Suchergebnisse

As the convenient outlet to the Bo Sea and the major region of economic development in the Yellow River Basin, Shandong Province in China has undergone large changes in land use/land cover (LULC) in the past two decades with rapid urbanization and population growth. The analysis of the LULC change patterns and its driving factors in the Shandong section of the Yellow River Basin can provide a scientific basis for rational planning and ecological protection of land resources in the Shandong section of the Yellow River Basin. In this manuscript, we analyzed the spatial pattern of LULC and its spatial and temporal changes in the Shandong section of the Yellow River Basin in 2000, 2010, and 2020 by using the random forest classification algorithm with the Google Earth Engine platform and multi-temporal Landsat TM/OLI data. The driving factors of LULC changes were also quantified by the factor detector and interaction detector in the geodetector. Results show that in the past two decades, the LULC types in the study area are mainly farmland and construction land, among which the proportion of farmland area has decreased and the proportion of construction land area has increased from 19.4% to 29.7%. Based on the results of factor detector, it can be concluded that elevation, slope, and soil type are the key factors affecting LULC change in the study area. The interaction between elevation and slope, slope and soil type, and temperature and precipitation has strong explanatory power for the spatial variation of LULC change in the study area. The research results can provide data support for ecological environmental protection, sustainable, and high-quality development of the Shandong section of the Yellow River Basin, and help local governments take corresponding measures to achieve coordinated and sustainable socioeconomic and environmental development.

This book mainly focuses on the multi-media energy prediction technology and optimization methods of iron and steel enterprises. The technical methods adopted include swarm intelligence algorithm, neural network, reinforcement learning, and so on. Energy saving and consumption reduction in iron and steel enterprises have always been a research hotspot in the field of process control. This book considers the multi-media energy balance problem from the perspective of system, studies the energy flow and material flow in iron and steel enterprises, and provides energy optimization methods that can be used for planning, prediction, and scheduling under different production scenes. The main audience of this book is scholars and graduate students in the fields of control theory, applied mathematics, energy optimization, etc.