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نتیجه جستجو - سیستم خبره فازی

تعداد مقالات یافته شده: 7
ردیف عنوان نوع
1 Smart frost measurement for anti-disaster intelligent control in greenhouses via embedding IoT and hybrid AI methods
اندازه گیری یخ زدگی هوشمند برای کنترل هوشمند ضد فاجعه در گلخانه ها از طریق تعبیه روش های اینترنت اشیا و هوش مصنوعی ترکیبی-2020
A novel Agro-industrial IoT (AIIoT) technology and architecture for intelligent frost forecasting in greenhouses via hybrid Artificial Intelligence (AI), is reported. The Internet of Things (IoT) allows the objects interconnection on the physical world using sensors and actuators via the Internet. The smart system was designed and implemented through a climatological station equipped with Artificial Neural Networks (ANN) and a fuzzy associative memory (FAM) for ecological control of the anti-frost disaster irrigation. The ANN forecasts the inside temperature of the greenhouses and the fuzzy control predicts the cropland temperatures for the activation of five output levels of the water pump. The results were compared to a Fourier-statistical analysis of hourly data, showing that the ANN models provide a temperature prediction with effectiveness higher than 90%, as compared to monthly data model. Moreover, results of this process were validated through the determination of the coefficient of variance analysis method (R2).
Keywords: Smart frost measurement in greenhouses | Anti-frost irrigation | Artificial Neural Network | Fuzzy expert system | Internet-of-things | Hybrid AI methods
مقاله انگلیسی
2 Design and implementation of the fuzzy expert system in Monte Carlo methods for fuzzy linear regression
طراحی و اجرای سیستم خبره فازی در روش های مونت کارلو برای رگرسیون خطی فازی-2019
In this study, fuzzy expert system (FES) in Monte Carlo (MC) method, which is used for estimating fuzzy linear regression model (FLRM) parameters, is applied to determine the parameter intervals, for the first time in the literature. MC method in estimating FLRM parameters is a new field of study that is very useful and time saving. However a major problem might occur in determining the parameter intervals from which the regression model parameters are supposed to come. If the intervals are calculated too large, FLRM error will be very large. Accordingly, the actual model parameters will not be obtained if the intervals are calculated too narrow. This drawback has not been addressed in the literature before and only optimization methods have been applied to achieve the best interval values. In this article, the FES is used for the first time in order to solve the problem in parameter estimation process for the FLRM in the field of statistics. For this purpose, the difference between the fuzzy observation value and fuzzy estimation value’s support set (W) is taken into account. The most appropriate intervals calculated for the parameters are those that make W as small as possible. Thus, FES is designed to determine the best intervals for the model parameters. The system knowledge base is composed of 7 fuzzy rules. As a result, it is deduced that the FLRM parameter estimates obtained from the MC method using FES are very close to the real values. The real impact of this paper will be in showing the applicability of FESs in order to solve problems that we encounter in the field of statistics by the help of linguistic expressions. Moreover, these outcomes will be useful for enriching the studies that have already focused on FLRMs and will encourage researchers to use FES to solve problems in statistics. To sum up, this study demonstrates that FESs which is used in technological devices and makes our lives easier can also be used in solving problems that we confront in the field of statistics efficiently with using linguistic expressions like human inference system.
Keywords: Fuzzy expert system | Fuzzy linear regression | Monte Carlo
مقاله انگلیسی
3 Design and implementation of an expert system for periodic and emergency control under uncertainty: A case study of city gate stations
طراحی و اجرای سیستم خبره برای کنترل دوره ای و اضطراری تحت عدم اطمینان: مطالعه موردی ایستگاه های دروازه شهر-2019
Safety analysis is essential in the natural gas transmission industry to guarantee effective hazard identification and to prevent the failure of components in advance. The overall aim of this research is to introduce a new hybrid expert system and fuzzy logic to monitor city gate stations as one of the most vital installations of gas distribution networks. The proposed model utilizes fuzzy if-then rules based on multiple experts opinions to study the compound interrelations between the mechanical and physical elements of city gate stations. The presented expert system accounts for uncertainty associated with the experts’ judgments by fuzzy sets theory. The expert system is implemented in an object-oriented platform and is programmed with C#. The validity of the expert system is confirmed using simulation experiments through a case study of city gate stations.
Keywords: City gate stations | Fuzzy expert system | Gas industry | Decision tree Uncertainty | Inference chain
مقاله انگلیسی
4 Fishbone model and universal authentication framework for evaluation of multifactor authentication in mobile environment
مدل fishbone و چارچوب احراز هویت جهانی برای ارزیابی تأیید هویت چند عامل در محیط سیار-2019
The trend of rapid evolutionary development of mobile technologies and the existence of different user’s priorities are creating new challenges with regard to selection of multifactor authentication (MFA) solutions. This becomes even more challenging by creating a univer- sal authentication framework (UAF). In order to cope with these challenges, this paper has proposed a Fishbone model and developed in form of the UAF which is based on a larger number of linguistic variables and a wider set of user’s priorities such as security, usability, accessibility, pricing, complexity, privacy and convenience (SUAPCPC). In comparison to all other papers available in the literature, the Fishbone model provides numerical evaluation of MFA with the possibility of changing weighted criteria for the selected user priorities. In addition, the contributions of this model are twofold. For user’s, to enable easier choice of MFA solution, for developers, to identify spots where a method or solution could be improved. For development of the Fishbone model, fuzzy methodology is used in form of a Fuzzy Expert System (FES) tool. Also, the block diagram and the basic modules of the Fish- bone model architecture are given. The results of implementation of the Fishbone model in form of the UAF have showed that this model is applicable and very efficient in practice. Finally, the Fishbone model gives an ideal template in UAF at which user’s priorities satisfy the best individual users’ solutions. The realization of this template presents challenge for all future developers of MFA solutions.
Keywords: Fishbone model | Universal authentication framework | (UAF) | Multifactor authentication (MFA) | SUAPCPC factors | Fuzzy Expert System (FES)
مقاله انگلیسی
5 A fuzzy expert system for mitigation of risks and effective control of gas pressure reduction stations with a real application
یک سیستم خبره فازی برای کاهش خطرات و کنترل مؤثر ایستگاه های کاهش فشار گاز با کاربرد واقعی-2019
Environmental changes and increased uncertainty due to technical damage, explosions and large fires have caused the risk of an inevitable element in the gas industry. This study purposes developing a new hybrid fuzzy expert system as a decision support system to mitigate the risk associated with gas transmission stations. The designed knowledge-based system combines the procedural and descriptive rules based on experts’ judgments to analyze the complex relationships between the different components of a gas pressure reduction station. The developed fuzzy expert system is coded in C language integrated production system (CLIPS) and is linked with MATLAB software for calling fuzzy functions. A real case study of gas pressure reduction stations in Iranian gas industry is conducted to validate the proposed expert system model. The expert system provides more than one thousand rules based on expert knowledge to prevent the pressure drop and the quality loss of gas or shutting off gas flow which accordingly increases gas flow stability. The proposed expert system could minimize the risk of hazardous scenarios, such as leakage and corrosion, in the gas industry and provide an acceptable precision in the provision of periodic control strategies and appropriate response under an emergency condition.
Keywords: Expert systems | Gas city stations | Decision support | Fuzzy variables | Gas pressure
مقاله انگلیسی
6 FSCT: A new fuzzy search strategy in concolic testing
FSCT: یک استراتژی جدید جستجوی فازی در آزمایش برش سنجی-2019
Context: Concolic testing is a promising approach to automate structural test data generation. However, combina- torial explosion of the path space, known as path explosion, and also constrained testing budget, makes achieving high code coverage in concolic testing a challenging task. Objective: All branches of the previously explored paths make up the search space of concolic testing and search strategy define the mechanism of choosing branches to be flipped to drive the execution toward testing goals. With regard to the large number of candidate branches, choosing the right branch to continue the search is so crucial and has a direct impact on coverage rate and effort. This paper aims to improve the effectiveness of branch testing by considering the characteristics of paths reaching uncovered branches and presenting a novel search strategy for effectively and efficiently exploring the search space. Method: We model the branch selection process in concolic testing as a decision making system and introduce a new Fuzzy Search Strategy in Concolic Testing (FSCT). FSCT chooses a branch to be filliped in which the most suitable path with respect to the proposed coverage factors reaches an uncovered branch with the highest priority and this priority is assigned by the designed fuzzy expert system. The proposed coverage factors effectively help to determine the characteristics of paths. Results: We implemented FSCT on top of CREST and evaluated it using several popular benchmarks. The experi- mental results show that FSCT outperforms the state-of-the-art techniques in terms of coverage rate and coverage effort. Conclusion: FSCT helps concolic testing to better cope with path explosion problem and shows its capabilities to achieve higher code coverage while at the same time decreases testing efforts in terms of both runtime and number of iterations.
Keywords: Software testing | Automatic test case generation | Concolic Testing | Fuzzy expert system
مقاله انگلیسی
7 یک سیستم خبره فازی برای ارزیابی ریسک صنعت هوایی
سال انتشار: 2009 - تعداد صفحات فایل pdf انگلیسی: 8 - تعداد صفحات فایل doc فارسی: 28
سیستم ارزیابی ریسک عملیات پرواز (FORAS) یکی از متدولوژی های مدلسازی ریسک است که عوامل ریسک و روابط متقابل آن ها را به صورت یک سیستم خبره فازی نشان می دهد. مدل ریسکFORAS یک شاخص ریسک نسبی کمّی ارائه می کند که نشان دهنده برآوردی از آثار تجمعی خطرات احتمالی بر عملیات پرواز است. FORAS فرایند استخراج تخصص انسانی را روشمند می سازد، تصویری طبیعی از دانش در یک سیستم خبره ارائه می دهد و فرایند ارزیابی ریسک را خودکار می سازد. ابزار FORAS به منظور بررسی روند ریسک برای واحدهای ایمنی شرکت های هواپیمایی، به منظور ارزیابی ریسک مرتبط با هر پرواز برای خلبان ها و دیسپچرها و به منظور محاسبه آثار ایجاد تغییرات مرتبط با ایمنی برای مدیریت خطوط هوایی ارزشمند است. شاخص ریسک نسبی کمّی که FORAS ایجاد می کند امکان مقایسه بین پروازها را فراهم می کند و اعلام مسائل ایمنی در سراسر سازمان را تسهیل می کند.
کلیدواژه ها: سیستم های مبتنی بر قواعد فازی | ارزیابی ریسک | ایمنی صنعت هوایی
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