AIMC Topic: Algorithms

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Modeling and control of operator functional state in a unified framework of fuzzy inference petri nets.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In human-machine (HM) hybrid control systems, human operator and machine cooperate to achieve the control objectives. To enhance the overall HM system performance, the discrete manual control task-load by the operator must b...

A time-delay neural network for solving time-dependent shortest path problem.

Neural networks : the official journal of the International Neural Network Society
This paper concerns the time-dependent shortest path problem, which is difficult to come up with global optimal solution by means of classical shortest path approaches such as Dijkstra, and pulse-coupled neural network (PCNN). In this study, we propo...

Multitask Protein Function Prediction through Task Dissimilarity.

IEEE/ACM transactions on computational biology and bioinformatics
Automated protein function prediction is a challenging problem with distinctive features, such as the hierarchical organization of protein functions and the scarcity of annotated proteins for most biological functions. We propose a multitask learning...

A Natural Language Processing Framework for Assessing Hospital Readmissions for Patients With COPD.

IEEE journal of biomedical and health informatics
With the passage of recent federal legislation, many medical institutions are now responsible for reaching target hospital readmission rates. Chronic diseases account for many hospital readmissions and chronic obstructive pulmonary disease has been r...

Artificial intelligence (AI) systems for interpreting complex medical datasets.

Clinical pharmacology and therapeutics
Advances in machine intelligence have created powerful capabilities in algorithms that find hidden patterns in data, classify objects based on their measured characteristics, and associate similar patients/diseases/drugs based on common features. How...

Generating highly accurate prediction hypotheses through collaborative ensemble learning.

Scientific reports
Ensemble generation is a natural and convenient way of achieving better generalization performance of learning algorithms by gathering their predictive capabilities. Here, we nurture the idea of ensemble-based learning by combining bagging and boosti...

Beta Hebbian Learning as a New Method for Exploratory Projection Pursuit.

International journal of neural systems
In this research, a novel family of learning rules called Beta Hebbian Learning (BHL) is thoroughly investigated to extract information from high-dimensional datasets by projecting the data onto low-dimensional (typically two dimensional) subspaces, ...

Collective mutual information maximization to unify passive and positive approaches for improving interpretation and generalization.

Neural networks : the official journal of the International Neural Network Society
The present paper aims to propose a simple method to realize mutual information maximization for better interpretation and generalization. To train neural networks and obtain better performance, neurons should impartially consider as many input patte...

Counterfactual simulations applied to SHRP2 crashes: The effect of driver behavior models on safety benefit estimations of intelligent safety systems.

Accident; analysis and prevention
As the development and deployment of in-vehicle intelligent safety systems (ISS) for crash avoidance and mitigation have rapidly increased in the last decades, the need to evaluate their prospective safety benefits before introduction has never been ...