Environmental science and pollution research international
Apr 14, 2020
In recent years, global climate change caused by carbon dioxide emissions has attracted more and more attention. Adjusting the energy mix by predicting energy demands is currently a more effective way to address climate issues and energy supply issue...
Neural networks : the official journal of the International Neural Network Society
Apr 13, 2020
I review unsupervised or self-supervised neural networks playing minimax games in game-theoretic settings: (i) Artificial Curiosity (AC, 1990) is based on two such networks. One network learns to generate a probability distribution over outputs, the ...
Environmental science and pollution research international
Apr 11, 2020
De-carbonization of the transport sector is an important pathway to climate-change mitigation and presents the potential for future lower emissions. To assess the potential quantitatively under different optimization measures, this paper presents a h...
We propose a novel method for training neural networks to predict the future prices of stock indexes. Unlike previous works, we do not use target stock index data for training neural networks for index prediction. Instead, we use only the data of ind...
Many models can be used to fill the gaps caused by incomplete geospatial data. But not all are valid. To study the validity of geospatial information diffusion model, in this article, two judging criteria are suggested to check if a model is valid fo...
State-of-the-art machine learning (ML) artificial intelligence methods are increasingly leveraged in clinical predictive modeling to provide clinical decision support systems to physicians. Modern ML approaches such as artificial neural networks (ANN...
Medical oncology (Northwood, London, England)
Apr 3, 2020
Artificial intelligence (AI) is revolutionizing healthcare and transforming the clinical practice of physicians across the world. Radiology has a strong affinity for machine learning and is at the forefront of the paradigm shift, as machines compete ...
Neural networks : the official journal of the International Neural Network Society
Apr 2, 2020
A conformal predictive system(CPS) is based on the learning framework of conformal prediction, which outputs cumulative distribution functions(CDFs) for labels in regression problems. The CDFs output by a CPS provide useful information for users, as ...
Daily activity forecasts play an important role in the daily lives of residents in smart homes. Category forecasts and occurrence time forecasts of daily activity are two key tasks. Category forecasts of daily activity are correlated with occurrence ...