The performance evaluation of chaotic maps in estimating the shape parameters of radial basis functions to solve partial differential equations by Javad Alikhani Koupaei, Mohammad Javad Ebadi, Majid Iran Pour

“…Purpose: This study aims to investigate the potential of chaotic optimization algorithms in improving performance compared to other optimization methods, focusing on determining the appropriate shape parameter of radial basis functions for solving partial differential equations.Methodology: In this research, a two-stage process is employed where the Kansa method, based on meshless local techniques, is combined with the FCW method. …”
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Anomaly Detection and Root Cause Analysis for Energy Consumption of Medium and Heavy Plate: A Novel Method Based on Bayesian Neural Network with Adam Variational Inference by Qiang Guo, Fenghe Li, Hengwen Liu, Jin Guo

“…Anomaly detection and root cause analysis of energy consumption not only optimize energy use and improve equipment reliability but also contribute to green and low-carbon development. …”
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IDE-SVM algorithm and it's usage in physical layer security method for IoT by WANG Qiang, ZHU Chenming, PAN Su, QIN Yuxi

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A study on the prediction of mountain slope displacement using a hybrid deep learning model by Yuyang Ma, Xiangxiang Hu, Yuhang Liu, Yaya Shi, Zhiyuan Yu, Xinmin Wang, Liangbai Hu, Shuailing Liu, Dongdong Pang

“…Abstract To address the challenges of large prediction errors and limited reliability in conventional modeling approaches, this study proposes a hybrid framework that integrates optimization and deep learning techniques. The method employs an Improved Whale Optimization Algorithm (IWOA) to fine-tune parameters for GNSS data fitting, ensuring accurate signal feature extraction. …”
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The Application of Kalman Filter Algorithm in Rail Transit Signal Safety Detection by Zhinong Miao, Qilong Liao

“…Firstly, the improved Kalman filter algorithm is used to denoise the signal to ensure the accuracy of signal transmission. …”
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Medium and Long Term Wind Power Prediction Based on Graph Convolutional Network and Wind Velocity Differential Fitting by Zihan CHEN, Wei TENG, Xuefeng XU, Xian DING, Yibing LIU

“…In order to make full use of the prior relationships among data features and improve the prediction accuracy of medium and long term wind power at wind farms, a medium and long term wind power prediction model based on graph convolution neural network (GCN), wind velocity differential fitting (DF), and particle swarm optimization (PSO) is proposed. …”
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Multipopulation Management in Evolutionary Algorithms and Application to Complex Warehouse Scheduling Problems by Yadong Yu, Haiping Ma, Mei Yu, Sengang Ye, Xiaolei Chen

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Assessing and Reducing Energy Consumption of Grain Cleaning and Drying Equipment by Yu. N. Sap’yan, V. A. Kolos, M. I. Suleymanov, E. N. Kabakova

“…(Research purpose) To adapt the criteria and algorithm of energy-saving optimization of field technology to assess and improve the status of energy efficiency, reduce energy consumption and identify the maximum available energy saving potential of grain drying equipment during energy audit. …”
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Study on the Switching Model Predictive Control Algorithm in Batch Polymerization Process by Jong Nam Kim, Chun Bae Ma, Hyok Jo, Un Chol Han, Hyon-Tae Pak, Son Il Hong, Ri Myong Kim

“…The results show that the proposed control system can significantly improve temperature control performance (overshoot: 0.2%, root mean square error: 0.3) compared to before introduction (overshoot: 1.1%, root mean square error: 1.2ྟC) .…”
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Performance Analysis of Marine Predators Algorithm for Automatic Voltage Regulator System by Zeynep Garip, Murat Erhan Çimen, Ali Fuat Boz

“…With the proposed algorithm, this study aimed to minimize the maximum percent excess of the terminal voltage, settling time, rise time, and steady-state error and improve the transient response of the automatic voltage regulator system with an optimal proportional–integral– derivative controller. …”
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Permission clustering-based attribute value optimization by Wenchao WU, Zhiyu REN, Xuehui DU

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Research on Optimization of Magnetic Ranging by Mechanism & Intelligence by QIAN Hongyu, CHE Yang, WANG Xiufang, FENG Fuping, JIANG Chunlei

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Research on rock strength prediction model based on machine learning algorithm by Xiang Ding, Mengyun Dong, Wanqing Shen

“…By selecting different features, the optimal feature combination for predicting rock compressive strength was obtained, and the optimal parameters for different models were obtained through the Sparrow Search Algorithm (SSA). …”
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Synthesis of an Algorithm for Classifying Underwater Objects on Based on the Analysis of their Noise Spectra by Evgeniy Storozhok, Vladimir Kristalinskii

“…The need to reduce the probability of false alarms in such systems actualizes the issues of developing an optimal algorithm for classifying underwater objects by their sonar field. …”
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Post-integration based point-line feature visual SLAM in low-texture environments by Yanli Liu, Zhengyuan Feng, Heng Zhang, Wang Dong

“…Abstract To address the issues of weak robustness and low accuracy of traditional SLAM data processing algorithms in weak texture environments such as low light and low contrast, this paper first studies and improves the data feature extraction method, optimizing the AGAST-based feature extraction algorithm to adaptively adjust the extraction threshold according to the gradient size of different data features. …”
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Automated Calibration of SWMM for Improved Stormwater Model Development and Application by Hossein Ahmadi, Durelle Scott, David J. Sample, Mina Shahed Behrouz

“…The tool also supports parallelized optimization algorithms and utilizes Application Programming Interfaces (APIs) to dynamically update SWMM model parameters, accelerating both model execution and convergence. …”
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Multi-Objective Intelligent Routing Algorithm for LEO Satellite Networks Based on DQN by LUO Zongyi, JIN Shichao, DONG Tao, YIN Jie

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Combined use of near infrared spectroscopy and chemometrics for the simultaneous detection of multiple illicit additions in wheat flour by Xinyi Dong, Ying Dong, Jinming Liu, Siting Wu

“…The model combines long short-term memory network (LSTM) data dimensionality reduction with partial least squares to detect multiple illicit additives in wheat flour. The Bayesian optimization algorithm was used to optimize the LSTM parameters. …”
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An Area-Time Efficient Hardware Architecture for ML-KEM Post-Quantum Cryptography Standard by Trong-Hung Nguyen, Tuan-Kiet Dang, Duc-Thuan Dam, Khai-Duy Nguyen, Phuc-Phan Duong, Cong-Kha Pham, Trong-Thuc Hoang

“…To facilitate the integration of the NIST-standardized post-quantum cryptographic (PQC) algorithm, Module Lattice-based Key Encapsulation Mechanism (ML-KEM), into quantum-resistant devices and cryptosystems, this study introduces an area-time efficient hardware implementation. …”
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RRMSE-enhanced weighted voting regressor for improved ensemble regression. by Shikun Chen, Wenlong Zheng

“…This uniform weighting approach doesn't consider that some models may perform better than others on different datasets, leaving room for improvement in optimizing ensemble performance. To overcome this limitation, we propose the RRMSE (Relative Root Mean Square Error) Voting Regressor, a new ensemble regression technique that assigns weights to each base model based on their relative error rates. …”
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