Multi-Objective Optimization of Machinability and Energy Consumption of Cast Iron Depending on Cooling Rate by Burak Öztürk, Fuat Kara

“…Energy efficiency has become a critical focus in sustainable production techniques and cost-effective machining processes. This variation directly influences machinability, with higher hardness generally improving surface quality. …”
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A Comparative Analysis of Hyper-Parameter Optimization Methods for Predicting Heart Failure Outcomes by Qisthi Alhazmi Hidayaturrohman, Eisuke Hanada

“…We evaluated three optimization approaches—Grid Search (GS), Random Search (RS), and Bayesian Search (BS)—across three machine learning algorithms—Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost). …”
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Developing an Equitable Machine Learning–Based Music Intervention for Older Adults At Risk for Alzheimer Disease: Protocol for Algorithm Development and Validation by Chelsea S Brown, Luna Dziewietin, Virginia Partridge, Jennifer Rae Myers

“…The recommendation accuracy of the ML algorithm will be assessed using multiple performance metrics, including root-mean-square error and normalized discounted cumulative gain as well as the mean acceptability score with a goal of 85% user acceptability. …”
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An adaptive k-means clustering algorithm based on grid and domain centroid weights for digital twins in the context of digital transformation by Wei Cai, Fei Yang, Bo Yao, Chuanxian Li, Guangyu Sun

“…The algorithm automatically determines the optimal number of clusters k and initial centroids. …”
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User Experience Optimization Researcb on Personalized Pusb Approacb of IPTV Service Based on Label of Contents by Yingbo Zhu, Jianwei Diao, Bo Kang, Shengqiang Liu

“…It is needed to introduce active personalized push approach of content in order to improve user experience, due to higher cost of remote controller than PC and mobile phone. …”
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Enhancing Quality Control of Packaging Product: A Six Sigma and Data Mining Approach by Resty Ayu Ramadhani, Rina Fitriana, Anik Nur Habyba, Yun-Chia Liang

“… Six Sigma is of paramount importance to organizations as it provides a structured and data-driven approach, fostering continuous improvement, minimizing defects, and optimizing processes to meet and exceed customer expectations. …”
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Lithium-Ion Battery State of Health Estimation Based on CNN-LSTM-Attention-FVIM Algorithm and Fusion of Multiple Health Features by Guoju Liu, Zhihui Deng, Yonghong Xu, Lianfeng Lai, Guoqing Gong, Liang Tong, Hongguang Zhang, Yiyang Li, Minghui Gong, Mengxiang Yan, Zheng Ye

“…The model adopts the collaborative architecture of a convolutional neural network and time series module, strengthens the cross-level feature interaction by introducing a multi-level attention mechanism, then uses the FVIM optimization algorithm to optimize the key parameters to realize the overall model architecture. …”
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Research on Multi-Objective Coordinated Planning of Distribution Networks Based on Improved Generative Adversarial Networks by Li Zhu

“…Next, a bi-level distribution network planning model considering carbon footprints is established: the upper level minimizes the annual comprehensive cost by optimizing the planning schemes of distributed generation (DG), energy storage systems (ESS), and capacitor banks (CB); the lower level minimizes operating costs, voltage deviations, and carbon emissions by formulating operation strategies under typical scenarios, considering on-load tap changers (OLTC), controllable loads, capacitor banks, energy storage, and distributed generation. …”
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Data-Driven Robust Optimization for Solving the Heterogeneous Vehicle Routing Problem with Customer Demand Uncertainty by Jingling Zhang, Mengfan Yu, Qinbing Feng, Longlong Leng, Yanwei Zhao

“…Through test experiments, it is proved that the robust optimization model can effectively reduce the number of customers affected by the uncertainty, greatly improve customer satisfaction, and effectively reduce total cost and demonstrate that the improved algorithm also exhibits good performance.…”
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Data Mining Techniques for Early Detection and Classification of Plant Diseases: An Optimization-Based Approach by Wagh Swapnil, Sharma Ruchi

“…Furthermore, low-level optimization techniques like genetic algorithms as well as particle swarm optimization are used to fine tune the specific model parameters and to reduce the computational overhead for improving the detection efficacy still more. …”
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Enhancing Supply Chain Agility and Sustainability through Machine Learning: Optimization Techniques for Logistics and Inventory Management by Vikram Pasupuleti, Bharadwaj Thuraka, Chandra Shikhi Kodete, Saiteja Malisetty

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Toward Robust GNSS Real-Time Orbit Determination for Microsatellites Using Factor Graph Optimization by Cong Hou, Xiaojun Jin, Xiaopeng Yang, Tong Xiao

“…However, the performance of EKF-RTOD is markedly degraded when the microsatellite deviates from a stable Earth-pointing attitude and employs a low-cost receiver. Factor graph optimization (FGO), which addresses nonlinear problems through multiple iterations and re-linearization, has demonstrated superior accuracy and robustness compared to EKF in challenging environments such as urban canyons. …”
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Optimization of trusted wireless sensing models based on deep reinforcement learning for ISAC systems by Hao Zhang, Yi Jing, Wenhui Xu, Ronghui Zhang

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Smart UAV-assisted rose growth monitoring with improved YOLOv10 and Mamba restoration techniques by Fan Zhao, Zhiyan Ren, Jiaqi Wang, Qingyang Wu, Dianhan Xi, Xinlei Shao, Yongying Liu, Yijia Chen, Katsunori Mizuno

“…We introduced MambaIR, a novel SRR algorithm based on selective state-space models, which significantly outperforms existing methods in enhancing low-resolution UAV imagery (PSNR: 28.34 dB, SSIM: 77.07 %). …”
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UV-Vis spectroscopy coupled with firefly algorithm-enhanced artificial neural networks for the determination of propranolol, rosuvastatin, and valsartan in ternary mixtures by Ahmed Serag, Maram H. Abduljabbar, Yusuf S. Althobaiti, Farooq M. Almutairi, Shaker T. Alsharif, Rami M. Alzhrani, Marwa F. Ahmed, Atiah H. Almalki

“…An experimental design of 25 samples was employed as a calibration set, and a central composite design of 20 samples was used as a validation set. The firefly algorithm (FA) was evaluated as a variable selection procedure to optimize the developed ANN models resulting in simpler models with improved predictive performance as evident by lower relative root mean square error of prediction (RRMSEP) values compared to the full spectrum ANN models. …”
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Multi-Agent Deep Reinforcement Learning for Scheduling of Energy Storage System in Microgrids by Sang-Woo Jung, Yoon-Young An, BeomKyu Suh, YongBeom Park, Jian Kim, Ki-Il Kim

“…To defeat the above issues, in this paper, we propose a new DRL-based scheduling algorithm using a multi-agent proximal policy optimization (MAPPO) framework that is combined with Pareto optimization. …”
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An adaptive differential evolution algorithm to solve the multi-compartment vehicle routing problem: A case of cold chain transportation problem by Supaporn Sankul, Naratip Supattananon, Raknoi Akararungruangkul, Narong Wichapa

“…The ADE algorithm aims to minimize the total cost, which includes both the expenses for traveling and using the vehicles. …”
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Deep Temporal Clustering of Pathological Gait Patterns in Post-Stroke Patients Using Joint Angle Trajectories: A Cross-Sectional Study by Gyeongmin Kim, Hyungtai Kim, Yun-Hee Kim, Seung-Jong Kim, Mun-Taek Choi

“…Rehabilitation of gait function in post-stroke hemiplegic patients is critical for improving mobility and quality of life, requiring a comprehensive understanding of individual gait patterns. …”
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Application of High Efficiency and High Precision Network Algorithm in Thermal Capacity Design of Modular Permanent Magnet Fault-Tolerant Motor by Yunlong Yi, Sheng Ma, Bo Zhang, Wei Feng

“…Aiming at the problems of low thermal analysis efficiency and high computational cost of traditional computational fluid dynamics (CFD) methods for modular fault-tolerant permanent magnet synchronous motors (MFT-PMSMs) under complex working conditions, this paper proposes a fast modeling and calculation method of motor temperature field based on a high-efficiency and high-precision network algorithm. …”
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Multi‐objective multi‐period optimal site and size of distributed generation along with network reconfiguration by Ghulam Abbas, Zhi Wu, Aamir Ali

“…To address the pointed‐out challenge of multiperiod optimal DG allocation and reconfiguration while simultaneously decreasing the cost of energy supplied, the cost of energy lost, and the voltage deviation, a novel Multi‐objective Bidirectional co‐evolutionary algorithm (BiCo) is implemented. …”
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