AIMC Topic: Algorithms

Clear Filters Showing 12781 to 12790 of 28713 articles

H Tracking Control of Uncertain Markovian Hybrid Switching Systems: A Fuzzy Switching Dynamic Adaptive Control Approach.

IEEE transactions on cybernetics
This article investigates the H stochastic tracking control problem for uncertain fuzzy Markovian hybrid switching systems by using a fuzzy switching dynamic adaptive control approach. The long and the short is to construct multiple piecewise stochas...

Automatic Image Processing Algorithm for Light Environment Optimization Based on Multimodal Neural Network Model.

Computational intelligence and neuroscience
In this paper, we conduct an in-depth study and analysis of the automatic image processing algorithm based on a multimodal Recurrent Neural Network (m-RNN) for light environment optimization. By analyzing the structure of m-RNN and combining the curr...

An Animation Model Generation Method Based on Gaussian Mutation Genetic Algorithm to Optimize Neural Network.

Computational intelligence and neuroscience
With the rapid development of computer graphics, 3D animation has been applied to all fields of people's lives, especially in the industries of film and television works, games, and entertainment. The wide application of animation technology makes it...

Optimization algorithm of CT image edge segmentation using improved convolution neural network.

PloS one
To address the problem of high failure rate and low accuracy in computed tomography (CT) image edge segmentation, we proposed a CT sequence image edge segmentation optimization algorithm using improved convolution neural network. Firstly, the pattern...

Genetic Analysis of Coronary Artery Disease Using Tree-Based Automated Machine Learning Informed By Biology-Based Feature Selection.

IEEE/ACM transactions on computational biology and bioinformatics
Machine Learning (ML) approaches are increasingly being used in biomedical applications. Important challenges of ML include choosing the right algorithm and tuning the parameters for optimal performance. Automated ML (AutoML) methods, such as Tree-ba...

EPGAT: Gene Essentiality Prediction With Graph Attention Networks.

IEEE/ACM transactions on computational biology and bioinformatics
Identifying essential genes and proteins is a critical step towards a better understanding of human biology and pathology. Computational approaches helped to mitigate experimental constraints by exploring machine learning (ML) methods and the correla...

A Novel Adaptive Linear Neuron Based on DNA Strand Displacement Reaction Network.

IEEE/ACM transactions on computational biology and bioinformatics
Analog DNA strand displacement circuits can be used to build artificial neural network due to the continuity of dynamic behavior. In this study, DNA implementations of novel catalysis, novel degradation and adjustment reaction modules are designed an...

iPhosS(Deep)-PseAAC: Identification of Phosphoserine Sites in Proteins Using Deep Learning on General Pseudo Amino Acid Compositions.

IEEE/ACM transactions on computational biology and bioinformatics
Among all the PTMs, the protein phosphorylation is pivotal for various pathological and physiological processes. About 30 percent of eukaryotic proteins undergo the phosphorylation modification, leading to various changes in conformation, function, s...

LDICDL: LncRNA-Disease Association Identification Based on Collaborative Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics
It has been proved that long noncoding RNA (lncRNA) plays critical roles in many human diseases. Therefore, inferring associations between lncRNAs and diseases can contribute to disease diagnosis, prognosis and treatment. To overcome the limitation o...

Finite-frequency control for nonlinear semi-Markov jump systems with piecewise transition probabilities.

ISA transactions
Considering the frequency effect of external disturbances, this paper concerns the finite-frequency control problem for nonlinear semi-Markov jump systems (SMJSs) with piecewise transition probabilities (TPs) via the Takagi-Sugeno (T-S) fuzzy modelin...