AIMC Topic: Forecasting

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Deep-Learning Model for Influenza Prediction From Multisource Heterogeneous Data in a Megacity: Model Development and Evaluation.

Journal of medical Internet research
BACKGROUND: In megacities, there is an urgent need to establish more sensitive forecasting and early warning methods for acute respiratory infectious diseases. Existing prediction and early warning models for influenza and other acute respiratory inf...

Data-driven prediction of greenhouse aquaponics air temperature based on adaptive time pattern network.

Environmental science and pollution research international
Greenhouse aquaponics system (GHAP) improves productivity by harmonizing internal environments. Keeping a suitable air temperature of GHAP is essential for the growth of plant and fish. However, the disturbance of various environmental factors and th...

Insights and trends review: artificial intelligence in hand surgery.

The Journal of hand surgery, European volume
Artificial intelligence (AI) in hand surgery is an emerging and evolving field that will likely play a large role in the future care of our patients. However, there remain several challenges to makes this technology meaningful, acceptable and usable ...

Building an automated, machine learning-enabled platform for predicting post-operative complications.

Physiological measurement
. In 2019, the University of Florida College of Medicine launched thealgorithm to predict eight major post-operative complications using automatically extracted data from the electronic health record.. This project was developed in parallel with our ...

Forecasting the United State Dollar(USD)/Bangladeshi Taka (BDT) exchange rate with deep learning models: Inclusion of macroeconomic factors influencing the currency exchange rates.

PloS one
Forecasting a currency exchange rate is one of the most challenging tasks nowadays. Due to government monetary policy and some uncertain factors, such as political stability, it becomes difficult to correctly forecast the currency exchange rate. Prev...

Human Factor Engineering Research for Rehabilitation Robots: A Systematic Review.

Computational intelligence and neuroscience
The application of human factors engineering for rehabilitation robots is based on a "human-centered" design philosophy that strives to provide safe and efficient human-robot interaction training for patients rather than depending on rehabilitation t...

Learning matrix factorization with scalable distance metric and regularizer.

Neural networks : the official journal of the International Neural Network Society
Matrix factorization has always been an encouraging field, which attempts to extract discriminative features from high-dimensional data. However, it suffers from negative generalization ability and high computational complexity when handling large-sc...

Forecasting shipping index using CEEMD-PSO-BiLSTM model.

PloS one
Shipping indices are extremely volatile, non-stationary, unstructured and non-linear, and more difficult to forecast than other common financial time series. Based on the idea of "decomposition-reconstruction-integration", this article puts forward a...

Coupling machine learning with signal process techniques and particle swarm optimization for forecasting flood routing calculations in the Eastern Black Sea Basin, Türkiye.

Environmental science and pollution research international
With the effect of global warming, the frequency of floods, one of the most important natural disasters, increases, and this increases the damage it causes to people and the environment. Flood routing models play an important role in predicting flood...