Predicting Ocean Current Temperature Off the East Coast of America with XGBoost and Random Forest Algorithms Using Rstudio by Lulut Alfaris, Anas Noor Firdaus, Ukta Indra Nyuswantoro, Ruben Cornelius Siagian, Aldi Cahya Muhammad, Rohana Hassan, Rodulfo T. Aunzo, Jr., Reza Ariefka

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Optimal Low-Carbon Scheduling for Smart Microgrids With Dynamic Thermal Capacity Constraints by Peng Xie, Hongwei Liu, Chun Chen, Mingjun Liu

“…This study proposes a two-stage day-ahead robust optimization framework for the microgrids, integrating tri-level min-max-min modeling to address multidimensional uncertainties through parameterized uncertainty sets to balance conservatism and optimize costs under worst-case scenarios. …”
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Engineering project management technology based on visual simulation module and particle swarm optimization by Hua Tian

“…The particle swarm multi-objective optimization algorithm performed well in reducing project cost prediction errors. …”
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Cloud-edge hybrid deep learning framework for scalable IoT resource optimization by Umesh Kumar Lilhore, Sarita Simaiya, Yogesh Kumar Sharma, Anjani Kumar Rai, S. M. Padmaja, Khan Vajid Nabilal, Vimal Kumar, Roobaea Alroobaea, Hamed Alsufyani

“…Simulations using real-world IoT data on the iFogSim platform showed significant improvements: task scheduling time was reduced by 21%, operational costs by 17%, and energy consumption by 22%. …”
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Energy-aware Application Mapping onto 3D Mesh-Based Network-on-Chip using Heuristic Mapping Algorithms by Kiran K A, Jaison Jacob

“…The study’s objective is to estimate these algorithms’ effectiveness in optimizing communication cost, communication energy, and CPU run time in both 2D and 3D mesh NoC architectures. …”
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Comparative analysis of machine learning models for malaria detection using validated synthetic data: a cost-sensitive approach with clinical domain knowledge integration by Gudi V. Chandra Sekhar, Chekol Alemu

“…XGBoost achieved optimal performance with highest $$\text {AUC}$$ (0.956, 95% $$\text {CI}$$ : 0.952–0.961) and competitive clinical cost (5,496), representing 2.8% improvement over Random Forest. …”
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Multi-Energy Optimal Dispatching of Port Microgrids Taking into Account the Uncertainty of Photovoltaic Power by Xiaoyong Wang, Xing Wei, Hanqing Zhang, Bailiang Liu, Yanmin Wang

“…Firstly, based on the improved Iterative Self-organizing Data Analysis Techniques Algorithm (ISODATA) clustering algorithm and backward reduction method, a set of typical scenarios that represent the uncertainties of PV and load is generated. …”
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An experimental optimization environment for developing an intracycle pitch control in cross flow turbines by Stefan Hoerner, Roberto Leidhold, Shokoofeh Abbaszadeh, Karla Ruiz-Hussmann, Timo Bennecke, Zhao Zhao, Paul Joedecke, Christian-Thoralf Weber, Pierre-Luc Delafin, Cyrille Bonamy, Yves Delannoy

“… Cross-flow tidal turbines have not reached the efficiency of horizontal-axis turbines. Among various improvement approaches found in the literature, the intracycle pitch control is one of the most promising ones. …”
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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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Metamodel-Based Optimization Method for Traffic Network Signal Design under Stochastic Demand by Wei Huang, Xuanyu Zhang, Haofan Cheng, Jiemin Xie

“…By incorporating the model bias, the combined metamodel can better approximate the original optimal solution. Moreover, incorporating the gradient information of the traffic flow in the optimization search algorithm can further improve the solution performance. …”
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Integrated Optimization on Train Control and Timetable to Minimize Net Energy Consumption of Metro Lines by Yuhe Zhou, Yun Bai, Jiajie Li, Baohua Mao, Tang Li

“…Energy-efficient metro operation has received increasing attention because of the energy cost and environmental concerns. This paper developed an integrated optimization model on train control and timetable to minimize the net energy consumption. …”
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Dynamic path planning of UAV with least inflection point based on adaptive neighborhood A* algorithm and multi-strategy fusion by Longyan Xu, Mao Xi, Ren Gao, Ziheng Ye, Zaihan He

“…In order to solve these challenges, this paper proposes a dynamic obstacle avoidance algorithm (MSF-MTPO) with multi-strategy fusion to achieve the least inflection point path optimization. …”
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Comprehensive Utilization and Optimal Allocation of Environmental Protection Building Materials in the Construction of Civil Engineering by Li Ren, Huasha Ru, Ruiya Xiao, Yao Ju

“…The research results show that through scientific and reasonable material optimization allocation, the utilization rate of materials can be further improved, the construction efficiency can be improved, the overall construction cost can be reduced, and the carbon emission can be reduced by more than 20%, which provides an essential reference for the sustainable development of civil engineering construction.…”
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A Bi-Level Optimization Model for Flexible Capacity Allocation with Coordinated Planning and Operation by Xinyu Yin, Xiaoyan Bian, Qinran Zhu, Jinbin Zhao, Shunfu Lin, Kwok L. Lo

“…The aim is to optimize the annual total cost and flexibility of the system. …”
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Source-storage-load optimization control technology of DC microgrid with virtual energy storage by WANG Chang, JIANG Yu, FU Shouqiang, SHU Yinan, ZHANG Xiangyu

“…On this basis, under the coordinated control of source and storage of DC microgrid, particle swarm optimization algorithm is used to optimize the design of virtual capacitance values in different periods of time to improve the economic benefits of the system. …”
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Reverse Logistics Network Optimization for Retired BIPV Panels in Smart City Energy Systems by Cimeng Zhou, Shilong Li

“…Meanwhile, the multi-level recycling network which covers “building points-regional transfer stations-specialized distribution centers” is designed in the research, the Pareto solution set is solved by the improved NSGA-II algorithm, a “1 + 1” du-al-core construction model of distribution center and transfer station is developed, so as to minimize the total cost and life cycle carbon footprint of the logistics network. …”
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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

“…To address these issues, a novel Lyapunov-driven optimization algorithm for device selection and bandwidth allocation is introduced. …”
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Explainable AI and optimized solar power generation forecasting model based on environmental conditions. by Rizk M Rizk-Allah, Lobna M Abouelmagd, Ashraf Darwish, Vaclav Snasel, Aboul Ella Hassanien

“…The results of this paper improve the performance of the original model's conventional LSTM, where the improvement rate is; 148%, 21%, 27%, 20%, 134% for R2, RMSE, COV, MAE, and EC respectively. …”
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A Parameter-Optimized DBN Using GOA and Its Application in Fault Diagnosis of Gearbox by Jingbo Gai, Junxian Shen, He Wang, Yifan Hu

“…Aiming at the problems of poor self-adaptive ability in traditional feature extraction methods and weak generalization ability in single classifier under big data, an internal parameter-optimized Deep Belief Network (DBN) method based on grasshopper optimization algorithm (GOA) is proposed. …”
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An optimal weighting-based hybrid classifier for Children's congenital heart diseases signal processing by Morteza Ebrahimpour, Mehdi Khashei

“…In this paper, a hybrid classifier incorporating Long Short-Term Memory (LSTM), Support Vector Machine (SVM), and Convolutional Neural Network (CNN) is proposed and applied to diagnose congenital heart disease in children. The most distinguishing feature of the proposed hybrid classifier compared to existing ones is its optimal weighting algorithm. …”
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