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1441
Deep learning and fuzzy algorithm in improving the effectiveness of college English translation teaching
Published 2025-06-01“…This study combines deep learning and fuzzy algorithm to improve the effect of translation teaching. …”
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1442
Optimization of Gantry Cranes’ Operation Path for Transshipment Based on Improved TSP
Published 2020-01-01“…Based on the basic model of TSP, the paper constructed the optimization model for the operation path of RMG, and designed the Ant Colony Algorithm (ACA) to solve it, and then obtained the operation scheme of RMG having the highest efficiency. …”
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1443
Minimum cost of job assignment in polynomial time by adaptive unbiased filtering and branch-and-bound algorithm with the best predictor
Published 2025-06-01“…The minimum cost of job assignment (Min-JA) is one of the practical NP-hard problems to manage the optimization in science-and-engineering applications. …”
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1444
Environmental and Economic Dispatching of Fire-Wind Combined System Based on Improved MOPSO
Published 2025-01-01“…Then, an improved multi-objective particle swarm optimization algorithm, LRMOPSO, is proposed by combining multi-objective particle swarm optimization algorithm, Levy flight jamming strategy and reverse learning strategy. …”
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1445
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1446
A Heuristic Optical Flow Scheduling Algorithm for Low-Delay Vehicular Visible Light Communication
Published 2025-07-01“…In response to this problem, we propose a heuristic optical flow scheduling algorithm. First, the optical flow scheduling problem of VVLC is built as a multi-objective optimization model considering the makespan, delay, schedulable ratio, and bandwidth utilization with non-conflict constraints. …”
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1447
Improved Butterfly Optimizer-Configured Extreme Learning Machine for Fault Diagnosis
Published 2021-01-01“…The model is mainly based on an improved butterfly optimizer algorithm- (BOA-) optimized kernel extreme learning machine (KELM) model. …”
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1448
Marine Voyage Optimization and Weather Routing with Deep Reinforcement Learning
Published 2025-04-01“…These algorithms are computationally costly, so we split optimization into an offline phase (costly pre-training for a route) and an online phase where the algorithms are fine-tuned as updated weather data become available. …”
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1449
Enhancing Wind Power Forecasting Accuracy Based on OPESC-Optimized CNN-BiLSTM-SA Model
Published 2025-07-01“…This study proposes OPESC-CNN-BiLSTM-SA, a hybrid model combining an optimized escape algorithm (OPESC), convolutional neural network (CNN), bidirectional long short-term memory (BiLSTM) network, and self-attention (SA). …”
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1450
Fault Diagnosis Method for Transformer Winding Based on Differentiated M-Training Classification Optimized by White Shark Optimization Algorithm
Published 2025-04-01“…The principal contributions are threefold: First, building upon the fundamental principles of the M-training algorithm, we establish a classification model incorporating diversified classifiers. …”
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1451
Bayesian optimization with Optuna for enhanced soil nutrient prediction: a comparative study with genetic algorithm and particle swarm optimization
Published 2025-12-01“…The investigation confirms that Optuna-optimized models are at least 13 % more precise than GA and PSO models. …”
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1452
Optimizing capacitor bank placement in distribution networks using a multi-objective particle swarm optimization approach for energy efficiency and cost reduction
Published 2025-04-01“…The novelty of this work lies in the application of the MOPSO algorithm to optimize capacitor bank placement, considering multiple objectives such as energy loss reduction, voltage stability, and cost savings, which differentiates it from conventional approaches. …”
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1453
Automated Generation of Hybrid Metaheuristics Using Learning-to-Rank
Published 2025-05-01“…Metaheuristic algorithms, due to their superior global exploration capabilities and applicability, have emerged as critical tools for addressing complicated optimization tasks. …”
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1454
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1455
Forecasting the daily evaporation by coupling the ensemble deep learning models with meta-heuristic algorithms and data pre-processing in dryland
Published 2025-08-01“…To overcome the drawback that directly using measured evaporation time series to predict evaporation may lead to large error, the Variational mode decomposition (VMD) was used to extract multiscale traits of evaporation time series, and Whale optimization algorithm (WOA) was adopted to find the optimal parameters of VMD, and a novel hybrid deep learning model WOA-VMD-CNN-SSA-BiLSTM was proposed to estimate the evaporation in the Linze County, China. …”
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1456
Improved machine classification algorithm for electric rail circuits in train warning systems
Published 2019-12-01“…In this article, we present an improved classification algorithm, which combines the simplicity of implementation and accuracy. …”
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1457
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1458
Design of Instrumentation and Control Components of Power Distribution Systems
Published 2024-03-01“…In recent years, the development of high-voltage power systems has received a boost due to the need for infrastructural support for priority development areas. Universal models and algorithms are required to implement processes in power components and identify their optimal parameters. …”
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1459
Research on Collaborative Optimization Strategy of Railway Signal Nonlinear Control System Based on BBO Algorithm and Multi-objective Optimization
Published 2025-12-01“…The research constructs a mathematical model with multiple objective constraints, accurately identifies the adaptation shortcomings of the existing system in dynamic scenarios, and then employs a Biogeography-Based Optimization (BBO) algorithm for global optimization of control parameters. …”
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1460
Application of the metaheuristic algorithms to quantify the GSI based on the RMR classification
Published 2025-08-01“…With this objective, GSI quantification directly from RMR can be an attractive issue as it remains a complex task still due to the limited accuracy and generalizability of existing empirical models under varying geological conditions. This study addresses this challenge by analyzing data from fourteen different rock types and employing three metaheuristic optimization algorithms, namely Particle Swarm Optimization (PSO), Simulated Annealing (SA), and Grey Wolf Optimization (GWO), to develop predictive models for quantifying GSI based on the RMR. …”
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