A hybrid machine learning algorithm approach to predictive maintenance tasks: A comparison with machine learning algorithms by Jorge Paredes, Danilo Chávez, Ramiro Isa-Jara, Diego Vargas

“…However, there is room for improvement in this prediction. In this paper, a hybrid approach that combines supervised learning (multi-layer perceptron MLP) and reinforcement learning (Q-learning) algorithms is proposed with the aim of improving the accuracy and precision of predicting the RUL. …”
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PCA-FSA-MLR Model and Its Application in Runoff Forecast by GUO Cunwen, CUI Dongwen

“…To improve the accuracy of runoff forecast,and establish a runoff forecast model combining principal component analysis (PCA),future search algorithm (FSA),and multiple linear regression (MLR),this paper reduces the dimensionality of the sample data by PCA,selects 8 standard test functions and simulates and verifies FSA under different dimensional conditions,optimizes MLR constant terms and partial regression coefficients by FSA,proposes a PCA-FSA-MLR runoff forecast model,constructs PCA-LS-MLR,PCA-FSA-SVM,and PCA-SVM models with dimensionality reduction processing by PCA and FSA-MLR,LS-MLR,FSA-SVM,and SVM without dimensionality reduction processing as a comparison model,and verifies each model through forecasting the annual runoff and monthly runoff in December of Longtan station in Yunnan Province.The results show that:①FSA has better optimization accuracy and global extremum search ability under different dimensional conditions;②The average absolute relative error of the annual runoff and monthly runoff in December of Longtan station through PCA-FSA-MLR model are 1.63% and 3.91% respectively,and its forecast accuracy is better than the other 7 models,with higher forecast accuracy and stronger generalization ability;③For the same model,the forecast accuracy after dimensionality reduction processing by PCA is better than that without dimensionality reduction processing,so the data dimensionality reduction by PCA is helpful to improve the forecast accuracy of models.…”
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Efficiency multi-agent model assisted Moea/D algorithm for optimization design for building taking into account annual energy consumption and annual user discomfort hours by Hua Deng, Kai Zhou

“…Then it introduces a multi-agent model auxiliary mechanism to improve the decomposition based multi-objective evolutionary optimization algorithm, and then solves the multi-objective optimization model for building energy efficiency. …”
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Improved Deviation Sparse Fuzzy C-Means-2D Cumulative Sum Average Filter and Modified Sine Cosine Crow Search Algorithm-Wavelet Extreme Learning Machine for Brain Tumor Detection a... by Suvashisa Dash, Satyasis Mishra, Mohammed Siddique, Demissie J. Gelmecha, Ram Sewak Singh

“…The hybrid modified sine cosine algorithm-crow search algorithm (MSCA-CSA)–based WELM model is proposed to classify the brain tumor. …”
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A novel approach for efficient resource allocation in 6G V2V networks using neighbor-aware greedy algorithm and sweep line model by Spandana Mande, Nandhakumar Ramachandran

“…In our research, we present an Enhanced Neighbor Node Associated Greedy-based Resource Distributed V2V Model with Sweep Line Model (NNAGbRD-V2V-SLM) for secure resource handling and management in V2V and V2X communication. …”
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Transient Stability Analysis of Wind-Integrated Power Systems via a Kuramoto-like Model Incorporating Node Importance by Min Cheng, Jiawei Yu, Mingkang Wu, Yayao Zhang, Yihua Zhu, Yuanfu Zhu

“…First, virtual node technology is utilized to optimize the power grid topology model. Then an improved PageRank algorithm embedded by a critical node identification method is proposed, which simultaneously considers transmission efficiency, coupling transmission probability, and voltage influence among nodes. …”
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General statement of the challenge of selection of decisions to improve the protection of objects of life support from the population from the impact of air shock wave by Voskoboev V.F., Rybakov A.V., Ivanov E.V.

“…An algorithm for solving the problem is presented. A multi-factor model for assessing the security of an object against the impact of a shock wave is the basis of the algorithm. …”
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PAPR optimization based on SLM and PTS algorithms in NC-OFDM systems by Jie ZHOU, Bernardo Esono Esono Mikue, Xueying WANG, Huiting ZHOU, Hong LUO

“…Based on the non-continuous orthogonal frequency division multiplexing (NC-OFDM) model, a fusion optimization technology based on selected mapping (SLM) algorithm and partial transmit sequence (PTS) algorithm was proposed, and a system model of fusion technology was designed.Through simulation comparison with other literature methods, it was verified that the SLM-PTS fusion technology had excellent peak to average power ratio (PAPR) reduction ability, but the algorithm implementation complexity was too high.Therefore, a complementary SLM-Clipping fusion solution was proposed, and the deep learning method PAPRnet model was construted.The simulation results verif that prove the effectiveness of the method, the algorithm has an excellent PAPR suppressed effect on the NC-OFDM system, and greatly improves the computational efficiency.…”
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PAPR optimization based on SLM and PTS algorithms in NC-OFDM systems by Jie ZHOU, Bernardo Esono Esono Mikue, Xueying WANG, Huiting ZHOU, Hong LUO

“…Based on the non-continuous orthogonal frequency division multiplexing (NC-OFDM) model, a fusion optimization technology based on selected mapping (SLM) algorithm and partial transmit sequence (PTS) algorithm was proposed, and a system model of fusion technology was designed.Through simulation comparison with other literature methods, it was verified that the SLM-PTS fusion technology had excellent peak to average power ratio (PAPR) reduction ability, but the algorithm implementation complexity was too high.Therefore, a complementary SLM-Clipping fusion solution was proposed, and the deep learning method PAPRnet model was construted.The simulation results verif that prove the effectiveness of the method, the algorithm has an excellent PAPR suppressed effect on the NC-OFDM system, and greatly improves the computational efficiency.…”
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A Deformation Prediction Model for Concrete Dams Based on RSA-VMD-AttLSTM by Pei Liu, Hao Gu, Chongshi Gu, Yanbo Wang

“…Analysis of the five evaluation criteria revealed that the RSA can better optimize the parameters of the VMD algorithm. Consequently, the proposed model demonstrates superior noise reduction capabilities and improved prediction accuracy.…”
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Modeling of Common Mode Interference of Secondary Side of Potential Transformer in VFTO Excitation by PANG Fubin, JI Jianfei, WU Xianqiang, ZHOU Mengxia, YAN Wei, XU Dong

“…Finally, a VFTO interference model for substation is established based on attenuated damping oscillation waves and a method for extracting the model parameters is proposed based on difference evolutionary algorithm. …”
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Effects of off-design performances and multiple market carbon trading mechanism on integrated energy systems with waste incineration power units by Jing Liu, Tong Zhao, Haolin Sui

“…Furthermore, to analyze effects of off-design performances and MMCTM on the electricity-gas-heating-cooling IES, five case studies have been conducted on a typical electricity-gas-heating-cooling IES and the improved slime mould algorithm (ISMA) were adopted. …”
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An orderly charging and discharging strategy for electric vehicles based on cooperative game and dynamic time-of-use pricing by Zhengyu SHU, Wencan LIU, Huangqiang LI, Can WANG, Qin YAO

“…Additionally, a dynamic time-of-use optimized charging and discharging simulation model for electric vehicles is constructed. In the solution process, an improved fruit fly optimization algorithm (FOA) is uesd to plan the charging periods of electric vehicles. …”
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Optimal load frequency control system for two-area connected via AC/DC link using cuckoo search algorithm by Gaber EL-SAADY, Alexey MIKHAYLOV, Nora BARANYAI, Mahrous AHMED, Mahmoud HEMEIDA

“…Results: The CSA was compared with particle swarm optimization algorithm (PSO) under identical conditions. The system was modeled based on a state-space mathematical representation and simulated using MATLAB. …”
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Time-Variation Damping Dynamic Modeling and Updating for Cantilever Beams with Double Clearance Based on Experimental Identification by Yunhe Zhang, Fanjun Meng, Xueguang Li, Wei Song, Dashun Zhang, Faping Zhang

“…Finally, a case study is conducted to verify the presented model. In comparison with the initial dynamic model based on constant damping, the modal assurance criterion (MAC) of the proposed improved model based on time-variation damping is improved by 43.97%, the mean relative error (MRE) of the frequency response function (FRF) is reduced by 32.6%, and the root mean square error (RMSE) is reduced by 18.19%. …”
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RF-SFAD: A RANDOM FOREST MODEL FOR SELECTIVE FORWARDING ATTACK DETECTION IN MOBILE WIRELESS SENSOR NETWORKS by N Usha Bhanu, Soubhagya Ranjan Mallick, Sreenivasa Rao Chappidi, K Sangeethalakshmi

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Quantitative relationship model between soil profile salinity and soil depth in cotton fields based on data assimilation algorithm: forecasting cotton field yields and profits by Yang Gao, Yang Gao, Lin Chang, Lin Chang, Mei Zeng, Mei Zeng, Quanze Hu, Quanze Hu, Jiaojiao Hui, Jiaojiao Hui, Qingsong Jiang, Qingsong Jiang

“…The multivariate linear regression model was used to study the relationship between soil salinity and soil depth in different periods, and the Kalman filter algorithm was used to improve the model accuracy. …”
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Enhancing crane and gate OCR efficiency at container terminal using a hybrid genetic algorithm and neural network model: case study of tangier med port by Hamza Garmouch, Otman Abdoun

“…The research incorporates a hybrid GA-Neural Network (NN) model further, using machine learning to speed up fitness evaluation and provide optimal settings for OCR performance improvement that is applicable in real world. …”
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Dimensional Accuracy Analysis of Splined Shafts and Hubs Obtained by Fused-Deposition Modeling 3D Printing Using a Genetic Algorithm and Artificial Neural Network by Alin-Daniel Rizea, Cristina-Florena Banică, Tatiana Georgescu, Alexandru Sover, Daniel-Constantin Anghel

“…To optimize dimensional accuracy, artificial neural networks (ANNs) were trained using experimental data, and a genetic algorithm (GA) was employed for multi-objective optimization. …”
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Dual-Closed-Loop Control System for Polysilicon Reduction Furnace Power Supply Based on Hysteresis PID and Predictive Control by Shihao Li, Tiejun Zeng, Shan Jian, Guiping Cui, Ziwen Che, Genghong Lin, Zeyu Yan

“…To address this challenge, a dual-loop control system is proposed, combining model-free adaptive control (MFAC) with an improved PID controller. …”
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