast cancer tumor informed approaches are increasingly used for detecting molecular residual disease (MRD) and early recurrence. In advanced stage, ctDNA provides a possibility for monitoring disease progression and
Eva Valentina Klocker +14 more
wiley +1 more source
Combination of Evolutionary Algorithms with Experimental Design, Traditional Optimization and Machine Learning [PDF]
, 2016 Evolutionary algorithms alone cannot solve optimization problems very efficiently since there are many random (not very rational) decisions in these algorithms.
Zhang, Qingfu
core
Autonomous Evolutionary Algorithm [PDF]
, 2010 Evolutionary algorithms (EA) are randomized heuristic search methods based on the principles of natural evolution (Banzhaf et al., 1998; Goldberg, 1989; Holland, 1975; Back, 1996; Koza, 1992). If we know how to describe the problem using the terminology of artificial evolution, the EAs are quite easy to apply.
openaire +4 more sources
Molecular Oncology, EarlyView.The authors applied joint/mixed models that predict mortality of trifluridine/tipiracil‐treated metastatic colorectal cancer patients based on circulating tumor DNA (ctDNA) trajectories. Patients at high risk of death could be spared aggressive therapy with the prospect of a higher quality of life in their remaining lifetime, whereas patients with a ...
Matthias Unseld +7 more
wiley +1 more source
Molecular Oncology, EarlyView.Breast tumor samples scored for metabolic deregulation (M1 to M3) were given a hypoxia score (HS). The highest HS occurred in patients with strongest metabolic deregulation (M3), supporting tumor aggressiveness. HS correlated with the highest number of metabolic pathways in M1. This suggests hypoxia to be an early event in metabolic deregulation.
Raefa Abou Khouzam +2 more
wiley +1 more source