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Apllication of optimization algorithms to improve the design of turnouts
Published 2016-04-01“…One of the most important tasks for improving the infrastructure facility of railways is its optimization. …”
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Resilience-Improving Based Optimization of Post-Disaster Emergency Maintenance Strategy for Transmission Networks
Published 2022-03-01Subjects: Get full text
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An improved termite life cycle optimizer algorithm for global function optimization
Published 2025-02-01“…The termite life cycle optimizer algorithm (TLCO) is a new bionic meta-heuristic algorithm that emulates the natural behavior of termites in their natural habitat. …”
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Research on formant estimation algorithm for high order optimal LPC root value screening
Published 2022-06-01“…Objectives: The existing linear prediction (LP) formant estimation algorithms are difficult to locate formant precisely because of the pseudo root interference and interaction between poles.Because of the low order fitting formant of LP prediction,the accuracy of formant extraction is fundamentally limited.It is difficult to remove false roots and spectrum aliasing caused by pole interaction in the formant extraction of high-order LP.In order to solve the problem of large error of LP formant detection,a formant estimation algorithm based on high-order LP coefficient root value screening was proposed. …”
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COMQ: A Backpropagation-Free Algorithm for Post-Training Quantization
Published 2025-01-01Get full text
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Text classification using SVD, BERT, and GRU optimized by improved Seagull optimization (ISO) algorithm
Published 2025-06-01“…In the present research, a Gated Recurrent Unit (GRU) optimized by the Improved Seagull Optimization (ISO) algorithm was utilized to address these issues, resulting in notable improvements in classification performance. …”
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Stability optimization of dynamic migration algorithm for Post-Copy of virtual machine based on KVM
Published 2021-07-01“…The dynamic migration technology of virtual machine provides a strong support for the resource scheduling of virtualization system.As one of the two core algorithms of virtual machine dynamic migration, Post-Copy algorithm has been a hot issue for scholars at home and abroad for its advantages of stable migration time and short migration downtime.The fault tolerance mechanism of virtual machine, the connection between the transfer mode of memory page and the page missing error during the migration process, and the source code of QEMU-KVM platform were studied.A fault tolerant method based on transaction synchronization was proposed to improve the stability of the Post-Copy migration algorithm.The experimental results show that the proposed algorithm can ensure the fast repair of deep end virtual machine failure, target virtual machine failure and network fault during the migration process, and solve the stability problem at a small cost.The method proposed effectively improves the stability of the Post-Copy migration algorithm, and provides reference for the future optimization research direction.…”
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Multiple R&D Projects Scheduling Optimization with Improved Particle Swarm Algorithm
Published 2014-01-01Get full text
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Development of an Algorithm to Determine the Most Efficient Trajectories in Directional Wells
Published 2025-07-01“…We present the development of an algorithm designed to determine the most efficient trajectories for directional wells, a key method used in oil and gas extraction. …”
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Noise Reduction of Steam Trap Based on SSA-VMD Improved Wavelet Threshold Function
Published 2025-03-01Subjects: Get full text
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Environmental Impact Minimization Model for Storage Yard of In-Situ Produced PC Components: Comparison of Dung Beetle Algorithm and Improved Dung Beetle Algorithm
Published 2024-11-01“…As a result of applying the developed model, the optimization of the improved dung beetle optimization algorithm was verified to be efficient by improving the neighboring correlation by 22.79% and reducing carbon dioxide emissions by 18.33% compared to the dung beetle optimization algorithm. …”
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An improved Multi-Objective Whale Optimization Algorithm for hydrodynamic and acoustic performance optimization of Myring-shaped underwater vehicle
Published 2025-12-01“…These improvements enhance the algorithm’s capability in solving Multi-Objective Optimization (MOP) problems. …”
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Designing a new optimal controller for a PEMFC by an improved design of the Coot Optimizer
Published 2025-05-01“…Comparative analyses against three other control techniques confirm a wide system enhancement, evidenced by a substantial reduction in both current and overshoot ripples. Algorithm verification using benchmark functions shows the ICOA achieves lower mean values and standard deviations, with p-values indicating statistically significant improvements (p < 0.05) in Root Mean Square Error (RMSE) compared to COA, MVO, EPO, and LOA algorithms, validating its enhanced optimization capabilities for PEMFC control.…”
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Improving Airport Flight Prediction System Based on Optimized Regression Vector Machine Algorithm
Published 2024-09-01“…In this research, the optimized support vector regression (SVR) algorithm has been used to improve the accuracy of air delay prediction. …”
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Enhanced Dung Beetle Optimizer-Optimized KELM for Pile Bearing Capacity Prediction
Published 2025-07-01“…In response to the need for rapid and precise predictions of pile bearing capacity, this study introduces a kernel extreme learning machine (KELM) prediction model optimized through a multi-strategy improved beetle optimization algorithm (IDBO), referred to as the IDBO-KELM model. …”
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Research on Robot Path Planning Based on Improved RRT-Connect Algorithm
Published 2025-02-01“…Firstly, an improved RRT algorithm is employed to search and add a middle root node, facilitating the simultaneous expansion of four random trees to expedite algorithm convergence. …”
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Application of bioinspired global optimization algorithms to the improvement of the prediction accuracy of compact extreme learning machines
Published 2022-04-01“…By adjusting input weights with bioinspired optimization algorithms, it was shown that the prediction accuracy of ELMs in regression problems can be improved to reduce the number of hidden-layer neurons to reach a high prediction accuracy on learning and test datasets. …”
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