Results 21 to 30 of about 3,829,483 (294)
Applying Genetic Programming to the Problem of Term Weight Algorithms [PDF]
, 2000 This article investigates the use of the technique of Genetic Programming to the generation of term weight algorithms. It represents an initial study into attempting to reproduce standard algorithms and to evolving new algorithms based on user rankings ...
Wade, Steve +2 more
core +4 more sources
Genetic algorithm and application
ScienceOpen Research, 2023 Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. They are considered as a search-based technique based on the principles of Genetics and Natural Selection used in computing to find an exact or approximate solution for ...
Khuong Le, Tianyu Wei, Justin Tagalogon
openaire +1 more source
Identifying Patterns of Hospitalizations Among Childhood Cancer Survivors: A Population‐Based Study
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Childhood cancer survivors (CCSs) experience more hospitalizations than the general population. We aimed to identify distinct hospitalization patterns among Queensland CCSs and the associated characteristics. Methods Cases (aged ≤14 years) diagnosed between 1995 and 2019 while residents of Queensland were identified through the ...
Hai Pham +7 more
wiley +1 more source
Multidimensional crossover in genetic algorithms
Journal of Numerical Analysis and Approximation Theory, 1999 Not available.
Márton-Ernö Balázs
doaj +2 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Purpose To explore caregivers' experiences and perceptions of the nutritional challenges faced by children and adolescents undergoing cancer treatment, including oral intake and the use of nutritional support. Methods This was a qualitative study based on focus groups with parents and caregivers at a Brazilian pediatric oncology hospital ...
Danyelle Apparecida Balsamão Marques +5 more
wiley +1 more source
Variations of Genetic Algorithms
CoRR, 2019 The goal of this project is to develop the Genetic Algorithms (GA) for solving the Schaffer F6 function in fewer than 4000 function evaluations on a total of 30 runs. Four types of Genetic Algorithms (GA) are presented - Generational GA (GGA), Steady-State (mu+1)-GA (SSGA), Steady-Generational (mu,mu)-GA (SGGA), and (mu+mu)-GA.
Alison Jenkins +3 more
openaire +2 more sources
On the practical genetic algorithms [PDF]
Proceedings of the 7th annual conference on Genetic and evolutionary computation, 2005 This paper offers practical design-guidelines for developing efficient genetic algorithms (GAs) to successfully solve real-world problems. As an important design component, a practical population-sizing model is presented and verified.
Chang Wook Ahn +2 more
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Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Introduction Peritoneal dialysis (PD) is an established home‐based kidney replacement therapy (KRT), but its uptake remains low in Japan. We evaluated whether individualized education in a dedicated outpatient clinic was associated with the initiation of PD.
Yasuko Ito +7 more
wiley +1 more source
Engineering peptides into antibodies—opportunities and strategies for therapeutic innovation
FEBS Letters, EarlyView.Peptides and antibodies occupy complementary therapeutic niches. Peptides recognize difficult targets in a compact format, while antibodies add specificity, long half‐life, and effector functions. This review examines strategies that merge both modalities—peptide grafting into loops, terminal and Fc fusions, and bioconjugation—highlighting how ...
Jinling Wang +2 more
wiley +1 more source
UNIFORM POPULATION IN GENETIC ALGORITHMS
Electrica, 2002 The most of researchers dealing with genetic algorithms apply variation on the genetic operators. Some of them propose new genetic algotihm types. However, none of them deals with generating population of good quality, initially.
Ali KARCI, Ahmet ARSLAN
doaj +2 more sources