دانلود و نمایش مقالات مرتبط با Fuzzy decision::صفحه 1
دانلود بهترین مقالات isi همراه با ترجمه فارسی 2

با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد). 

نتیجه جستجو - Fuzzy decision

تعداد مقالات یافته شده: 12
ردیف عنوان نوع
1 Analysis of the innovation strategies for green supply chain management in the energy industry using the QFD-based hybrid interval valued intuitionistic fuzzy decision approach
تجزیه و تحلیل استراتژی های نوآوری برای مدیریت زنجیره تامین سبز در صنعت انرژی با استفاده از فاصله ترکیبی مبتنی بر QFD ، ارزش تصمیم گیری فازی شهودی-2021
This study aims to analyze the innovation strategies for the green supply chain management with QFD (quality function deployment) multidimensionally. The novelty of the study is to define the criteria of green supply chain for each stage of QFD and propose a hybrid model by IVIF (interval-valued intuitionistic fuzzy) DEMATEL (decision making trial and evaluation laboratory) and IVIF MOORA (Multi-Objective Optimization by Ratio Analysis) respectively. The results demonstrate that understanding the customer expectations with customer relation management is the most important innovation strategy for the green supply chain management in en- ergy industry with the consecutive stages of QFD whereas benchmarking the competitive market environment has relatively the last seat in the ranking. Hence, it is recommended that energy companies should have an effective customer relationship management. In this context, these companies should make a detailed analysis to learn what their customers directly expect from them. With the help of this issue, these companies should generate their product and services based on these expectations. Additionally, it is also stated that new service and product development is also essential for energy companies to improve their innovativeness. For this pur- pose, a research and development department should be created, and the qualified people should be employed. Additionally, different opinions should be collected from various parties, such as customers, employees, and suppliers. Since customers who are satisfied will prefer these companies, the energy companies can catch the opportunity to increase their market share.
Keywords: GSCM | Energy industry | Innovation | QFD | IVIF DEMATEL | IVIF MOORA
مقاله انگلیسی
2 A fuzzy decision system for money investment in stock markets based on fuzzy candlesticks pattern recognition
یک سیستم تصمیم گیری فازی برای سرمایه گذاری پول در بورس اوراق بهادار بر اساس تشخیص الگوی شمعدانهای فازی-2019
This article proposes a novel fuzzy recommendation system for stock market investors. This intelligent decision tool uses fuzzy Japanese candlesticks and includes the effect of currency devaluation on the forecasting. To do so, first the next market session is obtained by a new designed fuzzy forecasting trad- ing system. Then, it is compared to the one obtained by a non-parametric system based on the k-nearest neighbor technique. Finally, an amount of money to be invested is considered using a new capital man- agement fuzzy strategy. The results have been compared to an analogous fuzzy trading system that has the same all-or-nothing investment strategy with risk control, but where this capitalization is not in- cluded. Both intelligent decision systems have been applied to two very different stock markets, the American Nasdaq100 and the Spanish Ibex35 markets, using the Buy and Hold investment strategy as benchmark. Results prove that the proposed fuzzy system with capitalization is profitable and presents high stability, and could be a good support system for investors.
Keywords: Japanese candlestick | Fuzzy trading | Stock market forecasting | Capital management | Investment strategy | Recommendation system
مقاله انگلیسی
3 A fuzzy decision support system for managing maintenance activities of critical components in manufacturing systems
یک سیستم پشتیبانی تصمیم گیری فازی برای مدیریت فعالیت های نگهداری از قطعات مهم در سیستم های تولید-2019
Management of critical components in manufacturing systems aims at managing components with very low reliability or the highest risk which can cause disruptions in manufacturing. This study presents a method for identifying critical components and a decision support tool for managing maintenance activities of critical components in manufacturing systems. Unlike the traditional reliability function, the proposed method uses the duty cycle, utilization rate of capacity, safety stock effect, and redundancy effect. It also has the ability to calculate some of the costs associated with the reliability and maintenance. In addition to the proposed method, an expert system as a decision support tool has also been proposed to assist in managing maintenance activities of critical components. The proposed method and the developed decision support system have been tested with a real data set taken from an industrial company and a randomly generated data set. The results have shown that the proposed method has a more realistic impact on component reliability compared to the traditional reliability function. The experimental results have validated the credibility of the proposed decision support system to manage maintenance activities of critical components. Besides, two comparison tables have shown that the proposed decision support system outperforms some approaches such as ANN, FMEA, FMECA, and AHP.
Keywords: Critical component management | Maintenance management | Reliability | Fuzzy logic | Decision support sys
مقاله انگلیسی
4 Application of fuzzy decision tree in EOR screening assessment
کاربرد درخت تصمیم فازی در ارزیابی غربالگری EOR-2019
Ranking of best possible Enhanced Oil Recovery (EOR) technics for implementing on a target field is one of the most important questions that should be answered by reservoir engineers. EOR screening can be considered as a tool for recommending the most appropriate EOR methods. Although for each candidate reservoir, the applicability of EOR processes must be investigated specifically, EOR screening can be used as an indicator before economic evaluations or reservoir descriptions are done and executive decisions are made. Implementing an EOR project for predictions that pass this screening is the next step. In this study, the fuzzy decision tree method (with the ability to rank and classify EOR methods simultaneously) is introduced for EOR screening. Basic features for this study are permeability, viscosity, depth, temperature, saturation, and API. Using a fuzzy decision tree enables us to design an expert system which generates EOR rules automatically. This is one of the noticeable features of this study which reduces the importance of a human expert role while designing the system and making it as expert as possible. Here, the fuzzy decision tree method is implemented on a dataset consisting of 548 observations related to 10 different EOR techniques. Predictions made by this method which are ranked from the most applicable EOR method to the least one include the EOR method mentioned in the dataset for every observation in both training and test set. Moreover, using the procedure introduced here for training the trees enables the expert system to be adaptive whenever the dataset is updated
Keywords: Data mining | Expert system | Artificial intelligence algorithms | EOR screening | Fuzzy logic | Fuzzy decision tree | Automatic rule generation
مقاله انگلیسی
5 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
مقاله انگلیسی
6 On Distributed Fuzzy Decision Trees for Big Data
درخت تصمیم گیری فازی توزیع شده برای داده های بزرگ-2018
Fuzzy decision trees (FDTs) have shown to be an effective solution in the framework of fuzzy classification. The approaches proposed so far to FDT learning, however, have generally neglected time and space requirements. In this paper, we propose a distributed FDT learning scheme shaped according to the MapReduceprogrammingmodelforgeneratingbothbinaryandmultiway FDTs from big data. The scheme relies on a novel distributed fuzzy discretizer that generates a strong fuzzy partition for each continuous attribute based on fuzzy information entropy. The fuzzy partitions are, therefore, used as an input to the FDT learning algorithm, which employs fuzzy information gain for selecting the attributes at the decision nodes. We have implemented the FDT learning scheme on the Apache Spark framework. We have used ten real-world publicly available big datasets for evaluating the behavior of the scheme along three dimensions: 1) performance in terms of classification accuracy, model complexity, and execution time; 2) scalability varying the number of computing units; and 3) ability to efficiently accommodate an increasing dataset size. We have demonstrated that the proposed scheme turns out to be suitable for managing big datasets even with a modest commodity hardware support. Finally, we have used the distributed decision tree learning algorithm implemented in the MLLib library and the Chi-FRBCS-BigData algorithm, a MapReduce distributed fuzzy rule-based classification system, for comparative analysis
Index Terms: Apache spark, big data, fuzzy decision trees (FDTs), fuzzy discretizer, fuzzy entropy, fuzzy partitioning,MapReduce
مقاله انگلیسی
7 Critical success factors of sustainable project management in construction: A fuzzy DEMATEL-ANP approach
عوامل موفقیت بحرانی مدیریت پروژه های پایدار در ساخت و ساز: یک رویکرد DEMATEL-ANP فازی-2018
There is an extensive number of factors that influence the success and failure of projects, however, literature lacks an inclusive categorization of them especially in construction. This paper aims to identify critical success factors (CSFs) of project management and categorize them into five criteria groups: (1) project, (2) project management, (3) organization, (4) external environment and (5) sustainability. To determine the interdependence and weight of the CSFs, data was gathered from 26 Australian project managers from the construction industry. The contribution of the paper is in identifying cause and effect criteria of CSFs and in identifying their weights. Using the fuzzy decision making and evaluation labo ratory (fuzzy DEMATEL) method it is shown that the organization, external environment and sustain ability are “cause” criteria, while project and project management are identified as “effects”. The fuzzy analytic network process (fuzzy ANP) is used to weigh the sub-criteria by considering the interdepen dence of the main criteria. The findings revealed that the highest weights are assigned to top manage ment and sponsor support (s), stakeholder expectations (w45 ¼ 0:050) and end users imposed restrictions (w41 ¼ 0:039), respectively. Project managers can significantly improve project success by focusing on more important critical success factors rather than paying equal attention to all of them.
Keywords: Project management ، Sustainable construction ، Critical success factors ، Fuzzy DEMATEL ، Fuzzy ANP
مقاله انگلیسی
8 A Fuzzy Decision in Smart Fire and Home Security System
یک تصمیم فازی در سیستم هوشمند آتش و امنیت خانه-2017
There has been a major rise in the fire incidents occurring over the past few years in the Pacific Island Countries (PICs) and especially property fires are a major concern. Often it is noticed that these usually lead to loss of homes, personal belongings and even lives of people. Objective of this paper to present a monitoring device that is able to detect the presence of a gas leak and take action before there is an actual fire. To optimize the decision of the system, a fuzzy logic based smart rules are developed to avoid false alarming. The prototype system is designed considering cost, simplicity and reliability. Further, the proposed system helps to reduce fire accident by triggering alarm well-in advance and therefore it can react as an early warning system.© 2016 The Authors. Published by Elsevier B.V.Peer-review under responsibility of organizing committee of the 2016 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS 2016).© 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Peer-review under responsibility of organizing committee of the 2016 IEEE International Symposium on Robotics and Intelligent Sensors(IRIS 2016).
Keywords: Fuzzy decision | Safety device | Early warning system | Pacific Island Countries
مقاله انگلیسی
9 On Distributed Fuzzy Decision Trees for Big Data
درخت تصمیم گیری فازی توزیع شده برای داده های بزرگ-2017
Fuzzy decision trees (FDTs) have shown to be an effective solution in the framework of fuzzy classification. The approaches proposed so far to FDT learning, however, have generally neglected time and space requirements. In this paper, we propose a distributed FDT learning scheme shaped according to the MapReduce programming model for generating both binary and multi-way FDTs from big data. The scheme relies on a novel distributed fuzzy discretizer that generates a strong fuzzy partition for each continuous attribute based on fuzzy information entropy. The fuzzy partitions are therefore used as input to the FDT learning algorithm, which employs fuzzy information gain for selecting the attributes at the decision nodes. We have implemented the FDT learning scheme on the Apache Spark framework. We have used ten real-world publicly available big datasets for evaluating the behavior of the scheme along three dimensions: i) performance in terms of classification accuracy, model complexity and execution time, ii) scalability varying the number of computing units and iii) ability to efficiently accommodate an increasing dataset size. We have demonstrated that the proposed scheme turns out to be suitable for managing big datasets even with modest commodity hardware support. Finally, we have used the distributed decision tree learning algorithm implemented in the MLLib library and the Chi-FRBCS-BigData algorithm, a MapReduce distributed fuzzy rule-based classification system, for comparative analysis.
Keywords: Fuzzy Decision Trees | Big Data | Fuzzy Entropy | Fuzzy Discretizer | Apache Spark | MapReduce | Fuzzy Partitioning
مقاله انگلیسی
10 مدل تحلیل ریسک امنیت اطلاعات با استفاده از نظریه¬ی تصمیم¬گیری فازی
سال انتشار: 2016 - تعداد صفحات فایل pdf انگلیسی: 10 - تعداد صفحات فایل doc فارسی: 33
این مقاله یک مدل تحلیل ریسک برای ارزیابی امنیت اطلاعات ارائه می دهد که دنباله ای از رخدادها (اینها را آلترناتیو می نامیم) را شناسایی و ارزیابی می کند. این رخدادها در یک سناریوی تصادفی احتمالی اتفاق می-افتند که از وقوع یک رویداد آغازکننده ی متناظر با سوءاستفاده از سیستم های فناوری اطلاعات تبعیت می-کند. مقاله ی پیش رو به منظور انجام این ارزیابی، از تحلیل درخت رخداد ترکیب شده با نظریه ی تصمیم گیری فازی استفاده می کند. سهم پژوهشی طرح پیشنهادی شامل این موارد است: ایجاد دسته بندی برای سناریوها و رخدادها، رتبه بندی آلترناتیوها براساس بحرانی بودن ریسک، لحاظ نمودن زیان مالی، و نهایتاً فراهم نمودن اطلاعاتی در خصوص علل حملات به سیستم های اطلاعاتی در بالاترین رده ی مدیریتی برای سازمان ها. ما مثال مفصلی در خصوص مرکز داده با هدف نشان دادن قابلیت کاربردی مدل پیشنهادی، ارائه دادیم. برای ارزیابی نظام مندی آن، دوازده آلترناتیو را با در نظر گرفتن دو روش مختلف تعیین احتمالات وقوع رخدادها، تحلیل نمودیم. نتایج نشان داد که کاوش در حملات سرویس های پایگاه داده ی خارجی، خطرناک ترین آلترناتیو است.
کلیدواژه ها: امنیت اطلاعات | تحلیل ریسک | نظریه ی تصمیم گیری فازی.
مقاله ترجمه شده
rss مقالات ترجمه شده rss مقالات انگلیسی rss کتاب های انگلیسی rss مقالات آموزشی
logo-samandehi
بازدید امروز: 4987 :::::::: بازدید دیروز: 3097 :::::::: بازدید کل: 39254 :::::::: افراد آنلاین: 45