Search
Search Results
-
A Modified Bayesian Optimization Approach for Determining a Training Set to Identify the Best Genotypes from a Candidate Population in Genomic Selection
Training set optimization is a crucial factor affecting the probability of success for plant breeding programs using genomic selection....
-
Combination of optimization-free kriging models for high-dimensional problems
Kriging metamodeling (also called Gaussian Process regression) is a popular approach to predict the output of a function based on few observations....
-
SFU: Surface-Free Utility-Based Design for Dose Optimization in Cancer Drug Combination Trials
Precision oncology has demonstrated the potential of drug combinations in effectively enhancing anti-tumor efficiency and controlling disease...
-
Dynamic Kernel Clustering by Spider Monkey Optimization Algorithm
In data, analysis clustering plays a major role. In the past decade varieties of clustering algorithms are proposed and produced better results. But...
-
Density Peak Clustering Using Grey Wolf Optimization Approach
Density peak clustering (DPC) finds the center of the cluster as the point with high density and a large distance from the center of the other...
-
Surrogate Models for Optimization of Dynamical Systems
Surrogate models using a suitable orthogonal decomposition and radial basis functions have been proposed by many researchers to reduce the...
-
Optimization of Redundancy Allocation Problem Using Quantum Particle Swarm Optimization Algorithm Under Uncertain Environment
Reliability optimization of a redundancy allocation problem is an important area of research in the literature. The main purpose of this type of...
-
Reliability in Portfolio Optimization using Uncertain Estimates
Portfolio optimization problems are rather easy to solve if one assumes normality of the (joint) distribution of returns with given parameters and a...
-
Black-box optimization on hyper-rectangle using Recursive Modified Pattern Search and application to ROC-based Classification Problem
In statistics, it is common to encounter multi-modal and non-smooth likelihood (or objective function) maximization problems, where the parameters...
-
Determination of optimal prevention strategy for COVID-19 based on multi-agent simulation
This study proposes a direction for the utilization of multi-agent simulation (MAS) to consider an optimal prevention strategy for the spread of the...
-
Reliability and Optimization for k-out-of-n: G Mixed Standby Retrial System with Dependency and J-Vacation
Based on the design and potential application of wind-solar storage intelligent power generation systems in engineering practice, this paper develops...
-
Stochastic and Physics-Based Simulation of Extreme Situations
This chapter addresses two alternative approaches to extreme situations, which may be useful when the lack of extreme observations severely limits...
-
Batch sequential adaptive designs for global optimization
Efficient global optimization (EGO) is one of the most popular sequential adaptive design (SAD) methods for expensive black-box optimization...
-
Bivariate Block and Basu’s Exponential Distribution Through Entropy Optimization and Its Application to Rainfall Data
The q-bivariate Block and Basu’s exponential distribution (q-BBBED) is a generalized version of the bivariate Block and Basu’s exponential...
-
Prescriptive Analytics: Optimization and Modeling
Prescriptive analytics, a type of complex business analytics, aims to suggest the best among various decision options to benefit from the predicted...
-
A comparison of optimization solvers for log binomial regression including conic programming
Relative risks are estimated to assess associations and effects due to their ease of interpretability, e.g., in epidemiological studies. Fitting...
-
Sparse reduced-rank regression for simultaneous rank and variable selection via manifold optimization
We consider the problem of constructing a reduced-rank regression model whose coefficient parameter is represented as a singular value decomposition...
-
Bayesian Optimization Approaches for Identifying the Best Genotype from a Candidate Population
Bayesian optimization is incorporated into genomic prediction to identify the best genotype from a candidate population. Several expected improvement...
-
Optimization of the Stacking Process of Wire Mesh Coils in Industrial Processors
This study proposes to optimise the post-production and storage process of electro-welded mesh rolls in companies in the city of Lima, for which this...
-
Voting Rights, Markov Chains, and Optimization by Short Bursts
Finding outlying elementsin probability distributions can be a hard problem. Taking a real example from Voting Rights Act enforcement, we consider...
