An Improved Interpolation Algorithm for Surface Meteorological Observations via Fuzzy Adaptive Optimisation Fusion by Xiaoya Jiang, Xiong Xiong, Wenlan Wang, Xiaoling Ye, Xin Chen, Yihu Wang, Fangjian Zhang

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Using 'sentinel' plants to improve early detection of invasive plant pathogens. by Francesca A Lovell-Read, Stephen Parnell, Nik J Cunniffe, Robin N Thompson

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Optimizing Photovoltaic Panel Performance: A Comparative Study of Meta-Heuristic Algorithms by M. Sundar Rajan

“…This paper addresses the parameter estimation of four distinct PV panel models—PV-RTC, PV-PWP 201, PV-STM6 40/36, and PV-STP6 120/36—using a range of meta-heuristic optimization algorithms. …”
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Joint beam hopping and coverage control optimization algorithm for multibeam satellite system by Guoliang XU, Feng TAN, Yongyi RAN, Feng CHEN

“…To improve the performance of multibeam satellite (MBS) systems, a deep reinforcement learning-based algorithm to jointly optimize the beam hopping and coverage control (BHCC) algorithm for MBS was proposed.Firstly, the resource allocation problem in MBS was transformed to a multi-objective optimization problem with the objective maximizing the system throughput and minimizing the packet loss rate of the MBS.Secondly, the MBS environment was characterized as a multi-dimensional matrix, and the objective problem was modelled as a Markov decision process considering stochastic communication requirements.Finally, the objective problem was solved by combining the powerful feature extraction and learning capabilities of deep reinforcement learning.In addition, a single-intelligence polling multiplexing mechanism was proposed to reduce the search space and convergence difficulty and accelerate the training of BHCC.Compared with the genetic algorithm, the simulation results show that BHCC improves the throughput of MBS and reduces the packet loss rate of the system, greedy algorithm, and random algorithm.Besides, BHCC performs better in different communication scenarios compared with a deep reinforcement learning algorithm, which do not consider the adaptive beam coverage.…”
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Swarm Intelligence Algorithms for Optimization Problems a Survey of Recent Advances and Applications by Mande Smita Samrat, M Srinivasulu, Anand Sruthi, K Anuradha, Tiwari Mohit, U Esakkiammal

“…For many years swarm intelligence (SI) algorithms have shown successful performance for complex optimization problems in many fields. …”
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Optimizing Imbalanced Data Classification: Under Sampling Algorithm Strategy with Classification Combination by Nauval Dwi Primadya, Adhitya Nugraha, Sahrul Yudha Fahrezi, Ardytha Luthfiarta

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An automated software algorithm for optimizing microwave ablation parameters for treatment of liver tumors by Sabrina Q. R. Liew, Nathaniel Rex, Celina Hsieh, Hyeonseon Kim, Scott A. Collins, Grayson L. Baird, DaeHee Kim, Aaron W. P. Maxwell

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Application of Improved Fault Detection and Robust Adaptive Algorithm in GNSS/INS Integrated Navigation by Qinghai Wang, Jianghua Liu, Jinguang Jiang, Xianrui Pang, Zhimin Ge

“…In vehicle GNSS/INS integrated navigation, robust and adaptive algorithms have become one of the key technologies for achieving a comprehensive PNT due to their ability to control the gross errors of the observation model and dynamic model. …”
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Fault detection algorithm for underground conveyor belt deviation based on improved RT-DETR by AN Longhui, WANG Manli, ZHANG Changsen

“…To address the issue, an underground conveyor belt deviation fault detection algorithm based on an improved real-time detection transformer (RT-DETR) was proposed. …”
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Research on control strategy of bidirectional DC-DC converter based on improved genetic algorithm by LI Li, CHEN Can, LI Can, GAO Feifan, CHEN Zhuaixia, LIU Yang, ZHOU Hongxi

“…The controller parameters were optimized using an improved genetic algorithm. Different control parameters have different control effects. …”
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A Review: The Application of Path Optimization Algorithms in Building Mechanical, Electrical, and Plumbing Pipe Design by Ruijun Deng, Xiaoliang Li, Yuhua Tian

“…This review systematically integrates recent advancements in path optimization algorithms for the automated layout of mechanical, electrical, and plumbing (MEP) systems within complex building environments. …”
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Optimized YOLOv8 framework for intelligent rockfall detection on mountain roads by Peng Peng, Langchao Gao, Jiachun Li, Hongzhen Zhang

“…To enable efficient detection, this study proposes a rockfall detection system based on embedded technology and an improved Yolov8 algorithm, termed Yolov8-GCB. The algorithm enhances detection performance through the following optimizations: (1) integrating a lightweight DeepLabv3+ road segmentation module at the input stage to generate mask images, which effectively exclude non-road regions from interference; (2) replacing Conv convolution units in the backbone network with Ghost convolution units, significantly reducing model parameters and computational cost while improving inference speed; (3) introducing the CPCA (Channel Priori Convolution Attention) mechanism to strengthen the feature extraction capability for targets with diverse shapes; and (4) incorporating skip connections and weighted fusion in the Neck feature extraction network to enhance multi-scale object detection. …”
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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

“…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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Investigating the Performance of Open-Vocabulary Classification Algorithms for Pathway and Surface Material Detection in Urban Environments by Kauê de Moraes Vestena, Silvana Phillipi Camboim, Maria Antonia Brovelli, Daniel Rodrigues dos Santos

“…Our approach uses large language models (LLMs) to improve the accuracy of classifying different pavement types. …”
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A Dendritic Neural Network-Based Model for Residential Electricity Consumption Prediction by Ting Jin, Rui Xu, Kunqi Su, Jinrui Gao

“…In this study, a dendritic neural network-based model (DNM), combined with the AdaMax optimization algorithm, is used to predict residential electricity consumption. …”
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Multi-Attribute Collaborative Optimization for Multimodal Transportation Based on User Preferences by Youpeng Lu, Gang Gao

“…Firstly, a four-dimensional optimization model is established with the objectives of minimizing transportation costs, transportation time, carbon emissions, and transportation risks. …”
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MILP Modeling and Optimization of Multi-Objective Three-Stage Flexible Job Shop Scheduling Problem With Assembly and AGV Transportation by Shiming Yang, Leilei Meng, Saif Ullah, Biao Zhang, Hongyan Sang, Peng Duan

“…To solve this problem, a mixed-integer linear programming model (MILP) is developed and the optimal Pareto front for small-scale instances are solved by using the <inline-formula> <tex-math notation="LaTeX">$\varepsilon $ </tex-math></inline-formula>-method. …”
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Daily Runoff Prediction Model Based on Multivariate Variational Mode Decomposition and Correlation Reconstruction by DING Jie, TU Peng-fei, FENG Yu, ZENG Huai-en

“…Finally, the integrated prediction combining fluctuation and random terms under condition 5 yielded R2 of 0.87 and 0.93 for the overall prediction at Ankang and Baihe stations, respectively, demonstrating excellent model performance. [Conclusions](1) The MVMD decomposition method can control the number of decomposition layers, ensuring complete signal feature extraction without overfitting while improving processing speed.(2) Pearson correlation coefficient method enhances prediction accuracy through decomposed data classification.(3) The MEA-BP can improve signal-to-noise ratio, adapt to complex environments, enhance learning efficiency and generalization ability, and reduce computational complexity.(4) The GWO-ELM algorithm integrates grey wolf optimizer with extreme learning machine, providing a fast and adaptive solution for time-series prediction with reduced overfitting and improved efficiency.(5) The overall combined model can efficiently and stably process large amount of data while ensuring high accuracy.…”
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Stability Analysis and Construction Parameter Optimization of Tunnels in the Fractured Zone of Faults by Banma Huang, Haibo Chen, Chenglong Duan, Wenhu Li

“…In order to improve the construction method of highway tunnel fault, improve the excavation level, improve the construction efficiency, reduce the project cost, and shorten the construction period, so as to find a specific road, this paper puts forward the research method of tunnel stability analysis and construction parameter optimization in the fault fracture zone. …”
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A composite photovoltaic power prediction optimization model based on nonlinear meteorological factors analysis and hybrid deep learning framework by Mengji Yang, Haiqing Zhang, Xi Yu, Aicha Sekhari Seklouli, Abdelaziz Bouras, Yacine Ouzrout

“…Firstly, to reduce the redundancy of the input for the prediction model and the computational time complexity, while enhancing the robustness and stability of the prediction model, nonlinear correlation search algorithm based on time window extending and time window shrinking strategies have been proposed. …”
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