A Data-Driven Parameter Adaptive Clustering Algorithm Based on Density Peak by Tao Du, Shouning Qu, Qin Wang

“…Clustering is an important unsupervised machine learning method which can efficiently partition points without training data set. However, most of the existing clustering algorithms need to set parameters artificially, and the results of clustering are much influenced by these parameters, so optimizing clustering parameters is a key factor of improving clustering performance. …”
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Decomposition-Based Multiobjective Evolutionary Algorithm for Community Detection in Dynamic Social Networks by Jingjing Ma, Jie Liu, Wenping Ma, Maoguo Gong, Licheng Jiao

“…In this paper, we propose a decomposition-based multiobjective community detection algorithm to simultaneously optimize these two objectives to reveal community structure and its evolution in dynamic networks. …”
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Optimizing the Performance of Data Warehouse by Query Cache Mechanism by Ch Anwar Ul Hassan, Muhammad Hammad, Mueen Uddin, Jawaid Iqbal, Jawad Sahi, Saddam Hussain, Syed Sajid Ullah

“…In the era of Big Data, the cache is regarded as one of the most effective techniques to improve the performance of accessing data. …”
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MODELLING FLUCTUATIONS OF GROUNDWATER LEVEL USING MACHINE LEARNING ALGORITHMS IN THE SOKOTO BASIN by Samson Alfa, Haruna Garba, Augustine Odeh

“…This study investigates the application of machine learning models, specifically Long Short-Term Memory (LSTM), eXtreme Gradient Boosting (XGBoost)and Random Forest (RF) algorithms to predict groundwater levels across six boreholes within the Sokoto Basin. …”
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Vehicle Authentication-Based Resilient Routing Algorithm With Dynamic Task Allocation for VANETs by Nagaraju Pacharla, K. Srinivasa Reddy

“…With the goal of reducing task offloading delay and improving enhanced reaction time, a VANET-based task scheduling system is proposed after selecting an optimal route in the VANET. …”
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A nonrevisiting genetic algorithm based on multi-region guided search strategy by Qijun Wang, Chunxin Sang, Haiping Ma, Chao Wang

“…This study proposes a nonrevisiting genetic algorithm with a multi-region guided search to improve the search efficiency. …”
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Algorithms for big data mining of hub patent transactions based on decision trees by Zhukov Aleksandr, Pronichkin Sergey, Mihaylov Yuri, Kartsan Igor

“…Based on evolutionary computing, the optimal values of the parameters of algorithms for big data mining of hub patent transactions have been established.…”
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Identifying Capsule Defect Based on an Improved Convolutional Neural Network by Junlin Zhou, Jiao He, Guoli Li, Yongbin Liu

“…The improved CNN algorithm is based on regularization and the Adam optimizer (RACNN), on which a dropout layer and L2_regularization are added between the full connection and the output layer to solve the overfitting problem. …”
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Toward an algorithm of percutaneous microelectrolysis: a randomized clinical trial on invasive techniques by Carlos Eduardo Girasol, Nathaly Escobar Durán, Santiago Marcelo D’Almeida, Oscar Ariel Ronzio

“…CONCLUSIONS: All needling techniques demonstrated analgesic effects on myofascial trigger points, with the algorithm-enhanced MEP showing the most notable improvement in self-reported pain. …”
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Application of the YOLOv11-seg algorithm for AI-based landslide detection and recognition by Luhao He, Yongzhang Zhou, Lei Liu, Yuqing Zhang, Jianhua Ma

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Optimizing Locations of Primary Schools in Rural Areas of China by Yulong Chen

“…Scientific location selection of schools is an important way to optimize the allocation of educational resources, improve the efficiency of operating schools, and realize the balanced development of education, especially in rural areas. …”
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Task-dependent Optimal Weight Combinations for Static Embeddings by Nathaniel Robinson, Nathaniel Carlson, David Mortensen, Elizabeth Vargas, Thomas Fackrell, Nancy Fulda

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OPTIMIZATION OF HEMISPHERICAL RESONATOR GYROSCOPE STANDING WAVE PARAMETERS by O. S. Khalyutina

“…In this case, if the output signal of the compensating effects should coincide with the ideal signal at the most.…”
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Local Outlier Detection Method Based on Improved K-means by Yu ZHOU, Hao XIA, Xuezhen YUE, Peichong WANG

“…Hence, an improved K-means clustering algorithm is proposed by introducing fast search and discovering density peak methods. …”
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Control Optimization of Steam Boilers via Reinforcement Learning by Emmanuel Okafor, Maad Alowaifeer

“…Extensive experimental validation confirms the superiority of hybrid controllers, achieving significantly faster settling times, peak overshoot reductions to <inline-formula> <tex-math notation="LaTeX">$(\leq 2\%)$ </tex-math></inline-formula>, and lower error metrics than MRAC alone. While optimized PID serves as a baseline, hybrid controllers consistently achieve faster settling times and improved robustness under most nonlinear operating conditions. …”
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The Improved MNSPI Method for MODIS Surface Reflectance Data Small-Area Restoration by Meixiang Wang, Wenjuan Zhang, Bowen Wang, Xuesong Ma, Peng Qi, Zixiang Zhou

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Statistical Analysis Method for Optimal Prameters of Telemetry Communication by XIE Jun, WU Sailong, HAO Hang, ZHANG Songwei, WU Ruiqing, SUN Xiangyang

“…In order to improve the performance of telemetry of logging while drilling (TLWD) in complex drilling environment, the telemetry communication system is developing towards the trend of multi-architecture, multi-modal and multi-method, which brings a complication and inefficiency in the processing of selecting the optimal communication parameters. …”
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Optimization Design of Diaphragm Profile based on Kriging Model by Geng Hu, Zhigang Chen, Ding Zhang

“…To improve the fatigue performance of the diaphragm coupling，a optimization design method for the diaphragm profile parameters based on the Kriging model is proposed to maximize the high-cycle fatigue safety factor of the diaphragm design. …”
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Research on intelligent control of coal slime flotation based on the WOA-GRU model by DOU Zhiheng, WANG Ranfeng, QIN Xinkai, CHAI Yuqing, LI Pinyu, LIU Shutong

“…To address the low fitting accuracy of traditional identification methods, a Whale Optimization Algorithm (WOA)-based Gated Recurrent Unit (GRU) system identification model (WOA-GRU) was proposed. …”
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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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