Analysis on evaluation ability of nonlinear safety assessment model of coal mines based on artificial neural network

Based on the integration analysis of goods and shortcomings of various methods used in safety assessment of coal mines, combining nonlinear feature of mine safety sub-system, this paper establishes the neural network assessment model of mine safety, analyzes the ability of artificial neural network to evaluate mine safety state, and lays the theoretical foundation of artificial neural network using in the systematic optimi- zation of mine safety assessment and getting reasonable accurate safety assessment result.

Study on evaluation of cities' ability reducing earthquake disasters

Cities ability reducing earthquake disasters is a complex system involving numerous factors, moreover the re-search on evaluating cities ability reducing earthquake disasters relates to multi-subject, such as earthquake sci-ence, social science, economical science and so on. In this paper, firstly, the conception of cities ability reducing earthquake disasters is presented, and the ability could be evaluated with three basic elements the possible seis-mic casualty and economic loss during the future earthquakes that are likely to occur in the city and its surround-ings and time required for recovery after earthquake; based upon these three basic elements, a framework, which consists of six main components, for evaluating citys ability reducing earthquake disasters is proposed; then the statistical relations between the index system and the ratio of seismic casualty, the ratio of economic loss and re-covery time are gained utilizing the cities prediction results of earthquake disasters which were made during the ninth five-year plan; at last, the method defining the comprehensive index of cities ability reducing earthquake disasters is presented. Thus the relatively comprehensive theory frame is set up. The frame can evaluate cities ability reducing earthquake disasters absolutely and quantitatively and consequently instruct the decision-making on reducing cities earthquake disasters loss.

Empirical Analysis of Evaluation of English Teachers＇ Educational Ability Under MOOC Environment

In order to improve the English teachers＇ education ability evaluation accuracy, promote the upgrading of the level of English teacher education, the evaluation model of English teacher education ability is proposed in MOOC environment. Data fusion model of English teacher education ability evaluation index is obtained based on big data analysis method, data clustering analysis of English teaching evaluation indicators is carried out, Characteristic data of English Teaching are extracted, and combining fuzzy C means algorithm to analyze the characteristics of English teachers＇ educational ability in MOOC environment, adaptive mining evaluation of English teachers＇ educational ability is realized. Then we develop and design the evaluation system of English teacher education ability under the MOOC environment. The empirical data analysis is taken, and results show that it has good accuracy by using this method for evaluation of English teacher＇s ability, it improves the comprehensive evaluation level of English teachers.

Design of an Index System for Deep Groundwater Management Efficiency Evaluation: A Case Study in Tianjin City, China

An effective evaluation system can provide specific and practical suggestions to the deep groundwater management. But such kind of evaluation system has not been proposed in China. In this study, an evaluation index system is specifically developed to evaluate deep groundwater management efficiency. It is composed of three first-level indicators(law enforcement capability, management ability, and management effectiveness) and eleven second-level indicators. The second-level indicators include seven mandatory indicators and four optional indicators. Piecewise linear function is used to normalize the quantitative indicators, and expert scoring method and questionnaire survey method are used to normalize the qualitative indicators. Then a comprehensive indicator weighting evaluation method is used to evaluate the first-level indicators and the target topic. A case study is carried out to evaluate deep groundwater management efficiency in Tianjin City. According to the evaluation score in each period, the management efficiency of every district in Tianjin City gradually improved. The overall evaluation score in the early deep groundwater extraction period is 0.12. After a series of deep groundwater protection efforts, this score reached to 0.61 in 2007, and met the regulation criteria. The evaluation results also showed that the further groundwater management efforts in Tianjin City should be focused on building a dynamic database to collect comprehensive deep well-log data; and on a reasonable design and distribution of the groundwater monitoring network. It demonstrated that the index system is suitable to locate the deficiencies of current groundwater management systems and to guide further improvements. It can then be used to protect deep groundwater.

专科规范化培训医师岗位胜任能力评价研究:以上海市6个专科医师培养基地为例

目的利用专科规范化培训胜任力模型对上海市范围内的参培专科医师进行总体评价,旨在为培训模式的优化提供政策参考。方法本次调查对象包括上海市6个专科医师培养基地、在站培训的全部专科医师,按照50%的比例进行随机抽样。设计调查表针对专科医师规范化培训胜任力模型5个一级指标下的42个二级指标展开胜任力评价。结果品质素质维度的得分相对高于技能、知识、社会能力和自我认知4个维度,知识和技能维度相对在5个一级维度中有更高的提升空间。在控制了人口学变量之后发现不同参培阶段的专科医师在岗位胜任力自评的结果上呈现差异,且随着培训年限的增加,胜任力表现呈上升趋势。结论借助专科医师规范化培训胜任力模型可以为专科医师的管理、培训和考核提供量化工具。相比较而言,医学相关法律、公共卫生知识以及科研转化能力在专科医师规范化培训中具有更大的提升空间。

Real-time comprehensive driving ability evaluation algorithm for intelligent assisted driving

To meet the needs of the human-machine co-driving decision problem in the intelligent assisted driving system for real-time comprehensive driving ability evaluation of drivers,this paper proposes a real-time comprehensive driving ability evaluation method that integrates driving skill,driving state,and driving style.Firstly,by analyzing the driving experiment data obtained based on the intelligent driving simulation platform(the experiment can effectively distinguish the driver's driving skills and avoid the interference of driving style),the feature values that significantly represent driving skills and driving state are selected,and the time correlation between driving state and driving skills is pointed out.Furthermore,the concept of relativity in comprehensive driving ability evaluation is further proposed.Under this concept,the natural driving trajectory dataset-HighD is used to establish the distribution map of feature values of the human driver group as the evaluation benchmark to realize the relative evaluation of driving skill and driving state.Similarly,HighD is used to establish a distribution map of human driver style feature values as an evaluation benchmark to achieve relative driving style evaluation.Finally,a comprehensive driving ability evaluation model with a“punishment”and“affirmation”mechanism is proposed.The experimental comparative analysis shows that the evaluation algorithm proposed in this paper can take into account the driver's driving skill,driving state,and driving style in the real-time comprehensive driving ability evaluation,and draw differential evaluation conclusions based on the“punishment”and“affirmation”mechanism model to achieve a comprehensive and objective evaluation of the driver's driving ability.It can meet the needs of human-machine shared driving decisions for driver's driving ability evaluation.