Anchor Dragging Risk Estimation Strategy from Supervised Cost-Sensitive Learning by Sang-Lok Yoo, Shem Otoi Onyango, Joo-Sung Kim, Kwang-Il Kim

“…This suggested that the optimal ML strategy would involve undersampling the majority class and cost-sensitive learning. …”
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Spatio-Temporal Joint Planning for Integrated Energy Systems with Internet Data Center Considering Privacy Preservation by WU Chengbang, CHENG Zhijiang, LU Haifeng, YANG Handi

“…Considering the privacy preservation requirements between the IDC and IES， an enhanced Benders decomposition algorithm for mixed-integer linear programming subproblems was improved， and a distributed solution framework was designed to solve the spatio-temporal joint planning model. …”
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Emergency evacuation paths for tank farm fires based on bi-objective dynamic planning by Guanbo Chou, Yili Duo, Jie Liu, Lin Sun, Yuyuan Zhang, Tie Sun

“…The BODP method includes both an equivalent rule proposed for the first time based on the linear weighting method, and an improved Dijkstra algorithm designed in this paper. …”
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Numerical thermodynamic-economic study and machine learning-based optimization of an innovative biogas-driven integrated power plant combined with sustainable liquid CO2 and liquid... by Ruijia Yuan, Fan Shi, Azher M. Abed, Mohamed Shaban, Sarminah Samad, Ahmad Almadhor, Barno Abdullaeva, Mouloud Aoudia, Salem Alkhalaf, Samah G. Babiker

“…In industrial environments, it effectively optimizes energy use and production processes by examining various operational factors, which leads to cost reductions and improved efficiency via predictive maintenance and cohesive energy strategies. …”
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A Robust Multi-Objective Evolutionary Framework for Artificial Island Construction Scheduling Under Dynamic Constraints by Tianju Zheng, Liping Sun, Mingwei Li, Guangyao Yuan, Shuqi Li

“…Artificial island construction is a multifaceted engineering endeavor that demands precise scheduling to optimize resource allocation, control costs, ensure safety, and minimize environmental impact within dynamic marine environments. …”
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Cost-efficient dynamic quota-controlled routing in multi-community delay-tolerant networks by Jiagao Wu, Yue Ma, Linfeng Liu

“…In this article, we present a network model of the multi-community delay-tolerant networks and formulate a dynamic quota-controlled routing problem of minimizing the average number of copies of a message that satisfies the required delivery probability under the given time-to-live of the message as a nonlinear optimization problem. To solve this problem, we propose an improved genetic algorithm called genetic algorithm for delivery probability and time-to-live optimization for the dynamic quota-controlled routing scheme to reduce the routing cost further. …”
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Enhancing stochastic optimal power flow with modified cheetah optimizer for integrating renewable energy sources by Majid Saeidi, Taher Niknam, Mohsen Zare, Zulfiqar Ali Memon

“…A backward-forward correction method was used to correct errors in three types of reserves, improving the solution quality. The effectiveness of the MCO in solving practical large-scale optimization problems was demonstrated by the results of the 10-unit and 30-unit dynamic economic dispatch, achieving lower cost values than previously published papers. …”
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A Multi-Objective Particle Swarm Optimization Approach for Optimizing K-Means Clustering Centroids by Aina Latifa Riyana Putri, Joko Riyono, Christina Eni Pujiastuti, Supriyadi

“…This study evaluates the performance of the standard K-Means algorithm and proposes a Multiobjective Particle Swarm Optimization K-Means (MOPSO+K-Means) approach to improve clustering accuracy. …”
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Heuristically enhanced multi-head attention based recurrent neural network for denial of wallet attacks detection on serverless computing environment by Sarah A. Alzakari, Mohammad Alamgeer, Abdullah M. Alashjaee, Monir Abdullah, Khalid Nazim Abdul Sattar, Asma Alshuhail, Ahmad A. Alzahrani, Abdulwhab Alkharashi

“…The detection and classification of DoW attacks, the multi-head attention-based bi-directional gated recurrent unit (MHA-BiGRU) model is utilized. Eventually, the improved secretary bird optimizer algorithm (ISBOA)-based hyperparameter choice process is accomplished to optimize the detection results of the MHA-BiGRU model. …”
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Future Smart Grids Control and Optimization: A Reinforcement Learning Tool for Optimal Operation Planning by Federico Rossi, Giancarlo Storti Gajani, Samuele Grillo, Giambattista Gruosso

“…This study presents a methodology based on reinforcement learning (RL) for evaluating optimal power flow with respect to various cost functions. …”
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Optimal Temperature Calculation for Multicriteria Optimization of the Hydrogenation of Polycyclic Aromatic Hydrocarbons by NSGA-II Method by A. A. Alexandrova, S. N. Koledin

“…Introduction. Multicriteria optimization, taking into account contradicting criteria, is used to improve production efficiency, reduce costs, improve product quality and environmental safety of processes. …”
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Hardware implementation of RSA encryption algorithm based on pipeline by Yang Longfei, Lu Shi, Peng Kuang

“…To address the high cost of implementing long-bits RSA encryption algorithms in hardware, improvements have been made to the traditional radix-4 Montgomery algorithm. …”
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Provident garbage collection algorithm for SSD storage system by Xuezhen TU, Zhenjiang Huang, Zhengguang CHEN

“…A predictive based proactive garbage collection algorithm was proposed.Firstly,the data was separated according to different heat factors,then the upper and lower predictions were performed on the number of different types of page allocation requests (PAR) that would be reached in the future.While satisfying the page allocation request lower prediction,the PAR upper prediction requirement was maximally satisfied,the WA problem was optimized,and invalid effective data migration was reduced,thereby maximizing the garbage collection utility.A mathematical model was defined for this problem,and an algorithm for obtaining the approximate optimal solution was given.The applicable scenario of the model was analyzed.The practical results show that the algorithm can obtain the maximum benefit and can significantly improve the performance of SSD and reduce the cost.…”
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Machine Learning-Based Sentiment Analysis in English Literature: Using Deep Learning Models to Analyze Emotional and Thematic Content in Texts by Jie Yu, Chunhong Qi

“…The model is designed to capture complex emotional nuances and themes in literature by processing text data from both forward and backward directions, while the attention mechanism enables the model to focus on the most important sections of the text. Hyperparameter optimization is performed using the Improved Particle Swarm Optimization (IPSO) algorithm to fine-tune the model for efficient sentiment extraction. …”
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Artificial Intelligence and/or Machine Learning Algorithms in Microalgae Bioprocesses by Esra Imamoglu

“…Despite these hurdles, AI/ML technologies have shown significant improvements in system performance, scalability, and resource efficiency, as well as in cutting costs, minimizing downtime, and reducing environmental impact. …”
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An intelligent hybrid grey wolf-particle swarm optimizer for optimization in complex engineering design problem by Muhammad Suhail Shaikh, Haoyue Lin, Senlin Xie, Xiaoqing Dong, Yifan Lin, Chandan Kumar Shiva, Wulfran Fendzi Mbasso

“…The improvement in the average best optimal value varies across different cases, demonstrating the effectiveness of the proposed method. …”
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Synchronous Firefly Algorithm for Cluster Head Selection in WSN by Madhusudhanan Baskaran, Chitra Sadagopan

“…In this work, a modified firefly heuristic, synchronous firefly algorithm, is proposed to improve the network performance. …”
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Multi-Level Particle System Modeling Algorithm with WRF by Julong Chen, Bin Wang, Rundong Gan, Xuepeng Mou, Shiping Yang, Ling Tan

“…Experimental results show that, compared with similar algorithms, our algorithm reduces the average running time by 37.5%, indicating enhanced computational efficiency and real-time capability, and the average number of required particles by 30.1%, reducing the cost of long-range computing. …”
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Development of Low-Cost Single-Chip Automotive 4D Millimeter-Wave Radar by Yongjun Cai, Jie Bai, Hui-Liang Shen, Libo Huang, Bing Rao, Haiyang Wang

“…This study focuses on developing single-chip 4D automotive millimeter-wave radar, covering system architecture design, antenna optimization, signal processing algorithm creation, and performance validation. …”
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Optimizing Euclidean Distance Computation by Rustam Mussabayev

“…The Euclidean distance, being a computational bottleneck in large-scale optimization problems, requires efficient computation techniques to improve the performance of various distance-dependent algorithms. …”
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