Analysis and simulation of interception characteristics of broad-leaved forest canopy based on parameter optimization: Dianchi basin case by Qi Yi, Shengfang Hou, Xiaodong Dou, Yuting Gao, Zhongbin Li, Yiyan Liu

“…This study investigated the rainfall redistribution characteristics of three typical subtropical semi-humid evergreen broad-leaved forests in the Dianchi Basin of China. The model structure was improved by incorporating both canopy density and leaf area index (LAI) as indicators, and optimized the parameters using the Gauss-Newton algorithm, with appropriate threshold settings for absorption and additional interception. …”
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Multi-Objective Optimization of Chiral Metasurface for Sensing Based on a Distributed Algorithm by Xianglai Liao, Lili Gui, Shulei Bi, Ang Gao, Zhenming Yu, Kun Xu

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FPGA multi-unit parallel optimization and implementation of post-quantum cryptography CRYSTALS-Kyber by Bin LI, Xiaojie CHEN, Feng FENG, Qinglei ZHOU

“…In lattice-based post-quantum cryptography, polynomial multiplication is complicated and time-consuming.In order to improve the computational efficiency of lattice cryptography in practical applications, an FPGA multi-unit parallel optimization and implementation of post-quantum cryptography CRYSTALS-Kyber was proposed.Firstly, the flow of Kyber algorithm was described and the execution of NTT, INTT and CWM were analyzed.Secondly, the overall structure of FPGA was given, the butterfly arithmetic unit was designed by pipeline technology, and the Barrett modulus reduction and CWM scheduling optimization were used to improve the calculation efficiency.At the same time, 32 butterfly arithmetic units were executed in parallel, which shortens the overall calculation cycle.Finally, the multi-RAM channel was optimized to improve the memory access efficiency with alternate data access control and RAM resource reuse.In addition, with the loosely coupled architecture, the overall operation scheduling was realized by DMA communication.The experimental results and analysis show that the proposed scheme implemented can complete NTT, INTT and CWM operations within 44, 49, and 163 clock cycles, which is superior to other schemes and has high energy efficiency ratio.…”
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A Feasibility Study of a Virtual Power Line Device to Improve Hosting Capacity in Renewable Energy Sources by Seong-Eun Rho, Sung-Moon Choi, Joong-Seon Lee, Hyun-Sang You, Seung-Ho Lee, Dae-Seok Rho

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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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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

“…To solve this problem, a mixed-integer linear programming model (MILP) is developed and the optimal Pareto front for small-scale instances are solved by using the <inline-formula> <tex-math notation="LaTeX">$\varepsilon $ </tex-math></inline-formula>-method. …”
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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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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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Crime Type Identification Using High-Order Deep Residual Network with Multiple Attention Algorithm by Dawei Qiu, Chang Liu, Yuangfeng Shang, Zixu Zhao, Jinlin Shi

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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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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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Research on location algorithm of opencast mine vehicle based on improved adaptive H ∞ CKF and IAGA by Zhen Yang, Liwen Ji, Xin Li, Haoyuan Liu, Jianxiong Li, Dianxing Sun, Ruiheng Sun

“…Improved Adaptive Genetic Algorithm (IAGA) updates the optimal preservation strategy of traditional genetic algorithm and redefines the adaptive cross rate and variation rate. …”
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An Improved Unscented Kalman Filter Applied to Positioning and Navigation of Autonomous Underwater Vehicles by Jinchao Zhao, Ya Zhang, Shizhong Li, Jiaxuan Wang, Lingling Fang, Luoyin Ning, Jinghao Feng, Jianwu Zhang

“…Excessive noise interference may cause a decrease in filtering accuracy and is highly likely to result in divergence by means of the traditional Unscented Kalman Filter, resulting in an increase in uncertainty factors during submersible mission execution. An estimation model for system noise, the adaptive Unscented Kalman Filter (UKF) algorithm was derived in light of the maximum likelihood criterion and optimized by applying the rolling-horizon estimation method, using the Newton–Raphson algorithm for the maximum likelihood estimation of noise statistics, and it was verified by simulation experiments using the Lie group inertial navigation error model. …”
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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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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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Application of the joint clustering algorithm based on Gaussian kernels and differential privacy in lung cancer identification by Hang Yanping, Zheng Haixia, Yang Minmin, Wang Nan, Kong Miaomiao, Zhao Mingming

“…For the LLCS dataset, For the LLCS dataset, the DPFCM_GK demonstrates significant improvement as the privacy budget increases, especially in low-budget scenarios, where the performance gap is most pronounced (T=4.20, 8.44, 10.92, 3.95, 7.16, 8.51, P < 0.05). …”
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Coordinated System Intelligent Optimization for an Ultra-Supercritical Power Unit Based on Improved Simplex Method and Condensate Throttling by Liangyu MA, Qianqian LI, Fan LI

“…Based on the established models, a classic optimization theory-improved simplex method was selected as the CCS optimization algorithm. …”
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Mechanism-learning prediction model for pitting depth of buried pipeline based on HMOGWO-RF by Fulin SONG, Hong ZHAO, Xingyuan MIAO

“…Methods This paper presents a prediction model for the pitting depth of buried pipelines, guided by the corrosion mechanism and combining a Random Forest (RF) algorithm with a Multi-Objective Optimization process. …”
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Optimal Setting Method of Inverse Time Overcurrent Protection for the Distribution Networks Based on the Improved Grey Wolf Optimization by Bo Yang, Jun Tang, Changsen Feng, Chen Yang, Xiaofeng Dong

“…Simulation results verify the feasibility and superiority of the proposed model in case of the two-phase and three-phase faults and discuss the influence of time differential on parameters setting and the research direction of algorithm optimization and engineering application.…”
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