Recent advances in Grey Wolf Optimizer, its versions and applications
The Grey Wolf Optimizer (GWO) has emerged as one of the most captivating swarm
intelligence methods, drawing inspiration from the hunting behavior of wolf packs. GWO's …
intelligence methods, drawing inspiration from the hunting behavior of wolf packs. GWO's …
Forecasting CO2 emissions of China's cement industry using a hybrid Verhulst-GM (1, N) model and emissions' technical conversion
The cement industry is a significant contributor to anthropogenic CO 2. For China, the
cement industry is crucial for development, considering the surging urbanization. CO 2 …
cement industry is crucial for development, considering the surging urbanization. CO 2 …
Hybrid decision tree-based machine learning models for short-term water quality prediction
Water resources are the foundation of people's life and economic development, and are
closely related to health and the environment. Accurate prediction of water quality is the key …
closely related to health and the environment. Accurate prediction of water quality is the key …
Image segmentation of Leaf Spot Diseases on Maize using multi-stage Cauchy-enabled grey wolf algorithm
Grey wolf optimizer (GWO) is a widespread metaphor-based algorithm based on the
enhanced variants of velocity-free particle swarm optimizer with proven defects and …
enhanced variants of velocity-free particle swarm optimizer with proven defects and …
Application of a new grey multivariate forecasting model in the forecasting of energy consumption in 7 regions of China
M Wang, W Wang, L Wu - Energy, 2022 - Elsevier
Scientific prediction of regional energy is of practical significance for rational control of
energy supply. In this paper, to further minimize the influence of subjective factors, the grey …
energy supply. In this paper, to further minimize the influence of subjective factors, the grey …
A novel method for carbon emission forecasting based on Gompertz's law and fractional grey model: Evidence from American industrial sector
With the manufacturing reshoring to the US, increasing attention are focus on its energy
consumption and environmental effects and accurate prediction of carbon emissions is vital …
consumption and environmental effects and accurate prediction of carbon emissions is vital …
A novel machine learning-based electricity price forecasting model based on optimal model selection strategy
Current electricity price forecasting models rely on only simple hybridizations of data
preprocessing and optimization methods while ignoring the significance of adaptive data …
preprocessing and optimization methods while ignoring the significance of adaptive data …
Light Gradient Boosting Machine: An efficient soft computing model for estimating daily reference evapotranspiration with local and external meteorological data
Accurate estimation of reference evapotranspiration (ETo) is required in many fields, eg
irrigation scheduling design, agricultural water management, crop growth modeling and …
irrigation scheduling design, agricultural water management, crop growth modeling and …
Driving forces of China's CO2 emissions from energy consumption based on Kaya-LMDI methods
Anthropogenic carbon emission gives rise to a situation where global warming is becoming
serious. China is paying for reducing carbon emissions. The concept of carbon curse …
serious. China is paying for reducing carbon emissions. The concept of carbon curse …
Carbon trading volume and price forecasting in China using multiple machine learning models
Motivated by reducing carbon emissions, carbon trading market have been opened to
promote environmental protection. Accurate carbon trading volume and price forecasts have …
promote environmental protection. Accurate carbon trading volume and price forecasts have …