Yield prediction, pest and disease diagnosis, soil fertility mapping, precision irrigation scheduling, and food quality assessment using machine learning and deep learning algorith... by S. Ajith, S. Vijayakumar, N. Elakkiya

“…Artificial intelligence algorithms efficiently process vast datasets from unmanned aerial vehicles, ground vehicles, and satellites, enabling precise and timely interventions. …”
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Kinematic analysis and optimisation of a gantry spraying robot for ship blocks by Jiangmin Xu, Jinhao Liu, Xuwen Jing, Honggen Zhou, Xiaocai Hu, Jianbo Ji, Zhenchun Han

“…The differential evolution algorithm and the adaptive differential evolution algorithm were both utilized to solve the optimal inverse solution. …”
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Distributed Robust Low-Carbon Economic Dispatch of Power Systems Considering Extreme Scenarios by HU Heng, QIN Jianru, LI Haibo, LIU Jiefeng

“…[Methods] To address this， this paper first constructs RE generation scenarios using Latin hypercube sampling （LHS） and modified k-means clustering， verifying their reserve feasibility， while transforming reserve-infeasible scenarios into extreme scenario sets. …”
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Prediction of maximum forming depth in single point incremental forming of 6061 aluminum alloy based on Adaboost regression by LIANG Zhikai, ZHANG Zhichao, HU Lan, PANG Qiu

“…The maximum error between the four groups of tests and simulations is 4.24%， while the maximum error with the actual forming results is -2.45%.…”
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Early Detection of Voltage Instability: A Transparent, Rule-Based Method for Cyber-Resilient Grids by Mahtab Khalilifar, Seyed Mohammad Shahrtash

“…Optimized for real-time operation, the simulation-based algorithm meets stringent computational speed requirements for online stability assessment. …”
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Concrete Creep Prediction Based on Improved Machine Learning and Game Theory: Modeling and Analysis Methods by Wenchao Li, Houmin Li, Cai Liu, Kai Min

“…Therefore, in this study, three machine learning (ML) models, a Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting Machine (XGBoost), are constructed, and the Hybrid Snake Optimization Algorithm (HSOA) is proposed, which can reduce the risk of the ML model falling into the local optimum while improving its prediction performance. …”
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Ship Typhoon Avoidance Route Planning Method Under Uncertain Typhoon Forecasts by Zhengwei He, Junhong Guo, Weihao Ma, Jinfeng Zhang

“…The experimental results demonstrate that under adverse conditions of uncertain typhoon forecasts, the proposed multi-objective typhoon avoidance route optimization model can effectively avoid high wind and wave areas of the typhoon while balancing and optimizing multiple navigation indicators. …”
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Analysis of Unmanned Surface Vehicles Heading KF-Based PI-(1+PI) Controller Using Improved Spider Wasp Optimizer by Xiaoyu Li, Xiangye Zeng, Jingyi Wang, Qi Li, Baoshuo Fan, Qi Zeng

“…A transfer function model of the USV heading system is established using voyage data, with ISWO optimizing its parameters, achieving a 5.67% reduction in mean squared error (MSE) compared to the original Spider Wasp Optimizer and outperforming classical algorithms like Arithmetic Optimization Algorithm (AOA), Crayfish Optimization Algorithm (COA), and Marine Predators Algorithm (MPA). …”
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Volumetric Patch-Based Super-Resolution Reconstruction of Hyperpolarized ¹³C Cardiac MRI by Sung-Han Lin, Junjie Ma, Jae Mo Park

“…This study is to develop and characterize a volumetric patch-based super-resolution reconstruction algorithm that enhances spatial resolution 13C cardiac MRI by utilizing structural information from 1H MRI. …”
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Rapid differentiation of patients with lung cancers from benign lung nodule based on dried serum Fourier-transform infrared spectroscopy combined with machine learning algorithms by Huanyu Li, Lixue Dai, Shaomei Guo, Hongluan Wang, Lei Lei, Jie Yu, Xiaoyun Li, Jun Wang

“…All algorithms successfully differentiated the three groups, with LDA achieving the highest accuracy (93.9 %). …”
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Performance Comparison of Multi-Objective Optimizers for Dynamic Balancing of Six-Bar Watt Linkages Using a Fully Cartesian Model by María T. Orvañanos-Guerrero, Claudia N. Sánchez, Luis Eduardo Robles-Jiménez, Sara Carolina Gómez-Delgado

“…A wide set of optimization methods is analyzed and compared, and among them, the S-Metric Selection Evolutionary Multi-objective Optimization Algorithm (SMS-EMOA) demonstrates superior performance. …”
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Evaluation of statistical and machine learning models using satellite data to estimate aboveground biomass: A study in Vietnam Tropical Forests by Thuy Phuong Nguyen, Phuc Khoa Nguyen, Huu Ngu Nguyen, Thanh Duc Tran, Gia Tung Pham, Thai Hung Le, Dinh Huy Le, Trung Hai Nguyen, Van Binh Nguyen

“…The study identified the optimal model for estimating forest aboveground biomass and minimizing the number of input variables while achieving satisfactory model performance. …”
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Satellite- and Cache-Assisted UAV: A Joint Cache Placement, Resource Allocation, and Trajectory Optimization for 6G Aerial Networks by Dinh-Hieu Tran, Symeon Chatzinotas, Bjorn Ottersten

“…In this context, we aim to maximize the minimum achievable throughput per ground user (GU) by jointly optimizing cache placement, the UAV’s resource allocation, and trajectory while cache capacity and flight time are limited. …”
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Research on Q-Learning-Based Cooperative Optimization Methodology for Dynamic Task Scheduling and Energy Consumption in Underwater Pan-Tilt Systems by Shan Tao, Lei Yang, Xiaobo Zhang, Shengya Zhao, Kun Liu, Xinran Tian, Hengxin Xu

“…Simulation results demonstrate that compared to fixed-duration observation schemes, the proposed optimization strategy achieves a 11.11% improvement in monitoring effectiveness while achieving 16.21% energy savings.…”
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Blockchain-based heterogeneous resource configuration scheme in computing power network by Qiang Gao, Chunyu Liu, Lei Wang, Yiqing Liu, Yueqiang Xu

“…Given the complexity of the original problem, we decompose it into two subproblems and solve each using the Lagrange multiplier iterative algorithm. To validate the effectiveness of our proposed solution, we compare it with several baseline approaches, including those based on Particle Swarm Optimization (PSO) and reinforcement learning methods such as Proximal Policy Optimization (PPO). …”
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Fluid flow characteristics estimation of a new integrated bifluid/airbased photovoltaic thermal system utilizing a hybrid optimization method by Ghassan A. Bilal, Abdullateef A. Jadallah, Omayma M. Abdulmajeed, Müslüm Arıcı

“…For the reliability of the proposed algorithm, the mean absolute percentage error was used for error estimation detection. …”
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STUDY ON CALCULATION METHOD OF STRESS SEPARATION BY OBLIQUE INCIDENCE TECHNIQUE by LIU XiaoMeng, DAI ShuGuang

“…Conventional method for solving nonlinear overdetermined equations is difficult,new particle swarm optimization algorithms are proposed for oblique incidence stress separation. …”
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Joint Optimization of Resource Allocation and Task Offloading Strategies in Multi-Cell Dynamic MEC Systems Using Multi-Agent DRL by Yuntao Hu, Ming Chen, Haowen Sun, Yinlu Wang, Yihan Cang

“…The energy consumption minimization is achieved by jointly optimizing the task offloading proportions, transmit power allocations, and computational resource distributions while ensuring the overall deadline constraints and the minimum processing size requirements in each scheduling cycle. …”
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Efficient resource allocation for D2D-enabled social IoT networks: A tripartite and time-scale optimization approach by Saurabh Chandra, Rajeev Arya, Maheshwari Prasad Singh

“…The problem is solved in two stages: a tripartite graph-based resource allocation stage and a time-scale optimization stage. The proposed approach prioritizes maintaining Quality of Service (QoS) and resource allocation to minimize power consumption while maximizing sum throughput. …”
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Optimizing UAV Location for Deployment in Cell-Free Massive MIMO Networks Using a Soft Actor-Critic Reinforcement Learning by Okello Kenneth, Elijah Mwangi, Dominic Bernard Onyango Konditi

“…The uncrewed aerial vehicles (UAVs) communication network has recently garnered significant attention and motivation in academic and industrial research due to its flexible mobility concept in providing dynamic coverage in hotspot or congested areas with frequent user demand. While UAVs offer reliable connectivity in such challenging scenarios, integrating them with Cell-Free Massive MIMO (CF-mMIMO) networks presents severe issues in optimal deployment and coverage efficiency. …”
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