AIMC Topic: Neural Networks, Computer

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Understanding the Research Landscape of Deep Learning in Biomedical Science: Scientometric Analysis.

Journal of medical Internet research
BACKGROUND: Advances in biomedical research using deep learning techniques have generated a large volume of related literature. However, there is a lack of scientometric studies that provide a bird's-eye view of them. This absence has led to a partia...

Identification of Insider Trading in the Securities Market Based on Multi-task Deep Neural Network.

Computational intelligence and neuroscience
Illegal insider trading identification is of great significance to the healthy development of the securities market. However, with the development of information technology, problems such as multidata sources and noise bring challenges to the insider...

An Intelligent Optimization for Building Design Based on BP Neural Network and SPEA-II Multiobjective Algorithm.

Computational intelligence and neuroscience
With the continuous development of the field of building optimization, more and more optimization methods have sprung up, among which there are many kinds of intelligent optimization algorithms. This kind of intelligent optimization algorithm usually...

Application of a semivariogram based on a deep neural network to Ordinary Kriging interpolation of elevation data.

PloS one
The Ordinary Kriging method is a common spatial interpolation algorithm in geostatistics. Because the semivariogram required for kriging interpolation greatly influences this process, optimal fitting of the semivariogram is of major significance for ...

Compound FAT-based prespecified performance learning control of robotic manipulators with actuator dynamics.

ISA transactions
In the framework of the backstepping algorithm, this article proposes a new function approximation technique (FAT)-based compound learning control law for electrically-driven robotic manipulators with output constraint. The Fourier series expansion i...

Developed multiple-layer perceptron neural network based on developed search and rescue optimizer to predict iron ore price volatility: A case study.

ISA transactions
In economic investment, the role of forecasting is very important because in an economic project, the investor must carefully examine the dimensions of the work such that one of the most important and perhaps the main factor of a future investor and ...

Event-triggered integral reinforcement learning for nonzero-sum games with asymmetric input saturation.

Neural networks : the official journal of the International Neural Network Society
In this paper, an event-triggered integral reinforcement learning (IRL) algorithm is developed for the nonzero-sum game problem with asymmetric input saturation. First, for each player, a novel non-quadratic value function with a discount factor is d...

Multistability analysis of delayed recurrent neural networks with a class of piecewise nonlinear activation functions.

Neural networks : the official journal of the International Neural Network Society
This paper studies the multistability of delayed recurrent neural networks (DRNNs) with a class of piecewise nonlinear activation functions. The coexistence as well as the stability of multiple equilibrium points (EPs) of DRNNs are proved. With the B...

Artificial neural networks with conformable transfer function for improving the performance in thermal and environmental processes.

Neural networks : the official journal of the International Neural Network Society
This research proposes a novel transfer function based on the hyperbolic tangent and the Khalil conformable exponential function. The non-integer order transfer function offers a suitable neural network configuration because of its ability to adapt. ...

Deep neural networks learn general and clinically relevant representations of the ageing brain.

NeuroImage
The discrepancy between chronological age and the apparent age of the brain based on neuroimaging data - the brain age delta - has emerged as a reliable marker of brain health. With an increasing wealth of data, approaches to tackle heterogeneity in ...