Regional Differences and Optimal Allocation of Cultivated Land Utilization Benefits Based on Improved TOPSIS Method:A Case Study of Guangxi

Taking 14 prefecture-level cities in Guangxi as an object,this paper explored the difference of cultivated land utilization efficiency in Guangxi,comprehensively evaluated the economic,social,and ecological aspects,and analyzed the regional differences in cultivated land use efficiency in Guangxi from 2005 to 2018 based on the improved TOPSIS method.By studying the quantitative change trends and spatial differences of the utilization benefit of cultivated land resources in Guangxi,it came up with recommendations for optimizing the allocation of cultivated land from the quantity and quality of cultivated land.It is intended to provide a scientific and theoretical reference for improving the use efficiency of cultivated land in Guangxi.

Ship System Maintenance Strategy Selection Based on DELPHI-AHP-TOPSIS Methodology

Maintenance decision problems generally involve multiple criteria which apparently are best addressed using Multi-Criteria Decision Making (MCDM) tools. This paper describes the use of a hybrid MCDM technique in prioritizing maintenance strategy for ship systems. The Hybrid MCDM technique combines Delphi method, AHP and TOPSIS methods. While the Delphi method and AHP are applied in screening of decision criteria and decision criteria weights determination respectively, the TOPSIS method is used in the ranking of alternative maintenance strategies. Five alternative maintenance strategies which include corrected maintenance, scheduled overhaul, scheduled replacement, continuous on-condition task and scheduled on-condition task are considered and the optimum maintenance strategy is selected based on twelve critical maintenance decision criteria. To demonstrate the suitability of the approach a case study of sea water pump of the central cooling system of a marine diesel engine is used.

Research on a TOPSIS energy efficiency evaluation system for crude oil gathering and transportation systems based on a GA-BP neural network

As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crude oil gathering and transportation systems and identify the energy efficiency gaps.In this paper,the energy efficiency evaluation system of the crude oil gathering and transportation system in an oilfield in western China is established.Combined with the big data analysis method,the GA-BP neural network is used to establish the energy efficiency index prediction model for crude oil gathering and transportation systems.The comprehensive energy consumption,gas consumption,power consumption,energy utilization rate,heat utilization rate,and power utilization rate of crude oil gathering and transportation systems are predicted.Considering the efficiency and unit consumption index of the crude oil gathering and transportation system,the energy efficiency evaluation system of the crude oil gathering and transportation system is established based on a game theory combined weighting method and TOPSIS evaluation method,and the subjective weight is determined by the triangular fuzzy analytic hierarchy process.The entropy weight method determines the objective weight,and the combined weight of game theory combines subjectivity with objectivity to comprehensively evaluate the comprehensive energy efficiency of crude oil gathering and transportation systems and their subsystems.Finally,the weak links in energy utilization are identified,and energy conservation and consumption reduction are improved.The above research provides technical support for the green,efficient and intelligent development of crude oil gathering and transportation systems.

Analysis of migraine in mutlicellular organism based on trapezoidal neutrosophic cubic hesitant fuzzy TOPSIS method

In this paper,we define a new idea of trapezoidal neutrosophic cubic hesitant fuzzy number based on migraine diseases.We define and the migraine diseases on trapezoidal neutrosophic cubic hesitant fuzzy number and operational laws of trapezoidal neutrosophic cubic hesitant fuzzy number and hamming distance of TrNCHFNs.The new concept of trapezoidal neutrosophic cubic hesitant fuzzy TOPSIS method is introduced.Furthermore,we extend MCDM method based on the trapezoidal neutrosophic cubic hesitant fuzzy TOPSIS method.Finally,an illustrative example is given to verify and demonstrate the practicality and effectiveness of the proposed method.

New type of cancer patients based on triangular cubic hesitant fuzzy TOPSIS method

In this paper,we define the new idea of triangular cubic hesitant fuzzy number(TCHFN).We discuss some basic operational laws of triangular cubic hesitant fuzzy number and hamming distance of TCHFNs.We introduce the new concept of triangular cubic hes­itant TOPSIS method.Furthermore,we extend the classical cubic hesitant the tech­nique for order of preference by similarity to ideal solution(TOPSIS)method to solve the Multi-Criteria decision-making(MCDM)method based on triangular cubic hesitant TOPSIS method.The new ranking method for TCHFNs is used to rank the alternatives.Finally,an illustrative example is given to verify and demonstrate the practicality and effectiveness of the proposed method.

Comparative Analysis of Pythagorean MCDM Methods for the Risk Assessment of Childhood Cancer

According to the World Health Organization(WHO),cancer is the leading cause of death for children in low and middle-income countries.Around 400,000 kids get diagnosed with this illness each year,and their survival rate depends on the country in which they live.In this article,we present a Pythagorean fuzzy model that may help doctors identify the most likely type of cancer in children at an early stage by taking into account the symptoms of different types of cancer.The Pythagorean fuzzy decision-making techniques that we utilize are Pythagorean Fuzzy TOPSIS,Pythagorean Fuzzy Entropy(PF-Entropy),and Pythagorean Fuzzy PowerWeighted Geometric(PFPWG).Ourmodel is fed with nineteen symptoms and it diagnoses the risk of eight types of cancers in children.We develop an algorithm for each method and calculate its complexity.Additionally,we consider an example to make a clear understanding of our model.We also compare the final results of various tests that prove the authenticity of this study.

Index system and methods for comprehensive assessment of cross-border power grid interconnection projects

With the global economy integration and progress in energy transformation,it has become a general trend to surpass national boundaries to achieve wider and optimal energy resource allocations.Consequently,there is a critical n eed to adopt scie ntific approaches in assessi ng cross-border power grid interconnection projects.First,con sidering the promotion of large-scale renewable energy resources and improvements in system adequacy,a comprehensive assessment index system,including costs,socio-economic benefits,environmental benefits,and technical benefits,is established in this study.Second,a synthetic assessment framework is proposed for cross-border power grid interconnection projects based on the index system comprising cost-benefit analysis,with market and network simulations,iterative methods for indicator weight evaluation,and technique for order preferenee by similarity to an ideal solution(TOPSIS)method for the project rankings.Fin ally,by assessi ng and comparing three cross-border projects betwee n Europe and Asia,the proposed index system and assessment framework have been proved to be effective and feasible;the results of this system can thus support investment decision-making related to such projects in the future.

Application of an Optimized Entropy-TOPSIS Multicriteria Decision Making Model to Facilities Management

Performance evaluation of facilities management plays a key role in the facilities management process. This paper proposes an optimized multicriteria decision making model to evaluate the performance of facilities management in schools in Hong Kong. In this model, entropy weights acted as weight coefficients for evaluated criteria in order to avoid uncertainty and randomicity of subjective judgments. Besides, the TOPSIS method was incorporated in this model. Then this model was em- ployed to evaluate the performance of facilities management in classrooms, offices and laboratories and satisfying results were obtained. Moreover, findings indicated that one of the schools could be rehabilitated rather than removed.

Extension of TOPSIS for fuzzy multi-attribute decision making problem based on experimental analysis

This paper is concerned with a technique for order performance by similarity to ideal solution（TOPSIS） method for fuzzy multi-attribute decision making,in which the information about attribute weights is partly known and the attribute values take form of triangular fuzzy numbers.Considering the fact that the triangular fuzzy TOPSIS results yielded by different distance measures are different from others,a comparative analysis of triangular fuzzy TOPSIS ranking from each distance measure is illustrated with discussion on standard deviation.By applying the most reasonable distance,the deviation degrees between attribute values are measured.A linear programming model based on the maximal deviation of weighted attribute values is established to obtain the attribute weights.Therefore,alternatives are ranked by using TOPSIS method.Finally,a numerical example is given to show the feasibility and effectiveness of the method.

TOPSIS based Taguchi design optimization for CVD growth of graphene using different carbon sources: Graphene thickness, defectiveness and homogeneity

Chemical inhomogeneity of chemical vapor deposition(CVD) grown graphene compromises its usage in highperformance devices. In this study, TOPSIS based Taguchi optimization was performed to improve thickness uniformity and defect density of CVD grown graphene. 1.56% decrease in the mean 2 D/G intensity ratio, 87.96% improvement in the mean D/G intensity ratio, 56.07% improvement in the standard deviation D/G intensity ratio, 25.21%improvement in the standard deviation 2 D/G intensity ratio, and 69.32% improvement in the surface roughness were achieved with TOPSIS based Taguchi optimization. The statistical differences between the copper and silicon substrates have been found significantly in terms of their impacts on the graphene's properties with the0.000 p-value for the mean D/G intensity ratio and with the 0.009 p-value for the mean 2 D/G intensity ratio, respectively. Graphene having 11% lower mean D/G intensity ratio(low defective graphene products) compared to the values given in the literature using single-response optimization was obtained using multi-response optimization.

On some new fuzzy entropy measure of Pythagorean fuzzy sets for decision-making based on an extended TOPSIS approach

Fuzzy entropy measures are valuable tools in decision-making when dealing with uncertain or imprecise information.There exist many entropy measures for Pythagorean Fuzzy Sets(PFS)in the literature that fail to deal with the problem of providing reasonable or consistent results to the decision-makers.To deal with the shortcomings of the existing measures,this paper proposes a robust fuzzy entropy measure for PFS to facilitate decision-making under uncertainty.The usefulness of the measure is illustrated through an illustration of decision-making in a supplier selection problem and compared with existing fuzzy entropy measures.The Technique for Order Performance by Similarity to Ideal Solution(TOPSIS)approach is also explored to solve the decision-making problem.The results demonstrate that the proposed measure can effectively capture the degree of uncertainty in the decision-making process,leading to more accurate decision outcomes by providing a reliable and robust ranking of alternatives.

The Synthetic Evaluation of Warhead Overall Efficiency

The evaluation system of smart ammunition warhead overall efficiency has been established in this paper. Allkinds of evaluation methods have been analyzed. Having led the concept of hierarchical structure into technique for orderpreference by similarity to ideal solution (TOPSIS) method, we put forward the step TOPSIS method which is suitable forevaluating the overall efficiency of smart ammunition warheads. In the calculation of index weight, the graded weight cal-culus is put forward which hardly relies on the subjectivity of decision-makers and can reflect the sensitivity and compatibili-ty of the index. In the graded weight calculation, the proportional-arithmetic weight value calculus and sensitivity-compati-bility weight value calculus are given respectively.

Comprehensive Evaluation on the Level of Agricultural Modernization in Eastern China

Based on correct understanding of the connotation and essence of agricultural modernization,according to the data in 2008 China Statistical Yearbook and the relevant literatures about eastern China,a total of 12 indices are selected to construct the evaluation index system of agricultural modernization in eastern China by combining with its social development and following the principles of systematization,comprehensiveness,representativeness,legitimacy and comparability.Then,according to the decision-making rules of modern science,3 alternatives are put forward and max compatibility degree method is used to generate the optimization solution.Result shows that agricultural modernization in eastern China can be classified into three types.The first type is Shanghai;the second type includes Zhejiang,Jiangsu,Fujian and Shandong;and the third type is Jiangxi and Anhui.The evaluation result is in accord with the actual situation of agricultural development in eastern China.Finally,since there still needs improvement in capital investment,rural education,agricultural science and technology research,peasant training,and social and organizational structure,it is pointed out that we should optimize the investment agriculture,enhance support for science and technology,perfect the mechanism of "promoting agriculture development by industry and developing the township by the city",and accelerate the development of agricultural modernization in eastern China.

Artificial Logging or Natural Growth

Global climate change makes forestry carbon sequestration a hot issue. In order to improve the comprehensive benefits of forest management, this paper studies the carbon accounting problem, and uses the forest stock conversion factor method to create a carbon sequestration accounting model based on the reserve transformation method. Then, the HWP carbon sequestration accounting algorithm is obtained after the improvement of the reserve change method and the atmospheric flow method with the HWP half-life as a bridge. Based on the ecological and economic benefits, a multi-objective and multi-attribute decision-making model for forest management plan is constructed, and the optimal strategy of stand structure based on selective cutting is proposed. Finally, the entropy weight TOPSIS method is used to quantitatively analyze the comprehensive benefit value and provide suggestions for forestry departments. To verify the model, we chose the Greater Khingan Mountains forest region as the research site. Through successive iterations of CSAM, we calculate that the forest will absorb 534 million tons of live forest and forest products in 100 years. From the stand structure of the forest area, when the selected cutting intensity is 20% and the selected cutting cycle is 10.7 years, the comprehensive benefit value of the Greater Khingan Mountains is the highest.

Framework on low-carbon retrofit of rural residential buildings in arid areas of northwest China:A case study of Turpan residential buildings

At present,buildings in arid and hot regions are facing severe challenges of indoor comfort improvement and carbon emission reduction,especially in rural areas.Multi-objective optimization could be an effective tool for tackling the aforementioned challenges.Therefore,this paper proposes a life-cycle optimization framework considering thermal comfort,which is beneficial to promoting residents’motivation for low-carbon retrofit in arid climate regions.First,in response to the above problems,three objective functions are specified in the framework,which are global warming potential(GWP),life cycle cost(LCC),and thermal discomfort hours(TDH).To improve the optimization efficiency,this research uses Deep Neural Networks(DNN)combined with NSGA-II to construct a high-precision prediction model(meta-model for optimization)based on the energy consumption simulation database formed by the orthogonal multi-dimensional design parameters.The accuracy index of the modified model is R2>0.99,cv(RMSE)≤1%,and NMBE≤0.2%,which gets rid of the dilemma of low prediction accuracy of traditional machine learning models.In the scheme comparison and selection stage,the TOPSIS based on two empowerment methods is applied to meet different design tendencies,where the entropy-based method can avoid the interference of subjective preference and significantly improve the objectivity and scientific nature of decision analysis.Additionally,sensitivity analysis is conducted on the variables,which supports guidance for practitioners to carry out the low-carbon design.Finally,the multi-objective optimization analysis for a farmhouse in Turpan is taken as a case study to evaluate the performance of the framework.The results show that the framework could significantly improve the building performance,with 60.8%,52.5%,and 14.2%reduction in GWP,LCC,and TDH,respectively.