Results 31 to 40 of about 12,241,994 (329)
Random Backtracking in Backtrack Search Algorithms for Satisfiability [PDF]
, 2007 This paper proposes the utilization of randomized backtracking within complete backtrack search algorithms for propositional satisfiability (SAT). In recent years, randomization has become pervasive in SAT algorithms.
Marques-Silva, J. +3 more
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Machine Learning and Knowledge Extraction, 2023 In an era characterised by rapid technological advancement, the application of algorithmic approaches to address complex problems has become crucial across various disciplines.
Samuel Corecco +2 more
doaj +1 more source
Ephemeral data derived potentials for random structure search [PDF]
Physical review B, 2022 Structure prediction has become a key task of the modern atomistic sciences, and depends on the rapid and reliable computation of the energy landscape. First principles density functional based calculations are highly reliable, faithfully describing the ...
Chris J. Pickard
semanticscholar +1 more source
Optimum Design of Reinforced Cylindrical Shells Under Combined Axial Compression and Internal Pressure [PDF]
Journal of Mechanical Engineering, 2021 This paper discusses the use of the random search method for the optimal design of single-layered rib-reinforced cylindrical shells under combined axial compression and internal pressure with account taken of the elastic-plastic material behavior.
Heorhii V. Filatov
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Weighted Random Search for Hyperparameter Optimization [PDF]
International Journal of Computers Communications & Control, 2019 We introduce an improved version of Random Search (RS), used here for hyperparameter optimization of machine learning algorithms. Unlike the standard RS, which generates for each trial new values for all hyperparameters, we generate new values for each ...
A. Florea, Razvan Andonie
semanticscholar +1 more source
Search for the smallest random forest [PDF]
Statistics and Its Interface, 2009 Random forests have emerged as one of the most commonly used nonparametric statistical methods in many scientific areas, particularly in analysis of high throughput genomic data. A general practice in using random forests is to generate a sufficiently large number of trees, although it is subjective as to how large is sufficient.
Heping, Zhang, Minghui, Wang
openaire +2 more sources
Random Search Hyperparameter Optimization for BPNN to Forecasting Cattle Population [PDF]
E3S Web of ConferencesBackpropagation Neural Network (BPNN) is a suitable method for predicting the future. It has weaknesses, namely poor convergence speed and instability, requiring parameter tuning to overcome speed problems, and having a high bias.
Khotimah Bain Khusnul +6 more
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Searching for nodes in random graphs [PDF]
Physical Review E, 2011 We consider the problem of searching for a node on a labelled random graph according to a greedy algorithm that selects a route to the desired node using metric information on the graph. Motivated by peer-to-peer networks two types of random graph are proposed with properties particularly amenable to this kind of algorithm.
openaire +3 more sources
Time Series Forecasting of Motor Bearing Vibration Based on Informer
Sensors, 2022 Electric energy, as an economical and clean energy, plays a significant role in the development of science and technology and the economy. The motor is the core equipment of the power station; therefore, monitoring the motor vibration and predicting time
Zhengqiang Yang +3 more
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Towards large scale continuous EDA: a random matrix theory perspective [PDF]
, 2013 Estimation of distribution algorithms (EDA) are a major branch of evolutionary algorithms (EA) with some unique advantages in principle. They are able to take advantage of correlation structure to drive the search more efficiently, and they are able to ...
Kabán, Ata +5 more
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