Research on the construction of carbon emission model of power generation industry in Jilin province

Although Jilin Province has abundant forest reserves and has a relatively large carbon neutral advantage compared to other provinces, the installed capacity of thermal power is still relatively high, and the installed capacity of renewable energy such as wind power, photovoltaic and hydropower is insufficient. This paper builds a carbon emission model for the power generation industry in Jilin Province based on the characteristics of the power generation industry in Jilin Province and years of field test experience.

Three-dimensional numerical investigation on micro-meter droplet impact and penetration into the porous media with different velocities

Droplets impacting and penetration into porous media is commonly seen in natural and engineering processes, in which the kinetics and capillary effect are of great importance to the lateral spreading and vertical penetration. In this study, a three-dimensional numerical simulation method was proposed to study the micro-meter droplet impact and penetration into the porous media. It is found that both the lateral spread and vertical penetration occur on the millisecond timescale and larger velocity will enhance the lateral spreading but have little influence on the penetration time and depth. The direct numerical method proposed in this study can be applied to predict the actual spreading and penetration status in the droplet-powder system and further insight into the droplet-powder interaction.

Research on the cost effectiveness of carbon emission reduction in the full life cycle of electric vehicles based on grey prediction

In order to research the carbon emission reduction potential of electric vehicles, a cost effectiveness model is used to calculate and compare the economic costs and carbon emissions of fuel vehicles and electric vehicles throughout the life cycle, and an improved grey prediction model is utilized to analyze the future trends of electric vehicle emission reduction benefits. The results show that electric vehicles play a positive role in carbon emission reduction, and the unit cost of carbon emission reduction is decreasing by years. Therefore, China should vigorously develop the electric vehicle industry and technology, and achieve the strategic goal of carbon emission reduction by promoting the electrification of vehicles.

Research on MVB conformance test system

The design and implementation of the MVB conformance test system is of great significance in both professional theory and practical application. Conformance test for MVB, mainly to determine whether the MVB equipment IUT is consistent with the MVB protocol standard requirements in the TCN standard. The conformance test of MVB equipment IUT covers most of the contents of the RTP real-time protocol such as the physical layer, link layer, network layer, transport layer and application layer. This subject will analyse and study the consistency test of the MVB physical layer.

The patterns of traveling wave on shallow water modeled by Green-Naghdi equation

The Green-Naghdi equations are a shallow water waves model which play important roles in nonlinear wave fields. By using the trial equation method and the Complete discrimination system for the polynomial we obtained the classification of travelling wave patterns. Among those patterns, new singular patterns and double periodic patterns are obtained in the first time. And we draw the graphs which help us to understand the dynamics behaviors of the Green-Naghdi model intuitionally.

Impact of the epidemic on the world economy

The impact of the epidemic on the global economy has exposed the fragility and complexity of the internal and external economic system, and the global economic situation is not optimistic. Taking the epidemic as an example, this paper analyzed the impact of emergencies on the global economy from multiple perspectives. The outbreak of the epidemic has made most offline businesses shut down overnight. At the same time, it has also led to the rapid development of online economy, such as online education, home office software, video entertainment and so on. The outbreak and spread of the epidemic has promoted the digital upgrading of all walks of life, including online government affairs, commerce, science, education, culture and health organization, operation and maintenance. The era of digital economy has come, and digitization is the general trend.

Algorithm of axial compressor stall warning based on BP neural network and fuzzy logic

Stall warning of axial compressor is very challenging and the existing warning margin is not enough. A algorithm based on BP neural network fusion fuzzy logic is proposed. Firstly, BP neural network is used for training recognition, next the identification results are fused with fuzzy logic reasoning to form the result judgment of time sequence, finally the stall early warning of axial compressor is realized. The simulation results of the experimental data show that the stall data at all speeds are at least 0.1s in advance of the early warning. Compared with other methods, this method has a better surge early warning margin performance and engineering practicability.

Multi scale switchable atrous convolution for target detection based on feature pyramid

Repeated observation mechanism can effectively solve the problem of low efficiency of feature extraction. By extracting features for many times to strengthen target features, this paper proposed a multi-scale switchable atrous convolution based on feature pyramid, SPC. The head of the detector adopted pyramid convolution mode, constructs 3-D convolution in the feature pyramid, and detected the same target in different pyramid levels by using the shared convolution with different stride changes, which realized the repeated observation of target features on multi-scale. The module optimized the convolution layer, extracted the features of the same image by convolution check of different sizes, and then selected and integrated the extracted results by using switch function, which effectively expanded the field of view of convolution kernel. In this paper, we choosed retinanet as the baseline network, and improved the loss function of focal loss proposed by retinanet to further solved the problem of unbalanced number of samples and sample distribution in the network model. The proposed method performed well on MS coco data set, improved the average accuracy of 9.8% on the basis of retinanet to 48.9%, and achieved FPS of 5.1 in 1333 * 800 images.

Association analysis in food sampling inspection data

At present, China exists a problem that the cost of food sampling inspection is too high. This paper attempts to reduce the number of sampling inspection items in the same food category, reduce the cost of food sampling inspection, and improve the work efficiency through the association analysis of national sampling inspection data. And this paper applies Apriori algorithm to analyse the association rules, which is based on the unqualified pastry sampling inspection data in the 2019 national food sampling inspection database. Finally, we obtain 10 strong association rules through experiments. The results show that this association analysis can reduce the workload of food sampling inspection effectively.