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Dynamic economic emission dispatch（DEED） problem in power system is a kind of high-dimensional multiobjective optimization problem with large-scale constraints. The traditional evolutionary algorithm is easy to fall into local optimization, and the distribution and convergence of the obtained Pareto frontier are poor. In this paper, it fully explore the clonal selection principle of immune system, and propose a hybrid immune multi-objective optimization algorithm（HIMOA）. The proposed algorithm takes the traditional evolutionary algorithm as the basic framework.Since the deficiency of falling local optimization for the high-dimensional decision variables optimization, the external archive update mechanism is improved to preserve the excellent individuals from previous generations, and the cloning and Gaussian mutation strategy is adopted to strengthen the local exploitation ability, forcing effectively the HIMOA to jump out of the stagnant search state. In order to cope with the large-scale constraints, designing the fine-turning output power step by step to improve the feasibility of the evolutionary population. In the numerical simulation experiment, taking a 10-unit system as a test example, and compares HIMOA with the famous algorithms MODE,NSGAII, IMOEA/D-CH, ADEA, MOHDE＿SAT, MONNDE. The results show that HIMOA can provide a better Pareto solution to the 10-unit system of the DEED problem, and the convergence and distribution of the Pareto frontier obtained are better than other algorithms. The box diagram of each evaluation metric shows that HIMOA has better statistical characteristics than other algorithms. [ABSTRACT FROM AUTHOR]

In order to investigate the evolution patterns of city size in China, nighttime light images were used to analyze city size distribution and its spatiotemporal patterns for 338 prefectural cities from 1993 to 2012 based on total nighttime light index, rank⁃size analysis and Markov transition matrix analysis. Statistical analysis shows that, all provincial regions and economic zones have experienced nighttime light growth, with a growth rate of 257% in the Southwest and 254% in the Northwest. Tibet is the fastest growing provincial region with a growth rate of 842%. The rank ⁃size analysis shows all the other economic zones, except for the Northeast economic zone, become less agglomerated during this period. The Markov transition matrix analysis shows the city size has inertia from 1993 to 2012. Cities in lowest level remain their levels with a probability of 82%. In addition, the size of a city may transit to the neighboring level, but the crossing⁃level transition rarely happens. This study reveals the city size evolution patterns in a multiple spatial scale and a long period, providing evidences to evaluate policies for Chinese urban development. [ABSTRACT FROM AUTHOR]

Considering the rational decision makers usually make the best choice to obtain high cost-performance results, further analysis is conducted based on the Pareto non-inferior solutions that are derived by solving a tri-objective optimization problem. Based on the concept of cost-performance ratio, the basic rule of ordering the Pareto front points is established, the concept of the adjacent points is defined, and the method for the selection of adjacent points is clarified. Based on the distribution feature of the Pareto front points and their adjacent points, the Pareto front change rate is calculated. The concept of sensitivity ratio is defined, and the bias degree of each Pareto non-inferior solution corresponding to each objective is calculated. The innovations are as follows:(i) a new dominance relationship that is formed by the Pareto front sensitivity ratio of the tri-objective optimization problem is used to obtain a subset that has a smaller range than the Pareto non-inferior solution set; (ii) the bias degree that corresponds to each Pareto non-inferior solution for each objective is quantified for the tri-objective optimization problems for the first time; (iii) the unbalance degree, which corresponds to each Pareto non-inferior solution for each objective, is also derived. Finally, the above calculation process is demonstrated by calculating numerical examples, and the results are compared with that obtained by other common methods. The results illustrate that the proposed method in this paper is feasible and valid. This research is a significant theoretical advancement for understanding the important features of Pareto non-inferior solutions and for solving tri-objective optimization problems. [ABSTRACT FROM AUTHOR]

Tractor transmission shaft is one of the components that affect the reliability of the tractor. Compiling load spectrum which can reflect the actual working conditions of high-power tractor drive shaft is of great significance to improve the reliability of the tractor. It is time consuming and expensive to obtain the actual measurement for load spectrum of the whole life cycle, so extrapolated methods are always applied by using the load spectrum of the limited measurement duration. However, the traditional method of rain flow counting and rain basin extrapolation in the process of compiling load spectrum of transmission system has limitations, this paper proposed a POT (peak over threshold) model based time domain extrapolation method for driving shaft load of high-power tractor. Firstly, a set of wireless torque measurement system for tractor transmission shaft is built, which mainly includes strain gauges, batteries, wireless strain nodes and wireless acquisition terminals. The strain gauge is pasted on the proper part of the tractor drive shaft and connected with the wireless torque node. The wireless transmitter is encapsulated in the wireless torque node and transmits the measured torque signal to the wireless receiver synchronously. The test data of the drive shaft under field working conditions are stored in a portable computer connected to a wireless receiver. Then, POT model is established based on extremum theory to extract the peak and valley values of the test data and eliminate the small load cycles, and the intervals of the optimal thresholds are determined by using the mean excess function graph, which are [492, 501] N·m for the upper limit and [325, 334] N·m for the lower limit, respectively. Thirdly, the data in the threshold interval is divided according to a certain gradient, and the fitting effect corresponding to each threshold is preliminarily tested by calculating R-square. The grey relational degree analysis method is used to select the optimal threshold and calculate the grey relational degree of each threshold in the corresponding threshold range. the optimum threshold values 497 N·m for upper limit and 333 N·m for lower limit are achieved by comparing the values of grey correlation degree corresponding to different threshold. The excess threshold data are fitted by generalized Pareto distribution and the CDF and P-P figures are plotted to evaluate the effectiveness of fitting test. The results show that the fitting curve of generalized distribution function can accurately describe the distribution law of extreme samples. Finally, according to the fitted generalized distribution function, the load sequence with the same distribution is generated. The time domain extrapolation of the load is achieved by replacing the original extremum load with the generated sequence. The cumulative frequency curve of the load cycle is developed according to the original load data and the results obtained by the time domain extrapolation method and the rain flow extrapolation method. The results show that the frequency curves obtained by the traditional rain flow extrapolation method and the time domain extrapolation method are consistent. Compared to the original load data, both load extrapolation results have a small amount of large extreme load which did not occur during the test. Therefore, it can be indicated that the load extrapolation method based on the POT model not only increases the frequency of the load cycle, but also extrapolates the load extreme value to a certain extent based on the distribution law of the large extreme load. The accuracy of the time domain extrapolation method is verified. The load time domain extrapolation method developed in this paper has good applicability to the measured loads of high-power tractor transmission shaft in operation conditions. Compared with the rain basin extrapolation method, the load time domain extrapolation method based on POT model can not only obtain the load time domain sequence of arbitrary mileage, but also retain the order of the measured load cycle to a great extent, which can provide reliable data support for the indoor load spectrum loading test of high-power tractor transmission system in the future. [ABSTRACT FROM AUTHOR]

Tractor transmission shaft is one of the components that affect the reliability of the tractor. Compiling load spectrum which can reflect the actual working conditions of high-power tractor drive shaft is of great significance to improve the reliability of the tractor. It is time consuming and expensive to obtain the actual measurement for load spectrum of the whole life cycle, so extrapolated methods are always applied by using the load spectrum of the limited measurement duration. However, the traditional method of rain flow counting and rain basin extrapolation in the process of compiling load spectrum of transmission system has limitations, this paper proposed a POT (peak over threshold) model based time domain extrapolation method for driving shaft load of high-power tractor. Firstly, a set of wireless torque measurement system for tractor transmission shaft is built, which mainly includes strain gauges, batteries, wireless strain nodes and wireless acquisition terminals. The strain gauge is pasted on the proper part of the tractor drive shaft and connected with the wireless torque node. The wireless transmitter is encapsulated in the wireless torque node and transmits the measured torque signal to the wireless receiver synchronously. The test data of the drive shaft under field working conditions are stored in a portable computer connected to a wireless receiver. Then, POT model is established based on extremum theory to extract the peak and valley values of the test data and eliminate the small load cycles, and the intervals of the optimal thresholds are determined by using the mean excess function graph, which are [492, 501] N·m for the upper limit and [325, 334] N·m for the lower limit, respectively. Thirdly, the data in the threshold interval is divided according to a certain gradient, and the fitting effect corresponding to each threshold is preliminarily tested by calculating R-square. The grey relational degree analysis method is used to select the optimal threshold and calculate the grey relational degree of each threshold in the corresponding threshold range. the optimum threshold values 497 N·m for upper limit and 333 N·m for lower limit are achieved by comparing the values of grey correlation degree corresponding to different threshold. The excess threshold data are fitted by generalized Pareto distribution and the CDF and P-P figures are plotted to evaluate the effectiveness of fitting test. The results show that the fitting curve of generalized distribution function can accurately describe the distribution law of extreme samples. Finally, according to the fitted generalized distribution function, the load sequence with the same distribution is generated. The time domain extrapolation of the load is achieved by replacing the original extremum load with the generated sequence. The cumulative frequency curve of the load cycle is developed according to the original load data and the results obtained by the time domain extrapolation method and the rain flow extrapolation method. The results show that the frequency curves obtained by the traditional rain flow extrapolation method and the time domain extrapolation method are consistent. Compared to the original load data, both load extrapolation results have a small amount of large extreme load which did not occur during the test. Therefore, it can be indicated that the load extrapolation method based on the POT model not only increases the frequency of the load cycle, but also extrapolates the load extreme value to a certain extent based on the distribution law of the large extreme load. The accuracy of the time domain extrapolation method is verified. The load time domain extrapolation method developed in this paper has good applicability to the measured loads of high-power tractor transmission shaft in operation conditions. Compared with the rain basin extrapolation method, the load time domain extrapolation method based on POT model can not only obtain the load time domain sequence of arbitrary mileage, but also retain the order of the measured load cycle to a great extent, which can provide reliable data support for the indoor load spectrum loading test of high-power tractor transmission system in the future. [ABSTRACT FROM AUTHOR]

The direct economical losses and the tolls of earthquakes are main impacts of earthquake insurance. This paper collected the loss data of earthquake during the years 1950-2015 in China and modeled the direct economical losses and the tolls of earthquake using Copula-mixed distribution model. First, the truncated Gumble distribution and generalized Pareto distribution are mixed to fit the direct economical losses, and the truncated negative binominal distribution and generalized Pareto distribution are mixed to fit the tolls of earthquake. Second, copulas are used to model the dependence between the direct economical losses and the tolls of earthquake. Finally, Monte Carlo simulation method is used to calculate VaR and ES. The models proposed in the paper may be applied to establish earthquake insurance system in China. [ABSTRACT FROM AUTHOR]

Objective To find out the reasons of medical disputes, grasp the regulation of medical disputes, and provide references for the control of medical malpractice for hospital managers. Method Pareto diagram was used to find out the main reasons, and then made clear the most urgent problems to be solved. Results The number and rate of medical disputes in surgical department were the highest, and the ones of pediatrics were the lowest. Form the pareto diagram of 117 medical disputes, the cumulative percent of medical professional ability defects, complications and medical accidents, the shortage of occupational morality was 36.7% ~ 69.9%, these three reasons were foremost. The cumulative percent of not timely treatment and rescue was 83.5%, this reason was secondary. The cumulative percent of poor treatment and management oversight link was 95.9 ~ 100%, these reasons were generally. The main reasons of medical disputes were medical professional ability defects, complications and medical accidents, the shortage of occupational morality. Conclusion To control of medical disputes, hospitals should take the following measures in practice: improve the technical level of medical staff, enhance the capacity of medical staff, enforce rules and regulations strictly and deal with the complications and medical accidents flexibly. [ABSTRACT FROM AUTHOR]

To construct Lorenz curves of high fitting precision, this paper put forward two single-parameter models for Lorenz curves. Furthermore, it constructed a set of extended Lorenz curves by means of ways of such as compound, the weighted product and the convex combination, etc. based on the two proposed models. An illustration example shows that, compared with utilizing the Lorenz curves of trigonometric forms or the Lorenz curves of Pareto distribution separately, the Lorenz curves generated by the combination the Lorenz curves of trigonometric forms and the Lorenz curves of Pareto distribution have higher fitting precision, which verify the Lorenz curves of trigonometric forms are effective extensions of the existing ones. [ABSTRACT FROM AUTHOR]