Research on the Assessment System of Computational Mechanics Courses Based on the TOPSIS Entropy Weight Model

This paper takes the assessment and evaluation of computational mechanics course as the background,and constructs a diversified course evaluation system that is student-centered and integrates both quantitative and qualitative evaluation methods.The system not only pays attention to students’practical operation and theoretical knowledge mastery but also puts special emphasis on the cultivation of students’innovative abilities.In order to realize a comprehensive and objective evaluation,the assessment and evaluation method of the entropy weight model combining TOPSIS(Technique for Order Preference by Similarity to Ideal Solution)multi-attribute decision analysis and entropy weight theory is adopted,and its validity and practicability are verified through example analysis.This method can not only comprehensively and objectively evaluate students’learning outcomes,but also provide a scientific decision-making basis for curriculum teaching reform.The implementation of this diversified course evaluation system can better reflect the comprehensive ability of students and promote the continuous improvement of teaching quality.

Prediction of rock burst classification using cloud model with entropy weight

The method of cloud model with entropy weight was adopted for the prediction of rock burst classification. Some main factors of rock burst including the uniaxial compressive strength （σc）, the tensile strength （σt）, the tangential stress （σθ）, the rock brittleness coefficient （σc/σt）, the stress coefficient （σθ /σc） and the elastic energy index （Wet） are chosen to establish evaluation index system. The entropy？cloud model and criterion are obtained through 209 sets of rock burst samples from underground rock projects. The sensitivity of indicators is analyzed and 209 sets of rock burst samples are discriminated by this model. The discriminant results of the entropy-cloud model are compared with those of Bayes, KNN and RF methods. The results show that the sensitivity order of those factors from high to low is σ_θ /σ_c, σ_θ, W_（ct）, σ_c/σ_t, σ_t, σ_c, and the entropy-cloud model has higher accuracy than Bayes, K-Nearest Neighbor algorithm （KNN） and Random Forest （RF） methods.

Entropy weight coefficient model and its application in evaluation of groundwater vulnerability of the Sanjiang Plain

The research of groundwater vulnerability is the basic work to protect the groundwater. For utilizing groundwater resource continuably, groundwater vulnerability evaluation is necessary. Useful reference to protect, exploit and utilize on groundwater resource are provided rationally. According to the real condition of Sanjiang Plain, the indexes system is established based on the traditional DRASTIC model. The new system includes the following seven indexes： Depth of Water, Net Recharge, Aquifer Media, Soil Media, Conductivity of the Aquifer, Land Utilizing Ratio and Populace Density. The related analysis appears that the system is rather reasonable. Because traditional methods, such as analytic hierarchy process and fuzzy mathematics theory, can＇t be avoided human interference in selection of weights, they could lead to an imprecise result. In order to evaluate the groundwater vulnerability reasonably, entropy weight coefficient method is applied for the first time, which provides a new way to groundwater vulnerability evaluation. The method is a model whose weights are insured by the calculation process, so the artificial disturb can be avoided. It has been used to evaluate the groundwater vulnerability in Sanjiang Plain. The satisfied result is acquired. Comparably, the same result is acquired by the other method named projection pursuit evaluation based on real-coded accelerating genetic algorithm. It shows that entropy weight coefficient method is applicable on groundwater vulnerability evaluation. The evaluation result can provide reference on the decision-making departments.

Group Decision-Making Model of Renal Cancer Surgery Options Using Entropy Fuzzy Element Aczel-Alsina Weighted Aggregation Operators under the Environment of Fuzzy Multi-Sets

Since existing selection methods of surgical treatment schemes of renal cancer patients mainly depend on physicians’clinical experience and judgments,the surgical treatment options of renal cancer patients lack their scientifical and reasonable information expression and group decision-making model for renal cancer patients.Fuzzy multi-sets(FMSs)have a number of properties,which make them suitable for expressing the uncertain information of medical diagnoses and treatments in group decision-making(GDM)problems.To choose the most appropriate surgical treatment scheme for a patient with localized renal cell carcinoma(RCC)(T1 stage kidney tumor),this article needs to develop an effective GDM model based on the fuzzy multivalued evaluation information of the renal cancer patients.First,we propose a conversionmethod of transforming FMSs into entropy fuzzy sets(EFSs)based on the mean and Shannon entropy of a fuzzy sequence in FMS to reasonably simplify the information expression and operations of FMSs and define the score function of an entropy fuzzy element(EFE)for ranking EFEs.Second,we present the Aczel-Alsina t-norm and t-conorm operations of EFEs and the EFE Aczel-Alsina weighted arithmetic averaging(EFEAAWAA)and EFE Aczel-Alsina weighted geometric averaging(EFEAAWGA)operators.Third,we develop a multicriteria GDM model of renal cancer surgery options in the setting of FMSs.Finally,the proposed GDM model is applied to two clinical cases of renal cancer patients to choose the best surgical treatment scheme for a renal cancer patient in the setting of FMSs.The selected results of two clinical cases verify the efficiency and rationality of the proposed GDM model in the setting of FMSs.

Cost-benefit Analysis of Scale Pig Breeding in Shandong Province Based on Modified Entropy Weight-TOPSIS Model

According to the relevant statistical data in National Agricultural cost-benefit Data Compilation(2001- 2013),we use the modified entropy weight- TOPSIS model to research the cost-benefit status of scale pig breeding in Shandong Province from the perspective of comparing it with that of the entire country and 9 other main pig producing areas. The results show that compared with the national average,the cost-benefit ratio of small scale pig breeding in Shandong Province is lower,while the cost-benefit ratio of medium scale and large scale pig breeding is significantly improved; the cost-benefit ratio of small scale pig breeding in Shandong Province is basically the same as that in 9 other main pig producing areas,while the cost-benefit ratio of medium scale and large scale pig breeding is higher; the output value of main products and the purchase price of piglet are two major bottlenecks restricting the cost-benefit improvement of scale pig breeding in Shandong Province.

Comprehensive security risk factor identification for small reservoirs with heterogeneous data based on grey relational analysis model

Identification of security risk factors for small reservoirs is the basis for implementation of early warning systems.The manner of identification of the factors for small reservoirs is of practical significance when data are incomplete.The existing grey relational models have some disadvantages in measuring the correlation between categorical data sequences.To this end,this paper introduces a new grey relational model to analyze heterogeneous data.In this study,a set of security risk factors for small reservoirs was first constructed based on theoretical analysis,and heterogeneous data of these factors were recorded as sequences.The sequences were regarded as random variables,and the information entropy and conditional entropy between sequences were measured to analyze the relational degree between risk factors.Then,a new grey relational analysis model for heterogeneous data was constructed,and a comprehensive security risk factor identification method was developed.A case study of small reservoirs in Guangxi Zhuang Autonomous Region in China shows that the model constructed in this study is applicable to security risk factor identification for small reservoirs with heterogeneous and sparse data.

Disassemblability Modeling Technology of Configurable Product Based on Disassembly Constraint Relation Weighted Design Structure Matrix(DSM)

The current research of configurable product disassemblability focuses on disassemblability evaluation and disassembly sequence planning. Little work has been done on quantitative analysis of configurable product disassemblability. The disassemblability modeling technology for configurable product based on disassembly constraint relation weighted design structure matrix （DSM） is proposed. Major factors affecting the disassemblability of configurable product are analyzed, and the disassembling degrees between components in configurable product are obtained by calculating disassembly entropies such as joint type, joint quantity, disassembly path, disassembly accessibility and material compatibility. The disassembly constraint relation weighted DSM of configurable product is constructed and configuration modules are formed by matrix decomposition and tearing operations. The disassembly constraint relation in configuration modules is strong coupling, and the disassembly constraint relation between modules is weak coupling, and the disassemblability configuration model is constructed based on configuration module. Finally, taking a hydraulic forging press as an example, the decomposed weak coupling components are used as configuration modules alone, components with a strong coupling are aggregated into configuration modules, and the disassembly sequence of components inside configuration modules is optimized by tearing operation. A disassemblability configuration model of the hydraulic forging press is constructed. By researching the disassemblability modeling technology of product configuration design based on disassembly constraint relation weighted DSM, the disassembly property in maintenance, recycling and reuse of configurable product are optimized.

AModel for the Optimization of the Shale Gas HorizontalWell Section Based on the Combination of Different Weighting Methods in the Frame of the Game Theory

Existing“evaluation indicators”are selected and combined to build a model to support the optimization of shale gas horizontal wells.Towards this end,different“weighting methods”,including AHP and the so-called entropy method,are combined in the frame of the game theory.Using a relevant test case for the implementation of the model,it is shown that the horizontal section of the considered well is in the middle sweet spot area with good physical properties and fracturing ability.In comparison with the FSI(flow scanner Image)gas production profile,the new model seems to display better abilities for the optimization of horizontal wells.

Empirical Research on the Relationship between Education Poverty Alleviation and Rural Revitalization—Spatial Panel Simultaneous Equation Model Based on Provincial Panel Data

On the basis of using entropy weight method to measure China’s education poverty alleviation and rural revitalization evaluation indicators, using the panel data of 30 provinces in China (excluding Xizang, Hong Kong, Macao and Taiwan) from 2012 to 2021, a spatial panel simultaneous equation model is constructed based on adjacency matrix, geographical distance matrix and economic geographical distance matrix deeply study the interaction mechanism and spatial spillover effects between education poverty alleviation and rural revitalization through the generalized spatial three-stage least squares method (GS3SLS). The results indicate that there is a significant spatial spillover effect and a positive spatial correlation between education poverty alleviation and rural revitalization, and there is a significant interactive effect between the two variables, while promoting each other positively. Therefore, the government should clarify the deep relationship between education poverty alleviation and rural revitalization based on the current background, and better consolidate and expand the effective connection between the achievements of education poverty alleviation and rural revitalization.

New Retrieval Method Based on Relative Entropy for LanguageModeling with Different Smoothing Methods

A language model for information retrieval is built by using a query language model to generate queries and a document language model to generate documents. The documents are ranked according to the relative entropies of estimated document language models with respect to the estimated query language model. Two popular and relatively efficient smoothing methods, the Jelinek- Mercer method and the absolute discounting method, are used to smooth the document language model in estimation of the document language, A combined model composed of the feedback document language model and the collection language model is used to estimate the query model. A performacne comparison between the new retrieval method and the existing method with feedback is made, and the retrieval performances of the proposed method with the two different smoothing techniques are evaluated on three Text Retrieval Conference （TREC） data sets. Experimental results show that the method is effective and performs better than the basic language modeling approach; moreover, the method using the Jelinek-Mercer technique performs better than that using the absolute discounting technique, and the perfomance is sensitive to the smoothing peramters.

Fermentation process modeling of exopolysaccharide using neural networks and fuzzy systems with entropy criterion

The prediction accuracy and generalization of fermentation process modeling on exopolysaccharide (EPS) production from Lactobacillus are often deteriorated by noise existing in the corresponding experimental data. In order to circumvent this problem, a novel entropy-based criterion is proposed as the objective function of several commonly used modeling methods, i.e. Multi-Layer Perceptron (MLP) network, Radial Basis Function (RBF) neural network, Takagi-Sugeno-Kang (TSK) fuzzy system, for fermentation process model in this study. Quite different from the traditional Mean Square Error (MSE) based criterion, the novel entropy-based criterion can be used to train the parameters of the adopted modeling methods from the whole distribution structure of the training data set, which results in the fact that the adopted modeling methods can have global approximation capability. Compared with the MSE- criterion, the advantage of this novel criterion exists in that the parameter learning can effectively avoid the over-fitting phenomenon, therefore the proposed criterion based modeling methods have much better generalization ability and robustness. Our experimental results confirm the above virtues of the proposed entropy-criterion based modeling methods.

Research on the navigational risk of liquefied natural gas carriers in an inland river based on entropy:A cloud evaluation model

Due to the flammability and explosive nature of liquefied natural gas(LNG),an extremely strict process is followed for the transporta-tion of LNG carriers in China.Particularly,no LNG carriers are operating in inland rivers within the country.Therefore,to ensure the future navigation safety of LNG carriers entering the Yangtze River,the risk sources of LNG carriers’navigation safety must be identi-fied and evaluated.Based on the Delphi and expert experience method,this paper analyses and discusses the navigation risk factors of LNG carriers in the lower reaches of the Yangtze River from four aspects(human,ship,environment and management),identifies 12 risk indicators affecting the navigation of LNG carriers and establishes a risk evaluation index system.Further,an entropy weight fuzzy model is utilized to reduce the influence of subjective judgement on the index weight as well as to conduct a segmented and overall evaluation of LNG navigation risks in the Baimaosha Channel.Finally,the cloud model is applied to validate the consistent feasibility of the entropy weight fuzzy model.The research results indicate that the method provides effective technical support for further study on the navigation security of LNG carriers in inland rivers.

Evaluation on Urban Land Ecological Security Based on the PSR Model and Matter-Element Analysis: A Case Study of Zhuhai, Guangdong, China

As one of the Special Economic Zones since the reform and opening up, Zhuhai has developed during the past 30 years. Its economic development, industrial structure and ecological environment have undergone great changes. Research on changes in Zhuhai’s land ecological security is of great significance. Using relevant data from 2007-2012, this study established a land ecological security assessment system based on the PSR conceptual framework model. The system contained 18 indicators from 3 aspects according to the concrete features of Zhuhai. Then we used the matterelement analysis and the improved entropy weight to analyze and evaluate the land ecological security of Zhuhai. The results showed that: from 2007 to 2012, the levels of the land ecological security of Zhuhai were “secure”, and the value increased year by year;as the land ecological security response value increased, Zhuhai was capable of solving land ecosystem problems. However, it should be noted that the structure of land ecosystem in Zhuhai has not formed and that rapid expansion of construction land has caused the shortage of cultivated land and other issues. Measures should be taken to control the construction area, improve land intensive utilization and improve the land ecological security.

On grey relation projection model based on projection pursuit

Multidimensional grey relation projection value can be synthesized as one-dimensional projection value by using projection pursuit model. The larger the projection value is,the better the model. Thus,according to the projection value,the best one can be chosen from the model aggregation. Because projection pursuit modeling based on accelerating genetic algorithm can simplify the implementation procedure of the projection pursuit technique and overcome its complex calculation as well as the difficulty in implementing its program,a new method can be obtained for choosing the best grey relation projection model based on the projection pursuit technique.

Study on Entropy Weight Coefficient Method and Application for Water Quality Evaluation

In order to evaluate the quality of water environment, the conception of entropy is applied in information science, and the entropy weight model is built to evaluate comprehensively water quality. The indexes weights of water quality are determined by value of entropy. This kind of method is applied on evaluating water quality in the new water to be built. The result shows that the water quality in it which supply water is between grade Ⅲ and Ⅳ, and the result is similar to that of gray related method.

Evaluation Model of Teaching Quality Based on Cloud Computing

In the teaching quality evaluation, due to the influence of various human factors, the teaching quality evaluation system is presented with some grey characteristics. Traditional evaluation methods cannot solve the problem effectively. Through gray relational analysis, the grey system of partial information known and unknown can be analyzed. It is difficult for the qualitative description language evaluation index to use traditional mathematical model for accurate representation. In this paper, cloud model is combined with grey relational analysis, and an evaluation method is proposed based on the cloudgrey relational analysis, in order to realize the mutual transformation between the qualitative information and quantitative numerical. Three university teachers’ information was collected by questionnaire survey, and the teaching quality was evaluated through the evaluation model based on grey relational analysis built in MATLAB. The results were compared with those of fuzzy comprehensive evaluation and the BP neural network evaluation. The results show that the teaching quality evaluation model based on cloud grey relational analysis has certain rationality and feasibility.

网络视角下航空公司竞争态势及影响因素研究

为剖析疫情时期中国国内主要客运航空公司竞争格局和竞争优势的影响因素,利用TOPSIS-熵值法和修正Huff模型量化航空公司在航线上的竞争优势强度,构建基于优势强度的航空公司-航线赋权二分网络,从网络的视角对航空公司竞争优势市场划分及其静态特征进行研究,利用Tobit回归模型剖析竞争优势的影响因素。研究表明:在疫情时期航空公司多市场接触程度较低,三大航空公司竞争优势明显,其优势在城市分布上差异巨大,主要集中在其基地城市。HU、3U等航空公司在市场竞争中优势不明显,更多表现为竞争且主要围绕沿海二线城市展开;航空公司竞争优势受到多因素共同制约,疫情时期收益更多表示成本控制的能力,低成本航空公司9C相较HU、3C等航空公司更具优势。

基于熵权-TOPSIS法的绿色城市发展水平评价研究:以济南市为例

绿色城市是绿色发展理念的载体和新型城镇化高质量发展的目标,开展绿色城市发展水平评价研究具有重要的现实意义。界定绿色城市的内涵,采用驱动力-状态-响应模型,构建绿色城市发展水平评价指标体系,基于济南市2018—2022年间的指标数据,综合运用熵权法和TOPSIS模型展开绿色城市发展水平实证研究。结果表明:研究期内济南市绿色城市发展水平整体表现为上升趋势,现已达到良好水平且进入优化发展阶段。针对性地提出对策与建议,以期为济南市绿色城市发展提供借鉴。

基于云模型的“一带一路”沿线省份国际冷链物流发展水平评价研究

在全球消费需求日益扩大的背景下,冷链产品进出口量剧增,为冷链物流提供新的发展机遇。为研究区域间国际冷链物流发展水平差异,考虑营商环境和地理因素,构建国际冷链物流发展水平评价指标体系,运用熵权-云模型对国际冷链物流发展水平进行评价,以“一带一路”沿线省份为例进行实证分析。结果表明:71%的省份国际冷链物流发展水平处于中上水平。在营商环境、基础设施和地理环境方面存在发展差异,其中进出口总额、冷藏车数、国际联系强度和对外开放水平是影响发展的主要因素。空间上,沿海省份国际冷链物流发展水平高于内陆省份,北部地区呈现“一核一副,周边聚集”的特征,东南沿海地区呈带状分布,西北地区呈现“中部低,两端高”的特征。

组合赋权法在卷烟机综合性能评价中应用

【目的】客观准确地评价卷烟机设备性能,从质量水平、消耗水平和效能水平3个维度出发,构建设备综合性能评价指标体系和组合赋权评价模型。【方法】利用最大熵原理给出最优组合系数和方案评价计算步骤。开展Topsis方法、层次分析法、熵值法和组合赋权法在卷烟机设备综合性能评价的实例分析和比较工作。【结果】4种方法具有显著正相关关系,评价结果满足一致性。组合赋权法与其他评价方法相比具有最优组合系数和误差平方和小优势。