China's green data center development:Policies and carbon reduction technology path.

Data center is a very important infrastructure to support the development of information technology, and its development and increment are very remarkable. However, with the rapid and large-scale development of data centers, the problem of energy consumption turns to be also very prominent. Under the background of global carbon peak and carbon neutrality, developing green and low-carbon data centers has become an inevitable trend.

Hybrid Degradation Equipment Remaining Useful Life Prediction Oriented Parallel Simulation considering Model Soft Switch.

Equipment parallel simulation is an emerging simulation technology in recent years, and equipment remaining useful life (RUL) prediction oriented parallel simulation is an important branch of parallel simulation. An important concept in equipment parallel simulation is the model evolution driven by real-time data, including model selection and model parameter evolution. The current research on equipment RUL prediction oriented parallel simulation mainly focuses on a single continuous degradation mode, such as linear degradation and nonlinear degradation.

Self-adaptive prediction of cloud resource demands using ensemble model and subtractive-fuzzy clustering based fuzzy neural network.

In IaaS (infrastructure as a service) cloud environment, users are provisioned with virtual machines (VMs). To allocate resources for users dynamically and effectively, accurate resource demands predicting is essential. For this purpose, this paper proposes a self-adaptive prediction method using ensemble model and subtractive-fuzzy clustering based fuzzy neural network (ESFCFNN).

Characteristic analysis for odor gas emitted from food waste anaerobic fermentation in the pretreatment workshop.

Gas chromatography-mass spectrometry, olfactometry, and other related methods were applied for the qualitative and quantitative analysis of the characteristics of odorous gases in the pretreatment workshop. The composition of odorous gases emitted from municipal food waste was also investigated in this study. The results showed that the tested gases are mainly composed of aromatic gases, which account for 49% of the total volatile organic compounds (VOC) concentrations.