Determination of Sequential Well Placements Using a Multi-Modal Convolutional Neural Network Integrated with Evolutionary Optimization by Seoyoon Kwon, Minsoo Ji, Min Kim, Juliana Y. Leung, Baehyun Min

“…This complex multi-million-dollar problem involves optimizing multiple parameters using computationally intensive reservoir simulations, often employing advanced algorithms such as optimization algorithms and machine/deep learning techniques to find near-optimal solutions efficiently while accounting for uncertainties and risks. …”
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Multi-Objective Optimization Methods for University Campus Planning and Design—A Case Study of Dalian University of Technology by Lin Qi, Chaoran Chen, Jun Dong

“…This study focuses on the multi-objective coordination problem in university campus planning and design, proposing an optimized methodology integrating an improved multi-objective decision-making framework. …”
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Precision Soil Moisture Monitoring Through Drone-Based Hyperspectral Imaging and PCA-Driven Machine Learning by Milad Vahidi, Sanaz Shafian, William Hunter Frame

“…The primary aim was to understand the relationship between root zone water content and canopy reflectance, pinpoint the depths where this relationship is most significant, identify the most informative wavelengths, and train a machine learning model using those wavelengths to estimate soil moisture. …”
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Distributionally robust optimal scheduling of flexible distribution networks considering dynamic spatio-temporal correlation of renewable energy by Shunxiang Yu, Xiaoming Dong, Chengfu Wang, Tianguang Lu

“…By utilizing the 1-norm and ∞-norm to characterize the uncertainty sets between sources and loads, this strategy effectively minimizes operational costs while ensuring robust performance. The proposed model is linearized and relaxed through second-order cone programming and solved using the column and constraint generation (C&CG) algorithm. …”
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An Optimal Sizing Methodology for a Wind/PV Hybrid Energy Production System for Agricultural Irrigation in Skikda, Algeria by Nadhir Abderrahmane, Allaoua Brahmia, Adlen Kerboua, Ridha Kelaiaia

“…The optimization algorithm used was tailored to the formulated problem, ensuring reliable and applicable results. …”
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A Distributed Economic Power Dispatch Strategy Considering State of Charge for Microgrids by Kaicheng Lu, Shufeng Dong, Yonghua Song

“…Every node estimates the average SoC of all battery energy storage systems(BESSs) in a microgrid and determines the power of the local BESS and microturbine (MT) autonomously to achieve SoC balancing and economic dispatch with component constraints and power balance constraints by peer-to-peer communication with its neighbors. To improve the effectiveness of power distribution, an improved average consensus algorithm(IACA) based on particle swarm optimization (PSO) is proposed to adjust the weight matrix of communication networks, which reduces the number of iterations to estimate the average SoC. …”
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Research on the optimal scheduling of a multi-storage combined integrated energy system based on an energy supply grading strategy by Na Zhang, Feng You, Bingqian Hu, Jingyu Li, Guangchen Liu

“…Next, considering the system operational cost and carbon emission cost as the optimization goal, a comprehensive energy optimization scheduling model of multi-storage combined hierarchical energy supply is constructed. …”
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Enhancing microgrid forecasting accuracy with a TCNN-TLS framework: A novel approach to mitigating uncertainty in renewable energy and load predictions by Md. Omer Faruque, Md. Majharul Islam, Md Jakaria Talukder, Arif Mia, Shahriar Tasnim, Md. Alamgir Hossain, S.M. Muyeen

“…The employed settings contain a temporal convolutional neural network (TCNN) optimized with a pelican optimization algorithm (POA) to enhance its hyper-parameter selection. …”
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On the Use of Azimuth Cutoff for Sea Surface Wind Speed Retrieval From SAR by Yuting Zhu, Giuseppe Grieco, Jiarong Lin, Marcos Portabella, Xiaoqing Wang

“…The methodology probabilistically combines SAR data with ancillary meteorological information and optimizes the retrieval process through a cost function that leverages the sensitivity of the azimuth cutoff to changes in wind vector fields. …”
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Machine Learning-Driven Optimization of Transport Layers in MAPbI₃ Perovskite Solar Cells for Enhanced Performance by Velpuri Leela Devi, Piyush Kuchhal, Debasis de, Abhinav Sharma, Neeraj Kumar Shukla, Mona Aggarwal

“…In this research work, among those eight ML models, the XGBoost algorithm shows high accuracy for predicting the power conversion efficiency (PCE) of the cell, achieving root mean square error (RMSE) of 0.052 and a coefficient of determination (R2) of 0.999. …”
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Enhancing Security for Resource-Constrained Smart Cities IoT Applications: Optimizing Cryptographic Techniques with Effective Field Multipliers by Atef Ibrahim, Fayez Gebali

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Modular Coordination of Vehicle Routing and Bin Packing Problems in Last Mile Logistics by Nikica Perić, Anđelko Kolak, Vinko Lešić

“…<i>Background</i>: Logistics and transport, core of many business processes, are continuously optimized to improve efficiency and market competitiveness. …”
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A Study on an Anti-Multiple Periodic Frequency Modulation (PFM) Interference Algorithm in Single-Antenna Low-Earth-Orbit Signal-of-Opportunity Positioning Systems by Lihao Yao, Honglei Qin, Hao Xu, Deyong Xian, Donghan He, Boyun Gu, Hai Sha, Yunchao Zou, Huichao Zhou, Nan Xu, Jiemin Shen, Zhijun Liu, Feiqiang Chen, Chunjiang Ma, Xiaoli Fang

“…This paper proposes a Signal Adaptive Iterative Optimization Resampling (SAIOR) algorithm, which leverages the periodicity of PFM jamming signals and the characteristics of LEO constellation signals. …”
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Machine learning model for classifying high school students’ academic performance in mathematics amidst the COVID-19 context by Gisella Luisa Elena Maquen-Niño, Moisés Alvin Miguel_Flores, Leysi Yarely Aurich_Mio, Ivan Adrianzén Olano, Percy Edwin De la Cruz Vélez de Villa, Diana Mercedes Castro Cárdenas

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YOLO-SAIL: Attention-Enhanced YOLOv5 With Optimized Bi-FPN for Ship Target Detection in SAR Images by Prabu Selvam, P. Shanmuga Sundari, M. Tamilselvi, T. Suresh, M. Murugappan, Muhammad E. H. Chowdhury

“…It has recently become increasingly popular to apply deep learning algorithms to the identification of ships in SAR images. …”
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Detection Method for Bolts with Mission Pins on Transmission Lines Based on DBSCAN-FPN by Zhenbing ZHAO, Shuai ZHANG, Wei JIANG, Peng WU

“…Then, the FPN model is improved: based on the prior knowledge of bolts, the convolutional network is used to achieve bottom-up feature extraction, the bilinear interpolation method is used to transfer the high-level semantic information of the features to each level from top to bottom, the convolution filtering method is used to laterally strengthen the information fusion of high-level semantic features and high-resolution features, and a more optimized feature expression of bolts with missing pins is obtained. …”
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GAT-ADNet: Leveraging Graph Attention Network for Optimal Power Flow in Active Distribution Network With High Renewables by Dinesh Kumar Mahto, Mahipal Bukya, Rajesh Kumar, Akhilesh Mathur, Vikash Kumar Saini

“…The high penetration of renewables into the active distribution network (ADN) brings voltage deviation and difficulties to the optimal power flow (OPF) problem. The optimal operation of the distribution grid aims to efficiently manage the flow of electricity from sources to end-users, ensuring a resilient and sustainable grid. …”
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Research on Rolling Bearing Fault Diagnosis Using Improved Majorization-Minimization-Based Total Variation and Empirical Wavelet Transform by Yangli Ou, Shuilong He, Chaofan Hu, Jiading Bao, Wenjie Li

“…However, manually selecting parameters requires professional experience in a process that it is time-consuming and laborious, while the use of genetic algorithms is cumbersome. Therefore, an improved particle swarm algorithm (IPSO) is used to find the optimal solution of λ. …”
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Soft-sensor modeling of silicon content in hot metal based on sparse robust LS-SVR and multi-objective optimization by GUO Dong-wei, ZHOU Ping

“…Last, the multi-objective evaluation index that synthesizes the modeling residue and the estimated trend was&nbsp;presented to compensate for the deficiency of the single root mean square error (RMSE) index. Based on those, an on-line soft sensor model of hot metal[Si] with the optimal parameters was obtained by using the multi-objective genetic algorithm (NSGA-Ⅱ) with the non-dominated sort and elitist strategy. …”
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Risk-managed economic dispatch in hybrid hydrothermal-wind-solar systems: a novel multi-objective optimization approach by Zhe Wang, Tao Sun, Na Liu

“…The model integrates spinning reserve (SR) constraints and a synchronous peak shaving strategy to enhance system stability and cost efficiency. A Multi-Objective Artificial Rabbits Optimization (MOARO) algorithm, incorporating Pareto criteria and fuzzy theory, is applied to optimize dispatch decisions while balancing cost and risk. …”
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