Fan Xiao¹, Xiong Ping¹, Yeyang Li^2,*, Yusen Xu², Yiqun Kang¹, Dan Liu¹, Nianming Zhang¹

Energy Engineering, Vol.121, No.2, pp. 359-376, 2024, DOI:10.32604/ee.2023.040887

Abstract The fluctuation of wind power affects the operating safety and power consumption of the electric power grid and restricts the grid connection of wind power on a large scale. Therefore, wind power forecasting plays a key role in improving the safety and economic benefits of the power grid. This paper proposes a wind power predicting method based on a convolutional graph attention deep neural network with multi-wind farm data. Based on the graph attention network and attention mechanism, the method extracts spatial-temporal characteristics from the data of multiple wind farms. Then, combined with a deep neural network, a convolutional graph… More >

Chunhua Jin, Hanqing Hu^*

Energy Engineering, Vol.118, No.3, pp. 655-665, 2021, DOI:10.32604/EE.2021.014281

Abstract With the increase of total energy consumption, eco-environmental quality drops sharply, which has attracted concerns from all circles. It has become the top priority of construction of socialist ecological civilization to clarify the influences of energy consumption on the level of eco-environmental pollution. Ecological environmental pollution control cannot be one size fits all. It can avoid resource depletion and environmental deterioration via adjusting measures to local conditions to coordinate ecological environmental pollution and energy consumption problems. In this essay, entropy method is adopted to measure the composite indexes of eco-environmental pollution of 30 provinces and cities in China, based on… More >

Ahmed Bachir^{1, *}, Ibrahim Mufrah Almanjahie^{1, 2}, Mohammed Kadi Attouch³

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2049-2064, 2020, DOI:10.32604/cmc.2020.011491

Abstract It is well known that the nonparametric estimation of the regression function is highly sensitive to the presence of even a small proportion of outliers in the data. To solve the problem of typical observations when the covariates of the nonparametric component are functional, the robust estimates for the regression parameter and regression operator are introduced. The main propose of the paper is to consider data-driven methods of selecting the number of neighbors in order to make the proposed processes fully automatic. We use the More >