AIMC Topic: Forecasting

Clear Filters Showing 1071 to 1080 of 1639 articles

Applying Deep Neural Networks and Ensemble Machine Learning Methods to Forecast Airborne Pollen.

International journal of environmental research and public health
Allergies to airborne pollen are a significant issue affecting millions of Americans. Consequently, accurately predicting the daily concentration of airborne pollen is of significant public benefit in providing timely alerts. This study presents a me...

Time series trend detection and forecasting using complex network topology analysis.

Neural networks : the official journal of the International Neural Network Society
Extracting knowledge from time series provides important tools for many real applications. However, many challenging problems still open due to the stochastic nature of large amount of time series. Considering this scenario, new data mining and machi...

Integrated support vector regression and an improved particle swarm optimization-based model for solar radiation prediction.

PloS one
Solar energy is a major type of renewable energy, and its estimation is important for decision-makers. This study introduces a new prediction model for solar radiation based on support vector regression (SVR) and the improved particle swarm optimizat...

Online sequential echo state network with sparse RLS algorithm for time series prediction.

Neural networks : the official journal of the International Neural Network Society
Recently, the echo state networks (ESNs) have been widely used for time series prediction. To meet the demand of actual applications and avoid the overfitting issue, the online sequential ESN with sparse recursive least squares (OSESN-SRLS) algorithm...

Development and evaluation of a deep learning approach for modeling seasonality and trends in hand-foot-mouth disease incidence in mainland China.

Scientific reports
The high incidence, seasonal pattern and frequent outbreaks of hand, foot, and mouth disease (HFMD) represent a threat for millions of children in mainland China. And advanced response is being used to address this. Here, we aimed to model time serie...

Unveiling tropospheric ozone by the traditional atmospheric model and machine learning, and their comparison:A case study in hangzhou, China.

Environmental pollution (Barking, Essex : 1987)
Tropospheric ozone in the surface air has become the primary atmospheric pollutant in Hangzhou, China, in recent years. Previous analysis is not enough to decode it for better regulation. Therefore, we use the traditional atmospheric model, Weather R...

The role of AI classifiers in skin cancer images.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
BACKGROUND: The use of different imaging modalities to assist in skin cancer diagnosis is a common practice in clinical scenarios. Different features representative of the lesion under evaluation can be retrieved from image analysis and processing. H...