Results 81 to 90 of about 460,152 (328)
A Multi‐Objective Molecular Generation Method Based on Pareto Algorithm and Monte Carlo Tree Search
Pareto Monte Carlo Tree Search Molecular Generation (PMMG), a molecular generation approach leveraging Monte Carlo Tree Search (MCTS) and Pareto algorithm, efficiently explores the Pareto front in high‐dimensional objective spaces for multi‐objective drug design.
Yifei Liu+12 more
wiley +1 more source
STUDY ON THE EVOLUTION OF SOME FINANCIAL PRODUCTS BASED ON MARKOV CHAINS METHOD [PDF]
In probability theory it is known that Markov chain is frequently used in order to predict the future situations. Moreover, Markov chain theory is used to study the change rules of the economic phenomenons, to describe consumers’ brand loyalty, in ...
Marta Kovacs (Kiss)
doaj
DPImpute is a two‐step pipeline that outperforms existing tools in whole‐genome SNP imputation, particularly under conditions of ultra‐low coverage sequencing, small sample sizes, and limited references. It enables precise imputation for single blastocyst cells, supporting genomic selection at the pre‐implantation stage.
Weigang Zheng+11 more
wiley +1 more source
Abstract The brown treesnake (BTS) (Boiga irregularis) invasion on Guåhan (in English, Guam) led to the extirpation of nearly all native forest birds. In recent years, methods have been developed to reduce BTS abundance on a landscape scale. To help assess the prospects for the successful reintroduction of native birds to Guåhan following BTS ...
Robert M. McElderry+3 more
wiley +1 more source
Research on the uncertainty of wind power has a significant influence on power system planning and decision-making. This paper proposes a novel method for wind power interval forecasting based on rough sets theory, weighted Markov chain, and kernel ...
Xiyun Yang+3 more
doaj +1 more source
A Hopf-power Markov chain on compositions [PDF]
In a recent paper, Diaconis, Ram and I constructed Markov chains using the coproduct-then-product map of a combinatorial Hopf algebra. We presented an algorithm for diagonalising a large class of these "Hopf-power chains", including the Gilbert-Shannon ...
C.Y. Amy Pang
doaj +1 more source
The Importance Markov chain is a novel algorithm bridging the gap between rejection sampling and importance sampling, moving from one to the other through a tuning parameter. Based on a modified sample of an instrumental Markov chain targeting an instrumental distribution (typically via a MCMC kernel), the Importance Markov chain produces an extended ...
Charly Andral+3 more
openaire +3 more sources
CPL‐Diff: A Diffusion Model for De Novo Design of Functional Peptide Sequences with Fixed Length
This study presents a diffusion model for generating functional peptide sequence lengths using mask control. The model can generate antimicrobial, antifungal, and antiviral peptides with specific lengths on demand. The model learns the structure of peptides better and generates peptides with better physicochemical properties, and the model has good ...
Zhenjie Luo+5 more
wiley +1 more source
Switching Control of Closed-Loop Supply Chain Systems with Markov Jump Parameters
The switching system model of a closed-loop supply chain with Markov jump parameters is established. The system is modeled as a switching system with Markov jump parameters, taking into account the uncertainties of the process and the inventory decay ...
Huiming Wu, Sicong Guo
doaj +1 more source
Reduction of Markov chains with two-time-scale state transitions
In this paper, we consider a general class of two-time-scale Markov chains whose transition rate matrix depends on a parameter $\lambda>0$. We assume that some transition rates of the Markov chain will tend to infinity as $\lambda\rightarrow\infty$.
Jia, Chen
core +1 more source