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Xiao-Meng Dai, Liang Zong, Yang Ding, Hao-Wen Zhang and Feng-Wei Shi
The use of modular steel construction (MSC) achieves a minimum of on-site work and the potential for removability and reuse. In order to realize the overall disassembly of module buildings and the rapid off-site reconstruction after disassembly, special ...
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Shuhe Zheng, Chongcheng Chen and Yuming Guo
Aiming at the problems found in grinding Jun-Cao, such as poor grinding effect and high grinding power of mill, this study proposes a blade Jun-Cao grinding hammer based on the traditional hammer mill. With dynamics model analysis, it had better performa...
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Gerasim V. Krivovichev and Valentina Yu. Sergeeva
The paper is devoted to the theoretical and numerical analysis of the two-step method, constructed as a modification of Polyak?s heavy ball method with the inclusion of an additional momentum parameter. For the quadratic case, the convergence conditions ...
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Anton Kolosnitsyn, Oleg Khamisov, Eugene Semenkin and Vladimir Nelyub
We consider the Golden Section and Parabola Methods for solving univariate optimization problems. For multivariate problems, we use these methods as line search procedures in combination with well-known zero-order methods such as the coordinate descent m...
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Nikolaos Bakas
Function approximation is a fundamental process in a variety of problems in computational mechanics, structural engineering, as well as other domains that require the precise approximation of a phenomenon with an analytic function. This work demonstrates...
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Kenneth Lange
The current paper proposes and tests algorithms for finding the diameter of a compact convex set and the farthest point in the set to another point. For these two nonconvex problems, I construct Frank?Wolfe and projected gradient ascent algorithms. Altho...
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Giorgio Lazzarinetti, Riccardo Dondi, Sara Manzoni and Italo Zoppis
Solving combinatorial problems on complex networks represents a primary issue which, on a large scale, requires the use of heuristics and approximate algorithms. Recently, neural methods have been proposed in this context to find feasible solutions for r...
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Abdullahi T. Sulaiman, Habeeb Bello-Salau, Adeiza J. Onumanyi, Muhammed B. Mu?azu, Emmanuel A. Adedokun, Ahmed T. Salawudeen and Abdulfatai D. Adekale
The particle swarm optimization (PSO) algorithm is widely used for optimization purposes across various domains, such as in precision agriculture, vehicular ad hoc networks, path planning, and for the assessment of mathematical test functions towards ben...
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Ken Jom Ho, Ender Özcan and Peer-Olaf Siebers
Solving multiple objective optimization problems can be computationally intensive even when experiments can be performed with the help of a simulation model. There are many methodologies that can achieve good tradeoffs between solution quality and resour...
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Jiaming Li, Ning Xie and Tingting Zhao
In recent years, with the rapid advancements in Natural Language Processing (NLP) technologies, large models have become widespread. Traditional reinforcement learning algorithms have also started experimenting with language models to optimize training. ...
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