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Wind power DC collection system, as a crucial component of wind farms, plays a vital role in ensuring the safe and stable operation of the entire wind farm. This paper proposes a reliability assessment method for wind power DC collection systems based on MLFTA-SMC. Firstly, it analyzes the topology and key equipment of wind power DC collection systems. Secondly, based on the topology of different wind power DC collection systems, it constructs multi-level fault tree models to calculate the comprehensive importance of different events, thus providing data support for subsequent reliability assessment. Then, it utilizes the MLFTA-SMC method to assess and analyze the reliability of different wind power DC collection system topologies. Finally, taking a 100 MW wind farm in Northwest China as an example, the proposed reliability assessment method is verified through simulation. The results indicate that this method exhibits good effectiveness and superiority.

This paper summarizes the key line identification method of the most representative power network in the complex networks. It is of great significance to identify the key line of the power transmission network to prevent the cascade failure of the power system. By analyzing and comparing the methods of identifying key line in recent years,this paper summarizes the power betweenness method, electrical betweenness method, comprehensive importance method,entropy theory and some other methods,and expounds their advantages and disadvantages. Based on this,the future research direction of critical line identification in complex power transmission networks is proposed.

In the cutting process, there are many parameters that affect the cutting effect, and the same parameter has different degrees of influence on different performance indicators, which makes it difficult to select key parameters for parameter optimization and parameter combination evaluation while considering multiple performance indicators at the same time. The process of titanium alloy milling with an integrated end mill is studied herein. The values of cutting tool flank face wear and material removal rates are obtained with experimental and analytical methods. Numerical characteristics and causes of the cutting tool flank face wear at different stages are also analyzed. The dynamic, comprehensive evaluation method based on the double incentives model is used to evaluate the dynamic, comprehensive importance of cutting parameters in view of the problem of considering multiple performance indicators and the characteristics of the dynamic change in performance indicators in the cutting process. According to the result of a dynamic, comprehensive evaluation, the cutting parameters with the highest comprehensive importance are selected. Finally, the radar map is used to plot the comprehensive importance of the cutting parameters. The overall comprehensive importance of each cutting parameter is intuitively displayed as well. As a result of the research, the dynamic, comprehensive evaluation method based on the double incentives model has a good application value in the evaluation of tool performance in the cutting process and can quickly select the best tool performance parameter combination; it is established that the most comprehensive parameter is the cutting speed, and the cutting width is the second most important. In turn, the comprehensive importance of the cutting depth is the lowest.

As urbanization is growing faster, the term “Smart” is becoming more widely used. However, it is difficult to define how to objectively evaluate intellectualization. This study aims to explore an objective method of evaluating intellectualization in Japanese zoos and suggest project directions for their future development. First, we will define the unique Japanese zoo smart projects. Then, an analytic hierarchy process (AHP) will be used to determine the weights of each item, and the fuzzy comprehensive evaluation method (FCEM) will be used to evaluate the degree of construction. Finally, the strengths and weaknesses of each project will be analyzed by importance–performance analysis (IPA). The findings showed that the research subject, Ueno Zoo, is still in the early stage of smartening, and most of the items are not sufficient for users to have a full tourist experience. There is a need to increase the level of intellectualization and ease-of-use for the construction of the zoos of Tokyo. This study provides an objective approach for evaluating the intellectualization of zoos in Japan and provides a method of construction advice for intellectualization construction.

Camellia oleifera Abel. is an economically important woody oil plant native to China. To explore the genetic diversity of wild C. oleifera phenotypic traits and effectively protect these germplasm resources, this study provides a thorough evaluation of the phenotypic variability of a cluster of 143 wild C. oleifera germplasm resources. A total of 41 characters, including leaves, flowers, fruits, seeds, and oil quality characters, were investigated based on the quantization of physical and chemical descriptors and digital image analysis. The findings revealed significant variations among the 41 characters with a high range of Shannon–Wiener indexes ( H ′) from 0.07 to 2.19. The coefficient of variation (CV) among 32 quantitative characters ranged from 5.34% to 81.31%, with an average of 27.14%. High genetic diversity was also detected among the 143 germplasm. Based on the analysis of hierarchical clustering, 143 accessions were separated into six categories. All the individuals can be clearly distinguished from each other according to the result of the principal component analysis (PCA). The M-TOPSIS exhaustive evaluation method based on correlation and PCA analyses of 32 quantitative characters was applied for the 143 wild C. oleifera accessions, and the top 10 varieties were identified as YA53, YA13, YA40, YA34, YA57, YA19, YA33, YA41, DZ8, and YA7. This research optimized the germplasm evaluation system and perfected the statistical phenotypic traits for distinctness, uniformity, and stability (DUS) testing. Some top-notch germplasm sources were also screened for oil-tea Camellia breeding.

The machining accuracy reliability of machine tools has important practical significance for the quality of processed parts. In the milling process, the geometric errors and vibration errors are the two key error sources which severely decrease the machining accuracy reliability of machine tools. To ensure that machine tools can maintain high machining accuracy and reliability for a long time, the paper proposes a machining accuracy reliability evaluation method that considers both the geometric and vibration errors. Based on the milling dynamics theory and the full-discretization method (FDM), a four degrees of freedom (DOF) milling dynamics model of the tool-workpiece vibration system and a vibration error prediction model of the tool-workpiece system are established. The former is used for the milling stability prediction and the milling parameter optimization, while the latter is used for the vibration errors prediction. Utilizing the multi-body system (MBS) theory, a comprehensive error model considering both the geometric and vibration errors is established to explain the influence of errors on machining accuracy. Based on the Monte Carlo simulation of directional importance sampling (DIS-MCS), a machining accuracy reliability model is proposed to evaluate the machining ability of machine tools. The method is applied to a five-axis CNC machine tool, and the application results explain the correctness and competitiveness of the proposed method. It can realize the milling parameter optimization, the vibration error prediction of the tool-workpiece system, and the machining accuracy reliability evaluation of machine tools.

The extensive application of modern information and communication technology in the power system through the in-depth integration of the information system and the power system has led to the gradual development of the cyber-physical power system (CPPS). While advanced information technology increases the safety and reliability of power system operations, it also increases the risks of fault propagation. To improve the reliability of CPPS from the perspective of power communication routing, it is proposed that the CPPS model and vulnerability assessment of power node reflect the correlation between information and energy flows with the service impact on power grid operation, which is an important index for evaluating communication services. According to the distribution of services at the different important levels on the links, the importance of the cross-layer link is established as the vulnerability evaluation index of the communication network. Then, the routing optimization model is proposed in combination with the service transmission risk under cyber-attack and the operating characteristics of the information system, which is solved through an improved fast-convergent genetic algorithm. The simulation results show that the proposed method allocates the alternate route to the low-risk link without significantly increasing the delay of the main route, which effectively improves the power supply reliability of CPPS in extreme cyber-attack scenarios.

With the increasing penetration of new energy sources, the volatility and uncertainty of new energy output can lead to interruptions or fluctuations in the supply of electricity. Power cuts to critical loads can have a significant impact on public safety, social stability, and the economy. Dealing with the effects of uncertainty from new energy sources means we need to find and strengthen the important loads and power sources when designing and operating the power system. Therefore, the assessment of the importance of loads, conventional power sources, and new energy sources is crucial. This paper proposes a power source importance evaluation method based on load importance and new energy uncertainty. The method constructs a load importance evaluation system considering structural characteristics, outage loss, regulation capability, and other factors. To determine the importance of each load, the method uses the ideal solution method and ranks them accordingly. Next, the method calculates the power supply coefficient, which represents the power supply capability of the power source to the critical loads. This calculation involves using the three-point estimation method, which combines the characteristics of the new energy output and the importance of each load. Following that, the evaluation of load importance and the power supply capacity to critical loads is accomplished based on the ideal solution method, taking into account the diversity of power supply characteristics. This comprehensive evaluation allows us to assess the significance of each load and the power supply capability to meet the needs of critical loads, considering the unique characteristics of each power source. Finally, an example analysis is carried out on the IEEE39 to calculate the importance of various types of power sources, which can accurately reflect the power supply capacity of power sources to important loads and verify the validity of the evaluation method. This method provides subsidies for future power system grid planning and operation.

Aiming at the problem that the customer can obtain the personalized products in a timely and satisfactory manner, the enterprise can reasonably and effectively carry out the decision-making guidance of the manufacturing decision and propose a method to evaluate the customer satisfaction based on the fuzzy level kano-QDF model. The fuzzy hierarchical Kano model is used to identify and classify the customer’s needs. Based on the GM (1,1) model, the classification results of the fuzzy hierarchical Kano model are dynamically analyzed and verified. Secondly, the mathematical model of customer satisfaction evaluation is established by using the fuzzy comprehensive evaluation method. The demand for the importance of the final determination, the use of QFD method to confirm the importance of product quality characteristics and weight. Finally, the customer demand for personalized customized products is described as an example.

To address the issue of traditional static evaluation models being unable to comprehensively analyze the performance of ultra-supercritical coal-fired units under varying loads, we propose a dynamic comprehensive evaluation model based on the improved Criteria Importance Through Inter-criteria Correlation (CRITIC) method and entropy weight method (EWM). The comprehensive performance evaluation index system of ultra-supercritical coal fired units is constructed by examining the boiler performance, turbine performance, plant power performance, environmental performance, and flexible performance of coal-powered units. The CRITIC and EWM methods are used to calculate the weights of the indicators, which are then combined with the static evaluation results. Using a dynamic comprehensive evaluation model, we analyze ultra-supercritical coal-fired units, taking into account time weight. This allows us to obtain the comprehensive dynamic real-time evaluation value of the units under different loads. The research indicates that the weight of the evaluation index is changed when using the dynamic comprehensive evaluation model of the improved CRITIC and EWM. The index with lower weight is increased by 6.2%, while the index with higher weight is decreased by 0.22%. This alteration in weight range can provide a more objective reflection of the relationship between evaluation indicators. This model offers significant advantages in improving evaluation accuracy, weight balance distribution, and generality.