AIMC Topic: Neural Networks, Computer

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A Malicious Domain Detection Model Based on Improved Deep Learning.

Computational intelligence and neuroscience
With the rapid development of the Internet, malicious domain names pose more and more serious threats to many fields, such as network security and social security, and there have been many research results on malicious domain detection. This article ...

Forecasting Subway Passenger Flow for Station-Level Service Supply.

Big data
Demand forecasting is one of the managers' concerns in service supply chain management. With accurate passenger flow forecasting, the station-level service suppliers can make better service plans accordingly. However, the existing forecasting model c...

Speckle-Based Optical Cryptosystem and its Application for Human Face Recognition via Deep Learning.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Face recognition has become ubiquitous for authentication or security purposes. Meanwhile, there are increasing concerns about the privacy of face images, which are sensitive biometric data and should be protected. Software-based cryptosystems are wi...

GraphDPA: Predicting drug-pathway associations by graph convolutional networks.

Computational biology and chemistry
Pathway-based drug discovery is a promising strategy for the discovery of drugs with low toxicity and side effects. However, identifying the associations between drug and targeting pathways is challenging for this method. The formation of various bio...

GalaxyWater-CNN: Prediction of Water Positions on the Protein Structure by a 3D-Convolutional Neural Network.

Journal of chemical information and modeling
Proteins interact with numerous water molecules to perform their physiological functions in biological organisms. Most water molecules act as solvent media; hence, their roles may be considered implicitly in theoretical treatments of protein structur...

Rational Design of Field-Effect Sensors Using Partial Differential Equations, Bayesian Inversion, and Artificial Neural Networks.

Sensors (Basel, Switzerland)
Silicon nanowire field-effect transistors are promising devices used to detect minute amounts of different biological species. We introduce the theoretical and computational aspects of forward and backward modeling of biosensitive sensors. Firstly, w...

Optimization of Sample Construction Based on NDVI for Cultivated Land Quality Prediction.

International journal of environmental research and public health
The integrated use of remote sensing technology and machine learning models to evaluate cultivated land quality (CLQ) quickly and efficiently is vital for protecting these lands. The effectiveness of machine-learning methods can be profoundly influen...

Model architecture can transform catastrophic forgetting into positive transfer.

Scientific reports
The work of McCloskey and Cohen popularized the concept of catastrophic interference. They used a neural network that tried to learn addition using two groups of examples as two different tasks. In their case, learning the second task rapidly deterio...

Analysis and Prediction of Corporate Finance and Exchange Rate Correlation Based on Machine Learning Algorithms.

Computational intelligence and neuroscience
Based on the risk management of exposure to foreign exchange assets and liabilities and the application of financial derivatives, this paper provides an in-depth analysis of the financial and exchange rate risks of foreign-funded enterprises. Therefo...

A Micro Neural Network for Healthcare Sensor Data Stream Classification in Sustainable and Smart Cities.

Computational intelligence and neuroscience
A smart city is an intelligent space, in which large amounts of data are collected and analyzed using low-cost sensors and automatic algorithms. The application of artificial intelligence and Internet of Things (IoT) technologies in electronic health...