Research on intelligent routing with VAE-GAN in the internet of body. by Song Qian, Tianping Zhang, Siping Hu

“…The traditional artificial intelligence routing algorithm cannot deal with the low model prediction accuracy and poor generalization ability caused by large noise and small data volume. …”
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Modeling Chaotic Behavior of Chittagong Stock Indices by Shipra Banik, Mohammed Anwer, A. F. M. Khodadad Khan

“…In this paper, a comparative study has been conducted to predict stock index values using soft computing models and time series model. …”
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Ultrafast silicon photonic reservoir computing engine delivering over 200 TOPS by Dongliang Wang, Yikun Nie, Gaolei Hu, Hon Ki Tsang, Chaoran Huang

“…Experimental results demonstrate state-of-the-art performance in prediction, emulation, and classification tasks across various machine learning applications. …”
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Parametric Studies of Laminated Cooling Configurations: Overall Cooling Effectiveness by Chen Wang, Chunhua Wang, Jingzhou Zhang

“…Moreover, based on the numerical results, an empirical correlation is developed to predict the overall cooling efficiency in a specific range, and a genetic algorithm is applied to determine the empirical parameters. …”
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Hybrid solver with deep learning for transport problem in porous media by Vladislav Trifonov, Egor Illarionov, Anton Voskresenskii, Musheg Petrosyants, Klemens Katterbauer

“…Extensive experiments with dynamic and static reservoir features revealed that improving predictive accuracy does not necessarily improve fluid modeling. …”
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A Reduced-Order Model for Active Suppression Control of Vehicle Longitudinal Low-Frequency Vibration by Donghao Hao, Changlu Zhao, Ying Huang

“…Establishing a prediction model, with linearity and few dof (degree of freedom), is a key step for the design of a control algorithm based on the modern control theory. …”
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Automatic Fault Classification for Journal Bearings Using ANN and DNN by Narendiranath Babu THAMBA, Arun ARAVIND, Abhishek RAKESH, Mohamed JAHZAN, Rama Prabha DURAISWAMY, Ramalinga Viswanathan MANGALARAJA

“…Proper analysis of the various bearing faults and predicting the modes of failure beforehand are essential to increase the working life of the bearing. …”
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Bearing clearance test and lifetime analysis for EMU traction motor by GENG Min, ZHAO Pengyu, LI Xiaoyang, LEI Guanbiao, WANG Xilian

“…The mechanical load is the only factor of influence considered in the traditional bearing lifetime prediction algorithm. However, for the traction motor of the electric multiple units (EMUs) in actual working conditions, its bearing is also subject to the additional electromagnetic load derived from the additional radial electromagnetic force acting on its rotor, which is under effect of bearing clearance. …”
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Analysis of crop disease and pest occurrences: Insights from Japan's national surveys. by Jianqiang Sun, Sunao Ochi, Takehiko Yamanaka

“…However, the prediction error remained substantial, with an RMSE of 6.2 ± 19.6. …”
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RIM-MAC:a receiver initiated multi-session MAC protocol for underwater acoustic networks by Chao LI, Yong-jun XU, Bo-yu DIAO, Feng WANG, Qi WANG

“…,neighboring nodes’ propagation delay maps and expected transmission schedules) to launch multiple simultaneous sessions.RIM-MAC increases the chances of concurrent transmissions in the underwater channel and achieve the channel reuse at both the sender and receiver side,improving the overall throughput at least 36% compared to the typical MAC protocols.Moreover,a traffic prediction based adaptive data polling scheme named fair traffic algorithm (FTA) guarantees fairness across multiple contending nodes.Extensive simulation results have confirmed that the RIM-MAC protocol outperforms existing MAC protocols and provides fair medium access in representative long propagation delay scenarios.…”
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Online State of Charge Estimation of Lithium-Ion Cells Using Particle Filter-Based Hybrid Filtering Approach by Ming Zhang, Kai Wang, Yan-ting Zhou

“…However, if the system is a moving EV during rapid acceleration or regenerative braking or when using heating or air conditioning, most of the existing works suffer from poor prediction of state and state estimation error covariance, leading to the problem of accuracy degeneracy of the algorithm. …”
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Network pharmacognosy of Galphimia glauca: Mapping the molecular landscape of a traditional Mexican medicinal plant. by María José Cambero Acosta, Guillermo de Anda-Jáuregui

“…Community detection with the Walktrap algorithm further segmented the network into functionally relevant modules linked to cell survival, immune response, and inflammation, reflecting the therapeutic effects historically attributed to G. glauca. …”
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Cotton Disease Detection Using TensorFlow Machine Learning Technique by Sandeep Kumar, Rajeev Ratan, J. V. Desai

“…In this paper, the CNN algorithm is used to create the prediction model by leveraging the TensorFlow’s Keras API. …”
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Discover the road sequences of bus lines using bus stop information and historical bus locations by Ying Zhou, Guiyuan Jiang, Guifeng Jiang

“…To solve the problem, we first construct a high-quality global positioning system (GPS) trajectory and then employ a novel map-matching algorithm to the resultant dense trajectory to obtain the road sequence of the bus line. …”
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Optimization of Oil Yield from the Macro Algae Spirogyra by Solvent Extraction Process Using RSM and ANN by S. Aravind, Debabrata Barik, Nagaraj Ashok

“…The coefficient of determination, R2 of 98.92%, and the mean absolute percentage deviation (MAPD) of 0.492% for ANN revealed that the current model created with a network topology of 3 : 11 : 1 with tansig (hyperbolic tangent sigmoid) transfer function in the input layer and purelin (pure linear) transfer function in the output layer trained with trainlm (Levenberg–Marquardt) algorithm found to provide the optimal solution with better accuracy in prediction of the output. …”
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A reversible database watermarking method non-redundancy shifting-based histogram gaps by Yan Li, Junwei Wang, Xiangyang Luo

“…First, an integer data histogram is constructed with the absolute value of the prediction error of the data as a variable. Second, the positional relationship between each column and the gap in the histogram is analyzed to find out all the columns adjacent to the gap. …”
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A Method of Abnormal Behavior Detection for Safety Site Surveillance by Wenjing Wang, Yangyang Zhang, QingE Wu

“…The experimental results show that the accuracy of the abnormal behavior detection method proposed in this paper can better discern the beginning and end of behavior occurrence, abnormal behavior prediction, behavior online detection, and other aspects from the visual image data stream, and the correct detection rate is more than 90%, which reduces the consumption of human resources. …”
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Multiobjective Reliability-Based Design Optimization of Recycled Aggregates Used in Corrosive Environment Based on Response Surface Modelling by Abdol Ghaium Dehvari, Mohsen Khazaei, Mohammad Reza Sohrabi, Mahmoud Miri

“…These models were then evaluated using a metaheuristic optimization algorithm coupled with a simple and fast usability new method of reliability evaluation. …”
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Optimizing diesel engine heterogeneous combustion performance and NOx emissions: A next energy perspective with AI by Aditya Kolakoti

“…The combustion results are trained in a feed-forward artificial neural network (ANN) algorithm for the predictions, and an error histogram with 20 bins helps identify the accuracy of the trained model. …”
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An Efficient Trajectory Negotiation and Verification Method Based on Spatiotemporal Pattern Mining by Yongqi Liu, Miao Wang, Zhaohua Zhong, Kelin Zhong, Guoqing Wang

“…Therefore, this paper develops a framework for trajectory negotiation and verification and describes the trajectory prediction, negotiation, and verification processes based on a four-dimensional trajectory. …”
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