AI Medical Compendium Topic

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Optimal Underwater Acoustic Warfare Strategy Based on a Three-Layer GA-BP Neural Network.

Sensors (Basel, Switzerland)
A defense platform is usually based on two methods to make underwater acoustic warfare strategy decisions. One is through Monte-Carlo method online simulation, which is slow. The other is by typical empirical (database) and typical back-propagation (...

End-to-End Hierarchical Reinforcement Learning With Integrated Subgoal Discovery.

IEEE transactions on neural networks and learning systems
Hierarchical reinforcement learning (HRL) is a promising approach to perform long-horizon goal-reaching tasks by decomposing the goals into subgoals. In a holistic HRL paradigm, an agent must autonomously discover such subgoals and also learn a hiera...

A Network Model for Detecting Marine Floating Weak Targets Based on Multimodal Data Fusion of Radar Echoes.

Sensors (Basel, Switzerland)
Due to the interaction between floating weak targets and sea clutter in complex marine environments, it is necessary to distinguish targets and sea clutter from different dimensions by designing universal deep learning models. Therefore, in this pape...

Fuzzy Clustering Algorithm Based on Improved Global Best-Guided Artificial Bee Colony with New Search Probability Model for Image Segmentation.

Sensors (Basel, Switzerland)
Clustering using fuzzy C-means (FCM) is a soft segmentation method that has been extensively investigated and successfully implemented in image segmentation. FCM is useful in various aspects, such as the segmentation of grayscale images. However, FCM...

A machine learning method for predicting the probability of MODS using only non-invasive parameters.

Computer methods and programs in biomedicine
OBJECTIVES: Timely and accurate prediction of multiple organ dysfunction syndrome (MODS) is essential for the rescue and treatment of trauma patients However, existing methods are invasive, easily affected by artifacts and can be difficult to perform...

Efficient Perturbation Inference and Expandable Network for continual learning.

Neural networks : the official journal of the International Neural Network Society
Although humans are capable of learning new tasks without forgetting previous ones, most neural networks fail to do so because learning new tasks could override the knowledge acquired from previous data. In this work, we alleviate this issue by propo...

Stability analysis with general fuzzy measure: An application to social security organizations.

PloS one
An effective method for evaluating the efficiency of peer decision-making units (DMUs) is data envelope analysis (DEA). In engineering sciences and real-world management problems, uncertainty in input and output data always exists. To achieve reliabl...

Estimation of Parameters on Probability Density Function Using Enhanced GLUE Approach.

Computational intelligence and neuroscience
The most essential process in statistical image and signal processing is the parameter estimation of probability density functions (PDFs). The estimation of the probability density functions is a contentious issue in the domains of artificial intelli...

Modelling built-up land expansion probability using the integrated fuzzy logic and coupling coordination degree model.

Journal of environmental management
The expansion of built-up area is the most noticeable form of urbanization-induced land use/land cover (LULC) change. In the global cities of south, the urban sprawl is increasing rapidly with even higher probabilities of future built-up expansion. T...

Deep learning-based neural networks for day-ahead power load probability density forecasting.

Environmental science and pollution research international
Energy efficiency is crucial to greenhouse gas (GHG) emission pathways reported by the Intergovernmental Panel on Climate Change. Electrical overload frequently occurs and causes unwanted outages in distribution networks, which reduces energy utiliza...