Joint beam hopping and coverage control optimization algorithm for multibeam satellite system by Guoliang XU, Feng TAN, Yongyi RAN, Feng CHEN

“…To improve the performance of multibeam satellite (MBS) systems, a deep reinforcement learning-based algorithm to jointly optimize the beam hopping and coverage control (BHCC) algorithm for MBS was proposed.Firstly, the resource allocation problem in MBS was transformed to a multi-objective optimization problem with the objective maximizing the system throughput and minimizing the packet loss rate of the MBS.Secondly, the MBS environment was characterized as a multi-dimensional matrix, and the objective problem was modelled as a Markov decision process considering stochastic communication requirements.Finally, the objective problem was solved by combining the powerful feature extraction and learning capabilities of deep reinforcement learning.In addition, a single-intelligence polling multiplexing mechanism was proposed to reduce the search space and convergence difficulty and accelerate the training of BHCC.Compared with the genetic algorithm, the simulation results show that BHCC improves the throughput of MBS and reduces the packet loss rate of the system, greedy algorithm, and random algorithm.Besides, BHCC performs better in different communication scenarios compared with a deep reinforcement learning algorithm, which do not consider the adaptive beam coverage.…”
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A low-carbon optimization scheduling method of CIES based on PPO algorithm by CHEN Fan, WU Lingxiao, WANG Man, LYU Ganyun, ZHANG Xiaolian

“…The tiered carbon trading mechanism and optimization scheduling model solving algorithm are pivotal for the community integrated energy system (CIES). …”
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Optimizing firefighting resilience in airports through genetic algorithms and decision-making frameworks by Yulong Zhu, Wei Tian, Xuhong Jia, Quanyi Liu

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Optimizing diabetic retinopathy detection with electric fish algorithm and bilinear convolutional networks by Udayaraju Pamula, Venkateswararao Pulipati, G. Vijaya Suresh, M. V. Jagannatha Reddy, Anil Kumar Bondala, Srihari Varma Mantena, Ramesh Vatambeti

“…To enhance classification accuracy, the system introduces a hybrid Electric Fish Optimization Arithmetic Algorithm (EFAOA), which refines the exploration phase, ensuring rapid convergence. …”
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The optimal route search in Bengaluru city transport using Hamilton circuit algorithm by Parkavi S, Parthiban A

“…So, drawing inspiration and motivation from the outstanding work of Mungporn, Pongsiri et al., “Modeling and control of multiphase interleaved fuel-cell boost converter based on Hamiltonian control theory for transportation applications, IEEE Transactions on Transportation Electrification 6.2, 2020, pp. 519-529”, in this paper, we study an intelligent agent model to perform route engineering for public transportation in the Bengaluru city, based on the Hamilton circuit algorithm and analyze the best and optimal route among the three significant routes out of twelve available using various parameters. …”
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An Ensemble Formal Approach to Improve Energy Efficiency and Data Aggregation in Smart Agriculture by Shahbaz Ahmad, Nadeem Akhtar, Adeel Ahmed, Saman Iftikhar, Shaikhan Bawazeer, Saima Abdullah

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An Enhanced PSO-Based Clustering Energy Optimization Algorithm for Wireless Sensor Network by C. Vimalarani, R. Subramanian, S. N. Sivanandam

“…Maximizing the lifetime of the Wireless Sensor networks, energy conservation measures are essential for improving the performance of WSNs. This paper proposes an Enhanced PSO-Based Clustering Energy Optimization (EPSO-CEO) algorithm for Wireless Sensor Network in which clustering and clustering head selection are done by using Particle Swarm Optimization (PSO) algorithm with respect to minimizing the power consumption in WSN. …”
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MILP Modeling and Optimization of Multi-Objective Three-Stage Flexible Job Shop Scheduling Problem With Assembly and AGV Transportation by Shiming Yang, Leilei Meng, Saif Ullah, Biao Zhang, Hongyan Sang, Peng Duan

“…In the MPCEA, we design a strategy to select relatively high-quality individuals to enhance the algorithm’s convergence speed, and design a multi-objective variable-neighborhood search (MOVNS) method to improve the local search ability. …”
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Engine Optimization Model for Accurate Prediction of Friction Model in Marine Dual-Fuel Engine by Mina Tadros

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Spike-RISC: Algorithm/ISA Co-Optimization for Efficient SNNs on RISC-V by Ipek Akdeniz, Sandy A. Wasif, Paul R. Genssler, Hussam Amrouch

“…This paper proposes Spike-RISC, a holistic algorithm/instruction set architecture (ISA) co-optimization for efficient SNN inference. …”
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An automated software algorithm for optimizing microwave ablation parameters for treatment of liver tumors by Sabrina Q. R. Liew, Nathaniel Rex, Celina Hsieh, Hyeonseon Kim, Scott A. Collins, Grayson L. Baird, DaeHee Kim, Aaron W. P. Maxwell

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Milling Machine Fault Diagnosis Using Acoustic Emission and Hybrid Deep Learning with Feature Optimization by Muhammad Umar, Muhammad Farooq Siddique, Niamat Ullah, Jong-Myon Kim

“…A convolutional neural network (CNN) based on the VGG16 architecture is utilized for spatial feature extraction, followed by a bidirectional long short-term memory (BiLSTM) network to capture the temporal dependencies of the scalograms. The genetic algorithm (GA) is used to optimize feature selection and ensure the selection of the most relevant features to further improve the model’s performance. …”
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A Review: The Application of Path Optimization Algorithms in Building Mechanical, Electrical, and Plumbing Pipe Design by Ruijun Deng, Xiaoliang Li, Yuhua Tian

“…This review systematically integrates recent advancements in path optimization algorithms for the automated layout of mechanical, electrical, and plumbing (MEP) systems within complex building environments. …”
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Daily Runoff Prediction Model Based on Multivariate Variational Mode Decomposition and Correlation Reconstruction by DING Jie, TU Peng-fei, FENG Yu, ZENG Huai-en

“…Finally, the integrated prediction combining fluctuation and random terms under condition 5 yielded R2 of 0.87 and 0.93 for the overall prediction at Ankang and Baihe stations, respectively, demonstrating excellent model performance. [Conclusions](1) The MVMD decomposition method can control the number of decomposition layers, ensuring complete signal feature extraction without overfitting while improving processing speed.(2) Pearson correlation coefficient method enhances prediction accuracy through decomposed data classification.(3) The MEA-BP can improve signal-to-noise ratio, adapt to complex environments, enhance learning efficiency and generalization ability, and reduce computational complexity.(4) The GWO-ELM algorithm integrates grey wolf optimizer with extreme learning machine, providing a fast and adaptive solution for time-series prediction with reduced overfitting and improved efficiency.(5) The overall combined model can efficiently and stably process large amount of data while ensuring high accuracy.…”
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Autonomous Decision-Making for Air Gaming Based on Position Weight-Based Particle Swarm Optimization Algorithm by Anqi Xu, Hui Li, Yun Hong, Guoji Liu

“…As the complexity of air gaming scenarios continues to escalate, the demands for heightened decision-making efficiency and precision are becoming increasingly stringent. To further improve decision-making efficiency, a particle swarm optimization algorithm based on positional weights (PW-PSO) is proposed. …”
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A Dendritic Neural Network-Based Model for Residential Electricity Consumption Prediction by Ting Jin, Rui Xu, Kunqi Su, Jinrui Gao

“…In this study, a dendritic neural network-based model (DNM), combined with the AdaMax optimization algorithm, is used to predict residential electricity consumption. …”
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Efficiency multi-agent model assisted Moea/D algorithm for optimization design for building taking into account annual energy consumption and annual user discomfort hours by Hua Deng, Kai Zhou

“…Then it introduces a multi-agent model auxiliary mechanism to improve the decomposition based multi-objective evolutionary optimization algorithm, and then solves the multi-objective optimization model for building energy efficiency. …”
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A review of state-of-the-art resolution improvement techniques in SPECT imaging by Zhibiao Cheng, Ping Chen, Jianhua Yan

“…This survey offers a thorough overview of the rapid advancements in resolution enhancement techniques within the field of SPECT, with the objective of identifying the most recent trends. This is anticipated to facilitate further optimization and improvement of clinical systems, enabling the visualization of small lesions in the early stages of tumor detection, thereby enhancing accurate localization and facilitating both diagnostic imaging and radionuclide therapy, ultimately benefiting both clinicians and patients.…”
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Research on Indoor Object Detection and Scene Recognition Algorithm Based on Apriori Algorithm and Mobile-EFSSD Model by Wenda Zheng, Yibo Ai, Weidong Zhang

“…The specific research contents are as follows: (1) To address complex indoor scenes and occlusion, this paper proposes an improved Mobile-EFSSD object detection algorithm. An optimized MobileNetV3 with ECA attention is used as the backbone. …”
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A composite photovoltaic power prediction optimization model based on nonlinear meteorological factors analysis and hybrid deep learning framework by Mengji Yang, Haiqing Zhang, Xi Yu, Aicha Sekhari Seklouli, Abdelaziz Bouras, Yacine Ouzrout

“…Firstly, to reduce the redundancy of the input for the prediction model and the computational time complexity, while enhancing the robustness and stability of the prediction model, nonlinear correlation search algorithm based on time window extending and time window shrinking strategies have been proposed. …”
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