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).
ردیف | عنوان | نوع |
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61 |
Data-driven automated discovery of variational laws hidden in physical systems
کشف خودکار داده های محور از قوانین تغییر یافته پنهان در سیستم های فیزیکی-2020 The automated discovery of physical laws from discrete noisy data is significant for eval- uating the response, stability, and reliability of dynamic systems. In contract to the exist- ing work on the discovery of differential laws, this paper presents a data-driven method to discover the variational laws of physical systems. The effectiveness and robustness to measurement noise are demonstrated with five physical cases. Two features of variational laws, the compact form and holistic viewpoint, lead to two intrinsic advantages in the data-driven discovery of variational laws, namely, reduced data requirement and robust- ness to noise. The presented data-driven method can be applied to discover variational laws in real time for physical fields or more complicated social sciences, with or without prior knowledge. |
مقاله انگلیسی |
62 |
Online adaptive water management fault diagnosis of PEMFC based on orthogonal linear discriminant analysis and relevance vector machine
تشخیص خطای مدیریت آب انطباقی آنلاین PEMFC بر اساس تجزیه و تحلیل تمایز خطی متعامد و دستگاه بردار ارتباط-2020 A data-driven strategy for characterizing the water management failure in a Proton Exchange
Membrane Fuel Cell (PEMFC) is presented in this paper. To carry out the diagnosis
of water management failure, first the original single cell voltages are projected into lowerdimension
features by applying orthogonal linear discriminant analysis (OLDA). Then, a
classification methodology termed relevance vector machine (RVM) is employed to classify
the lower-dimension features into different categories that indicate the respective health
states of the system. The initially trained projecting vectors and classifiers lose their efficiency
gradually the characteristics of PEMFC system change, such as the cell voltages
decaying with time due to the normal degradation due to aging. An online adaptive diagnostic
strategy based on the posterior probability of RVM is proposed, so as to keep the
diagnostic accuracy over time. The efficiency and reliability of this online adaptive diagnostic
strategy is validated using an experimental database from a 90-cell PEMFC stack. Keywords: Proton exchange membrane fuel cell | (PEMFC) | Orthogonal linear discriminant | analysis (OLDA) | Relevance vector machine (RVM) | Water management failure | Online adaptive diagnostics |
مقاله انگلیسی |
63 |
Mining and Utilization of Special Information for Archives Management Based on 5G Network and Internet of Things
استخراج و استفاده از اطلاعات ویژه برای مدیریت بایگانی بر اساس شبکه 5G و اینترنت اشیا-2020 5G technology is currently in the process of demographic data, data mining, the next-generation mobile networks are considered to be one of the main factors. Through research and data analysis, are expected to overcome the complexity of these networks, and it will be possible to carry out dynamic management and business operations. It is a trade item in that category, which is a particular file. Data collection chosen field of study is the core part. These files are considered to know how it organize their files and save them for future posterity. Finally, deal with digitized archive material; these traditional archives sought to highlight the problems faced by the digital age. Issues related to critical skills of a digitized archive of documents as extended support for mobile telephone networks, and can be considered the next generation of ultra-fast 5G network technology. 5G network includes all kinds of advanced technology, to provide excellent service. Therefore, new architecture and applications of new technology service management solutions should be advised to resolve reliability issues and ensure data transmission capacity, high data rates, and Quality of services (QoS). Cloud computing, networking, as well as software-defined network technology are some of the core networks 5G. Cloud-based service, providing flexible and efficient solutions for information and communication technologies by reducing the cost of the investment and management of information technology infrastructure. In terms of functionality are decoupled control and data planes to support programmability, flexibility and adaptability in a changing network architecture promising architecture. Keywords: Quality of services (QoS) | Internet of things (IoT) | Programmability | Flexibility | 5G network |
مقاله انگلیسی |
64 |
A contingency based energy management strategy for multi-microgrids considering battery energy storage systems and electric vehicles
یک استراتژی مدیریت انرژی مبتنی بر شرایط احتمالی برای چند میکروگرید با توجه به سیستم های ذخیره انرژی باتری و وسایل نقلیه الکتریکی-2020 The emergence of microgrids along with extending the use of new energy resources, energy storage systems and
electric vehicles at distribution level has changed traditional distribution systems into multi-microgrids (MMGs)
which are usually more stable and reliable. For an MMG system, the probability of a fault occurrence at each
time period makes the system operation process more complex. From this point of view, this paper aims at
proposing a coordinated energy management strategy for optimal operation of MMG systems using a variable
weighted multi-objective function. Based on this method, in the case of occurrence of a contingency problem,
multiple operators are able to change the weight of functions depending on contingencies and are responsible for
the proper use of energy storage systems and other distributed energy resources. Moreover, an efficient optimization
algorithm called targeted search shuffled complex evolution is proposed to quickly optimize decision
parameters during faulted and normal operation modes. Finally, a unified framework is presented to implement
the proposed energy management strategy along with the reliability study of the intended test system, and the
ability of the proposed approach is investigated in a modified reliability-based case study by considering different
scenarios Keywords: Energy management strategy | Energy storage systems | Electric vehicles (EVs) | Multi-microgrid (MMG) | Optimization | Shuffled complex evolution |
مقاله انگلیسی |
65 |
Z-number based earned value management (ZEVM): A novel pragmatic contribution towards a possibilistic cost-duration assessment
مدیریت ارزش به دست آمده مبتنی بر عدد Z (ZEVM): سهم عملگرا جدید نسبت به ارزیابی هزینه تمام شده احتمالی-2020 The Earned value management (EVM) is one of the simplified analytical cost-duration assessment tools which
assist project managers in monitoring the status of the project undertaken. The EVM has been elaborated by both
deterministic and uncertain numbers such as fuzzy logic in the light of time. Even though cost-duration analysis
is so sensitive and fluctuating in projects, the adopted approaches were unable to consider the conspicuous
unreliability which is always involving the decision-making data. This problem impedes project managers to
trust the foreseen inferences. To help in overcoming this critical deficiency, Z-numbers were proposed to take
possibilities and reliabilities into account. Applying Z-numbers and possibilistic modeling in the EVM is a
challenging topic which causes the accuracy of cost-duration tracing results to be significantly enhanced. This
paper presents the application of z-numbers for modeling the earned value indicators and proves the superiority
of the ZEVM against traditional fuzzy EVM. This work originally adds to the state-of-the-art literature on earned
value management by presenting a proposal and applications of a new as Z-Earned Value Management (ZEVM).
An illustrative case is resolved to magnify the capability of the proposed framework in dealing with higher levels
of uncertainty associated with decision-making data. Keywords: Earned value management | Fuzzy sets | Project evaluation | Uncertainty | Z-number |
مقاله انگلیسی |
66 |
الگوریتم تکاملی چند هدفه مبتنی بر شبکه عصبی برای زمانبندی گردش کار پویا در محاسبات ابری
سال انتشار: 2020 - تعداد صفحات فایل pdf انگلیسی: 16 - تعداد صفحات فایل doc فارسی: 45 زمانبندی گردشکار یک موضوع پژوهشی است که به طور گسترده در محاسبات ابری مورد مطالعه قرار گرفته است و از منابع ابری برای کارهای گردش کار استفاده می¬شود و برای این منظور اهداف مشخص شده در QoS را لحاظ می¬کند. در این مقاله، مسئله زمانبندی گردش کار پویا را به عنوان یک مسئله بهینه سازی چند هدفه پویا (DMOP) مدل می¬کنیم که در آن منبع پویایی سازی بر اساس خرابی منابع و تعداد اهداف است که ممکن است با گذر زمان تغییر کنند. خطاهای نرم افزاری و یا نقص سخت افزاری ممکن است باعث ایجاد پویایی نوع اول شوند. از سوی دیگر مواجهه با سناریوهای زندگی واقعی در محاسبات ابری ممکن است تعداد اهداف را در طی اجرای گردش کار تغییر دهد. در این مطالعه یک الگوریتم تکاملی چند هدفه پویا مبتنی بر پیش بینی را به نام الگوریتم NN-DNSGA-II ارائه می¬دهیم و برای این منظور شبکه عصبی مصنوعی را با الگوریتم NGSA-II ترکیب می¬کنیم. علاوه بر این پنج الگوریتم پویای مبتنی بر غیرپیش بینی از ادبیات موضوعی برای مسئله زمانبندی گردش کار پویا ارائه می¬شوند. راه¬حل¬های زمانبندی با در نظر گرفتن شش هدف یافت می¬شوند: حداقل سازی هزینه ساخت، انرژی و درجه عدم تعادل و حداکثر سازی قابلیت اطمینان و کاربرد. مطالعات تجربی مبتنی بر کاربردهای دنیای واقعی از سیستم مدیریت گردش کار Pegasus نشان می¬دهد که الگوریتم NN-DNSGA-II ما به طور قابل توجهی از الگوریتم¬های جایگزین خود در بیشتر موارد بهتر کار می¬کند با توجه به معیارهایی که برای DMOP با مورد واقعی پارتو بهینه در نظر گرفته می¬شود از جمله تعداد راه¬حل¬های غیرغالب، فاصله¬گذاری Schott و شاخص Hypervolume. |
مقاله ترجمه شده |
67 |
AI and Reliability Trends in Safety-Critical Autonomous Systems on Ground and Air
روند هوش مصنوعی و قابلیت اطمینان در سیستمهای خودمختار ایمنی در زمین و هوا-2020 Safety-critical autonomous systems are
becoming more powerful and more integrated to enable
higher-level functionality. Modern multi-core SOCs are
often the computing backbone in such systems for which
safety and associated certification tasks are one of the key
challenges, which can become more costly and difficult to
achieve. Hence, modeling and assessment of these systems
can be a formidable task. In addition, Artificial Intelligence
(AI) is already being deployed in safety critical autonomous
systems and Machine Learning (ML) enables the
achievement of tasks in a cost-effective way.
Compliance to Soft Error Rate (SER) requirements is an
important element to be successful in these markets. When
considering SER performance for functional safety, we need
to focus on accurately modeling vulnerability factors for
transient analysis based on AI and Deep Learning
workloads. We also need to consider the reliability
implications due to long mission times leading to high
utilization factors for autonomous transport. The reliability
risks due to these new use cases also need to be
comprehended for modeling and mitigation and would
directly impact the safety analysis for these systems. Finally,
the need for telemetry for reliability, including capabilities
for anomaly detection and prognostics techniques to
minimize field failures is of paramount importance. Index Terms : SER | safety | AI | ML. reliability |
مقاله انگلیسی |
68 |
An efficient interactive framework for improving resilience of power-water distribution systems with multiple privately-owned microgrids
یک چارچوب تعاملی کارآمد برای بهبود مقاومت در برابر سیستم های توزیع آب و انرژی با چندین میکروگرید متعلق به بخش خصوصی-2020 Resilience improvement of power distribution networks against natural disasters is an important problem. Water
network similar to other important infrastructures depends on power networks. In this paper, resilience improvement
is defined as increasing the users’ accessibility to water and power after natural disasters. Microgrids
with appropriate operation can provide energy to restore disconnected loads in distribution networks. In the
proposed interactive framework, a stochastic energy management program for microgrids is designed that not
only determines the amount of energy can be delivered to distribution systems, but also considers the reliability
of local loads during emergency conditions. Each microgrid provides a list of bid-quantity energy blocks to the
distribution system operator (DSO) during the emergency period. Then, the DSO chooses the best plan to restore
disconnected loads considering inaccessibility values to power and water and also the damage of power and
water distribution networks. Demand response actions in microgrids are also considered as effective tools for the
energy management program, and their impact on the distribution system resilience is investigated. The proposed
model is tested on the modified IEEE 33-bus distribution system with multiple microgrids, and the effectiveness
of the proposed method is validated accordingly. Keywords: Microgrids | Natural disasters | Resilience | Stochastic linear programming | Water network |
مقاله انگلیسی |
69 |
Energy management in multi-microgrids considering point of common coupling constraint
مدیریت انرژی در چند میکروگرید با توجه به محدودیت اتصال مشترک-2020 There are different models for Energy Management of Multi-Microgrids (MMGs). Generally, the owners of microgrids
are not identical. In this case, due to privacy concerns and overcomes drawbacks of conventional decentralized
systems, hybrid energy management system is proposed. Unlike other energy management models,
in hybrid model, multi-microgrids are connected to the grid through the common line entitled Point of Common
Coupling (PCC). Energy management in hybrid multi-microgrids considering optimal utilization of PCC capacity
is a critical issue that has been less taken into account. In this paper, a new bi-level method is proposed for
optimal energy management in hybrid MMG systems taking into account the PCC line capacity. In the first level,
each microgrid implements its day-ahead scheduling based on different quantities of PCC line capacity and
extracts its profit-quantity curve. This novel curve shows the variations of microgrid profits versus different PCC
limits. Subsequently, a two-stage optimization problem is presented in the second level, in which in the first
stage an introduced microgrid aggregator (MGA) maximizes microgrids aggregated profit and determines optimal
quota of each microgrid from PCC line based on corresponding profit-quantity curves while in the second
stage, this profit is fairly divided among microgrids via Shapely value. Numerical results demonstrate the efficiency
and reliability of the proposed method. Keywords: Energy management | Multi microgrid | Aggregator | Congestion | Common line |
مقاله انگلیسی |
70 |
Solder joint reliability risk estimation by AI modeling
برآورد خطر قابلیت اطمینان اتصال لحیم کاری با مدل سازی هوش مصنوعی -2020 This paper studies AI modeling for the solder joint
fatigue risk estimation under the thermal cycle loading of
redistributed wafer level packaging. The artificial neural
network (ANN), recurrent neural network (RNN) and
vectorized-gate network long short-term memory (VNLSTM)
architectures have been trained by the same dataset
to investigate their performance for this task. The learning
accuracy criterion, the implementation of all neural
network architecture, the learning results and result
analysis would be covered.
Because the involvement of the time/temperaturedependent
nonlinearity material characteristics, it is
recommended that more than three hidden layers and a
proper neural network architecture, which is capable of the
sequential data processing, should be considered in order
to guarantee the required accuracy and the satisfied
convergence speed. Keywords: Solder joint fatigue risk estimation | Time/temperature-dependent nonlinearity | ANN | RNN | LSTM | machine learning |
مقاله انگلیسی |