A Hybrid-A* Path Planning Method Based on Equal Step Hierarchical Expansion by CHEN Xinpeng, XU Biao, HU Manjiang, QIN Zhaobo, BIAN Yougang

“…Then the numerical optimization method is adopted to further optimize of the path smoothness. …”
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Virtual Network Resource Allocation Algorithm Based on Load Balance in Carrier-SDN by Li Wang, Jihong Zhao, Hua Qu, Ya Guo

“…Resource allocation algorithm for virtual networks in carrier-SDN based on load balance was proposed.Firstly,multiple-layered model of carrier-SDN was constructed.Secondly,the binaryzation of particle swarm optimization algorithm with the characteristic of virtual network embedding（VNE）algorithm was realized.Finally,load balance was set as optimization object,then the solution of VNE problem was got.The simulation results demonstrate that the proposed algorithm has superior performance in terms of load balance,acceptance ratio and average compared with existing methods.…”
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Path Planning of Library Management Robot Based on PDO-ACO Algorithm by Na Lin

“…A path planning method based on Particle Differential Optimization-Ant Colony Optimization (PDO-ACO) algorithm for library management robots is proposed in the study, aiming to solve the problem of low efficiency of current path planning methods in complex environments. …”
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A novel meta-heuristic algorithm based on candidate cooperation and competition by Yue Cong, Bingnan Yang, Jie Wei

“…To address these limitations, we propose a novel metaheuristic algorithm called the Candidates Cooperative Competitive Algorithm (CCCA), which is inspired by distinctive human social behaviors and designed for continuous optimization problems. CCCA consists of two main stages: self-study and mutual influence among candidates. …”
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Questions of improvement of financing of activity of businessmen and enterprise structures by L. A. Akhmetov, D. A. Zuravlev, E. I. Akhmetova

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Reliable estimation via hybrid gradient boosting machine for mud loss volume in drilling operations by Xiaozhi Lu, Farag M. A. Altalbawy, Tarak Vora, R. Manjunatha, Debasish Shit, Shirin Shomurotova, Akshay Kumar, Atreyi Pramanik, Ajay Sharma, Raed H. C. Alfilh, Samim Sherzod, Mohammad Mahtab Alam

“…Abstract Mud loss during drilling operations poses a significant problem in the oil and gas industry due to its contributions to increased costs and operational risks. …”
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Research on improved RRT path planning algorithm based on multi-strategy fusion by Shangjing Lei, Tengyan Li, Xiaochan Gao, Pengjun Xue, Guozhu Song

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Research on the Reconstruction of the Temperature Field in Two-Dimensional Steady-State Thermal Conductivity Based on Physics-Informed Neural Networks by Yufan Pan, Ke Zhang, Ji Zhang, Ning Mei

“…By optimizing the distribution of sample points without increasing their quantity, the average relative error is further reduced by approximately 1%, thereby enhancing inversion accuracy. …”
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Research on LSTM-PPO Obstacle Avoidance Algorithm and Training Environment for Unmanned Surface Vehicles by Wangbin Luo, Xiang Wang, Fang Han, Zhiguo Zhou, Junyu Cai, Lin Zeng, Hong Chen, Jiawei Chen, Xuehua Zhou

“…In response to the above problems, this paper proposes a long and short memory network-proximal strategy optimization (LSTM-PPO) intelligent obstacle avoidance algorithm for non-particle models in non-ideal environments, and designs a corresponding deep reinforcement learning training environment. …”
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Encrypted traffic classification method based on convolutional neural network by Rongna XIE, Zhuhong MA, Zongyu LI, Ye TIAN

“…Aiming at the problems of low accuracy, weak generality, and easy privacy violation of traditional encrypted network traffic classification methods, an encrypted traffic classification method based on convolutional neural network was proposed, which avoided relying on original traffic data and prevented overfitting of specific byte structure of the application.According to the data packet size and arrival time information of network traffic, a method to convert the original traffic into a two-dimensional picture was designed.Each cell in the histogram represented the number of packets with corresponding size that arrive at the corresponding time interval, avoiding reliance on packet payloads and privacy violations.The LeNet-5 convolutional neural network model was optimized to improve the classification accuracy.The inception module was embedded for multi-dimensional feature extraction and feature fusion.And the 1*1 convolution was used to control the feature dimension of the output.Besides, the average pooling layer and the convolutional layer were used to replace the fully connected layer to increase the calculation speed and avoid overfitting.The sliding window method was used in the object detection task, and each network unidirectional flow was divided into equal-sized blocks, ensuring that the blocks in the training set and the blocks in the test set in a single session do not overlap and expanding the dataset samples.The classification experiment results on the ISCX dataset show that for the application traffic classification task, the average accuracy rate reaches more than 95%.The comparative experimental results show that the traditional classification method has a significant decrease in accuracy or even fails when the types of training set and test set are different.However, the accuracy rate of the proposed method still reaches 89.2%, which proves that the method is universally suitable for encrypted traffic and non-encrypted traffic.All experiments are based on imbalanced datasets, and the experimental results may be further improved if balanced processing is performed.…”
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Improving the navigation optimization of hospital logistics robots under complex lighting changes by using improved ORB-SLAM3 and deep learning visual SLAM algorithm by Feng Xiao, Youhai Zhang, Jie Fang, Xing Guo, Rubing Huang

“…Abstract Under complex lighting conditions, hospital logistics robots are facing serious challenges in positioning and navigation.The traditional ORB (Oriented FAST and rotated BRIEF) algorithm often has problems such as unstable feature point extraction, poor positioning accuracy, and long navigation path planning time in environments with large lighting changes, which greatly affects the robot's navigation efficiency and accuracy. …”
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PDAA: An End-to-End Polygon Dynamic Adjustment Algorithm for Building Footprint Extraction by Longjie Luo, Jiangchen Cai, Bin Feng, Liufeng Tao

“…It is at least 2% higher than existing methods in terms of average precision (AP), and the generated polygonal contours are closer to the real building geometry. …”
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Machine learning techniques and multi-objective programming to select the best suppliers and determine the orders by Asma ul Husna, Saman Hassanzadeh Amin, Ahmad Ghasempoor

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Uma heurística híbrida para minimizar custos com antecipação e atraso do sequenciamento da produção em uma máquina A hybrid heuristic algorithm for job scheduling problem on a sing... by Puca Huachi Vaz Penna, Marcone Jamilson Freitas Souza, Frederico Augusto de Cezar Almeida Gonçalves, Luiz Satoru Ochi

“…In order to solve this problem, a three-phase heuristic approach, the so-called GTSPR, was developed. …”
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Deep Reinforcement Learning-Based Secrecy Rate Optimization for Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surface-Assisted Unmanned Aerial Vehicle-Integ... by Jianwei Wang, Shuo Chen

“…As the considered problem involves coupled variables and is non-convex, it is difficult to solve using traditional optimization methods. …”
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Dynamic content-cached satellite selection and routing for power minimization in LEO satellite networks by Jeongmin Seo, Dongho Ham, Jeongho Kwak

“…To solve this long-term time-averaged problem, we leverage Lyapunov optimization framework to transform the original problem into a series of slot-by-slot problems. …”
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LEO computing satellite constellation design for heterogeneous QoS requirements by PENG Yuming, SUN Yijing, DI Boya

“…By establishing a satellite-to-terrestrial connection model, the average computational resources and backhaul capacity available to ground users were analyzed and a multi-objective optimization problem for designing ultra-dense LEO constellations was modelled, aiming to minimize the total number of satellites while meeting the heterogeneous quality of service (QoS) requirements for user task offloading. …”
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An Adaptive Harmony Search Part-of-Speech tagger for Square Hmong Corpus by Di-Wen Kang, Shao-Qiang Ye, Sharifah Zarith Rahmah Syed Ahmad, Li-Ping Mo, Feng Qin, Pan Zhou

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Model for evaluation of technical and economic indicators of offshore wind farms by D. Y. Davydov, S. G. Obukhov

“…The solution to this problem is possible by increasing efficiency while reducing costs as much as possible, which requires optimal design of offshore wind farms.GOAL. …”
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Machine Learning Model for Hepatitis C Diagnosis Customized to Each Patient by Leran Chen, Ping Ji, Yongsheng Ma

“…A general-purpose machine learning algorithm depends on a large amount of data and requires abundant computing power support, relies on the average level to describe the model performance, and cannot achieve optimal results on a specific problem. …”
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