Analysis of algorithms of interference coding and improving the efficiency in the complex systems by Oleg Pavlovich Malofey, Alexander Olegovych Malofey, Anastasia Evgenievna Shangina

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Machine learning approach for optimizing usability of healthcare websites by Amandeep Kaur, Jaswinder Singh, Satinder Kaur

“…Key metrics such as R-square, Mean Square Error (MSE), Mean Absolute Error (MAE), and Explained Variance Score (EVS) confirmed the model’s predictive accuracy. …”
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Optimization design and simplified decoding for short frame CCPM by Xiao-jie DAI, Ya-feng ZHAN

“…Considering the demand of burst communications,optimization and simplified decoding for coded GMSK sys-tem in short frame was focused on to give an optimum proposal of C²PPM system.Simplified demodulator,optimized generation polynomial of the convolution code and matched interleavers were discussed.Simulation results show that for coded GMSK system under AWGN,the performance is better than individual convolution code.Especially when BER is 1×10^-5,it performs better than Turbo code and LDPC code with the same frame length,and there is no error floor occur-ring.Finally,complexity analysis shows that the coded GMSK system has lower implementation complexity in compari-son with the commonly used convolution code,Turbo code and LDPC code.…”
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Bayesian optimization and machine learning for vaccine formulation development. by Lillian Li, Sung-In Back, Jian Ma, Yawen Guo, Thomas Galeandro-Diamant, Didier Clénet

“…Model analysis using prediction error plot, Shapeley Additive exPlanations, permutation importance, etc. can provide additional insights into relations between model and experimental design, the influence of features of interest, and non-linear responses. …”
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Application of Integer Response Optimization Models for the Healthcare Resources by Abdulkadir Atalan

“…In the study, statistical analysis was performed, and the integer response optimization models were created using the linear regression response optimization models. …”
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Landslide Displacement Prediction Model Based on Optimal Decomposition and Deep Attention Mechanism by Shuai Ren, Kamarul Hawari Ghazali, Yuanfa Ji, Samra Urooj Khan

“…Moreover, the Mean Absolute Scaled Error (MASE) analysis confirms the robustness of the model in capturing both short-term fluctuations and long-term trends. …”
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Multiobjective Optimal Control of FOPID Controller for Hydraulic Turbine Governing Systems Based on Reinforced Multiobjective Harris Hawks Optimization Coupling with Hybrid Strateg... by Wenlong Fu, QiPeng Lu

“…For this purpose, multiobjective optimization problem of fractional order PID (FOPID) controller for HTGS is constructed through the consideration of no-load disturbance and on-load disturbance operation conditions, where the performance indicators of integral time absolute error (ITAE) under both operation conditions are employed as the objective functions. …”
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Enhancing building energy efficiency with thermal mass optimization by Yichen Han, Zhengyu He, Shuangdui Wu, Yuqiu Liu, Yingkai Lian, Chaohong Wang, Jiajia Feng, Zhengnan Zhou

“…The results demonstrate that optimizing thermal mass arrangements tailored to specific building schedules can significantly enhance energy efficiency. …”
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Performance Evaluation of Beluga Whale Optimization–Long Short-Term Memory–Random Forest Networks for Trajectory Control and Energy Optimization in Excavator Systems by Van Hien Nguyen, Kyoung Kwan Ahn

“…Simulations and experiments confirm that our approach achieves a positional error below 3 mm, ensuring precise tracking and providing reliable data for operators. …”
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Design and parameter optimization of portable tree transplanting machine by Zhang Jingping, Zhu Jianxi, Sun Teng

“…And the average relative error between the optimization and trials is 10.90%.In conclusion, the optimization experiment improves the machine's operating performance and also provides a preferable reference for the design of the tree transplanting machine.…”
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Nonlinear H∞ Optimal Control Scheme for an Underwater Vehicle with Regional Function Formulation by Zool H. Ismail, Matthew W. Dunnigan

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Optimal Combination of Currency Assets and Algorithm Simulation under Exchange Rate Risk by Jun Wei

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Development and Optimization of IoT-Based Weighing Rain Gauge by Aldrich L. Saniel, Roma Joy D. Ombao, James Micole T. Montemayor, Jandrix Clarence B. Hoybia, Philip Angelito M. Cruz, Pierre Sheann B. Hernandez, Rommel Glenn S. Mendova, Dan William C. Martinez, Ariel N. Panaligan

“…Calibration used hysteresis and linear regression analysis to minimize errors, ensuring 99.999 % data accuracy. …”
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Quantitative Analysis of 3-Monochloropropane-1,2-diol in Fried Oil Using Convolutional Neural Networks Optimizing with a Stepwise Hybrid Preprocessing Strategy Based on Fourier Tra... by Xi Wang, Siyi Wang, Shibing Zhang, Jiping Yin, Qi Zhao

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Deep Learning-Based Video Anomaly Detection Using Optimised Attention-Enhanced Autoencoders by Anjali S, Don S

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Establishment of an Improved Elman Neural Network Model for Predicting the Corrosion Rate of 3C Steel in Marine Environment and Analysis of the Factors Affecting Model Accuracy by Wenbo Jin, Zhuo Chen, Wanying Liu, Qing Quan, Zongxiao Ren

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Delay-Dependent Exponential Optimal Synchronization for Nonidentical Chaotic Systems via Neural-Network-Based Approach by Feng-Hsiag Hsiao

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Dynamic reconstruction of electroencephalogram data using RBF neural networks by Xuan Wang, Congcong Du, Xianjin Ke, Jian Zhang, Zheng Zheng, Yayan Yue, Ming Yu

“…Signals were preprocessed through bandpass filtering (1–35 Hz) and Independent Component Analysis (ICA) for artifact removal. neural network was trained on EEG time-series data with PSO employed to optimize model parameters identify fixed points in the reconstructed neural system. …”
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CPO-VMD Combined With Multiscale Permutation Entropy for Noise Reduction in GNSS Vertical Time Series in Mining Areas by Xu Yang, Xinxin Yao, Xinjian Fang, Xuexiang Yu, Yi Wu, Shicheng Xie

“…The results of simulation and example analysis show that compared with wavelet denoising (WD), empirical modal decomposition (EMD), ensemble empirical mode decomposition (EEMD), and improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), this method shows significant advantages in the evaluation indexes of noise reduction effect—Pearson’s correlation coefficient (R), the signal-to-noise ratio (SNR), and the root-mean-square error (RMSE)—and all the indexes are better than the comparative methods. …”
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Integrating an artificial neural network with genetic, particle swarm optimization algorithms, and fuzzy rule to optimize the surface roughness in dry turning AISI 1045 steel by Abdulmajeed Dabwan, Mohammed K Almatani, Mohammed Alqahtani, Husam Kaid, Khaled N Alqahtani, Mustafa M Nasr, Adham E Ragab

“…This research aims to propose optimization methods including a hybrid artificial neural network (ANN) with genetic algorithms (GA) particle swarm optimization (PSO), and Adaptive Neuro-Fuzzy Inference System (ANFIS) to predict and optimize surface roughness during dry machining of AISI 1045 steel. …”
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