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Abstract In the realm of engineering practice, various factors such as limited availability of measurement data and complex working conditions pose significant challenges to obtaining accurate load spectra. Thus, accurat...

The solution of matrix eigenvalues has always been a research hotspot in the field of modern numerical analysis, which has important value in practical application of engineering technology and scientific research. Despi...

Optical neural networks have significant advantages in terms of power consumption, parallelism, and high computing speed, which has intrigued extensive attention in both academic and engineering communities. It has been ...

Abstract This study uses the Levenberg–Marquardt strategy with feed forward neural networks (LMS-FNN) to inspect the Soret-Dufour effect on radiative hybrid nanofluid flow across a Riga plate with gyrotactic microorgan...

Abstract The co-frequency vibration fault is one of the common faults in the operation of rotating equipment, and realizing the real-time diagnosis of the co-frequency vibration fault is of great significance for monitor...

Abstract Intracerebral hemorrhage (ICH) is a devastating neurological condition with high mortality and morbidity. Despite advancements in medical and surgical treatments, the long-term prognosis of ICH remains poor. Ste...

Abstract Echo State Networks are recurrent neural networks that leverage a random reservoir’s dynamics, training only a simple readout layer. This approach is computationally efficient but limits network performance. B...

Abstract To address the limitations of existing oil-well production forecasting models, particularly suboptimal hyperparameter selection, difficulties in fine-tuning, insufficient global search capability, and slow conve...

Abstract Alzheimer’s disease, a progressive neurodegenerative disorder, presents a growing global health challenge due to its increasing prevalence and lack of accessible early diagnostic methods. Even though it has en...

Microelectronic computers have encountered challenges in meeting all of today’s demands for information processing. Meeting these demands will require the development of unconventional computers employing alternative p...

Brain-computer interface (BCI) is a neuro-engineering technology that establishes a direct communication pathway between the brain and external devices. It can realize bidirectional information interaction between the br...

Many underlying relationships among data in several areas of science and engineering, e.g., computer vision, molecular chemistry, molecular biology, pattern recognition, and data mining, can be represented in terms of gr...

El problema de satisfacibilidad (SAT), el primero en demostrarse que es NP-completo, es fundamental en muchos campos de las ciencias de la computación, la ingeniería eléctrica y matemática. En el presente trabajo se ...

Previous article Next article Fractional Brownian Motions, Fractional Noises and ApplicationsBenoit B. Mandelbrot and John W. Van NessBenoit B. Mandelbrot and John W. Van Nesshttps://doi.org/10.1137/1010093PDFBibTexSecti...

Subjects / keywords: Solar cells; Neural networks (Computer science); Electric controllers; Electrical engineering; Solar batteries

In spite of years of research and development, formal structured estimation of time and effort required to develop a Management Information System (MIS) is still an open problem. Usual estimation techniques applied by no...

Recently, channel attention mechanism has demonstrated to offer great potential in improving the performance of deep convolutional neural networks (CNNs). However, most existing methods dedicate to developing more sophis...

Subjects / keywords: Feed forward; Computer science; Feedforward neural network; Artificial intelligence; Artificial neural network; Control engineering; Engineering

Subjects / keywords: Computer science; Feed forward; Feedforward neural network; Artificial intelligence; Artificial neural network; Control theory (sociology); Control engineering; Control (management); Engineering

An end-to-end methodology based on deep learning for the detection and localization of microcalcifications in digital mammograms introduces a novel methodology designed for the preprocessing and localization of clusters ...

Abstract Tracking control of tendon-driven manipulators has become a prevalent research area. However, the existence of flexible elastic tendons generates substantial residual vibrations, resulting in difficulties for tr...

Abstract The lower limb exoskeletons are used to assist wearers in various scenarios such as medical and industrial settings. Complex modeling errors of the exoskeleton in different application scenarios pose challenges ...

Abstract When the mobile robot performs certain motion tasks in complex environment, wheel slipping inevitably occurs due to the wet or icy road and other reasons, thus directly influences the motion control accuracy. To...

Abstract This paper presents a novel neural-fuzzy-based adaptive sliding mode automatic steering control strategy to improve the driving performance of vision-based unmanned electric vehicles with time-varying and uncert...