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Reliability-based design optimization under dependent random variables by a generalized polynomial chaos expansion
This article brings forward a new computational method for reliability-based design optimization (RBDO) of complex mechanical systems subject to...
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Generalizing Univariate Predictive Mean Matching to Impute Multiple Variables Simultaneously
Predictive mean matching (PMM) is an easy-to-use and versatile univariate imputation approach. It is robust against transformations of the incomplete...
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Random Processes
This chapter discusses some important basic results on the theory of random processes. The field generated by typical light sources is not...
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Success-History Based Adaptive Differential Evolution Algorithm for Discrete Structural Optimization
Discrete structural optimization is generally regarded as a complicated optimization problem due to the presence of discrete variables. However,...
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Multiple Random Variables and Their Characteristics
This chapter is devoted to multiple random variables (mainly two variables). The transformation of two variables is presented initially by expanding...
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Detectability of Discrete-Time Mean-Field Linear Stochastic Systems with Periodic Coefficients
This paper is concerned with the detectability of discrete-time mean-field linear systems with periodic coefficients and multiplicative noise. By use...
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High-dimensional Bayesian Design Optimization Over Mixed Variables
Bayesian Optimization (BO) has gained considerable popularity as an effective technique for optimizing black-box functions that are expensive to...
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Study on the influence of seismic intensity on the mechanical properties of ballast bed based on discrete element method
To explore the impact of seismic intensity on the working performance of ballasted track bed, the seismic acceleration corresponding to earthquakes...
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Stochastic efficient global optimization with high noise variance and mixed design variables
Engineering design and optimization commonly require the minimization of expected value functions with high noise variance and mixed/discrete design...
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Prediction of the concrete compressive strength using improved random forest algorithm
Concrete is one of the most widely used materials in the construction industry. The most common parameter to achieve the quality and strength of...
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Optimal design of frame structures with mixed categorical and continuous design variables using the Gumbel–Softmax method
In optimizing real-world structures, due to fabrication or budgetary restraints, the design variables may be restricted to a set of standard...
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Discrete Marine Predators Algorithm for Symmetric Travelling Salesman Problem
This paper addresses the well-known NP-hard problem, the Symmetric Travelling Salesman Problem (STSP), which has numerous applications in logistics...
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A Calibration Method for Random Models with Dependent Random Parameters: The Applied Case of Tumor Growth
In the real world, multiple dynamic biological phenomena present an intrinsic randomness due to their nature. One of the most common ways of modeling...
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Regulation Control for Discrete-time Stochastic Nonlinear Active Suspension
The regulation problem of discrete-time stochastic nonlinear active suspension is considered in this paper. Firstly, a stability theorem of...
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Entropy Modeling of Random Vectors in the Presence of Discrete Components
Entropy modeling is widely used in the study of open stochastic systems in various fields. However, when using differential entropy to model...
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Random Samples
Probability theory is an efficient tool in order to analyze physical systems including random nature. The randomness property could be arise due to...
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DBHC: Discrete Bayesian HMM Clustering
Sequence data mining has become an increasingly popular research topic as the availability of data has grown rapidly over the past decades. Sequence...
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Hyperchaotic bilateral random low-rank approximation random sequence generation method and its application on compressive ghost imaging
Hyperchaotic systems have been widely used in the field of communication and information security to generate random numbers due to their super-long...
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Periodic Event-triggered Consensus of Multiagent Systems Under Random Packet Dropouts
In this paper, the periodic event-triggered consensus problem for linear multiagent systems (MASs) with random packet dropouts in a generic directed...
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Random Variables and Random Processes
Show that the magnitude of the correlation coefficient \(|\rho |\) is always less than or equal to unity.