AIMC Topic: Algorithms

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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. ...

A hybrid deep learning approach for driver anomalous lane changing identification.

Accident; analysis and prevention
Reliable knowledge of driving states is of great importance to ensure road safety. Anomaly detection in driving behavior means recognizing anomalous driving states as a direct result of either environmental or psychological factors. This paper provid...

Weakly Supervised Occupancy Prediction Using Training Data Collected via Interactive Learning.

Sensors (Basel, Switzerland)
Accurate and timely occupancy prediction has the potential to improve the efficiency of energy management systems in smart buildings. Occupancy prediction heavily depends on historical occupancy-related data collected from various sensor sources. Unf...

Dynamic and Static Features-Aware Recommendation with Graph Neural Networks.

Computational intelligence and neuroscience
Recommender systems are designed to deal with structured and unstructured information and help the user effectively retrieve needed information from the vast number of web pages. Dynamic information of users has been proven useful for learning repres...

Optimization of English Machine Translation by Deep Neural Network under Artificial Intelligence.

Computational intelligence and neuroscience
To improve the function of machine translation to adapt to global language translation, the work takes deep neural network (DNN) as the basic theory, carries out transfer learning and neural network translation modeling, and optimizes the word alignm...

Construction of Home Product Design System Based on Self-Encoder Depth Neural Network.

Computational intelligence and neuroscience
The traditional home product design system mainly depends on relatively shallow learning network, relatively simple embedded technology and Internet of things technology. The traditional home design system mainly depends on the traditional self-encod...

Training of artificial neural networks with the multi-population based artifical bee colony algorithm.

Network (Bristol, England)
Nowadays, artificial intelligence has gained recognition in every aspect of life. Artificial neural networks, one of the most efficient artificial intelligence techniques, is remarkably successful in computers' acquisition of the learning and interpr...

KeratoScreen: Early Keratoconus Classification With Zernike Polynomial Using Deep Learning.

Cornea
PURPOSE: We aimed to investigate the usefulness of Zernike coefficients (ZCs) for distinguishing subclinical keratoconus (KC) from normal corneas and to evaluate the goodness of detection of the entire corneal topography and tomography characteristic...

Decentralized Distributed Multi-institutional PET Image Segmentation Using a Federated Deep Learning Framework.

Clinical nuclear medicine
PURPOSE: The generalizability and trustworthiness of deep learning (DL)-based algorithms depend on the size and heterogeneity of training datasets. However, because of patient privacy concerns and ethical and legal issues, sharing medical images betw...

Effective prediction of soil micronutrients using Additive Gaussian process with RAM augmentation.

Computational biology and chemistry
In soil chemistry, the nutrients exhibit non-linear and complex relationships owing to their stochastic nature but mostly their similarity is a function of the distance between the data points. The similarity assessment using distance metrics is a po...