Bio inspired optimization techniques for disease detection in deep learning systems by A. Ashwini, Vanajaroselin Chirchi, S. Balasubramaniam, Mohd Asif Shah

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Evaluation of Water Resources Carrying Capacity in Heilongjiang Province Based on PSO-SVM Model by WANG Tao, LI Zhijun

“…The problem of water resources has triggered a global crisis.With the rapid development of the social economy,the rapid increase in population,and the acceleration of modernization and urbanization,the demand for water in various industries is gradually increasing,and the problems of water shortage and water waste are becoming serious.Heilongjiang Province is an important industrial base and a major grain-producing province in China.With the rapid development of the economy and society,the contradiction between the supply and demand of water resources has become increasingly prominent.Although many measures have been taken to protect water resources in Heilongjiang Province,the development and utilization situation of water resources is still severe.In view of the above problems,this paper established a support vector machine (SVM) model optimized by particle swarm optimization (PSO) algorithm to evaluate the water resources carrying capacity in Heilongjiang Province.Based on the actual situation of Heilongjiang Province,an evaluation index system and index grading standards were established to evaluate the water resources carrying capacity of 13 cities in Heilongjiang Province in 2020.It thus provides a reference for the development and utilization of water resources in the future and plays a certain role in the application and promotion of SVM in water resources.The PSO-SVM model complements the theory of multi-factor comprehensive evaluation.…”
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Geometric Accuracy Design and Tolerance Allocation of Precision Horizontal Machining Centers by Lina Wang, Xingxing Liu, Wenjie Tian, Dawei Zhang

Subjects: “…precision horizontal machining center…”
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Combined mechanistic and machine learning method for construction of oil reservoir permeability map consistent with well test measurements by Evgenii Kanin, Alsu Garipova, Sergei Boronin, Vladimir Vanovskiy, Albert Vainshtein, Andrey Afanasyev, Andrei Osiptsov, Evgeny Burnaev

“…The developed approach outperforms kriging in terms of numerical reservoir modeling outcomes. This research advances existing geostatistical interpolation techniques by fusing well logging and well test data to build the reservoir permeability map through an optimization framework coupled with machine learning. …”
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Machine Learning in Biomedical Informatics: Optimizing Resource Allocation and Energy Efficiency in Public Hospitals by Agostino Marengo, Vito Santamato, Massimo Iacoviello

“…By integrating interpretable machine learning with computational optimization, the model contributes to building sustainable and high-performing hospital systems aligned with both operational and environmental objectives.…”
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An Analysis of Semi-Supervised Machine Learning in Electrical Machines by V. Raju Arvind, S. Shyamsharan, Poorvajaa Gurunathan, Krishna Kumba, Nawin Ra

“…SSML provides a key benefit in enhancing the effectiveness and precision of predictive models for optimizing electrical machine performance, reliability, and maintenance by leveraging labeled and unlabeled data. …”
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Utilizing Machine Learning Approach to Forecast Average Location Determination Errors in Wireless Sensor Networks by Zhihui Zhu, Meifang Zhu

“…Using a limited number of beacons and anchor nodes, the proposed approach leverages machine learning techniques, specifically Random Forest Regression (RFR) enhanced by Smell Agent Optimization (SAO) and Golden Jackal Optimization Algorithm (GJOA), to optimize network performance and minimize localization errors. …”
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Enhancing machine learning performance in cardiac surgery ICU: Hyperparameter optimization with metaheuristic algorithm. by Ali Bahrami, Morteza Rakhshaninejad, Rouzbeh Ghousi, Alireza Atashi

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Underwater Acoustic Signal Prediction Based on MVMD and Optimized Kernel Extreme Learning Machine by Hong Yang, Lipeng Gao, Guohui Li

“…Based on the prediction model of kernel extreme learning machine (KELM), this paper uses grey wolf optimization (GWO) algorithm to optimize and select its regularization parameters and kernel parameters and proposes an optimized kernel extreme learning machine OKELM. …”
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Hybrid Harris hawks-optimized random forest model for detecting multi-element geochemical anomalies related to mineralization by Hamid Sabbaghi, Nader Fathianpour

Subjects: “…Advanced machine learning model…”
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A Bayesian-Optimized Surrogate Model Integrating Deep Learning Algorithms for Correcting PurpleAir Sensor Measurements by Masrur Ahmed, Jing Kong, Ningbo Jiang, Hiep Nguyen Duc, Praveen Puppala, Merched Azzi, Matthew Riley, Xavier Barthelemy

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Comparing and Optimizing Four Machine Learning Approaches to Radar-Based Quantitative Precipitation Estimation by Miaomiao Liu, Juncheng Zuo, Jianguo Tan, Dongwei Liu

“…Compared to using only radar reflectivity, the KAN deep learning model reduced the MRE by 20.78%, MAE by 4.07%, and RMSE by 12.74%, while increasing the coefficient of determination (R²) by 18.74%. (3) The integration of multiple meteorological features and machine learning optimization significantly enhanced QPE accuracy, with the KAN deep learning model performing best under varying meteorological conditions. …”
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Machine learning-aided lattice optimization for ultra-lightweight 3D-printed aligners by Poom Narongdej, Bradley Yuhasz, Tianmin Kong, Diego Rojas, Qidi Peng, Ehsan Barjasteh

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Optimizing resource allocation in industrial IoT with federated machine learning and edge computing integration by Ala'a R. Al-Shamasneh, Faten Khalid Karim, Yu Wang

“…This algorithm adeptly balances resource expenditures with model quality, employing Lyapunov-driven optimization theory to convert long-term stochastic challenges into short-term deterministic resolutions. …”
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Enhancing patient rehabilitation outcomes: artificial intelligence-driven predictive modeling for home discharge in neurological and orthopedic conditions by Leonardo Buscarini, Paola Romano, Elena Sofia Cocco, Carlo Damiani, Sanaz Pournajaf, Marco Franceschini, Francesco Infarinato

“…This process involved variables recoding, scaling, and the evaluation of different dataset balancing methods to optimize model performance. Following a thorough review and comparison of algorithms commonly employed in the clinical-rehabilitative field, the Random Over Sampling (ROS) technique, in combination with the Random Forest (RF) machine learning model, was selected. …”
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BIMSSA: enhancing cancer prediction with salp swarm optimization and ensemble machine learning approaches by Pinakshi Panda, Sukant Kishoro Bisoy, Amrutanshu Panigrahi, Abhilash Pati, Bibhuprasad Sahu, Zheshan Guo, Haipeng Liu, Prince Jain

“…Then, SSA was implemented to optimize feature size. To optimize feature space, five separate machine learning classifiers, Support Vector Machine (SVM), Random Forest (RF), Extreme Learning Machine (ELM), AdaBoost, and XGBoost, were applied as the base learners. …”
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Machine learning-based coalbed methane well production prediction and fracturing parameter optimization by HU Qiujia, LIU Chunchun, ZHANG Jianguo, CUI Xinrui, WANG Qian, WANG Qi, LI Jun, HE Shan

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Structural Parameter Optimization of a Tubular Permanent-Magnet Linear Machine for Regenerative Suspension by Dongsheng Lu, Hailong Zhang, Jian Liu, Enrong Wang

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Optimized Motion Capture for Cricket Shot Classification Using Minimal Hardware and Machine Learning by J. Ishan Randika, Kanishka Rajamanthri, Avishka Kothalawala, Niroshan Gunawardana, Ashan Induranga, Pathum Weerakkody, Kaveendra Maduwantha, B. T. G. S. Kumara, Kaveenga Koswattage

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Robust predictive framework for diabetes classification using optimized machine learning on imbalanced datasets by Inam Abousaber, Haitham F. Abdallah, Hany El-Ghaish

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