Comparative analysis of machine learning techniques in metabolomic-based preterm birth prediction by Ying-Chieh Han, Jane Shearer, Chunlong Mu, Donna M. Slater, Suzanne C. Tough, Gavin E. Duggan

“…Linear models such as PLS-DA and logistic regression demonstrated moderate classification performance (AUROC ≈ 0.60), whereas non-linear approaches, including ANN and XGBoost, exhibited marginal improvements. …”
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Classification of Anxiety Levels of IGD Patients at RSU Royal Prima Medan Using Support Vector Machine (SVM) Algorithm by Kharisma Gunanta Ginting, Nugroho Prasetyo, Al Vino Gunawan, Magdalena Sihombing, Adli Abdillah Nababan

“…The preprocessing process includes imputing missing values and normalizing numerical features so that the model can learn optimally. Performance evaluation shows that the use of SMOTE increases classification accuracy from 95% to 97%, as well as improving precision, recall, and F1-score metrics at almost all anxiety levels. …”
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Prediction and dynamic optimization of drilling performance based on the combination of mineral composition and operational factors by Xiong Xiuli, Li Qian, Liu Junhao, Jiang Jie

“…According to the training and testing results, the introduction of mineral composition can effectively improve the training speed and testing accuracy. Through the established prediction function, a dynamic optimization algorithm combined with DOE (Design of Experiments) theory was also developed. …”
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Optimal Coordination of Directional Overcurrent Relays in Microgrids Considering European and North American Curves by León F. Serna-Montoya, Sergio D. Saldarriaga-Zuluaga, Jesús M. López-Lezama, Nicolás Muñoz-Galeano

“…The proposed model is formulated as a mixed-integer nonlinear programming problem and solved using four metaheuristic techniques: the genetic algorithm (GA), Imperialist Competitive Algorithm (ICA), Harmonic Search (HS), and Firefly Algorithm (FA). …”
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An Optimized Cascaded CNN Approach for Feature Extraction From Brain MRIs for Tumor Classification by Santosh Kumar Chhotray, Debahuti Mishra, Sarada Prasanna Pati, Sashikala Mishra

“…The enhanced version of the Custom-CNN-CBAM model utilizing the BEO, referred to as Custom-CNN-CBAM-BEO, demonstrated superior convergence speed and accuracy compared to models optimized with genetic algorithm (GA) and particle swarm optimization (PSO), highlighting the effectiveness of the BEO optimization approach. …”
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Optimized deep residual networks for early detection of myocardial infarction from ECG signals by Pon Bharathi A, Madavan R, Sakthivel E

“…The proposed system introduces a novel MI detection technique using a Deep Residual Network (DRN), where the solution is optimized by the proposed Social Ski-Spider (SSS) Optimization algorithm is the novel combination of both Social Ski-driver (SSD) Optimization and the Spider Monkey Optimization (SMO). …”
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Numerical Simulation Study on Adjoint-Based Optimization of a Propeller Using Reverse Engineering by Hao Wang, Yaoqing Liao, Mingge Shen, Sujie Zhou, Gang Xu

“…The optimization target was set at a 10% improvement in the lift-to-drag ratio, and the adjoint-based optimization of the target airfoil sections at different angles of attack was performed using the gradient descent algorithm. …”
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Hybrid intelligence framework for optimizing shear capacity of lightweight FRP-reinforced concrete beams by Iman Faridmehr, Moncef L. Nehdi, Mohammad Ali Sahraei, Kiyanets Aleksandr Valerievich, Chiara Bedon

“…Leveraging a dataset of 260 experimental FRP-RC beam cases, two distinct Artificial Neural Network (ANN) models were developed using the Levenberg-Marquardt algorithm. …”
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ABC and HML-methods application for determination and optimization of stock for electrical equipment accessory parts by A. V. Beloglazov, A. G. Rusina, O. V. Fomenko, D. A. Pekhota, V. A. Fyodorova

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Optimizing frequency stability with adaptive fast frequency reserves and Wide-Area Monitoring Systems by Bwandakassy Elenga Baningobera, Irina Oleinikova, Kjetil Uhlen

“…The adaptive algorithm’s ability to adjust to varying system conditions reduces the risk of over-shedding or under-shedding loads, thereby optimizing the system’s performance. …”
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Optimal energy management of multi-carrier energy system considering uncertainty in renewable generation by Ankit Garg, K. R. Niazi, Shubham Tiwari, Sachin Sharma, Tanuj Rawat

“…The optimization model is solved using the Modified Water Evaporation algorithm. …”
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Improvement of the Diagnostics of the Fetus Heart Anomalies During a Routine Screening Ultrasound Examination by Markin L., Medvjedjeva O.

“…So, the study of fetal heart is one of the most important stages of screening ultrasound in the second trimester of pregnancy.…”
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Optimizing urban energy flows: Integrative vehicle-to-building strategies and renewable energy management by Jian Hern Yeoh, Kai-Yun Lo, I-Yun Lisa Hsieh

“…This study introduces a scalable, multi-objective optimization model that utilizes Vehicle-to-Building (V2B) interactions to mitigate grid load by leveraging EVs as mobile energy storage units. …”
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Optimizing TCP Performance in Multi-AP Residential Broadband Connections via Minislot Access by Domenico Giustiniano, Eduard Goma, Alberto Lopez Toledo, George Athanasiou

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A power-distribution joint optimization arrangement for multi-point source jamming system by Zhihao Cai, Shiqi Xing, Sinong Quan, Xinyuan Su, Junpeng Wang

“…Third, a multi-objective time-varying mapping particle swarm optimization (MOTPSO) algorithm is adopted to solve the model, thereby achieving the optimal arrangement. …”
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Dynamic Error Compensation Control of Direct-Driven Servo Electric Cylinder Terminal Positioning System by Mingwei Zhao, Lijun Liu, Zhi Chen, Qinghua Yang, Xiaowei Tu

“…Then, a model to observe the dynamic error of the DDSEC-TPS was established using the improved beetle antennae search algorithm backpropagation neural network (IBAS-BPNN) prediction model according to the rigid–flexible deformation error theory of feed motion, and the observed dynamic error was compensated for in the vector control strategy of the DDSEC-TPS. …”
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Optimizing role assignment for scaling innovations through AI in agricultural frameworks: An effective approach by Sonia Bisht, Ranjana, Swapnila Roy

“…Significance: Furthermore, the study highlights the potential of AI to transform traditional farming practices, reduce labor-intensive processes, and improve decision-making accuracy. The proposed approach serves as a blueprint for agricultural enterprises aiming to adopt AI technologies while ensuring optimal utilization of human and technological resources. …”
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Optimization of the Canopy Three-Dimensional Reconstruction Method for Intercropped Soybeans and Early Yield Prediction by Xiuni Li, Menggen Chen, Shuyuan He, Xiangyao Xu, Panxia Shao, Yahan Su, Lingxiao He, Jia Qiao, Mei Xu, Yao Zhao, Wenyu Yang, Wouter H. Maes, Weiguo Liu

“…With these improvements, a high-precision 3D canopy point-cloud model of soybeans covering the entire growth period was successfully constructed. …”
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Enhancing Energy Efficiency in IoT-WSNs Through Optimized PSO Cluster Head Selection by Muhammad Haris, Haewoon Nam

“…In IoT-based wireless sensor networks (WSNs), clustering is one of the most effective energy-saving approaches for optimizing the life cycle of networks. …”
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Hybrid Attention-Enhanced Xception and Dynamic Chaotic Whale Optimization for Brain Tumor Diagnosis by Aliyu Tetengi Ibrahim, Ibrahim Hayatu Hassan, Mohammed Abdullahi, Armand Florentin Donfack Kana, Amina Hassan Abubakar, Mohammed Tukur Mohammed, Lubna A. Gabralla, Mohamad Khoiru Rusydi, Haruna Chiroma

“…Additionally, we developed a novel learning rate scheduler that dynamically adjusts the learning rate based on image size at each training phase, improving training efficiency and model adaptability. …”
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