Research on the Optimization of the PID Control Method for an EOD Robotic Manipulator Using the PSO Algorithm for BP Neural Networks by Yunkang Zhou, Xiaohui He, Faming Shao, Xiangpo Zhang

“…Simulation results indicate that compared to traditional BP+PID control, genetic algorithm (GA)+PID control, and whale optimization algorithm (WOA)-BP+PID control, the PSO-BP+PID algorithm control rapidly tunes the PID control parameters K_p, K_i, and K_d. …”
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Generalization bias in large language model summarization of scientific research by Uwe Peters, Benjamin Chin-Yee

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Research on Reverse Search System of Intelligent Parking Lot by MA Jihui, WANG Lijie, ZHAO Yuanzhen, SUN Jianbo

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Machine learning-based prediction of CO2 solubility in methyldiethanolamine solutions: A comparative study by Sajjad Fazeli, Mohammad Amin Moradkhani, Behrouz Bayati

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Research on the Prediction of Pipelines Corrosion Rate Based on GA-LSSVM by CHEN Yong-hong, SU Yong-sheng, HU Ping

“…Corrosion rate is an important characteristic parameter to reflect the corrosion dynamics process of pipeline.In order to accurately evaluate the long-term operation reliability and remaining life of pipeline, the prediction of corrosion rate is particularly important.Least squares support vector machine(LSSVM)is a method based on machine learning, which is often used in classification and prediction research.Since penalty parameters γ and kernel parameters σ2 are two important parameters of LSSVM, the value of these two parameters can only be obtained by experience in calculation, causing a great impact on the calculation results.In this paper, the genetic algorithm(GA)was used to optimize the parameters, the GA-LSSVM prediction model was built and the model was applied to the prediction of pipeline corrosion rate.Compared with the results of other prediction models, the results showed that the accuracy of GA-LSSVM model and prediction results were relatively higher, which could realize the prediction of pipeline corrosion rate.…”
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Why implementing machine learning algorithms in the clinic is not a plug-and-play solution: a simulation study of a machine learning algorithm for acute leukaemia subtype diagnosis... by Gernot Pucher, Till Rostalski, Felix Nensa, Jens Kleesiek, Hans Christian Reinhardt, Christopher Martin Sauer

“…Findings: The AI-PAL algorithm demonstrated significantly lower performance in our simulated clinical implementation compared to prior published results. …”
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Research on Energy-Saving Optimization Control Strategy for Distributed Hub Motor-Driven Vehicles by Bin Huang, Jinyu Wei, Minrui Ma, Xu Yang

“…Aiming at the problems of energy utilization efficiency and braking stability in electric vehicles, a high-efficiency and energy-saving control strategy that takes both driving and braking into account is proposed with the distributed hub motor-driven vehicle as the research object. Under regular driving and braking conditions, the front and rear axle torque distribution coefficients are optimized by an adaptive particle swarm algorithm based on simulated annealing and a multi-objective co-optimization strategy based on variable weight coefficients, respectively. …”
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Comparative analysis of NTRUEncrypt modified post-quantum cryptographic system and standard RSA cryptosystem by P. V. Razumov, I. A. Smirnov, I. A. Pilipenko, A. V. Selyova, L. V. Cherkesova

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Research on linear solvability of network coding based cooperative recovery scheme by Jun YIN, Xueqi SHA, Lei WANG, Dengyin ZHANG, Yuwang YANG

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Research on Non-Probabilistic Reliability Partitioning Methods for Large Workspace Robots by Jianping Sun, Weian Yang, Xin Meng, Jun Peng, Zhaoping Tang

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Research of the Finite State Machine with Programmable Logic as a Part of Digital Information and Control System Based on FPGA by Barkalov A., Titarenko L., Zeleneva I., Hrushko S.

“…The purpose of this research is to determine the effective way of implementation of the control algorithm, as an important functional part of information and control computer systems. …”
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Research on Detection and Counting Method of Green Walnut Based on YOLOv8n-RBP by Bangbang Chen, Keke Tan, Kun Li, Baojian Ma, Xiangdong Liu

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Research on Joint Stiffness Identification and Error Compensation of the Serial Six DOF Robot by Ping Rui, Guifang Qiao, Xiulan Wen, Ying Zhang, Dongxia Wang

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Shell and tube heat exchanger optimization: A critical literature assessment and fairness-based comparative performance analysis of meta-heuristic algorithms by Samet Gürgen

“…This design problem has been addressed by many researchers with different optimization algorithms. …”
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Comparative Analysis of Two Mathematical Models of Single Diode Photovoltaic Cells for Extracting PV Parameters Using Levenberg – Marquardt Algorithm by Chahet Youssef, Mimouni Abdelmalek, Bouaichi Abdellatif, El Amraoui Mohamed, El Amrani Aumeur, Bejjit Lahcen

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Unleashing Predicting a Comparative Study of Machine Learning for Bankruptcy Risk Prediction by Yupeng Li, Ke Sun

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Human-Centred Design Meets AI-Driven Algorithms: Comparative Analysis of Political Campaign Branding in the Harris–Trump Presidential Campaigns by Hedda Martina Šola, Fayyaz Hussain Qureshi, Sarwar Khawaja

“…The study underscores the complex interplay between neuroscience AI algorithms and human-centred design in political campaign branding, offering valuable insights for future research in neuromarketing and design communication strategies. …”
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Comparative Analysis of Machine Learning Algorithms for Potential Evapotranspiration Estimation Using Limited Data at a High-Altitude Mediterranean Forest by Stefanos Stefanidis, Konstantinos Ioannou, Nikolaos Proutsos, Ilias Karmiris, Panagiotis Stefanidis

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Enhancing Privacy in IoT Networks: A Comparative Analysis of Classification and Defense Methods by Ahmet Emre Ergun, Ozgu Can, Murat Kantarcioglu

“…Additionally, the Decision Tree (DT), Random Forest (RF), k-Nearest Neighbors (kNN), and GRU classification algorithms are also evaluated and compared with the XGBoost and LSTM classifiers for the proposed attack model. …”
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A comparative study of four deep learning algorithms for predicting tree stem radius measured by dendrometer: A case study by Guilherme Cassales, Serajis Salekin, Nick Lim, Dean Meason, Albert Bifet, Bernhard Pfahringer, Eibe Frank

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