Results 41 to 50 of about 174,883 (339)
Time and Individual Duration in Genetic Programming
IEEE Access, 2020 This paper presents a new way of measuring complexity in variable-size-chromosome-based evolutionary algorithms. Dealing with complexity is particularly useful when considering bloat in Genetic Programming.
Francisco Fernandez de Vega +7 more
doaj +1 more source
A Comparison of Cartesian Genetic Programming and Linear Genetic Programming [PDF]
, 2008 Two prominent genetic programming approaches are the graph-based Cartesian Genetic Programming (CGP) and Linear Genetic Programming (LGP). Recently, a formal algorithm for constructing a directed acyclic graph (DAG) from a classical LGP instruction sequence has been established.
Garnett Wilson, Wolfgang Banzhaf
openaire +2 more sources
Looking for Prototypes by Genetic Programming [PDF]
, 2006 In this paper we propose a new genetic programming based approach for prototype generation in Pattern Recognition problems. Prototypes consist of mathematical expressions and are encoded as derivation trees. The devised system is able to cope with classification problems in which the number of prototypes is not a priori known.
L. P. CORDELLA +3 more
openaire +4 more sources
FoxO1 signaling in B cell malignancies and its therapeutic targeting
FEBS Letters, EarlyView.FoxO1 has context‐specific tumor suppressor or oncogenic character in myeloid and B cell malignancies. This includes tumor‐promoting properties such as stemness maintenance and DNA damage tolerance in acute leukemias, or regulation of cell proliferation and survival, or migration in mature B cell malignancies.
Krystof Hlavac +3 more
wiley +1 more source
A comparison of machine learning techniques for survival prediction in breast cancer
BioData Mining, 2011 Background The ability to accurately classify cancer patients into risk classes, i.e. to predict the outcome of the pathology on an individual basis, is a key ingredient in making therapeutic decisions.
Vanneschi Leonardo +5 more
doaj +1 more source
Hydropower Unit Commitment Using a Genetic Algorithm with Dynamic Programming
Energies, 2023 This study presents a genetic algorithm integrated with dynamic programming to address the challenges of the hydropower unit commitment problem, which is a nonlinear, nonconvex, and discrete optimization, involving the hourly scheduling of generators in ...
Shuangquan Liu +6 more
doaj +1 more source
Iterative Genetic Improvement: Scaling Stochastic Program Synthesis [PDF]
arXiv, 2022 Program synthesis aims to {\it automatically} find programs from an underlying programming language that satisfy a given specification. While this has the potential to revolutionize computing, how to search over the vast space of programs efficiently is an unsolved challenge in program synthesis.
arxiv
FEBS Letters, EarlyView.Metabolic dysfunction‐associated steatotic liver disease (MASLD) affects nearly one‐third of the global population and poses a significant risk of progression to cirrhosis or liver cancer. Here, we discuss the roles of hepatic dendritic cell subtypes in MASLD, highlighting their distinct contributions to disease initiation and progression, and their ...
Camilla Klaimi +3 more
wiley +1 more source
Multi Expression Programming for solving classification problems [PDF]
arXiv, 2022 Multi Expression Programming (MEP) is a Genetic Programming variant which encodes multiple solutions in a single chromosome. This paper introduces and deeply describes several strategies for solving binary and multi-class classification problems within the \textit{multi solutions per chromosome} paradigm of MEP.
arxiv
Insights into PI3K/AKT signaling in B cell development and chronic lymphocytic leukemia
FEBS Letters, EarlyView.This Review explores how the phosphoinositide 3‐kinase and protein kinase B pathway shapes B cell development and drives chronic lymphocytic leukemia, a common blood cancer. It examines how signaling levels affect disease progression, addresses treatment challenges, and introduces novel experimental strategies to improve therapies and patient outcomes.
Maike Buchner
wiley +1 more source