Results 11 to 20 of about 17,798 (304)

Simple Case Study on Radius of Radial Basis Function Network for Sequential Approximate Optimization

open access: yesSICE Journal of Control, Measurement, and System Integration, 2017
Radial basis function (RBF) networks are used for various research field. Especially, they make handling easy for classification and function approximation due to their mathematical form.
Yoshiaki Katada
doaj   +2 more sources

Exploiting a Deep Neural Network for Efficient Transmit Power Minimization in a Wireless Powered Communication Network

open access: yesApplied Sciences, 2020
In this paper, we propose a learning-based solution for resource allocation in a wireless powered communication network (WPCN). We provide a study and analysis of a deep neural network (DNN) which can reasonably effectively approximate the iterative ...
Iqra Hameed, Pham-Viet Tuan, Insoo Koo
doaj   +1 more source

Development of rapid heating cycle molding using heater and process parameters optimization

open access: yesNihon Kikai Gakkai ronbunshu, 2023
Plastic injection molding (PIM) is a manufacturing technology to plastic products, and it is important to determine optimal process parameters for high product quality and high productivity.
Shogo TSURITA   +5 more
doaj   +1 more source

Application of the Global Equilibrium Search Method for Solving Boolean Programming Problems

open access: yesКібернетика та комп'ютерні технології, 2023
Introduction. The significance of methods and algorithms for solving discrete optimization problems in mathematical supporting computer technologies of diverse levels and objectives is increasing.
Ivan Sergienko   +3 more
doaj   +1 more source

A Comparison between Fixed-Basis and Variable-Basis Schemes for Function Approximation and Functional Optimization [PDF]

open access: yes, 2012
Fixed-basis and variable-basis approximation schemes are compared for the problems of function approximation and functional optimization (also known as infinite programming).
Gnecco, Giorgio   +3 more
core   +1 more source

Design Optimization of Multibody Systems by Sequential Approximation

open access: yesMultibody System Dynamics, 1998
We propose to couple the multibody analysis and optimization algorithm by approximation concepts. The basic idea is to generate approximations of objective function and constraints in a certain part of the design space, and to find the optimum point for this approximate optimization problem.
Etman, L.F.P.   +2 more
openaire   +2 more sources

Design optimization of initial blank shape and segmented variable blank holder force trajectories in deep drawing

open access: yesNihon Kikai Gakkai ronbunshu, 2016
Blank shape minimizing earing, which is trimmed off after forming, is an important issue in sheet metal forming. In addition, blank holder force (BHF) have an influence on the product quality.
Kiichiro KAWAMOTO   +6 more
doaj   +1 more source

Sequential approximate optimality conditions for a constrained convex vector minimization problem and application to multiobjective fractional programming problem [PDF]

open access: yesIranian Journal of Numerical Analysis and Optimization
The aim of this paper is to establish sequential necessary and sufficient approximate optimality conditions for a constrained convex vector mini-mization problem without any constraint qualifications, characterizing the approximate proper and weak ...
A. Ed-dahdah   +3 more
doaj   +1 more source

On the approximation of some optimal sequential plan [PDF]

open access: yesApplicationes Mathematicae, 1988
The paper is concerned with the problem of sequential estimating the parameter of the drift coefficient in stochastic diffusion processes and fields. We consider the models when drift is known up to a multiplicative constant. For such models \textit{A. A. Novikov} [Theor. Probab. Appl. 16, 391-393 (1971); translation from Teor. Veroyatn. Primen.
openaire   +2 more sources

A Bayesian Optimization Approach for Water Resources Monitoring Through an Autonomous Surface Vehicle: The Ypacarai Lake Case Study

open access: yesIEEE Access, 2021
Bayesian Optimization is a sequential method for obtaining the maximum of an unknown function that has gained much popularity in recent years. Bayesian Optimization is commonly used to monitor the surface of large-scale aquatic environments using an ...
Federico Peralta Samaniego   +4 more
doaj   +1 more source

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