scholarly journals Multi-Criteria Analysis in the Decision-Making Approach for the Linear Ordering of Urban Transport Based on TOPSIS Technique

Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 274
Author(s):  
Sławomira Hajduk
Keyword(s):  
Decision Making ◽  
Smart Cities ◽  
Urban Transport ◽  
Linear Ordering ◽  
Future Research ◽  
Entropy Weight ◽  
Rapid Urbanization ◽  
Relative Closeness ◽  
Entropy Weight Method ◽  
Topsis Technique

The effects of urban transport are highly concerning. The rapid urbanization and motorization in smart cities have a huge impact on sustainability. The goal of the paper is to analyse the smart cities selected, in terms of the urban transport. This paper presents an overview of research works published between 1991 and 2020 concerning urban transport and MCDM (multi-criteria decision making). The author highlights the importance of decision-making criteria and their weight, as well as techniques. Seven criteria and forty-four objects were used as the input of the approach. The entropy weight method was used to compute the weight of each criterion. The TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) was applied to calculate the assessment and ranking of transport performance for each smart city. Portland was found to be the best location for transport enterprises and projects; Tbilisi was ranked last. The values of the relative closeness coefficient ranged from 0.03504 to 0.921402. Finally, some suggestions for future research are discussed.

scholarly journals A Decision-Making Approach Based on TOPSIS Method for Ranking Smart Cities in the Context of Urban Energy

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2691
Author(s):  
Sławomira Hajduk ◽  
Dorota Jelonek
Keyword(s):  
Decision Making ◽  
Smart Cities ◽  
Energy Performance ◽  
Linear Ordering ◽  
Topsis Method ◽  
Research Papers ◽  
The World ◽  
Urban Energy ◽  
World Council ◽  
Topsis Technique

This paper presents the use of multi-criteria decision-making (MCDM) for the evaluation of smart cities. During the development of the method, the importance of the decision-making approach in the linear ordering of cities was presented. The method of using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was proposed for the preparation of ranking. The method was verified by the application in the measurement of energy performance in smart cities. The authors conducted a literature review of research papers related to urban energy and MCDM published in the period from 2010 to 2020. The paper uses data from the World Council on City Data (WCCD). The research conducted allowed for the identification of the most popular MCDM techniques in the field of urban energy such as TOPSIS, AHP and DEA. The TOPSIS technique was used to organize and group the analyzed cities. Porto took the top position, whereas Buenos Aries was the last.

scholarly journals A FUZZY MULTI-ATTRIBUTE DECISION-MAKING METHOD UNDER RISK WITH UNKNOWN ATTRIBUTE WEIGHTS / NERAIŠKUSIS MAŽESNĖS RIZIKOS DAUGIATIKSLIS SPRENDIMŲ PRIĖMIMO METODAS SU NEŽINOMAIS PRISKIRIAMAIS REIKŠMINGUMAIS

2011 ◽  
Vol 17 (2) ◽  
pp. 246-258 ◽  
Author(s):  
Zuosheng Han ◽  
Peide Liu
Keyword(s):  
Decision Making ◽  
Data Types ◽  
Decision Matrix ◽  
Entropy Weight ◽  
Attribute Weights ◽  
Relative Closeness ◽  
Entropy Weight Method ◽  
Multi Attribute Decision Making ◽  
Weight Method ◽  
Multiple Attributes Decision Making

This paper aims at solving hybrid multiple attributes decision-making problems under risk with attribute weight known and a new decision approach based on entropy weight and TOPSIS is proposed. First, the risk decision matrix is transformed into the certain decision matrix based on the expectation value. Then, the deviation entropy weight method is used to determine the attribute weights. And according to the definitions of the distance and the positive/negative ideal solutions for different data types, the relative closeness coefficients can be calculated by TOPSIS. Furthermore, the alternatives are ranked by the relative closeness coefficients. Finally, an application case is given to demonstrate the steps and effectiveness of the proposed approach. Santrauka Šiame straipsnyje siekiama išspręsti mišrias mažesnės rizikos daugiatiksles sprendimo priėmimo problemas su žinomu priskiriamu reikšmingumu bei yra siūlomas naujas sprendimų priėmimo metodas grindžiamas entropijos reikšmingumu ir TOPSIS. Pirmiausia, rizikos sprendimų matrica yra transformuojama į tam tikrą sprendimų matricą, grindžiamą galimybės verte. Tuomet yra naudojamas entropijos reikšmingumo nuokrypio metodas norint nustatyti priskiriamą reikšmingumą. Atsižvelgiant į atstumo apibrėžimus ir teigiamus / neigiamus idealius sprendimus skirtingiems duomenų tipams, santykinio artumo koeficientas gali būti apskaičiuojami remiantis TOPSIS. Be to, alternatyvos yra reitinguojamos pagal santykinio artumo koeficientus. Galiausiai, yra pateiktas pritaikymo atvejis, siekiant parodyti visus žingsnius ir siūlomo metodo veiksmingumą.

scholarly journals Smart City Decision Making System Based on Event-driven Platform

2021 ◽  
Vol 12 (1) ◽  
pp. 99-110
Author(s):  
Andrej Saric ◽  
Ivona Zakarija ◽  
Vedran Batos ◽  
Srecko Krile
Keyword(s):  
Decision Making ◽  
Smart City ◽  
Energy Demand ◽  
Smart Cities ◽  
Future Research ◽  
Rapid Urbanization ◽  
Reliability Factor ◽  
Event Driven ◽  
Decision Making System ◽  
Decision Making Processes

Abstract With the occurrence of rapid urbanization and intensive growth of different modes of transport, we face issues such as resource management, energy demand and lack of capacity due to overcrowding. To help with these issues we leverage technology and the Internet of Things (IoT) to develop smart cities. In this paper, we propose an innovative approach to development of new smart city event-driven platform with which we want to simplify data input, data transformation, and decision making processes. The platform uses events, labels and reliability factor to make decisions and trigger actions. This paper begins with an overview of the smart city framework and we review the characteristics of event-driven models. The event-driven platform is presented and discussed. The paper closes with our findings, suggestions, open issues, and future research possibilities.

scholarly journals Decision-Making of Irrigation Scheme for Soybeans in the Huaibei Plain Based on Grey Entropy Weight and Grey Relation–Projection Pursuit

Entropy ◽  
2019 ◽  
Vol 21 (9) ◽  
pp. 877 ◽  
Author(s):  
Yi Cui ◽  
Shangming Jiang ◽  
Juliang Jin ◽  
Ping Feng ◽  
Shaowei Ning
Keyword(s):  
Decision Making ◽  
Water Consumption ◽  
Projection Pursuit ◽  
Crop Water ◽  
Irrigation Scheme ◽  
Entropy Weight ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Projection Pursuit Model ◽  
Grey Relation

To provide a scientific reference for formulating an effective soybean irrigation schedule in the Huaibei Plain, potted water deficit experiments with nine alternative irrigation schemes during the 2015 and 2016 seasons were conducted. An irrigation scheme decision-making index system was established from the aspects of crop water consumption, crop growth process and crop water use efficiency. Moreover, a grey entropy weight method and a grey relation–projection pursuit model were proposed to calculate the weight of each decision-making index. Then, nine alternative schemes were sorted according to the comprehensive grey relation degree of each scheme in the two seasons. The results showed that, when using the entropy weight method or projection pursuit model to determine index weight, it was more direct and effective to obtain the corresponding entropy value or projection eigenvalue according to the sequence of the actual study object. The decision-making results from the perspective of actual soybean growth responses at each stage for various irrigation schemes were mostly consistent in 2015 and 2016. Specifically, for an integrated target of lower water consumption and stable biomass yields, the scheme with moderate-deficit irrigation at the soybean branching stage or seedling stage and adequate irrigation at the flowering-podding and seed filling stages is relatively optimal.

scholarly journals A Method of Determining Multi-Attribute Weights Based on Single-Valued Neutrosophic Numbers and Its Application in TODIM

Symmetry ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 506 ◽  
Author(s):  
Dongsheng Xu ◽  
Yanran Hong ◽  
Kaili Xiang
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Entropy Weight ◽  
Attribute Weights ◽  
Attribute Weight ◽  
Decision Making Problem ◽  
Entropy Weight Method ◽  
Todim Method ◽  
Multi Attribute Decision Making ◽  
Weight Method

In this paper, the TODIM method is used to solve the multi-attribute decision-making problem with unknown attribute weight in venture capital, and the decision information is given in the form of single-valued neutrosophic numbers. In order to consider the objectivity and subjectivity of decision-making problems reasonably, the optimal weight is obtained by combining subjective weights and objective weights. Subjective weights are given directly by decision makers. Objective weights are obtained by establishing a weight optimization model with known decision information, then this method will compare with entropy weight method. These simulation results also validate the effectiveness and reasonableness of this proposed method.

scholarly journals Effectiveness of Entropy Weight Method in Decision-Making

2020 ◽  
Vol 2020 ◽  
pp. 1-5 ◽  
Author(s):  
Yuxin Zhu ◽  
Dazuo Tian ◽  
Feng Yan
Keyword(s):  
Decision Making ◽  
Water Source ◽  
Entropy Weight ◽  
Weighting Method ◽  
Numerical Discrimination ◽  
Differentiation Degree ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Degree Of Differentiation ◽  
Index Weight

Entropy weight method (EWM) is a commonly used weighting method that measures value dispersion in decision-making. The greater the degree of dispersion, the greater the degree of differentiation, and more information can be derived. Meanwhile, higher weight should be given to the index, and vice versa. This study shows that the rationality of the EWM in decision-making is questionable. One example is water source site selection, which is generated by Monte Carlo Simulation. First, too many zero values result in the standardization result of the EWM being prone to distortion. Subsequently, this outcome will lead to immense index weight with low actual differentiation degree. Second, in multi-index decision-making involving classification, the classification degree can accurately reflect the information amount of the index. However, the EWM only considers the numerical discrimination degree of the index and ignores rank discrimination. These two shortcomings indicate that the EWM cannot correctly reflect the importance of the index weight, thus resulting in distorted decision-making results.

Smart City Governance

2019 ◽  
pp. 1417-1453
Author(s):  
Maria do Rosário Matos Bernardo
Keyword(s):  
Decision Making ◽  
Content Analysis ◽  
Good Governance ◽  
Smart Cities ◽  
Future Research ◽  
Extensive Literature ◽  
Governance Practices ◽  
Smart Governance ◽  
Different Levels ◽  
Public Decision

Smart governance is one of the characteristics of smart cities, having its roots in e-government, in the principles of good governance, and in the assumptions of citizens' participation and involvement in public decision-making. This chapter aims to answer the question: “What smart governance practices are being implemented in smart cities” through an extensive literature review in the areas of e-government, good governance, smart cities and smart governance, and content analysis of the websites of seven smart cities: Amsterdam, Barcelona, Copenhagen, Lisbon, Manchester, Singapore, and Stockholm. The objective was to identify the presence of factors related with e-participation; e-services; and public administration functioning on the cities' websites. The chapter ends with directions for future research and the conclusion that all the smart cities analyzed presented some factors related with smart governance, but with different levels of development and application.

Smart City Governance

2017 ◽  
pp. 290-326 ◽  
Author(s):  
Maria do Rosário Matos Bernardo
Keyword(s):  
Decision Making ◽  
Content Analysis ◽  
Good Governance ◽  
Smart Cities ◽  
Future Research ◽  
Extensive Literature ◽  
Governance Practices ◽  
Smart Governance ◽  
Different Levels ◽  
Public Decision

Smart governance is one of the characteristics of smart cities, having its roots in e-government, in the principles of good governance, and in the assumptions of citizens' participation and involvement in public decision-making. This chapter aims to answer the question: “What smart governance practices are being implemented in smart cities” through an extensive literature review in the areas of e-government, good governance, smart cities and smart governance, and content analysis of the websites of seven smart cities: Amsterdam, Barcelona, Copenhagen, Lisbon, Manchester, Singapore, and Stockholm. The objective was to identify the presence of factors related with e-participation; e-services; and public administration functioning on the cities' websites. The chapter ends with directions for future research and the conclusion that all the smart cities analyzed presented some factors related with smart governance, but with different levels of development and application.

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