Machine Learning Performance Analysis for Bagging System Improvement: Key Factors, Model Optimization, and Loss Reduction in the Fertilizer Industry by Ari Primantara, Udisubakti Ciptomulyono, Berlian Al Kindhi

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Designing Predictive Analytics Frameworks for Supply Chain Quality Management: A Machine Learning Approach to Defect Rate Optimization by Zainab Nadhim Jawad, Balázs Villányi

“…The framework employs advanced ML algorithms, including extreme gradient boosting (XGBoost), support vector machines (SVMs), and random forests (RFs), to accurately predict defect rates and derive actionable insights for supply chain optimization. …”
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Exploring the best fit: A comparative analysis of AFINN, Textblob, VADER, and Pattern on Arabic reviews for optimal dictionary extraction by Shakeel Ahmad, Sheikh Muhammad Saqib, Asif Hassan Syed, Nashwan Alromema, Ali Kararay

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Enhanced supervised classification of seasonal pastures on the Qinghai-Tibet Plateau (1990–2020) using Landsat optimal time window by Panfei Fang, Jia Wang, Haifeng Xu, Ruonan Li, Long Yu, Shaodong Huang, Yuying Liang, Pengfei Zheng

“…The framework leverages Landsat imagery within the optimal time window (Days of Year, DOYs 190–280), incorporates algorithms for automated sample generation and refinement, and employs the Random Forest (RF) classifier to enable fully automated seasonal pasture mapping. …”
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Optimization of guidelines for Risk Of Recurrence/Prosigna testing using a machine learning model: a Swedish multicenter study by Una Kjällquist, Nikos Tsiknakis, Balazs Acs, Sara Margolin, Luisa Edman Kessler, Scarlett Levy, Maria Ekholm, Christine Lundgren, Erik Olsson, Henrik Lindman, Antonios Valachis, Johan Hartman, Theodoros Foukakis, Alexios Matikas

“…Purpose: Gene expression profiles are used for decision making in the adjuvant setting in hormone receptor-positive, HER2-negative (HR+/HER2-) breast cancer. While algorithms to optimize testing exist for RS/Oncotype Dx, no such efforts have focused on ROR/Prosigna. …”
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MALDI-TOF mass spectrometry combined with machine learning algorithms to identify protein profiles related to malaria infection in human sera from Côte d’Ivoire by Fateneba Kone, Lucie Conrad, Jean T. Coulibaly, Kigbafori D. Silué, Sören L. Becker, Brama Kone, Issa Sy

“…When four supervised ML algorithms were tested by tenfold cross-validation, P. falciparum-positive sera were discriminated against P. falciparum-negative sera with a global accuracy ranging from 73.28% to 81.30%, while sensitivity ranged from 70.23% to 83.97%. …”
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Two-Stage Collaborative Power Optimization for Off-Grid Wind–Solar Hydrogen Production Systems Considering Reserved Energy of Storage by Yiwen Geng, Qi Liu, Hao Zheng, Shitong Yan

“…To address this, this paper proposes a two-stage power optimization method integrating rule-based allocation with algorithmic optimization for wind–solar hydrogen production systems, considering reserved energy storage. …”
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Energy-Efficient and Fault-Tolerant Control of a Six-Axis Robot Based on AI Models by Patryk Nowak, Zoran Pandilov

“…Obstacles are present in the robot’s workspace. The goal of the algorithm is to control the robot in such a way that energy consumption is minimized while also avoiding obstacles and ensuring fault tolerance in the event of axis failures. …”
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Multi-Project Scheduling with Uncertainty and Resource Flexibility: A Narrative Review and Exploration of Future Landscapes by Marzieh Aghileh, Anabela Tereso, Filipe Alvelos, Maria Odete Monteiro Lopes

“…It categorizes solution approaches, from exact algorithms to heuristic and metaheuristic methods, while reviewing the primary instance sets and benchmarks used in the field. …”
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Improved grey wolf optimization for parameter extraction of polycrystalline and mono crystalline solar PV panels using double diode model by Madhusudana Rao Ranga, Venkateswara Rao Bathina, Srikumar Kotni

“…In this paper an enhanced version of the Grey Wolf Optimizer (GWO) algorithm called Improved Grey Wolf Optimizer (IGWO) has been proposed for extraction of parameters. …”
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Biomimetic Computing for Efficient Spoken Language Identification by Gaurav Kumar, Saurabh Bhardwaj

“…We have evaluated the accuracy of our proposed technique against state-of-the-art biomimetic computing models such as GA, PSO, GWO, DE, and ACO. While ACO achieved up to 89.45% accuracy, our Bayesian Optimization with LSTM outperformed all others, reaching a peak accuracy of 95.55%, demonstrating its effectiveness in enhancing spoken language identification. …”
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Stiffness Optimization for Hybrid Electric Vehicle Powertrain Mounting System in the Context of NSGA II for Vibration Decoupling and Dynamic Reaction Minimization by Zhanpeng Fang, Qihang Li, Lei Yao, Xiaojuan Hu

“…A 6-DOF dynamic model was established to analyze the decoupling rate and frequency distribution in its inherent characteristics, calculate the dynamic reaction of the suspension system, set the decoupling rate and the dynamic reaction of the suspension as optimization objectives, and use the NSGA II (Non-dominated Sorting Genetic Algorithm II) optimization algorithm to optimize the stiffness of the suspension. …”
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A multi-attribute group decision-making algorithm based on soft intervals that considers the priority rankings of group members on attributes of objects, along with some applicatio... by Gözde Yaylalı Umul

“…In this study, soft intervals were generated from the orderings on a soft set which were based on the users rankings of object attributes. The first algorithm enabled us to obtain the choice object based on the ranking of decision makers with equal influence on the decision, while the second algorithm achieved this for rankings of those with different influences. …”
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Verifiable secure image retrieval for cloud-assisted IoT environments by GUO Jiaqi, MA Zhi, WANG Wensheng, TIAN Cong, DUAN Zhenhua

“…The proposed scheme improves image retrieval accuracy and security while optimizing computational and storage resources, making it suitable for cloud-assisted IoT environments.…”
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Cooperative Sleep and Energy-Sharing Strategy for a Heterogeneous 5G Base Station Microgrid System Integrated with Deep Learning and an Improved MOEA/D Algorithm by Ming Yan, Tuanfa Qin, Wenhao Guo, Yongle Hu

“…However, accurately predicting base station traffic demand and optimizing energy consumption while maximizing green energy usage—especially concerning quality of service (QoS) for users—remains a challenge. …”
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Generic Method for Social–Environmental System Boundary Delineation—An Amalgamation of Spatial Data Integration, Optimization, and User Control for Resource Management by Mohammad Shahriyar Parvez, Xin Feng

“…The framework also leverages the SKATER algorithm for precise regionalization, ensuring spatial continuity and compactness while allowing user control over region selection and data dimensions. …”
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Synergizing neural networks with multi-objective thermal exchange optimization and PROMETHEE decision-making to improve PCM-based photovoltaic thermal systems by Yongxin Li, Ali Basem, As'ad Alizadeh, Pradeep Kumar Singh, Saurav Dixit, Hanaa Kadhim Abdulaali, Rifaqat Ali, Pancham Cajla, Husam Rajab, Kaouther Ghachem

“…This study addresses the integration of machine learning (ML) and artificial intelligence (AI) for optimizing photovoltaic-thermal (PVT) systems. While ML modeling has become prevalent in this field, a significant gap remains in combining ML with AI-based optimization and decision-making methods to enhance PVT performance. …”
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An Optimization Framework for Waste Treatment Center Site Selection Considering Nighttime Light Remote Sensing Data and Waste Production Fluctuations by Junbao Xia, Yanping Liu, Haozhong Yang, Guodong Zhu

“…Using Beijing as a case study, the gradient boosting regression algorithm yielded a prediction accuracy of 92%. Furthermore, in light of the substantial costs associated with waste recovery route planning and site selection for treatment facilities, this research further devised a location and distribution framework for waste treatment centers based on high-precision predictions of waste production while employing multi-objective evolutionary algorithms (MOEAs) alongside the non-dominated sorting genetic algorithm II (NSGA-II) for optimization. …”
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Reliability Analysis of High-Pressure Tunnel System Under Multiple Failure Modes Based on Improved Sparrow Search Algorithm–Kriging–Monte Carlo Simulation Method by Yingdong Wang, Chen Xing, Leihua Yao

“…Then, the improved sparrow search algorithm (ISSA) is used to optimize the hyper-parameters of the Kriging surrogate model, in order to improve the computational efficiency and accuracy of the reliability analysis model. …”
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Research on unmanned mining truck path planning based on grey wolf optimization adaptive hybrid A* and artificial potential field by HAN Yanling, LYU Jinke, ZHOU Guofeng, ZHANG Like, ZHANG Yun

“…The proposed method emploied the grey wolf optimization algorithm to adaptively adjust the key parameters of the hybrid A*(HA*) algorithm, achieving a multi-objective balance among path length, smoothness, and planning time. …”
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