Research on Ship Engine Fuel Consumption Prediction Algorithm Based on Adaptive Optimization Generative Network by Defu Zhang, Yuxuan Song, Jianfeng Gao, Zhenyu Shen, Liangkuan Li, Anren Yao

“…The MD-RAN algorithm is significantly better than the original model in terms of prediction accuracy, stability, and nonlinear expression ability. …”
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An Improved Substation Locating and Sizing Method Based on the Weighted Voronoi Diagram and the Transportation Model by Shiju Wang, Zhiying Lu, Shaoyun Ge, Chengshan Wang

“…Large amount of experiments show that the improved method can get more reasonable and more optimized planning result within shorter time than the original WVD and other algorithms.…”
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Optimization Strategy of Microgrid Hierarchical Scheduling Considering Electric Vehicles User Satisfaction Degree by Huiqun YU, Shen YIN, Hao ZHANG, Shanshan SHI, Daogang PENG, Guoshun CAI

“…Renewable energy is used to support the load of the microgrid in the source storage layer, and the excess part is absorbed by the dispatchable electric vehicle, which makes the comprehensive cost of the microgrid minimized. The improved ant lion algorithm is used to solve the model of the source storage layer. …”
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Improving Surgical Site Infection Prediction Using Machine Learning: Addressing Challenges of Highly Imbalanced Data by Salha Al-Ahmari, Farrukh Nadeem

“…<b>Conclusions</b>: This study underscores the potential of ML models as effective tools for assessing SSI risk, warranting further clinical exploration to improve patient outcomes. …”
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Predicting Student Performance through Machine Learning Methods: Naive Bayesian Classifier by Chenyang Li, Qianzhi Zhou, Luming Du, Sihan Zhang

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Optimization on construction machinery considering sequence-dependent setup times and personnel fatigue based on the improved gray wolf and whale algorithm. by Dawei Wang, Bo Gao, Lei Zhang

“…An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. …”
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An improved lightweight method based on EfficientNet for birdsong recognition by Haolun He, Hui Luo

“…Finally, we employ the Adam optimization algorithm to improve network convergence speed. …”
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Optimization of Time-Varying Temperature Profiles for Enhanced Beer Fermentation by Evolutive Algorithms by Pablo Ruarte, Nadia Pantano, Marianela Noriega, Cecilia Fernández, Emanuel Serrano, Gustavo Scaglia

“…This method integrates Fourier series and orthogonal polynomials for control action parameterization, in combination with evolutionary algorithms for parameter optimization. A key advantage of this methodology lies in its ability to handle a reduced parameter set efficiently, resulting in temperature profiles that are continuous and differentiable. …”
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Research on location algorithm of opencast mine vehicle based on improved adaptive H ∞ CKF and IAGA by Zhen Yang, Liwen Ji, Xin Li, Haoyuan Liu, Jianxiong Li, Dianxing Sun, Ruiheng Sun

“…Improved Adaptive Genetic Algorithm (IAGA) updates the optimal preservation strategy of traditional genetic algorithm and redefines the adaptive cross rate and variation rate. …”
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Improving Genetic Algorithm with Fine-Tuned Crossover and Scaled Architecture by Ajay Shrestha, Ausif Mahmood

“…Our implementation tests show that leveraging these new concepts of mtDNA and Continental Model results in relative improvement of the optimization quality of GA.…”
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IPO: An Improved Parrot Optimizer for Global Optimization and Multilayer Perceptron Classification Problems by Fang Li, Congteng Dai, Abdelazim G. Hussien, Rong Zheng

“…The Parrot Optimizer (PO) is a new optimization algorithm based on the behaviors of trained Pyrrhura Molinae parrots. …”
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Optimization method of obstacle avoidance path for dual-arm cooperative robot based on machine vision by Jing Li

“…An improved bat algorithm is employed to optimize the obstacle avoidance path of the dual-arm cooperative robot, ultimately yielding the optimal path. …”
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Metaheuristics and Large Language Models Join Forces: Toward an Integrated Optimization Approach by Camilo Chacon Sartori, Christian Blum, Filippo Bistaffa, Guillem Rodriguez Corominas

“…Since the rise of Large Language Models (LLMs) a couple of years ago, researchers in metaheuristics (MHs) have wondered how to use their power in a beneficial way within their algorithms. …”
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Modeling of 3 SAT discrete Hopfield neural network optimization using genetic algorithm optimized K-modes clustering by Xiaojun Xie, Saratha Sathasivam, Hong Ma

“…Subsequently, the paper presented a DHNN-3SAT model optimized by genetic algorithms combined with K-modes clustering. …”
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Improving Modularity Regularization Techniques for Estimating Structures in Complex Network by Samaa F. Ibraheem, Basad Al-Sarray

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Robust DWT-HMM image watermarking algorithm optimized with content-adaptive approach by WANG Chun-tao1, NI Jiang-qun1, HUANG Ji-wu1, ZHANG Rong-yue1, LUO Xi-zhang1

“…A robust watermarking algorithm based on content-adaptive approach was proposed to optimize the tradeoff between robustness and imperceptibility,which was characterized as follows: the entropy masking proposed by Watson etc.was constructed in wavelet domain,which was then used to constitute the integrated HVS model;three different measures,namely,energy,entropy and integrated HVS,for content-adaptive selection were constructed and investigated;repeat-accumulate（RA） code with erasure and error correction was used to tackle the synchronization issue of the exact positions for watermark embedding;and a posteriori DWT-HMM detector was utilized for watermark detection.Simula-tion results show that the proposed content-adaptive watermarking algorithm,under the same imperceptibility,has con-siderable improvement in robustness performance over the traditional one with stochastic approach.…”
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Multi-Condition Magnetic Core Loss Prediction and Magnetic Component Performance Optimization Based on Improved Deep Forest by Haotian Shi, Zipeng Jin

“…To achieve high efficiency and high power density designs, it is essential to study core loss characteristics and optimize operating parameters. This paper proposes a core loss prediction model based on an improved deep forest algorithm and information entropy-enhanced genetic algorithm. …”
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Prediction of Spatiotemporal Distribution of Electric Vehicle Charging Load Based on Multi-Source Information by WANG Qiang, BI Yuhao, GAO Chao, SONG Duoyang

“…[Objective] Factors such as road networks， temperature， and electric vehicle （EV） type affect the spatial and temporal distribution of EV charging loads. To improve prediction accuracy， a spatiotemporal EV charging load prediction model is developed by integrating multiparty information. …”
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Improving Forecasts of the EGARCH Model Using Artificial Neural Network and Fuzzy Inference System by Geleta T. Mohammed, Jane A. Aduda, Ananda O. Kube

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Improvement of Assemble-to-Order Model Processes With Process Mining: Dynamic Analysis and Hybrid Approaches by Ufuk Celik, Yuksel Yurtay

“…Insights derived from the analysis informed actionable recommendations to optimize production workflows. This study demonstrates the potential of hybrid process mining techniques for understanding and improving ATO systems, offering a dynamic and scalable framework for addressing inefficiencies in similar production models.…”
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