In recent literature, various blind carrier frequency offset (CFO) estimation algorithms have been developed for Orthogonal Frequency-Division Multiple Access (OFDMA) systems. Nonetheless, the majority of the develope...
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The design and comparison of a frequency-reconfigurable microstrip patch antenna specifically suited for 5G wireless communication systems using the K-Ka band are the main topics of this research. To enable frequency ...
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In civil engineering, resource allocation refers to how best to divide resources including labor, supplies, and machinery among different jobs in building projects. This distribution is critical to meeting project dea...
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ISBN:
(纸本)9798331539948
In civil engineering, resource allocation refers to how best to divide resources including labor, supplies, and machinery among different jobs in building projects. This distribution is critical to meeting project deadlines, cutting expenses, and improving project efficiency. Because it is combinatorial in nature and has many constraints, resource allocation in civil engineering is categorized as NP-hard. According to the theory of NP-hardness, as a problem gets complex, it becomes computationally impossible to find an exact optimal solution in a reasonable amount of time. The complexity and uncertainty included in civil engineering projects, make traditional methods such as deterministic algorithms and linear programming unsuitable for tackling resource allocation challenges. By utilizing iterative optimization strategies motivated by mathematical models or natural processes, meta-heuristic algorithms offer a strong substitute. The capacity of meta-heuristic techniques to navigate large solution spaces and adjust to changing project restrictions and goals makes them especially well-suited for resource allocation in the civil engineering field. GA and DE are able to effectively explore and exploit solutions that standard algorithms could take longer to find in realistic timeframes by modeling biological evolution or natural selection *** this work, this paper access and contrast Differential Evolution (DE) and Genetic Algorithm(GA) for their respective roles in resource allocation optimization in civil engineering applications. This work show through rigorous experimentation and research that Differential Evolution performs better than Genetic Algorithm in terms of convergence speed and solution quality. The study offers significant contributions to the field of civil engineering resource allocation by providing useful insights into the application of meta-heuristic methodologies. This research is expected to have a positive impact on stakeholders, enginee
Epilepsy is a disease of the brain that causes unprovoked or reflex seizures that affects millions of individuals worldwide. Traditionally, identifying epileptic states involves assessing neuroimaging scans or brain e...
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The human brain has a simple time analyzing and processing images. The brain is able to rapidly deconstruct and distinguish an image's various components when the eye perceives it. With the Convolutional Neural Ne...
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The space modular self-reconfigurable satellite is an innovative satellite that has a reconfigurable structure and adjustable functions, its free-floating flying state makes its joint trajectory coupled with the satel...
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Machine vision systems can effectively improve production efficiency and accuracy. However, existing machine vision technologies are difficult to meet standards. Therefore, this article used traditional image algorith...
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The present paper deals with an overview of particle swarm algorithms and hybrid genetic-particle swarm algorithms, and a comparison between the related convergence speed and correlation error. The work includes also ...
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This paper presents a comprehensive comparative study of the Local Binary Patterns Histogram (LBPH), Convolutional Neural Network (CNN), and Principal Component Analysis (PCA) algorithms in image analysis and recognit...
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This paper presents a hierarchical framework that integrates path planning and trajectory optimization to achieve the reconfiguration of a platform composed of multiple unmanned surface vehicles (USV). Firstly, the eq...
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