Search Results - evolution algorithm

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The primary objective in the production of parts is to optimize the manufacturing process. As the industry recognizes the roughness of the cut product as one of the key criteria, it becomes critical to select the correct laser settings with minimum trial, error and at the lowest possible cost while...

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A Ge-doped dual-core dispersion compensation photonic crystal fiber (DC-DCPCF) is proposed. The small diameters of two layers’ air holes make DC-DCPCF form a dual-core structure, which is conducive to broadband dispersion compensation. Low Ge-doped silica as the only background material r...

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Aiming at the multiobjective cloud resource scheduling problem, with the goal of optimizing the total completion time and total execution cost of the task, a fuzzy cloud resource scheduling model is established using the method of fuzzy mathematics.Utilizing the advantage of the covariance matrix t...

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Abstract The intensity and frequency of heat extremes is expected to increase with climate change. However, answering questions about their physical mechanisms and how they may evolve in the future is challenging because of their rareness. Here we investigate the evolution of the mechanisms leading...

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Microgrids have drawn attention due to their helpfulness in the development of renewable energy. It is necessary to make an optimal power dispatch scheme for each micro-source in a microgrid in order to make the best use of fluctuating and unpredictable renewable energy. However, the computational t...

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Effective corrective control is critical for maintaining secure power system operations. Conventional corrective control methods often struggle to balance computational speed with control optimality. In contrast, deep reinforcement learning facilitates faster control. However, significant uncertaint...

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As deep learning and reinforcement learning technologies advance, intelligent rural information management is transforming substantially. This article presents an innovative framework, the evolutionary bidirectional long short-term memory deep Q-network (EBLM-DQN), which integrates evolutionary algo...

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This paper presents a hybrid memetic algorithm for finding a conditional global extremum of functions. The algorithm combines such characteristics as modularity and adaptability which provides flexibility and controllability of the algorithm and reduces the influence of parameters. On the basis of t...

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The estimation of electrical parameters in three-phase induction motors is necessary for tasks such as performance analysis, control design, and predictive maintenance. Nonetheless, manufacturers typically provide limited electrical data, and existing methods often require invasive testing or additi...

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Abstract This paper presents a novel hybrid metaheuristic, the Hybrid Coati Optimization Algorithm with Differential Evolution (HCOADE), developed to address complex global optimization tasks and constrained engineering design problems. HCOADE integrates the exploration-driven behaviour of the Coati...

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With the growing prevalence of cybercrime, botnets have emerged as a significant threat, infiltrating an increasing number of legitimate computers annually. Challenges arising for organizations, educational institutions, and individuals as a result of botnet attacks include distributed denial of ser...

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This paper presents a digital twin-driven multi-objective optimization approach for enhancing the performance and productivity of a multi-product manufacturing system under complex operational challenges. More specifically, the concept of digital twin is applied to virtually replicate a physical sys...

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Lennox–Gastaut syndrome is an epileptic encephalopathy with onset in childhood. The classical triad of diagnostic criteria is well known: 1) presence of various types of refractory epileptic seizures (tonic, atypical absences, myoclonic, tonic/atonic drop attacks, generalized tonic-clonic, focal); 2...

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<b>Background/Objectives</b>: In recent work, we have demonstrated that principal component analysis (PCA) and Fourier Transformation Infrared (FTIR) spectra are powerful tools for analyzing the changes in microorganisms at the biomolecular level to detect changes in bacteria with resist...

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In electricity generation systems, problems related to economic and environmental dispatch represent potential for improvement in generating plants. The Environmental Economic Dispatch (EED) consists of minimizing the cost of generation and emission of pollutants such as CO2, SO2 and NOx. In additio...

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This study investigates a novel Quantum-inspired Evolutionary Algorithm (QiEA) for denoising phonocardiogram signals using a fractional-order digital differentiator FIR filter (FODD). The filter coefficients were optimised using the proposed QiEA with Adaptive Rotation Gate Operator (ARGO). The prop...

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This study examines the paradigm shift of traditional media in the face of the digital era, focusing on the adaptation processes and forms of media convergence through Norman Fairclough's Critical Discourse Analysis (CDA) approach. The research analyzes the discourse representations of digital...

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Artificial neural networks are widely used in applications from various scientific fields and in a multitude of practical applications. In recent years, a multitude of scientific publications have been presented on the effective training of their parameters, but in many cases overfitting problems ap...

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