A Novel Technique for Solving Fully Fuzzy Nonlinear Systems Based on Neural Networks

Jafari, Raheleh; Razvarz, Sina; Gegov, Alexander

doi:10.1142/s2196888820500050

Cited by 15 publications

(9 citation statements)

References 34 publications

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“…e simulation consistency is shown in Figure 7. e complexity of a problem depends on the selected model and the datasets [29][30][31][32][33][34][35][36][37][38]. From the simulation analysis results in Figure 7, under the recursive fuzzy neural network algorithm, it can be seen that with the increase of simulation times, the optimization stability of the two groups of data is higher and higher in the process of optimizing different types of logistics distribution path.…”

Section: Optimization Process Of Recursive Fuzzy Neural Networkmentioning

confidence: 99%

[Retracted] Logistics Distribution Route Optimization Model Based on Recursive Fuzzy Neural Network Algorithm

Liu

2021

Computational Intelligence and Neuroscience

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In recent years, more and more attention has been paid to the utilization of data and information in the logistics distribution path optimization system of e-commerce, but it is difficult to have scientific guarantee in the process of determining the optimal distribution path scheme of e-commerce. How to realize the optimization and adaptive setting of distribution path by using intelligent algorithm has become a hot spot. To battle these issues, this paper studies the logistics distribution path optimization model based on recursive fuzzy neural network algorithm. This paper analyses the research status of logistics distribution path determination scheme and applies the recursive fuzzy neural network algorithm in the selection of e-commerce logistics distribution path scheme. The experimental results show that the recursive fuzzy neural network algorithm can realize the optimization of e-commerce logistics distribution path, and the best distribution route can be made according to the characteristic difference of logistics distribution route, and its distribution accuracy can reach more than 97%.

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Section: Optimization Process Of Recursive Fuzzy Neural Networkmentioning

confidence: 99%

[Retracted] Logistics Distribution Route Optimization Model Based on Recursive Fuzzy Neural Network Algorithm

Liu

2021

Computational Intelligence and Neuroscience

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“…Artificial intelligence has become the most effective approach which attracts many investigators to deeply research [20][21][22][23][24][25]. It has been successfully used for leak detection.…”

Section: Takedownmentioning

confidence: 99%

Pipeline Leak Detection and Location based on Fuzzy Controller

Razvarz

Jafari

Vargas-Jarillo

et al. 2020

2020 IEEE Symposium Series on Computational Intelligence (SSCI)

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Pipeline systems have been taken as one of the most important tools for transmission around the world. It will be important for the industrial society that pipeline systems function appropriately by taking into consideration the growing requirement for effective interconnecting fluid networks. Typically, there are various kinds of control systems or algorithms for pipeline leak detection. In this paper, a pipeline leak detection and location method is proposed based on fuzzy control. It is concluded that the response of the fuzzy controller is fast and has no oscillations and this is appropriate for numerous high-precision usages like robotics as well as weapon systems. The numerical results demonstrate that the suggested technique is simple, efficient, and has a high level of localization precision.

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“…In [11], a new method based on auxiliary mass spatial probing by the stationary wavelet transform is suggested to detect damage in beams. Artificial intelligence with fuzzy logic has become the most effective approach, which attracts many investigators to deeply research it [12][13][14][15][16]. It has been successfully used for leak detection.…”

Section: Introductionmentioning

confidence: 99%

“…It has been successfully used for leak detection. In [17], a low-cost wireless sensor system it [12][13][14][15][16]. It has been successfully used for leak detection.…”

Section: Introductionmentioning

confidence: 99%

Pipeline Leak Detection and Estimation Using Fuzzy PID Observer

et al. 2022

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A pipe is a ubiquitous product in the industries that is used to convey liquids, gases, or solids suspended in a liquid, e.g., a slurry, from one location to another. Both internal and external cracking can result in structural failure of the industrial piping system and possibly decrease the service life of the equipment. The chaos and complexity associated with the uncertain behaviour inherent in pipeline systems lead to difficulty in detection and localisation of leaks in real time. The timely detection of leakage is important in order to reduce the loss rate and serious environmental consequences. The objective of this paper is to propose a new leak detection method based on an autoregressive with exogenous input (ARX) Laguerre fuzzy proportional-integral-derivative (PID) observation system. The objective of this paper is to propose a new leak detection method based on an autoregressive with exogenous input (ARX) Laguerre fuzzy proportional-integral-derivative (PID) observation system. In this work, the ARX–Laguerre model has been used to generate better performance in the presence of uncertainty. According to the results, the proposed technique can detect leaks accurately and effectively.

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A Novel Technique for Solving Fully Fuzzy Nonlinear Systems Based on Neural Networks

Cited by 15 publications

References 34 publications

[Retracted] Logistics Distribution Route Optimization Model Based on Recursive Fuzzy Neural Network Algorithm

[Retracted] Logistics Distribution Route Optimization Model Based on Recursive Fuzzy Neural Network Algorithm

Pipeline Leak Detection and Location based on Fuzzy Controller

Pipeline Leak Detection and Estimation Using Fuzzy PID Observer

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