Since China's economic reform, the country's economy has thrived. Chinese foreign direct
investment is attracting more and more attention throughout the globe. Although China's …

All governments have lately placed a high priority on achieving carbon neutrality.
Environmental sustainability may be achieved via the evaluation of novel approaches. We …

As the proportion of photovoltaic (PV) power generation rapidly increases, accurate PV
output power prediction becomes more crucial to energy efficiency and renewable energy …

This article investigates the feasibility of applying the broad learning system (BLS) to realize
a novel Takagi–Sugeno–Kang (TSK) neuro-fuzzy model, namely a broad learning based …

The trend prediction of the stock is a main challenge. Accidental factors often lead to short-
term sharp fluctuations in stock markets, deviating from the original normal trend. The short …

We propose a hybrid deep learning neural network model for accurately calculating
municipal solid waste (MSW) production and diversions with socioeconomic and …

Data from a survey of 21 European nations from 2006 to 2018 investigates the relationship
between economic development and carbon dioxide emissions. The PCA of normalised …

The concept of randomized neural networks (RNNs), such as the random vector functional
link network (RVFL) and extreme learning machine (ELM), is a widely accepted and efficient …

The rapid identification of coal types in the field is an important task. This research combines
spectroscopy with deep learning algorithms and proposes a method for quickly identifying …

The electrical capacitance tomography is considered to be a promising non-invasive
visualization method for the measurement of multiphase flow parameters, but low-quality …