Spatial Downscaling of TRMM Precipitation Data Using an Optimal Subset Regression Model with NDVI and Terrain Factors in the Yarlung Zangbo River Basin, China by Jinping Liu, Wanchang Zhang, Ning Nie

“…The objective of this study was to develop a reliable statistical downscaling algorithm to produce high quality, high spatial resolution precipitation products from Tropical Rainfall Monitoring Mission (TRMM) 3B43 data over the Yarlung Zangbo River Basin using an optimal subset regression (OSR) model combined with multiple topographical factors, the Normalized Difference Vegetation Index (NDVI), and observational data from rain gauge stations. …”
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Small Ship Detection Based on Improved Neural Network Algorithm and SAR Images by Jiaqi Li, Hongyuan Huo, Li Guo, De Zhang, Wei Feng, Yi Lian, Long He

“…Therefore, based on the YOLOv5s model, this paper improves its backbone network and feature fusion network algorithm to improve the accuracy of ship detection target recognition. …”
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Facilitating Circular Transition in the Construction Industry: Optimizing a Prefabricated Construction Site Layout Using a Novel BIM-Integrated SLP-GA Model by Lin Wang, Qi Wang, Shuxiu Dong, Yue Cao, Liang Wang

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OPTIMIZATION OF FUZZY INVENTORY MANAGEMENT IN INDUSTRIAL PROCESSES USING DEEP LEARNING ALGORITHMS: A HYBRID APPROACH FOR ENHANCING DEMAND FORECASTING AND SUPPLY CHAIN EFFICIENCY by K. Kalaiarasi*, S. Swathi

“…A mathematical model and algorithmic implementation demonstrate the approach’s effectiveness and a numerical example highlights improvements in inventory control, including reduced holding costs. …”
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Impact of agricultural industry transformation based on deep learning model evaluation and metaheuristic algorithms under dual carbon strategy by Xuan Zhao, Weiyun Tang, Qiuyan Liu, Hongtao Cao, Fei Chen

“…Convolutional Neural Networks are used to extract spatial features from agricultural data, while Long Short-Term Memory networks processed time series data. To enhance model performance, the slime mould algorithm is employed for parameter optimization. …”
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Forecasting the daily evaporation by coupling the ensemble deep learning models with meta-heuristic algorithms and data pre-processing in dryland by Tonglin Fu, Dong Wang, Jing Jin

“…To overcome the drawback that directly using measured evaporation time series to predict evaporation may lead to large error, the Variational mode decomposition (VMD) was used to extract multiscale traits of evaporation time series, and Whale optimization algorithm (WOA) was adopted to find the optimal parameters of VMD, and a novel hybrid deep learning model WOA-VMD-CNN-SSA-BiLSTM was proposed to estimate the evaporation in the Linze County, China. …”
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Commercial Vehicle Ride Comfort Optimization Based on Intelligent Algorithms and Nonlinear Damping by Shuilong He, Keren Chen, Enyong Xu, Wei Wang, Zhansi Jiang

“…To improve the reliability of ride comfort optimization and analysis, a ride comfort optimization method based on nonlinear damping and intelligent algorithms is proposed. …”
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Robust Photovoltaic Power Forecasting Model Under Complex Meteorological Conditions by Yuxiang Guo, Qiang Han, Tan Li, Huichu Fu, Meng Liang, Siwei Zhang

“…To effectively mitigate these limitations, this work proposes a dual-stage feature extraction method based on Variational Mode Decomposition (VMD) and Principal Component Analysis (PCA), enhancing multi-scale modeling and noise reduction capabilities. Additionally, the Whale Optimization Algorithm is adopted to efficiently optimize the hyperparameters of iTransformer for the framework, improving parameter adaptability and convergence efficiency. …”
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Algorithm on joint optimization of power allocation and slot allocation in satellite communication systems by Han HAN, Ying LI, Xu DONG, Xiao-bo GUO, Qin-fei HUANG

“…An algorithm to jointly optimize the power allocation and the slot allocation in order to improve the utilization efficiency of the limited resources on the satellite was proposed.The basic principles of the mutual compensation and mutual independence between these two resources are explored to pave the way for joint optimization.Considering the differences about each station’s channel condition and capacity requirement,a state-combination model for optimally allocating the resources is setted up,so as to adapt the multi-resource usage pattern with each earth station.Targeting at the energy efficiency,an iterative dual optimization algorithm is proposed,and the final optimal policy for resource allocation with low complexity is obtained.With the simulation and analysis,the proposed joint optimization is verified to perform better than the non-joint ones in the perspective of the energy efficiency,especially when the frequency resource (the carrier number) is less.…”
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Optimization of the Naive Bayes Algorithm with SMOTETomek Combination for Imbalance Class Fraud Detection by Arief Tri Arsanto, Arif Faizin, Moch lutfi, Zulfatun Nikmatus Saadah

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FCC algorithm for power loss diminution by Kanagasabai L.

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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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Intelligent analysis algorithm for power engineering data based on improved BiLSTM by Yuanyuan Xu, Jiapeng Yang, Xin Cai

“…In equipment fault diagnosis, the accuracy of improved BiLSTM under current, voltage, temperature and pressure is significantly higher than that of models such as GRU.…”
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Multi-Level Particle System Modeling Algorithm with WRF by Julong Chen, Bin Wang, Rundong Gan, Xuepeng Mou, Shiping Yang, Ling Tan

“…To improve modeling efficiency, cascade Bezier curves are designed at different line-of-sights (LoSs), utilizing the weight information of boundary particles to optimize cloud contours. …”
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Detecting Planting Holes Using Improved YOLO-PH Algorithm with UAV Images by Kaiyuan Long, Shibo Li, Jiangping Long, Hui Lin, Yang Yin

“…Lastly, our proposed Siblings Detection Head reduces computational burden while significantly improving detection performance. Ablation experiments demonstrate that compared to baseline models, YOLO-PH exhibits notable improvements of 1.3% in mAP50 and 1.1% in mAP50:95 while simultaneously achieving a reduction of 48.8% in FLOPs and an impressive increase of 26.8 FPS (frames per second) in detection speed. …”
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A Novel Optimization Algorithm for Modifying the Parameter Unit of Solar PV Cell by V. Senthil Nayagam, S. Sanal Kumar, V. Thiyagarajan, Neel Kamal, N. Nisha, J. Samson Isaac, Adane Kassa

“…As a result, combining these two mechanisms can considerably improve the whale optimization algorithm capacity to find the optimal answer. …”
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A navigation satellite selection algorithm for optimized positioning based on Gibbs sampler by Na Xia, Qinan Zhi, Menghua He, Yunqing Hong, Huazheng Du

“…In addition, the scheme is updated by the conditional probability distribution model of the Gibbs sampler algorithm, and it gradually approaches the global optimal solution of the satellite combination with better geometric distribution of the space satellite. …”
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Research on Wellbore Trajectory Optimization and Drilling Control Based on the TD3 Algorithm by Haipeng Gu, Yang Wu, Xiaowei Li, Zhaokai Hou

“…After reinforcement learning training, the trajectory offset is significantly reduced, and the accuracy is greatly improved. This research shows that the TD3 algorithm is superior to the multi-objective optimization algorithm in optimizing key parameters, such as well deviation, kickoff point (KOP), and trajectory length, especially in well deviation and KOP optimization. …”
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Leveraging AI to Drive Timely Improvements in Patient Experience Feedback: Algorithm Validation by Mustafa Khanbhai, Catalina Carenzo, Sarindi Aryasinghe, David Manton, Erik Mayer

“…However, the accuracy of our algorithm significantly improved when individual trust coding templates were applied. …”
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Computational intelligence analysis on drug solubility using thermodynamics and interaction mechanism via models comparison and validation by Ahmad J. Obaidullah, Wael A. Mahdi

“…In addition, the Fireworks Algorithm (FWA) is presented as an optimization method, demonstrating its potential in improving the model’s predictive abilities by effectively exploring and exploiting the search space. …”
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