MODELLING FLUCTUATIONS OF GROUNDWATER LEVEL USING MACHINE LEARNING ALGORITHMS IN THE SOKOTO BASIN by Samson Alfa, Haruna Garba, Augustine Odeh

“…Among the models, the XGBoost algorithm demonstrated the highest performance, providing precise predictions that closely aligned with the actual groundwater levels. …”
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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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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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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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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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Optimal allocation of STATCOM for multi-objective ORPD problem on thermal wind solar hydro scheduling using driving training based optimization by Tushnik Sarkar, Sabyasachi Gupta, Chandan Paul, Susanta Dutta, Provas Kumar Roy, Anagha Bhattacharya, Ghanshyam G. Tejani, Seyed Jalaleddin Mousavirad

“…The Driving Training Based Optimization (DTBO) method has been used to achieve the goals, and its performance has been compared to that of other optimization algorithms that have been reported in recent ORPD studies. …”
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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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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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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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Optimization Design of Diaphragm Profile based on Kriging Model by Geng Hu, Zhigang Chen, Ding Zhang

“…Finally，the initial Kriging model is updated with MP （minimizing the predicted objective function） infill-sampling criterion and genetic algorithm，and the optimal design is obtained via the final Kriging model. …”
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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

“…The results confirm that the method significantly reduces the bit error rate by 3.3% and improves the success rate of deframing in most experimental wells. …”
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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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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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Enhancing network lifetime in WSNs through coot algorithm-based energy management model by Namita Shinde, Dr. Vinod H․ Patil

“…This addresses issues such as high energy consumption, communication delays, and security.To ensure energy savings and network reliability, the fitness function evaluates cluster heads and best routes based on constraints.COOT outperforms other Metaheuristics Algorithms like Butterfly Optimization Algorithm, Genetic Algorithm, Tunicate Swarm Gray Wolf Optimization Algorithm, and Bird Swarm Algorithm in simulation with performance measurements and enhancing network functionality and protection.Key methodology points include: • Proposed a multiple constraints clustering and routing technique using COAto solve the most crucial issues that arise in WSNs. • Integrated an advanced fitness function that determines cluster head selection, and the routing path based on residual energy, delay, security, trust, distance, and link quality so that energy load is evenly distributed and credible data flow is maintained across the network and made Innovative and Effective Solution. • Proven Results Demonstrated superior network performance, achieving the lowest delay, highest network lifetime (3571 rounds) and enhanced security (0.8) and trust (0.6) compared to existing algorithms with less energy consumption, making it the most suitable solution for WSN performance improvement.…”
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Graph neural processes for molecules: an evaluation on docking scores and strategies to improve generalization by Miguel García-Ortegón, Srijit Seal, Carl Rasmussen, Andreas Bender, Sergio Bacallado

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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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Development of Spectral Clustering Algorithm in Cognitive Diagnosis Model: Approach for Student’s Psychological Growth by Xiao Chang

“…The spectral clustering (SC) algorithm iterative optimization was combined with a similarity matrix and Laplacian matrix to construct an improved spectral clustering cognitive diagnosis model. …”
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A comprehensive review of fiber-reinforced topology optimization for advanced polymer composites produced by automated manufacturing by Bence Szederkenyi, Norbert Krisztian Kovacs, Tibor Czigany

“…Accordingly, the review introduces the main TO techniques and the common reinforcement path design strategies using concurrent and sequential optimization approaches. Furthermore, this paper examines the potential transformation of the conventional role of TO algorithms in structural optimization by integrating Artificial Intelligence (AI) into the optimization process [1]. …”
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