A New Online Learned Interval Type-3 Fuzzy Control System for Solar Energy Management Systems

Liu, Zhi; Mohammadzadeh, Ardashir; Turabieh, Hamza; Mafarja, Majdi; Band, Shahab S.; Mosavi, Amir

doi:10.1109/access.2021.3049301

Cited by 126 publications

(58 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Designing sustainable and environmentally friendly buildings with the approach of reducing energy consumption in buildings [121][122][123][124] and optimal energy consumption in different parts of the building (cooling, heating, and lighting) is a smart solution to deal with this great concern [124][125][126][127]. Sustainable architecture is also called green architecture, a design that uses a natural building, which is energy-efficient in some way and has little or no effect on the nature and resources of a site [128][129][130][131].…”

Section: Discussionmentioning

confidence: 99%

Hotel Construction Management considering Sustainability Architecture and Environmental Issues

Kadaei

Sadeghian

Majidi

et al. 2021

Shock and Vibration

View full text Add to dashboard Cite

Sustainable development and environment in the activities of the construction industry has attracted the attention of experts in most countries of the world. One of the obvious and problematic features of the construction industry of countries is the use of modern building materials using traditional construction methods. Changing the paradigm for sustainable buildings requires a change in the architectural design process. Today, smart buildings are buildings that are at a lower level in terms of energy consumption and operate in a dynamic and integrated environment, creating a perfect harmony between management, system, services, and structure. These qualities make plastics ideal products for construction and an essential component for a sustainable built environment. In the design of smart and sustainable buildings, the use of environmentally friendly materials increases the lifespan of the building and an effective step is taken towards the design of sustainable architecture. In this paper, we evaluate hotel construction based on sustainability issues with MCDM. The results show that alternative A4 is the best alternative in sustainable issues. With the increasing population and its concentration in large cities, the concern of energy supply and energy efficiency in buildings is one of the main concerns of urban planners, officials, and city residents. Construction projects mainly consume large amounts of materials and leave a huge amount of waste, and this problem sometimes includes existing buildings that cannot be demolished and need to be rebuilt and maintained.

show abstract

Section: Discussionmentioning

confidence: 99%

Hotel Construction Management considering Sustainability Architecture and Environmental Issues

Kadaei

Sadeghian

Majidi

et al. 2021

Shock and Vibration

View full text Add to dashboard Cite

show abstract

“…The type-3 FLSs (T3-FLSs) have been recently developed to improve the estimation capability of conventional FLSs and improve the robustness against noisy environments. T3-FLSs have been employed in various practical problems, such as energy management [30], gyroscopes [31], forecasting problems [32], industrial 5G converters [33], and so on. In the aforementioned studies, it is verified that the developed T3-FLSs give a better performance in noisy conditions.…”

Section: Literature Reviewmentioning

confidence: 99%

Non-Singleton Type-3 Fuzzy Approach for Flowmeter Fault Detection: Experimental Study in a Gas Industry

Wang

Tavoosi

Mohammadzadeh

et al. 2021

Sensors

Self Cite

View full text Add to dashboard Cite

The main contribution of this paper is to develop a new flowmeter fault detection approach based on optimized non-singleton type-3 (NT3) fuzzy logic systems (FLSs). The introduced method is implemented on an experimental gas industry plant. The system is modeled by NT3FLSs, and the faults are detected by comparison of measured end estimated signals. In this scheme, the detecting performance depends on the estimation and modeling performance. The suggested NT3FLS is used because of the existence of a high level of measurement errors and uncertainties in this problem. The designed NT3FLS with uncertain footprint-of-uncertainty (FOU), fuzzy secondary memberships and adaptive non-singleton fuzzification results in a powerful tool for modeling signals immersed in noise and error. The level of non-singleton fuzzification and membership parameters are tuned by maximum correntropy (MC) unscented Kalman filter (KF), and the rule parameters are learned by correntropy KF (CKF) with fuzzy kernel size. The suggested learning algorithms can handle the non-Gaussian noises that are common in industrial applications. The various types of flowmeters are investigated, and the effect of common faults are examined. It is shown that the suggested approach can detect the various faults with good accuracy in comparison with conventional approaches.

show abstract

“…Due to the low self‐discharge rate of lithium‐ion batteries (LiBs), high energy density, and high working voltage, they become a primary choice of the onboard energy storage system in electric vehicles (EVs) 1,2 . Although, in consumer electronics, mobile devices, and EVs, numerous field failures of LiBs are documented.…”

Section: Introductionmentioning

confidence: 99%

Multivariate gated recurrent unit for battery remaining useful life prediction: A deep learning approach

Ardeshiri

2021

Int J Energy Res

View full text Add to dashboard Cite

Summary This paper proposes the gated recurrent unit (GRU)‐recurrent neural network (RNN), a deep learning approach to predict the remaining useful life (RUL) of lithium‐ion batteries (LIBs), accurately. The GRU‐RNN structure can self‐learn the network parameters utilizing adaptive gradient descent algorithms, leading to a reduced computational cost. Unlike the long short‐term memory (LSTM) model, GRU‐RNN allows time‐series dependencies to be tracked between degraded capacities without using any memory cell. This enables the method to predict non‐linear capacity degradations and build an explicitly capacity‐oriented RUL predictor. Additionally, feature selection based on the random forest technique was used to enhance the prediction precision. The analyses were conducted based on four separate cycling life testing datasets of a lithium‐ion battery. The experimental results indicate that the average percentage of root mean square error for the proposed method is about 2% which respectively is 1.34 times and 8.32 times superior to the LSTM and support vector machine methods. The outcome of this work can be used for managing the Li‐ion battery's improvement and optimization.

show abstract

A New Online Learned Interval Type-3 Fuzzy Control System for Solar Energy Management Systems

Cited by 126 publications

References 46 publications

Hotel Construction Management considering Sustainability Architecture and Environmental Issues

Hotel Construction Management considering Sustainability Architecture and Environmental Issues

Non-Singleton Type-3 Fuzzy Approach for Flowmeter Fault Detection: Experimental Study in a Gas Industry

Multivariate gated recurrent unit for battery remaining useful life prediction: A deep learning approach

Contact Info

Product

Resources

About