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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Forest canopy closure estimation in mountainous southwest China using multi-source remote sensing data by Wenwu Zhou, Wenwu Zhou, Qingtai Shu, Cuifen Xia, Li Xu, Qin Xiang, Lianjin Fu, Zhengdao Yang, Shuwei Wang

“…Combined with 54 measured plot data, the improved machine learning model of the Bayesian optimization (BO) algorithm was used to obtain the FCC in the footprint-scale ATLAS footprint. …”
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Enhanced Vector Quantization for Embedded Machine Learning: A Post-Training Approach With Incremental Clustering by Thommas K. S. Flores, Morsinaldo Medeiros, Marianne Silva, Daniel G. Costa, Ivanovitch Silva

“…This study introduces a novel method to optimize Post-Training Quantization (PTQ), a widely used technique for reducing model size, by integrating Vector Quantization (VQ) with incremental clustering. …”
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An efficient hybrid Hopfield convolutional neural network for detecting spam bots in Twitter platform by A.V. Santhosh Kumar, N. Suresh Kumar, R. Kanniga Devi

“…This method helps to reduce the feature dimensionality and overfitting issues. In order to improve the optimization algorithm’s searching ability, an X-shaped transfer function is used. …”
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Topology control algorithm backing for network coding in cognitive wireless ad hoc networks by Jun LIU, Qian SUN, Ying-mei WANG, Ning YE, Ming-bo SHA

“…In order to study the limited bandwidth resource in cognitive wireless ad hoc network,a topology control algo-rithm backing for network coding was proposed.The algorithm was mainly composed of three phases.In the stage of ini-tial topology construction,the algorithm used the shortest path algorithm to construct topology for unicast services,used the shortest path algorithm based on network coding to construct topology for multicast services.In the stage of topology optimization,the algorithm deleted links which met certain conditions one by one to optimize the topology.In the stage of topology recovery,the algorithm used the least cost links which were not in the path cluster including failed links to recover network connectivity.Simulation results show that the proposed algorithm can improve the spatial reuse of radio resource and enhance network invulnerability.…”
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Research on Sparse Code Multiple Access Detection Technology in Satellite Communication Systems by Yiting JIANG, Lidong ZHU

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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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Biomechanical Modeling of Selected Methods of Load Carriage to Improve Military Capabilities of Troops by Mostafa Hajlotfalian, Alireza Redaei, Heydar Sadeghi

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Nonlinear waveform optimization for wireless power transfer systems by Lina Yuan, Huajun Chen, Maoxue Hu, Jing Gong

“…We develop single-user and multi-user algorithms that maximize the output DC voltage of the weighted and/or minimum moment antennas by optimizing waveform design. …”
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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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Multi-objective quantum hybrid evolutionary algorithms for enhancing quality-of-service in internet of things by Shailendra Pratap Singh, Gyanendra Kumar, Umakant Ahirwar, Shitharth Selvarajan, Firoz Khan

“…The hybrid algorithm enhances QoS in IoT applications by achieving superior optimization in terms of energy efficiency, latency reduction, convergence, and coverage cost. …”
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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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A comparative study of hybrid adaptive neuro-fuzzy inference systems to predict the unconfined compressive strength of rocks by Wei Cao

“…However, the inclusion of optimization algorithms significantly improved the performance of the SVR framework. …”
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A multi strategy bidirectional RRT* algorithm for efficient mobile robot path planning by Yourui Huang, Wenxin Jiang, Shanyong Xu

“…During the parent node rewiring phase, a multi-factor path cost function is constructed to optimize parent node selection, thereby improving path quality. …”
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A parallel multi-objective genetic algorithm for scheduling scientific workflows in cloud computing by Muhammad Sardaraz, Muhammad Tahir

“…The results show that the proposed algorithm achieves an improvement in makespan and reduces the cost with a well load balanced system.…”
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A Novel Proposed Algorithm to Enhance the Overcurrent Relays’ Performance in Active Distribution Networks by Sally El-Tawab, Hassan S. Mohamed, A. M. Abdel-Aziz

“…In this study, the improved wild horse optimization (IWHO) algorithm is used as a novel metaheuristic method for solving optimization issues in coordination of OCRs in a distribution network, for the first time. …”
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A multi-objective approach to load balancing in cloud environments integrating ACO and WWO techniques by Umesh Kumar Lilhore, Sarita Simaiya, Yogendra Narayan Prajapati, Anjani Kumar Rai, Ehab Seif Ghith, Mehdi Tlija, Tarik Lamoudan, Abdelaziz A. Abdelhamid

“…We assessed our methods in comparison to well-established algorithms, such as WWO, genetic algorithm (GA), spider monkey optimization (SMO), and ACO. …”
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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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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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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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