Results 41 to 50 of about 395 (112)

Comparative Study of Neuroevolution and Deep Reinforcement Learning for Voltage Regulation in Power Systems

Inventions
The regulation of voltage in transmission networks is becoming increasingly complex due to the dynamic behavior of modern power systems and the growing penetration of renewable generation.
Adrián Alarcón Becerra, Vinícius Albernaz Lacerda, Roberto Rocca, Ana Patricia Talayero Navales, Andrés Llombart Estopiñán   +4 more
doaj   +1 more source

Practical Approach to Studying Evolutionary Methods for Setting Weight Coefficients of Artificial Neural Networks

Цифровая трансформация
The article describes the problems of developing neurocontrollers for controlling dynamic objects, including the complexity of forming training data sets. It is indicated that one of the known methods for training an artificial neural network controlling
D. O. Petrov
doaj   +1 more source

Improved Search in Neuroevolution Using a Neural Architecture Classifier With the CNN Architecture Encoding as Feature Vector

IEEE Access
Designing Convolutional Neural Networks (CNNs) for a specific task requires not only Deep Learning expertise but also knowledge of the problem. The goal of Neuroevolution is to find CNN architectures automatically through evolution.
Jhon I. Pilataxi, Jorge E. Zambrano, Claudio A. Perez, Kevin W. Bowyer   +3 more
doaj   +1 more source

Review of some contemporary trends in machine learning technology

E-Management, 2019
The construction of machine learning systems constitutes today one of the most popular, relevant and modern areas of human activity at the interface of information technology, mathematical analysis and statistics.
M. Koroteev
doaj   +1 more source

Neuroevolutionary Convolutional Neural Network Design for Low-Resolution Face Recognition

IEEE Access
Face recognition (FR) is one of the most widely used biometric methods for identity authentication. Although most of the recently proposed methods demonstrate remarkable performance on high-quality datasets, such as LFW, their effectiveness is limited ...
Jhon I. Pilataxi, Juan P. Perez, Claudio A. Perez, Kevin W. Bowyer   +3 more
doaj   +1 more source

Neuroevolution of Liquid State Machine Based on Neural Configurations and Positions

Mathematical and Computational Applications
Liquid State Machines (LSMs), a reservoir computing model based on recurrent spiking neural networks, provide a powerful framework for solving spatiotemporal classification tasks by leveraging rich temporal dynamics and event-driven processing.
Carlos-Alberto López-Herrera, Héctor-Gabriel Acosta-Mesa, Efrén Mezura-Montes, Jesús-Arnulfo Barradas-Palmeros   +3 more
doaj   +1 more source

EvoDevo: Bioinspired Generative Design via Evolutionary Graph-Based Development

Algorithms
Automated generative design is increasingly used across engineering disciplines to accelerate innovation and reduce costs. Generative design offers the prospect of simplifying manual design tasks by exploring the efficacy of solutions automatically ...
Farajollah Tahernezhad-Javazm, Andrew Colligan, Imelda Friel, Simon J. Hickinbotham, Paul Goodall, Edgar Buchanan, Mark Price, Trevor Robinson, Andy M. Tyrrell   +8 more
doaj   +1 more source

Classification of Common Bean Landraces of Three Species Using a Neuroevolutionary Approach with Probabilistic Color Characterization

Mathematical and Computational Applications
The common bean is a widely cultivated food source. Many domesticated species of common bean varieties, known as landraces, are cultivated in Mexico by local farmers, exhibiting various colorations and seed mixtures as part of agricultural practices.
José-Luis Morales-Reyes, Elia-Nora Aquino-Bolaños, Héctor-Gabriel Acosta-Mesa, Nancy Pérez-Castro, José-Luis Chavez-Servia   +4 more
doaj   +1 more source

Estimation of Anthocyanins in Heterogeneous and Homogeneous Bean Landraces Using Probabilistic Colorimetric Representation with a Neuroevolutionary Approach

Mathematical and Computational Applications
The concentration of anthocyanins in common beans indicates their nutritional value. Understanding this concentration makes it possible to identify the functional compounds present.
José-Luis Morales-Reyes, Elia-Nora Aquino-Bolaños, Héctor-Gabriel Acosta-Mesa, Aldo Márquez-Grajales   +3 more
doaj   +1 more source

Neuroevolution-Based Network Architecture Evolution in Semiconductor Manufacturing. [PDF]

ACS Omega, 2023
Feng YW, Jiang BR, Lin AS.
europepmc   +1 more source