AIMC Topic: Neural Networks, Computer

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Adaptive dynamic programming-based hierarchical decision-making of non-affine systems.

Neural networks : the official journal of the International Neural Network Society
In this paper, the problem of multiplayer hierarchical decision-making problem for non-affine systems is solved by adaptive dynamic programming. Firstly, the control dynamics are obtained according to the theory of dynamic feedback and combined with ...

Convolutional neural network-multi-kernel radial basis function neural network-salp swarm algorithm: a new machine learning model for predicting effluent quality parameters.

Environmental science and pollution research international
A wastewater treatment plant (WWTP) is an essential part of the urban water cycle, which reduces concentration of pollutants in the river. For monitoring and control of WWTPs, researchers develop different models and systems. This study introduces a ...

An unsupervised wavelet neural network model for approximating the solutions of non-linear nervous stomach model governed by tension, food and medicine.

Computer methods in biomechanics and biomedical engineering
The human stomach is a complex organ. Its role is to degrade food particles by using mechanical forces and chemical reactions in order to release nutrients. All ingested items, including our nutrition, should first pass through the stomach, making it...

A bi-layer model for identification of piwiRNA using deep neural learning.

Journal of biomolecular structure & dynamics
piwiRNA is a kind of non-coding RNA (ncRNA) that cannot be translated into proteins. It helps in understanding the study of gametes generation and regulation of gene expression over both transcriptional and post-transcriptional levels. piwiRNA has th...

Multiple-instance ensemble for construction of deep heterogeneous committees for high-dimensional low-sample-size data.

Neural networks : the official journal of the International Neural Network Society
Deep ensemble learning, where we combine knowledge learned from multiple individual neural networks, has been widely adopted to improve the performance of neural networks in deep learning. This field can be encompassed by committee learning, which in...

Layer adaptive node selection in Bayesian neural networks: Statistical guarantees and implementation details.

Neural networks : the official journal of the International Neural Network Society
Sparse deep neural networks have proven to be efficient for predictive model building in large-scale studies. Although several works have studied theoretical and numerical properties of sparse neural architectures, they have primarily focused on the ...

Bidirectionally self-normalizing neural networks.

Neural networks : the official journal of the International Neural Network Society
The problem of vanishing and exploding gradients has been a long-standing obstacle that hinders the effective training of neural networks. Despite various tricks and techniques that have been employed to alleviate the problem in practice, there still...

Bridged adversarial training.

Neural networks : the official journal of the International Neural Network Society
Adversarial robustness is considered a required property of deep neural networks. In this study, we discover that adversarially trained models might have significantly different characteristics in terms of margin and smoothness, even though they show...

Enhanced Multiwavelength Response of Flexible Synaptic Transistors for Human Sunburned Skin Simulation and Neuromorphic Computation.

Advanced materials (Deerfield Beach, Fla.)
In biological species, optogenetics and bioimaging work together to regulate the function of neurons. Similarly, the light-controlled artificial synaptic system not only enhances computational speed but also simulates complex synaptic functions. Howe...

CoTrFuse: a novel framework by fusing CNN and transformer for medical image segmentation.

Physics in medicine and biology
Medical image segmentation is a crucial and intricate process in medical image processing and analysis. With the advancements in artificial intelligence, deep learning techniques have been widely used in recent years for medical image segmentation. O...