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Andry Sedelnikov, Evgenii Kurkin, Jose Gabriel Quijada-Pioquinto, Oleg Lukyanov, Dmitrii Nazarov, Vladislava Chertykovtseva, Ekaterina Kurkina and Van Hung Hoang
This paper describes the development of a methodology for air propeller optimization using Bezier curves to describe blade geometry. The proposed approach allows for more flexibility in setting the propeller shape, for example, using a variable airfoil o...
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Weixuan Wang, Jingbo Peng and Yu Zhang
This paper presents a study on the modeling and control of an aero-engine within the full flight envelope using the Takagi?Sugeno (T-S) fuzzy theory. A highly accurate aero-engine small deviation state variable model (SVM) was developed using the adaptiv...
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Vladimir Stanovov, Lev Kazakovtsev and Eugene Semenkin
Differential evolution (DE) is a popular and efficient heuristic numerical optimization algorithm that has found many applications in various fields. One of the main disadvantages of DE is its sensitivity to parameter values. In this study, we investigat...
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Tong Zhang, Chunjiang Liu, Jiaqi Li, Minghui Pang and Mingang Wang
In view of traditional point-line feature visual inertial simultaneous localization and mapping (SLAM) system, which has weak performance in accuracy so that it cannot be processed in real time under the condition of weak indoor texture and light and sha...
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Laxman Bhukya, Narender Reddy Kedika and Surender Reddy Salkuti
In the recent past, the solar photovoltaic (PV) system has emerged as the most promising source of alternative energy. This solar PV system suffers from an unavoidable phenomenon due to the fluctuating environmental conditions. It has nonlinearity in I-V...
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Shakhnaz Akhmedova, Vladimir Stanovov and Yukihiro Kamiya
In this study, a new approach for novelty and anomaly detection, called HPFuzzNDA, is introduced. It is similar to the Possibilistic Fuzzy multi-class Novelty Detector (PFuzzND), which was originally developed for data streams. Both algorithms initially ...
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Aleksei Vakhnin and Evgenii Sopov
Modern real-valued optimization problems are complex and high-dimensional, and they are known as ?large-scale global optimization (LSGO)? problems. Classic evolutionary algorithms (EAs) perform poorly on this class of problems because of the curse of dim...
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Alexey Vakhnin and Evgenii Sopov
Many modern real-valued optimization tasks use ?black-box? (BB) models for evaluating objective functions and they are high-dimensional and constrained. Using common classifications, we can identify them as constrained large-scale global optimization (cL...
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Vladimir Stanovov, Shakhnaz Akhmedova and Eugene Semenkin
In this study, a new parameter control scheme is proposed for the differential evolution algorithm. The developed linear bias reduction scheme controls the Lehmer mean parameter value depending on the optimization stage, allowing the algorithm to improve...
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Nada Chakhim, Mohamed Louzar, Abdellah Lamnii and Mohammed Alaoui
Diffuse optical tomography (DOT) is an emerging modality that reconstructs the optical properties in a highly scattering medium from measured boundary data. One way to solve DOT and recover the quantities of interest is by an inverse problem approach, wh...
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