AIMC Topic: Forecasting

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An Optimization Analysis Model of Tourism Specialized Villages Based on Neural Network and System Dynamics.

Computational intelligence and neuroscience
With the rapid development of tourism, professional tourism villages emerge one after another, which has become the focus of the tourism industry. At present, there are some problems in tourism professional villages, such as imperfect management and ...

Algal bloom forecasting with time-frequency analysis: A hybrid deep learning approach.

Water research
The rapid emergence of deep learning long-short-term-memory (LSTM) technique presents a promising solution to algal bloom forecasting. However, the discontinuous and non-stationary processes within algal dynamics still largely limit the functions of ...

Deep Learning Applications in Surgery: Current Uses and Future Directions.

The American surgeon
Deep learning (DL) is a subset of machine learning that is rapidly gaining traction in surgical fields. Its tremendous capacity for powerful data-driven problem-solving has generated computational breakthroughs in many realms, with the fields of medi...

[Artificial intelligence-based ECG analysis: current status and future perspectives-Part 1 : Basic principles].

Herzschrittmachertherapie & Elektrophysiologie
Even though electrocardiography is a diagnostic procedure that is now more than 100 years old, medicine cannot do without it. On the contrary, interest in the procedure and its clinical significance is even increasing again. Reports on the evaluation...

ECMWF short-term prediction accuracy improvement by deep learning.

Scientific reports
This paper aims to describe and evaluate the proposed calibration model based on a neural network for post-processing of two essential meteorological parameters, namely near-surface air temperature (2 m) and 24 h accumulated precipitation. The main i...

Multi-Step Hourly Power Consumption Forecasting in a Healthcare Building with Recurrent Neural Networks and Empirical Mode Decomposition.

Sensors (Basel, Switzerland)
Short-term forecasting of electric energy consumption has become a critical issue for companies selling and buying electricity because of the fluctuating and rising trend of its price. Forecasting tools based on Artificial Intelligence have proved to...

Exploration of Stock Portfolio Investment Construction Using Deep Learning Neural Network.

Computational intelligence and neuroscience
To study the intelligent and efficient stock portfolio in China's financial market, based on the relevant theories such as deep learning (DL) neural network (NN) and stock portfolio, this study selects 111 stable stocks from the constituent stocks of...

Dynamic Learning Framework for Smooth-Aided Machine-Learning-Based Backbone Traffic Forecasts.

Sensors (Basel, Switzerland)
Recently, there has been an increasing need for new applications and services such as big data, blockchains, vehicle-to-everything (V2X), the Internet of things, 5G, and beyond. Therefore, to maintain quality of service (QoS), accurate network resour...

Multivariate time series forecasting method based on nonlinear spiking neural P systems and non-subsampled shearlet transform.

Neural networks : the official journal of the International Neural Network Society
Multivariate time series forecasting remains a challenging task because of its nonlinear, non-stationary, high-dimensional, and spatial-temporal characteristics, along with the dependence between variables. To address this limitation, we propose a no...