Wenzhe Guo¹, Leian Zhang^1,*, Chao Lv², Weisheng Liu³, Jiabin Tian²

Energy Engineering, Vol.120, No.10, pp. 2307-2323, 2023, DOI:10.32604/ee.2023.030029

Abstract Aiming at the drift problem that the tracking control of the actual load relative to the target load during the electromagnetic excitation biaxial fatigue test of wind turbine blades is easy to drift, a biaxial fatigue testing machine for electromagnetic excitation is designed, and the following strategy of the actual load and the target load is studied. A Fast Transversal Recursive Least Squares algorithm based on fuzzy logic (Fuzzy FTRLS) is proposed to develop a fatigue loading following dynamic strategy, which adjusts the forgetting factor in the algorithm through fuzzy logic to overcome the contradiction between convergence accuracy and convergence… More >

Yongqiu Liu¹, Shaohui Zhong^2,*, Nasreen Kausar³, Chunwei Zhang^4,*, Ardashir Mohammadzadeh⁴, Dragan Pamucar^5,6

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 793-812, 2024, DOI:10.32604/cmes.2023.028175

Abstract In this paper, a stable and adaptive sliding mode control (SMC) method for induction motors is introduced. Determining the parameters of this system has been one of the existing challenges. To solve this challenge, a new self-tuning type-2 fuzzy neural network calculates and updates the control system parameters with a fast mechanism. According to the dynamic changes of the system, in addition to the parameters of the SMC, the parameters of the type-2 fuzzy neural network are also updated online. The conditions for guaranteeing the convergence and stability of the control system are provided. In the simulation part, in order… More >

Shahzad Noor Abbasi¹, Shahzaib Ashraf^1,*, M. Shazib Hameed¹, Sayed M. Eldin^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2795-2844, 2023, DOI:10.32604/cmes.2023.028963

Abstract The primary goal of this research is to determine the optimal agricultural field selection that would most effectively support manufacturing producers in manufacturing production while accounting for unpredictability and reliability in their decision-making. The PFS is known to address the levels of participation and non-participation. To begin, we introduce the novel concept of a PFZN, which is a hybrid structure of Pythagorean fuzzy sets and the ZN. The PFZN is graded in terms of membership and non-membership, as well as reliability, which provides a strong advice in real-world decision support concerns. The PFZN is a useful tool for dealing with… More >

Zekai Li¹, Wenfeng Wang^2,3,4,5,6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2881-2899, 2023, DOI:10.32604/cmes.2023.028670

Abstract We advanced an emerging federated learning technology in city intelligentization for tackling a real challenge— to learn damaged objects in aerial videos. A meta-learning system was integrated with the fuzzy broad learning system to further develop the theory of federated learning. Both the mixed picture set of aerial video segmentation and the 3D-reconstructed mixed-reality data were employed in the performance of the broad federated meta-learning system. The study results indicated that the object classification accuracy is up to 90% and the average time cost in damage detection is only 0.277 s. Consequently, the broad federated meta-learning system is efficient and… More >

Tomader Almeshal^1,*, Jawad Berri¹, Tarifa Almulhim², Areej Alhogail¹, Emam Ahmed³

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1665-1690, 2023, DOI:10.32604/csse.2023.038871

Abstract Blockchain is one of the innovative and disruptive technologies that has a wide range of applications in multiple industries beyond cryptocurrency. The widespread adoption of blockchain technology in various industries has shown its potential to solve challenging business problems, as well as the possibility to create new business models which can increase a firm’s competitiveness. Due to the novelty of the technology, whereby many companies are still exploring potential use cases, and considering the complexity of blockchain technology, which may require huge changes to a company’s existing systems and processes, it is important for companies to carefully evaluate suitable use… More >

Zaihe Cheng¹, Yuwen Tao², Xiaoqing Gu³, Yizhang Jiang², Pengjiang Qian^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1613-1633, 2023, DOI:10.32604/cmes.2023.027708

Abstract Through semi-supervised learning and knowledge inheritance, a novel Takagi-Sugeno-Kang (TSK) fuzzy system framework is proposed for epilepsy data classification in this study. The new method is based on the maximum mean discrepancy (MMD) method and TSK fuzzy system, as a basic model for the classification of epilepsy data. First, for medical data, the interpretability of TSK fuzzy systems can ensure that the prediction results are traceable and safe. Second, in view of the deviation in the data distribution between the real source domain and the target domain, MMD is used to measure the distance between dierent data distributions. The objective… More >

Maha Noorwali¹, Mohammed Shehu Shagari^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1937-1956, 2023, DOI:10.32604/cmes.2023.028239

Abstract The real world is filled with uncertainty, vagueness, and imprecision. The concepts we meet in everyday life are vague rather than precise. In real-world situations, if a model requires that conclusions drawn from it have some bearings on reality, then two major problems immediately arise, viz. real situations are not usually crisp and deterministic; complete descriptions of real systems often require more comprehensive data than human beings could recognize simultaneously, process and understand. Conventional mathematical tools which require all inferences to be exact, are not always efficient to handle imprecisions in a wide variety of practical situations. Following the latter… More >

Mohammed M. Ali Al-Shamiri^1,2, Ghous Ali^3,*, Muhammad Zain Ul Abidin³, Arooj Adeel³

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1891-1936, 2023, DOI:10.32604/cmes.2023.027844

Abstract Spherical fuzzy soft expert set (SFSES) theory blends the perks of spherical fuzzy sets and group decision-making into a unified approach. It allows solutions to highly complicated uncertainties and ambiguities under the unbiased supervision and group decision-making of multiple experts. However, SFSES theory has some deficiencies such as the inability to interpret and portray the bipolarity of decision-parameters. This work highlights and overcomes these limitations by introducing the novel spherical fuzzy bipolar soft expert sets (SFBSESs) as a powerful hybridization of spherical fuzzy set theory with bipolar soft expert sets (BSESs). Followed by the development of certain set-theoretic operations and… More > Graphic Abstract

Yu-Ming Chu¹, Saima Rashid^2,*, Shazia Karim³, Anam Sultan²

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1573-1611, 2023, DOI:10.32604/cmes.2023.027724

Abstract The fractional-order Boussinesq equations (FBSQe) are investigated in this work to see if they can effectively improve the situation where the shallow water equation cannot directly handle the dispersion wave. The fuzzy forms of analytical FBSQe solutions are first derived using the Adomian decomposition method. It also occurs on the sea floor as opposed to at the functionality. A set of dynamical partial differential equations (PDEs) in this article exemplify an unconfined aquifer flow implication. This methodology can accurately simulate climatological intrinsic waves, so the ripples are spread across a large demographic zone. The Aboodh transform merged with the mechanism… More >

Wafa F. Alfwzan¹, Dumitru Baleanu^2,3,4, Fazal Dayan^5,*, Sami Ullah⁵, Nauman Ahmed^4,6, Muhammad Rafiq^7,8, Ali Raza^4,9

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1909-1924, 2023, DOI:10.32604/iasc.2023.039249

Abstract A susceptible, exposed, infectious, quarantined and recovered (SEIQR) model with fuzzy parameters is studied in this work. Fuzziness in the model arises due to the different degrees of susceptibility, exposure, infectivity, quarantine and recovery among the computers under consideration due to the different sizes, models, spare parts, the surrounding environments of these PCs and many other factors like the resistance capacity of the individual PC against the virus, etc. Each individual PC has a different degree of infectivity and resistance against infection. In this scenario, the fuzzy model has richer dynamics than its classical counterpart in epidemiology. The reproduction number… More >