Coordinated Volt/VAR Control in Distribution Networks Considering Demand Response via Safe Deep Reinforcement Learning by Dong Hua, Fei Peng, Suisheng Liu, Qinglin Lin, Jiahui Fan, Qian Li

“…Next, a safe deep reinforcement learning (SDRL) algorithm is proposed, incorporating a novel Lagrange multiplier update mechanism to ensure that the control policies adhere to safety constraints during the learning process. …”
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Stability Analysis of Axisymmetric Concave Slopes Based on Two-Dimensional Limit Equilibrium Approach considering Additional Shear Resistance by Xiao-ming Liu, Rui Zhang, Jie Han, Sha Chen

“…Combined with an iteration algorithm, the procedure can obtain the factors of safety for axisymmetric concave slopes in a simple and efficient way. …”
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Research on End-Effector Position Error Compensation of Industrial Robotic Arm Based on ECOA-BP by Wenping Xiang, Junhua Chen, Hao Li, Zhiyuan Chai, Yinghou Lou

“…To achieve error compensation, an approach based on an Enhanced Crayfish Optimization Algorithm (ECOA) optimizing a BP neural network was proposed to compensate for position errors. …”
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Evolving Spiking Neural Network Model for PM2.5 Hourly Concentration Prediction Based on Seasonal Differences: A Case Study on Data from Beijing and Shanghai by Hengyuan Liu, Guibin Lu, Yangjun Wang, Nikola Kasabov

“…Therefore, we have developed a staging evolving spiking neural network (eSNN) model named Staging-eSNN that first employs a time series clustering algorithm to distinguish the seasonal from the diurnal variation in the PM2.5 concentration. …”
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Monthly Runoff Prediction Based on STL-CEEMDAN-LSTM Model by WANG Hai, SHEN Yanqing, QI Shansheng, PAN Hongzhong, HUO Jianzhen, WANG Zhance

“…The complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) algorithm was then applied to decompose the residual terms to obtain intrinsic mode functions (IMFs) of different frequency components. …”
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A New Robust Classifier on Noise Domains: Bagging of Credal C4.5 Trees by Joaquín Abellán, Javier G. Castellano, Carlos J. Mantas

“…The Credal C4.5 (CC4.5) model is a new classification tree procedure based on the classical C4.5 algorithm and imprecise probabilities. It represents a type of the so-called credal trees. …”
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Cluster-driven non-uniform characteristic analysis of underwater target acoustic scattering field by Tianyang Xu, Hongjian Jia, Jixing Qin

“…Secondly, the t-distributed stochastic neighbor embedding algorithm is employed to improve the internal connection of the feature vector in the low-dimensional feature space and to construct the visualized feature space. …”
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Processing Uncertain RFID Data in Traceability Supply Chains by Dong Xie, Jie Xiao, Guangjun Guo, Tong Jiang

“…Moreover, we further propose a processing algorithm for group and independent objects. Experimental evaluations show that our approach is effective and efficient in terms of the compression and traceability queries.…”
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Optimization of Bus Bridging Service under Unexpected Metro Disruptions with Dynamic Passenger Flows by Jiadong Wang, Zhenzhou Yuan, Yonghao Yin

“…A multi-objective optimization model is established with objectives to minimize total waiting time, the number of stranded passengers and dispatched vehicles with constraints such as fleet size and vehicle capacity. The NSGA-II algorithm is used for the solution. Finally, we apply the proposed model to Shanghai Metro to access the effectiveness of our approaches in comparison with the current bridging strategy. …”
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Influence of nominal distortion of Beidou-3 B1C signal on ranging performance by Xue WANG, Yao GUO, Yongnan RAO, Xiaochun LU, Li KANG

“…The B1C signal is selected as a civil navigation signal for the BDS-3 system,which adopts a complex constant envelope modulation in the B1 frequency band.Therefore,it is easy to generate nominal distortion during signal generation.Such nominal distortion of each satellite produces inconsistent ranging deviation and directly degrades the system positioning performance.A complete ranging deviation estimation method was proposed for B1C signals in this paper.Firstly,the S-Curve Bias (SCB) was used to quantitatively analyze the B1C signal ranging deviation,and the standard correlation curve estimation method was proposed to realize the accurate estimation of the code phase deviation at the peak of the correlation curve.Secondly,a algorithm was designed to solve the problem of QMBOC signal mislocking at the platform during receiver tracking.Finally,the actual ranging bias and nature ranging bias of each satellite of Beidou-3 under different correlation intervals and front-end bandwidth of the user receiver were analyzed based on the satellite downlink signals collected from the 40-meter high-gain antenna at the National Time Service Center,and the recommended user receiver parameter range was given.The strategy proposed in this paper can be extended to other MBOC signal ranging error estimation,and the test results can be thought of as a reference to the development of BeiDou-3 receiver.…”
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A Multiple Beamforming Network for Unequally Spaced Linear Array Based on CORPS by Armando Arce, Marco Cardenas-Juarez, Ulises Pineda-Rico, David H. Covarrubias, Enrique Stevens-Navarro

“…The nonuniform aperture and the complex inputs of the feeding network are optimized by means of a differential evolution algorithm. In addition, a comparative analysis between a uniform and nonuniform linear array with the proposed feeding network is performed. …”
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Hyper-redundant endoscopic manipulator position compensation under external load by Giacoppo Giuliano A., Schulze Eric, Pott Peter P.

“…A simulation was performed using MATLAB, where mathematical models and algorithms were used to calculate the required tension. …”
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A Coons Patch Spanning a Finite Number of Curves Tested for Variationally Minimizing Its Area by Daud Ahmad, Bilal Masud

“…Given the demonstrated ability of our optimization algorithm to reduce area by as much as 23 percent for a spanning surface not close of being a minimal surface, this much smaller fractional decrease suggests that the Coons patch we have been able to write is already close of being a minimal surface.…”
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VIBRATION ANALYSIS AND OPTIMAL DESIGN OF LIGHT TRUCKS FUEL FILTER BRACKET by WU Hao, ZHONG ZiFeng

“…Lastly,the fuel filter bracket was multi-objective optimization analyzed based on Isight platform integrated CATIA,HYPERMESH and NASTRAN by adopting non-dominated sorting genetic algorithm. So the circular tube optimal parameters are obtained and the bracket maximum stress value are lower than the allowable stress after optimization. …”
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Study on Optimization of Coal Truck Flow in Open-Pit Mine by Haiming Bao, Ruixin Zhang

“…The truck flow planning model is solved using particle swarm intelligence algorithm. The simulation results show that the result of truck flow planning can effectively reduce truck number, truck dispatching number, transportation costs, and truck queuing. …”
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Smart Shift Decision Method Based on Stacked Autoencoders by Zengcai Wang, Yazhou Qi, Guoxin Zhang, Lei Zhao

“…The stacked autoencoder (SAE) algorithm, a type of artificial neural network, is used in this study to predict shifting gear timing on the basis of throttle percentage, vehicle velocity, and acceleration. …”
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Progressive active inference method of protocol state machine by Yan PAN, Wei LIN, Yuefei ZHU

“…Protocol state machine active inference is a technique that relies on active automata learning.However, the abstraction of the alphabet and the construction of the mapper present critical challenges.Due to the diversity of messages of the same type, the response types of the same type are different, causing the method of regarding the message types as the alphabet will result in the loss of states or state transitions.To address the issue, message types were refined into subtypes according to the different responses and a progressive active inference method was proposed.The proposed method extracted the state fields from the existing protocol data to construct the initial alphabet and the mapper, and obtained the initial state machine based on active automata learning.It then mutated the existing messages to explore the response sequences, which were inconsistent with the current state machine.The mutated message was regarded as a protocol subtype and added to the alphabet, and a new state machine was inferred progressively based on the new alphabet.In order to reduce the interactions, a pre-response query algorithm was proposed based on prefix matching for the caching mechanism in the active automata learning.The ProLearner tool was utilized to evaluate the proposed method in the context of the SMTP and RSTP protocols.It is verified that the pre-response query method can effectively reduce the number of actual interactions, with an average reduction rate of about 10%.…”
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Fast Compressed Sensing MRI Based on Complex Double-Density Dual-Tree Discrete Wavelet Transform by Shanshan Chen, Bensheng Qiu, Feng Zhao, Chao Li, Hongwei Du

“…In this paper, we propose a CS-based reconstruction scheme, which combines complex double-density dual-tree discrete wavelet transform (CDDDT-DWT) with fast iterative shrinkage/soft thresholding algorithm (FISTA) to efficiently reduce such visual artifacts. …”
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A Cognitive Radio Spectrum Sensing Method for an OFDM Signal Based on Deep Learning and Cycle Spectrum by Guangliang Pan, Jun Li, Fei Lin

“…Firstly, we analyze the cyclic autocorrelation of an OFDM signal and the cyclic spectrum obtained by the time domain smoothing fast Fourier transformation (FFT) accumulation algorithm (FAM), and the cyclic spectrum is normalized to gray scale processing to form a cyclic autocorrelation gray scale image. …”
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A CNN-Based Microwave Imaging System for Detecting Watermelon Ripeness by Zachary M. Choffin, Lingyan Kong, Yu Gan, Nathan Jeong

“…The integration of a non-invasive microwave imaging system with a machine learning algorithm could improve food quality and food safety. …”
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