Well Production Forecasting in Volve Field Using Kolmogorov–Arnold Networks by Xingyu Lu, Jing Cao, Jian Zou

“…The experimental results demonstrate that, compared to the best-performing baseline model, the KAN reduces the Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) by 78.5% and 89.5% for well 15/9-F-11 and by 80.1% and 91.8% for well 15/9-F-14, respectively. …”
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WisdomModel: convert data into wisdom by Israa Mahmood, Hasanen Abdullah

“…This paper presents the development of a wisdom framework that reduces the error rate to less than 3% without human intervention. …”
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The Design and Evaluation of an Ergonomic Contactless Gesture Control System for Industrial Robots by Gilbert Tang, Phil Webb

“…The developed gesture control system was targeting applications in system recovery and error correction in flexible manufacturing environment shared between humans and robots. …”
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Bosonic Pauli+: Efficient Simulation of Concatenated Gottesman-Kitaev-Preskill Codes by Florian Hopfmueller, Maxime Tremblay, Philippe St-Jean, Baptiste Royer, Marc-Antoine Lemonde

“…A promising route towards fault-tolerant quantum error correction is the concatenation of a Gottesman-Kitaev-Preskill (GKP) code with a qubit code. …”
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Orbifolds of chiral fermionic CFTs and their duality by Kohki Kawabata, Shinichiro Yahagi

“…For lattices based on binary error-correcting codes, we show the duality between reflection and shift orbifolds using a triality structure inherited from the binary codes. …”
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Numerical Implementation of Stochastic Operational Matrix Driven by a Fractional Brownian Motion for Solving a Stochastic Differential Equation by R. Ezzati, M. Khodabin, Z. Sadati

“…Finally, the numerical examples demonstrate applicability and accuracy of this method.…”
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Joint iterative decision feedback channel estimation and detection for Turbo coded V-BLAST MIMO-OFDM systems by QIAO Xiao-qiang1, CAI Yue-ming1, XU Xin1, XU You-yun1

“…For Turbo coded V-BLAST MIMO-OFDM systems,a joint iterative decision feedback channel estimation and detection scheme were presented,which combined the Turbo iterative decoding with least square channel estimation,and made full use of the soft systematic bits and soft parity bits of Turbo iterative decoding to improve the channel estimation performance.The simulation results showed that not only the error propagation was corrected at low signal-noise-ratio but also the channel estimation performance of the whole system was improved greatly.Furthermore,the scheme is applicable for very bad channel environments.…”
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Use of artificial intelligence for gestational age estimation: a systematic review and meta-analysis by Sabahat Naz, Sahir Noorani, Syed Ali Jaffar Zaidi, Abdu R. Rahman, Saima Sattar, Jai K. Das, Jai K. Das, Zahra Hoodbhoy

“…In studies using deep learning for 2D images, those employing CNN reported a mean error of 5.11 days (95% CI: 1.85, 8.37) in gestational age estimation, while one using DNN indicated a mean error of 5.39 days (95% CI: 5.10, 5.68). …”
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Machine-learning based high-bandwidth magnetic sensing by Galya Haim, Stefano Martina, John Howell, Nir Bar-Gill, Filippo Caruso

“…Our results indicate a potential reduction of required data points by at least a factor of 3, while maintaining the current error level. Our results promote quantum machine learning protocols for sensing applications towards more feasible and efficient quantum technologies.…”
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A survey of GNSS receiver autonomous integrity monitoring: Research status and opportunities by Zhen Huang, Zhen Huang, Weihua Mou, Weihua Mou, Rui Wang, Pengpeng Li, Pengpeng Li, Zhicheng Lyu, Zhicheng Lyu, Gang Ou, Gang Ou

“…The paper provides a comprehensive review of RAIM algorithms for global navigation satellite system (GNSS) positioning applications. The parameters related to integrity assessment and typical fault detection and exclusion methods are reviewed, and RAIM is categorized into three types of methods: error probability distribution model-based, set representation-based, and machine learning-based. …”
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Prediction Model of Asphalt Content of Asphalt Mixture Based on Dielectric Properties by Yanhui Zhong, Yilong Wang, Bei Zhang, Xiaolong Li, Songtao Li, Yanmei Zhong, Meimei Hao, Yanlong Gao

“…Among the models, the Rayleigh model has a wide range of applications and exhibits a high accuracy, with an average relative error of only 1.86%. …”
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A combined ML and DFT strategy for the prediction of dye candidates for indoor DSSCs by Carmen Coppola, Anna Visibelli, Maria Laura Parisi, Annalisa Santucci, Lorenzo Zani, Ottavia Spiga, Adalgisa Sinicropi

“…However, such activities are often based on trial-and-error procedures which are frequently expensive and time-consuming. …”
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Data-Driven Simulation of Pedestrian Movement with Artificial Neural Network by Weili Wang, Jiayu Rong, Qinqin Fan, Jingjing Zhang, Xin Han, Beihua Cong

“…To predict pedestrian movement is of vital importance in a wide range of applications. Recently, data-driven models are receiving increasing attention in pedestrian dynamics studies, demonstrating a great potential in enhancing simulation performance. …”
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Non-destructive Thermal Monitoring of Temperature and Flow Rate of the Heat Carrier in a Heating Device by Pavlov Mikhail Vasilyevich, Karpov Denis Fedorovich, Vafaeva Khristina Maksudovna, Reddy G. Keerthi, Makhija Himanshu, Deorari Rajesh, Verma Raman, Raju K. Butchi, Tiwari Deepak Kumar

“…Contact measurement means are not always applicable, especially for small-diameter pipelines. …”
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Hardware-Centric Exploration of the Discrete Design Space in Transformer–LSTM Models for Wind Speed Prediction on Memory-Constrained Devices by Laeeq Aslam, Runmin Zou, Ebrahim Shahzad Awan, Sayyed Shahid Hussain, Kashish Ara Shakil, Mudasir Ahmad Wani, Muhammad Asim

“…The model, with its tuned hyperparameters, outperforms recent methodologies in terms of mean squared error, mean absolute error, model size, and R-squared scores across three different datasets. …”
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Empowering Quality of Recommendations by Integrating Matrix Factorization Approaches With Louvain Community Detection by Srilatha Tokala, Murali Krishna Enduri, T. Jaya Lakshmi, Ashu Abdul, Jenhui Chen

“…The steps involved in the proposed approach are: 1) The rating matrix is modeled as a bipartite network. 2) Communities are generated from the network. 3) Extract the rating matrices that belong to the communities and apply MF to these matrices in parallel. 4) Merge the predicted rating matrices belonging to the communities and evaluate root mean square error (RMSE), mean square error (MSE), and mean absolute error (MAE). …”
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An Investigation into Item Types and Text Types of Reading Comprehension Section of Iranian PhD Entrance Exams Using G-theory by Masoumeh Ahmadi Shirazi, Seyyed Mohammad Alavi, Hossein Salarian

“…This study investigates some problems of PhD applicants in their entrance exams in the case of answering the reading comprehension questions. …”
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Research on Adaptive Variable Impedance Control Method Based on Adaptive Neuro-Fuzzy Inference System by Xianlun Wang, Chuanhuan Li, Dexin Cai, Yuxia Cui

“…Meanwhile, to improve the applicability of the controller and avoid using expert experience to formulate fuzzy rules, this paper designs an adaptive neuro-fuzzy inference system (ANFIS) to dynamically adjust the update rate. …”
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An Optimal Longitudinal Control Strategy of Platoons Using Improved Particle Swarm Optimization by Zhizhou Wu, Zhibo Gao, Wei Hao, Jiaqi Ma

“…Then, a linear-quadratic optimal controller was designed considering the perspectives of driving safety, efficiency, and ride comfort with three performance indicators including vehicle gap error, relative speed, and desired acceleration. …”
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Time Synchronization in Wireless Sensor Networks Using Max and Average Consensus Protocol by Zhao Dengchang, An Zhulin, Xu Yongjun

“…Through several simulations, we can see that this protocol can reduce clock error to ±10 ticks, adapt to dynamic topology, and be suitable to large-scale applications.…”
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