Optimizing Natural Image Quality Evaluators for Quality Measurement in CT Scan Denoising by Rudy Gunawan, Yvonne Tran, Jinchuan Zheng, Hung Nguyen, Rifai Chai

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Adaptive Reconfigurable Learning Algorithm for Robust Optimal Longitudinal Motion Control of Unmanned Aerial Vehicles by Omer Saleem, Aliha Tanveer, Jamshed Iqbal

“…The proposed algorithm is formulated to track the optimal trajectory yielded by the baseline Linear Quadratic Integral (LQI) controller. …”
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Optimization of Relay Node Deployment in Wireless Sensor Communication Networks Based on IGA-RNDP Algorithm by Shubo Xu, Cheng Zhong

“…To achieve reasonable deployment of relay nodes, a relay node deployment algorithm on the basis of improved genetic algorithm is proposed. …”
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5G-Practical Byzantine Fault Tolerance: An Improved PBFT Consensus Algorithm for the 5G Network by Xin Liu, Xing Fan, Baoning Niu, Xianrong Zheng

“…With the development of 5G network technology, its features of high bandwidth, low latency, and high reliability provide a new approach for consensus algorithm optimization. To take advantage of the features of the 5G network, this paper proposes 5G-PBFT, which is an improved practical Byzantine fault-tolerant consensus algorithm with three ways to improve PBFT. …”
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Management of large energy storage power plants: optimization of charging and discharging with cuckoo search algorithm by Behnam Motalebinejad, Majid Hosseina, Mojtaba Vahedi, Mahmoud Samiei Moghaddam

“…This algorithm has the capability to find global optimal solutions and can significantly improve the efficiency and profitability of large-scale energy storage facilities. …”
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Optimizing Sentiment Analysis of Digital Wayang Viewer Comments using SMOTE and the Naïve Bayes Algorithm by mawar hardiyanti, Maria Karmelia Fajarlestari

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An Improved Extreme Learning Machine (ELM) Algorithm for Intent Recognition of Transfemoral Amputees With Powered Knee Prosthesis by Yao Zhang, Xu Wang, Haohua Xiu, Wei Chen, Yongxin Ma, Guowu Wei, Lei Ren, Luquan Ren

“…Additionally, a hybrid grey wolf optimization and slime mould algorithm (GWO-SMA) is proposed to optimize the hidden layer bias of the improved ELM classifier. …”
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Approximated Optimal Solution for Economic Manufacturing Quantity Model by Jinyuan Liu, Pengfei Jiang, Shr-Shiung Hu, Gino K. Yang

“…This study investigates the use of the bisection algorithm in inventory models to obtain an approximated optimal solution for the economic manufacturing quantity (EMQ) problem under imperfect production conditions. …”
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Strategic scheduling of the electric vehicle-based microgrids under the enhanced particle swarm optimization algorithm by Saeed Abdollahi Khou, Javad olamaei, Mohammad Hassan Hosseini

“…However, the persistent problem of PSOAs (particle swarm optimization algorithms) being affected by local optima emphasizes the need for more improvements to these algorithms. …”
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Modification of the WaldBoost algorithm to improve the efficiency of solving pattern recognition problems in real-time by A. N. Chesalin, S. Ya. Grodzenskiy, M. Yu. Nilov, A. N. Agafonov

“…The efficiency of the proposed algorithm is shown by specific examples. The results are confirmed by statistical modeling on several data sets. …”
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Large-scale post-disaster user distributed coverage optimization based on multi-agent reinforcement learning by Wenjun XU, Silei WU, Fengyu WANG, Lan LIN, Guojun LI, Zhi ZHANG

“…In order to quickly restore emergency communication services for large-scale post-disaster users, a distributed intellicise coverage optimization architecture based on multi-agent reinforcement learning (RL) was proposed, which could address the significant differences and dynamics of communication services caused by a large number of access users, and the difficulty of expansion caused by centralized algorithms.Specifically, a distributed k-sums clustering algorithm considering service differences of users was designed in the network characterization layer, which could make each unmanned aerial vehicle base station (UAV-BS) adjust the local networking natively and simply, and obtain states of cluster center for multi-agent RL.In the trajectory control layer, multi-agent soft actor critic (MASAC) with distributed-training-distributed-execution structure was designed for UAV-BS to control trajectory as intelligent nodes.Furthermore, ensemble learning and curriculum learning were integrated to improve the stability and convergence speed of training process.The simulation results show that the proposed distributed k-sums algorithm is superior to the k-means in terms of average load efficiency and clustering balance, and MASAC based trajectory control algorithm can effectively reduce communication interruptions and improve the spectrum efficiency, which outperforms the existing RL algorithms.…”
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Large-scale post-disaster user distributed coverage optimization based on multi-agent reinforcement learning by Wenjun XU, Silei WU, Fengyu WANG, Lan LIN, Guojun LI, Zhi ZHANG

“…In order to quickly restore emergency communication services for large-scale post-disaster users, a distributed intellicise coverage optimization architecture based on multi-agent reinforcement learning (RL) was proposed, which could address the significant differences and dynamics of communication services caused by a large number of access users, and the difficulty of expansion caused by centralized algorithms.Specifically, a distributed k-sums clustering algorithm considering service differences of users was designed in the network characterization layer, which could make each unmanned aerial vehicle base station (UAV-BS) adjust the local networking natively and simply, and obtain states of cluster center for multi-agent RL.In the trajectory control layer, multi-agent soft actor critic (MASAC) with distributed-training-distributed-execution structure was designed for UAV-BS to control trajectory as intelligent nodes.Furthermore, ensemble learning and curriculum learning were integrated to improve the stability and convergence speed of training process.The simulation results show that the proposed distributed k-sums algorithm is superior to the k-means in terms of average load efficiency and clustering balance, and MASAC based trajectory control algorithm can effectively reduce communication interruptions and improve the spectrum efficiency, which outperforms the existing RL algorithms.…”
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Hierarchical Swarm Model: A New Approach to Optimization by Hanning Chen, Yunlong Zhu, Kunyuan Hu, Xiaoxian He

“…This proposed model is intended to suggest ways that the performance of HSO-based algorithms on complex optimization problems can be significantly improved. …”
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The machine learning algorithm based on decision tree optimization for pattern recognition in track and field sports. by Guomei Cui, Chuanjun Wang

“…Specifically, by introducing adaptive feature selection and ensemble learning methods, the decision tree algorithm effectively improves the recognition ability of the model for different athletes and sports states, thus reducing the over-fitting phenomenon and improving the generalization ability. …”
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Optimization of the Hybrid Movie Recommendation System Based on Weighted Classification and User Collaborative Filtering Algorithm by Zhenning Yuan, Jong Han Lee, Sai Zhang

“…Aiming at the problem that the single model of the traditional recommendation system cannot accurately capture user preferences, this paper proposes a hybrid movie recommendation system and optimization method based on weighted classification and user collaborative filtering algorithm. …”
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Optimizing an LSTM Self-Attention Architecture for Portuguese Sentiment Analysis Using a Genetic Algorithm by Daniel Parada, Alexandre Branco, Marcos Silva, Fábio Mendonça, Sheikh Mostafa, Fernando Morgado-Dias

“…To address this complexity, a discrete genetic algorithm was used to find an optimal configuration, selecting the layer types, placement of self-attention, dropout rate, and model dimensions and shape. …”
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Research on Audit Risk Prediction in Enterprise Management Based on Optimized BP Neural Network Algorithm by Wang Mingming

“…Under the development of enterprise management intelligence, there are more and more studies on the identification and evaluation of audit risks, in order to accurately identify enterprise audit risks, enterprises have created an audit risk identification model with artificial intelligence algorithm as the core, which aims to identify enterprise audit risks with high quality and significantly improve audit efficiency. …”
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Enhanced Network Traffic Classification Using Bayesian-Optimized Logistic Regression and Random Forest Algorithm by Manisankar Sannigrahi, R. Thandeeswaran

“…Bayesian optimization is employed to systematically fine-tune the model’s hyperparameters, thereby improving accuracy and efficiency by concentrating on promising areas of the hyperparameter space and avoiding unnecessary evaluations. …”
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Optimal Design of Linear Quadratic Regulator for Vehicle Suspension System Based on Bacterial Memetic Algorithm by Bala Abdullahi Magaji, Aminu Babangida, Abdullahi Bala Kunya, Péter Tamás Szemes

“…The results of the LQR-BMA are compared with those of the optimized LQR based on the genetic algorithm (LQR-GA) and the Virus Evolutionary Genetic Algorithm (LQR-VEGA) to substantiate the potency of the proposed model. …”
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Research on Stability Optimization for Automatic Train Operation of Heavy-haul Trains of Baoshen Railway by FU Shangyuan

“…During the departing stage, the optimization algorithm effectively improved operational stability on steep grades, and increased the departing speed by about 11.1%. …”
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