Machine learning prediction and interpretability analysis of high-risk chest pain: a study from the MIMIC-IV database by Hongyi Chen, Haiyang Song, Hongyu Huang, Xiaojun Fang, Huang Chen, Qingqing Yang, Junyu Zhang, Wenjun Ding, Zheng Gong, Jun Ke

“…To address class imbalance, we implemented feature engineering with SMOTE and under-sampling techniques. Model optimization was performed via Bayesian hyperparameter tuning. …”
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Train adaptive energy saving strategy based on iterative induced genetic algorithm by MEI Wenqing, SHI Ke, ZHANG Zhengfang

“…Then, to overcome the difficulty of traditional genetic algorithms in solving continuous sub-interval optimization problems due to discrete independence, an iterative induced genetic algorithm was designed to calculate the Pareto optimal solution set for the energy-saving objective function. …”
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The necessity of the Black Sea region transport structure improvement by L.V. Nazarova

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A Detailed Comparison of Two New Heuristic Algorithms Based on Gazelles Behavior by Emine Baş

“…In this study, Mountain Gazelle Optimization (MGO) and Gazelle Optimization Algorithm (GOA) algorithms, which have been newly proposed in recent years, were examined. …”
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Energy scheduling algorithm for urban rail active traction power supply system by ZHANG Chao, LI Hongbo, ZHAO Liying, HUANG Zihao, LUO Wenguang, WANG Xiong

“…The full power and constant voltage models were used to simulate the two different working conditions of the bidirectional converter, and the internal and external double-layer iterative algorithm was used to calculate the power flow. …”
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A Review on Path Planning and Obstacle Avoidance Algorithms for Autonomous Mobile Robots by Anis Naema Atiyah Rafai, Noraziah Adzhar, Nor Izzati Jaini

“…This paper reviews the mobile robot navigation approaches and obstacle avoidance used so far in various environmental conditions to recognize the improvement of path planning strategists. Taking into consideration commonly used classical approaches such as Dijkstra algorithm (DA), artificial potential field (APF), probabilistic road map (PRM), cell decomposition (CD), and meta-heuristic techniques such as fuzzy logic (FL), neutral network (NN), particle swarm optimization (PSO), genetic algorithm (GA), cuckoo search algorithm (CSO), and artificial bee colony (ABC). …”
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Application of artificial intelligence technology in the economic development of urban intelligent transportation system by Ziming Zhao, Jinyu Chen

“…A traffic flow prediction model was established for traffic flow prediction and optimized scheduling algorithms were used to dispatch vehicles on congested urban roads intelligently. …”
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Optimizing power network expansion with pumped hydro energy storage using a multi-objective enhanced spider wasp optimizer approach by Mohamed M. Refaat, Saad F. Al-Gahtani, Hussain Bassi, Ziad M. Ali, Shady H. E. Abdel Aleem

“…The problem is framed as a comprehensive multi-objective optimization model designed to minimize the cost of network expansion while maximizing the benefits of integrating various PHES technologies. …”
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Automatic strip layout design in progressive dies using the grouping genetic algorithm by Mehran Afshari, Behrooz Arezoo

“…In the present study, a new method is presented for the automatic strip layout design for progressive dies using the Grouping Genetic Algorithm. A two-objective function is used in the optimization process. …”
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Research on short-term precipitation forecasting method based on CEEMDAN-GRU algorithm by Hua Xu, Zongkai Guo, Yu Cao, Xu Cheng, Qiong Zhang, Dan Chen

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Storage Assignment Optimization in Robotic Mobile Fulfillment Systems by Ruiping Yuan, Juntao Li, Wei Wang, Jiangtao Dou, Luke Pan

“…A two-stage hybrid algorithm combining greedy algorithm and improved simulated annealing is designed to solve the model. …”
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Energy-efficient collaborative transmission algorithm based on potential game theory for beamforming by Jing Zhang, Li Lei, Xin Feng

“…Second, a potential game model is proposed as a joint method for optimizing the collaborative parameters of the cooperative nodes and their energy consumption balancing features. …”
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Toward an algorithm of percutaneous microelectrolysis: a randomized clinical trial on invasive techniques by Carlos Eduardo Girasol, Nathaly Escobar Durán, Santiago Marcelo D’Almeida, Oscar Ariel Ronzio

“…CONCLUSIONS: All needling techniques demonstrated analgesic effects on myofascial trigger points, with the algorithm-enhanced MEP showing the most notable improvement in self-reported pain. …”
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Multi-Task Perception Algorithm for Rail Transit Scenarios Based on Triplet Attention by GAO Rui, XIONG Yanping, WEI Chenfeng, XIE Guotao, GAO Ming

“…Through validation using datasets from actual scenes, the model exhibited significant improvements in small object detection, detection speed, and environmental adaptability. …”
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Research on Flexible Job Shop Scheduling Method for Agricultural Equipment Considering Multi-Resource Constraints by Zhangliang Wei, Zipeng Yu, Renzhong Niu, Qilong Zhao, Zhigang Li

“…To tackle this complex problem, a Multi-Objective Discrete Grey Wolf Optimization (MODGWO) algorithm is proposed. The MODGWO algorithm integrates a hybrid initialization strategy and a multi-neighborhood local search to effectively balance the exploration and exploitation capabilities. …”
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Leveraging the Louvain algorithm for enhanced group formation and collaboration in online learning environments by Minkyung Lee, Priya Sharma

“…Traditional methods of group formation, such as teacher intervention and self-selection, often fail to create balanced and effective groups, especially in large online courses. The Louvain algorithm, known for its efficiency in modularity optimization, identifies clusters based on actual student interaction patterns. …”
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A hybrid Spatial Ant Lion optimization and utilitarian data transmission approach for intelligent optimization for energy-efficient wireless sensor networks by Malathy Sathyamoorthy, Rajesh Kumar Dhanaraj, C N Vanitha, Md Shohel Sayeed

“…Results demonstrate that the proposed model achieved a 1.86% increase in throughput, a 2.56% reduction in delay, and a 3.18% improvement in energy efficiency when compared to existing schemes such as PSO, ALO, and SA-AOA.…”
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Image Reconstruction Algorithm Based on Extreme Learning Machine for Electrical Capacitance Tomography by SU Ziheng, CHEN Deyun, WANG Lili

“…Aiming at the problem that the traditional ECT is not accurate in complex situations, this paper proposes a depth learning based inversion method Through the improvement and optimization of the traditional extreme learning machine, the image feature information obtained by the reconstructed image method is used as the training data, and the result obtained by inputting the data into the predictive model is used as the prior information The cost function is used to encapsulate the prior knowledge and domain expertise, and spatial regularizers and time regularizers are introduced to enhance sparsity The separated Bregman (SB) algorithm and the iterative shrinkage threshold (FIST) method are used to solve the specified cost function The final imaging result is obtained The simulation results show that the image reconstructed by this method has less than 10% error compared with the original flow pattern, and reduces artifacts and distortion, which improves the reconstructed image quality…”
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Research of Online Error Prediction and Parallel Algorithm for Voltage Transformer in Smart Grid by Xin Xianfeng, Chen Rongye, Lin Cong, Liu Qingchan, He Zhaolei, Li Tengbin, Yang Guangrun, Kochan Orest, Karpa Mykhailo

“…This article mainly focuses on the online error prediction and the parallelization method of voltage transformers. First, an optimized multi-layer perceptron model based on the sparrow search algorithm (SSA) is proposed. …”
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KAB: A new k-anonymity approach based on black hole algorithm by Lynda Kacha, Abdelhafid Zitouni, Mahieddine Djoudi

“…Clustering-based approaches have been successfully adapted for k-anonymization as they enhance the data quality, however, the computational complexity of finding an optimal solution has shown as NP-hard. Nature-inspired optimization algorithms are effective in finding solutions to complex problems. …”
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