Voronoi-GRU-Based Multi-Robot Collaborative Exploration in Unknown Environments by Yang Lei, Jian Hou, Peixin Ma, Mingze Ma

“…In the lower layer, navigation planning is achieved using A* and Timed Elastic Band (TEB) algorithms, while an improved Cartographer algorithm is used to construct a joint map for the multi-robot system. …”
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Detection of Tomato Leaf Pesticide Residues Based on Fluorescence Spectrum and Hyper-Spectrum by Jiayu Gao, Xuhui Yang, Simo Liu, Yufeng Liu, Xiaofeng Ning

“…In order to improve the operating rate of discrimination, a continuous projection algorithm (SPA) was used to extract the characteristic wavelengths of the fluorescence spectra and hyperspectral data of pesticide residues, and algorithms such as the least-squares support vector machine (LSSVM) algorithm and least partial squares regression (PLSR) were used to build a quantitative model, while algorithms such as the convolutional neural network (BPNN) algorithm and decision tree algorithm (CART) were used to build a qualitative model. …”
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Adaptive Variational Modal Decomposition–Dual Attention Mechanism Parallel Residual Network: A Tool Lifetime Prediction Method Based on Adaptive Noise Reduction by Jing Kang, Taiyong Wang, Yi Li, Ye Wei, Yaomin Zhang, Ying Tian

“…The method first adapts the parameters of the variational modal noise reduction algorithm using an improved sparrow optimization algorithm, and then reconstructs the original vibration signal with noise reduction. …”
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A novel method for power transformer fault diagnosis considering imbalanced data samples by Jun Chen, Yong Wang, Lingming Kong, Yilong Chen, Mianzhi Chen, Qian Cai, Gehao Sheng

“…Hyperparameter tuning is achieved through the Bayesian optimization algorithm to identify the model parameter set that maximizes test set accuracy.ResultsAnalysis of the transformer fault case library reveals that the model proposed in this paper reduces diagnostic time by nearly half compared to traditional machine learning diagnosis models. …”
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Prediction of COD Degradation in Fenton Oxidation Treatment of Kitchen Anaerobic Wastewater Based on IPSO-BP Neural Network by Tianpeng Zhang, Pengfei Ji, Dayong Tian, Rui Xu

“…The Fenton oxidation process is used to treat kitchen anaerobic wastewater, and the effects of H2O2 dosage, Fe2+ dosage, reaction time and pH value on chemical oxygen demand (COD) degradation efficiency are explored. The improved particle swarm optimization (IPSO) algorithm is used to optimize the back propagation (BP) neural network, and a prediction model of COD degradation is established based on IPSO-BP neural network. …”
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Research review on intelligent object detection technology for coal mines based on deep learning by Fan ZHANG, Jiarong ZHANG, Haixing CHENG

“…How to improve the accuracy, model adaptability, and computational efficiency of mine object detection is an urgent research topic in the field of mining artificial intelligence. …”
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Review: the application of deep reinforcement learning to quantitative trading in financial market by XU Bo, HE Yijun, WEN Jiancheng, LI Xiangxia

“…It is believed that with the continuous optimization of algorithms and the improvement of computing power, DRL will play a more important role in the field of quantitative trading in financial market, providing more accurate and reliable support for investment decisions.…”
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A Multiobjective Incremental Control Allocation Strategy for Tailless Aircraft by Maoyu Su, Jianbo Hu, Yingyang Wang, Zihou He, Jiping Cong, Linxiao Han

“…In this way, the dependence on subjective experience is minimized based on the theory of Pareto optimal. Meanwhile, the huge computational burden that the intelligent optimization algorithm brings can also be avoided. …”
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Complex Large-Deformation Multimodality Image Registration Network for Image-Guided Radiotherapy of Cervical Cancer by Ping Jiang, Sijia Wu, Wenjian Qin, Yaoqin Xie

“…The DSC index of the MTEF algorithm is 5.64% higher than that of the TransMorph algorithm. …”
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A Three-Dimensional Phenotype Extraction Method Based on Point Cloud Segmentation for All-Period Cotton Multiple Organs by Pengyu Chu, Bo Han, Qiang Guo, Yiping Wan, Jingjing Zhang

“…In addition, to address the challenge of accurately segmenting overlapping regions between different cotton organs, we introduced an optimization strategy that combines point distance mapping with curvature-based normal vectors and developed an improved region-growing algorithm to achieve fine segmentation of multiple cotton organs, including leaves, stems, and flower buds. …”
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Selection of third-party logistics provider based on extended multimoora technique under double hierarchy linguistic single-valued neutrosophic set by Abbas Qadir, Marya Nawaz, Muhammad Ali Khan

“…The demand for third-party logistics (3PL) providers becomes an increasingly important issue for corporations seeking improved customer service and cost reduction. Currently, there is no way to select the appropriate method for selecting 3PL. …”
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Wireless-powered cooperative energy aware anycast routing in wireless sensor networks by Fazle Hadi, Sheeraz Ahmed, Abid Ali Minhas, Abdulaziz Al Mazyad, Najam ul Islam, Imran Ahmed, Nadeem Javaid

“…Results further reveal that our proposed algorithm has improved energy consumption in comparison to the non-cooperative energy aware anycast scheme and the cooperation-based robust cooperative routing protocol scheme. …”
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IoT intrusion detection method for unbalanced samples by ANTONG P, Wen CHEN, Lifa WU

“…In recent years, network traffic increases exponentially with the iteration of devices, while more and more attacks are launched against various applications.It is significant to identify and classify attacks at the traffic level.At the same time, with the explosion of Internet of Things (IoT) devices in recent years, attacks on IoT devices are also increasing, causing more and more damages.IoT intrusion detection is able to distinguish attack traffic from such a large volume of traffic, secure IoT devices at the traffic level, and stop the attack activity.In view of low detection accuracy of various attacks and sample imbalance at present, a random forest based intrusion detection method (Resample-RF) was proposed, which consisted of three specific methods: optimal sample selection algorithm, feature merging algorithm based on information entropy, and multi-classification greedy transformation algorithm.Aiming at the problem of unbalanced samples in the IoT environment, an optimal sample selection algorithm was proposed to increase the weight of small samples.Aiming at the low efficiency problem of random forest feature splitting, a feature merging method based on information entropy was proposed to improve the running efficiency.Aiming at the low accuracy problem of random forest multi-classification, a multi-classification greedy transformation method was proposed to further improve the accuracy.The method was evaluated on two public datasets.F1 reaches 0.99 on IoT-23 dataset and 1.0 on Kaggle dataset, both of which have good performance.The experimental results show that the proposed model can effectively identify the attack traffic from the massive traffic, better prevent the attack of hackers on the application, protect the IoT devices, and thus protect the related users.…”
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Design of 3D Environment Combining Digital Image Processing Technology and Convolutional Neural Network by Xiaofei Lu, Shouwang Li

“…To enhance 3D reconstruction accuracy, this study proposes a digital image processing technology that combines binocular camera calibration, stereo correction, and a convolutional neural network (CNN) algorithm for optimization and improvement. By employing the refined stereo-matching algorithm, a 3D reconstruction model was developed to augment 3D environment design and reconstruction accuracy while optimizing the 3D reconstruction effect. …”
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A predictive framework using advanced machine learning approaches for measuring and analyzing the impact of synthetic agrochemicals on human health by Sahezpreet Singh, Puneet Kaur, Inderdeep Kaur, Gurpreet Singh, Satinder Kaur, Parminder Kaur

“…Furthermore, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) used for model optimization. …”
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Automatic collaborative water surface coverage and cleaning strategy of UAV and USVs by Tianping Deng, Xiaohui Xu, Zeyan Ding, Xiao Xiao, Ming Zhu, Kai Peng

“…The simulation results show that the proposed algorithms have higher generality and flexibility while effectively improving computational efficiency and reducing actual cleaning costs compared with other schemes.…”
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Multi-Intersection Signal Control Based on Asynchronous Reinforcement Learning by Jixiang Wang, Siqi Chen, Jing Wei, Boao Wang, Haiyang Yu

“…Simulation experiments show that the asynchronous decision-making method proposed in this paper not only improves the model convergence speed by at least 19% compared to the multiagent deep RL (MADRL) algorithm used for synchronous decision-making, but also improves the model by at least 10.5% in vehicle driving speed, maximum queue length, and average queue length within the decodable range (the traffic density is between 100 vehicles/km and 400 vehicles/km). …”
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Brown Rice Germ Integrity Identification Based on Deep Learning Network by Shuofeng Li, Bing Li, Jin Li, Bin Liu

“…This paper improves the brown rice (BR) segmentation algorithm based on background skeleton. …”
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Learning atomic forces from uncertainty-calibrated adversarial attacks by Henrique Musseli Cezar, Tilmann Bodenstein, Henrik Andersen Sveinsson, Morten Ledum, Simen Reine, Sigbjørn Løland Bore

“…Abstract Adversarial approaches, which intentionally challenge machine learning models by generating difficult examples, are increasingly being adopted to improve machine learning interatomic potentials (MLIPs). …”
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UAV target tracking method based on global feature interaction and anchor-frame-free perceptual feature modulation. by Yuanhong Dan, Jinyan Li, Yu Jin, Yong Ji, Zhihao Wang, Dong Cheng

“…In this study, in order to refine the feature representation and reduce the computational effort to improve the efficiency of the tracker, we perform feature fusion in deep inter-correlation operations and introduce a global attention mechanism to enhance the model's field of view range and feature refinement capability to improve the tracking performance for small targets. …”
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