Research on Unmanned Aerial Vehicle Path Planning for Carbon Emission Monitoring of Land-Side Heavy Vehicles in Ports by Xincong Wu, Zhanzhu Li, Xiaohua Cao

“…In the simulation experiment results, the proposed algorithm outperforms A*, ACO, and IEA algorithms in optimizing path length, reducing collision points to ensure path safety, and robustness. …”
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An efficient tuning method for networked control systems by Debashish Pal, Shiv Kumar Bhagat, G. Shanmugasundar, Ranjan Kumar Ghadai

“…To reach this goal, this study uses a meta-heuristic optimization method called the Whale Optimization Algorithm (WOA) along with a fuzzy-PID controller for a Networked Control System (NCS) plant. …”
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Planning and Evaluation of Water-Dropping Strategy for Fixed-Wing Fire Extinguisher Based on Multi-Resolution Modeling by Xiyu Wang, Yuanbo Xue, Yongliang Tian, Hu Liu, Zhiyong Cai

“…Case studies validate the system’s capability to forecast fire and smoke propagation, plan a water-dropping trajectory based on the fire line, optimize flight paths based on the trajectory, and simulate as well as evaluate the whole firefighting mission process. …”
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Hydrodynamic Performance and Motion Prediction Before Twin-Barge Float-Over Installation of Offshore Wind Turbines by Mengyang Zhao, Xiang Yuan Zheng, Sheng Zhang, Kehao Qian, Yucong Jiang, Yue Liu, Menglan Duan, Tianfeng Zhao, Ke Zhai

“…For this, this study employs the Whale Optimization Algorithm (WOA) to optimize the Long Short-Term Memory (LSTM) neural network. …”
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Simulation and Prediction of Springback in Sheet Metal Bending Process Based on Embedded Control System by Jinhan Xu, Jun Yan, Yan Huang, Dawei Ding

“…Subsequently, an enhanced WOA-BP (Whale Optimization Algorithm—Backpropagation) model, integrating Latin hypercube sampling and neural network techniques, is deployed to anticipate and counteract these springback errors. …”
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Hybrid beamforming for ISAC based on mmWave cell-free MIMO by DUO Lin, YANG Xin, REN Yong, XU Boyu

“…Two kinds of power constraints are considered in the study, and the improved orthogonal matching pursuit algorithm and the Riemann conjugate gradient algorithm are used for optimization. …”
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Observer-Based Sliding Mode Control for Vehicle Way-Point Tracking with Unknown Disturbances and Obstacles by Jiacheng Song, Mingjie Shen, Yanan Zhang

“…An observer compensation technique is utilized to monitor and mitigate disturbances, while sliding mode control, enhanced by a HyperSpiral algorithm, ensures accurate and stable tracking performance. …”
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A distributed energy-efficient opportunistic routing accompanied by timeslot allocation in wireless sensor networks by Man Gun Ri, Ye Song Han, Jin Pak

“…In our new algorithm, clustering and routing tree construction is performed while introducing the optimal relay transmission distance achieved by using opportunistic routing principle, and at the same time, interference-free wake up time is scheduled, which may optimize energy consumption and decrease the number of various control messages as possible to prolong the network lifetime. …”
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Adaptive Anomaly Detection in Network Flows With Low-Rank Tensor Decompositions and Deep Unrolling by Lukas Schynol, Marius Pesavento

“…To optimize the deep network weights for detection performance, we employ a homotopy optimization approach based on an efficient approximation of the area under the receiver operating characteristic curve. …”
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Adaptive Localization in Wireless Sensor Network through Bayesian Compressive Sensing by Zuoxin Xiahou, Xiaotong Zhang

“…Furthermore, we provide adaptive iteration BCS localization (AIBCSL) algorithm, which is based on BCS and will choose measurement sensors according to the environment adaptively with only an initial value, while other frameworks require prior knowledge such as target numbers to choose measurements. …”
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Enhancing grid frequency regulation in low inertia modern multi‐area power systems using cascaded non‐integer control approaches with BESS‐based virtual inertia by Tushar Kanti Roy, Amanullah Maung Than Oo

“…It should be noted that improper controller parameters can worsen frequency deviations and system stability. Hence, a whale optimization algorithm optimizes control parameters using the integral time absolute error based objective function. …”
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Prediction model of middle school student performance based on MBSO and MDBO-BP-Adaboost method by Rencheng Fang, Tao Zhou, Baohua Yu, Zhigang Li, Long Ma, Tao Luo, Yongcai Zhang, Xinqi Liu

“…Firstly, the model incorporates the good point set initialization, triangle wandering strategy and adaptive t-distribution strategy to obtain the Modified Dung Beetle Optimization Algorithm (MDBO), secondly, it uses MDBO to optimize the weights and thresholds of the BP neural network, and lastly, the optimized BP neural network is used as a weak learner for Adaboost. …”
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Degradation Type-Aware Image Restoration for Effective Object Detection in Adverse Weather by Xiaochen Huang, Xiaofeng Wang, Qizhi Teng, Xiaohai He, Honggang Chen

“…In the training phase, we jointly optimize the whole framework on a mixed weather dataset, including degraded images and clean images. …”
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The superior coupled model with innovative strategy for accurate imputation of missing hydrological monitoring data in water research-A case of groundwater level data by Xian-Qi Zhang, Zi-Yu Li, Xian-Liang Liu, Xiao-Yan Wu, Xin-Yong Xu, En-Kuan Li, Bo-Wen Wang, Su-Bo Han, Shao-Bo Liu

“…This paper proposes a strategy of “Decomposition-Classification-Feature Extraction-Imputation” and establishes a coupled model integrating Extreme-point Symmetric Mode Decomposition (ESMD), Permutation Entropy (PE), Singular Value Decomposition (SVD), and Whale Optimization Algorithm-Bidirectional Long Short-Term Memory (WOA-BiLSTM) for the hydrological monitoring data imputation. …”
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A Vision-Based Method for Detecting the Position of Stacked Goods in Automated Storage and Retrieval Systems by Chuanjun Chen, Junjie Liu, Haonan Yin, Biqing Huang

“…This paper proposes a novel machine vision-based detection algorithm that integrates a pallet surface object detection network (STEGNet) with a box edge detection algorithm. …”
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Efficient black-box attack with surrogate models and multiple universal adversarial perturbations by Tao Ma, Hong Zhao, Ling Tang, Mingsheng Xue, Jing Liu

“…By combining MUAPs with surrogate models, SMPack effectively overcomes the black-box constraints and improves the efficiency of generating adversarial examples. Additionally, we optimize this process using a Genetic Algorithm (GA), allowing for efficient search of the perturbation space while conserving query budget. …”
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Energy-Balanced Routing for Maximizing Network Lifetime in WirelessHART by Sheng Zhang, Ao Yan, Tianming Ma

“…Then node communication load, the residual energy, and the link transmission power are integrated as a link cost function that is accurately measured in this algorithm. A node chooses the optimal next hop by comparing the link cost function of all its neighbor nodes, which guarantees the energy balancing of the whole network. …”
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Automation and control of the vacuum block by Melikov Elchin, Maharramova Tamella, Safarova Aygun

“…In a wide range of changing conditions in input disturbing factors in quantity and quality, as well as insufficient operational quality information on the selected petroleum products, the proposed method and principles of development algorithm for controlling the process under study allows for prompt preliminary local regulation modes correction and the selection of new optimal modes for adaptive control as a whole. …”
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TA-RRT*: Adaptive Sampling-Based Path Planning Using Terrain Analysis by Taegeun Oh, Yun-Jae Won, Sungjin Lee

“…While existing RRT*-based algorithms perform node sampling and tree expansion in various ways to optimize path planning, they may still generate inefficient paths in complex terrain environments. …”
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Causal Unit Selection using Tractable Arithmetic Circuits by Haiying Huang, Adnan Darwiche

“…While early studies focused mainly on bounding a specific class of counterfactual objective functions using data, more recent work allows one to find optimal units exactly by reducing the causal objective to a classical objective on a meta-model, and then applying a variant of the classical Variable Elimination (VE) algorithm to the meta-model---assuming a fully specified causal model is available. …”
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