Multi-source information transmission and classification algorithm for equipment based on compressed sensing by Xiaohu ZHAO, Gang WANG, Boming SONG, Jiacheng YU

“…Aiming at the characteristics of various types of equipment in coal preparation plant and the dispersion of monitoring points,a multi-source information wireless transmission and classification algorithm for equipment based on compressed sensing was proposed.By constructing a multi-hop information transmission model,the information transmission problem was transformed into the compressed sensing problem of multi-path measurement signals,thereby the measurement matrix acquisition was transformed into the routing problem of the multi-hop information transmission model.Aiming at the large coherence of the obtained measurement matrix and affecting the signal reconstruction effect,the idea of random routing was introduced into the routing construction,and a random dynamic self-organizing routing algorithm was proposed.In order to solve the problem that the time domain features of the reconstructed signal were difficult to accurately classify the fault type,a new time domain feature,the total variation (TV) of the vibration signal,was introduced for the reconstructed signal,and the compensation distance estimation algorithm was adopted to verify the superiority of the introduction of indicators.The analysis of the measured data of the coal preparation plant shows that the proposed multi-source information transmission and classification algorithm can effectively improve the fault recognition accuracy under the condition of improving the real-time transmission efficiency of the monitoring data.…”
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Multi-source information transmission and classification algorithm for equipment based on compressed sensing by Xiaohu ZHAO, Gang WANG, Boming SONG, Jiacheng YU

“…Aiming at the characteristics of various types of equipment in coal preparation plant and the dispersion of monitoring points,a multi-source information wireless transmission and classification algorithm for equipment based on compressed sensing was proposed.By constructing a multi-hop information transmission model,the information transmission problem was transformed into the compressed sensing problem of multi-path measurement signals,thereby the measurement matrix acquisition was transformed into the routing problem of the multi-hop information transmission model.Aiming at the large coherence of the obtained measurement matrix and affecting the signal reconstruction effect,the idea of random routing was introduced into the routing construction,and a random dynamic self-organizing routing algorithm was proposed.In order to solve the problem that the time domain features of the reconstructed signal were difficult to accurately classify the fault type,a new time domain feature,the total variation (TV) of the vibration signal,was introduced for the reconstructed signal,and the compensation distance estimation algorithm was adopted to verify the superiority of the introduction of indicators.The analysis of the measured data of the coal preparation plant shows that the proposed multi-source information transmission and classification algorithm can effectively improve the fault recognition accuracy under the condition of improving the real-time transmission efficiency of the monitoring data.…”
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Fog Visibility Detection of Highway Based on Improved Dark Channel Prior Algorithm by Huiqi Zhang, Yong Liu, Chenxi Wu

“…This paper presents an algorithm for detecting fog visibility in expressway based on improved dark channel prior method, which transforms the difficult problem of detecting visibility through image processing into the problem of calculating atmospheric extinction coefficient. …”
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LC oscillator frequency prediction using machine learning linear regression algorithm by Mandar Jatkar, Vasudeva G, Tripti R. Kulkarni, Roopa R. Kulkarni, Aneesh Pandurangi

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A Variational Neural Network Based on Algorithm Unfolding for Image Blind Deblurring by Shaoqing Gong, Yeran Wang, Guangyu Yang, Weibo Wei, Junli Zhao, Zhenkuan Pan

“…For blur kernel estimation, we introduce an <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>L</mi></mrow><mrow><mn>0</mn></mrow></msub></mrow></semantics></math></inline-formula> regularizer to constrain the gradient information and use the fast fourier transform (FFT) to solve the iterative results, thereby improving accuracy. …”
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An innovative complex-valued encoding black-winged kite algorithm for global optimization by Chengtao Du, Jinzhong Zhang, Jie Fang

“…Abstract The black-winged kite algorithm (BKA) constructed on the black-winged kites’ migratory and predatory instincts is a revolutionary swarm intelligence method that integrates the Leader tactic with the Cauchy variation procedure to retrieve the expansive appropriate convergence solution. …”
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Phenology-Aware Machine Learning Framework for Chlorophyll Estimation in Cotton Using Hyperspectral Reflectance by Chunbo Jiang, Yi Cheng, Yongfu Li, Lei Peng, Gangshang Dong, Ning Lai, Qinglong Geng

“…Five regression approaches were evaluated, including univariate and multivariate linear models, along with three machine learning algorithms: Random Forest, K-Nearest Neighbor, and Support Vector Regression. …”
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Wearable Spine Tracker vs. Video-Based Pose Estimation for Human Activity Recognition by Jonas Walkling, Luca Sander, Arwed Masch, Thomas M. Deserno

“…We tested a comprehensive selection of state-of-the-art time series classification algorithms. Both systems achieved high classification performance, with average <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>F</mi><mn>1</mn></msub></semantics></math></inline-formula> scores of 0.90 for both datasets using a 1-second time window and the random dilated shapelet transform (RDST) and QUANT classifier for FlexTail and camera data, respectively. …”
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Oil-cooled transformer hot spot temperature reduction using windings height optimum design by Mohammad Ali Taghikhani

“…Thus, electrical and physical optimization of transformers are important. On the other hand, estimation of the temperature rise and reduction of the hot spot temperature (HST) in a transformer increase the loading capability and life span of the transformer. …”
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Edge_MVSFormer: Edge-Aware Multi-View Stereo Plant Reconstruction Based on Transformer Networks by Yang Cheng, Zhen Liu, Gongpu Lan, Jingjiang Xu, Ren Chen, Yanping Huang

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DTW-based multi-wavelet data compression algorithm for wireless sensor networks by Si-wang ZHOU, Lan LI

“…A data compression algorithm for wireless sensor networks based on DTW and multi-wavelet transform is pro-posed. …”
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A New Algorithm for Solving Terminal Value Problems of q-Difference Equations by Yong-Hong Fan, Lin-Lin Wang

“…We propose a new algorithm for solving the terminal value problems on a q-difference equations. …”
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Three-Axes Mems Calibration Using Kalman Filter and Delaunay Triangulation Algorithm by Anwer Sabah Ahmed, Qais Al-Gayem

“…Accelerometer error parameters were estimated using the transformed unscented Kalman filter (TUKF) with triangulation algorithm is suggested for calibrating inertial measurement unit (MPU6050) three-axes accelerometer. …”
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Improved Empirical Mode Decomposition Algorithm of Processing Complex Signal for IoT Application by Xianzhao Yang, Gengguo Cheng, Huikang Liu

“…Hilbert-Huang transform is widely used in signal analysis. However, due to its inadequacy in estimating both the maximum and the minimum values of the signals at both ends of the border, traditional HHT is easy to produce boundary error in empirical mode decomposition (EMD) process. …”
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Deep Learning Algorithm for Optimized Sensor Data Fusion in Fault Diagnosis and Tolerance by M. Elhoseny, Deepak Dasaratha Rao, Bala Dhandayuthapani Veerasamy, Noha Alduaiji, J. Shreyas, Piyush Kumar Shukla

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Development and investigation of parallel model of bee colony algorithms for cryptanalysis problem solving by Yury O Chernyshev, Alexander S Sergeev, Alexander N Ryazanov, Evgeny O. Dubrov

“…Research Results . Theoretical estimates of time complexity of the bee colony algorithm are given as the key data. …”
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Deep learning for compressed sensing based sparse channel estimation in FDD massive MIMO systems by Yuan HUANG, Yigang HE, Yuting WU, Tongtong CHENG, Yongbo SUI, Shuguang NING

“…For FDD massive multi-input multi-output (MIMO) downlink system, a novel deep learning method for compressed sensing based sparse channel estimation was proposed, which was called convolutional compressed sensing network (ConCSNet).In the ConCSNet, the convolutional neural network was utilized to solve the inverse transformation process from measurement vector y to signal h and solve the underdetermined optimization problem through data-driven method without sparsity.Simulation results show that the algorithm can recover the channel state information in massive MIMO Systems with unknown sparsity more quickly and accurately.…”
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Enhanced Fault Localization for Active Distribution Networks via Robust Three-Phase State Estimation by Guorun He, Dong Liang, Yuezi Zhao, Xiaoxue Wang

“…Then, a robust fault SE model is built using the quadratic-constant-based generalized maximum likelihood estimation, solved through the iteratively reweighted least squares algorithm that postpones phasor measurement weight updates until after initial iterations to prevent residual contamination. …”
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A Non-Contact Privacy Protection Bed Angle Estimation Method Based on LiDAR by Yezhao Ju, Yuanji Li, Haiyang Zhang, Le Xin, Changming Zhao, Ziyi Xu

“…Our methodology integrates advanced techniques, including coordinate system transformation, plane fitting, and a deep learning framework combining YOLO-X with an enhanced A2J algorithm. …”
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Formation of a dynamic knowledge base of fuzzy inference systems for estimating changing in time objects by A. Kostikova, N. Skiter

“…The decision-making algorithm based on the fuzzy inference method for estimating objects changing in time is considered. …”
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