PRO-BiGRU: Performance Evaluation Index System for Hardware and Software Resource Sharing Based on Cloud Computing by Nan Wang

“…The novelty of this research lies in the combination of the PRO algorithm with the BiGRU network, which effectively captures complex data features and enhances the model's reliability and robustness in performance assessment tasks. …”
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Unmanned Surface Vessel Cluster Path Planning Based on Deep Reinforcement Learning by Manjiang YU, Jiawei HE, Bowen XING

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Lidar-Binocular Camera-Integrated Navigation System for Underground Parking by Wei He, Rui Li, Wenjie Liao

“…The obtained Lidar data from the simulation experiment are preprocessed, and the matching results of the inertial navigation system (INS) under the normal distributions transform (NDT) algorithm and the iterative closest point (ICP) algorithm are compared. …”
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Nonlinear Decoupling Study of Six-Axis Acceleration Sensor Based on Improved BP Neural Network by Jialin Zhang, Chunzhan Yu, Chengxin Du, Zhe Hao, Zhibo Sun

“…Aiming at the problem of nonlinear coupling error in the measurement of parallel six-axis accelerometers, this study improves the back propagation (BP) neural network and proposes an improved BP neural network decoupling model that introduces the gradient descent with momentum and the Levenberg–Marquardt (LM) algorithm. By introducing the momentum factor in the model updating stage, the LM algorithm is used in the local learning stage to improve the convergence speed and shock resistance of the network, and to enhance the accuracy of the algorithm. …”
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Learning Condition-Invariant Scene Representations for Place Recognition across the Seasons Using Auto-Encoder and ICA by Tariqul Islam, Sheikh Rabiul Islam, Mahbubur Rahman

“…Especially, when the robot moves through a changing environment, ICA provided more accurate outcomes than the other algorithm (baseline algorithm). On the other hand, the auto-encoder can distinguish between two features of scene variant condition and invariant condition. …”
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WEIGHTED ADDITIVE MODEL AND CHANCE CONSTRAINED TECHNIQUE FOR SOLVING NONSYMMETRICAL STOCHASTIC FUZZY MULTIOBJECTIVE LINEAR PROGRAM by Grandianus Seda Mada, Nugraha K.F. Dethan, Fried Markus Allung Blegur, Adriano Dos Santos

“…An example of numerical computations has been provided at the end of the discussion in order to illustrate how the algorithm works. The resulted Model and algorithm are expected to help companies in the decision making process.…”
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Preliminary Development of a Database for Detecting Active Mounting Behaviors Using Signals Acquired from IoT Collars in Free-Grazing Cattle by Miguel Guarda-Vera, Carlos Muñoz-Poblete

“…The algorithm achieves an average F1 Score of 88.6% for the World Frame of reference, showing a significant improvement compared to the algorithm trained with Body Frame (78.6%) when both are trained with the same 112 features. …”
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SDN Controller Selection and Secure Resource Allocation by Sasibhushana Rao Pappu, Kalyana Chakravarthy Chilukuri

“…However, in energy-effective task scheduling and security, the centralized control architecture of SDN brings challenges. This research proposes a new approach for blockchain-based secure resource allocation with controller selection in SDN, utilizing the Entropy Oppositional Based Learning-Interpolation Blue Monkey Optimization Algorithm (EOBL-IBMOA). …”
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Curvature-Based Machine Vision Method for Measuring the Dimension of Ball Screws by Yijia Chen, Yao Yao, Hao Yang, Yue Wu, Kunpeng Zhang, Xiaoming Pan

“…However, most of the current approaches are ineligible for rapid ball screw in-situ inspections due to the installation condition requirement of the production line. In this research, a machine vision method is presented to achieve highly accurate measurements of crucial parameters (the center distance and raceway arcs) in ball screws using a curvature edge detection algorithm. …”
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Optimization of the Operation Plan of Airport Express Train with Consideration of Train Departure Time Window by Jin He, Yinzhen Li, Yuhong Chao, Ruhu Gao

“…Neighborhood solution strategies include the increase or haut of train operations and the adjustment of the number of stops, which refines the solution space and boosts the process efficiency of the heuristic algorithm. Additionally, the model and algorithm proposed in this paper are practiced during the peak hour of Nanjing Metro Line S1 for empirical validation. …”
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A Context-Driven Worker Selection Framework for Crowd-Sensing by Jiangtao Wang, Yasha Wang, Sumi Helal, Daqing Zhang

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An Assistant Decision-making System for Black-Start Path Generation and System Restoration by Yinxing XIANG, Xiaojian TANG, Jikeng LIN

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A Smart Device Enabled System for Autonomous Fall Detection and Alert by Jian He, Chen Hu, Xiaoyi Wang

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VELOCITY GRADIENT OF THE FLOOR EXERCISE by Marina Petrova, Bonka Dimitrova

“…The basic motor habits differ only as regards the specificity of the particular apparatus. The aim of the research is to establish the role of the velocity gradient for the learning algorithm in a multi-annual aspect and on floor exercise. …”
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Complex Multisnapshot Sparse Bayesian Learning for Offgrid DOA Estimation by Qinghua Liu, Yuanxin He, Kai Ding, Quanmin Xie

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A novel machine learning model for perimeter intrusion detection using intrusion image dataset. by Shahneela Pitafi, Toni Anwar, I Dewa Made Widia, Zubair Sharif, Boonsit Yimwadsana

“…To overcome these limitations, this research enhances the traditional DBSCAN algorithm. …”
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Unified Resource Allocation and Mobility Management Technique Using Particle Swarm Optimization for VLC Networks by Muhammet Selim Demir, Sadiq M. Sait, Murat Uysal

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Application of Data Mining for Tuberculosis Disease Classification Using K-Nearest Neighbor by Delima Sitanggang, lamria Simangunsong, Geertruida Frederika Sundah, Rani Hutahaean, Indren Indren

“…This type of research is quantitative. The literature study used is the documentation study. …”
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Travel Time Prediction of Urban Agglomeration Significance Channel: A Case Study on the Cross-Hangzhou Bay Channel by Wang Yu, Hu Xiaowei, Cui Shu, Rao Zonghao

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Prediction of Shear Strength of Steel Fiber-Reinforced Concrete Beams with Stirrups Using Hybrid Machine Learning and Deep Learning Models by B. R. Kavya, A. S. Shrikanth, K. S. Sreekeshava

“…The shear behavior of beams cast with steel fiber reinforced concrete and provided with stirrups is a complex phenomenon that depends on various factors. In the present research effort, a hybrid support vector regression model combined with a particle swarm optimization algorithm is provided, to explore the relationship between the material and dimensional characteristics of a concrete beam and its shear strength. …”
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