Results 11 to 20 of about 222,299 (265)
A Hybrid Stochastic Deterministic Algorithm for Solving Unconstrained Optimization Problems
Mathematics, 2022 In this paper, a new deterministic method is proposed. This method depends on presenting (suggesting) some modifications to existing parameters of some conjugate gradient methods.
Ahmad M. Alshamrani +4 more
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Training Artificial Neural Networks Using a Global Optimization Method That Utilizes Neural Networks
AI, 2023 Perhaps one of the best-known machine learning models is the artificial neural network, where a number of parameters must be adjusted to learn a wide range of practical problems from areas such as physics, chemistry, medicine, etc.
Ioannis G. Tsoulos, Alexandros Tzallas
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NeuralMinimizer: A Novel Method for Global Optimization
Information, 2023 The problem of finding the global minimum of multidimensional functions is often applied to a wide range of problems. An innovative method of finding the global minimum of multidimensional functions is presented here.
Ioannis G. Tsoulos +3 more
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On a Stochastic Approximation Method [PDF]
The Annals of Mathematical Statistics, 1954 Asymptotic properties are established for the Robbins-Monro [1] procedure of stochastically solving the equation $M(x) = \alpha$. Two disjoint cases are treated in detail. The first may be called the "bounded" case, in which the assumptions we make are similar to those in the second case of Robbins and Monro. The second may be called the "quasi-linear"
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An Intelligent Technique for Initial Distribution of Genetic Algorithms
Axioms, 2023 The need to find the global minimum in multivariable functions is a critical problem in many fields of science and technology. Effectively solving this problem requires the creation of initial solution estimates, which are subsequently used by the ...
Vasileios Charilogis +2 more
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Proceedings, 2018 The design of energy-efficient electric motor is a complex problem since diverse requirements and competing goals have to be fulfilled simultaneously. Therefore, different approaches to the design optimization of electric motors have been developed, each
Johannes Schmelcher +4 more
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Proceedings, 2018 Designing energy-efficient electric motor is a task where multiple goals have to be achieved at once. To find the best design possible, different approaches have been developed.
Johannes Schmelcher +4 more
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Stochastic Quasi-Newton Methods for Nonconvex Stochastic Optimization [PDF]
SIAM Journal on Optimization, 2017 published in SIAM Journal on ...
Xiao Wang +3 more
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Química Nova, 2008 The paper presents an introductory and general discussion on the quantum Monte Carlo methods, some fundamental algorithms, concepts and applicability. In order to introduce the quantum Monte Carlo method, preliminary concepts associated with Monte Carlo ...
Wagner Fernando Delfino Angelotti +3 more
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Selecting Some Variables to Update-Based Algorithm for Solving Optimization Problems
Sensors, 2022 With the advancement of science and technology, new complex optimization problems have emerged, and the achievement of optimal solutions has become increasingly important.
Mohammad Dehghani, Pavel Trojovský
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