Results 81 to 90 of about 5,670,636 (381)
Implementation Aspects Regarding Closed-Loop Control Systems Using Evolutionary Algorithms
When an optimal control problem requires an important computational effort, a metaheuristic algorithm (MA) can be a useful approach. An MA is conceived to solve a specific optimal control problem having a characteristic objective function. This algorithm
Viorel Minzu, Saïd Riahi, Eugen Rusu
doaj +1 more source
This article advocates integrating temporal dynamics into cancer research. Rather than relying on static snapshots, researchers should increasingly consider adopting dynamic methods—such as live imaging, temporal omics, and liquid biopsies—to track how tumors evolve over time.
Gautier Follain+3 more
wiley +1 more source
Epigenetic opportunities for Evolutionary Computation [PDF]
Evolutionary Computation is a group of biologically inspired algorithms used to solve complex optimisation problems. It can be split into Evolutionary Algorithms, which take inspiration from genetic inheritance, and Swarm Intelligence algorithms, that take inspiration from cultural inheritance. However, recent developments have focused on computational
arxiv
Stability of evolutionary algorithms
AbstractWe prove under mild conditions the convergence of some evolutionary algorithm to the solution of the global optimization problem. In the proof, the Lyapunov function's techniques is applied to some semi-dynamical system generated by a Foias operator on the space of the probability measures defined on the set of admissible solutions.
openaire +3 more sources
This study used longitudinal transcriptomics and gene‐pattern classification to uncover patient‐specific mechanisms of chemotherapy resistance in breast cancer. Findings reveal preexisting drug‐tolerant states in primary tumors and diverse gene rewiring patterns across patients, converging on a few dysregulated functional modules. Despite receiving the
Maya Dadiani+14 more
wiley +1 more source
An Analytic Expression of Relative Approximation Error for a Class of Evolutionary Algorithms [PDF]
An important question in evolutionary computation is how good solutions evolutionary algorithms can produce. This paper aims to provide an analytic analysis of solution quality in terms of the relative approximation error, which is defined by the error between 1 and the approximation ratio of the solution found by an evolutionary algorithm.
arxiv +1 more source
On the Analysis of Evolutionary Algorithms [PDF]
There is a lot of experimental evidence that crossover is, for some functions, an essential operator of evolutionary algorithms. Nevertheless, it was an open problem to prove for some function that an evolutionary algorithm using crossover is essentially more efficient than evolutionary algorithms without crossover.
Jansen, Thomas, Wegener, Ingo
openaire +2 more sources
This paper is concerned with the co-existence of different synchronization types for fractional-order discrete-time chaotic systems with different dimensions.
Samir Bendoukha+6 more
doaj +1 more source
B‐cell chronic lymphocytic leukemia (B‐CLL) and monoclonal B‐cell lymphocytosis (MBL) show altered proteomes and phosphoproteomes, analyzed using mass spectrometry, protein microarrays, and western blotting. Identifying 2970 proteins and 316 phosphoproteins, including 55 novel phosphopeptides, we reveal BCR and NF‐kβ/STAT3 signaling in disease ...
Paula Díez+17 more
wiley +1 more source
Runtime Analysis of Competitive co-Evolutionary Algorithms for Maximin Optimisation of a Bilinear Function [PDF]
Co-evolutionary algorithms have a wide range of applications, such as in hardware design, evolution of strategies for board games, and patching software bugs. However, these algorithms are poorly understood and applications are often limited by pathological behaviour, such as loss of gradient, relative over-generalisation, and mediocre objective stasis.
arxiv