با سلام خدمت کاربران عزیز، به اطلاع می رساند ترجمه مقالاتی که سال انتشار آن ها زیر 2008 می باشد رایگان بوده و میتوانید با وارد شدن در صفحه جزییات مقاله به رایگان ترجمه را دانلود نمایید.
Performance assessment of coupled green-grey-blue systems for Sponge City construction
ارزیابی عملکرد سیستم های سبز و خاکستری-آبی همراه برای ساخت و ساز شهر اسفنجی-2020
In recent years, Sponge City has gained significant interests as a way of urban water management. The kernel of Sponge City is to develop a coupled green-grey-blue system which consists of green infrastructure at the source, grey infrastructure (i.e. drainage system) at the midway and receiving water bodies as the blue part at the terminal. However, the current approaches for assessing the performance of Sponge City construction are confined to green-grey systems and do not adequately reflect the effectiveness in runoff reduction and the impacts on receiving water bodies. This paper proposes an integrated assessment framework of coupled green-grey-blue systems on compliance of water quantity and quality control targets in Sponge City construction. Rainfall runoff and river system models are coupled to provide quantitative simulation evaluations of a number of indicators of landbased and river quality. A multi-criteria decision-making method, i.e., Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is adopted to rank design alternatives and identify the optimal alternative for Sponge City construction. The effectiveness of this framework is demonstrated in a typical plain river network area of Suzhou, China. The results demonstrate that the performance of Sponge City strategies increases with large scale deployment under smaller rainfall events. In addition, though surface runoff has a dilution effect on the river water quality, the control of surface pollutants can play a significant role in the river water quality improvement. This framework can be applied to Sponge City projects to achieve the enhancement of urban water management.
Keywords: Low impact development | Sponge City | Green-grey-blue system | Performance assessment | TOPSIS
Multi-criteria decision-making considering risk and uncertainty in physical asset management
تصمیم گیری چند معیار با توجه به ریسک و عدم اطمینان در مدیریت دارایی های فیزیکی-2020
In this work we present a method for risk-informed decision-making in the physical asset management context whereby risk evaluation and cost-benefit analysis are considered in a common framework. The methodology uses quantitative risk measures to prioritize projects based on a combination of risk tolerance criteria, cost-benefit analysis and uncertainty reduction metrics. There is a need in the risk and asset management literature for a unified framework through which quantitative risk can be evaluated against tolerability criteria and trade-off decisions can be made between risk treatment options. The methodology uses quantitative risk measures for loss of life, loss of production and loss of property. A risk matrix is used to classify risk as intolerable, As Low As Reasonably Practicable (ALARP) or broadly tolerable. Risks in the intolerable and ALARP region require risk treatment, and risk treatment options are generated. Risk reduction benefit of the treatment options is quantified, and cost-benefit analysis is performed using discounted cashflow analysis. The Analytic Hierarchy Process is used to derive weights for prioritization criteria based on decision-maker preferences. The weights, along with prioritization criteria for risk reduction, tolerance criteria and project cost, are used to prioritize projects using the Technique for Order Preference by Similarity to Ideal Solution. The usefulness of the methodology for improved decision-making is illustrated using a numerical example.
Keywords: Risk analysis | Uncertainty | Asset management | Multi-criteria decision analysis | Risk matrix | Cost-benefit analysis
A decision framework of offshore wind power station site selection using a PROMETHEE method under intuitionistic fuzzy environment: A case in China
چارچوب تصمیم گیری برای انتخاب سایت نیروگاه بادی فراساحلی با استفاده از یک روش PROMETHEE در محیط فازی شهودی: یک مورد در چین-2020
Multi-criteria decision-making (MCDM) method has a widely application in management and energy field. Considering the broad development prospects of offshore wind power and deficiency of integrated coastal management, a decision framework combining triangular intuitionistic fuzzy numbers (TIFNs), Analytic Network Process (ANP) and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) is proposed and applied in site selection of offshore wind power station (OWPS). The aim of this study is to provide theoretical and methodological support for the site selection decision-making of coastal wind power projects and to improve the benefits of integrated coastal management. Taking six criteria (wind resources, construction, economic, environment, society, risk) and the related sub-criteria into consideration, an evaluation system of OWPS site selection is established. The optimal location scheme is determined by the decision framework in current paper. After a sensitivity analysis and a comparative analysis, the result shows that decision framework has strong robustness and feasibility. Thus, the evaluation criteria and methodology in this paper can provide a theoretical reference for the development of coastal management and offshore wind power.
Keywords: Offshore wind power station | Site selection | Triangular intuitionistic fuzzy numbers | ANP | PROMETHEE
Analytic network process: Academic insights and perspectives analysis
فرآیند شبکه تحلیلی: بینش دانشگاهی و تحلیل چشم اندازها-2019
Diversity multi-criteria decision-making methods have been developed to address different complex decision-making problems, and the analytic network process has been found to be one of the most effective techniques. There is an increase in the quality and quantity of publications related to the analytic network process. This detailed overview can provide the research status and development characteristics of analytic network process research and will be useful to researchers for future research directions. To achieve these goals, bibliometric techniques were used. In addition, past and present hotspots of analytic network process research were concluded, and future research trends were determined. The bibliometric analysis was carried out from various aspects including countries and regions, institutions, journals, authors, research areas, articles and author keywords based on data harvested from the Web of Science database. There were 1485 analytic network process-related publications retrieved from theWeb of Science. The results show that Expert Systems with Applications was the most productive journal publishing articles in analytic network process research (118); its number of publications has decreased dramatically since 2013, while Journal of Cleaner Production has shown an upward trend in recent years and ranks second with 47 publications. The most collaborative country is the United States. Taiwan takes a leading position in analytic network process research with 436 publications (29.36%), and National Chiao Tung University, which is located in Taiwan, produced the most articles and has gained the highest h-index (28). The major hot topics that employ analytic network process are sustainability, environmental management and supply chain management. These topics may continue to attract more attention in the future.
Keywords: Analytic Network Process | Web of science | Bibliometrics | Hot topics | Sustainability | Environmental management | Supply chain management
A comparative assessment of flood susceptibility modeling using Multi- Criteria Decision-Making Analysis and Machine Learning Methods
ارزیابی مقایسه ای مدل سازی حساسیت به سیل با استفاده از روش های تصمیم گیری چند معیاره و روشهای یادگیری ماشین-2019
Floods around the world are having devastating effects on human life and property. In this paper, three Multi-Criteria Decision-Making (MCDM) analysis techniques (VIKOR, TOPSIS and SAW), along with two machine learning methods (NBT and NB), were tested for their ability to model flood susceptibility in one of China’s most flood-prone areas, the Ningdu Catchment. Twelve flood conditioning factors were used as input parameters: Normalized Difference Vegetation Index (NDVI), lithology, land use, distance from river, curvature, altitude, Stream Transport Index (STI), Topographic Wetness Index (TWI), Stream Power Index (SPI), soil type, slope and rainfall. The predictive capacity of the models was evaluated and validated using the Area Under the Receiver Operating Characteristic curve (AUC). While all models showed a strong flood prediction capability (AUC > 0.95), the NBT model performed best (AUC=0.98), suggesting that, among the models studied, the NBT model is a promising tool for the assessment of flood-prone areas and can allow for proper planning and management of flood hazards.
Keywords: Flood susceptibility | Machine Learning | Multi-Criteria Decision-Making | GIS | China
Using combined multi-criteria decision-making and data mining methods for work zone safety: A case analysis
استفاده از روشهای تصمیم گیری چند معیار و داده کاوی برای ایمنی در منطقه کار: تحلیل مورد-2019
Work zone accidents are important concerns for transportation decision-makers. Therefore, knowledge of driving behaviors and traffic patterns are essential for identifying significant risk factors (RF) in work zones. Such knowledge can be difficult obtain in a field study without introducing new risks or driving hazards. This research uses integrated data mining and multi-criteria decision-making (MCDM) methods as part of a simulatorbased case study of work zone logistics along a highway in Missouri. The research design incorporates k-mean clustering to cluster driving behavior trends, analytic network process (ANP) to determine weights for criteria that are most likely to impact work zones, and the Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method to rank the alternatives (clusters). Transportation engineers and decision makers can use results from this case study to identify driving populations most likely to engage in risky driving behaviors within work zones, and to provide guidance on effective work zone management.
Keywords: Work zone accidents | Case study | Multi-criteria decision-making | Data mining | k-mean clustering | ANP | VIKOR method
A fuzzy-based decision aid method for product deletion of fast moving consumer goods
یک روش کمک به تصمیم فازی مبتنی بر فاز برای حذف محصول کالاهای مصرفی سریع در حال حرکت-2019
Technological and market cycles pressure organizations to introduce new products. To make room for the new products, product deletion (PD) decisions are inevitable. PD implementation, however, is beyond the reactive elimination of mature or low-profit products. As a competitive and proactive managerial tool, PD requires incorporation of supply chain financial and non-financial attributes to not only benefit organizations, but also maintain important partnerships. To successfully apply strategic PD, consideration of a broader set of decision factors is necessary. To update the traditional view, this paper introduces supply chain and competitive factors to product deletion decision-making (PDDM). Given the complex multi-criteria problem, including both qualitative and quantitative factors and the relative uncertainties and interaction between the factors, a Nested-Fuzzy Inference System with Interactions (NFISI) model as part of a multi-stage, multi-method expert system is introduced to aid the decision-making process. The model is verified using a practical case in a major fast-moving consumer goods (FMCG) company. The priority of alternative products for deletion is obtained through the application of the developed model considering the newly introduced factors. The results provide initial, albeit idiosyncratic, insights with a discussion of practical implications. It is demonstrated that considering supply chain factors makes a difference in PDDM outcomes. A brief overview of research opportunities is finally presented to guide researchers in contributing to this under-studied subject.
Keywords: Product deletion | Supply chain | Fast-moving consumer goods | Multi-criteria decision-making | Fuzzy inference system
بررسی تصمیم گیری چند معیاره برای بهره وری انرژی در مهندسی خودرو
سال انتشار: 2018 - تعداد صفحات فایل pdf انگلیسی: 13 - تعداد صفحات فایل doc فارسی: 41
دولت های سراسر جهان، دستورالعمل هایی برای محاسبه بهره وری انرژی وسایل نقلیه و کل وسیله نقلیه جدید نه تنها به وسیله مدل ها ثبت کردند. این مقاله به مطالعه چندمعیاره تصمیم گیری (MCDM) مربوط به صنعت خودرو می پردازد. یک مرور منابع سیستماتیک در مورد مطالعات MCDM تا سال 2015 تا برای شناسایی الگوهای برنامه ها MCDM برای طراحی وسایل نقلیه با هدف کاهش مصرف سوخت و دستیابی کامل به دستورالعمل های بهره وری انرژی (به عنوان مثال، Inovar-Auto) منتشر کردیم. از 339 مقاله، 45 مقاله برای شرح برخی از تکنیکهای MCDM و ارتباط آن با صنعت خودرو شناسایی شد. سپس به طبقه بندی رایج ترین تکنیک و کاربرد MCDM در صنعت خودرو پرداختیم. رویکردهای یکپارچه بیشتر از موارد فردی بود. از روش های فازی برای مقابله با عدم اطمینان داده ها استفاده شد. با وجود دانش کافی در استفاده از MCDM در زمینه های مختلف صنعت خودرو، هیچ یک از آنها رابطه مستقیمی با بهره وری انرژی در طراحی ماشین ندارد. فرآیند تحلیل سلسله مراتبی به عنوان روشی کاربردی در صنایع خودرو شناخته شد.
کلید واژه ها: آنالیز چند معیاره | مدیریت تصمیم گیری چند معیاره | بهره وری انرژی
|مقاله ترجمه شده|
Developing an integrated risk management framework for agricultural water conveyance and distribution systems within fuzzy decision making approaches
ایجاد یک چارچوب مدیریت ریسک یکپارچه برای سیستم های انتقال و توزیع آب کشاورزی در رویکرد تصمیم گیری فازی-2018
Irrigation canal networks, as the primary agricultural water conveyance and delivery systems, are exposed to a variety of hazards affecting the water distribution processes. This study, for the first time, develops a comprehen sive risk management framework for the canal network through a Fuzzy Hierarchical method. In this regard, the risk is analyzed by a combination of probability, consequence, and vulnerability against identified hazards based on the hierarchical framework. The developed model is based on fuzzy numbers to consider the uncertainties arise from experts opinion. To aggregate the calculated risk in the hierarchical framework, the Fuzzy Simple Ad ditive Weighting (FSAW) approach was employed. To enhance the reliability of the water distribution system and decrease the risk of failure, six risk management alternatives are proposed based on the risk assessment re sults and the most significant hazards. To prioritize managerial scenarios, two sets of criteria were selected in cluding quantitative criteria (consisting of cost of operation and risk reduction) and a qualitative set (compromising social and operational criteria). The risk management scenarios were prioritized based on two rational multi-criteria decision-making (MCDM) methods of a Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Simple Additive Weighting (SAW). Regarding different degrees of importance of the criteria, a pair-wise comparison was conducted by a group of experts to determine the relative weight of the criteria. According to the risk assessment results, the riskiest hazards are poor maintenance, seepage, unex pected event, drought, and vandalism of the structure. Moreover, employing the MCDM model in risk-based
Keywords: Hierarchical risk assessment ، Risk management ، Irrigation canal network ، TOPSIS ، SAW
A hybrid fuzzy MCDM approach for mitigating airport congestion: A case in Ninoy Aquino International Airport
یک رویکرد ترکیبی فازی MCDM برای کاهش ازدحام فرودگاه: مورد در فرودگاه بین المللی نینوی آکوئینو-2017
In this paper, we introduce the application of an integrated fuzzy multi-criteria decision-making (MCDM) model to mitigate airport congestion which affects the on-time performance of airlines, operational reputation of airports, and air travel experience of passengers. In a classical approach, when congestion occurs at the destination airport while the aircraft is en-route, an air traffic flow management action is prompted for implementation. In selecting the most suitable action in the event of airport congestion, the decision must reflect the multiple criteria nature of the problem as well as the uncertainty and vagueness associated with the decision-making process; thus, an integrated fuzzy MCDM is adopted. The applicability of the proposed approach is demonstrated in a case study at Ninoy Aquino International Airport. It is found that stakeholders of the commercial aviation industry favored to apply rerouting, among other actions, as this satisfies aviation safety as the most prioritized criterion.
Keywords: Airport congestion | ANP | DEMATEL | Fuzzy set theory | TOPSIS