I Can Make It!

When some one makes your day,they do something that makes you happy.When you make the most of something,you get as much good out of it as you can.When you make do,you use what you have.

A decision support system for satellite layout integrating multi-objective optimization and multi-attribute decision making

A decision support system, including a multi-objective optimization framework and a multi-attribute decision making approach is proposed for satellite equipment layout. Firstly, given three objectives (to minimize the C.G. offset, the cross moments of inertia and the space debris impact risk), we develop a threedimensional layout optimization model. Unlike most of the previous works just focusing on mass characteristics of the system, a space debris impact risk index is developed. Secondly, we develop an efficient optimization framework for the integration of computer-aided design (CAD) software as well as the optimization algorithm to obtain the Pareto front of the layout optimization problem. Thirdly, after obtaining the candidate solutions, we present a multi-attribute decision making approach, which integrates the smart Pareto filter and the correlation coefficient and standard deviation (CCSD) method to select the best tradeoff solutions on the optimal Pareto fronts. Finally, the framework and the decision making approach are applied to a case study of a satellite platform.

Solution to multiple attribute group decision making problems with two decision makers

A kind of multiple attribute group decision making （MAGDM） problem is discussed from the perspective of statistic decision-making. Firstly, on the basis of the stability theory, a new idea is proposed to solve this kind of problem. Secondly, a con- crete method corresponding to this kind of problem is proposed. The main tool of our research is the technique o~ the jackknife method. The main advantage of the new method is that it can identify and determine the reliability degree of the existed decision making information. Finally, a traffic engineering example is given to show the effectiveness of the new method.

Large-Scale Group Decision Making:A Systematic Review and a Critical Analysis

The society in the digital transformation era demands new decision schemes such as e-democracy or based on social media.Such novel decision schemes require the participation of many experts/decision makers/stakeholders in the decision processes.As a result,large-scale group decision making(LSGDM)has attracted the attention of many researchers in the last decade and many studies have been conducted in order to face the challenges associated with the topic.Therefore,this paper aims at reviewing the most relevant studies about LSGDM,identifying the most profitable research trends and analyzing them from a critical point of view.To do so,the Web of Science database has been consulted by using different searches.From these results a total of 241 contributions were found and a selection process regarding language,type of contribution and actual relation with the studied topic was then carried out.The 87 contributions finally selected for this review have been analyzed from four points of view that have been highly remarked in the topic,such as the preference structure in which decision-makers’opinions are modeled,the group decision rules used to define the decision making process,the techniques applied to verify the quality of these models and their applications to real world problems solving.Afterwards,a critical analysis of the main limitations of the existing proposals is developed.Finally,taking into account these limitations,new research lines for LSGDM are proposed and the main challenges are stressed out.

Feed back Mechanism in Decision Support Systems

Feedback mechanism is a specific feature of control systems, however, the similarity has been found in decision support systems. Just because of this, the DSS can provide a flexible learning and thinking environment, and help decision maker to solve semistructured and unstructured problems actively and creatively. In this paper, the role and type of the feedback in decision making are discussed from different point of view. This is also true in DSS because it supports decision making. The feedback design, especially the feedback interface design, is described through a case of practice DSS. Based on these points, the feedback mechanism is an important feature of DSS, and it is one of the differences between DSS and MIS.

A Model-Based, Aspiration-Led Decision Support System NY-IEDSS

An AI-aided simulation system embedded in a model-based, aspiration-led decision support system NY-IEDSS is reported. The NY-IEDSS is designed for mid-term development strategic study of the Nanyang Region in Henan, China, and is getting beyond its prototype stage under the decision maker's (the end user) orientation. The integration of simulation model system, decision analysis and expert system for decision support in the system implementation was reviewed. The intent of the paper is to provide insight as to how system capability and acceptability can be enhanced by this integration. Moreover, emphasis is placed on problem orientation in applying the method.

Decision Making Support System(DSS)——A Synthesized and Integrated Crystallization of Systems Engineering, Artificial Intelligence and Electronic Technologies

I firmly believe that of systems engineering is the requirement-driven force for the progress ofsoftware engineering, artificial intelligence and electronic technologies. The development ofsoftware engineering, artificial intelligence and electronic technologies is the technical supportfor the progress of systems engineering. INTEGRATION can be considered as "bridging" the ex-isting technologies and the People together into a coordinated SYSTEM.

CNOOC Makes Efforts to Open up Overseas Business

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Latitudinal gradients of biodiversity and ecosystem services in protected and non-protected oak forest areas can inform climate smart conservation

Adaptive governance of areas set aside for future protection of biodiversity,sustainable production,and recreation requires knowledge about whether and how effects of area protection are modulated by climate change and redistribution of species.To investigate this,we compare biodiversity of plants(assessed using vegetation plots)and arthropods(collected with Malaise traps,analyzed using metabarcoding)and productivity(tree growth,determined using dendrochronology)in protected and non-protected oak(Quercus spp.)forests along a latitudinal gradient(55.6°N–60.8°N)in Sweden.We also compare historical,recent and projected future climate in the region.In contrast to established global latitudinal diversity gradients,species richness of plants and arthropods increased northwards,possibly reflecting recent climate-induced community redistributions,but neither was higher in protected than in non-protected areas,nor associated with contemporary ground temperature.Species composition of arthropods also did not differ between protected and non-protected areas.Arthropod biomass increased with latitude,suggesting that the magnitude of cascading effects mediated via their roles as pollinators,herbivores,and prey for other trophic levels,varies geographically and will change with a moving climate.Annual growth rate of oaks(an ecosystem service in the form of biomass increase and carbon sequestration)was independent of latitude and did not differ between protected and non-protected areas.Our findings question the efficacy of contemporary designation and management of protected oak forests,and emphasize that development and implementation of modified climate smart conservation strategies is needed to safeguard ecosystem functioning,biodiversity,and recreational values of protected forest areas against future challenges.

A Large-Scale Group Decision Making Model Based on Trust Relationship and Social Network Updating

With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted.

To make choice,to compromise and to grow up

美国作家路易莎·梅·奥尔科特(Louisa May Alcott)的小说《小妇人》(Little Women)已经四次被搬上荧屏,而最近的2019年版更是还未公映便已获得奥斯卡六项提名,着实令人期待。《小妇人》的故事围绕南北战争时期马奇(March)家四姐妹如何彼此珍惜,一起应对艰难时局的种种挑战展开。四姐妹性格迥异,大姐梅格(Meg)个性温柔,向往成为贤妻良母;二姐乔(Jo)热情好动,像个假小子,渴望成为作家.

Weapon system selection based on trust network and probabilistic hesitant fuzzy entropy

In order to solve the problem of uncertainty and fuzzy information in the process of weapon equipment system selec-tion,a multi-attribute decision-making(MADM)method based on probabilistic hesitant fuzzy set(PHFS)is proposed.Firstly,we introduce the concept of probability and fuzzy entropy to mea-sure the ambiguity,hesitation and uncertainty of probabilistic hesitant fuzzy elements(PHFEs).Sequentially,the expert trust network is constructed,and the importance of each expert in the network can be obtained by calculating the cumulative trust value under multiple trust propagation paths,so as to obtain the expert weight vector.Finally,we put forward an MADM method combining the probabilistic hesitant fuzzy entropy and grey rela-tion analysis(GRA)model,and an illustrative case is employed to prove the feasibility and effectiveness of the method when solving the weapon system selection decision-making problem.

Group Decision-Making Based on GIS and MultiCriteria Analysis for Assessing Land Suitability for Agriculture

Themain purpose of this work is to propose amethodology that considers themulticriteria andmulti-actor aspects for assessing land suitability for agriculture.This involves offering a group spatial decision-making approach.The members of a multidisciplinary team can decide on the relative importance of the criteria and the ranking of alternatives.Each member provides his judgment and contributes in a distinct and identifiable manner to find a compromise solution.Twelve criteria(easily available water reserve,cation exchange capacity,electric conductivity,potential of hydrogen(pH),drainage,permeability,active limestone,soil texture,soil useful depth,slopes,labor availability,and proximity to roads)grouped into four factors(agronomy,planning and socio-economy,land enhancement and improvement,conservation of soils and environmental protection)were selected in this study.The methodology consists of calculating the initial criteria weights using the AHP method.The final weights are obtained using the Consensual Convergence Model(CCM),and the decision-maker’s performance is aggregated using the ELECTRE Tri method.All the required processing methods were integrated into a GIS environment.The methodological developments were motivated by an application to the suitability of land for durum wheat cultivation in a study area in Mleta,Algeria,which is comprised of 74 land units.Every criterion was classified from the best to the poor based on its values and used for assessing land suitability for agriculture.The land units were assigned to different predefined classes.The final results are presented as a map produced according to the optimistic procedure of ELECTRE Tri.The greatest contribution of this research lies in integrating group decisionmaking in multicriteria spatial decisions,particularly the land suitability for agriculture,which has never been previously addressed.The consistency of the obtained map confirms the methods’effectiveness.

An Effective Prediction Method for Supporting Decision Making in Real Estate Area Selection

Real estate has been a dominant industry in many countries. One problem for real estate companies is determining the most valuable area before starting a new project. Previous studies on this issue mainly focused on market needs and economic prospects, ignoring the impact of natural disasters. We observe that natural disasters are important for real estate area selection because they will introduce considerable losses to real estate enterprises. Following this observation, we first develop a self-defined new indicator named Average Loss Ratio to predict the losses caused by natural disasters in an area. Then, we adopt the existing ARIMA model to predict the Average Loss Ratio of an area. After that, we propose to integrate the TOPSIS model and the Grey Prediction Model to rank the recommendation levels for candidate areas, thereby assisting real estate companies in their decision-making process. We conduct experiments on real datasets to validate our proposal, and the results suggest the effectiveness of the proposed method.

Maximizing Supermarket Profits:Data-Driven Strategies for Pricing,Sales,and Forecasting

The actual circumstances of daily life are crucial for the purchasing and pricing strategies of supermarkets.Developing strategies based on these circumstances can assist businesses in ensuring profits and fostering win-win cooperation.This paper explores methods to maximize profit through purchasing and sales strategies.Initially,the relevant data for various categories of vegetables is integrated.Through histograms,their sales patterns are directly understood,highlighting the most popular vegetables.Upon analyzing each vegetable category,it becomes evident that their sales data do not conform to normal distributions.Therefore,Spearman correlation coefficients are calculated,revealing strong correlations between certain categories,such as aquatic roots and edible fungi.A line chart depicting the top ten selling vegetables indicates a noticeable periodicity.Traditional fitting methods struggle to adequately model the sales of each vegetable category and their relationship with cost-plus pricing.To address this,additional factors such as holidays,weeks,and months are incorporated using techniques like random forest regression.This approach yields cost-plus pricing dependence curves that better capture the relationship,while effectively managing noise.Regarding sales volume prediction,the original data displays significant volatility,necessitating the handling of outliers using the threshold method.For missing data,linear interpolation is employed to mitigate the impact of continuous missing values on prediction accuracy.Subsequently,Adam-optimized long short-term memory(LSTM)networks are utilized to forecast incoming quantities for the next seven days.By extrapolating from normal sales volume,market capacity is estimated,allowing for additional sales through discount strategies.This framework has the potential to increase original income by 1.1 times.

An Evaluation of the Critical Success Factors in Sustainable Food Supply Chains in Developing Countries

Food is one of the biggest industries in developed and underdeveloped countries. Supply chain sustainability is essential in established and emerging economies because of the rising acceptance of cost-based outsourcing and the growing technological, social, and environmental concerns. The food business faces serious sustainability and growth challenges in developing countries. A comprehensive analysis of the critical success factors (CSFs) influencing the performance outcome and the sustainable supply chain management (SSCM) process. A theoretical framework is established to explain how they are used to examine the organizational aspect of the food supply chain life cycle analysis. This study examined the CSFs and revealed the relationships between them using a methodology that included a review of literature, interpretative structural modeling (ISM), and cross-impact matrix multiplication applied in classification (MICMAC) tool analysis of soil liquefaction factors. The findings of this research demonstrate that the quality and safety of food are important factors and have a direct effect on other factors. To make sustainable food supply chain management more adequate, legislators, managers, and experts need to pay attention to this factor. In this work. It also shows that companies aiming to create a sustainable business model must make sustainability a fundamental tenet of their organization. Practitioners and managers may devise effective long-term plans for establishing a sustainable food supply chain utilizing the recommended methodology.

中外企业知识分享模式研究——基于MAKE获奖企业的分析

本文首先通过对2010年以来MAKE获奖数据的分析,对比全球企业在Global MAKE(全球MAKE大奖)和China MAKE(中国MAKE大奖)中的表现,并对两个奖项的评选指标进行数据分析,选择"组织知识分享"这一近年来国外企业知识管理的关注热点作为研究对象,从MAKE获奖企业名单中选取青岛啤酒和斯伦贝谢作为企业知识分享的国内外优秀案例,对企业知识分享的原因、发展过程、模型及措施等进行系统的对比分析,以期为我国企业知识管理与创新提供借鉴。

动态系统理论视域下英语专业学习者虚化动词发展研究——以make为例

基于动态系统理论的研究视角,参照词汇深度知识的分类、发展框架以及语料库语言学的词汇共选理念与工作程序,从使用频率、类联接、搭配、近义词网络拓展等四个维度,分别对大学英语专业不同年级学习者使用虚化动词make的发展轨迹进行考察。研究表明:make内部四个不同维度及同一维度下各方面有各自的变异轨迹,呈现出非线性、复杂性的发展态势。

基于语料库的高中英语写作中高频动词MAKE的使用研究

本文以总词数相当的两个子语料库——牛津高中英语教材M1到M7七个模块中46篇Reading和Project中的文章以及任教的两个高二班级学生的210篇英语作文2为研究语料,主要对比分析了两大子语料库中MAKE使用频率相对较高的使役动词、虚化动词及实意动词用法。研究发现,学生作文语料库中MAKE使用次数远远超过牛津高中英语教材中MAKE出现的次数,这说明教材中的语篇并未对学生使用MAKE起到直接导向的作用,并且在作文语料库中学生过度使用、错用MAKE的现象较为普遍。因此,本文还就学生作文语料库中MAKE的过度使用、错用等原因进行了探究,以期对高中英语写作教学起到一定的帮助作用。

Solid Waste Management:A MADM Approach Using Fuzzy Parameterized Possibility Single-Valued Neutrosophic Hypersoft Expert Settings

The dramatic rise in the number of people living in cities has made many environmental and social problems worse.The search for a productive method for disposing of solid waste is the most notable of these problems.Many scholars have referred to it as a fuzzy multi-attribute or multi-criteria decision-making problem using various fuzzy set-like approaches because of the inclusion of criteria and anticipated ambiguity.The goal of the current study is to use an innovative methodology to address the expected uncertainties in the problem of solid waste site selection.The characteristics(or sub-attributes)that decision-makers select and the degree of approximation they accept for various options can both be indicators of these uncertainties.To tackle these problems,a novel mathematical structure known as the fuzzy parameterized possibility single valued neutrosophic hypersoft expert set(ρˆ-set),which is initially described,is integrated with a modified version of Sanchez’s method.Following this,an intelligent algorithm is suggested.The steps of the suggested algorithm are explained with an example that explains itself.The compatibility of solid waste management sites and systems is discussed,and rankings are established along with detailed justifications for their viability.This study’s strengths lie in its application of fuzzy parameterization and possibility grading to effectively handle the uncertainties embodied in the parameters’nature and alternative approximations,respectively.It uses specific mathematical formulations to compute the fuzzy parameterized degrees and possibility grades that are missing from the prior literature.It is simpler for the decisionmakers to look at each option separately because the decision is uncertain.Comparing the computed results,it is discovered that they are consistent and dependable because of their preferred properties.