An enhanced alpha evolution moss growth optimizer for prognostic prediction in spontaneous intracerebral hemorrhage by Lingxian Hou, Yongsheng Wang, Xiuqi Lin, Chengye Li, Huangrong Guo, Congcong Jin, Yi Chen, Huiling Chen, Jing Ji, Wenzong Zhu

“…Abstract Spontaneous Intracerebral Hemorrhage (SICH) is a critical condition with high mortality rates, requiring prompt and effective prognostic assessment. This study aims to improve SICH outcome prediction by developing the Alpha Evolution Moss Growth Optimization (AEMGO) algorithm for feature selection in high-dimensional medical datasets. …”
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Optimization of Communication Signal Adversarial Examples by Selectively Preserving Low-Frequency Components of Perturbations by Yi Zhang, Lulu Wang, Xiaolei Wang, Dianxi Shi, Jiajun Bai

“…As a result, selectively preserving LFCP is established as the fundamental concept of the optimization strategy. By utilizing the binary search algorithm, which considers the inconsistency in the model’s predictions as a constraint, LFCP can be effectively identified, and the aim of minimizing perturbed distortion while maintaining ASR can be achieved. …”
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Urban Multi-Scenario Land Use Optimization Simulation Considering Local Climate Zones by Jie Chen, Zikun Dong, Ruijie Shi, Geng Sun, Ya Guo, Zhuopeng Peng, Min Deng, Kaiqi Chen

“…The research employs a genetic algorithm to optimize the LCZ quantity structure in order to improve the urban temperature environment. …”
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Conditional distributionally robust dispatch for integrated transmission-distribution systems via distributed optimization by Jie Li, Xiuli Wang, Zhicheng Wang, Zhenzi Song

“…To ensure tractability, the model is reformulated into a linear programming problem through the duality theory-based transformation and Conditional Value-at-Risk (CVaR) approximation. …”
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Enhancement method of series hybrid ship energy efficiency for speed and energy collaborative optimization by Yupeng Yuan, Xiaoyu Wang, Liang Tong, Chengqing Yuan, Boyang Shen, Teng Long

“…Afterwards, the optimised speed of the ship and the optimised output power of each power source were determined using the grasshopper optimization algorithm. The ship's energy efficiency levels before and after using the energy efficiency enhancement method were compared and analysed, and the effects of this optimization method on the ship's energy efficiency in several typical voyages were analysed. …”
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Analysis of Smart Grid Optimal Scheduling considering the Demand Response of Different EV Owners by Xiaohua Zhang, Chongyang Liao, Xingrui Chen, Kuiheng Deng, Bolin Chen, Yibo Gong

“…According to charging and vehicle-to-grid (V2G) data of EV owners, the K-means clustering algorithm (K-means) is used to classify EV owners, and the demand response (DR) model is established based on the classification results. …”
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Binary Classification of Pneumonia in Chest X-Ray Images Using Modified Contrast-Limited Adaptive Histogram Equalization Algorithm by Abror Shavkatovich Buriboev, Akmal Abduvaitov, Heung Seok Jeon

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Forecast uncertainties real-time data-driven compensation scheme for optimal storage control by Arbel Yaniv, Yuval Beck

“…The refined real-time control scheme is integrated with a day-ahead optimization engine and forecast model, which is utilized for illustrative simulations to highlight its potential efficacy on a real site. …”
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Optimized wavelength selection for eggplant seed vitality classification using information acquisition techniques by Bing Yang, Xuyang Liu, Dongfang Zhang, Dongfang Zhang, Xiaofei Fan, Xiaofei Fan, Bo Peng, Jun Zhang, Jun Zhang

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Fusion of Rough Set Theory, Genetic Algorithm-Backpropagation Neural Networks and Shapley Additive Explanations for the Design of Bamboo Furniture by Zhongchen Huang, Li Ye

“…Finally, an intelligent mapping model between product components and emotional needs was constructed using Genetic Algorithm-Backpropagation Neural Networks (GA-BPNN), which predicts the optimal product design parameters that meet users' emotional needs. …”
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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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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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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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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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